Analysis of Heavy-Duty Vehicle Sales Impacts Due to New Regulation: Response to Reviewer Comments


Analysis of Heavy-Duty Vehicle Sales
Impacts Due to New Regulation:
Response to Reviewers Comments
&EPA
United States
Environmental Promotion
Agency

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Analysis of Heavy-Duty Vehicle Sales
Impacts Due to New Regulation:
Response to Reviewers Comments
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
Prepared for EPA by
ERG, Eastern Research Group, Inc.
EPA Contract No. EP-C-17-011
Work Assignment No. 3-29
and
RTI International
EPA Contract No. EP-C-16-021
Work Assignment No. 4-34
NOTICE
This technical report does not necessarily represent final EPA decisions
or positions. It is intended to present technical analysis of issues using
data that are currently available. The purpose in the release of such
reports is to facilitate the exchange of technical information and to
inform the public of technical developments.
¦SEPA
United States	EPA-420-R-21-014
E nvi run marital Prolirclion	. „ _
Agency	May 2021

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March 2021
MEMORANDUM
SUBJECT: Peer Review for ERG Report, "Analysis of Heavy-Duty Vehicle Sales Impacts Due
to New Regulation"
In August 2020, EPA contracted with RTI International, who enlisted EnDyna as a subcontractor
(RTI/EnDyna), to conduct a peer review of a study conducted by ERG and its subcontractor
EERA (ERG/EERA). The draft study, titled "Analysis of Heavy-Duty Vehicle Sales Impacts Due
to New Regulation," estimated the effects of EPA standards for heavy-duty vehicles on sales of
those vehicles, including whether the standards elicited increased sales in advance of the standards
(pre-buy) and reduced sales after the standards came into effect (low-buy).
The peer reviewers selected by RTI/EnDyna were Drs. Jose Holguin-Veras of Rensselaer
Polytechnic Institute, Amelia Regan of the University of California at Irvine, Yan (Joann) Zhou of
Argonne National Laboratory, and Yichen (Christy) Zhou of Clemson University. EPA would like
to extend its appreciation to all four reviewers for their efforts in evaluating this survey. The
reviewers brought useful and distinctive views in response to the charge questions.
The first section of this document contains the final ERG/EERA report responding to the peer
reviewers' comments. The second section provides the peer review report conducted by
RTI/EnDyna. It documents the peer review process, provides both a summary of the peer review
comments and the detailed responses, the peer reviewers' curriculum vitae, the agenda from a
teleconference, and the form EnDyna used to evaluate potential conflicts of interest.
CONTENTS
I.	Analysis of Heavy-Duty Vehicle Sales Impacts Due to New Regulation: Response to Reviewer
Comments, February 25, 2021, conducted by ERG/EERA.
1.	Minor
2.	Moderate
3.	Major
II.	Analysis of Heavy-Duty Vehicle Sales Impacts due to New Vehicle Regulation (October 9, 2020):
Peer Review Final Report, January 21, 2021, conducted by RTI/EnDyna
1.	Introduction
2.	Charge Questions
3.	Summary of Peer Reviewers' Comments
4.	Individual Peer Reviewers' Comments
5.	Peer Reviewer Curriculum Vitae
6.	Agenda for Peer Review Teleconference
7.	Conflict of Interest Form and Non-disclosure/Confidentiality Agreement

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Analysis of Heavy-Duty Vehicle Sales
Impacts Due to New Regulation: Response
to Reviewer Comments
Comments received are categorized into minor, moderate, and major. Minor comments do not
affect the outcomes of the report and may be addressed with straightforward adjustments to the
text. Moderate comments do not affect the outcomes of the report, but require more significant
adjustments to the text, or effort to update tables and figures. Major comments may affect the
outcomes of the report and may require extensive modifications to the text, tables, and figures, and
may include adjustments to model specification
February 25, 2021

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1 Minor
Reviewer
Section
Comment
Response
Dr. Yan
Zhou
Ex. Sum. and
Conclusion
suggest changing the "abstract" to "Executive
Summary" and move some of the contents from
the "Conclusions" to "Summary". For people
who do not have time to read the 80-page report,
they can still comprehend a full picture of the
data and methodologies used, as well as the key
take-ways from this study.
Abstract changed to "Executive
Summary" and key sections from the
conclusions were copied to the executive
summary
Dr. Yan
Zhou
1
suggest clarifying in the "Introduction" and
"Summary" that although the HDV regulation
covers from class 2b to class 8, this study focus
on class 6-8 due to data limitations.
Suggestion incorporated
Dr. Yan
Zhou
3
In the beginning of Section 3 Data and
Methodology, I would suggest adding a table to
show all the data considered in the analysis and
modeling.
•	Variable
•	Models (in which data was used)
•	Unit
•	Source
•	Notes
Table added to top level of Section 3:
Data and Methodology
Dr. Yan
Zhou
2.8
Table 3 and Section 4.7: More description about
how these costs were estimated and used in this
analysis would be appreciated.
Text has been added discussing these
regulations and associated costs.
Dr. Yan
Zhou
3.1.1
Page 38 Section 3.1.1: Please cite the reference for
the vehicle sales in the content, not just on the
figure.
Citation added
Dr. Yan
Zhou
4.2
Page 55 Section 4.2: I am confused about what
exactly is the dependent variable? The Class 7 or
8 sales, or the changes in the monthly sales?
Changed dependent variable to Sales_i,t,
where i is class, and t is month of year

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Dr. Yan
Zhou
4.4.2
Page 60-61: Was the effect due to recession
considered when analyzing the impact of 2007
regulations? The recession was mentioned earlier
when discussing the sales trend. However, it was
not clear whether that was controlled in the
analysis.
Text has been added to section 4.4.2 on
p61 discussing how the models control
for recession periods, by controlling for
change in GDP, and how the results
indicate a diminishing low-buy effect
(and lower statistical power) approaching
the recession
Dr. Yan
Zhou
3.1.4
Page 44/Figure 8: Could you add an example to
show how to read the chart, such as the "regime
shifts in the PPI-Trucks corresponding to the
2007 and 2010 enforcement periods"?
Added discussion of the changepoint
algorithm and graph interpretation to
section 3.1.4.
Dr. Yan
Zhou
2.3.4
Page 11/17: Why would buyers move up in
vehicle class if higher class is more expensive?
Then on page 17, it actually states an opposite
trend.
Text has been added to section 2.3.4
suggesting reasons for class shifting
Dr. Yan
Zhou
2.6.1
Page 24: Did the IEA study which was conducted
13 years later (since 2004) conclude faster
decoupling?
Evidence from the IEA report does not
indicate faster decoupling, see figure 6 of
the IEA report.
Dr. Yan
Zhou
Throughout
Figure 4: Font size is too small to see
Figure size increased throughout the
document
Dr. Y.
Christy
Zhou
4.4
The authors did not explicitly state the
assumptions that allow them to identify the
parameters /?4 and /?5 (and the jump in the
parameters before and after the introduction of
the new standards).
Section 4.4 has been updated with
greater clarity about the specification of
/?4 and /?5 and the underlying
assumptions.
Dr. Y.
Christy
Zhou
4.4.1
In the worst case, when the identifying
assumption falls apart, we should interpret the
estimates of "pre buy" and "low buy" as
conservative estimates.
This suggestion has been incorporated,
with additional detail in footnote 12.
Dr. Y.
Christy
Zhou
3
the authors can benefit by explaining specific
variables that go into Equation (4) on page 58. In
the current version, that does not appear until
page 66 in the regression table.
A table has been added to section 3 to
identify the variables used up front in the
text, and clarifying text has been added
related to EQ 4.

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Dr. Y.
Christy
Zhou
4.4
Also, the month variable is usually called the
"month-of-the-year dummy variables" in a
regression like this. Stating montht as a month
will confuse readers who imagine the month as
1,2,.. .12; 13,14	24; 25..., which is typical when
you have more than a year.
Text has been added clarifying that
Month_t corresponds to month of year
dummy variables, rather than a series of
sequential months.
Dr. Y.
Christy
Zhou
4.1 onwards
The authors may want to call MogClassit as
MogSalest. Usually, the class is a dummy, so
readers will be confused. What the authors mean
are sales. Given that the authors estimate
Equation (4) separately for each class,
AlogSalest is sufficient and there is no need for
AlogSalesit. The authors should state Equation
(4) is estimated separately for each class before
getting into Section 4.4.1; otherwise, readers will
wonder why the authors do not have a dummy
for each class on the right-hand-side.
We have updated the regression
equations to MogSaleStf as suggested
by the reviewer. We appreciate the
guidance on clarity
Dr. Y.
Christy
Zhou
4.1 onwards
for the Equation on page 65, it is better to call
"log Class 8" as "sales". It can be MogSales8t
or another way depending on the authors'
preference. Also, it may be helpful to add an
equation number.
Equations have been changed to
MogSalesi t throughout, where i
represents class. All equations are now
numbered.
Dr. Y.
Christy
Zhou
4.4.1
The authors stated on page 58 that they group
months together in the pre and post dummies.
The authors should clearly state the number of
months they group in their baseline estimates. (If
they do robustness and adjust the bandwidth, they
can explain that later.)
As discussed in Section 4.4.1 we do not
specify a baseline number of months, but
instead test across the set of available
months, comparing statistical tests for
the different combinations of months.
Dr. Y.
Christy
Zhou
4.4.1
First, for Figures 14-23, and Figures 25-28, it
appears the authors plot the coefficients of
seasonality dummies on top of the "pre buy" and
"post buy" dummies, aka + /?4 before the
new regulation year, and /?im + /?5 after the
Text has been added to section 4.4.1
discussing that the figures only show the
coefficients on the regulation variables.
We only show the coefficients on the
regulatory variables; seasonality is

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regulation is introduced. However, the authors
only say "these models show ... (Figure 14)"
without informing me explicitly what are plotted
in those figures. I recommend the authors state
what they plot at least once. Then the rest of the
figures would be self-explanatory
otherwise controlled for by the month
dummies.
Dr. Y.
Christy
Zhou
4.4.2 and 4.4.3
Second, given Equation (4) is the main equation,
and Figures 14-15 are the main two figures, the
authors should at least present the regression
table of Equation (4) just like they have presented
Table 13 for the Equation on page 65.
Regression tables have been added for
Class 8 and Class 7 regression models
Dr. Amelia
Regan
2.8
On page 33... Table 3 has the column heading,
Estimated/Anticipated Costs, but the word
expected shows up in the text of this paragraph
on page 33. Is expected incremental = estimated?
Or = anticipated? Or neither? Is this expected as
in probabilistic expectation? Sorry if my concern
appears silly, but this section of the text is difficult
to follow.
These costs are incremental, which has
been clarified in the text accompanying
table 3. "Expected" has been changed to
"estimated" as the regulatory costs
discussed are derived from EPA
estimates.
Dr. Amelia
Regan
4.4.2
In Section 4.4.2, it might help if a sentence is
added to explain the positive beta coefficient for
one-month period post-regulation. I can guess
that these were pre-ordered vehicles that for some
reason did not arrive until the first month after
the regulation was in place. Perhaps the sales
were therefore not even governed by the new
regulations? The six-month period post the 2004
regulation is actually months 2-6, not 1-6.
Text has been added under figure 16 per
the reviewer's suggestion.
Dr. Amelia
Regan
5
There is a statement on page 78 that makes sense
but would clearer with a second sentence.
"In the case of the 2010 regulations,
significant pre-buy and low-buy periods
partially cancel one another out, though
Thank you for the useful suggestion, the
text in the conclusion has been updated
based on the reviewer's suggestion.

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the period of significance was longer and
larger for the pre-buy."
MY SUGGESTION: By that we mean that the
pre-buying before regulation and reduced
purchases post-regulation are on the same scale.
Together they reduce the effectiveness of the
regulation.

Dr. Jose
Holguin-
Veras
2.3.1
Page 15, section 2.3.1: The trucking companies
that exercise pre-buy, low-buy, and class-
switching are not in competitive markets. In these
markets, rates are equal to marginal costs, and the
carriers do not recover the fixed costs, and
obviously cannot purchase new trucks. The
companies that participate in pre-buy, low-buy,
and class-switching behaviors are those that
operate in markets where the companies have
some pricing power. Owner-operators,
intermodal-truck operators, and other small
companies are not likely to do pre-buy, low-buy,
or class-switching.
We agree with the reviewer. In a non-
competitive market, firms have greater
power to set the price of freight. In such
instances, more expensive vehicles, or
earlier purchases, may have little effect,
as firms can adjust the freight rate to
cover costs.
Text has been added to section 2.3.1
incorporating the reviewer's suggestions.
Dr. Jose
Holguin-
Veras
2.3.4
Page 16, Section 2.3.4: It should be made clear
that pre-buy, low-buy, and class-switching
(together with do-nothing) are alternative choices
for company managers.
Clarifying text has been added to section
2.3.4
Pre-buy may lead to low buy as vehicles
have already been purchased. Low buy
may also occur independently when
purchasers are holding off because of
price increases or unobserved or
technical reasons.
We emphasize that "do nothing" is also
a viable pathway, but remains

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unobservable. Pre-buy and low-buy
effects are the differences compared to
the do-nothing/baseline. We're testing
whether buyers diverge from their
normal purchase cycles, and to what
extent.
Dr. Jose
Holguin-
Veras
4.4
Section 4.4. Statements such as "Model results for
Class 7 show visual evidence..." are too informal
for a report of this nature. They need to support
such conclusions with statistical tests.
Figures are too small.
Figure 21, by the authors' admission, shows
results that are not statistically significant. In cases
like that, it is better to simply add a note
indicating that these results were not significant.
Informal statements have been removed
and supporting statistics added where
appropriate.
Figure sizes have been increased to
improve readability.
Results that are not statistically
significant carry important information —
that we are not able to identify an effect.
We believe it is important to provide the
full evidence of our analyses.
Dr. Jose
Holguin-
Veras
4.1 onwards
Notation used in equations:
1.	The vast majority of the equations in the
report seem to be under-specified. Are alpha
and beta vectors of parameters? Or single
parameters? Please clarify.
2.	In equation 3, is betal constant for all
months t?
3.	Is the variable "Month" in equation 2, a
time index that start with 1... until the
number of the last time period? Or is it a set
of binary variables for each month?
Equations have been updated to improve
clarity, along with supporting text.

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2 Moderate
Reviewer
Section
Comment
Response
Dr. Yan
Zhou
2.2
First, an overall summary of all the regulations
(e.g., 2004, 2007 and 2010...) studied would be
helpful to ensure the audiences understand the
major policies implied by each of them. Table 3
did show the cost estimates of each regulation.
However, a discussion of the major emission
standards, and how that could change the vehicle
cost but also reduce the operation cost would be
very helpful to put some of the results into
context.
We had added a summary of the regulations, per the
reviewer's suggestion
Dr. Yan
Zhou
3.3
Page 51 Section 3.3: Why do you choose 12
months as the analysis horizon? Is this the
standard study period for pre-buy? What are the
typical periods considered for pre-buy and low-
buy analysis?
We have added text clarifying the choice of the 12-
month period of analysis to section 3.3. While there are
no standard practices, prior work (Rittenhouse and
Zaragoza-Watkins) looked at an 8-month period, which
this work extends, consistent with vehicle model year
update and purchasing cycles.
Dr. Yan
Zhou
4.2.1
For the oil price: Did you use monthly or annual
oil price in the analysis? If monthly, have you
tried using the average oil price over a few
months (4-5 months for example)?
We tested a range of combinations for aggregating
monthly fuel prices, including averaging over a period of
1—6 months. The coefficient on fuel price was affected
by this exploratory analysis; however, the coefficients on
other independent variables, including the coefficients on
regulations, were essentially unchanged when examining
aggregated fuel prices.
Dr. Yan
Zhou
2.8
Table 3 did not show the expected cost impact of
the 2014 regulations. Secondly, again, a brief
description of each studied regulation and their
impacts on vehicle ownership cost (vehicle,
operation, maintenance) would be helpful. Third,
did you find similar things for other regulations?
Fourth, if this conclusion is true, then the take-
way for audiences like DOE would be energy-
We have added text related to table 3 discussing the
regulations in greater detail.
The reviewer's point, that energy efficient technologies,
while increasing up front capital costs, lead to lower
operating and lifetime costs, is included in the discussion
of the 2014 regulations.

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efficient technologies in HDV could be cost-
effective for fleet operators

Dr. Yan
Zhou
Ex. Sum.
And
Conclusion
Figure 18-23: Please add discussions about
whether the analysis shows one behavior is
greater than the other. For example, does Figure
18 mean there was more "low buy" than "pre
buy"? except Figure 18.
We have added text to the executive summary and
concluding sections regarding the importance of also
considering the duration of the effect, in addition to the
magnitudes observed.
Dr. Yan
Zhou
2.5.2
Section 2 Literature Review: Are there any
literature on the energy and emissions impact of
pre-buy and low-buy behaviors? If yes, could you
add a short description of them?
The literature review has been updated to include a
summary of potential emissions impacts from pre-
buy/low-buy behaviors
Dr. Y.
Christy Zhou
4.4
To improve the validity of the assumption, first, I
think the authors can benefit from stating it
explicitly after introducing Equation (4) on page
58. Also, as I will mention under Charge
Questions #3 and #4, after introducing Equation
(4), the authors would benefit from stating the
specific controls log(Xt) included in the
Equation, which does not appear until page 66.
The authors should explain log(Xt) right after
Equation (4) before explicitly laying out the
identifying assumption. Without introducing
which variables go into the Equation, it will be
unclear what /?4 and /?5 pick up. Third, the
authors should discuss in which directions and in
which cases their estimates are biased when their
assumption does not hold up. I think the
estimates can be conservative for the reasons that
I stated above if their assumption does not hold
up. The authors should lay out all possibilities
that they believe might be possible.
Text has been added to section 4.4 below EQ 4 explicitly
stating the effects that beta_4 and beta_5 are picking up.
Text has also been added discussing the directions
estimated.
Dr. Y.
Christy Zhou
Throughout
the authors can benefit from using more
consistent descriptions
We have adjusted descriptions throughout the text to
improve clarity

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Dr. Y.
Christy Zhou
Throughout
Given that Figures 14-23, and Figures 25-28, plot
coefficients, these figures should include
confidence intervals.
Significance levels have been added to the plots to
improve readability and identify significant coefficients
Dr. Y.
Christy Zhou
4.7
Section 4.7 is not the strongest part of the report
because of all the additional assumptions needed
for computing price changes for the elasticity. It
is reasonable given that Section 4.4 to 4.6 are the
main results. I recommend toning down Section
4.7 a little bit as potential implications or the
suggestive outcome or something along that line.
We have added language that this section is an
exploratory analysis
Dr. Jose
Holguin-
Veras
3.5
Another issue to be addressed is the tendency to
make informal statements such as this one from
page 53: "23 eta represents the "change in the percent
change in Y for a one-unit 'change in the percent change' of
X. The practical application of this coefficient is to
consider it identical to the elasticity. This statement is
wrong from the mathematical point of view.
We agree with the reviewer's suggestion to remove,
adjust, and support informal claims and have made
adjustments to the text accordingly.
It is incorrect that the statement is mathematically
wrong. We have provided a citation to section 3.5 to a
demonstration of this point.
Dr. Jose
Holguin-
Veras
2.5.4
Page 17, Section 2.3.5: This section conveys the
impression that changes in freight mode choice
are always forthcoming in response to price
changes. In fact, shippers and receivers—who
are the key decision makers in this matter—have
considerable inertia, and decide on mode and
vehicle changes after considering other factors,
e.g., reliability. Freight mode choice does not
change as easily as suggested in this section.
We have added text to a new section (2.5.4) discussing
vehicle choice and class switching. This section includes
discussion of the importance of considering the needs of
shippers and receivers, not just carriers.
Dr. Jose
Holguin-
Veras
2.3.4
Page 30, Section 2.7: The review must be
expanded to include papers and reports on
vehicle choice.
We have added text to a new section (2.3.4) discussing
vehicle choice and class switching
Dr. Jose
Holguin-
Veras
Throughout
Page 43, last paragraph: "Visual inspection" is not
a formal method to assess regime shifts. If not
supported by statistical tests, the analysis must be
removed.
We have removed informal language and provided
supporting statistics where relevant. We nevertheless
consider visual inspection to be a useful aid in
understanding our data and developing specifications.

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Dr. Jose
Holguin-
Veras
3.5
Page 50, top two lines: Using the log differences
imposes a functional form with constant
elasticities. This is a strong assumption as in most
cases elasticities are variable, i.e., as a function of
price and other variables.
Text has been added to section 3.5 discussing the
assumption of constant elasticities as reasonable here.
We agree with the reviewer that the aforementioned
assumption has its limitations in principle. For this study,
the costs of regulation, and other associated factors, are
likely felt similarly by all firms and the ranges in unit-
level costs anticipated by different firms are likely small.
We argue that the constant elasticity assumption holds as
reasonable in this case, because, for small changes, the
percent change and using a linear form produce similar
results.
Dr. Jose
Holguin-
Veras
4.4
Section 4.4. The authors should not use
statements such as "the coefficients for other
explanatory variables are robust to model
specification... and have been omitted in favor of
discussion ..." This is not appropriate. To start,
what is the meaning of "robust"? They must
show the parameter values, and their statistics, to
ensure that they are conceptually valid and
statistically significant.
Class 8 and Class 7 regression summary tables have been
added to the text to support claims of robustness,
including standard errors and significance levels across a
set of model specifications. "Robust" is commonly used
in econometric studies to indicate that a coefficient does
not change very much when other factors in the
regression change. It is a term of art, not precision.
Dr. Jose
Holguin-
Veras
4.5
Section 4.5: Class Shifting
1.	As explained in my answer to question 2,
this section is problematic for numerous
reasons, the analysis/theory framework is
inadequate; the variables used cannot
properly explain the phenomenon, among
others. Moreover, the results are not
conceptually valid.
2.	The report seems to focus on the switch
involving classes 7 and 8. Was a switch
involving classes 8 and 9 considered? Or a
switch involving three or more classes?
The title of the section has been changed to indicate that
the class shifting analysis is exploratory. Otherwise we
believe that the text endeavors to convey that these
results are non-conclusive, and indicate "possible"
results.
Text has been added to the end of this section, further
highlighting that the results are only indicative, and not
comprehensive.
We are uncertain what the reviewer is referring to as
Class 9 vehicles; the classes (by weight) studied in this
analysis are as laid out in Section 2.1 and table 1.

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3 Major
Reviewer
Section
Comment
Response
Dr. Jose
Holguin-
Veras
4.5 and 4.7
In summary, the data sources are:
1.	Appropriate to obtain a general idea of
the existence of pre-buy and low-buy
behaviors, and to quantify direct
elasticities at the market level; and
2.	Inappropriate for analyses of class-
switching and estimation of cross-
elasticities.
We agree with the reviewer's comments in point 1.
Regarding point 2, we have added clarifying text that
these results are both exploratory, and only indicative
of the potential for class shifting.
We respectfully disagree with the reviewer's statement
that the methods employed are inappropriate for class-
switching and estimating cross price elasticities. The
methods employed in this analysis are statistically
rigorous, methodologically appropriate, and employ the
best available data. The state of published knowledge
on the study of class-switching is limited and in its
infancy, and we believe that the approaches employed
here, using macroeconomic factors, can support further
exploration of the class-switching issue.
Regarding cross-price elasticities, the analysis was
structured such that the direct outputs of our models
would return elasticities. Based on estimated vehicle
prices and EPA's own estimated price increases we
estimate the cross-price elasticity. This is a common
approach, consistent with best practices and while
micro-level transactional data offers an alternate
approach it does not invalidate this work, and is instead
a complement. The reviewer's statements that the
elasticities are larger than anticipated is best considered
in the context of the duration over which we identified
effects. These elasticities are not long-term, or annual
estimates, but instead reflect behaviours on the order

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of months, not years, as is typically reported.
Furthermore, we emphasize that pre-buy and low-buy
effects of zero change are also reflected in the results,
implying an elasticity of zero.
Dr. Jose
Holguin-
Veras
4
Section 4 ... is repetitive and unnecessarily long
(to a great extent because it discusses results that
are not statistically significant and not
conceptually valid). Section 4 is problematic in
other respects as it does not contains the model
statistics—such as t-values, R2, and F— that
reviewers need to judge the validity of the
results. In my view, this is unacceptable.
Focusing on results that are statistically
significant and conceptually valid; and adding a
comprehensive appendix with the final models
obtained (and the corresponding statistics)
would lead to a more concise, readable, and
useful document.
We have added supporting statistics and summary
tables where relevant to support the reader.
We respectfully disagree with the reviewer regarding
non-significant results, and chose to leave those in the
analysis. We believe that presentation of non-significant
findings is just as important as findings with statistical
significance, as they inform the reader of the
completeness of the analysis, and identify areas of study
for the benefit of the future researcher.
Dr. Jose
Holguin-
Veras

the conclusions reached regarding class-
switching and elasticities are very difficult to
defend.
As mentioned in other responses we have endeavored
to be clear that the discussions of price elasticities and
class-switching are exploratory, and have added
supporting text accordingly.
Dr. Jose
Holguin-
Veras
4.7
Moreover, the absolute values of the estimated
elasticities (0.558 to 2.347) are simply too high to
be credible. My conclusion is that the data do
not support a solid estimation of elasticities.
The text includes suggestions for why the estimated
elasticities may be higher than the reviewer expects,
including that the effects are short-lived and likely
capture other unobserved regulatory effects. Notably,
an elasticity of zero is also a potential outcome of this
analysis for consideration. Reference to this has been
added to the text (see section 4.7).
Dr. Jose
Holguin-
Veras
4.7
Equally concerning are the results for cross
elasticities, which were found to range between
0.681 and 1.712. As amply established in the
See above comment

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transportation literature on cross-elasticities,
relative to each other, cross elasticities ought to
be smaller than the corresponding direct
elasticities.

Dr. Jose
Holguin-
Veras
Throughout
In its current version, the report is unnecessarily
long, repetitive, with illegible figures, and lacking
technical details about the models discussed.
There are numerous ways to improve it. For
instance:
1.	Increase the size of figures to make them
readable. In most cases, the font size is 5 or
less.
2.	Include all the statistics of the models
discussed.
3.	Instead of copying / pasting / adjusting the
text to fit the results, summarize the results
in tables (with all relevant statistics).
4.	The authors discuss results that are not
statistically significant, and even results that
are not conceptually valid (that the authors
struggle to explain). I suggest removing all
discussions of non-significant and not
conceptually valid results. A focused
discussion of statistically significant and
conceptually valid results would cut the size
of the document by at least 50%.
We have increased the size of figures and restructured
the page layout to improve readability.
Model statistics have also been included.
As noted in our other response, we believe that
including non-significant findings is important and
have chosen to leave them in the text.
Dr. Jose
Holguin-
Veras
2.3.5
The literature review is very weak, particularly
on topics directly relevant to class-switching.
The authors must expand the literature review to
include a broader discussion of freight mode
choice and freight vehicle choice, and the
implications of the chief findings from the
The literature review has been updated to include the
reviewer's suggestions; see section 2.3.5.

-------


literature on the research reported in the
document.

