MEASURING INDUCED TRAVEL DEMAND
FROM ROADWAY CAPACITY EXPANSION:
AN EMPIRICAL ANALYSIS OF THE
U.S. MID-ATLANTIC REGION
FINAL REPORT
Energy and Environmental Analysis, inc.
1655 NORTH PORT MYER DR ARLINGTON, VIRGINIA 22209
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MEASURING INDUCED TRAVEL DEMAND
FROM ROADWAY CAPACITY EXPANSION:
AN EMPIRICAL ANALYSIS OF THE
U.S. MID-ATLANTIC REGION
FINAL REPORT
Prepared for:
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Policy, Planning and Evaluation
401 M Street, S.W.
Washington, D.C. 20460
Prepared by:
ENERGY AND ENVIRONMENTAL ANALYSIS, INC.
1655 North Fort Myer Drive, Suite 600
Arlington, Virginia 22209
Under subcontract to:
SIERRA RESEARCH
1801 J Street
Sacramento, California 95814
Contract 68-D4-0102, Work Assignment 4-15
September 30, 1999
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TABLE OF CONTENTS
Page
1 INTRODUCTION AND BACKGROUND 1-1
1.1 Induced Demand: The Issue and Underlying Economy Theory 1-2
1.2 Analysis Methodology 1-6
1.3 Data Description 1-8
2. PRELIMINARY DATA ANALYSIS 2-1
3 RESULTS OF ECONOMETRIC ANALYSIS 3-1
3 1 Base Model Run Results 3-1
3 2 Short/Long Run Elasticity Run Results 3-7
3.3 Low/High Traffic Volume Run Results 3-8
4. SUMMARY AND CONCLUSIONS 4-1
REFERENCES R-l
APPENDIX A. DETAILED RUN RESULTS
APPENDIX B: CORRELATION MATRICES
APPENDIX C DATA LISTING FOR DC AND DESCRIPTION OF DC METRO AREAS
APPENDIX D: COMPLETE LISTINGS FOR BASE RUNS
i
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LIST OF TABLES
Page
Table 2-1 Average County Values of Key Variables in 1995
(by State and Area) 2-2
Table 2-2 Average Annual Growth Rates of Key Variables (by State and
Area and First Year to Last Year of Available Data) 2-4
Table 2-3 Data Distributions (Number of Counties in Each Category in 1995) 2-6
Table 2-4 All States Logarithmic Correlation Matrix 2-7
Table 3-1 Summary of Base Run Results .... 3-2
Table 3-2 Summary of First Difference Run Results 3-6
Table 3-3 Summary of Short/Long Run Elasticity Results 3-9
Table 3-4 Traffic Volume Interaction Models 3-11
Table 3-5 Population Density Interaction Models 3-12
n
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LIST OF FIGURES
Page
Figure 1-1 Schematic Representation of the Impact of Roadway
Expansion on Travel 1-3
111
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1. INTRODUCTION AND BACKGROUND
This report documents the analysis undertaken by EEA under subcontract to Sierra Research Inc.
for the work assignment (EPA Contract No. 68-C7-0051) WA 1-01 This analysis focuses on
estimating econometric models of "induced travel demand", using data from the U.S. Mid-
AtJantic region, in a database that was developed by EEA mostly under a previous work
assignment (and under a different contract). Documentation of this database is provided in a
previous EEA report "Measuring Induced Demand and Emissions Impacts from Transportation
Facilities, Database Documentation and Preliminary Analysis"1
The principal objective of this analysis is to develop econometric models to empirically test the
relationship between vehicle travel and roadway capacity, while controlling for other potentially
important factors that affect travel. The basic hypothesis to be tested is that additions to roadway
capacity (measured here as increases in lane miles) have a significant positive impact on travel
(measured here as daily average vehicle miles of travel, or VMT).
The following section provides a discussion of the phenomenon known as induced travel
demand, and how this analysis address the questions surrounding the issue. This is followed by a
description of the methodology and database used in the analysis. Section 2 provides a basic
analysis of the data and a comparison of the study areas. Section 3 provides the principal results
and interpretation of the econometric analysis. Section 4 provides a brief summary of the
findings, and conclusions that emerge from the analysis. Several Appendices provide additional
results and other background information.
' Under Subcontract to Industrial Economics Incorporated, EPA Contract 68-D4-0102, WA 4-15,
September 1998
1-1
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1.1
INDUCED DEMAND: THE ISSUE AND UNDERLYING ECONOMIC THEORY
The concept of "induced demand" involves the idea that additions to roadway capacity result in,
or induce, increases in vehicle travel on the roadway above the level that occurred before the
capacity addition, after accounting for other exogenous travel factors such as changes in
population Whether, and to what extent, addition of roadway capacity "induces" additional
travel, has been a cause of controversy in recent years. If this is the case, it suggests that some of
the benefits of roadway capacity expansion are eroded by this travel response (such as reductions
in traffic congestion).
As mentioned above, the basic hypothesis to be tested in this analysis is that this relationship
exists: that expansions to highway capacity yield increases in travel, over time. This analysis
tests this hypothesis using data at the county level of aggregation: do increases in the total lane
miles of major roadways in a county result in increases in travel on those roadways? An
additional hypothesis tested here is that the "rebound" effect (the increase in travel that occurs
after a capacity increase) will be stronger in areas with higher traffic volumes (and that
presumably experience more congested travel) than areas with lower traffic volumes.
The basic theory underlying the concept of induced travel demand is straightforward and well
documented and requires little treatment here. The addition of roadway capacity, either through
additional miles of roadway or additional lanes on an existing roadway, improves traffic flow and
therefore lowers the time cost of travel. At some level of congestion, any given driver will
choose to avoid dealing with that congestion, either in favor of an alternative route, an alternative
mode, changing the departure time of the travel, or avoiding the trip entirely. This is illustrated
in schematic form in Figure 1 -1 Since each traveler experiences declining utility with each mile
traveled, at some point the cost of travel exceeds the benefit to the driver. Increasing time cost
associated with increasing congestion will, in part, determine this point. This is shown as point
"a" in the figure. If, however, congestion is relieved through the addition of roadway capacity,
the entire cost curve shifts outward (reflects a shift toward lower travel time cost). This allows
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higher aggregate levels of travel before a given level of congestion is reached. The effect is
shown in the figure as a shift of the time cost curve and a movement of the equilibrium point
along the demand curve from point a to point b. A reduction in time cost from point plop'
yields an increase in travel level from point q to q'.
FIGURE 1-1
SCHEMATIC REPRESENTATION OF THE IMPACT OF
ROADWAY EXPANSION ON TRAVEL
Miles of Travel
However, while this underlying economic relationship is conceptually straightforward, there are
at least two controversies surrounding its implications for roadway capacity expansion. The first
is the specific nature of the relationship between capacity expansion and "induced" increases in
travel (the size of the rebound). The second is whether the existence of this relationship indicates
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that roadway capacity expansion provides, on net, costs or benefits to society This analysis
focuses on the first of these questions
While this study does not directly address the second issue, it should be noted that the size and
nature of the effect has important implications for whether capacity expansion provides net
benefits to society. A large rebound effect, for example with an elasticity near -1, indicates that
nearly all the congestion benefits of highway expansion are lost to increased traffic volume (over
whatever time period the elasticity applies). On the other hand, it also suggests that there must
have been considerable "pent up" travel demand that was released when the cost of driving was
lowered Conversely, a small rebound effect, for example with an elasticity near -0 1, would
indicate that most congestion benefits from capacity expansion are retained, and also that there is
not significant latent travel demand going unfilled. The relative importance of these two effects
(lost congestion reduction benefits v. additional travel benefits) are at the crux of the debate
regarding whether capacity expansion is still worthwhile in the face of an established presence of
induced demand. Of course, from an environmental point of view, a failure of increased capacity
to reduce congestion suggests that capacity expansion is likely to be a poor approach to reducing
vehicle highway emissions. Highway development also may have important impacts on how and
where communities are developed, which too may have a variety of impacts on the environment.
It should also be noted that any findings of a significant presence of a travel "rebound" effect to
capacity additions, or the existence of "induced demand", from this study should not be
interpreted to mean that all roadway capacity expansion projects will suffer from this effect.
Given the aggregate nature of the data used in this analysis, it would be inappropriate to draw
conclusions about induced travel effects on any specific project. The conclusions from this
analysis are relevant primarily at a general policy level - in general, does capacity expansion
trigger a significant increase in travel levels? For any specific project, more detailed analysis of
existing travel conditions and other factors would be required.
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1.1.1 Recent "Work Estimating the Nature of Induced Demand
Recent papers by Hansen and Huang (1997) and Noland (1998) provide a review of recent
literature on estimating the relationship between roadway capacity expansion and induced travel
These two papers themselves provide important contributions to measuring this relationship
Hansen and Huang focus on metropolitan areas in California, using 17 years of panel data They
estimated fixed effects models that included lane miles by roadway type, population and income
per capita. Their results were significant and indicate a strong relationship between lane miles
and VMT. They estimated long run elasticities on the order of 0.6 to 0.7 for counties and 0.9 to
1.0 for metropolitan areas.