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January 21, 2021
Analysis of Heavy-Duty Vehicle
Sales Impacts
Regulation	(Octob
Peer Review
Final Report
Prepared for
US EPA 0AR/0TAQ
2000 Traverwood Dr.
Ann Arbor, MI 48105
Prepared by
RTI International
3040 E. Cornwallis Road
Research Triangle Park, NC 27709
RTI Project Number 0215574.004.034
EnDyna
HRTI
INTERNATIONAL

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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
TABLE OF CONTENTS
1.	Introduction	1
1.1	Background on ERG Draft Report	1
1.2	Identification and Selection of Expert Peer Reviewers	2
1.2.1	Identification of SMEs	2
1.2.2	Peer Reviewer Candidates	3
1.2.3	Conflict of Interest Screening Process	6
1.2.4	Selection of Peer Reviewers	6
1.3	Scope of Peer Review	8
1.4	Peer Review Teleconference	8
1.5	Addition of Alternate Peer Reviewer	9
1.6	Organization of Report	9
2.	Charge Questions	10
3.	Summary of Peer Reviewers' Comments	11
4.	Individual Peer Reviewers' Comments	21
4.1	Dr. Jose Holgufn-Vera	21
4.2	Dr. Amelia C. Regan	28
4.3	Dr. Yichen (Christy) Zhou	31
4.4	Dr. Yan (Joann) Zhou	35
5.	Peer Reviewer Curriculum Vitae	39
5.1	Dr. Jose Holguin-Veras	39
5.2	Dr. Amelia C. Regan	66
5.3	Dr Yichen (Christy) Zhou	68
5.4	Dr. Yan (Joann) Zhou	70
6.	Agenda for Peer Review Teleconference	74
7.	Conflict of Interest Form and Non-disclosure / Confidentiality Agreement	76

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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
1 Introduction
The U.S. Environmental Protection Agency (EPA), Office of Transportation and Air Quality (OTAQ),
contracted with RTI International for an independent external letter-style peer review of the draft final
report Analysis of Heavy-Duty Vehicle Sales Impacts due to New Regulation (dated October 9, 2020), prepared
by Eastern Research Group (ERG). The report is referred to throughout this peer review as the "ERG
draft report."
EPA's peer review guidelines specify that all influential scientific and technical work products must
undergo independent peer review per specific agency protocols. Under subcontract to RTI, EnDyna was
tasked with managing an independent external peer review process to evaluate the ERG draft report.
EPA's goal for this peer review was to ensure the use of the highest quality science in its predictive
assessments. By so doing, EPA seeks to assure its stakeholders that this analysis has been conducted in a
rigorous, appropriate, and defensible way.
The peer reviewer selection process for the ERG draft report involved selecting three expert peer
reviewers who were available to participate in the peer review, including preparing individual written
peer review comments during a specific time frame. In recruiting these expert peer reviewers, EnDyna
evaluated the qualifications of peer reviewer candidates, conducted a thorough conflict of interest (COI)
screening process, and independently selected the peer reviewers. RTI and EnDyna then provided
management and oversight of the independent external peer review process. RTI and EnDyna produced
this report that documents the peer review process and summarizes the peer reviewer comments on the
Charge Questions.
The sections below provide background on the ERG draft report, describe EnDyna's process for
identifying and selecting expert peer reviewers for this peer review, provide EPA's scope for the peer
review of the ERG draft report, discuss the peer review teleconference and issues encountered affecting
the independence of this peer review, discuss the addition of an alternate peer reviewer, and outline the
organization of this report.
1.1 Background on ERG Draft Report
EPA has been examining the effects of emissions standards on sales of heavy-duty vehicles. The
implementation of regulations that increase the capital costs of new vehicles could influence end-
user purchase decisions, especially when access to capital is limited. Instead of purchasing a new (more
expensive) vehicle, end users may choose to maintain their existing vehicles to extend their lives. Having
a means to estimate the sales impacts of regulatory standards would enhance EPA's ability to examine
the economic and environmental effects of the standards. From the abstract of the report:
Heavy-duty vehicle activity is a major source of criteria pollutants in the transportation sector,
contributing 35% more particulate matter emissions than light-duty vehicles in the United States. The
federal government has implemented a series of policies aimed at reducing pollution from heavy-duty
vehicles, which have cut particulate matter and nitrogen oxide emissions by 90% on a per unit activity
basis since 1997. These regulations have led to millions of dollars in estimated health and environmental
benefits, but do not come without cost.
Using sales data and time-series econometric methods, this work finds evidence of pre-buy and low-buy
behaviors around regulations, as well as possible class-shifting. Pre-buy and low-buy behavior effectively
reduce the effectiveness of proposed regulations, as industry purchases more vehicles than they normally
might prior to the regulation in order to avoid having to pay higher prices for regulation compliant
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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PEER REVIEW SUMMARY REPORT - Draft Final
vehicles after the regulation goes into effect. As such, the effect of the regulation is tempered as the
vehicles purchased just prior to regulations persist in the fleet long after the regulation goes into effect.
We [ERG] extended this analysis to explore the effect of predicted regulatory cost on pre-buy and low-
buy behavior, with mixed evidence supporting greater pre-buy and low-buy effects with greater
anticipated cost.
This study also identifies evidence of potential class-shifting, which has not been widely discussed in the
literature. In instances where regulatory pressure might lead a firm to purchase a Class 8 vehicle when
they might normally have purchased a Class 7 vehicle because of economic constraints, the effect of the
regulation may again be tempered, given that larger trucks have larger engines and thus higher emissions,
which runs counter to the goals of the regulations.
The ERG draft report meets the criteria for "influential scientific information" under the Office of
Management and Budget's Final Information Quality Bulletin for Peer Review. Therefore, EPA had
determined that this ERG draft report contained new scientific information that was subject to peer
review.
1.2 Identification and Selection of Expert Peer Reviewers
The peer reviewer selection process under WA 4-34 involved selecting three subject matter experts
(SMEs) who were available to participate in the peer review, including preparing individual written
comments, during a specific time frame. In recruiting the peer reviewers, EnDyna evaluated the
qualifications of peer reviewer candidates, conducted a thorough COI screening process, and
independently selected the peer reviewers. These activities are discussed in more detail below.
1.2.1 Identification of SMEs
As a subcontractor to RTI, EnDyna participated in a WA 4-34 kickoff conference call with RTI and
EPA OTAQ on August 25, 2020, to discuss the qualities for potential SMEs.
EnDyna was tasked with independently selecting peer reviewers who collectively had the background
and proven expertise for the following three areas:
1) Academic literature on vehicle demand modeling with a preference for research on heavy-duty
vehicles,
2) Regression analysis, and
3) Statistical analysis involving time-series data.
The SMEs were identified through literature and internet searches of scientific journals, professional
societies, universities, scientific meetings, nonprofit organizations, and government agencies. EnDyna
worked to identify SMEs representing a range of affiliations: academia, nonprofit organizations,
industry, trade associations, consulting, and government research facilities.
EnDyna contacted 24 people, of whom 10 people were interested in participating, provided their
CY/resume (or bio), and were also available during the anticipated peer review time frame. EnDyna
researched readily available information about the 10 interested individuals for relevant experience and
demonstrated expertise in the subject matter of the ERG draft report, as demonstrated by educational
degrees attained, research and work experience, publications, awards, and participation in relevant
professional societies.
EnDyna reviewed those 10 interested individuals' CVs/resumes (or bios) and removed one individual
from further consideration because of limited relevant expertise. EnDyna contacted the remaining nine
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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PEER REVIEW SUMMARY REPORT - Draft Final
interested individuals to request a signed COI form and a signed non-disclosure/confidentiality
agreement (NDA). Three of those remaining nine interested individuals did not complete a COI form
or NDA and thus were removed from further consideration.
Completed COI forms and NDAs were received from each of the remaining six interested individuals.
EnDyna removed one of the remaining six interested individuals from further consideration after
additional review of his qualifications and publications indicated that his expertise focused on discrete
choice models instead of relevant experience/expertise in time-series regression models.
1.2.2 Peer Reviewer Candidates
From the remaining five interested individuals who completed a COI form and NDA, EnDyna included
all of them, resulting in five candidate peer reviewers who best met the required fields of expertise for
this peer review.
The names and affiliations of the five candidate peer reviewers, as well as a brief summary of their
qualifications, are provided in Table 1.1. A CV/resume for each of the five candidate peer reviewers
who best met the required fields of expertise (see Table 1.1) was provided to RTI and EPA separately.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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PEER REVIEW SUMMARY REPORT - Draft Final
Table 1.1. Experience/Expertise Matrix for Peer Reviewer Candidates
Name
Affiliation
Academic Degrees
Areas of Expertise
Academic
literature on
vehicle
demand
modeling
Uegressio
n analysis
Statistical
analysis
involving
time-
series data
Jose
Holgui'n-
Veras, PhD
•	Rensselaer
Polytechnic Institute,
Department of Civil
and Environmental
Engineering
•	William H. Hart
Professor
•	Director of Volvo
Research and
Educational
Foundations (VREF)
Center of Excellence
for Sustainable Urban
Freight Systems
(COE-SUFS)
•	Director of the
Center for
Infrastructure,
Transportation, and
the Environment
(CITE)
•	PhD, University of Texas at
Austin, Transportation (1996)
•	MSc (Magister Scientiarum),
Universidad Central de Venezuela,
Transportation (1984)
•	BSc, magna cum laude,
Universidad Autonoma de Santo
Domingo, Dominican Republic,
Civil Engineering (1981)
SME*
vehicle
demand
modeling
with a
preference
for research
on heavy
duty
vehicles:
SME*
SME
SME
Amelia C.
Regan, PhD
•	University of
California at Irvine
•	Professor of
Computer Science
•	Professor of Civil
(Transportation
Systems) Engineering
•	PhD, University of Texas at
Austin, Civil (Transportation
Systems) Engineering (1997)
•	MSE, University of Texas at
Austin, Civil (Transportation
Systems) Engineering (1995)
•	MS, Johns Hopkins University,
Applied Mathematics (1990)
•	BAS, University of Pennsylvania,
Systems Engineering (1987)
SME
vehicle
demand
modeling
with a
preference
for research
on heavy
duty
vehicles:
SME
G
q**
Clifford
Winston,
PhD
•	Brookings Institution
•	Searle Freedom Trust
Senior Fellow,
Economic Studies
Program
•	PhD, University of California at
Berkeley, Economics (1979)
•	MSc, London School of
Economics, Economics (1975)
•	AB, University of California at
Berkeley, Economics (1974)
SME
vehicle
demand
modeling
with a
preference
for research
on heavy
duty
vehicles:
G
G
G
4