Noland conducted a similar analysis using U.S. state-level data with 13 years of panel data,
including a variety of roadway types He estimated a variety of fixed effects specifications and
distributed lag models. He estimated elasticities ranging from 0.3 to 0.6 short run and 0.7 to 1.0
long-run, on a nation-wide basis.
The analysis presented in this report follows these two previous efforts methodologically, but
provides two new contributions:
• It uses East Cost data to test the structure of the VMT - lane mile relationship in states
with many older, long - established communities.
• It provides a more detailed investigation of the differences in the VMT - lane mile
relationships across different types of counties, varying by population density and traffic
volumes.
In particular, this analysis attempts to address the question of whether induced demand occurs
differentially in areas that are initially low traffic volume (but in some cases high population
growth) v. areas that are more heavily congested but that are essentially fully developed. One
hypothesis is that areas that are newly developing will show a bigger difference between the short
run and long run elasticity than more established areas, since the effect of new roadways may be
to spur new development which will not occur immediately, but over a period of years or even
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decades. In fully developed areas with traffic congestion, the effect of adding roadway capacity
on inducing additional travel may be more immediate.
1.2 ANALYSIS METHODOLOGY
Following the approaches of Hansen and Huang and Noland, the approach taken in this study is
to econometrically estimate the relationship between roadway capacity, measured as lane miles,
and vehicle travel, measured as daily vehicle miles of travel, while controlling for other key
factors that may influence travel. The extent of highway travel in an area is a function of many
factors. These include population, income, car ownership levels, land use, fuel prices (and other
variable costs of travel), and availability of alternative modes of travel, such as transit. Any
attempt to estimate the impact of additions to roadway capacity on travel levels must account for
as many of these factors as possible.
As described in the previous database documentation report, the database for this analysis
includes, for each county in Maryland, North Carolina, and Virginia, as well as the District of
Columbia, the following data-
• Geographic area,
• Population and population density,
• Income per capita,
• Employment (available as total employment and unemployment rate), and
• Extent of roadway lane miles in different roadway categories (see data discussion,
below).
Vehicle availability was not included in the database since this is nearly universal now in the
U.S. (with more than one car per driver nationally), and it is quite highly correlated with the level
of population. Fuel prices, although potentially important, were not easily available on a county
level, only on a state level Use of state level data would result in all counties within a state
having the same fuel prices for a given year. This variable is therefore fully captured in any
regression model including an intercept term for each year of data, which all the models in this
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analysis do include (see discussion of fixed effects models, below.) Finally, transit data was not
available for many counties so it is not included in the analysis It has been noted by other
analysts (e.g., Hansen and Huang) that the availability of transit itself may be influenced by
roadway supply and may represent a joint product with highway travel, in which case controlling
for it would be inappropriate.
EEA has conducted the econometric analysis of induced demand in a sequential fashion, first
developing basic econometric models relating travel to the extent of lane miles and other
variables for each study area separately, then for all areas together, and then testing alternative
specifications to explore the underlying relationships in more detail. These alternative
specifications include first difference models, urban/rural models, and lagged dependent variable
models. Although both linear and log-linear (linear in logarithms) models were tested, most of
the discussion is focused on the log-linear models due to the ease of interpretation of the
coefficients in such models as elasticity estimates.
In all estimated models, a "fixed effects" specification approach has been used. Fixed effects
models use cross sectional and/or time series intercepts for each unit of observation in order to
capture residual variation that is not accounted for in the set of explanatory variables entered in
the model.
Econometrically, a "fixed effects" model acknowledges the researcher's lack of information
about the unique characteristics of each unit in the data It can also reduce or eliminate bias
associated with correlations across units that would normally be captured in the error term. The
closer the error term is to a random distribution of residual (unexplained) variation, the less bias
will be present in the model estimates - in this case the estimates of the relationship between lane
miles and VMT. Since the data base used here is a panel data base (i.e., the same counties
included repeatedly over a period of years) our fixed effects models also account for variations
across time that might be correlated in the error term for individual counties. Our fixed effects
models are thus specified with a separate intercept term for each county and each year of data.
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Although it is certainly possible to develop more complex assumptions regarding the residual
variations (e g., by using a "random effects" model), the fixed effects approach is generally
considered reasonable in cases where the data encompass the population in question (which is
mostly true here, since in most counties all daily travel on the types of roads included in the
analysis is reflected in the data). For a more detailed discussion of the fixed effects specification
see for example Kennedy (1992).
A logarithmic specification of the fixed effects model can be shown as
]og(VM7;,)=a1 +ft + XA* l°g(x;,)«„
k
where:
VMT„ is the daily vehicle miles of travel for county 1 in year t;
at is the fixed effect for county i, estimated in the analysis;
ft is the fixed effect for year t, estimated in the analysis;
X* is the value of explanatory variable k for county i and year t;
XL is each of the set of K coefficients to be estimated;
Elt is the outcome of a random variable for county 1 in year t, assumed to be
normally distributed with mean 0
This model, and variants of this model that introduce a lag structure, have been used throughout
this analysis.
1.3 DATA DESCRIPTION
As mentioned, most of the database used in this analysis was described in detail in a previous
EEA document (EEA 1998). A brief summary of the data is reproduced here for the readers'
convenience.
1-8
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EEA collected data for this analysis at the county level for Maryland, North Carolina, Virginia,
and the District of Columbia. EEA also made extensive efforts to obtain data for Baltimore City
but was unable to do so. This data appears to exist but not in any readily available form
As described in section 1.2 above, a variety of variables were obtained for each county in the
database. Most of these variables were obtained from the agencies that collect this data in each
of the three state governments. Most of the variables were straightforward to obtain and
incorporate into the database The greatest data development effort was need in obtaining and
cleaning the VMT and lane mile data, and this deserves some discussion here.
The VMT and lane mile data that states submit to the Federal Highway Administration for use m
the Highway Performance Monitoring System were not available (and most cases are not kept)
on a county-by-county basis However, each of the three states does collect and track this data at
a county level. However, in most cases the data does not cover all roads or travel within each
county, and so the state totals EEA obtained do not match the summary statistics for each state
produced by the FHWA. In particular, each of these slates only collect data on travel and
roadway extent for roads that are state-maintained. In each of the states included in the analysis,
this included all interstate lane miles, all state highways, and many (but not all) other primary
roads. Data covering some secondary roads was obtained for Maryland and North Carolina but
not for Virginia. EEA was not able to obtain estimates of the percentage of primary and
secondary roads in each state that are state-majntained, so there may be significant variation in
the roadway coverage in each state.
A discussion of the VMT data collection approach in Maryland and Virginia was provided in the
previous EEA report but is summarized here. The method of VMT data collection appears to be
similar in the three states. In each case, the states collect VMT data primarily through traffic
counts on a sample of roadway segments. Each state has a large number of portable "periodic"
traffic counting devices, and these are placed on different roadway segments for several days at a
time throughout the year in order to obtain the samples. There are also dedicated "continuous"
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counters that are kept permanently in one location, but generally far fewer of these than portable
counters used for sampling. A special effort is often, but not always, made to collect data on
segments that are being considered for or recently had changes in capacity. VMT samples are
aggregated to estimates of total VMT using a fairly standard methodology, involving the
development of growth factors for each roadway link, based on VMT changes from previous
years' sampling data. Although the basic approach to data collection appears similar in each
state, the details of the approaches differ somewhat, as do the number of traffic counters and the
frequency of sampling each roadway segment. This is, then, a source of uncertainty in the
accuracy and consistency of the VMT data across the states For this reason, EEA has chosen to
estimate separate regression models for each state (as presented below in Section 3).
There are several other weaknesses in the data that have been documented in the previous
reports. One is that no distinction is made between entirely new roadways and lane-mile
additions onto existing roadways. These two types of capacity expansion may have quite
different relationships to levels of travel, but we were not able to distinguish these in our
analysis. Also, since all VMT data is provided as average daily levels, no specific congestion
data or level-of-service data for each county was available. Third, the availability of years of
data varied considerably by state, with Virginia and Maryland data available back to 1970 and
1969, respectively, while data for North Carolina and DC does not extend back before 1985 and
1984, respectively. Finally, as always, there were a number of data errors, outliers, and other
issues in the obtained databases that required attention before the Analysis could be undertaken.
These issues and EEA's methods for addressing them are documented in the previous EEA
documentation report (EEA, 1998).
It should also be noted that there are some definitional differences between the roadway types
included in the databases from the four areas. For Virginia and North Carolina, data for VMT
and lane miles includes only interstate and primary state-maintained roads. No secondary roads
are included. This is because VMT data was unavailable for non-state-maintained roads, which
includes primarily local secondary roads. However, some primary roads are not state-
maintained, which means that our database does not include all primary roads in either state.