Areas
of Expertise
Name
Affiliation
Academic Degrees
Academic
literature on
vehicle
demand
modeling
Regressio
n analysis
Statistical
analysis
involving
time-
series data
Yan (Joann)
Zhou, PhD
• Argonne National
Laboratory, Energy
Systems Division
• Group Manager,
Vehicle and Energy
Technology &
Mobility Analysis
• Principal
Transportation
Systems Analyst
• PhD, Clemson University, Civil
(Transportation) Engineering
(2010)
• MS, Clemson University, Civil
Engineering (2008)
• BS, Wuhan University of
Technology, Wuhan, P. R. China,
Automotive Engineering (2003)
SME
vehicle
demand
modeling
with a
preference
for research
on heavy
duty
vehicles:
SME
SME
SME
Yichen
(Christy)
Zhou, PhD
• Clemson University
• Assistant Professor,
Department of
Economics
• Postdoctoral Fellow,
Resources for the
Future (RFF) (August
2016—July 2017)
• PhD, University of Maryland at
College Park, Economics (2016)
• MA, University of Maryland at
College Park, Economics (2014)
• BA with Distinction, University of
Virginia, Mathematics and
Economics (2010)
• BA student at large, Huazhong
University of Science and
Technology, P.R China (2006—
2008)
SMEW
vehicle
demand
modeling
with a
preference
for research
on heavy
duty
vehicles:
QXXX
SME
G
Key:
SME: Primary area(s) of expertise/experience
G: Good knowledge/experience
L: Limited knowledge/experience
Notes:
'^Freight transportation demand modeling is Dr. Holguin-Veras's primary expertise. His work on freight demand
modeling focuses on enhancing the realism of spatial price equilibrium models and development of simplified modeling
techniques. His work on freight generation and freight trip generation has led to the development of freight trip
generation models.
¦** Dr. Regan indicated she had "quite a bit of recent experience modeling time-series data," so she considered that
rating as borderline but stated she would "prefer to be conservative" by using G. (EnDyna had rated that as SME for
Dr. Regan.)
xxx £)r Christy Zhou's main area of expertise is vehicle demand estimation (of purchasing decisions rather than trip
decisions). Dr. Zhou indicated that the subrating under Column 1 would be G because the vehicle demand models she
has estimated were for passenger vehicles.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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PEER REVIEW SUMMARY REPORT - Draft Final
1.2.3 COI Screening Process
EnDyna conducted COI screening for the five candidate peer reviewers who best met the required
fields of expertise (see Table 1.1) to ensure that the SMEs had no COI or appearance of the lack of
impartiality. The COI screening was conducted in accordance with EPA's Peer Review Handbook and
involved each SME completing a COI questionnaire (COI form) to determine if they were involved
with any other work or organizations that might create an actual, potential, or perceived COI for this
peer review. Section 7 provides the COI form and NDA for this peer review.
Completed COI forms and a signed NDA were received from each of the five candidate peer reviewers.
Although some of the candidate peer reviewers disclosed previous or current research funding in related
fields, it was EnDyna's opinion that such research funding opportunities and relationships with research
funding agencies and organizations would not likely pose an actual or potential COI. SMEs with
expertise in areas related to this peer review are likely to engage in obtaining research funding and
conducting related research or similar project activities, and those disclosures were included on their
COI forms.
Dr. Holguin-Veras was careful to disclose on his COI form that he conducted sporadic consulting work
with transportation agencies and companies and indicated this was related to his employment as a
faculty member at Rensselaer Polytechnic Institute. EnDyna interpreted his approach to such disclosure
as documenting occasional consulting related to his role as faculty at Rensselaer Polytechnic Institute
that was either not during the preceding 2 years or did not provide 15% or more of his annual
compensation (either of which would have required fuller disclosure of consulting activities on the COI
form). EnDyna concluded it was not likely that Dr. Holguin-Veras's sporadic consulting work could
represent an appearance of the lack of impartiality for this peer review, which could potentially lead to
Dr. Holguin-Veras's impartiality as a peer reviewer to be questioned (if selected as a peer reviewer).
1.2.4 Selection of Peer Reviewers
EnDyna evaluated each peer reviewer candidate's credentials to select three SMEs who, collectively,
cover the areas of expertise needed for this peer review, have no actual or potential COI or appearance
of the lack of impartiality, and were available to complete the peer review within the desired time frame,
including preparing individual written comments.
After review and consideration of the available information, EnDyna selected the three peer reviewers
summarized in Table 1.2 on September 29, 2020. EnDyna also selected an alternate peer reviewer in
case one of the three selected peer reviewers became unavailable during the peer review time frame.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
Table 1.2. Selected Peer Reviewers
Name
Areas of Expertise
Academic literature on vehicle
demand modeling
Regression analysis
Statistical analysis involving time-
series data
Selected Peer Reviewers:
Amelia C. Regan, PhD
SME
vehicle demand modeling with a
preference for research on heavy
duty vehicles:
SME
G
G**
Yan (Joann) Zhou, PhD
SME
vehicle demand modeling with a
preference for research on heavy
duty vehicles:
SME
SME
SME
Yichen (Christy) Zhou,
PhD
SME***
vehicle demand modeling with a
preference for research on heavy
duty vehicles:
G***
SME
G
Alternate Peer Reviewer:
Jose Holgufn-Veras,
PhD
SME*
vehicle demand modeling with a
preference for research on heavy
duty vehicles:
SME*
SME
SME
Key:
SME: Primary area(s) of expertise/experience
G: Good knowledge/experience
L: Limited knowledge/experience
Notes: See Table 1.1 for definitions of asterisks
EnDyna completed the Peer Review Charge Document, which included the Charge Questions (see
Section 2) that EnDyna had developed and were approved by EPA. The three selected peer reviewers
— Dr. Amelia Regan, Dr. Y. Christy Zhou, and Dr. Joann Zhou —were issued a Peer Review Charge
Document on October 13, 2020.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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1.3 Scope of Peer Review
EPA approved the scope of this peer review as defined by EnDyna for the ERG draft report to focus
the peer review process effectively on the Charge Questions (see Section 2). The peer reviewers were
directed to keep their written peer review comments within the EPA scope, as defined below:
The scope of this letter-style peer review is technical in nature, reviewing the methods, data
quality, data sources, underlying assumptions, and the overall strengths and limitations of the
study. EPA is especially interested in comments that focus on the validity or scientific merit of
the methodology and that identify any significant weaknesses in the scientific information from
the methodology.
• Peer reviewers should focus on providing comments on the technical nature of the
report, and its consistency with the state of current science as you understand it. The
peer reviewers should evaluate the analysis used to develop the proposed methods and
the suitability of those methods to estimate sales, pre-buy, and other impacts for use in
policy analysis.
• Peer reviewers should also focus on the clarity and completeness of the presentation in
the draft report. Because the review is technical in nature, the peer reviewers should not
focus on editorial style.
1.4 Peer Review Teleconference
WA 4-34 required a peer review teleconference to give peer reviewers the opportunity to ask clarifying
questions related to the report. To facilitate an effective peer review teleconference, EnDyna requested
any major questions from the peer reviewers about the ERG draft report. EnDyna synthesized and
clarified each of those major questions, compiled them, and submitted those major questions to RTI
and EPA on October 28, 2020. EnDyna explained that those were the major scientific/technical
questions from the peer reviewers that would be on the agenda for the peer review teleconference
scheduled for November 4, 2020. EnDyna requested that EPA be prepared to provide responses to
those peer reviewer questions at the peer review teleconference.
Section 6 provides the agenda for the November 4, 2020, peer review teleconference, which included
the peer reviewer questions that were compiled by EnDyna and submitted to RTI and EPA on October
28, 2020. The agenda also included the following Peer Review Teleconference Ground Rules (from the
Peer Review Charge Document):
• An external peer review is intended to solicit individual reviewer feedback to increase the
independence of the peer review process.
• The peer reviewers are not asked to, and should not attempt to, form consensus or collective
recommendations, ratings, or opinions, and peer reviewers must understand that they should
provide individual feedback on the research product.
• Any EPA staff who may attend the peer review teleconference can only provide background
information on the research product to the peer reviewers, which can occur only during the
teleconference run by EnDyna and at EnDyna's request.
• The peer review teleconference will not include discussion related to EPA's policies and
decisions or current or proposed EPA regulations.
One of the three selected peer reviewers, Dr. Amelia Regan, unexpectedly did not call into the
November 4, 2020, peer review teleconference and did not respond to attempts by EnDyna to contact
her during the initial 15 minutes of the teleconference or the subsequent 2 days (see Section 4.2). After
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PEER REVIEW SUMMARY REPORT - Draft Final
the teleconference, RTI sent Dr. Regan information about the teleconference (copying EnDyna), but
neither RTI nor EnDyna received any response from Dr. Regan from that communication. Later, when
Dr. Regan finally answered a phone call from EnDyna on November 16, 2020, EnDyna confirmed that
Dr. Regan would review the information sent by RTI about the teleconference before completing her
written peer review comments. Given the uncertainty about Dr. Regan's availability and whereabouts,
EnDyna contacted the alternate peer reviewer (see Table 1.2) on November 6, 2020 (see Section 1.5).
1.5 Addition of Alternate Peer Reviewer
EnDyna contacted the alternate peer reviewer, Dr. Jose Holguin-Yeras, on November 6, 2020, and
obtained his agreement to participate in this peer review. EnDyna issued a Peer Review Charge
Document to Dr. Jose Holguin-Veras on November 6, 2020. This was necessary to ensure that at least
three expert peer reviewers would provide written peer review comments.
1.6 Organization of Report
This peer review report comprises six sections:
• Section 1 describes the process for this independent external letter-style peer review.
• Section ^presents the Charge Questions sent to each of the peer reviewers for comments.
• Section 3 includes the summary of the peer reviewers' comments.
• Section 4 consists of each individual peer reviewer's comments.
• Section 5 provides the curriculum vitae for each peer reviewer.
• Section 6 provides the agenda for the peer review teleconference.
• Section 7provides the COI form and NDA for this peer review.
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2 Charge Questions
The objective of this external letter-style peer review was to obtain written peer review comments from
individual experts to conduct an independent external peer review and evaluate the ERG draft report to
1) ensure the use of the highest quality science in EPA's predictive assessments and 2) for EPA to
assure its stakeholders that this analysis was conducted in a rigorous, appropriate, and defensible way.
RTI and EnDyna charged each peer reviewer with evaluating the ERG draft report and responding to
the eight Charge Questions presented in Table 2.1.
Table 2.1. Charge Questions
1. Does the overall presentation in the draft report describe the data and methods sufficiently to allow
the reader to form a general view of the quality and validity of the analysis performed?
2. Are the data sources and assumptions appropriate for the analysis conducted? If yes, explain why. If
not, describe all issues identified regarding the validity of data sources and assumptions and provide
suggestions and references for other available data that might be used to improve this analysis. As
relevant, describe how the validity of data sources and assumptions could be more clearly described in
the report.
3. Is the description of the analytic methods and procedures clear and detailed enough to allow the
reader to develop an adequate understanding of the steps taken and assumptions made in this
analysis? If yes, explain why. If not, explain how the analytic methods and procedures could be more
clearly described in the report.
4. Are the analytic methods and procedures employed technically appropriate and reasonable? Are the
analytic methods and procedures applied appropriately, given the state of current science as you
understand it? If yes, explain why. If not, explain why the methodology was not technically
appropriate. Provide a description of each identified strength or weakness regarding technical
appropriateness. Please distinguish between cases involving reasonable disagreement in methodology
as opposed to cases where you conclude that any analytic methods and procedures in the draft report
involve specific technical errors.
5. Are the results and conclusions of the analysis in the draft report presented in appropriate ways?
Were the conclusions in the draft report reasonably drawn? Do the conclusions follow logically from
the results of the analytic methods and procedures?
6. Are the selected figures, tables, and equations well-chosen and constructed to assist the reader in
understanding the approach, analytic methods and procedures, results, and conclusions? If yes,
explain why. If not, explain how the figures, tables, and equations could be improved to describe the
approach, analytic methods and procedures, results, and conclusions more clearly in the report.
7. Are there any other issues or concerns with the validity or scientific/technical merit of this report?
8. If you are aware of better methods, tools, and available research employed and documented
elsewhere to estimate sales, pre-buy, and other such impacts for use in policy analysis, provide
suggestions for how they might be used to improve this report and also provide the associated
references.
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3 Summary of Peer Reviewers' Comments
This section provides a summary of the peer reviewers' comments, concerns, and suggestions regarding
the Charge Questions (see Section 2), based on the individual peer reviewer's final written peer review
comments (see Section 4).
1. Does the overall presentation in the draft report describe the data and methods sufficiently to
allow the reader to form a general view of the quality and validity of the analysis performed?
All reviewers generally agreed that the overall presentation in the ERG draft report is sufficient as a
good general view of the analysis performed. Dr. Regan stated the overall presentation is exceptionally
clear, but also noted that Section 2.5.2 is challenging to understand and explained how use of the word
"expected" on page 33 is unclear.
Dr. Holguin-Veras suggested that readers without time to read the entire report would benefit from 1)
changing the current Abstract to an Executive Summary and 2) moving some report contents from the
current Conclusion to that suggested Executive Summary to present key takeaways from this study. This
reviewer also suggested that the current Introduction and the recommended Executive Summary clarify
that although the heavy-duty vehicle (HDV) regulation covers from Class 2b through Class 8, this study
focuses on Classes 6 through 8 because of data limitations.
2. Are the data sources and assumptions appropriate for the analysis conducted? If yes, explain
why. If not, describe all issues identified regarding the validity of data sources and assumptions
and provide suggestions and references for other available data that might be used to improve
this analysis. As relevant, describe how the validity of data sources and assumptions could be
more clearly described in the report.
Drs. Regan and Joann Zhou both commented that the data sources and assumptions seem appropriate
for the analysis conducted. Additionally, Dr. Regan commented that the explanation of each is clear. Dr.
Zhou suggested adding a table at the beginning of Section 3, Data and Methodology to summarize all
the data considered in the analysis and modeling and also suggested several specific clarifications related
to Table 3.
In contrast, Drs. Holguin-Veras and Christy Zhou provided detailed comments about the data and
assumptions. Dr. Holguin-Veras stated that the data sources are 1) appropriate to obtain a general idea
of the existence of pre-buy and low-buy behaviors and to quantify direct elasticities at the market level
and 2) inappropriate for analyses of class-switching and estimation of cross-elasticities. Dr. Zhou stated
the data sources and assumptions are appropriate for the analysis conducted, given data constraints the
authors had, but emphasized several caveats: 1) they are not the most ideal for this type of analysis, but
2) are still useful to understand the effect of regulation on HDV sales in the short run.
Aggregate Data for Pre-buy and Low-Buy Analysis
Dr. Christy Zhou stated that the ideal dataset contains transaction-level data or very fine registration-
level data, which are very costly to obtain. She stated the second best type of dataset are datasets that are
slightly more aggregate than this ideal dataset. For example, sales could be aggregated to make-by-class-
by-year level (better at the state level but acceptable if at the national level) or to make-by-class-by-
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buyer-type-by-year level. Dr. Zhou also acknowledged that obtaining such disaggregated datasets is not
always easy.
Dr. Holguin-Veras explained that the type of aggregate data used in the ERG draft report is unable to
identify the root behaviors at the core of transportation choice processes. However, he observed that if
the objective was exploratory analyses and only aimed at getting a general idea about pre-buy and low-
buy effects, then it may be appropriate. He strongly recommended further confirmatory research if the
objective was to use the findings to support policy-making. Dr. Holguin-Veras's comment is consistent
with Dr. Christy Zhou's caveat (see above) that the data sources and assumptions in the ERG draft
report are still useful to understand the effect of regulation on HDV sales.
Dr. Christy Zhou provided additional comments about the appropriateness of the level of class-by-
month dataset used in the ERG draft report, stating that it is appropriate with one advantage and one
shortcoming:
• The advantage is obtaining monthly data, which Dr. Zhou noted is limited to pinning down the
short-run effect, but this is the area of focus for the report.
• The shortcoming is the dataset lacks cross-sectional variation because those data are aggregated
to class (Classes 7, 8, and 9), which prevents exploiting cross-sectional variation that is typically
used in panel data (either in a difference-in-difference model, a fixed-effects model, or an event-
study model with fixed effects).
Dr. Zhou further explained that the ERG draft report instead uses temporal variation, due to constraints
from the data sources used in ERG's analyses. She believed that the approach in the ERG draft report is
appropriate to estimate the short-run effect of emission standards on sales, as specified in the main
Equation (4).
Equation 4
Dr. Christy Zhou commented that the ERG draft report does not explicitly state the assumptions
related to identifying parameters for Equation 4. She provided detailed comments about the
appropriateness of what the reviewer described as ERG's implicit assumption imposed by specifying
Equation 4. She also commented that this implicit assumption ruled out, or assumed away, any strategic
behavior HDV sellers or buyers may have done to reduce the impact of the regulation other than the
main pre-buy and low-buy effects. Dr. Zhou explained that in the case when this implicit assumption
fails the estimates of pre-buy and low-buy effects should be interpreted as conservative estimates.
Dr. Zhou commented that the validity of this implicit assumption could be improved by stating it
explicitly after introducing Equation 4 (page 58) in the ERG draft report. She also stated that the validity
of this implicit assumption could be improved by explaining the specific controls log(Xt) included in
Equation 4 and suggested including that log(Xt) explanation right after Equation 4 and before explicitly
stating this implicit assumption.
Additionally, she suggested including discussion about in which directions and in which cases the
estimates are biased when this implicit assumption fails. She encouraged laying out all possibilities in the
report and provided an example of a possible exaggeration of pre-buy and low-buy effects.
Aggregate Data to Estimate Class-Switching
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Dr. Holguin-Veras expressed concerns that aggregate data are not useful to evaluate class-switching. He
explained that aggregate data do not contain class-specific descriptors (e.g., cargo capacity and
operational costs) that could be used as independent variables for econometric models. He stated that
the consensus position established in the literature on freight mode and vehicle choice (with root
behaviors that are closely related to those in class-switching) is that using disaggregate data is, by far, the
best approach.
Aggregate Data to Estimate Cross-Elasticities
Dr. Holguin-Veras also expressed concerns about using aggregate time-series data to estimate elasticities.
He stated that aggregate time-series data can be used to estimate direct elasticities at the market level.
The reviewer also stated, however, that using aggregate data to estimate cross-elasticities is challenging in
the best of circumstances because these effects cannot be easily captured by aggregate data. This
reviewer emphasized that estimating cross-elasticities is not possible in the absence of class-specific data
about purchase prices and other descriptors of the vehicles in a class.
3. Is the description of the analytic methods and procedures clear and detailed enough to allow
the reader to develop an adequate understanding of the steps taken and assumptions made in
this analysis? If yes, explain why. If not, explain how the analytic methods and procedures
could be more clearly described in the report.
The reviewers provided a range of comments about whether the description of the analytic methods and
procedures is clear and detailed enough to allow the reader to develop an adequate understanding of the
steps taken and assumptions made in this analysis. The reviewers also provided numerous specific
comments about how the analytic methods and procedures could be more clearly described in the
report.
Overall Impressions
The range of comments about how well the ERG draft report describes the analytic methods and
procedures used in this study varied as follows:
• Dr. Holguin-Veras commented that, overall, the description of the analytic methods and
procedures is clear and detailed enough for a reader to understand what was done in this study.
He suggested, however, that including an overall summary of all the regulations (e.g., 2004, 2007,
2010) included in this study would be helpful to ensure that readers understand the major
policies implied by each of them. Dr. Holguin-Veras acknowledged that Table 3 shows the cost
estimates of each regulation but explained that including a discussion of the major emission
standards (along with how they could change the vehicle cost but also reduce the operation
costs) would be very helpful to put some of this study's results into context.
• Dr. Regan commented only about Section 3, Data and Methodology. She stated that Section 3.1
(Time Series Inputs) is exceptionally clear and observed it mainly presents information about the
data. With respect to Section 3.2 (Testing for Unit Roots), she made two main points: 1) the
execution of the augmented Dickey—Fuller (ADF) test is appropriate and clearly explained and 2)
the addition of the Kwiatkowski—Phillips—Schmidt—Shin (KPSS) test and explanation of its
meaning is also very helpful. Dr. Regan stated that Section 3.3 (Econometric Framework) and
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Section 3.4 (Leads and Lags) are very clear and illuminating (though acknowledging this
observation from the perspective of an educated reader, but not an econometrician).
• Dr. Christy Zhou stated that the description of the analytic methods and procedures is clear and
detailed enough to allow the reader to develop an adequate understanding of the steps taken and
assumptions made in this analysis. Nevertheless, she commented that the ERG draft report
could benefit from using more consistent descriptions of the model (see below).
• Dr. Joann Zhou commented that, in general terms, the ERG draft report is clearly written. She,
however, emphasized that Section 4, Results and Discussion is the exception. Dr. Zhou made
two main points about Section 4: 1) it is repetitive and unnecessarily long because Section 4
discusses results that are not statistically significant and not conceptually valid and 2) it does not
contain the model statistics—such as t-values, R2, and F—that reviewers need to judge the
validity of the results. To correct what Dr. Zhou described as unacceptable problems, she
recommended 1) limiting the discussion to results that are statistically significant and
conceptually valid and 2) adding a comprehensive appendix with the best models obtained and
the corresponding statistics (even if these models are not statistically significant and conceptually
valid). Dr. Zhou argued that those recommended solutions would lead to a more concise,
readable, and useful document that will reassure readers that the work conducted has rigor.
Descriptions of Model
Dr. Christy Zhou further explained her observations about inconsistencies in the model description that
she noticed in the report.
• First, Dr. Zhou observed the ERG draft report changes how it describes the model: in the
introduction, it describes the use of time-series methods but then in the main analysis, it
describes the use of difference-in-differences.
• Second, when the ERG draft report showed Equation 4 and the results, it appeared to Dr. Zhou
that it uses an event-study model because the presentation of /?4Pret_m is usually written as
dummies (in plural) before an event and /?5 Pret+m as dummies afterward. Dr. Zhou explained
that it was not until Table 13 that she realized the approach had one pre-dummy and one post-
dummy.
Dr. Zhou offered three recommendations regarding the description of the methodology:
• The report should not describe the model as difference-in-differences because there is no
control group (a cross-sectional control group).
• Although the authors implicitly used no-regulation years for the same class as a control to
identify /?4 and /?5, this would be better stated after Equation 4 when discussing identifying
assumptions.
• In observing that the authors do have first-difference, this should be stated when explaining the
variables in Equation 4. Right after Equation 4, the authors should explain that the left-hand-
side variable is a detrended first-difference variable of sales.
Equations
Dr. Regan commented that it was especially helpful that key equations are numbered and intermediate
(explanatory) ones are not. As described above, Dr. Christy Zhou commented again (see Charge
Question #2) that the report would benefit from explaining the specific variables that went into
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Equation 4 on page 58. She observed that in the ERG draft report that information does not appear
until page 66 in the regression table.
Dr. Christy Zhou pointed to Table 13 and commented that for the equation on page 65 it appears that
pre- and post- are "pre 2 months" and "post 2 months" and stated this made Equation 4 unclear in
comparison. This reviewer observed that the ERG draft report states on page 58 that this study's
approach grouped months together in the pre- and post-dummies. Dr. Zhou commented that the report
should clearly state the number of months grouped in the baseline estimates. Finally, Dr. Christy Zhou
provided minor suggestions for a few specific equations.
Dr. Holguin-Veras expressed concerns about the tendency to make informal statements in the ERG
draft report. He provided an example from such observations in the ERG draft report that he stated is
wrong from a mathematical point of view:
Beta represents the "change in the percent change in Y for a one-unit 'change in the percent
change' of X. The practical application of this coefficient is to consider it identical to the
elasticity, (from page 53 of ERG draft report)
Dr. Joann Zhou pointed to Section 4.2 (page 55 of the ERG draft report) and commented that it is
unclear and lacks exact identification of the dependent variable. She stated it is unclear whether the
dependent variable is the Class 7 or 8 sales or the changes in the monthly sales.
4. Are the analytic methods and procedures employed technically appropriate and reasonable?
Are the analytic methods and procedures applied appropriately, given the state of current
science as you understand it? If yes, explain why. If not, explain why the methodology was not
technically appropriate. Provide a description of each identified strength or weakness regarding
technical appropriateness. Please distinguish between cases involving reasonable disagreement
in methodology as opposed to cases where you conclude that any analytic methods and
procedures in the draft report involve specific technical errors.
All reviewers agreed that the analytic methods and procedures employed are technically appropriate and
reasonable. Dr. Christy Zhou noted the reasons were explained in her comments under Charge
Question #2 (see above). Dr. Holguin-Veras elaborated that the approach involving the use of
differencing to remove autocorrelation in the time-series data and then using OLS (ordinary least
squares) regression to conduct the analyses is a practical and acceptable technique. He also stated that it
is appropriate to use OLS to get a general idea about the existence of pre-buy and low-buy behaviors
and to estimate market-level direct elasticities.
Regarding the test for unit roots (i.e., systematic patterns that are unpredictable), Dr. Regan made two
primary points: 1) the execution of the ADF test is appropriate and clearly explained and 2) the addition
of the KPSS test and explanation of its meaning is also very helpful (also included above under Charge
Question #3). Dr. Regan also commented that the results are as expected in some cases. She noted that,
as an example, the causes for increases or decreases in purchases of Class 7 and 8 trucks (which carry
goods exclusively) are quite different from those of Class 6 vehicles (which vary considerably by
vocation).
Concerns
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Dr. Holguin-Veras emphasized that cross-elasticities may only be estimated if and only if there are
suitable data on prices and other key factors (cf. Dr. Holgum-Veras's detailed comments above under
Charge Question #2).
Dr. Joann Zhou expressed concerns about the time period selected for pre-buy in the ERG draft report.
She indicated it is not clear why 12 months was chosen as the analysis horizon (Section 3.3, page 51) in
this study and questioned whether 12 months is the standard study period for pre-buy analysis. Dr.
Joann Zhou indicated it would be helpful to provide more detailed context in the report by explaining
the typical periods considered for pre-buy and low-buy analysis.
With respect to Section 4.4.2, Dr. Regan commented that it might helpful if a sentence were added to
explain the positive beta coefficient for the 1-month period post-regulation. She guessed that these were
pre-ordered vehicles that for some reason did not arrive until the first month after the regulation was in
place. Dr. Regan believed that perhaps the sales were therefore not even governed by the new
regulations. Furthermore, regarding Section 4.4.2, she noted the 6-month period after the 2004
regulation is actually months 2 through 6, not 1 through 6.
Dr. Holguin-Veras expressed concerns about the use of "visual inspection" (page 43, last paragraph)
because that is not a formal method to assess regime shifts. He stated that if this analysis is not
supported by statistical tests, then it must be removed.
Dr. Joann Zhou questioned the approach for the oil price in the ERG draft report. More specifically,
she expressed concerns that it is not clear whether a monthly or annual oil price was used in the analysis.
The reviewer suggested that if a monthly oil price was used, then it may be helpful to conduct the
analysis using the average oil price over a few months (e.g., 4 through 5 months).
Dr. Holguin-Veras pointed to the top two lines on page 50 in the ERG draft report and stated that
using the log differences imposes a functional form with constant elasticities. He stated this is a very
strong assumption because in most cases elasticities are variable (i.e., as a function of price and other
variables).
Finally, Dr. Joann Zhou expressed concerns about whether the effect due to the recession was
considered when analyzing the impact of the 2007 regulations (pages 60 and 61) in the ERG draft
report. She noted that the recession was mentioned earlier in the ERG draft report when discussing the
sales trend. Dr. Zhou emphasized, however, that it is not clear whether the effect due to the recession
was controlled for in the analysis.
5. Are the results and conclusions of the analysis in the draft report presented in appropriate
ways? Were the conclusions in the draft report reasonably drawn? Do the conclusions follow
logically from the results of the analytic methods and procedures?
The reviewers provided a range of comments about whether the results and conclusions of the analysis
in the ERG draft report are appropriate.
• Dr. Holguin-Veras commented that the report provided, with appropriate caveats, defensible
conclusions about pre-buy and low-buy effects. In contrast, Dr. Holguin-Veras emphasized that
the conclusions presented in the report regarding class-switching and elasticities are very difficult
to defend.
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• Dr. Regan stated that the conclusions followed logically from the analysis. She commented that
the conclusion that pre-buy and low-buy behavior reduces the effectiveness of regulations, but
not by much, seems well grounded in the analysis.
• Dr. Christy Zhou commented that the results are presented appropriately but provided several
suggestions to improve the clarity of the results.
• Dr. Joann Zhou pointed out a conclusion about energy-efficient technologies in HDVs that
seems contradictive.
Estimation of Class-Switching
Dr. Holguin-Veras stated that attempting to estimate class-switching without data that characterize the
performance of the vehicles in the classes in question is simply not possible.
With respect to Section 4.5, Class Shifting, Dr. Holguin-Veras referred to comments provided under
Charge Question #2 (see above) about numerous reasons that this section of the ERG draft report is
problematic, including that the analysis/theoretical framework is inadequate and the variables used
cannot properly explain the phenomenon, among others. He emphasized that the results for class-
switching in the ERG draft report are not conceptually valid.
Finally, Dr. Holguin-Veras noted that the ERG draft report seemed to focus on the switch involving
Classes 7 and 8. He asked whether a switch involving Classes 8 and 9 was considered, or a switch
involving three or more classes, during the analyses conducted for this study.
Estimation of Elasticities
Dr. Holguin-Veras stated that the data in this study do not support a solid estimation of elasticities. He
commented further that the absolute values of the estimated elasticities (0.558 to 2.347) in the ERG
draft report are simply too high to be credible. Dr. Holguin-Veras provided a detailed explanation for
why the estimated elasticities are not credible.
Furthermore, Dr. Holguin-Veras expressed concerns that the estimated cross-elasticities are not
credible. He noted that the results for cross-elasticities, which were found to range between 0.681 and
1.712, should be smaller than the corresponding direct elasticities. He commented that the result in the
ERG draft report where cross-elasticities have the same order of magnitude as the corresponding direct
elasticities is not conceptually valid.
Under Charge Question #7 (see below), Dr. Christy Zhou recommended "toning down" Section 4.7
and explained it is not the strongest part of the ERG draft report because of all the additional
assumptions needed for computing price changes for the elasticity.
Suggestions to Improve Clarity
Dr. Christy Zhou stated that because Equation 4 is the main equation, and Figures 14 and 15 are the
main two figures, the report should at least present the regression table of Equation 4 in the same
manner that it presents Table 13 for the equation on page 65.
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Dr. Zhou expressed concerns about Figures 14 through 23 and Figures 25 through 28, which appear to
plot the coefficients of seasonality dummies on top of the pre-buy and post-buy dummies, that is,
Pi,m + Pa before the new regulation year and + /?5 after the regulation is introduced. She pointed
out that the ERG draft report only said "these models show ... (Figure 14)" without informing the
reader explicitly what was plotted in those figures. Dr. Zhou recommended stating at least once what
those figures plot, and then the rest of the figures would be self-explanatory.
Dr. Regan pointed to a statement in the ERG draft report that makes sense but would be clearer with a
second sentence:
In the case of the 2010 regulations, significant pre-buy and low-buy periods partially cancel one
another out, though the period of significance was longer and larger for the pre-buy. (from page
78 of the ERG draft report)
She suggested adding an explanation in the report that this statement means the pre-buying before
regulation and reduced purchases post-regulation are on the same scale, and together they reduce the
effectiveness of the regulation. Dr. Regan clarified that the reason for this suggested additional
explanation was that the first statement alone seems to suggest that the impacts cancel each other out
while the impacts are additive.
Dr. Holguin-Veras questioned the notation used in the equations. Overall, he expressed concerns that
the vast majority of the equations in the ERG draft report seem to be underspecified. As an example,
Dr. Holguin-Veras suggested clarifying whether alpha and beta are vectors of parameters or single
parameters. He also provided other specific comments about the notation for Equation 2 and Equation
3.
Section 4.4
Dr. Holguin-Veras provided specific comments about Section 4.4, stating it is not appropriate to use
general statements without discussion and without showing the parameter values and their statistics to
allow the reader to ensure that the results are conceptually valid and statistically significant. He also
argued against using informal statements (e.g., "Model results for Class 7 show visual evidence ...") and
emphasized that the report should support such conclusions with statistical tests.
Energy-Efficient Technologies in HDVs
Dr. Joann Zhou pointed out the following conclusion for the 2014 regulations:
This pre-buy effect is short-lived, which is intuitive as the 2014 Phase I regulations increased
capital costs, but also offered improved fuel economy, thereby reducing operating costs, (from
page 62 of the ERG draft report)
She asked whether this study found similar effects for the other regulations. She commented that if this
conclusion is true, that would imply energy-efficient technologies in HDVs could be cost-effective for
fleet operators. Dr. Zhou stated, however, that expert consensus is that HDV purchases are not fuel-
cost sensitive and observed that this study indicates that as well. Dr. Zhou stated that it seems this
conclusion on page 62 of the ERG draft report might be contradictive.
Dr. Zhou also noted that Table 3 does not show the expected cost impact of the 2014 regulations. She
again commented it would be helpful to include a brief description of each studied regulation and their
impacts on vehicle ownership cost (vehicle, operation, maintenance).
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6. Are the selected figures, tables, and equations well-chosen and constructed to assist the
reader in understanding the approach, analytic methods and procedures, results, and
conclusions? If yes, explain why. If not, explain how the figures, tables, and equations could be
improved to describe the approach, analytic methods and procedures, results, and conclusions
more clearly in the report.
The reviewers provided a range of comments about the figures, tables, and equations in the ERG draft
report. Dr. Regan stated simply that the figures, tables, and equations were all well chosen. Dr. Christy
Zhou commented that most of the tables and figures are clearly presented but recommended including
confidence intervals in Figures 14 through 23 and Figures 25 through 28 to improve the clarity of the
results. She also provided extensive comments about equations used in the ERG draft report under
other charge questions (see above under Charge Question #2 and Charge Question #3). Dr. Joann
Zhou provided specific suggestions for adding text in the report to improve the reader's ability to
understand Figure 8 and Figures 18 through 23.
Finally, Dr. Holguin-Yeras criticized the ERG draft report as being unnecessarily long, repetitive, with
illegible figures, and lacking technical details about the models discussed. He provided the following
suggestions to improve the report:
1) Increase the size of figures to improve readability.
2) Include all the statistics of the models discussed.
3) Summarize the results in tables (with all relevant statistics), instead of what this reviewer
described as ERG's copying/pasting/adjusting the text to fit the results.
4) Remove all discussions of not statistically significant and not conceptually valid results.
7. Are there any other issues or concerns with the validity or scientific/technical merit of this
report?
Two reviewers commented about the literature review in the ERG draft report with conflicting
responses. Dr. Joann Zhou generally supported the literature review, and Dr. Holguin-Veras criticized
the literature review.
• Dr. Zhou suggested including a short description of any literature available on the energy and
emissions impact of pre-buy and low-buy behaviors. Under Charge Question #8, she
commented that the literature review does a good job of summarizing the state of the art. Dr.
Zhou also provided several specific comments about statements in the ERG draft report that
seem inconsistent or incomplete.
• Dr. Holguin-Veras stated the literature review is very weak, particularly on topics directly
relevant to class-switching. This reviewer stated those concerns could be addressed by 1)
expanding the literature review to include a broader discussion of freight mode choice and
freight vehicle choice and 2) discussing implications of the chief findings from the literature
review for research conducted for the ERG draft report.
Drs. Regan and Christy Zhou had no other issues or concerns with the validity or scientific/technical
merit of the ERG draft report. Dr. Zhou, however, recommended "toning down" Section 4.7 and
explained it is not the strongest part of the ERG draft report because of all the additional assumptions
needed for computing price changes for the elasticity.
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8. If you are aware of better methods, tools, and available research employed and documented
elsewhere to estimate sales, pre-buy, and other such impacts for use in policy analysis, provide
suggestions for how they might be used to improve this report and also provide the associated
references.
Dr. Holguin-Veras concluded that disaggregate models and data are the best alternatives to study pre-
buy, low-buy, class-switching, and direct or cross-elasticities and stated this approach is consistent with
the behavior literature. He also stated that aggregate modeling cannot replace disaggregate techniques.
Dr. Holguin-Veras believed that a multimethod research effort involving qualitative and quantitative
disaggregate research techniques would produce significantly better results.
Drs. Regan and Christy Zhou had no comments about better methods or tools or other available
research. Dr. Joann Zhou was not aware of other literature not already cited in the ERG draft report.
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4 Individual Peer Reviewers' Comments
This section provides the individual peer reviewers' comments, with the peer reviewers presented in
alphabetical order.
4.1 Dr. Jose Holguin-Veras
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Jose Holguin-Veras
AFFILIATION:
William H. Hart Professor
Department of Civil and Environmental Engineering
School of Engineering
Rensselaer Polytechnic Institute
Jonsson Engineering Center
Troy, NY 12180
DATE: December 20, 2020
RESPONSE TO CHARGE QUESTIONS
1. Does the overall presentation in the draft report describe the data and methods
sufficiently to allow the reader to form a general view of the quality and validity of the
analysis performed?
The report provides a solid description of the history of EPA regulations and the theories related
to vehicle replacement, and a good general view of the work.
My interpretation of the research reported is that it is an exploratory effort to assess the feasibility
of using secondary data to detect and quantify pre-buy, low-buy, and class-switching behaviors.
Such exploratory research efforts are worthy undertakings because, although success is far from
guaranteed, if they succeed they add additional evidence that could support the policymaking
process.
I believe that EPA, USDOT, USDOE, and other regulatory agencies should undertake major
efforts to understand the behavioral responses of the freight industry to environmental/
transportation/energy policy. It is not possible to effect positive change in a system whose
behaviors are poorly understood by policy makers. I would like to urge all involved to redouble
efforts to understand freight industry behaviors. In my view, this report is a good step in this
direction.
2. Are the data sources and assumptions appropriate for the analysis conducted? If yes,
explain why. If not, describe all issues identified regarding the validity of data sources and
assumptions and provide suggestions and references for other available data that might
be used to improve this analysis. As relevant, describe how the validity of data sources and
assumptions could be more clearly described in the report.
I have various degrees of concerns about the data used to conduct the various analyses discussed
in the report. The quantitative component of the report focuses on the:
1) Identification of pre-buy and low-buy behaviors: There is consensus in the behavior
research community that aggregate data—like the one used in this report—are unable to
identify the root behaviors at the core of transportation choice processes. However, if the
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External Letter Peer Review of ERG draft report: Analysis ofHeavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Jose Holguin-Veras
objective of these analyses is exploratory, and only aimed at getting a general idea about
pre-buy and low-buy effects, the analyses may be appropriate. In contrast, if the intent is
to use the findings to support policy-making, further confirmatory research is strongly
recommended.
2) Identification of "class-switching": In this case, the use of aggregate data is of doubtful
utility to assess the extent of class switching for the simple reason that the data do not
contain class-specific descriptors, e.g., cargo capacity and operational costs, that could be
used as independent variables in the econometric models. As established by the literature
on freight mode and vehicle choice (with root behaviors that are closely related to those in
class-switching), the consensus position is that using disaggregate data is, by far, the best
approach. See: https:/ /www.nap.edu/catalog/25660/impacts-of-policy-induced-freight-
modal-shifts (National Academies of Sciences, Engineering, and Medicine. 2019. Iff/pacts of
Policy-Induced Freight Modal Shifts. Washington, DC: The National Academies Press); and
https://authors.elsevier.com/a/lcDsl3Rd3urYEY (Holguin-Veras, J., et al. 2002.
"Freight mode choice: Results from a nationwide qualitative and quantitative research
effort." Transportation Research Part A: Policy and Practice 143: 78-120).
3) Estimation of direct- and cross-elasticities: Aggregate time-series data can indeed be used
to estimate direct elasticities at the market level. However, the use of such data for the
estimation of cross-elasticities is challenging in the best of circumstances because these
effects cannot be easily captured by aggregate data. Moreover, in the absence of class-
specific data about purchase prices and other descriptors of the vehicles in a class,
estimating cross-elasticities is not possible.
In summary, the data sources are:
1) Appropriate to obtain a general idea of the existence of pre-buy and low-buy behaviors,
and to quantify direct elasticities at the market level; and
2) Inappropriate for analyses of class-switching and estimation of cross-elasticities.
Additional comments:
1) Page 15, Section 2.3.1: The trucking companies that exercise pre-buy, low-buy, and class-
switching are not in competitive markets. In these markets, rates are equal to marginal
costs, and the carriers do not recover the fixed costs, and obviously cannot purchase new
trucks. The companies that participate in pre-buy, low-buy, and class-switching behaviors
are those that operate in markets where the companies have some pricing power. Owner-
operators, intermodal-truck operators, and other small companies are not likely to do pre-
buy, low-buy, or class-switching.
2) Page 16, Section 2.3.4: It should be made clear that pre-buy, low-buy, and class-switching
(together with do-nothing) are alternative choices for company managers.
3. Is the description of the analytic methods and procedures clear and detailed enough to
allow the reader to develop an adequate understanding of the steps taken and
assumptions made in this analysis? If yes, explain why. If not, explain how the analytic
methods and procedures could be more clearly described in the report.
In general terms the report is clearly written.
22

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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis ofHeavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Jose Holguin-Veras
1) Page 43, last paragraph: "Visual inspection" is not a formal method to assess regime shifts.
If not supported by statistical tests, the analysis must be removed.
2) Page 50, top two lines: Using the log differences imposes a functional form with constant
elasticities. This is a very strong assumption as in most cases elasticities are variable, i.e., as
a function of price and other variables.
5. Are the results and conclusions of the analysis in the draft report presented in
appropriate ways? Were the conclusions in the draft report reasonably drawn? Do the
conclusions follow logically from the results of the analytic methods and procedures?
My conclusion is that the report provides, with appropriate caveats, defensible conclusions about
pre-buy and low-buy effects. In contrast, the conclusions reached regarding class-switching and
elasticities are very difficult to defend. As made clear in the literature, the estimation of
econometric models that capture the essence of freight mode or vehicle choice is a complex
undertaking in the best of circumstances. Attempting to estimate class-switching without data that
characterize the performance of the vehicles in the classes in question, is simply not possible. My
conclusion is that the data do not support a solid estimation of elasticities.
Moreover, the absolute values of the estimated elasticities (0.558 to 2.347) are simply too high to
be credible. To explain why I believe this is the case, it is useful to mention that there are two
primary mechanisms that could increase demand for truck services: (1) changes in the commodity
flows between shippers and receivers, and (2) changes in the supply chains that transport these
commodity flows.
It should be kept in mind that freight transportation activity is derived from the commodity flows
traded among other economic sectors. Carriers do not create the demand, they simply transport
the cargo. As a result, carriers would only increase fleet sizes if they are confident there will be a
sustained increase in the demand for their services. While it is true that drastic reductions in
transportation costs could indeed transform the structure of the economy and the associated
commodity flows, this only happens in massive projects such as the Erie Canal, the
transcontinental railroads, interstate highway system, or the UK-EU tunnel.
However, although commodity flows do not change much in response to small changes in
transportation costs, supply chains are another matter. In response to changes in transportation
costs of some importance, supply chains could react in multiple ways; from a complete
restructuring of the network, to changes in shipment sizes, frequency of shipments, and the type
of vehicles used. The latter changes (underlined) could be indeed triggered by changes in
transportation costs. The reason is that businesses always try to minimize the total logistic costs,
i.e., the summation of cost of transporting and storing the supplies. If transportation costs are
low, in relation to the storage cost, the best policy is to reduce shipment size and increase the
frequency of shipments (allowing the business to save storage costs). If transportation costs are
high, the opposite happens. These tradeoffs are at the core of the Economic Order Quantity
(EOQ) model. The applications of the EOO model clearly indicate that the elasticity of the
frequency of shipments (which is what determines the need for trucks) is inelastic.
24

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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/QTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Jose Holguin-Veras
As an example, the table below from Holguin-Veras and Sanchez-Diaz (2016), shows the effect of
an environmental charge of $5.86 for each delivery to commercial receivers of supplies. The table
below shows the optimal number of deliveries that minimizes the total logistic costs considering
the value of the space at the bottom of the third and fourth columns. As shown, an environmental
charge of 1:5.86 increases the shipping cost from $30.00 to $35.86, i.e., 23.44%; and reduces the
number of deliveries/day (or freight trip attraction) from 2.332 to 2.099, i.e., 9.99%. These results
indicate that the direct elasticity of the number of deliveries is -0.18. If the number of deliveries is
inelastic to an increase in transportation cost of 25%, it is extremely unlikely that a smaller
increase in the purchase costs of trucks would lead to a more than proportional increase in the
number of trucks purchased.
Tabic 1
Optimal ordering policies.
Description
Classic EOQ
Space-allocation EOQ (SA-EOQ)
SA-EOQ with receiver charge
Parameters

7tp ft/ft2/hour)
0.0000
0.8163
0.8163
^(fe/rt3)
0.1667
0.1667
0.1667
do (S/frVhour)
0.0204
0.0204
0.0204
Q: Order cost ($/delivery)
$5.00
$5.00
$5.00
Cr: Transport cost($/delivery)
$20.00
$20.00
$20.00
t: Receiver charge (S/delivery)
-
-
$5.86
C,; Inventory cost (S/ft3/hour)
$0.20
$0.20
$0.20
Results

Q: Optimal order size (ft3)
56.469
36.754
40.835
T: Optimal cycle time (hours)
15.811
10291
11.434
A,: Storage area (ft2)
9.412
6.126
6.806
Freight trip attraction. FTA, (trips/day)
1.518
2.332
2.099
(citation: Holguin-Veras, J. and I. Sanchez-Diaz. 2016. "Freight Demand Management and the Potential of
Receiver-Led Consolidation Programs." Transportation Research Part A 84: 109-130.)
.Elasticities larger than one imply that changes in the purchase prices of trucks (a tiny proportion
of the cost of production of the goods transported) would translate into more-than-proportional
changes in the numbers of trucks purchased. These results do not seem sensible, because the
change in purchase prices is too small to have any influence in the demand for truck
transportation.
Equally concerning are the results for cross-elasticities, which were found to range between 0.681
and 1.712. As amply established in the transportation literature on cross-elasticities, relative to
each other, cross-elasticities ought to be smaller than the corresponding direct elasticities. The
reason is simple: the cross-effect is less potent than the effect of the "own" price. In this case,
however, they have the same order of magnitude. Regrettably, I only found one paper on vehicle
choice that reported the cross-elasticities (Holguin-Veras 2002). The table below (the final results
are surrounded by a blue rectangle) shows that, as expected, the cross-elasticities are generally
much smaller than direct elasticities. The exception is cross-elasticity between the price of pickups
(P) and the demand for (mid-size) trucks (T), i.e., 0.067, that is larger in absolute value than the
direct elasticity (-0.036) and that, as noted in the 2002 paper, is an estimation error.
25

Elmlicidt* of etui in choice of
Variable i* w utility liuicixm of
f
T S

Simple .tverupe of individual elasticities
Pickups < /»}
-0.027
0.095 0.007
Trucks (T)
0 087
-0.079 0.007
Semitrailers (5)
12,153
0.549 -4.121

ibi Weighted average of individual elasticities
Pickup* (P)
-0.036
0.067 0.007
Truck* (D
0,0*2
-0 065 0.007
Sequtnulers (5)
0,015
0,120 -0.373
(citation: Holguin-Veras, J. 2002. "Revealed
Preference Analysis of Commercial Vehicle
Choice Process." Journal of Transportation
Engineering 128(4): 336-346).
Needless to say, the authors' result in the ERG draft report where cross-elasticities have the same
order of magnitude as the corresponding direct elasticities is not conceptually valid.
Additional comments:
1)
Section 4.4:
a) The authors should not use statements such as "the coefficients for other explanatory
variables are robust to model specification... and have been omitted in favor of
discussion ..This is not appropriate. To start, what is the meaning of "robust"?
They must show the parameter values, and their statistics, to ensure that they are
conceptually valid and statistically significant.
Statements such as "Model results for Class 7 show visual evidence..are too
informal for a report of this nature. The authors need to support such conclusions
with statistical tests.
Figures are too small.
Figure 21, by the authors' admission, shows results that are not statistically significant.
In cases like that, it is better to simply add a note indicating that these results were not
significant.
b)
c)
d)
2)
3)
Notation used in equations:
a) The vast majority of the equations in the report seem to be under-specified. Are alpha
and beta vectors of parameters? Or single parameters? Please clarify.
b) In Equation 3, is betal constant for all months t?
c) Is the variable "Month" in Equation 2, a time index that start with 1... until the
number of the last time period? Or is it a set of binary variables for each month?
Section 4.5: Class Shifting
a) As explained in my answer to Charge Question #2, this section is problematic for
numerous reasons, the analysis/theory framework is inadequate; the variables used
cannot properly explain the phenomenon, among others. Moreover, the results are not
conceptually valid.
b) The report seems to focus on the switch involving classes 7 and 8. Was a switch
involving classes 8 and 9 considered? Or a switch involving three or more classes?
26

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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
4.3 Dr. Yichen (Christy) Zhou
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales Impacts due to New
Regulation
NAME: Dr. Yichen (Christy) Zhou
AFFILIATION:
Assistant Professor of Economics
Clemson University
320M Wilbur O. and Ann Powers Hall
Clemson, SC 29634
DATE: November 29, 2020
RESPONSE TO CHARGE QUESTIONS
1. Does the overall presentation in the draft report describe the data and methods sufficiently to allow the
reader to form a general view of the quality and validity of the analysis performed?
The overall presentation in the draft report does a sufficient job of describing the data and methods and allowing the
reader to form a general view of the quality and the validity of the analysis performed.
The goal of the report is to analyze how new emission standards for heavy-duty vehicle (HDV) affect HDV sales in
the short run immediately before and after the time when the new standards went into effect. The analysis includes
three waves of new regulations that went into effect in 2007, 2010, and 2014 that target PM and NOx emissions rates.
All my comments under the subsequent charge questions evaluate how well the authors achieve this main goal in
various aspects.
2. Are the data sources and assumptions appropriate for the analysis conducted? If yes, explain why. If not,
describe all issues identified regarding the validity of data sources and assumptions and provide
suggestions and references for other available data that might be used to improve this analysis. As relevant,
describe how the validity of data sources and assumptions could be more clearly described in the report.
The data sources and assumptions are appropriate for the analysis conducted, given the constraints that the authors
have in terms of data access; they are not the most ideal (perfect) for the analysis but the data sets and the
assumptions are still useful to understand the effect of regulation on HDV sales in the short run.
The ideal dataset to answer this question is transaction-level data or very-fine registration level data, which are very
costly to obtain. The second-best dataset to answer this question are datasets that are slightly more aggregate than the
above one. For example, sales could be aggregated to make-by-class-by-year level (better at the state level but okay if
at the national level), or to make-by-class-by-buyer-type-by-year level. From my own experience, it is not always easy
to obtain datasets at this level.
The dataset the authors end up with is at the level of class-by-month. It is appropriate with one shortcoming and one
advantage. The advantage is the authors obtain monthly data, which is limited to pin down the short-run effect.
Getting the monthly data is an important and successful first step for the authors. The shortcoming is the data set has
a lack of cross-sectional variation since they are aggregated to class (class 7, 8, and 9) which prevents the authors to
exploit cross-sectional variation that is typically used in panel data (either in a Difference-in-Difference model, or a
fixed-effect model, or an event-study model with fixed effects). Because of the constraint of the data sources, the
authors choose to exploit temporal variation, which I think is appropriate to estimate the short-run effect of emission
standards on sales, as specified in their main Equation (4).
The authors did not explicitly state the assumptions that allow them to identify the parameters /?4 and /?5 (and the
jump in the parameters before and after the introduction of the new standards). However, given the authors know
how to specify Equation (4), the authors implicitly assume the following — "the factors that make sales to change
from the months t — m leading up to the standards and the months t + m immediately after the standards are (i)
solely due to the introduction of new standards and (ii) uncorrelated to other potential confounding factors, after
removing factors from the seasonality and covariates." Aka, conditional seasonality and covariates that the authors
control, the "pre birf' in t — m and "low birf' in t + m are not driven by factors other than the new regulation.
This is usually a weak assumption to defend if the data is more disaggregated (so that the authors can use fixed effects
to remove unobservables constant within each cross-sectional unit). Given the lack of cross-sectional variation, this
31

-------
U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales Impacts due to New
Regulation
NAME: Dr. Yichen (Christy) Zhou
assumption becomes a slightly stronger assumption. To make the identifying assumption appropriate, the authors
further include a few covariates to control for factors correlated to potential demand and supply shifters: GDP, Brent
oil, total imports and exports, and consumer sentiment. The authors have done the best they can to control for
potential bias given the data constraint.
In the case when the assumption fails, it is more likely that the authors underestimate the effects of "pre buy" and
"low buy" rather than exaggerate the effects. For example, the empirical strategy laid out in Equation (4) will pick up
all the increases in the sales in the aftermath of the new regulation and the authors find a negative effect. For one
example, to mitigate the impact, in months after the new regulation, buyers can still purchase older model years
remaining in the stock, if the carmakers still have any. In this case, the "low buy" effect is underestimated. For
another example, to mitigate the impact after the regulation, sellers can manipulate the price point. Carmakers can
lower the price (what I mean is lower the mark-up rate so that the price paid in the market is lower than the price
point if the carmakers had kept the same mark-up rate). The lower price would lead to more sales, in which case, the
"low buy" effect is underestimated. Or, in the third case, to reduce the within-make competition in t — m versus t +
m, the carmakers can slightly increase prices in t — m so that their sales in t + m will not decrease too much (of
course, carmakers have to balance potential gain in t + m to trade off the loss in t — rri). If this happens, the "pre
buy" is underestimated.
In summary, the identifying assumption (that the authors implicitly impose by specifying Equation (4)) rules out /
assumes away any strategic behavior HDV sellers or buyers may have done to reduce the impact of the regulation
other than the main channel "pre buy" and "low buy". In the worst case, when the identifying assumption falls apart,
we should interpret the estimates of "pre buy" and 'low buy" as conservative estimates.
To improve the validity of the assumption, first, I think the authors can benefit from stating it explicitly after
introducing Equation (4) on page 58. Also, as I will mention under Charge Questions #3 and #4, after introducing
Equation (4), the authors would benefit from stating the specific controls log(Xt) included in the Equation, which
does not appear until page 66. The authors should explain log(Xt) right after Equation (4) before explicitly laying out
the identifying assumption. Without introducing which variables go into the Equation, it will be unclear what /?4 and
/?5 pick up. Third, the authors should discuss in which directions and in which cases their estimates are biased when
their assumption does not hold up. I think the estimates can be conservative for the reasons that I stated above if
their assumption does not hold up. The authors should lay out all possibilities that they believe might be possible. For
example, if the authors consider it is also possible that unobservables can exaggerate the "pre buy" and "low buy"
effects (rather than dampen the effects), they should lay out the reasons and explain potential omitted variables and
channels that make that happen.
3. Is the description of the analytic methods and procedures clear and detailed enough to allow the reader to
develop an adequate understanding of the steps taken and assumptions made in this analysis? If yes,
explain why. If not, explain how the analytic methods and procedures could be more clearly described in the
report.
The description of the analytic methods and procedures is clear and detailed enough to allow the readers to develop
an adequate understanding of the steps taken and assumptions made in this analysis.
First, I have a few minor suggestions on a few specific equations.
As I stated under Charge Question #2, the authors can benefit by explaining specific variables that go into Equation
(4) on page 58. In the current version, that does not appear until page 66 in the regression table.
Also, the month variable is usually called the "month-of-the-year dummy variables" in a regression like this. Stating
montht as a month will confuse readers who imagine the month as 1,2,.. .12; 13,14 24; 25..., which is typical when
you have more than a year.
The authors may want to call AlogClassit as AlogSalest. Usually, the class is a dummy, so readers will be confused.
What the authors mean are sales. Given that the authors estimate Equation (4) separately for each class, AlogSalest
is sufficient and there is no need for AlogSalesit. The authors should state Equation (4) is estimated separately for
32

-------
U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales Impacts due to New
Regulation
NAME: Dr. Yichen (Christy) Zhou
each class before getting into Section 4.4.1; otherwise, readers will wonder why the authors do not have a dummy for
each class on the right-hand-side.
Similarly, for the Equation on page 65, it is better to call 'log Class 8" as "sales". It can be AlogSalese t or another
way depending on the authors' preference. Also, it may be helpful to add an equation number.
In Table 13 for the Equation laid out on page 65, it appears that pre and post are "pre 2 months" and "post 2
months" which makes Equation (4) unclear in comparison. The authors stated on page 58 that they group months
together in the pre and post dummies. The authors should clearly state the number of months they group in their
baseline estimates. (If they do robustness and adjust the bandwidth, they can explain that later.)
Second, the authors can benefit from using more consistent descriptions. The authors change how they describe their
model: in the introduction, the authors say they use time-series methods, then in the main analysis, the authors say
they use difference-in-differences. Then when the authors show the Equation and the results, it appears to me the
authors use an event-study model since the presentation of /?4Pret_m usually are written as dummies (in plural)
before an event and /?5Pret+m as dummies afterwards. It is not until Table 13, where I realize the authors have one
pre dummy and one post dummy. Regarding the description of the methodology, (i) the authors should not call the
model as diff-in-diff since there is no control group (a cross-sectional control group); the authors do implicitly use no-
regulation years for the same class as a control to identify /?4 and /?5 and the authors would better state that after
Equation (4) when discussing identifying assumptions. The authors do have first-difference, so when explaining
variables in Equation (4) right after Equation (4), the authors should tell/remind us the left-hand-side variable is a
detrended first-difference variable of sales.
4. Are the analytic methods and procedures employed technically appropriate and reasonable? Are the
analytic methods and procedures applied appropriately, given the state of current science as you understand
it? If yes, explain why. If not, explain why the methodology was not technically appropriate. Provide a
description of each identified strength or weakness regarding technical appropriateness. Please distinguish
between cases involving reasonable disagreement in methodology as opposed to cases where you conclude
that any analytic methods and procedures in the draft report involve specific technical errors.
The analytic methods and procedures are appropriate and reasonable. As for the reason, I have stated that under
Charge Question #2 as well.
5. Are the results and conclusions of the analysis in the draft report presented in appropriate ways? Were the
conclusions in the draft report reasonably drawn? Do the conclusions follow logically from the results of the
analytic methods and procedures?
The results are presented appropriately. The authors can improve the clarity of the results as follows:
First, for Figures 14-23, and Figures 25-28, it appears the authors plot the coefficients of seasonality dummies on top
of the "pre buy" and "post buy" dummies, aka /ll m + /?4 before the new regulation year, and /ll m + /?5 after the
regulation is introduced. However, the authors only say "these models show ... (Figure 14)" without informing me
explicitly what are plotted in those figures. I recommend the authors state what they plot at least once. Then the rest
of the figures would be self-explanatory.
Second, given Equation (4) is the main equation, and Figures 14-15 are the main two figures, the authors should at
least present the regression table of Equation (4) just like they have presented Table 13 for the Equation on page 65.
6. Are the selected figures, tables, and equations well-chosen and constructed to assist the reader in
understanding the approach, analytic methods and procedures, results, and conclusions? If yes, explain
why. If not, explain how the figures, tables, and equations could be improved to describe the approach,
analytic methods and procedures, results, and conclusions more clearly in the report.
Most tables and figures are clearly presented. The authors can improve the clarity of the results as follows:
Given that Figures 14-23, and Figures 25-28, plot coefficients, these figures should include confidence intervals.
7. Are there any other issues or concerns with the validity or scientific/technical merit of this report?
No further serious issues.
33

-------
U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales Impacts due to New
Regulation
NAME: Dr. Yichen (Christy) Zhou
Section 4.7 is not the strongest part of the report because of all the additional assumptions needed for computing
price changes for the elasticity. It is reasonable given that Section 4.4 to 4.6 are the main results. I recommend toning
down Section 4.7 a little bit as potential implications or the suggestive outcome or something along that line.
8. If you are aware of better methods, tools, and available research employed and documented elsewhere to
estimate sales, pre-buy, and other such impacts for use in policy analysis, provide suggestions for how they
might be used to improve this report and also provide the associated references.
No further comments.
34

-------
U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
4.4 Dr. Yan (Joann) Zhou
External Letter Peer Review of ERG draft report: Analysis of Heavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Yan (Joann) Zhou
AFFILIATION:
Group Leader, Mobility and Deployment
Systems Assessment Center
Energy Systems Division
Argonne National Laboratory
9700 S. Cass Ave, Building 362, E337
Lemont, IL 60439
DATE: November 25, 2020
RESPONSE TO CHARGE QUESTIONS
1.	Does the overall presentation in the draft report describe the data and methods
sufficiently to allow the reader to form a general view of the quality and validity of the
analysis performed?
Yes. However, I would suggest changing the "abstract" to "Executive Summary" and move some
of the contents from the "Conclusions" to "Summary". For people who do not have time to read
the 80-page report, they can still comprehend a full picture of the data and methodologies used, as
well as the key take-ways from this study.
Secondly, I would suggest clarifying in the "Introduction" and "Summary" that although the
HDV regulation covers from class 2b to class 8, this study focus on class 6-8 due to data
limitations.
2.	Are the data sources and assumptions appropriate for the analysis conducted? If yes,
explain why. If not, describe all issues identified regarding the validity of data sources and
assumptions and provide suggestions and references for other available data that might
be used to improve this analysis. As relevant, describe how the validity of data sources and
assumptions could be more clearly described in the report.
Overall, the data sources and assumptions are appropriate.
On the vehicle sales, have you compared the sales data with registration data to see whether they
are aligned (after removing the time gap between sales and registration)?
In the beginning of Section 3 Data and Methodology, I would suggest adding a table to show all
the data considered in the analysis and modeling. The suggested table could be similar to the
following (as an example).
Variable
Models
(in which the
data was used)
Unit
Source
Notes





Table 3 and Section 4.7: More description about how these costs were estimated and used in this
analysis would be appreciated. My understanding is that some of the cost estimates are for vehicle
35

-------
U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis ofHeavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Yan (Joann) Zhou
Page 60-61: Was the effect due to recession considered when analyzing the impact of 2007
regulations? The recession was mentioned earlier when discussing the sales trend. However, it was
not clear whether that was controlled in the analysis.
For the oil price: Did you use monthly or annual oil price in the analysis? If monthly, have you
tried using the average oil price over a few months (4-5 months for example)?
5.	Are the results and conclusions of the analysis in the draft report presented in
appropriate ways? Were the conclusions in the draft report reasonably drawn? Do the
conclusions follow logically from the results of the analytic methods and procedures?
Several regulations affect the vehicle cost and operation cost. I found the following conclusion
interesting but only for the 2014 regulations. First, Table 3 did not show the expected cost impact
of the 2014 regulations. Secondly, again, a brief description of each studied regulation and their
impacts on vehicle ownership cost (vehicle, operation, maintenance) would be helpful. Third, did
you find similar tilings for other regulations? Fourth, if this conclusion is true, then the take-way
for audiences like DOE would be energy-efficient technologies in HDV could be cost-effective
for fleet operators. However, we know, also indicated in this study, that HDV purchases are not
fuel cost sensitive. It seems to be this conclusion might be contradictive.
Page 62: Thispre-bity effect is short-lived, which is intuitive as the 2014 Phase I regulations increased capital
costs, but also offered improved^fuel economy, thereby reducing operating costs.
6.	Are the selected figures, tables, and equations well-chosen and constructed to assist the
reader in understanding the approach, analytic methods and procedures, results, and
conclusions? If yes, explain why. If not, explain how the figures, tables, and equations
could be improved to describe the approach, analytic methods and procedures, results,
and conclusions more clearly in the report.
Page 44/Figure 8: Could you add an example to show how to read the chart, such as the "regime
shifts in the PPI-Trucks corresponding to the 2007 and 2010 enforcement periods"?
Figure 18-23: Please add discussions about whether the analysis shows one behavior is greater
than the other. For example, does Figure 18 mean there was more "low buy" than "pre buy"?
except Figure 18.
7.	Are there any other issues or concerns with the validity or scientific/technical merit of
this report?
Page 11/17: Why would buyers move up in vehicle class if higher class is more expensive? Then
on page 17, it actually states an opposite trend.
"In instances where buyers move up in vehicle class... " (page 11)
"For exartple, if the price of class 8 HDl rs increases, tmckingfrms may substitute some class 7 HDl rs if they
are now relatively less costly to use in providing trucking services. " (page 17)
Section 2 Literature Review: Are there any literature on the energy and emissions impact of pre-
buy and low-buy behaviors? If yes, could you add a short description of them?
Page 24: Did the IEA study which was conducted 13 years later (since 2004) conclude faster
decoupling?
37

-------
U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
External Letter Peer Review of ERG draft report: Analysis ofHeavy-Duty Vehicle Sales
Impacts due to New Regulation
NAME: Dr. Yan (Joann) Zhou
"International Energy Agency (2017) and OECD (2004), for instance, suggest that a decoupling between
GDP/ economic activity and trucking sector or freight transport activity might be taking place (or has taken place)
in the United States, as the U.S. has seen a shift from goods production to services. "
Figure 4: Font size is too small to see
8. If you are aware of better methods, tools, and available research employed and
documented elsewhere to estimate sales, pre-buy, and other such impacts for use in policy
analysis, provide suggestions for how they might be used to improve this report and also
provide the associated references.
I think the literature review did a good job summarizing the state of the art. I am not aware of
other documents, which are not cited here.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
5 Peer Reviewers' Curricula Vitae
5.1 Dr. Jose Holgum-Veras
JOSE HOLGON-VERAS
6 CfaiBtine Ct.
Clifton Part NY 12065
Email, jhv3tpi.edu
Home phone: 518-348-3845
Work phone; 518-276-6221
Fax:	518-276-4833
1. EDUCATION
~	Ph. D., University of Texas at Austin, 1996
~	Magister Scientiarum, Universidad Central de Venezuela, 1984
~	Civil Eaparar, Magna Cum Laude, Universidad Autonama de Santo Domingo, 1981
Fellowships, awards, and distinctions
~	Runner up to the Jack Meredith Best Paper Award from the Journal of Operations
Management for the most impactful paper during the 2012-2016 period to the paper "On the
unique features of post-disaster humanitarian logistics"
~	Finalist of INFORMS' Edelman Award 2017.
~	Elected Fellow of the American Society of Civil Engineers. 2014
~	Recipient to the 2013 White House Transportation of Change Award.
~	Recipient of the 2013 School of Engineering Reseat ch Award. Rensselaer Polytechnic Inst
~	Honorary Professor'
c Daltang Jtaotong University, August IS. 2910
c Beijing University of Technology (Beijing Overseas Talent Professor), 2016.
o Umversidad del Pacific©, Lima, Peru, August 16L" 2018
o Universidad National de Colombia. August 24tk, 20! 8
c Universidad del Vale, Apiil 8fts 2019
~	Recipient of the 2007 University Transportation Research Center Best Paper Award for the
paper entitled "An Investigation on the Effectiveness of Joint Receiver-Carrier Policies to
Increase Truck Tiaffic in the Off-peak Hours™ (Parts I and II)., together with Michael Silas.
John Polimeni, and Brenda Cruz.
~	Recipient of the 2006 Robert E. Kerker Research Award in recognition of Excellence in
Research of Special Importance to Practitioners and Scholars of Public Administration and
Policy in Xe<»v York State.
~	Recipient of the 20C6 School of Engineenne Research Award, Rensselaer Pah technic Inst
~	Recipient of the CAREER Award from the National Science Foundation (2001)
~	Recipient of a Proclamation from the City Council of New York honoring his research
accomplishments and contributions to local communities (April 17, 2001).
~	Recipient of the Milton Pikarsky Manorial Award, 1996 (Council of University
Transportation Centers).
~	Magna Cum Laude i,Civil Engineering), Universidad Autonoma de Santo Domingo, IPS 1
Fellow of:
~	American Society of Civil Engineers. 2014
~	State Academy for Public Administration. 2006.
~	International Road Federation (IRFl "S91
~	Japanese International Cooperation Agency (JICA), 1989
~	Organization of American States (OAS), 1982-1984
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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PEER REVIEW SUMMARY REPORT - Draft Final
Editorial Boards, Conference Chairmanship, Leadership Positions
~	Founding President of the Pan-American Society of Transportation Research (PANAMSTR),
(201S-presentj
~	Chairman of the Pan-American Advanced Studies Institute on Sustainable Urban Freight
Systems, Colombia August 1-14 2014
~	President of the Scientific Committee of the Pan-American Conference of Transportation and
Traffic Engineering (2010-presentj
~	Elected Member of the Council of the Association for European Transport (2005-2011)
~	Vice President the Scientific Committee of the Pan-American Transportation and Traffic
Engineering Conferences (2005-2010)
~	Chairman of the XIII Pan American Conference of Traffic and Transportation Engineering..
Crowne Plaza Albany, September 27-29 2004
~	Chairman of the Pan-American Advanced Studies Institute on Transportation Sciences
(PASI-TS), Toluca and Queretaro; Mexico July 24-August 7th 2005
~	Member of the Executive Board of the City University of New York's University
Transportation Research Center (since 2002).
~	Member of the Advisory Board of the University of Vermont's Transportation Center (2006-
291C).
~	Member of the Conference Program Committee of the National Urban Freight Conference
^February lst-3rd, 2006, Long Beach California)
~	Member of the Organizing Committee of the Sri International Conference on City Logistics
(Madeira, Portugal 2003)
~	Member of the Organizing Committee of the 4th International Conference on City Logistics
(Lankawi, Malaysia 2005)
~	Associate Editor of Transportation for Network and Spatial Economics {2003-present)
~	Associate Editor of Transportation Research. Part A: Folic}' and Practice (since 2008).
~	Chair of the Review Committee (Editor) for the Freight Transportation Planning and
Logistics Committee (Transportation Research Board) (2001-2007)
Major public sector (pro-bono) appointments
~	USDOT's National Freight Advisory Committee (2012-2016)
~	Member of the National Academy of Sciences' Disaster Research Rour.dtable (2011-2,01.5)
~	Member of the Beard of the New York State Thruway Authority (2010-2018)
~	National Academy of Sciences' Transportation Research Board's Review Committee for the
Truck Size and Weight, study requested by Congress
~	Member of the Federal Emergency Management Agency's Core Group on Community
Engagement (June 2011-present)
~	Member of the Review Panel for the Cross-Westchester Expressway project (May 2011-
2012)
~	Member of the Advisory Panel for the NY-NJ-CT-PA Regional Catastrophic Plannine Group
(March 2010-2012)
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
2. AREAS OF PROFICIENCY
Humanitarian Logistics
~ He is, in. charge^ of one of the largest research groups on humanitarian logistics that
specializes ia the integration of social science and engineering research, and the integration
of field work, characterization, and mathematical modeling of the various aspects of the
relief efforts. This group has conducted path breaking field research on Katrina, Haiti, Japan,
Jophn and many other disasters.
Freight transportation modeling and economics
~ Recipient of two national awards: (a) (he Milton, Pikarsky Memorial Award, from the
Council ef University Transportation Centers (CUTC) in 1996; and ib) the CAREER Award
from the National Science Foundation in 2001, for his contributions to intermodal
transportation modeling and transportation economics. Leader in the area of freight behavior,
and freight demand modeling.
Transportation Planning Intelligent Transportation Systems
~ Proficient in the use of demand models for policy analysis and transportation system
planning. Major role in. three national transportation plans and fifteen major urban and
regional, transportation studies. Highly proficient in the use of advanced modeling
techniques, ranging from Random Utility Models, to Land-Use transportation models, and
traditional. UTPS approaches, including network applications to transportation problems.
Transportation Economics
~ Strong background in transportation economics, having performed cutting edge research on
road pricing (optimal tolls, behavioral responses from both passengers and freight,
development of comprehensive policies), the economic evaluation of more than a. thousand
hundred transportation projects, including land use projects, transit projects, freeways, too
suburban and interstate highways, port projects, tail projects, and rural roads. Has conducted
advanced research on price differentiation theory and congestion pricing application to
container terminals. Has been, consultant for the major international companies and
international organizations.
Infrastructure Planning
~ Strong background in the areas gfi highway design, demand forecasting and economic
analysis of urban highways and rural roads. Participated in planning and design of three
freeways, two intercity roads, two hundred rural roads, airports, rail and maritime projects m
a number of different countries. Internationa! consultant in Jhe area of Infrastructure Planning
and Modeling. Implemented Pavement Management Systems.
3. EXPERIENCE
Academic
~ William H. Hart Professor (July 2010-}, Rensselaer Polytechnic Institute
~ Professor of Civil and Environmental Engineering (since My 2006), Rensselaer Polytechnic
Institute (joint with Decision Sciences and Engineering Systems)
+ Associate Professor of Civil and Environmental Engineering (2002-2006), Rensselaer
Polvtechnic Institute
~ Associate Professor of Civil Engineering (2001-2002), The City College of New York.
~ Assistant Professor of Civil Engineering (1998-2001). The City College of New York.
J 3
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
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~ Visiting Assistant Professor of Civil Engineering, The City College of New York {1997).
~ Visiting Professor, California Polytechnic State University. Sail Luis Obispo 11996-1997).
~ Adjunct Professor of Transportation Economics and Transportation Planning 11984-1991),
and Port Engineering 11989-1991). Universidad Autonoma de Santo Domingo.
~ Lecturer of Urban Transportation Planning at fie Graduate Course in Transportation
Planning., Universidad Autonoma de Santo Domingo 1985-1986.
Leadership
~ Director of the VKEF Center of Excellence on Sustainable Urban Freight Systems (Since
January 2013-current)
~ Director of the Center for Infrastructure, Transportation, and the Environment (Since January
2010-cuirent)
~ Chair ofthe Rensselaer Faculty (May 2014 - April 2015)
~ President of the Faculty Senate (May 2013 - Apnl 2014)
~ Vice-President ofthe Faculty Senate (February 2012 - April 2013)
~ Acting Head, Department of Civil and Environmental Engineering (Jan. 2008-July 2009)
~ Deputy Director of the Transportation Planning Directorate, Ministry of Public Works,
October 1986-August 1987.
~ Academic Coordinator of the Graduate Course in Transportation Planning, Universidad
Autonoma de Santo Domingo 1985-1986.
~ Head, Transportation Planning Department, Ministry of Public Works, 1984-1986.
~ Head ofthe Special Studies Unit, Ministry of Public Works, Jan. 1981-Aug, 1984.
4. PUBLICATIONS (AN '**" MARKS PAPERS WITH STUDENTS AS LEAD AUTHORS)
Refereed journal publications (published)
1. Holguin-Veras, J., Johanna Amaya leal Ivan Sanchez-Diaz. Michael Browne, Jeffrey
Wojtov.icz, State of the art and practice of urban freight management Part II: Financial
approaches, logistics, and demand management Transportation Research Part A: Policy and
Practice, 20!i. https://doiora/l0.101 S/ltta-lO 18.10.036
2. Holguin-Veras, J., Johanna Amaya Lea!, Ivan Sanchez-Diaz, Michael Browne, Jeffrey
Wojtov.'icz, State of the art and practice of urban freight management: Part I: Infrastructure,
vehicie-relared, and traffic operations. Transportation Research Part A: Policy and Practice, 2018.
fattps'doLore/lO. 1016/i tra.2018.10.037
3. Castillo, V., Ivan Serrano, Luis F Macea, Jose Holgum-Veras, Discrete choice approach for
assessing deprivation cost in humanitarian relief operations. Sodo-Economic Plamune Sciences.
63.33-46.20 IS. http5:>/doi.or.g-10.1016.'i.seps2017.06.004
4. Yuslumito, W.. Jose Holguin-Veras, Tomas Gellona, Finn's efficiency and the feasibility' of
incentives for flexnme adoption: a preliminary anaivsis of Chilean employer's response
TranspraMiofi Letters, 10(4), 202-214,2C1S. httt3s:/,doi.ore-10.10IM9427867.20i6.124329'7
5. Campbell, S. Jose Holgum-Veras, Diana G. Rainirez-Rios, Carlos Gonzalez-Calderon, Lokesh
Kalahasthi and Jeffrey Wojtcwicz, Freight and service parking needs and tie role of demand
management European Transport Research Review, 10(2), 47, 2018.
fattps: "Vdoi.org '10.1186^12 544-018-0309-5
6. Gonzalez-Caldercn, C,, Ivan Sanchez-Diaz;, Ivan Samiieato-Ordosgcrtia, Jose Holguin-Veras,
Characterization and analysis of metropolitan freight patterns in Mede-lin, Colombia, European
Transport Research Review, 10(2), 23,2018. htlps:','doi.org/I0.1185 sl2544-0IS-0290-z
Jose HsIgiaB-Vea 4
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
7.	Macea, L.. Johanna Amaya, Victor Cantillo. Jose Holguin-Veras, Evaluating economic impacts of
'water deprivation in humanitarian relief distribution usme stated choice experiments, International
Journal olDisaster Risk Reduction, 25, 427-438,20IS. https. ' dot.org'10.1016 Midrr.2Q18.03.02P
8.	Holguin-Veras, J., Tolce Encamieion, Carlos A Gonza!ez-Calderon, James Winebrake, Cara
Wang, Sofia Kyle, Nibon. Herazo-Padilla, Lokesh Kalattasthi Wilson Adamie, Victor Castillo.
Hugo Yoshizaki Rudrigo Gairido, Direct impacts of off-hour deliveries on urban freight
emissions. Transportation Research Pat D: Transport and Environment, 61, 84-103, 201S.
https: > doi.org' 10.10M''itrd,2016.10 J IB
9.	Holguin-Veras, J., Shama Campbell, Carlos A Gonzalez-Calderor., Warn Ramirez-Rios, Lokesh
Kalahasthi Felipe Aros-Vera, Michael Browne, Ivan Sanchez-Diaz, Importance and Potential
Applications of Freight and Sendee Activity Models, Citv Logistics 1: New Opportunities and
Challenges, 45-63,20IS. https:Moi.ofr 10-1002 P781119425519.ch3
10.	Holguin-Veras. J, Stacey Hodge, Jeffrey Wojtowicz, Caesar Singh, Cara Wang, Miguel Jailer
Felipe Aros-Vera, Kaan Ozbay, Andrew Weeks, Michael Replogle, Charies Ukegbu, Jeff Ban,
Matthew Brom. Shania Campbell, Ivan Sanchez-Diaz, Carlos Gonza'ez-Calderon. Alam
Komhauser, Mark Simon, Susan McSheny. Asheque Rahman, Tnice Encarnacicn, X:a Yang,
Diana Ramirez-Rios, Lokesh Kalahashti, Johanna Amaya, Michael Silas, Brandon Allen, Brrnda
Citiz, The New York City Off-Hour Deliveries Program: A Business and Community'-Friendly
SustauiabiEty Program, Interfaces, 48(1), 70-86,2018. https:,1 doi.org 10.1287 inte.2017.Cv29
11.	Zhang. D., Xiaokun Wang, Jose Holguin-Veras, Wei Zou, Investigation of earners" ability to
transfer toll increases: an empirical analysis of freight agents' relative market power,
Transportation, I -1S, 2013. https:,- ¦ doi.org' 10. i 00'7'' s 11116-01S-P930-?.
12.	Wang, C., Diana Ramirez-Rios. Carlos Rivera-Gonzalez, Jose Holauin-Veras, Joshua Schmid,
Public Opinion Toward Crowd Deliveries m New York State. Transportation Research Board
P7tfc Annual Meeting Transportation Research Board, 18-02728.201S.
13.	Holguin-Veras. J., Diana Ramirez-Rios, Lokesh Kalahasthi, Shama Campbell, Carlos A
Gonzalez-Calderon, Jeffrey Wojtowicz, Quantification of Freight and Sendee Activity- Treads m
Cities, Transportation Research Board 97th Annual Meeting Transportation Research Beard, 18-
06422,2018.
14.	Dell'Olio, L„ Jose Lois Moara, Angel Ibeas, Ruben Cordera, Jose Holgiun-Veras, Receivers'
willingness-to-adopt novel urban goods distribution practices, Transportation Research Part A:
Pobey and Practice, 102.130-141,201"?. https://doi.orz, 10.1016;j.tra.2016.10.026
15.	Holguin-Veras, Jose: Leal, Johanna Arnaya; Seroya, Barbara B; Urbaa freight policymaking; The
role of qualitative and quantitative research. Transport Policy,. 56, 75-85, 2017.
https: doi.org 10.1016 j.tranpol.2017 02.011
16.	Holguin-Veras, J., Xiaokun Cara Wang, Ivan Sanchez-Diaz, Shama Campbell Stacey D Hodge,
Miguel Jailer, Jeffrey Wojtowicz, Fostering unassisted off-how deliveries: tike role of incentives.
Transportation Research Part A; Policy and Practice:, 102, 172-187, 2017.
https: /doi-org' 10.1016 'j.tra.2017.04.005
17.	Gonzakz-Caideron C, lose Holguin-Veras, Entropy-based freight tour synthesis and the role of
traffic count sampling, Transportation Research Part. E: Logistics anil. Transportation Review,
2017. https: dot ore i0.I0Witre.2Ql7 10.010
IS. Holguin-Veras, J., Shama Campbell, Lokesh Kalahasthi, Cara Wang, Role and potential of a
trusted vendor certification program to foster adoption, of unassisted off-hour deliveries,
Transportation Research Part A: Policy and Practice, 102, 157-171, 2017.
https;. sM.org/I0.ID16,'jira.,20M.Q5.Oi I
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19.	Zhou, Y., Xiaokua Wang., Jose Holguin-Veras,, Discrete choice with spatial correlation: A spatial
autoregressive binary probit model with endogenous weight matrix (SARBP-EWM),
Transportation Research Part B: Methodological, 94, 440-455, 2016.
https://doi.QrB/10.1016. i.ttb-2016.10.009
20.	Holguin-Veras, J... Trilce Encamarion, Carlos A GoozaJez-Calderon, James Winebrake, Cm
Wang, Sofia Kyle, Nikon Herazo-Padilla, Lokesh Kalahastlii Wilson Adaime, Victor Cantiflo,
Hugo Yosfcizaki, Rodrigo Garrido, Direct impacts of off-hour deliveries on urban freight
emissions. Transportation Research Part D Transport and Environment, 61, 84-103. 2016.
https:-'doi.ore 10.1016.jtrd 2016.10.013
21.	Holguin-Veras, J., Johanna Amaya-Leal, Victor Cantdlo, Luk N Van Wassenhove, Felipe Aros-
Vera, Miguel Jailer, Econometric estimation of deprivation cost functions: A contingent valuation
experiment. Journal of Operations Management 45, 44-56, 2016.
https: doi.orgf10.1016 i.iom.2016.05.008
22.	Holguin-Veras, J.. Ivan Sanchez-Diaz, Benjamin Reim, ETC adoption, ume-of-travel choice, and
comprehensive policies to enhance time-of-day pricing: a stared preference investigation.
Transportation. 43 (2), 273-299,2016. https:/'doi.oig''10.1007'sl 111-6-014-9575-9
23	Holguin-Veras, J.. Ivan Sanchez-Diaz, Freight Demand Management and the Potential of
Receiver-Led Consolidation programs. Transportation Research Pail A: Policy and Practice, 84.
109-130- 2016. https:'''doi.org' 101016 i.tra.2015.06.013
24	Fradhananga, R., Fatih Mutlu, Shaligram PokliareL Jose Holguin-Veras, Dinesh Seth, An
Integrated Resource Allocation and Distribution Model for Pre-Disaster Planning. Computers 
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
Networks and Spatial Economics, 15 (3), 883-915, 2015. hips' -dot wglQ.100A11067-G13-
P213-7
33.	Sanchez-Diaz. I.. Jose Holgiiin-Veras, Xoegang Baa, A Tine-Dependent Freight Tour Synthesis
Model Transportation Research Part B, 71(1), 144-168, 2015.
https^/doiorg-10.1 QM''itrb-20 15.04.007
34.	Holguin-Yeras, J., F. Aros-Yera, Self-Supported Freight Demand Management: Pricing am!
Incentives, EURO Journal on Trmsportation. and Logistics, 4(2), 237-260, 2015.
https: dci.org 10.1007 si:676-013-0042-l
35.	Perez-Rodriguez, N . J. Holguin-Yeras. Inventory-Allocation Distribution Models for Postdisaster
Humanitarian Losistics with Explicit Consideration of Deprivation Costs. Transportation Science,
50(4), 1261-1285"2015. faftps:,.¦ doi.org 10.1287.tr5c.2Q14.0565
36.	Jailer, M., X. Wang, J. Holguin-Yeras, Large Urban Freight Traffic Generators: Opportunities for
City Logistics Initiatives. Journal of Transportation and Land Use, 8(1). 17. 2015.
37.	Holguin-Yeras, J., I. Sanchez-Diaz, Freight Demand Management and the Potential of Receiver-
Led Consolidation Programs. Transportation Research A, 84, 109-130, 2015.
https"7/doLorg/10.10 l&'ltra.2015.06.013
38 CantiUo, V., M. Jailer, J. Holguin-Yeras, The Colombian Strategic Freight Transport Model Based
on Product Analysis, PRQMET-Traffic&Traiisportation, 26 (6), 487-496, 2014.
https:doi.or a' I0.7307»''pl.v26i6.1460
39. Yar.g, X., Z Sun. X. Ban, J. Holguin-Yeras, Urban Freight Delivery Stop Identification with GPS
Data. Transportation Research Record: Journal of the IransportitkMi Research Board, 2411, 55-
61, 2014. https: doi.org I0.314L2411-07
40 Perez-Rodtiguez. Is.. J. Holguin-Yeras, The Accumulation of Empty Containers in Urban Areas;
Policy Implications from a Stochastic Formulation, Networks and Spatial Economics, 14 (3-4),
379-408, 2014. https.1.doi.org-10.1007 si 1057-014-9231-0
41.	Holguin-Yeras, I., F. Ares-Vera, Geographically Focused incentives to Foster Off-Hour
Deliveries: Theory and Performance. Transportation Research Record, 2411, 27-33, 2014.
https :/Motofg/I03~141/2411-04
42.	Holeuin-Veras, J., E. Taniguchi, M. Jailer, F. Aros-Yera, F. Fenrara. R.G. Thompson, The
Tohoku disasters: Chief lessons concerning the post disaster humanitarian logistics response and
policy implications. Transportation Research Part A: Policy and Practice, 69, 86-104, 2014.
https:- doi.org 10.l01&'ltra.2014.08.003
43.	Yushimito, W., X. Ban, J. Holguin-Veras. A two-stage optimization model for staggered work
hours. Journal of Intelligent Transportation. Systems, 18 (4), 410-425, 2014.
hBps'7/doiorg 10.1010/15472450.2013.806736
44.	Holguin-Yeras. J., M. Jaler, L.N. Van. Wassenhove, N. Perez, T. Wachteidorf, Material
Convergence: An. Important and Understudied Disaster Phenomenon- Natural Hazards Review,
15(1), 1-12, 2014
45.	Yashimito, \Y.F, X. Ban, J. Holguin-Yeras A Two-Stage Optimization Model for Staggered
Work Hours. Journal of Intelligent Transportation Systems, 18(4). 410-425, 2014.
https: doi.org 10.1010/15472450.2013.806736
46.	Jailer, M J Holguin-Yeras, S.D. Hodge. Parking ie The City: Challenges for Freight Traffic.
Transportation Research Record, 2379, 46-56.2013. https: ¦ doi.org 10.3141 237P-Q6
47.	Holguin-Yeras, J., B. Allen, Time of day pricing and its muta-dimensional impacts: A stated
preference analysis, Transportation Research Part A: Policy and Practice, 55, 12-26, 2013.
https'j'ydoiorg'''I0.I01fe'''f:liaJ013J8.003'
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48.	Holgum-Veras. J.. N Perez. M. Jailer. L. N Yan Wassenhove, F. Aros-Veia. On tbe appropriate
objective function for post-disaster humanitarian logistics models, Journal of Operations
Management, 31(5), 262-280,2013. https:>¦ doi.org/10.10l6-'i.iom.2013.06.002
49.	Wachtendorf T., B. Bro'.vn, I. Holguin-Yeras, Catastrophe characteristics and their impact on
critical supply chains: problematizme materiel convergence and management following Hurricane
Katrma, Journal of Homeland Security and Emergency Management. 10 (2). 497-520, 2013.
https:' doi.org 1 0.1515,' jhsem-2012-0069
50.	Jailer, M, J. Holguin-Yeras. Comparative Analyses of Stated Behavioral Responses to Off-Hour
Deliver.' Policies. Transportation Research Record: Journal cf the Transportation Research Board,
2379(1), 18-28.2013. https://doia^l0-3141/2379-03
51.	Hokum-Veras, I., I. Sanchez-Diaz, C.T. Lawson, M. Jailer, S. Campbell, H.S. Levinson, H -S.
Shin. Transferability of Freight Trip Generation Models. Transportation Research Record: Journal
of the Transportation Research Board, 2379(1). 1-8.2013. https :.-'/doi org/10.3141/2379-01
52.	Holjptn-Yeras. J., I. Sanchez-Diaz. C A Goczalez-Calderou. Freight Demand Estimation from
Secondary Sources Case Study: Manhattan DYNA, SQ;:S2l 200-209,2013.
53.	Holguin-Yeras, J., R. Marquis, S. Campbell, J. Wojtovicz, C. Wang, M. Jailer, S13. Hodge, S.
Rothbard, R. Goevaers, Fostering the Use of Unassisted Off-Hour Deliveries: Operational and
Low-Noise Truck Technologies. Transportation Research Record: Journal of the Transportation
Research Board, 2379(1), 57-63, 2013. https.' doi.org'10.3141/2:379-07
54.	Holguin-Yeras, J.. C. Tones Cruz, J. Ban, On the comparative performance of urban delivery
¦vehicle classes".. Transportmetrica A: Transport Science, 9(11 50-73, 2013
tttp:/'dx.doi.org 10.10SQ 18128602.2010.523029
55.	Holguin-\"eras. J.. J. Redly, F. Arcs-Yet a, \V. Yushiniito, J. Isa, Park-and-Riae Facilities in New
York City: Economic ..Analysts of Alternative Locations. Transportation Research Record: Journal
of the Transportation Research Board, 2276(1), 123-130,2012. https doi.org 10.3141 '2276-15
56.	Holeutn-Veras, J.. \V. F. Yushiniito. F. Aros-Yera, J. Reilly. User rationality and optimal park-
aad-ride location under potential demand maximization. Transportation Research Pan B:
Methodological, 46(8), 949-970,2012. http:-.dx.doi.org 10.1016j.trb.2012.0:.011
57.	Lawson, C., J. Hoiguin-Yeras. I. Sanchez-Diaz. M. Jailer, S. Campbell. E. Powers, Estimated
Generation of Freight Trips Based on Land Use, Transportation Research Record: Journal of the
Transportation Research Board 2269, 65-72,2012. http: Vdx doiofg/iO.3141/2269-08
58.	Holguin-Veras. J., M. Jailer and T. W achtendorf (2012). "Comparative Peribrmance of
Alternative Humanitarian Logistic Structures after the Port-au-Prince Earthquake: ACEs, PIEs,
and CANs." Transportation Research Part A: Policy and Practice 46(10): 1623-1640.
http:- dx.doi.org-lQ.1016 i.tra.2012 OS.002
59.	Holguin-Yeras, J, M. Jailer, L.N Yan Wassenhove, N. Perez, T. Wachtendorf. Material
Convergence: Important and Understudied Disaster Phenomenon. Natural Hazards Review, 15(1),
1-12,2012.
60.	Holguai-Yeras. J.s M. Jailer L X V. Wassenhove. N. Perez, T. Wachtetidkrf, On the Vmqve
Features of Post-Disaster Humanitarian Logistics, Journal of Management, 30, 494-506, 2012.
fcttp:;'dx.doi.orgi'10 1016 1 iom.2012.03.003
61.	Gonzalez-Calderon CA, I. Sanchez-Diaz, J. Holguin Yeras, E. Thorson, An empirical
investigation on the impacts of spatial and temporal aggregation of empty trips models. Revista
Facultadde IngenierfaUniveisidad de Autioquia, 64,150-162,2012.
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Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
62. (*) Silas ML. I Holgum-Veras S. Jara-Diaz, Optimal Dislritaticm of Financial Incentives to Foster
Off-How Deliveries in Urban Areas Transportation Research. Part A, 46, 1205-1215, 2012.
http dx doi ere 10.1016 j.tra 2012.05 015
63	Holgum-Yeras. J Approximation Mode! to Estimate Joint Market Share in Off-Hour Deliveries,
Logistic Reseaich. 101-110,2012. hBo^ds.doi.oiglO.1007 812159-012-0065-1
64	Holgum-Yeras J X Xu C Shit. Ail assessment of the impara of inspection times en the air'ine
industry's market share after September llii. Journal of Air Transport Management 2H 0\ l7-
24, 2012. top dxiloi.cag,-10.1016. uairliaman.2012.02.004
65	Holguia-Yeras T K Ozbay, A. Kjxnhauser, M. Bfotn, S. Iyer, W.F. YnshiiMto, S. Ukkusuri, B.
Allea M A Silas Overall Impacts of Off-Hour Delivery Programs ill the New York City
Metiopolitar. Area Transportation. Research Record 2238, 68-76, 2011.
https, Joi.org 10,3141-2^38-09
66	Holgum-Vaas. J„ X Xu, G. De Jong, H. Maurer An experimental economics investigation of
shipper-earner interactions in the choice of mode and shipment size in freight transport. Xetvvoiks
aad Spatial Economics, 11(3). 509-532,2011 http 10 1007 si 1087-009-910?~x
67	Brotr. M.J KolguttiA'eras. S.D Hodge. Off-Hour Deliveries in Manhattan: Experiences of Pilot
Test Participants, Transportation Research Record, 2238, 77-85, 2011.
https: dot ore 10.3141 223S-10
68	Holguin-Yeras J.Q Wang N. Xu, K. Ozbay. The Impacts of Time of Day Pricing on Car User
Betavior Findings from the Port Authority of New York and Xew Jersey's Initiative,
Traospottatiott, 3S;3) 427-443 2011 http .hdl.h3ixtk.net 10 10C7 511116-010-9307-8
69.	Holgum-Yeras. I Urban deliver." industry response to cordon pricing, time-distance pricing, and
carrier-receiver policies in competitive markets, Transportation Research Part A: Policy and
Practice, 45(8). £02-824. 2011 https,-doi.org I0,1016rj.tra.2011.06.008
70.	Holguki-Yeras J, M Jailer Immediate reso.trce requirements after iiunicane Katrina Natural
Hazards Review, 13(2), 117-131, 2011. Mtpi/ttoLdolofB'' 10.1061 (ASCE'iNH 1527-
6996 0000068
71.	Destrn, L, J. Holguin-Veras, Material Convergence and its Detemimants: The Case of Hurricane
Katrina, Transportation Research Record 2234,14-21,2011. http. dx.doi.org 10.31412234-02
72	Holauin-Yeras, J., M. Jailer, L. Bestro, X. Ban, C. Ian-son, H Levinson, Freight Generation,
Freieht Tnp Generation, and the Perils of Using Constant Trip Rates. Transportation Research
Record, 2224. >58-Sl. 2011 https doi.org,''10,3141,'2224-09
73	Holguin-Veras J I Sanmento C A Gonzalez-CakJeron. Parameter Stability In Freight
Generation And Distribution Demand Models In Colombia Estabilidad De Parametros En
Modelos De Generacton Y Distribution De CargaEn Colombia. DYXA. 166,17. 2011
74	Holguin-Veras J I Sanchez. C Gonzalez. I Samuento E Thorson, Time-Dependent Effects on
Parameters of Freight Demand Models, An Empirical Investigation.' Transportation Research
Recoid 2224 42-50 2011 http dx dot org 10.3141 2224-06
75	Holguin-Veras. J Q Wang. Behavioral Investigation on the Factors that Determine Adoption of
an Electronic Toll Co'lectior. S\ stem. Freight Carriers, Transportation Research. Part C: Emerging
Technologies lPt4< 5^3-605.2'Jll.https duioig 10.1016'i.trc.2010.09.010
76. Holgum-Yeras J M Preziosi Behavioral tm estigation on the factors that oetemune adoption of
an electronic toil collection system Passenger car users. Transportation Research Pat C:
Emerging Technologies 19'31 498-509 2011,httpj/dx-doi-arg/lO, 1016-j.trc.2010,07,005
joss Helpna-Ys
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77. Yanmaz-Tozel, O., K. Ozibay, J. Holguin-Veras. Value of travel 'lime estimation using Merardiical
bayesian mixed iosit approach. Transportation Research Record: Journal of the Transportation,
Research Board, 21^87(1), 85-96, 2010. https: doi.org 10 3141 2187-12
7S. Holguin-Veras, J.. E. Thorson, J.C. Zoriilla. Commercial Vehicle Empty Trip Models with
Variable Zero Order Emptv Trip Probabilities. Network and Spatial Economics. 10(2), 241,2010.
http :/MxJ Qi.org< 10.100 7* si 1067-008-9066-7
79.	Silas,. M., J. Holguin-Veras, Behavioral Microsimiilatioa Formulation for Analysis and Design of
Off-how Deliver.' Policies in Urban Areas, Transportation Research Record. 2097. 43-50, 2010.
https:-f/doi.orgJ10.3 141 2097-06
80.	Holguin-Veras, J., S. Jara-Diaz. Optimal two-part pneing and capacity allocation with multiple
user classes and elastic arrivals at constrained transportation facilities. Networks and Spatial
Economics. 10(4). 427-454, 2010. http:"te.doi.org.;110.1007 si 1067-008-9075-6
81.	BasMa, C, J. Holguin-Veras. Freight Generation Models: Comparative Analysis of Regression
Models and Multiple Classification Analysis, Transportation Research Record, 2097, 51-61, 2009.
httpsy'doiorg'10.3141/2097-87
82.	Holguin-Veras. J., M. Cetin. Optimal tolls for multi-class traffic: Analytical formulations and
policy implications. Transportation Research Part A: Policy and Practice, 43(4), 445-467, 2009.
http:- ¦'dx.doi.om-' 10.1016/j tra2Q08.11.012.
S3. Wang, Q, J. Holguin-Veras, .An Investigation on the Attributes Determining Trip Chaining
Behavior in Hybrid Micro simulation Freight Models. Transportation Research Recoid. 2066,. 1-8,
20QS. fattpsi'doiors 10.3141,-2066-01
14. Holguin-Veras, X Necessary conditions for Off-Hour Deliveries and the Effectiveness of Urban
Freight Road Pricing and Alternative Financial Policies in Competitive Markets, Transportation
Research Part A: Poiicy and Practice, 42t2), 392-413,. 2008.
https^/doLorg 10.1016 j.tra.2007.10.008
§5. Friesz, T. L., R. Mookherjee, I. Holguin-Veras,, M. A. Rigdon, Dynamic Pricing in an Urban
Freight Environment Transportation Research Part B: Methodological, 42(4), 305-324, 2008.
https:-"'doi.Qrg/IQ.I016/f.lrb.2007.08.00I
86. Hokuin-Yeras, J., G. Patil, A Multi-Commodity Integrated Cooimodity Based-Empty Trip
Freight Origin-Destination Synthesis Model, Networks and Spatial Economics, 8(2-3), 309-326,
2008. http:.1'"dx-doi.org'10.1Q<37 si 1067-007-9053-4
87 Holguin-Veras. J.. M Silas. J. Poiimeni B. Cruz, An Investigation. on tie Effectiveness of Joint
Receiver-Camer Policies to Increase Truck Traffic in the Off-Peak Hours. Part II. The Behavior
of Carriers. Networks and Spatial Economics. §(4), 327-354. 20-08.
https: doi org' 10.1007 si 1-067-006-9011-6
88.	Holguin-Veras. J., N. Xu, Q. Wang, K. Ozbay, I. ZoirilJa, M. Cetin, New Jersey Turnpike Time-
of-Day Pricing Initiative s Behavioral Impacts: Observed Role of Travel Distance on Underlying
Elasticities, Transportation Research Record: Journal of the Transportation Research Board
2010(1), 53-61.2D01.http:''d\.doi.org'53-fil.10.3141 2010-07
89.	Hokuin-Yeras, J., M. Silas. I Poiimeni B. Craz, An Investigation on the Effectiveness of Joint
Receiver-Carrier Policies to Increase Truck Traffic in the Off-Peak Hems. Part I: The Behavior of
Receivers, Networks and Spatial Economics, 7(3), 277-295, 2007. https://doi.org/I0-1007/sl 1067-
006-9002-7
90.	Hokum-Yeras, J., N. Perez, S. Ukkusuri, T. Wacbteodorf, B. Brown, Emergency Logistics Issues
Affecting the Response to Katrina: A Synthesis and Preliminary Suggestions for Improvement,
Transportation Research Record, 2022, 76-S2,2007. https://doi.org '103141/2022-09
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91.	Holeuin-Veras. J.. G, Paul Integrated Origin-Destination Synthesis Model fcr Freight with
Conimcdity-Based and Empty Trip Models, Transportation Research Record, 2008, 60-66. 2007.
https: ¦ dot, org. 10 3141 2008-08
92.	Gzmen-Ertekin, D.. K. Ozbay, J. Holguin-Veras, Role of Transportation Accessibility ui
Attracting Businesses to New Jersev. Journal of Urban Planning and Development 133(2), 138-
149. 2007.
93.	Holguin-Veras, J., N. Perez, B Cruz J. Polimeni, Effectiveness of Financial incentives for Off
Peak Deliveries to- Restaurants in Manhattan, Transportation Research Record: Journal of the
Transportation Research Board 1966,51-59,2006. https://doi.org/10.314! 1966-07
34. Srinivasan, S., C.R. Bhat, I. Holguin-Veras, Empirical analysis of the impact of security
perception on intercity mode choice: A panel rank-ordered mixed logit model Transportation
Research Record: Journal of the Transportation Research Board, 1942(1), 9-15, 2006.
https: ''doi-org/10.11 ?7.'QS61198106194200102
95.	Ozbay, K, O. Yanmaz-Tuzel, J. Hclguin-Veras. Evaluation of Combined Traffic Impacts of
Time-of-Day Pncmg Program and E-ZPass Usage on New Jersey Turnpike, Transportation
Research Record: Journal of the Transportation Research Board, I960, 40-47, 2006.
Mlp5:.''/doi.orB,'103141 ¦ 1960-06
96.	Ozbay, K., O. Yanmaz-Tuzel, J. Holguin-Veras. Theoretical Derivation of Value, of Travel Time
and Demand Elasticity: Evidence from New Jersey Turnpike Toll Road. Transportation Research
Record. Journal of the Transportation Research Board, 1915(1},. 248-25#, 2006.
https • doi.org 10.3141 1PS5-27
97.	Ozbay. K„ O. Yanmaz-Tuzel, D. Ozmen, J. Holguin-Veras, Evaluation of Impacts of Time-of-
Day Pricing Initiative on Car and Track Traffic: Port Authority of New York and New Jersey,
Transportation Research Record: Journal of the Transportation Research Board 1960, 48-56,
2i306.http:'/dx.doi.org/10.3141/1960-07
98.	Holguin-Veras, J., M. Cetin, S. Xia, A Comparative Analysis of U.S. Toll Policy, Transportation
Research Part A: Policy and Practice, 40 (10), 852-871, 2006.
https :¦ ¦l'doi.of e,' 10.1016 '1 tra.2006.03.003
99.	Holguin-Veras, J., S. Jara-Diaz (2006) "Preliminary Insights into Optimal Pricing and Space
Allocation at Inteimodal Terminals with Elastic Arrivals and Capacity Constraint Network and
Spatial Economics, 6 (I), 25-38. 2006. http. dx.doi.org 10.1007/511067-006-7683-6
100.	Holguin-Veras, J., Q. Wang, N Xu, K Ozbay, M. tetm, J. Polimeni, The Impacts of Time
of Day Pricing on the Behavior of Freight Carriers m a Congested Urban Area: Implications to
Road Pricing, Transportation Research Part A: Policy and Practice, 40 (9), 744-766, 2006.
https:.Vdoi.org/10.1016. i ira2005.12.011
101.	Ozbay, K., D. Ozmeo-Ertekin O. Yanmaz-Tuzel, J. Holguin-Veras. Analysis of the Value
Pricing Impacts at Port Authority of New York and New Jersey Facilities, Transportation
Research Record: Journal, of the Transportation Research Board, 1932. 109-118, 2006.
http://dx-doi.org' 10.3141/1932-13
102.	Holguin-Veras, J, N. Xu, H Levinson C. E. McKnight, RB. Weiner, R E Paaswell, K
Ozbay, D. Ozmen-Ertekin. .An Investigation on the Aggregate Behavior of Finn. Relocations to
New Jersey tl99G-19?9> and the Underlying Market Elasticities, Networks and Spatial
Economics,"5'3). 293-331 2C05. https.' doi.org 10.1007 si 1067-005-3037-z
103.	Holguin-Veras, J., G. Patil, Observed Trip Chain Behavior of Commercial Vehicles,
Transportation. Research Record: Journal of the Transportation Research Board, 1906(1), 74-80,
2005. https^/doiorg/lO. 1177 0361198105190600109
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104.	Holguih-Veras, I, J. Polimeni, B. Cruz, N. Xo, G. List J. Nordstrom, J. Haddock, Off-Peak
Freight Deliveries: Challenges and Stakeholders Perceptions, Transportation Research. Record:
Journal of the Transportation Research Board, 1906: 42-4S, 2005. https:'¦ doi. org'' 10.3141 ¦' 1906-05
105.	Hoigum-Yeras, J., E. Ttaorson. K Ozbay, Preliminary Results of an Experimental
Economics Application to Urban Goods Modeling Research, Transportation Research Record:
Journal of die Transportation Research Board 1873: 9-16, 2004. https: .'doi-org-'lO 3141*1873-02
106.	Holguin-Yeras, J., D. Sackey, S. Hussam, Y Ochieng, On the Economic and Financial
Feasibility of Toll Trackways, Transportation Research Record: Journal of the Transportation
Research Board, 1833, 66-72, 2003. https: doi.org,-10.3141 .'1833-09
107.	Holguin-Veras, J.. K. Ozbav. R. Baker, D. Sackey, A. Medina, Towards a Comprehensive
Policy of Nighttime Construction Work, Transportation Research Record Journal of the
Transportation Research Board, 1861(1), 117-124, 2003 https://doi.oi g 10.3141/1861-12
108.	Holguih-Veras, J., E. Thorsoa, Modeling Commercial Vehicle Empty Trips with a First
Order Trip Chain Model Transportation Research Part B. 37(2)., 129-148. 2003.
https:' doi.org,110.1016/SO191-2615(01)00048-0
109.	Holgain-Veras, J., E. Thorson, Practical. implications of Modeling Commercial Vehicle
Empty Trips. Transportation Research Record: Journal of the Transportation. Research Board,
1833," 87-94,2003. https:: •'doLore 10 3141 1833-12
110.	(*) Lena, T.S., Y. Ocaieng, M. Carta, J. Holguin-Yeras, P. Kinney, Elemental Carbon and
PM2.5 levels in an Urban Coomuaitv Heavily Impacted tjy Truck Traffic, Environmental Health
Perspectives, 110 ;10). 1009-1015, 2002.10.12S9-ehp.0211Q1009
Hi. Hoiguin-Yeras, J., Y. Lopez, A. Salam. Truck Trip Generation at Container Terminals:
Results from a Nationwide Survev. Transportation Research Record: Journal of the Transportation
Research Board, 1790, 89-96,2002. https: doi.org. 10.3141/1790-11
112.	Holguin-Yeras, J.. Revealed Preference Analysis of the Commercial Vehicle Choice
Process, Journal of Transportation Engineering, 128(4), 336-346, 2002.
https://doi.arE/10- i061/(ASCE)Q 733-947X(2002)12S:4t336)
113.	Holguin-Yeras, J., E. Thereon, An Investigation of the Relationships Between the Trip
Length Distributions in Commodity-based and Trip-based Freight Demand Modeling,
Transportation Research Record: Journal of the Transportation Research Board. 1707, 37-41,
2000. https.-ftdoLora,-10-3141 ~l 707-05
114.	Holguin-Yeras, I, R. Paaswell, New York Regional. Intermodal Freight. Transportation
Planning: Institutional. Challenges, Transportation Law Journal's Special Issue on Intermodal
Transportation, 27;i31.453-473,2000.
115.	Holguin-Yeras, J., On the Attitudinal Characteristics of Motor Camera- Toward Container
Availability Systems, International Journal of Services Technology and Management, 1(2-3). 140-
155, 2000."https:,''.'doiofg/10.1504/IJSIM.2000.001569
116.	Holguin-Yeras, J., S. Jara-Diaz, Optimal Space Allocation and Pricing for Priority Sendee at
Container Ports, Transport Research Part B, 33(2), 81-106, 1999. fattosy/doiorg/I0.1016/S0191-
2615(98)00029-0
117.	Holguin-Yeras, J, Jara-Diaz, S, Practical Implications of Optimal Space Allocation and
Pricing, Ports' 98.1, 89-97, 1998. ISBN 0-7144-0329-5
118.	Holguin-Yeras, J.. S. Jara-Diaz,. Walton, Toward New Paradigms of Container Terminal
Modeling. Journal of Infrastructure, 3 (2), 3-9,1998.
Jesse- Haimiib-Ysras-
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119.	Holguin-Veras, J, CM. Walton, Oil the Application of Combined Models to Port
Simulation. Case Study: Gantry Crane Operations, Journal of the Transportation Research Forum,
37(1), 29-45,1998.
120.	Holgufn-Veras, J. C.M. Walton, Implementation of Priority Systems for Containers at
Marine Intenr.odal Terminals. Transportation Research Record. Journal of the Transportation
Research Board, 1502,57-64 1P97 httos. doi.org 10.3141 ¦¦1602-09
121.	Holguin-Veras, J.. Alternative Modeling Framework for Pavement Seraceainlity Analysis,
Journal of Tran^oitaaau. Enemeerins. 123(6), 473-483, 1997.
https:/,'''doi.org/I0. iOSl/t ASC E >0733 -947XjH997)123:6(478)
122.	Holguin-Vetas, J €3,1 Walton, The State of the Practice of Information System and
Information Technology at Marine Container Ports, Transportation Research Record Journal of
the Transportation Research Board, 1522,87-93,1996. httpsv doi org 10.3141/1522-1.2
123.	Holguin-Veras, I, Comparative Assessment of the Analytic Hierarchy Process and Molti
Attribute Value Functions for Hiehwav Evaluation: A Case Studv, Journal of Transportation.
Engineering, 121(2), 191-200.1995. https: doi.org. 10.10)51 •(ASCE)0733-947X
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5.	Holguin-Veias, I, C. Wang, M. Browne, SJ>. Hodge, and I Wqjtowicz, The New York City Off-
hour Delivery Project Lessens for City 'Logistics, in City Logistics MI, 2014
6.	Holguin-Yeras, J., I, Sanchez-Diaz, M. Jailer. F. Aros-Vera, S. Campbell, C. Wang, and S Hodge,
Off-Hour Deliver}- Programs, in City Logistics: Mapping The Future, p. 149, 2014
7.	Holguin-Yeras, J. and M. Jailer: Comprehensive Freight Demand Data Collection Framework for
Large Urban .Areas, in Sustainable Urban Logistics: Concepts, Methods and Information Systems,
J. Gonzalez-Feia F. Semet and J.L. Routhier, Editors, Springer-Yeriag: Berlin, 2014
8 Hokum-Yeras, J.. T. Wachtendoif. M. Jailer and T. Jefferson (20131 'Logistics and the
Management of Critical Supplies Following Catastrophes." Preparedness and Response for
Catastrophic Disasters: 131.
9.	Hokum-Yeras, I, M. Jailer and T. Wadrteodorf (2013). "Improving Postdisaster Humanitarian
Logistics: Three Key Lessons from Catastrophic Events." TRNews (287).
10.	Holguin-Yeras, J., E. Thorson, Q. Wang, X. Xu. C. Gonzalez, I. Sanchez-Diaz, .and I. Mitchell,
Urban freight tour models: state of the art and practice, 2012
11.	Holguin-Yeras, J. (2009), "The Truth, the Myths and the Possible in Freight Road Pricing in.
Congested Urban Areas," (Book Chapter ta City Logistics \T> pp. 615-630
12.	Holguin-Yeras, J., R. Paaswell and A. Perl (2008) "The Role of Government in Fostering
Intermodal Transport Innovation and Research" (Chapter 15 ill Komngs, R_. H. Pnemus & P.
Nijkamp (eds). The Future of Intermodal Freight Transoort: Operations. Desnzn and Policy.
Edward E3gax Publishing Limited, Cheltenham, UK. ISBN 978 1 84542 238 7)
13.	Holgum-Yeras, J., M. Silas, J. Polimeni and B. Craz (2007j "An Investigation on tie Atfitodinal
Factors Determining Participation in Cooperative Multi-Carrier Delivery Systems" (Book Chapter
in City7 Logistics V) pp. 49-62
14.	Ukkusuri, S. and J. Holguin-Yeras (2U06) "Assessing Critical Components in Transportation
Systems: Economic Models and Complex Network Science Approaches" in "Network Science,
Nonlinear Science and Infrastructure Systems,1' Teriy L. Friesz, (Editor), Springer-Yeriag.
15.	Holguin-Yeras, J., J.M. Pohmem, B. Cruz, and G. List (2005) Off-Peak Freight Deliveries to New
York City: Challenges and Policy Measures. In City Logistics IY (E. Taniguchi and R Thomson,
eds), pp. 547-559, ELsevier, .Amsterdam,
16.	Holguin-Yeras, 1., J. C. ZomlJa, and E. Thorson {2005)" Modeling Comma cial Vehicle Empty
Trips: Theory and Application" XYI International Symposium of Traffic and Transportation
Theory (ISTTT), pp. 585-508, H. Mahmassani (Editor), Elsevier.
17.	Friesz. T. and J. Holguin-Yeras (2005) "Dynamic Game-Theoretic Models of Urban Freight:
Formulation and Solution Approach"' in 'Methods and Models in Transport and
Telecommunications: Cross Atlantic Perspectives" pp. 143-161, Springer-'Yerlag.
18.	Holguin-Yeras, J. (2004). 'On the Estimation of the Maximum Efficiency of the Trucking
Industry: Implications for City Logistics."' In: City Logistics III (E. Taniguchi and R Thomson,
eds), pp. 123-134, Elsevier, Amsterdam.
19.	Holguin-Yeras, J., R. Paaswell and A Yali (2003) "Impacts of Extreme Events cm Intercity
Passenger Travel Behavior: The September 11th Experience" in Beyond September 11th:
Account of Post-Disaster Research. Special Publication *39 pp. 373-404. Boulder, CO: Natural
Hazards Research and Applications, information Center, University of Colorado).
20.	Holguin-Yeras. J. and R. Paaswell (2001). "New York Regional Intermodal. Freight
Transportation Planning: Institutional Challenges."' Reprinted from the Transportation Law
Journal Vol. 27 No. 3, Summer 2000, in "Intermodal Transportation: Selected Essays."1 Published
by the National Center for Inteimocal Transportation.
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Refereed book chapters in press
I.
Refereed book chapters feeing reviewed
1. -
Refereed conference proceedings
1. Holguin-Yeras. J... E.„ and M. Brcm 'Trucking Costs: Comparison Between Econometric
Estimation and Cost Accounting." Transport Research Record Annual Meeting of Transportation
Research Board, 2008
1.	Ozbay K., O. Yanmaz-Tuzel, and J. Holguio-Veras (2006) *L Evaluation of the Combined Impacts
of E-ZPass and Tane-of-Day Pricing on Port Authority of New York and New Jersey Crossings,
Proceedings of ITSC 2006- 9th International IEEE Conference on Intelligent Transportation
Systems, Toronto, Canada.
2.	Holguin-Yeras, J.. N. Xu, Q. Wang. K. Ozbay, M. Cetin. and J P oilmen:. J.C. Zorrilla and M
Silas "The Behavioral Impacts of the New Jersey Turnpike s Time of Da}' Pricing Initiative and
the Observed Role of Travel Distance on the Underlying Elasticities"" Annual Meeting of
Transportation. Research Board, 20*06
3_ Holguin-Yeras T N. Perez, B Cruz and J. Polimem "On the Effectiveness of Financial Incentives
to Off Peak Deliveries to Manhattan Restaurants" .Annual Meeting of Transportation Research
Board, 2006
4.	Holguin-Yeras, J„ Q. Wang. N. Xu, K. Ozbay, M. Cetin and I Polimem, and J.C. Zomila
"Behavioral Impacts of Time Of Day Pricing: General Findings from the Port Authority of New
York and New Jersey's Initiative'" Annual Meeting of Transportation Research Board, 2006
5.	Snnivasan, S., C. R. 3hat, J. Holguin-Yei as and C. Chen "Impact of Security Perception on.
Intercity Mode Choice: A Panel Rank-ordered Mixed-Logit Analysis" Annual Meeting of
Transportation Research Board, 2006
6.	Ozbay, K., O. Yanmaz-Tuzel, and J. Holguln-Yeras '"The Impacts of Time of Day Pricing
Initiative at NY N'J Port Authority Facilities Car and Track Movements" Annual Meeting of
Transportation Research Board, 2006
7.	Ozbay, K., O. Yanmaz-Tuzd, and J. Holguin-Yeras "The Impacts of Time of Day Pricing and
'the Tiavel Times on the New Jersey Turnpike Traffic" Annual Meeting of Transportation.
Research Board, 2006
8.	Ozbay K, O1. Yanmaz-Tiizel and J. Holguin-Yeras (2005) "Evaluation of New Jersey Turnpike
Time of Day Pricing Prop-am, presented m INFORMS Annual Meeting, November 13 -16 2005,
San Francisco. USA.
9.	Ozbay K_, O. Yanmaz-Tuzel, and I. Holguin-Veras (2005) "Analysis of Observed Behavior of
Users to- Yalue Pricing and Travel Time: New Jersey Turnpike Case," presented in Transportation
Research Board 84th Annual Meeting, January 2005, Washington D.C.
10.	Ozbay K.. O. Yanmaz-Tuzel, and J. Holguin-Yeras 1,2005) "The New Jersey Turnpike Road
Pricing Initiative: Analysis Traffic Impacts,"1 presented in PIARC, fateimaianal Seminar on Road
Pricing with emphasis on Financing, Regulation ami Equity, April 200.5, Cancua, Mexico (with
Ozbay K.; Holguin-Yeras J.)
11.	Chen. C, W. Li, R_. Paaswell, and J. Holguin-Veras "Impact of 9/11 on Intercity Tiavel
Behavior: Who Are Affected'1" submitted to Transportation Research Record (July 2005)
12.	Holguiu-Yeras. J., J. Polimem, B. Cruz, N. Xu, G List, J., Nordstrom and 1. Haddock (2005)
"Off-Peak Freight Deliveries: Challenges and Stakeholders Perceptions" Annual Meeting of
Transportation Research Board, 2005
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13.	Ozbay, K, D. Ozmen, and J. Holgaih-Veras I.2U05) "Analysis of the Value Pricing Impacts at
NYMJ Port Authority Facilities Annual Meeting of Tiansportaaon Research Board, 2005
14.	Ozbay, K, O. Yanmaz, and J, Holgum-Veras .,2005 < Anah sis of the Observed Behavior Of
Users to Value Pricing and Travel Time; The New Jeisey Turnpike Case" Annual Meeting of
Transportation Research Board. 2005
15.	Ozbay, K, O. Yacmaz, and J. Holgum-Veras (2005). "Evaluation of New Jersey Turnpike Time
ofDay Pricing Program'" INFORMS. New Orleans. November 13-16. 2005
16.	Holguin-Veras, J., and G. Paul i2005) "Observed Tnp Chain Behav.or of Commercial Vehicles"
Annual Meeting of Transportation Research Board. 2005
17.	Ozbay, K., O. Yanmaz, and J. Holguin-Veras (2004) NJ Value Pricing and the New Jersey
Turnpike: Travel Time Impacts", CD-ROM Pre-Pnnts of the S 5th. TIB Annual Conference, 2004,
Washington, DC.
IS. Ozbay, K.r D. Ozmen, and J. Holguin-Veras 1,2004) 'Analysis of the Value Pricing Impacts at
NY NJ Port Authority Facilities", CD-ROM Pre-Praits of the S5th TRB Annual Conference,
2 004, Washington, DC
19.	Ozbay K.. O. Yanmaz, and J. Holguin-Veras (20041 "The New Jersey Turnpike Road Pricing
Initiative Analysts Traffic Impacts. CD-ROM International Seminar in Road Pricing " (PIARC),
11-13. April, 2005. Cancim Mexico.
20.	Ozbay. K... D Ozmen, and J. Holguiii-Veras . (2004) "Price Elasticity of Demand at New
York New Jersey Port Authority Facilities Due to Variable Toll Pricing'. 13th Pan-American
Conference of Traffic and Transportation Engineering. Albany. NY, 2004.
21.	(*) Xia, S.; M. C'etin and J. Holguin-Veras (.2004)' An Econometric Investigation of Toll Policies
in the U.S,'r published by the XEI Pan .American Conference of Traffic and Transportation.
Engineering (CD ROM) Albany NY.
22.	(*) Zcmlla, J. C. and J, Holgum-Veras (2004) "Furthei Enhancements to Empty Trip Models"
published bv the XIII Pan American Conference of Traffic aad Transportation Engineering (CD
ROM) Albany NY.
23.	(*) Perez, N. and J. Holgum-Veras (2004) "A MuMipenod Model for the Accumulation Of
Empty Containers in Urban Areas" published by the XIII Pan American Conference of Traffic
and Transportation Engineering (CD ROM) Albany NY.
24.	(*) Thorson, E.. J. Holguin-Veras and I. Mitchell (2004) "An Appioadi for Solving the
Integrative Freight Market Simulation" published by the XIII Pan American Conference of Traffic
and Transportation Engineering (CD ROM) Albany NY.
25.. Seruya, B. and J, Holguin-Veras (2004) "The Role of Qualitative Research in 'Transportation.
Studies: Experiences from a Case Study"" published by tie XIII Pan American Conference of
Traffic aad Transportation Engineering (CD ROM) Albany NY.
26.	Holgum-Veras, 1, E. Thomson and K. Ozbay (2004) "Preliminary Results of an Experimental
Economics Application to Urban Goods Modeling Research" Annual Meeting of Transportation
Research Board, 2004
27.	Holguin-Veras. J. and E. Iftorsan (2003) "The Role of Experimental Economics in Freight
Transportation Research' Preliminary Results of Experimentation" Presented and published in the
Proceedings of the Association for European Transport's Annual Conference, Strasbourg 2003
28.	Holguin-Veras, J. and E Thorsoti (,2002) "Notes on Modeling Commercial Vehicle Empt Tup*"
published m the Proceedings of the Pan-American Congress XII (m CD ROM.), Quito. EcuaJoi.
Jose Httoas-Y«as	] g.
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19. Holsmn-Yeras. J. and E. Tliorson (2002) ''Preliminary Insights into- the Practical implications of
Modeling Commercial Vehicle Empty Trips" Proceedings of the Annual Conference of the
Association for European Transport, Hommerton College England.
30.	Holgum-Yeras: X and E. Thorson {2003) "Practical implications of Modeling Commercial
Vehicle Empty Trips" Annual Meeting of Transportation Research Boaid 2003
31.	Holgma-Yeras. J., K Ozbay, S_ Baker, D. Sackey, and A. Medina i.2003) "Towards a.
Comprehensive Policy of Nighttime Constnicticm Work'" Annual Meeting of Transportation
Research Board, 2003
32.	Holgvin-Yeras, J., D. Sackey, S Hussain, and V. Ochieng (2003) "On the Economic and
Financial Feasibility of Toll Trackways" Annual Meeting of Transportation Research Board. 2003
33.	Holguiii-Yeras, J., R. Paaswei and A. Perl (2002) "IntErorganBational Challenges and
Opportunities for Freight Automation Research si the United States" Proceedings of the FTAM
Conference, Delft University, The Netherlands.
34.	Holguin-Yeras, 1, Y. Lopez, and A. Salam (2002) "Track Trip Generation at Container
Terminals: Results torn a Nationwide Sureey" Annual Meeting of Transportation Research
Board, 2002
35.	Holguin-Yeras, I and Jara-Diaz, S. (2002) "Practical Implications of Optimal Space Allocation
and Pricing,"" in Ports* 98, Vol 1, pp. 89-97, Michael Kiaoaan, ed. March 1998. ISBN 0-7844-
0329-5.
36.	Holguin-Yeras, J. and E. Tliorson. (2000) "An Investigation of the Relationships Between the Trip
Length Distributions in Commodity-based and Trip-based Freight Demand Modeling." .Annual
Meeting of Transportation Research Board, 2000
37.	Holgum-Yeras, J. 12000). A Framework for an Integrative Freight Market Simulation. IEEE 3rd
Annual Intelligent Transportation Svstems Conference ITSC-2000, Dearborn Michigan, EEEE. pp.
476-481.
38.	Holguin-Yeras, I. and C M. Walton. (1996a) "On the Development of a Computer System to
Simulate Port Operations. Considering Priorities.' Proceedings of the 1996 Winter Simulation
Conference (ed. J.M. Chames, D.J. Momce, D.T. Bruimer, and I.J. Swain), pp. 1471-1478. The
Institute of Electrical and Electronic Engineers, New Jersey.
39.	Holguia-Veras, J. and C.M Walton. (1996b) ""The Role of Information Technology on 'the
Implementation of Priority Systems for Intermodal Containers." Proceedings of the 3rd Annual
World Congress on Intelligent Transportation Systems. Oilando, Florida.
40.	Holguin-Yeras, J. and C.M. Walton. (1996c) ""An Empirical Investigation of Alternative
Approaches to the Simulation of Gantry Crane Operations." Proceedings of the 3Sth Annual
Meeting of Transportation Research Forum, Vol. 2, pp. 459-477. San Antonio, Texas.
41.	Holguis-Yeras, J. and C.M. Walton. (,1997) "Implementation cf Priority Systems for Containers at
Marine Intermodal Terminals." Annual Meeting of Transportation Research Board, 1997
42.	Holguin-Yeras, J. and C.M. Walton (1996) "The State of the Practice of Information System, and
Information Technology at Marine Container Ports.'1 Annual Meeting of Transportation Research.
Board, 1996.
43.	Holguk-Veras, I. (1987) "The Calibration of the Leibbrand Model" Published by the Second
Transportation Congress, Santo Domingo.
44.	Holguia-Veras,, I. (1987) "Public Transportation: Informal vs. Formal Systems." Published by the
Second Transportation Congress, Santo Domingo.
45.	Holguia-Veras, J. et al. (1982) "Computational System for O-D Survey." Second (Latin
American) Congress of Transportation Engineering, Popayan.
Jose	17
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Non-refereed publications
1.	Holguin-Veras., I G List A, Mevbuig, K. Ozbay, R_ Paaswell, H. Teng. and S. Yahalom {2001)
"An Assessment of Methodological Alternatives for a Regional Freight Model in the XYMTC'
Region/" New York Ctt; Metropolitan Transportation Council •XYMTC), May 30,200!.
2.	Kinney, P., J. Holguin-Veras and M Carter, "Air Pollution and Traffic at Hunts Point,' Research
Report published by the University Transportation Research Center, October 2000,
3.	Holguin-Yeras, J. and CM. Walton (1997a) "Hie Performance Analysis of Priority Systems."
Research Report' SWUTC 97 4(T304-1, Center for Transportation Research, The University of
Texas at Austin, August 19'97: Austin, TX 78712.
4.	Holguin-Yeras, J. and C.M. Walton (1997b) "Range of Applicability of Priority Systems."
Research Report SWUTCr97'467304-2( Center for Transportation Research, 'The University of
Texas, at Austin, August 1997, Austin, TX 78712.
5.	Holguttt-Yetas, J. and CM. Walton {1995a) "A Categorized and Annotated Bibliography on the
Performance Analysis of Port Operations." Research Report SWOTC/95/7219I.2-I, Center for
Transportation Research, University of Texas at Austin. Austin, TX 78712.
6.	Holguin-Yeras, J. and C. Walton (1995b) "The Role of Information Technology cm the
Implementation of Priority Systems and The State of the Practice of Information System ad
Information Technology cm Marine Container Pons." Research Report SWUTC 96 721928-3,
Center for Transportation Research. University of Texas at Austin, Austin, TX 78712.
7.	Holguio-Veras. I. and C. Walton (1995c; "The Calibration of PRIOR A Computer System for the
Simulation of Port Operations Considering Priorities." Report SWUTC '96-721928-1, Center for
Transportation Research, University of Texas at Austin, Oct. 1995, Austin, TX 78712.
i. Holguin-Yeras, I and CM Walton (1995(1) "PRIOR, A Computer System for the Simulation of
Port Operations Considering Priorities:' Research Report SWUTC 96 721928-2, Center for
Transportation Research, The University of Texas at Austin. Oct 1995, Austin, TX 78712.
9.	Holguin-Yeras, I. and L, Simo [1984). "Methodological Framework for the Maintenance and
Rehabilitation Plan." Ministry of Public Works, Transportation Planning Department
10.	Holguin-Yeras. J. (1984) "Development of a model to quantify vehicle supply in freight
Transportation' Thesis (M.S. in transportation planning)--Universidad Central de Venezuela,
Institute de. Urbamsmo.
11.	Holguin-Yeras, J. (1984) "Definition of the Optimum Policy of Truck Import." Dominican
Republic 1984-1989. Ministry of Public Works
12.	Holguin-Veras,, I and M. Riibio. (1982) "Diagnosis of the Toll System." Ministry of Public
Works
5. CURRENT PROJECTS
~	"Collaborative Private-Pub lie Approaches to Foster Energy Efficient Logistics in the
Albany-New York City Corridor" ($2,000,000) US Department of Energy (2017-2020). This
project seeks to develop behavior-based policy approaches to foster changes in supply chains
to reduce fuel consumption.
~	"Role of Non-Established Relief Groups (MERGs) after Hurricanes Harvey, Irma, and
Mam" (SI20,000), National Science Foundation. This project is intended to collect
ffeldwork data about the performance of Non-Established Relief Groups.
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~	''Effective Decision-Making Methods for Freight-Efficient Land Use" ivS250 000), NCHRP
OS-111.This project seeks to develop models and methodologies to foster freight efficient
land uses.
~	"Methodology Implementation to Assess the Impact of Congestion on Supply Chains in
Haiti" {S8D,000), Inter-American Development Bank. This project intends to quantify the
impacts of congestion on the supply chains in Haiti using GPS data loggers.
~	"Freight Demand Model for Bangladesh" t$2:<0r000) Funded by the Woild Bank, this project
seeks the development of data efficient demand models for Bangladesh.
~	"Engaging Large Retailers on Off-Hour Deliver}- Programs" (United States Department of
Transportation. $100,000). This is a continuation effort that attempts to enlist the support of
nationwide retailers to foster off-hour delivery operations in large cities.
+ "Development of a Trusted Vendor Program to Support the Off-Hour Deliver/ Program"
NYSERDA. S30O,GOO
~	Volvo Research and Education Foundations Center cf Excellence on. Sustainable Urban
Freight Systems (COE-SUF5). This five years project is intended to foster an international
transformation of urban freight systems (Total budget: S3,800.009'
~	KCFRP 44 "Impacts of Policy Induced Modal Shifts" (National Cooperative Freight
Research Program. October 1, 2013, December 2014) (Total budget: $350,000) This
important project aims at the estimation of freight mode choice models.
6. COMPLETED PROJECTS
~	"Remote Sensing Decision Support T ools For Optimal Access Restoration. In. Post Disaster
Environments" This project will develop methodologies to optimally restore access in
transportation networks impacted by disasters (United States Department of Transportation,
$700,000)
~	"Methodology to Assess the Impacts of Congestion on Supply Chains" later-American
Development Bank ($200,000).
~	"NCFRP 25: Freight Trip Generation sad Land Use'' (National Cooperative Freight Research
Program, June 1, 2012, May 30w 2013) (Total budget 5400,000 Second phase)
~	"Pan-American Advanced Studies Institute on Sustainable Urban Freight Systems'" (NSF-
OISE-12421131. This project is intended to organize a workshop on Sustainable Urban
Freight Systems in Colombia t Total budget 5100,000).
~	"Cyber Enabled Discovery System for Advanced Multidisciplmary Stud}' of Humanitarian
Logistics for Disaster Response" (NSF-IIS 1124827) {.Total budget: S 1,510.0001 This project
aims at developing slate of the art models to deal with the unique complexities of
humanitarian logistics..
~	"Integrative Freight Demand Management in the New York City Metropolitan Area:
Implementation Phase" (United States Department cf Transportation): July, 1 2011-June 30,
2013; Co-PIs: Kaan Ozbay, and Alain Kornhauser; Total budget $3,200,000). This project
focuses on implementing off-hour deliveries in the NIT metropolitan area.
~	"Field Investigation on Post-Disaster Humanitarian Logistic Practices under Cascading
Disasters and a Persistent Threat: The Tchoku Earthquake Disasters"' (NSF-RAPID 1138621)
(Total budget: 550,000) This project is intended to identify the lessons to be learned from, the
response to the Tohoku disasters.
~	NCFRP 38 "Improving Freight in Metropolitan Areas (National Cooperative Freight
Research Program, June 1. 2012. May 3Qrt 2013) (Total budget: $450,000) This important
;	19
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project aims at defining techniques and procedures to increase the sustainability of freight
activity in urban areas.
~	' DRU: Contending with Materiel Convergence: Optimal Control, Coordination, and
Delivery of Critical Supplies to the Site of Extreme Events" (National Science Foundation
CMMI-GS240S3): January 2007-December 2010: Co-PIs: Tncia Wachtendorf, Satish
Ukkusuri. Total budget-S749,29S i. This project focuses on. the development of new
paradigms of supply chain mcdelmg integrating social sciences and logistics.
~	"RAPID: Field Investigation on the Comparative Performance of Alternative Humanitarian
Logistic Structures" (National Science Foundation NSF-RAPID 1034365); (Total, budget:
$51X000} January 2011 - December 2012, Co-PI Professor Tncia Wachtendorf. This project
gathered field data concerning the performance of the humanitarian logistic systems that
emerged after the Haiti earthquake.
~	"NCFRP 25: Freight Trip Generation and Land Use" (National Cooperative Freight
Research Program, January 1. 2010 March 31" 2011) (Total budget 5300,000 First phase)
~	"NCFRP 26: Freight Cost Data Elements"1 (National Cooperative Freieht Research Program,
July 1, 2010 December 31st 2011) (Total budget $300,000)
~	"New York City Park & Side Study" (New York State Department of Transportation)
December 15: 2008-June 14; 2010 (Total budget 5256,000)
~	"Feasibility Studv for Freight Data Collection" New York Metropolitan Transportation
Council (May L 2009-May 30a 2011) (Total budget 5100,000)
~	"Integrative Freight Demand Management in the New York. City Metropolitan Area" (United
States Department of Transportation); July, 1 2007-April 30, 2010: Co-PIs: Satish Ukkusuri,
Kaan Ozbay, and Drs. Allison de Cerreno and Alain Komhauser; Total budget $1.865.136).
This project focused on designing .and testing an innovative freight demand management for
the NYC metropolitan area.
+ '"A Smarter 1-278 Corridor: Moving People, Freight, and the Regional Economy, Phase F
University Transportation Research Center (Total budget 1145,000)
~	Director of 'the Center for Intermodal Freight Mobility .and Security (jointly with the
University of Mar/land); 2005-2009 Funded by the Federal Highway Administration (Total
budget: $700,000). This project focuses on the development of new modeling paradigms for
freight security and mobility analyses.
~	"SGER: Characterization of the Supply Chains in the Aftermath of an Extreme Event: The
Gulf Coast Experience" (National Science Foundation CMMI-0554949): February 2006-
January 2008: Professors Tncia Wachtendorf and Satish Ukkusuri are Co-PIs; Total
budget=$90.482j. This project gathered perishable data about formal and emergent supply
chains after Katrma.
~	"'Synthesis of Freight Origin-Destination Matrices from Intelligent Transportation Systems
Data (CAREER Award, CAREER- 0245165)" (National Science Foundation; March 2001-
February 2008; Total budget = $375,000). This project intends to develop techniques to
dynamically estimate OD matrices from ITS data for traffic control and planning purposes.
~	"Dynamic Game Theoretic Models for Urban Freight Systems" (National Science
Foundation CMS-0324380); August 2003-My 2007; Professors Terry Friesz and Warren
Powell Co-PIs; Total budget=$4S2.611). This project intends to develop anew formulation
for urban goods processes based on dynamic game theory.
~	"Impacts of Extreme Events: A Systematic .Analysis of Individual Travel Choice Decisions"
(National Science Foundation; CMS-0301391, May 2Q03-Febaruaiy 2007: Professors Robert
Jcs-s KQigmi-Vmm
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Paasweil and Chandra Bhat. Co-PIs; Total budget: 1249.573). This project assessed changes
on passenger travel behavior produced by the 9-11 attack.
~	"Potential for Off-Peak Deliveries to Commercial Areas" (New York State Department of
Transportation, January 2003-December 2006} (Total budget = S300.0QQ). This project
focuses on the definition of policies aimed at increasing off-peak deliveries to commercial
areas in New York City
~	"Pan-American Advanced Studies Institute on Transportation Sciences'" (National Science
Foundation OISE-0418035); August 2004-July 2005; Professor George List is Co-PI; Total
budget-597,060;. This project intends to create the foundations for long term collaboration
between American and Lata American scientists.
~	"Evaluation Study of the Port Authority of New York and New Jersey's Value Pricing
Initiative" (Federal Highway Administration Value Pricing Program January 2002 - March
2005: Tote! budget = $750,000). This project intends to assess behavioral and systemwide
impacts of the pricing initiative at the PANYNJ facilities.
~	''Evaluation Study of the New Jersey Turnpike Authority's Value Pricing Initiative" (Federal
Highway Administration Value Pricing Program: January 2002 - June 2005; Total budget =
$450,000). This project intends to assess behavioral and systemwide impacts of the pricing
initiative at the NJTA facilities.
~	"Impacts of Extreme Events on Passenger Travel Behavior" {Professor R. Paaswell is Co-
Principal Investigator) {National Science Foundation: April 1, 2002-March 31, 2003; Total
budget = S50J001 This project assessed changes on passenger travel, behavior produced by
the 9/11 attack.
~	"Integrative Freight Market Simulation" (National Science Foundation, CMS-1079266;
September 2000-August 2002; Total budget = $84,500). This project developed a new
modeling framework for freight movements on. .the. basis.. of a market equilibrium
formulation.
~	"'Human Factors in Nighttime Construction Zones" (New Jersey Department of
Transportation; October 20-00-Febniary 2001: Total budget = 585,000). This project focused
on analyzing human factors in nighttime construction zones to define strategies to mitigate
the negative impacts upon workers.
~	"North East Intranodal Transportation Corridor" (September, 2000- March 2001). This
project included freight demand modeling for the New York City metropolitan region
(funded by the Port Authority of New York and Mew Jersey).
~	"New Jersey's Links to the 21st Century" (Professor R. PaaswelL Co-Principal Investigator)
(New Jersey Department of Transportation; January 20 GO-Dec ember 2002; Total budget =
S650.00C]. This project modeled the relationship between economic development and
transportation to help define transportation policy.
~	' Strategic Plan for the Development of the Regional Freight Model" (New York
Metropolitan Transportation Council; January 2 GOO-May 2001; Total budget = $100,000).
This multi-university research project defined a development process for the regional freight
model to be developed by NYMTC.
~	"Truck-Trip Generation at Marine Container Temmls™ (PSC-CUNY; August 1999-My
2001; Total budget = 420,0001 As part of this project conducted in collaboration with the
American Association of Port Authorities,, data was collected and models of truck-trip
generation at container terminals were developed.
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~	"Operational Evaluation of the Integrated Incident Management System (IMS)" (New York
State Department of Transportation; 2000-2002; Total, budget = SI 10.000). This project
conducted a. before and alter analyses of the impacts of the IMS on interagency
communication.
~	"Demand Modeling for the Anillo Metropolitan® Project," Guatemala (Januaiy-Jime 1999).
This project included the demand modeling and forecast (both freight and passengers) of a
major bypass road in Guatemala City.
~	"Analysts of the Transportation Alternatives for the Grain Terminal," Dominican Republic.
Apnl-July 1991. It included the analysis of the terminal operations, multimodal alternatives,,
logistics and inventor/ policy for a neiv grain terminal
~	"Analysis of tSie Santo Domingo-San Cristobal Highway." Dominican Republic, Januaiy-
May 19SP. It included demand forecast, analysis of 'the alternatives and the economic
analysis.
~	"National Study of the Service Sector in tlie Dominican Republic." November 1988-Febnmy
1989. Financed by UNCTAD, this project focused on. the assessment of the impacts of free
market policies upon the transportation system, tourism and export sector. This analysis
helped shape the governmental position at the Uruguay Round of GATT.
+ "Panama's National Transportation Plan/" January-April 1988. It consisted of the calibration
of the modal split models, analysis of the intermoda! corridors, economic analysis of airport
projects (including the Marcos Gelabert airport), pipelines, railroads and port projects
{including port simulation), and formulation of the final investment plan.
~	"Formulation of the Widening Project of the Simon Bolivar Avenue,"" Dominican Republic,
August-November 1987. It included the design of alternatives, demand forecast and
economic .analysis.
~	"Institutional Development of the Dominican Port Authority.'" Dominican Republic,
September-October 1987. It included demand forecast for the port system and the
corresponding simulations, under contract with PRC-Harris. This project was financed by
Meramerican Development Bank.
~	"Rehabilitation Project of Rural Roads (Loan 98-FEDA-World Bank)," Dominican Republic,
August-October 198 7. It was comprised of the data collection planning, inspection of 300 km
of rural roads, the definition of the alternatives and their economic: analysis. This project was
financed by the World Bank.
~	"Economic Analysis of the Extension of the J.F. Kennedy Avenue" Dominican Republic,
May-June I9S7. It included the demand forecast and the economic analysis.
~	"Ex-post analysis of me Nunez de Caceres Avenue," Dominican Republic, May 1987 It
included the demand forecast and the economic analysis.
~	"Urban Plan for the Northern Zones of Santo Domingo City,' Dominican Republic, March-
April 1P87. This project considered the settlement of 250,000 people over a five year period.
The transportation plan for this urban development was developed.
~	"Evaluation of 180 km. of Rural Roads," Dom.mic.an Republic, March-April 1987. Under
contract with the Meramerican Development Bank, it included the formulation and
economic evaluation of the alternatives.
~	"Diagnosis and Perspectives of the Arterial System of Santo Domingo City," Dominican
Republic. January-February 1987. It was comprised of the comprehensive analysis of the
transportation needs and the demand forecast for the network oriented to the analysis for the
project, of the fourth bridge over the Ozama river.
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~	"Transportation Demand Forecast," January-August 1986, Transportation Planning
Department, Ministry of Public Works. Dominican Republic- It included the calibration of
the demand models and the definition of the alternatives.
~	"Pavement Maintenance and Rehabilitation Plan/' January-December 1936, Traosportatioa
Planning Department Ministry of Public Works, Dominican Republic. It included the
diagnosis of the network, the formulation of alternatives, and the implementation of a
Pavement Management System.
~	"Definition of the Fiscal Policy for the Transportation Sector," November 1986-May 1987,
Transportation Planning Department Ministry of Public Works, Dominican Republic.
~	"Analysis of the Railway Project La Vega-Santo Domingo." Dominican Republic. August
1985. Under contract tvith DELCANDA Intl. the demand forecast for passengers and freight
was done.
~	"Definition of the Optimum Foley of Track Import" Dominican Republic, January 1983-
August 1984. It included the definition of the import policy, the forecast of transportation
demand and supply, (including the development of fleet deterioration models), and the
development of a simulation system for the analysis of the alternatives and the quantification
of their impacts.
~	"Comprehensive Study of the Transportation System of the Capital Region,'' Venezuela,
June IPS 3- August 1984. The purpose of this study v. as the definition of an integrated policy
of land use and transportation that contributes to the decentralization of Caracas.
~	"Comprehensive Study of the Transportation System of the East Coast of the Maracaibo
Lake," Venezuela, February-May, 1983. It included the analysis of different policies of land
use and transportation by using transportation and land use integrated models.
~	"Institutional Study of the Ministry of Public Works,' Dominican Republic, 19S2. It
encompassed traffic studies, the definition of the optimum axle load for the highway system,
and the analysis of the toll system.
~	'Planning of the O-D Survey of Santo Domingo Ciry Dominican Republic, December
19S0-April 1981 It included the definition of the statistical frame and planning of the data
collection process.
~	"'Traffic Signal Coordination for the John F. Kennedy and Abraham, Lincoln Avenues;'
Dominican Republic, October-November 1979. It included the design of the system and the
economic analysis.
7. SERVICE WORK
At the Rensselaer Polytechnic Institute:
~	Chair of the Rensselaer Faculty (May 2014 - April 2 015 j
~	President of the Faculty Senate (May 2013 - April 20141
~	Vice-President of the Faculty Senate (February 2012 - April 2013)
~	Co-Chair of the 17541 Anniversary Committee {August 2009-2010)
~	Member of the Task Force on 'the Environmental Engineering Pi o gram (2009-2010)
~	Acting Department Head (December 2007-June 2009)
~	Member of the Executive Committee of the Rensselaer's RAMP-UP (Reforming Advancement
at Rensselaer) project (December 2007-June 2009)
~	Member of the School of Engineering Future of Engineering Committee (2006-2007)
~	Member of the Department Head Chair Committee (July 2005-August 2009)
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~	Member of the Graduate Program Committee al the Civil .and Environmental Engineering
Department (since Juh 20021
~	Chairman of the search committee for the seotechnical engineering faculty position {March
2003-March 2004)
+ Member of the Space Allocation Committee at the Civil and Environmental Engineering
Department (July 2002-20C3)
At The City College of New York:
~	Member of the CCNY Vice-President for Facilities Search Committee (February 2002)
~	Member of the CCNY President's Task Force oil Community Outreach (Dec, 2001-July 2002)
~	Doctoral Committee (2001- July 2002")
~	Member of School of Engineering Dean Search Committee (December 1999-June 2000)
~	Curriculum ABET Committee (1997-2000,1
S. STUDENT GUIDANCE
At the Rensselaer Polytechnic Institute:
~	Doctoral students Ellen Tfaorson (graduated in Spring 2005), Qian Wang {graduated in August
2008), Nrng Xu (graduated in August 2008), Michael Silas (graduated in August 200P1 Noel
Perez (graduated 1:1 2012). Miguel Jailer (graduated in 2012), Ivan Sanchez (graduated in
2014), Carlos Gonzalez (graduated in 2014), Felipe Arcs (graduated in 2014), Johanna Amaya
(graduated in 2016).
~	Current doctoral students; Shama Campbell, Lokesh Kalahashti, Trilce Encaniacion, Diana
Ramirez, and Nilson Herazo
~	Master students; Juan C. Zomlla (graduated iti Fall 2004). Shuwen Xia (graduated m Spring
200-). Brenda Cruz (graduated in Spring 2005), Nine Xu (August 2005), Ben Rem; (December
2006). Carlos Bastida tAugust 2007).. Pedro Canalda" (December 2007). Michael Preziosi (May
20CS l Coral Torres {August 2009). Brandon Allen (August 2009), Sofia Kyle (May 2016).
~	Advisor to the student chapter of the Society of Hispanic Engineers (SHEP'i
At The City College of New York:
~	Master students; Mostafa Kamal, Andrew Sakowkz, Abdus Salam, Amr Ibrahim.
~	Doctoral students; Judith Peter, Chang Guang, Victor Ochieng
f. COURSE AND CURKICCLUBrl DEVELOPMENT
New courses at Rensselaer Polytechnic Institute:
~	CIVL 6% 1; Critic al Issues on Transportation
Re-designed courses at Rensselaer Polytechnic Institute:
~	CIVL6230. Transportation Economics
~	CIVL6260; Transportation Algorithms
New comrs.es at CCNY:
~	CE2S4; Civil Engineering Data Analysis
~	CE5741; ITS Fundamentals and Applications
~	CE 5 5 42; GIS Transportatj on Modeling
Re-designed courses at CCNY:
~	CE 5 602; Transportation Economics
~	CE5635; Traffic. Engineering (redesigned as a. MI multimedia course)
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1#. PROFESSIONAL ACTIVITIES
Board Member of:
~	Me?; York State Thruway Authority (since July 2010)
~	Council of the Association for European Transport (Elected Member) (2005-2010)
~	Pan-American Transportation and Traffic Engineering Conferences (since 2005)
~	Council of Logistics Management's Western New England Roundtable (2004-2009)
~	Colegio Dominican© de Ingen:eros; Arquitectos y Agrimensores (1985-1986).
Member of award panels for:
~	National Science Foundation
~	Council of University Transportation Centers (CUTC)
Participation in professional societies and research panels:
~	Professional Engineer, New York (since 2000)
~	American Society of Civil Engineers (since 1999)
~	Member of the International Advisory Committee of the "Brain Korea" (BK) 21 Logistics
Team sponsored by the Ministry of Education in Korea at the Pusan National University.
~	Member of Transportation Research Board Technical Committees on: Freight Transportation
Planning and Marketing (A1BC2) (since 1991) and Intermodal Freight Terminal Design and
Operations A2MQ3 (since 1995)
~	Member of Transportation Research Board Task Force on Innovations on Freight
Transportation Modeling (AT0!6Ti (since November 2003 "i
~	Member of the C cuacil on Transportation (since 1999).
~	Member of Colegio Dotmmcano de Ingenieros, Arquitectos y Agrimensores (Board of
Engineers of Dominican Republic) since 1984.
National research panels:
~	Member of the United States Department of Transportation's 'National Freight Advisory
Committee, NF AC. iMa\ 2013 - April 2015).
~	Member of the National Academy of Sciences Review Committee of the United States
Department of Transportation's Truck Size and Weight Study mandated by the US Congress
(July 2013 - December 2013).
~	National Cooperative Highway Research Program i.NCHRP) Synthesis Panel (.2012;. 20-
05 Topic 44-01: FEMA and FHWA Emergency Relief Funds Reimbursements to DOTs
~	Strategic Highway Research Program 2 (SHRP 2) (2012) Capacity Expert Task Group (ETG)
for Freight Demand Modeling and Data Innovation Symposium (C43).
~	Transportation Research Board (TRB) (2012) "Adapting Freight Models and Traditional
Freight Data Programs for Performance Measurement" Chairman of the Pan-American
Advanced Studies Institute on Transportation Sciences (PASI-TS), Toluca and Queretaro,
Mexico July 24-August T4 2005
Invited lectures and chairmanships at professional conferences:
~	Invited to be the Distinguished Speaker at the David O'Brien Centre for Sustainable
Enterprise (DOCSE) on the subject of "Towards Sustainable Urban Freight Systems: The
Good, The Bad, and The Ugly" January 23*, 2014
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~	Burack Lecturer at the University of Vermont November 14th, 2013 on "Ike Lessons of
Large Disasters for Humanitarian Logistics"
~	Commencement speaker at the Institute Tecnologico de Santo Domingo, Dominican
Republic, October 12^, 2013
~	Plenary lecturer at the 6th International Conference on Management and Control of
Production and Logistics, Fortaleza Brazil on "The Lessons of Large Disasters for
Humanitarian Logistics: the Role of Industrial Engineers" September 124; 2013
~	Plenary lecturer at the Sustainable Smart Cities Symposium at the University of Alabama-
Birrningfcam April 3ri. 2013 oa ''Sustainable and Smart Urban Freight Transport"
~	Chairman of the Fan-American Advanced Studies Institute on Transportation Sciences
(PASI-TS), Toluca and Queretaro, Mexico July 24-August 7^2005
~	Conference Chairman of the XIII Pan American C oaference of Traffic and Transportation
Engineering, Crowne Plaza Albany, September 27-29 2004
~	Chairman of invited panels on applications of Intelligent Transportation Systems to
Commercial Vehicle Operations at the Intelligent Transportation Systems Council (ITSC-
IEEE i Conferences (2GQ0: 2001 and 2002).
~	In* itccl a? guest speaker at the Rebuild New York Conference, organized by Mr. Alan
Hevesi. Mew York City Comptroller (March 28. 2000).
~	Invited by the Government of Singapore to lecture on freight transportation and
transportation economics (November 1999}.
~	Invited to lecture by the Federal Highway Administration on Congestion Pricing and
Commercial Vehicle Traffic (January 1999)
~	Chairman of the session on Data Envelopment Analysis (DEA) at the Data Connection
Conference, New York December 1997.
~	Chairman of the session oa Strategic Data Sharing Alliances, organized by the Working
Group on New York City Area Data, Hew York Metropolitan Transportation Council
(NYMTC) January 1998.
Meferee foi the following professional Journals and professional conferences:
~	National Academies* Report on "Measuring International Trade on U.S. Highways" (2004)
~	Transportation Research A, B, C, D and E
~	Journal of the American Society of Civil Engineers
~	Transportation Research Record
~	Journal of the Transportation Research Forum
~	Decision Support Systems
~	World Conferences on Transport Research (since 7®)
~	Intelligent Transportation Systems Council (ITSC-IEEE) Conferences (since 2000)
11. PUBLIC OUTREACH ACTIVITIES
~	Professor Holguin-Veras is very involved in community activities and in policy making
activities that benefit the community at large. He has worked closely with a multitude of
community groups and grass root organizations including: The Point Community
Development Corporation, Nos Quedamos, Mothers in the Move. The Sports Foundation,
New York City Environmental Justice Alliance, and the like.
~	Speaker at Hie Dominican American National Roundtable (Washington. DC) (December 7-
10.. 2001).
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~	Liaison with the Association of Dominican Engineers, Society of Hispanic Engineers, Latin-
American Students Association.
4 Featured in newspapers articles (El Siglo, Manhattan Times, El Diario[, New York Post); and
TV programs (CBS News channel 47, February 3,1999).
~	Co-organizer of the Award to Meritorious High School Students. This important event, in
collaboration with the Dominican Consulate, has taken place at CCNY for the last three years
(1999, 2000 and 2001). Awards are given to 300 outstanding High School students of
Dominican descent. Fifteen hundred people attend each year the Award Ceremony at the
Great Hall of the City College of New York.
~	Speaker at the Dominicans 2000 Conference (held at CCNY, February 2000). The main
objective of this conference was to outline an agenda for the Dominican community in the
U.S. It attracted 1,400 participants.
~	Articulated a collaboration agreement between CCNY and the Instituto Tecnologico de Santo
Domingo, ENTEC (Dominican Republic) for teaching and research on transportation. The
agreement was signed by President Y. Moses and President Rafael D. Toribio Dominguez on
the 29* of July, 1998.
~	Articulated a collaboration agreement between CCNY and the Universidad Central de
Venezuela (Venezuela) for teaching and research on transportation.
12.	SELECTED PJTERYIEWS
~	On Sustainable Urban Freight Systems
o Interview after the David O'Brien Centre Distinguished Speaker Series (January 24,
2014) (https ::7www.youtube .com'watch?v=QgbQqKwx-SA)
+ On Disaster Response Logistics
o Interview after the meeting of the National Academy of Sciences' Disaster Research
Roundtable (March 11, 2011) (httpsi'7www-youmbexom/watch?v=0gGxNSqwOX4)
13.	LANGUAGES

Speak
Write
Rend
Elfish
Fluently
Fluently
Fhietily
Spanish
Fluenfly
Fluently
Fluently
9*
Jose Holguin-\ eras, Ph.D.,
P.E. William H. Hart
Professor, and
Director of the VREF Center of Excellence for Sustainable Urban Freight Systems
Jose Halgma-Yeas
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5.2 Dr. Amelia C. Regan
Amelia C. Regan
Professor of Computer Science and
Transportation Systems Engineering
University of California, Irvine. CA
949-228-8826
aregan'3uri.edu
http://faculty.sites.uci.sdu/aregan/
A. Professional Preparation
•	University of Texas, Austin	1991-1997
—	PhD in Civil (Transportation Systems) Engineering	1997
—	MSE in Civil (TVansportation Systems) Engineering	1995
•	Johns Hopkins University	1988-1990
—	MS Applied Mathematics	1990
> University of Pennsylvania	1983-1987
—	BAS Systems Engineering	1987
8. Experience
•	The University of California, Irvine
-	Professor of Computer Science, July 2009-Current
-	Professor of Civil Engineering (courtesy), July 2009-Current
-	Founding Director. Master of Computer Science Program 2015-2018
-	Faculty Director, MS and PhD Programs in Transportation Science (Interdisciplinary
Program). 2015-2018
-	Associate Professor of Computer Science, July 2008 - June 2009
-	Assistant and Associate Professor of Civil Engineering. March 1997 - June 2009
-	Associate Dean. Bren School of Information and Computer Science, July 2006-June 2009
•	University College Loudon
-	Reuben Smeed Memorial Professorial Research Fellow. Center for Transport Studies. March
2015-JuIy 2015
•	The Athens University of Economics and Business
-	Visiting Professor. Decision Sciences Summer 2002, Spring 2003, Spring 2004, Spring 2005,
Spring 200G
•	Technical University of Denmark
-	Visiting Professor, Operations Research Summer. 2003
•	The University of Texas, Department of Civil Engineering
-	Graduate Research Assistant, September 1991-December 1996
•	United Parcel Service/ROADNET Technologies, Baltimore, MD 1988-1991
-	Software Engineer/Operations Research Analyst/Industrial Engineering Supervisor
•	Association of American Railroads, Washington, DC 1987 - 1988
-	Research Analyst
C. Publications
Closely Related
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» Choi, E, and Jin, \V, ami	A )' 'J*. Ifr	•>-. i.; c u 'v	.-i '»i -!>-¦ -ai'i;
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Vt'ijfcdfiMihram.mian. N. fiJir \l t" >sl' Ad;'pii 1 >.n \ 1 'rc.t • m. s. I	-.u,j i I'm
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5.3 Dr. Yichen (Christy) Zhou
Updated My 2020
YiCHEX CHRISTY ZHOU
Ctemsoa University
John E. Walks*- Department of Economics
225 Waiter T. Cox Btad, Suite M-32QM, CiemsoiL SC, 29634
Email: yicheii3ff|'c1eiiisoB.eiiii
Website: Mtp:A"zhoii.Ye.com
EMPLOYMENT
Assistant ftofesaa: of Economics, Department of Ecoaotmcs, Gemsan University. July 2® 16-Present {On
Leave 2016-2017)
Postdoctoral Fellow, Resources for the Future (RFF), August 2016 - July 2017
EDUCATION"
PhD, in Economics, Unmn^r of Maryland at College Part May 2016
Dissertation: Essays in Energy, Environment and Technological Changs
Committee: Maureen Cropper (Chair), Andrew Sweeting (Co-chair), IM Banage, Sebastien Howie
MA. in Economics, University of Maryland at College Pant, May 2014
B.A. is Mathematics .and Economics, Distinction, University of Virginia, May 2010
B,A. student at large, Huazbang University of Science anil Technology, China, 2006-2008
FIELDS OF INTEREST
Environmental and Energy Economics, Empirical Industrial Organizalion
PUBLISHED AND ACCEFIED WORK
"The Effect of Fuel Price Changes on Fleet Demand for New Vehicle Fuel Economy", nidi Benj bob Lend,
Virginia McConaeB, The Journal of Industrial Economies 67, ao. 1,2019: 127-159
"The Effects of Fuel Prices and Vehicle Sales on Fuel-Saving Technology Adoption in Passenger Vehicles",
with Thomas Bur and Jo&na linn, Journal of Economics tf Management Strategy, 29 (3), 2020:
543-578
WORKING PAPERS
"Ho*' Much Do CtMwuums Value Fuel Economy anil Performance? Evidence too Technology Adoptin"
with Benjainiii Leard and Jodsn Lam, RFF Report, Jnly 2020, Third-round Revision Requested,
Review of Economics and Statistics
"Regulatory Spillover and Climate Co-benefits: Evidence from the New Souse Review Lawsuits", mitt
Hei-Sing Ron CStaa, January 2020, -Under Review
"Knowledge Capital., Technology Adoption, and Environmental Policies; Evidence from t&e US
Automobile Industry", February 201 6
SELECTED WORK IN PROGRESS
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Y. Christ)- Zhou Page 2 of 2
"The Effect of Adopting NextGen Air Transportation System on Air Travel Time and Jet Fuel Coanmptiaa:
Evidence from ffigh-fi-eqiimcy Air Trawl Data", wit Zqm Ota. May 2019
"Network Propagation and Air Traffic Policies", with. Tom Oaapug Lain, December 2019
TEACHIN G
Intermediate Meroeeontwaks, CkmscnUniversity, Spring 20IS—Present
fatrodactifln to Econometrics. Clemscn University, Spring 201S -Present
Computer Methods in Economics, Ifaivemty of Maryland, Spring 2012 - Spring 2013
GRANTS
Hayek Center for the Business of Prosperity on "Network Propagation and Air Traffic Policies" with Tom
Ctnmgsaiig Lam, Clemson University, 2020, $5,000
NBER Research Grant on "Economics of Energy Use in Transportation", Supported by tlie Department of
Energy, National Science Foundation, ani Affined P. Sloan Foundation, 2018- 2019, $16,289
Dean's Research Initiative Doctoral. Dissertation. Research Giant. Behavior and Social Science College,
University of Maryland, 201.5 - 2016, $2,500
OTHER EMPLOYMENT
Loot Mountain Fellow, Property & Environment Research Center {FER.Q, Montana, Simmer 2016
Summer Mem, Resources for the Future (KFF), Summer 2014, Summer 2015
CONIERENCE AND SEMINAR PRESENTATIONS
(* far Scheduled)
2021; ASSA-TFUG (Chicago)*
2019: NBER Ecooonii.cs of Energy Use in Transportation Conference, AEEE (Tahoe), Econometric
Society European Meeting, Southeast Energy & Environmental Economics Workshop (GaTech).
SEA-fadostoial Organization Society
2018: ASSA-AEA (Philly), NBER Energy Use im Transportation Fre^coufeience, DC IO Day (discussant)
2017: ASSA-AEA (Chicago), American University School of International Serra.ee, IFF. HOC Portss)
201ft Ohio University, Clenjsoti University, Arizona. State University. IMnsotv of Maryland Baltimore
County, HOC (FMly), PERC
2015: Maryland AREC, Maryland Eon, Northeast Workshop ©a Energy Policy ft Environmental
Economics (Yale), GenplraB GESE, Cany Resources
REFEREE AND OTHER SERVICE
Peer-reviewed Journals: Journal of Industrial Economics, Journal of the Association. of Environmental and
Resource Economists, Journal of Environmental Economics and Management, Energy Journal,
Energy Economics, Resource aid- Energy Ecoffl.otni.es
Ad Hoc Program Selection: SEA-AERE sessions, 2020
Ad Hoc Grant Proposal Bnins Alfred P. Sloan Foundation
DEPARTMENT AND UNIVERSITY SERVICE
Task Farce for the Tenure, Promotion and Reappointment Committee. 201" -201S
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5.4 Dr. Yan (Joann) Zhou
CttniciihanVita	Yan(Joaim}Zhou.	Septembe; 2G2D
Van (Joann) Zhou
9"00 S Ca;: Ave. Bias i6
Lanaoc:. IL S5439
EDVCATIOX
•	Ph.D. ia Civil Em.gim«rii»g (Tr»D.ipoit*fk>n)
CUm<.cn University, Clemsea, SC
« M.S. in Ciiil Eaginearing	2008
Clemson University, Clsase®, SC
« B.&. in Automotive Engineering	2003
Wnhin University of Technokipy. U'ohaa. P. 1_ China
WORKING EXPERIENCE
•	Cr«9 MR, Mobility and Deployment
ArgoKue National Laberatety, Argwuae, IL May, 20IS - Present
•	Princ>p*i Triasportatioa Systems Analyst
Argonae National Laboratory, Aigonne, IL Mar, 2012 - Present
•	Optralioii Manager,
UJ».-C3jiia Clean Energy Research Center-Clean Vehicle CcasninBt md TRUCE, las.., 2016-Piesent
•	Pojtdoetorjif R«st*rcber
Argtnme National Laboratory, Argonse, IL M»v. 2010 — Mar, 2012
AWARDS
« Lnnlipid Program, Cohort 3
Argonne Maternal Laboratory, Argoune, IL 1 .' 1
SELECTED PUBLICATIONS
Technical Report*
Y. Zhw, M., Marianne, T. Stephens, S. AescMiioa.ii, C. Mnd (2023) Electric Vehicle Adaption.inIllinois,
jtMJE5D-20.'"38. Septemba'. Available ob4dw skmhl
D. GsMke, Y. ZJ»#a (2020) Infracts of Electrification of Light-Duty Vehicles in tie United Stiles, 2010 -
2019, ASL.ffiSD-20'4. June. httos: /.^8nrw,.osti.eov-t'servIets''i»irll|'1^43114.
D, Gohlke, Y» Zi#o (20-19) Inspects ofEkctnJzcationof Light-Dnty Vehicles lafc United State, 2010 -
2018. ANL/ESD-19 ='2. Jarasarv. li,ttDsiir/www^sti.gQT^sgriitfe,%gal/I5^6474
M., Marianne. C. Maeal, Z. Gio, C. Kaligotia and Y, Zhou <2019) Ageni-B ased Transportation Energy
Analysis Model: Methodology and Initial Results. ANUESD-19/7, January,
https: /iwww.osti. gov/ senr kfe/psrFl S1S117.
La., 2tfeng? Yan Zk&o, Hao Cai, Michael Wag, Xan He, aad Steven Przesmitcki (2018) China Vehicle Fleet
Model.: Estimation of Vehicle Stacks, Usage, Emissions, and Energy Use -Mode! Description, Technical
DooEBB«ixkalio&, and User Guide. Argoime National Laboxatoiy, A'ML^SD-lSflS.. October.
T. Stephens. Y, Zhou. A. Bumham, and M. Wag (2011) Incemthrizing Adoption, of Plug-in Electric
Vehicles: A Review of Global Policies and Markets,, AN1/ESD4S^7. August.
h^5:/toww.osti.gcrc/5enrlet3/piirL'1480507.
A. Bnmham, A. Vyas, Y. Zhou and M. Wang (20IS) Assessment of Expanding Natural Gas Use in
Transportation, ANLESD-1 S/l I. May, https:»Vwww.cKti.fov''ser\,lets/pari,l1463249.
Page 1 of 4
Ema..	r:v
Phone: 630-2524215
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Cnnicalum Vila	Yan(Joann[) Zhou	September 2020
Y. Zhou (2811)	Energy And GransbMM Gas Baisubmt Ae;oa=liS( "Feat (NEAT):
DociiiDeolamoE. And User Guide: For Updated Domestic Freight Caraponemt, ANLflESD-lS.'5, May.
Iiftps	gor/serr lets,'pari'1433493.
Y. Zfcon, Vyas, A, Quo, Z. (20>17) Am Evaluation of the Potential &r Shifting of Freight fan Track, to Rail
sod Its Impacts on Energy 'Use and GHG HwnwKim, AJO/ESD-I.7/12, Report prepared fa DOE Vehicle
Tedmoiogies Office,
Y. Uso'ii, Levin, T.. and Flotkm, S. (2016) Plng-ia Elastic Vehicle Policy Effectiveness: Literature Review,
ANL/ESD/16-8, lipnt prepared fat DOE Office of Energy Policy and Systems Analysis, April,
Y, Zfcon, et. ai (2017) Electricity end uses, energy effieisney, and dmiilwiwl energy resources baseline,
Lawrence B-erisstey National Laboratory, LBNL-JO06?83, January,
Sitfps://eBip.lb!.go-s-/pisHic2ii€iDs,''rfeetiiatf-ead--Bses-energy.
Y. Zfco*, Vyas, A. (2014) VISION Model Description and User's Guide: Model Used to Estimate lite
Impaste of Highway Vehicle Technologies aai Fuels om Eneigy Use and Cation Emissions to 2100,
&HL/ESB'I4-L ktlc:.'1 ¦'"warig-ir3iiSBciifatiQn..3Bl-gB¥.''tidfs,frA',954.PDF
Jonrul Article
Bj, Z., Zlu» Y., Xm, F.t Lin Z., Wood E., Lea, D-Y (2020) QnanlificstioB of National Energy Impacts of
Eketaified Shared Mobility with Infrastructure Support, mbuutlwl to Journal qfEnergy My.
Hao, X, Zhoo, Y., Wang, H, Ouyang M. (2020) PImg-in electric vehicles m China aai the USA: a. technology
and market comparison, Mitigation and Adaptation Strategtesjor Global Change
Iiftps org/10.I007M 1027-01 9-09907-z
Zheng, J., Sun, 11, and, ZIn, Y. (2020) Electric Passenger Vehicles Sales and in Ckiaa's Leading Market
Journal of Cleaner Prodmc-Mem, Volume 243, IS January, 118607.
B'i, Zichfmg, Michael Reiner. Gregory KeoIadiiL Zhoo, Y., Michael Wang, aai Zhenhong Lai. (2019)
"Wireless charging and shared Maomw tattjr electric vehicles (W+SABEV): synergies that accelerate
sustainable mobility aat gnankNBt gas imAsmm redaction." Mitigaiisn and Adaptation Strstegiss for
Global dungs, https:tfdoi.org/ 10.1 WJh11.027-015-»878-9.
Gho, Z.,, .Zhcra, Z,» aad Zhon, Y, (2019) Impacts of Integrating Topology SaconfignratMa and Vehicle-to-
Giid Techaologi.es on Distribution System -Opaatio.il. IEEE Transactions oa Sustainable Energy. May,.
23mn,g, J., Zhss, Yit, 1., .Zhao, D., La,, Z., .ami Zhang, .P, (2019) SmtriI of Ckms Passeofer
Vehicles: A Data-driven Approach, Journal of Energy Policy, Volume 129. Page!!. 587-597.
Guo, Z. aid. Hem, Y. (2019) Residual Value Analysis Of Plug-la Vehicles Is The O.S., Journal qf Energy
Polity. Volume 125. fVbnBB?, Pages 445-455.
Huang, Y.., Zhou, Y. (2Q15) An Optimization Framework for Workplace Charging Strategies,
Transportation Rmmrek Part C,, pp 144-155 DOI lCL101€/j.tre.2Q15.€il.O22.
Zhou, Y,, Wang, M,. Johnson, L, Wang, BE., sod Hao, H. (2015) Plug-in Electric Vchide Maiket Pemetation
and Incentives; A Global Review, Mitigation and Adaptation Strategies for Global Change. Voltnn* 20,
Issue 5, pp 777-795.
Ha.o, H.. Wang M . Zh®ii, Y., Wang H . Ouyabi M , (2013) Tie Levelized Casts of Can«iili.onal tiid
Battery Ikeinc VaUcfes in Qnna: Beijing appanages, MMIgatim & Adapmtiom. Strstsgy far Gts&al
Clang'#, DOI: 10.1007fil 1027-013-9536-1, published online: 28 Deeemfeet 201.3.
Saafim, D., Zk«a, Y,, Kim, H., Gallagher, K . and Vyas, A.. (201.3) Plug-In Electric Cars far Wait Travel
Evainatum of Four Electric PswertraiE, Tramporiatton Rssearek Record, 2385, pp. 53-60
Zhou, Y., Vya#, A., and Smtini, D. {2013} Tiacfciag Hational Ho«sehoM Vehicle Usage by Type, Age, and
Ar«a in Support of Market Assessmeab for Flag-In. Hybrid Electric Vehicles. Journal of Transportation
r«bwfogi«,3, 174-1 S3,
Elg-ewainy, A„ Zksu, Y,, Vyas, A. Mabfik, M., Saatjui. D., Waag, M, (2012) Impact of Ping-in. Hybrid
Electnc Vehicle ChargiBg Choices in 2030, Transportation Research Rtcord: Journal qf Transportation
Research Bomi, "2287, pp. 9-17.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
Cnmculum Vita	Yan (Joann) Zhou	September 2020
P«r-Rn»ir«i Papers in Conference Proceedings
3i, Z., Zhou V., Xi». F., Lie Z.. Wood E., Lee, D-Y (2020) Quaniificaition of National Energy Impacts of
Electrified Shared Mobility with Infrastructure Support, Pmeemdmgz of 99fh Transportation. Research Boaid
Jbml Meeting, Washington, DC U.S., Jusory 5- 8,
Crtto. Z., Huang, 1., Zb»a Y., aaei Masai, Y. {2020) Agent-Based Modeling For Electrified Ride-Somcxng
Services, Proceedings tf 9ffe Transportation Research Bob! Animal Meeting, Washing!™, DC U.S..
January 5- 1,
Y, Zfco* ami M. Rood (2019) National Energy Itnpaeis of Heavy Electric Truck Adoption, tbr Freight,
EVS32 Symposium, Lyon, France, May 19-22.
Si® F_, Z, Lin,, Y. Zhou E. Wood (2011) Will Advanced Public Charging Liftastnicture Speed Up
Electrification of Future Transportation? 21st IEEE International Conference on Intelligent Transportation
Systems, November
Gun. Z., S Lei, Y. Wang. Z„ Zhou. Y. Zhou (2018) Dynamic Dtsonbatron lletweik Reconfiguration
Considering Travel Behaviors and Battoy Degradation of Electa* Vehicles, proceedings of 2017 Power sad
Energy Society Goad Meeting, July 1 §-20.
Z Goo. R Campbell, Y. Zfceo (2918) Residual Value Analysis Of Plug-In. Vehicle. In The U.s ,
Proceedings sf97ik Transportation Research Board! Annual Meeting. Washington, DC US, January 7- ii.
Campbell, R., Y. Zhou, Z, Lin, and I. Wait! (2017) Analysis of Mumfectanr Plug-fa. Electric Vehicle
iKHdim, Proceedings of 9€tl> Transportation Research Board .Anneal Meeting, Washington D.C.
ifcoa, Y,, D Santmi and T. Stephens (2016) Comparison of Vahie Retention of Plug-in Vehicles and
C ouvenftonal Vehicles and Potential C ontribuhc j Factors for presentation, Proceedings of 29ft. Electric
Vehicle Symposium, Montreal, Canada, Jus. 19-22.
Zhon, Y..s B. Santni, M. Rood, L. Bfciesiem, G. Mitchell, T. Stephens and J. Ward (20li) Ao Assessment of
Causes of PEV Success across U.S. Metro Aims, Proceedings «f 254 Electric Vehicle Symposium,
Montreal, Cauda. Job... 19-22.
Saniini, D . Y. Zhou. G. Mitchell, T. Stephens and J. Wad (2016) PIsig-m Vehicle Attributes'* Influence on
U.S. Sales is 2014 in Slates without Preferential Incentives for ZEVs, Prttemdmgs qfl'9ik Electric Vehicle
Svmpo->inm Montreal, Canada, Jim. 15-22.
Rood, M . D Santini, Y. Zhou, G. Mitchell, T. Stephens, 1. Miller and L. Bluestein (2018) Implications of
Successes sud Failures of BEV-Focuaed Incentive Support for PEVs in tlie U.S. aad EU, Proceedings o/2.9th.
Efeteic Vehicle Symposium, Montreal, Canada, Jun. 19-22.
Zhou, Y . Santini, D , Stephens, T.. Ward, J, (2016) Comparison of Vaha* Retention of Ping-in Vehicles and
Conventional Vehicles, mi Potential Contributing Factors, Proceedings tf 95th Transportation Research
Board Annua! ifoetmg•, Washington, DC, USA, Jan. 11-15.
Smilim, S... ZIhm. Y, (20151 Potential to Electrify Miles with Different Plug-in Vehicle BmcnnrtmB Paths,
PretseAifi &f*j4tk Transportation Emearch Board.imaalMmMttg, Washington, DC, USA, Jan.. 11.-15.
Sanrini D . Zbou. Y V. V. Ebnrc. Y X'l. and S... Gaeiisfer (2014). DtvUnt* CharpEg — What is Use
Hieorchy of Opporwmae: and Customer Need:? — A Case Study Band on Atlanta Commute Data,
qf!*ira T^inuipsrjjnm; Kezea'ch Beard Annual Masting, Washiagtaii, DC, USA, Jan. 12-16.
Santini. D.. Zhon. Y-. Stephens. T.. Vims. A. (20131 Cost Effactrra Annual Use and Charfmf Fr*q»eitcv for
Four Dittmm* Mtii-is Powa-teias,* S.AE Tsckacii Paper 201341-MM. 2M3, «:10.«7IQM3-01-04«,
prsssnted in As SAE ,2013 World Cocpns A Hxhibitaon, Detroit, Michigan, USA, Apr. 16-18.
Santini, D, Zh-ea, Y,, Eim. N., Gallagher, E„ and Vyas, A. (2013) Eteployiiig Phig-in Electric Cars Whkk
are 'Used fat Work: CorapalibiEty of Vaiyiag Daily Patterns of Use wtfii Feax Elacaic Pownbam
AichilKteras," Pmesedings sf 92md Trsmspariafism Research Board Jbmmd. Meeting, WssMmgfaii, DC,
USA, Jan. 13-17.
Stephens, T., Zhou, Y., Elgowainy, A.. Dtxiba, M.. Vjfas, A., Rousseau, A., (2013) Estimating On-Rsai Fnei
SoMoagr of FHEFs ia Test aai Agpe,gated Data, Procmiingi sf §2ttd Tmnspertmtisn Rssmreh Board
Ammm! Msetimg, Wssbm&m, DC, USA, Jan.. 3.3-17.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
L '.'XLviulam Vila	Yu (Joaan) Zhou	September 2020
Zkoa, 1% Vjw, A., Elgowamy, A,, Siatmi, D., (2012) Impacts of Multiple Daily PHEV Charging on
Electrified Idas aid Enorgy Demand. to ts pa¥lisiei in AveMtiifs afEVS 2&k International Electric
I'ektelm Sjinpeaimmr. Los Angelas, CA, May 6-9.
Santim, D., Zhou, Y,.. Vyas, A. (2012) An Analysis of Cw and SUV Daytime Parking for Potential
Oppartmiity Charging of Plug-m Electric Pcnvertrains — Effects on Hourly Electricity Demand and Tots!
Petroleum Use Reduction, to Im FoMkiwd in. Proceedhiga qf EVS 2&k Ifitfinmtiowal Electric Vehicles
Symposimsr; Los Angeles, CA, May 6-9.
Zfcan, Y., Vyn A,. Sadw, D. (2012) Tracking National Household Vehicle Usage by "type. Age, and Area
in Support of Market Assessments for Plug-in Hybrid Hectic Vehicles, Proceedings qfffl11' Transportation
Research Board Annual Meeting, Washington. B.C., Jan. 22-26.
Elgswainy, A,, ZkN, Y., Vyas, A, Mahalik, M_, Santim, D., Wane, M. (2012) Impact of Plug-in Hyfcrid
Electric Vehicle Charging Chokes m 2030, Proceedings qf 91"" Transportation Research Board Amaal
Memirtg, Washington. B.C., Jan. 22-26.
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/QTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
6 Agenda for Peer Review Teleconference
This section presents the 2-page agenda for the November 4, 2020, peer review teleconference.
AGENDA
November 4, 2020 Peer Review Teleconference
Analysis of Heavy-Duty Vehicle Sales Impacts due to New Regulation
12:00-
12:10pm
(10 mins)
Welcome and Introductions; Review of Agenda/Process for Peer Review Teleconference: Amy Doll,
EnDyna, Peer Review Lead; Kirsten Franzen, RI'I International, RTI Project Manager
12:10-
12:15pm
(5 mins)
Background on Draft Report: Gloria Hefland. EPA/OTAQ
Brief overview of Project History and Objectives section of Peer Review Materials Package
12:15-
12:20pm
(5 mins)
Scope of Peer Review: Amy Doll, EnDyna, Peer Review Lead
Review of Charge for (he Scope of this Peer Review section of Peer Review Materials Package
12:20-
12:35pm
(15 mins)
Clarification questions related to Charge Questions #2, #3, and #5: Kiisten Fran7.cn/Amy Doll
1) Provide clarification about analytical assumptions for how the potential regulation would affect actual
purchases- The authors review the industry background hut could do it in a way that is directly related to the
identification in Eq(4). For each round of the regulation, the mandate is effective on specific model years
(MY) and onward. (I understand the authors state model year may not be relevant since the way the business
works is through bargaining for a fleet of vehicles and through doing made-to-order.) As example scenario, if
a 2007 regulation will affect all new trucks in MY 2007. at the end of 2006 or in early months of2007, can a
buyer specify an order of an older model to get away from the regulation? This will create wiggle room for a
buyer to make a purchase that is in the short run exempted from the regulation. This is important because
readers need to know exactly what heta4 and beta5 arc identified from. This scenario I suspect does not mean
the identification in Et|(4) is invalid, but if that scenario is possible and if buyers do that a lot. the effect of
pre-buv and low-buy can be even higher (aka authors find a lower bound).
12:35-
12:50pm
(15 mins)
Clarification questions related to Charge Questions #2, #3, and #5: Kirsten Franzen/Amy Doll
2) Have the authors considered about how manufacturers can manipulate the price? HDV is not concentrated
as the LDV market, so I am fine with the price-taker assumption. But since there is a bargaining process, it is
important that analyses arc not picking up effects of lower prices in December and higher prices in months
after the regulation during the bargaining process.
12:50-
1:05pm
(15 mins)
Clarification questions regarding Charge Question #4 on technical methods: Kirsten Franzen Amy Doll
3) Why do the authors change how they describe their model: in the introduction, the authors say they use
time-series methods, then in the main analysis, the authors say they use difference-in-differences. llten when
the authors show the equation and die results, it appears the authors use an event-study model. I am not able to
comment on this charge question since I am not sure whether authors are doing (i) event-study without a
control group, or (ii) event-study with a control group by using no-regulation-change years as a control, the
latter of which is essentially a diff-in-diff in the event study-format. I think the confusion arises from (a)
unclear subscripts in Eq(4), (b) notation of the month variable (it is unclear whether the month variable refers
to the month in the datasct or if the authors mean the month-of-year), and (c) a lack of discussion of
identification after Eq(4), all of which could be easily explained.
l:05-l:20pm
(15 mins)
Clarification questions regarding Charge Question #4 on technical methods: Kirsten Franzen'Amy Doll
4) Can the authors or EPA clarify whether the Agency requires this analysis to extrapolate the results to
implications on elasticities? Changes in price are associated with changes in sales for factors correlated to
both. In addition to the common cndogcncity issue, the price measure is a sales-wcightcd-price so it has a
limitation in what this variable measures.
1:20-1:45pm
(25 mins)
Additional Clarification Questions (if any): Kirsten Franzen/Amy Doll
Any such scientific technical questions should be related to improving a reviewer's ability to respond
effectively to a specific Charge Question, and must be within the Charge for the Scope of this Peer Review.
1:45pm
Adjourn: Amy Doll, EnDyna, Peer Review Lead
1
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/QTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
Peer Review Teleconference "Ground Rules"
•	All external peer review is intended to solicit individual reviewer feedback, to increase the independence
of the peer review process.
•	The peer reviewers are not asked to, and should not attempt to, form consensus or collective
recommendations, ratings, or opinions, and peer reviewers must understand that they should provide
individual feedback on the research product.
•	Any EPA staff that may attend the peer review teleconference can only provide background information
on the research product to the peer reviewers, which can occur only during the teleconference run by
EnDyna, and at EnDyna's request.
•	The peer review teleconference w ill not include discussion related to EPA's policies and decisions or
current or proposed EPA regulations.
EPA Charge for the Scope of this Peer Review
EPA has defined the scope of this peer review for the ERG draft report in order to focus the peer review process
effectively on EPA's Charge Questions. Your written comments should stay within the EPA scope defined
below.
The scope of this ietter-stjie peer review is technical in nature, renewing the methods, data quality, data
sources, underlying assumptions, and the overall strengths and limitations of the study. EPA is especially
interested in comments that focus oil the validity or scientific merit of the methodology and that identify
any significant weaknesses in the scientific information from the methodology.
•	Peer reviewers should focus on providing comments on the technical nature of the report, and its
consistency with the state of current science as you understand it. The peer reviewers should
evaluate the analysis used to develop the proposed methods and the suitability of those methods to
estimate sales, pre-huy, and other impacts for use in policy analysis.
•	Peer reviewers should also focus oil the clarity and completeness of the presentation in the draft
report. Because the review is technical in nature, the peer reviewers should not focus on editorial
style.
Work Scope and Schedule
Your function as a peer reviewer is to review and provide written comments on the ERG draft report.
Specifically, you shall evaluate the KRG drafl report, respond to EPA's Charge Questions provided [in Charge
Document, included within Peer Review Materials Package], and provide specific comments that you feel could
improve the quality of the report. You are not requested to and should not provide input or advice on EPA's
policies, regulations, or policy/regulatory decisions. Your review is not page-limited, and you should take as
much space as you feel is necessary to complete your written responses to EPA's Charge Questions.
KEY PEER REVIEW DATES
Receive Peer Review Materials Package
October 13, 2020
Attend and Participate in Peer Review Teleconference
November 4. 2020
Complete and Submit Final Written Comments
November 20, 2020
2
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/QTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
7 Conflict of Interest Form and Non-disclosure / Confidentiality
Agreement
U.S. Environmental Protection Agency
Conflict of Interest Inquiry
You are being considered to sen'© as a Peer Reviewer for an EPA report tentatively entitled. Analysis of Heavy-
Duty Vehicle Sales Impacts Due to New Regulation, and your involvement in certain activities could pose a
conflict of interest or create the appearance of a loss of impartiality in your review. Although your involvement
in these activities is not necessarily grounds for exclusion from the peer review, affiliations or activities that
could potentially lead to conflicts of interest are included in the table.
Please complete the table and sign the certification below. If you have any questions, contact the Peer Review
Lead. Amy Doll, at EnDyna, Inc. (adolltf endvna.com) at your earliest convenience to discuss any perceived
conflict of interest issues. Please refer to the section below: "Information Relating to Conflict of Interest."
Conflict of Interest Analysis

YES
NO
1. To the best of your knowledge and belief, is there any connection between the subject
chemical or topic and any of your and/or your spouse's compensated or uncompensated
employment, including government service, during the past 24 months'?


2, To the best of your knowledge and belief, is there any connection between the sub ject
chemical or topic and any of your and/or your spouse's research support and project
funding, including from any government source, during the past 24 months'?


3. To the best of your knowledge and belief, is there any connection between the subject
chemical or topic and any consulting by you and/or your spouse, during the past 24
months'?


4. To the best of your knowledge and belief, is there any connection between the subject
chemical or topic and any expert witness activity by you and or your spouse, during the past
24 months'?


5. To the best of your knowledge and belief, have you, your spouse, or dependent child, held
in the past 24 months, any financial holdings (excluding well-diversified mutual funds and
holdings, with a value less than $15,000) with any coimection to the subject chemical or
topic?


6. Have you made any public statements or taken positions on or closely related to the subject
chemical or topic under review?


7. Have you had previous involvement with the development of the document (or review
materials) you have been asked to review?


8. To the best of your knowledge and belief, is there any other information thai might
reasonably raise a question about an actual or potential personal conflict of interest or bias?


9. To the best of your knowledge and belief, is there any financial benefit that might be gained
by you or your spouse as a result of the outcome of this review?


10, Compensated and non-compensated employment (for panel member/peer reviewer and spouse): list
sources of compensated and uncompensated employment, including government service, for the
preceding two years, including a brief deseription of the work.
1 of 4
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
11, Research Funding (lor panel member peer reviewer): list sou rues of rexearvh support and piojeet funding,
including from any uovcmmetit. for Hie pi seeding two years for which the panel member peer re\ iewer
served as the Principal investigator. Significant < 'ollaborator, Project Manager or Director, for the panel
in ember peer retiewer's spouse, ptovidc a general description of the spouse's research ami project
>wtn ities. for the preceding two years.
12. Consulting (for panel member peer review or): list .ill compensated consulting activities during the
preccding two (2*1 \ earn, inuluding the names of the client* if compensation provided 1 5"
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
16. Public Statements: Provide a brief (inscription of an; public statement find or positions taken that are
closely related to the mattci under rev lew h\ the panel member 'peer reviewer
17, invohwment vuth document under review. Provide a hrtef description ol' am prev bus mvoh ement of the
pone! member peer reviewer ill the development of the document (or rev icw materials) the indi\ idiiai ha«
been asked to review.
1S. Other potentially relevant information: iYov ide a brief description of anv other information that might
reasonably raise a question about actual or potential personal conflict of interest or bias.
n u m k \no\
I herein* certify that I have read the above statements and. to the best of my knowledge and belief, no
conflict of interest t.xtsh that max diminish my capacity to pro\ ide Hit impartial, technically sound,
objective review of the subject matter or otherwise result iti a biased opinion.
Name ¦¦ please print-
Signature:
l>jte
3 of 4
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
Information Uclatint; lu ( oiillict of Init io! (( (>1)
Peer rc\icwer,s arc espected to provide an impartial, technically sound, objective, independent, and unbiased
technical review of the study entitled*
Ihk/vv/.s of 1/t'i m - Unh I 'chick' Sales im/mcls Dttc to N(w Regulation.
We request the information in this CO! Inquiry Iron) interested peer reviewer candidates for the purpose of
ruling out CO! and other concerns as v\e work' to create an independent and balanced selection of peer
reviewers. An interested peer reviewer candidate's involvement in certain activities could pose a COl or create
the appearance of a loss of impartiality in the peer review. .Although involvement in such activities is not
necessarily grounds for exclusion from the peer review, peer reviewer candidates need to disclose affiliations,
interests, activities, or relationships that could lead to perceived COls,
Before you can be selected and agree to serve as a peer reviewer, yon will need to disclose any Actual or
Potential COl (as explained below) on this form. Tlie financial and professional information obtained from the
interested peer reviewer candidate as part of the evaluation to determine the existence of an Actual or Potential
COl is considered private and non-disclosahtc to outside entities except as required In law and'or regulation.
"lite following definitions provide general descriptions of Actual or Potential COl'
•	Actual COl; An Actual COl would be any financial interest held by an individual (or certain related
persons) thai could he affected by their participation in the peer review.
•	Potential COl: A Potential COl could be any circumstance related to an individual (or certain related
persons} that may cause ""a reasonable person with knowledge of the relevant facts" to question the
individual's impartiality in participating in the peer review (I.e.. "an appearance of loss of impartiality").
To preserve the independence and ethics of the peer review process, individuals w ith Actual or Potential Ceils
ma}' not be allowed to participate in the peer review, Please consider carefully whether you might have an
Actual or Potential CO! or if any other interests, activities, or relationships would cause your impartiality as a
peer reviewer to be questioned.
if) ou have any questions, contact the KrtDvna Peer Re\ iew Lead. Amy Doll (;tdoll-
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U.S. Environmental Protection Agency/Office of Transportation and Air Quality (EPA/OTAQ)
Contract Number EP-C-16-021 / WA 4-34
PEER REVIEW SUMMARY REPORT - Draft Final
N mi-Disclosure / Confidentiality Vjirirnicnt
Peer reviexxeis arc to ptoviik- written exmimenb. rcsponsixe to the charge questions in a specified formal by a specified
deadline. I agree to u\« the in form at ton revealed during peer review of the:
l-TA draft report tentatively entitled..!fo/wiv oflhxivy-Dnty I 'ehieL: Sukw Impact-, ihic
fo AVw fcc'tfiLttirm
onlv for t ",S. l-'nviromnentnl I'rotoction \goncy (l-'i'A) peer review purposes and understand that f must treat all of the
information as confidential and proprietary,
I also a woe to treat all of the supplementary information as. confidential and propi ietary, if any such
supplementary background materials) are prox ided for this puer rex ic-w.
•	Fees reviewers must comply with requests for confidentiality. as stated aboxe. regarding the rvkasu of draft
Agency products, positions or oilier tnatci iai« provided to the reviewer, 111 reports, spreadsheets, ami any other
background materials provided as pari of the review should be kept confidential and should not be discussed or
.shared With anyone, except the HnDyna I\wr Rexiww Lead: Ms. Amy Doll lorRTl l'eer Rexiexx Lead: Ms.
Kirstcn Pranzen),
•	Peer tm i ewers must avoid interactions including with .Vgeney representatives or members of the interested
puhhe that mialit create a perception of conflict of inlet est regaidmg the work product under review lixetcise
due care Its at did any actual 01 pcreuixxcl ctmllict of interest in earn ing out this peel review.
» Peer rex lexers should immediately infoim lite HnTHna (or R 1*1) Peci Review Lead if tile's are contacted regarding
this peer review or work product l\\ anyone else ltnl>\na will immediately inform LI'A of any such reports by
peer rex iew ers to guard against inappropriate influence from outside the selected peer rex ieu er>.
•	Peer rexiewt»*< will advise the FnDytia (or RTI) Peer Rexiew Lead of the disclosure of any information related to
this peer lexiew that is disclosed, used, 01 handled in a manner inconsistent with this agreement.
If in the course of this peci review , I do acquire or have access to any inlbinution, data, or material which is confidential,
proprietarx. or otlieixxisc prix ileyed. and is so indicated in writing. I agiec that such information xxill not be divulged to
am person or an) organization 01 utilized for mv ow n pi ix ate purposes 01 tn any mannei w hatsoex er. other than tn the
performance of this peer feviexx:
1.	without the pnoi written permission otTnPytM (orRtl) Peer Review f,cad ioi the work homg ex aluated, or
2,	until such information, data, or material is first publicly disseminated by the EPA or its contractor or grantee
performing the work, or
5 js or becomes known to the public from a source othei than mt or
4. is already known tome or my empkner as shown by poor lecurds, whichcxei exent shall first oceui, and this
knox\ ledge was ahead} disclosed in my signed Conflict of interest (I'OI) form,
\fteT this peel' rex iew, I xx ill destroy and or delete all reports, spreadsheets, and any other background materials related to
this peer review.
(Signature)	(Date)
(Xante!
Print od or Typed
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