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This is not believed to represent a problem since the main issue is that the data for VMT match
the data for lane miles in terms of road coverage, which it does.
For counties in Maryland, VMT data was only available as a total for all state-maintained roads,
including interstate, primary, and some secondary roads. Lane mile data was available in more
disaggregate form, but EEA used the lane mile total for all state-maintained roads in order to
match it with the VMT data.
Since the DC data was obtained during the current project, a full listing of data for DC is
provided in Appendix C. This Appendix also lists the counties included in the study area added
to this project, the DC/Baltimore metro area. This area uses the county data for the Maryland and
Virginia counties that EEA had obtained previously.
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2. PRELIMINARY DATA ANALYSIS
This section presents the results of a preliminary data analysis, intended to provide information
on the characteristics of the study areas as well as basic variable relationships, to serve as
background for the econometric analysis presented in Section 3. Detailed data analysis was
conducted as part of the previous study and is contained in EEA (1998). A short comparative
analysis of the study areas is provided here to set the context for the following multiple
regression analysis.
Basic characteristics of the five study areas (and all areas taken together) are shown in Table 2-1.
Note that averages in this data are taken across the counties without weighting for relative
population (which is appropriate when comparing these averages to subsequent regressions using
ordinary non-weighted least squares) Note also that data for Maryland and Virginia extend back
to 1969 and 1970, respectively, while data for North Carolina and the DC (and therefore the
DC/Baltimore area) extend back only to 1985 and 1984, respectively There are also differences
in the coverage of road types in the different states, as discussed above in Section 1. Thus some
caution must be exercised in comparing the averages across states.
Keeping in mind these caveats, several potentially important differences can be seen across the
different study areas. While the average geographic area of counties in each study area is quite
similar, the average population (and therefore population density) varies considerably The
DC/Baltimore area has about 1,600 persons per square mile, Maryland has about 420 per square
mile, Virginia has slightly under 200 per square mile, and North Carolina has less than 150 per
square mile. The travel per capita is somewhat inversely correlated with population density, with
Virginia showing 30 percent to 40 percent more daily travel per capita (on interstates and state-
maintained primary roads) than North Carolina and Maryland, with the DC/Baltimore metro area
about ten percent below Maryland. This suggests that the more densely populated areas require
2-1
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TABLE 2-1
AVERAGE COUNTY VALUES OF KEY VARIABLES IN 1995 (BY STATE AND AREA)
Units
Maryland
North Carolina
Virginia
DC Bait
All
Total # of Counties
X
23
100
96
16
220
Average Geographic Area
square miles
421
487
399
417
440
Average Population
people
188,699
71,867
45,582
326,878
74,804
Average Population Density
people/sq. mile
422
148
194
1,155
237
Average Daily VMT
miles/day
3,536,397
1,297,601
1,064,583
5,834,860
1,457,690
Average Daily VMT per Capita
VMT/person
21.62
20.55
29.25
19.77
24.43
Average Lane Miles
miles
624 42
364 60
260.28
683.45
349.45
Average Lane Miles per Capita
lane miles/person
0.0072
0.0087
0.0117
0 0031
0.0098
Average VMT per Lane Mile
VMT/lane mile
4,357
3,055
3,475
8,224
3,392
Average Income per Capita
1998$
24,644
19,846
20,891
29,623
20,865
Average Total # of Jobs
jobs
101,128
43,705
31,481
149,293
47,508
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fewer and/or shorter car trips, which may be due to proximity of destinations and/or greater
availability of alternative (non-auto) travel modes
The average number of Jane miles per capita is also greater in the areas with lower population
density, with a higher average in North Carolina and Virginia than in the DC/Baltimore metro
area and Maryland. This may reflect the presence of underutilized interstates and major artenals
that have been put in place to provide mobility to the scattered populous of the rural counties in
states such as North Carolina. It also may help explain why VMT per capita in densely
populated areas is lower - the availability of roadway miles per person is much lower. If true,
this would imply that congested conditions limit the VMT of residents in such an area to levels
below areas with more roadway capacity available. This is conjecture, but these relationships are
examined more formally in the following section through techniques of multiple regression
Finally, the average daily travel (VMT) per lane mile of available roadway is indeed much higher
in the more densely populated areas, again indicating that there is much less available road
capacity in the DC/Baltimore area than in Virginia, with North Carolina and Maryland
intermediate. This information on the variation in roadway use intensity provides an opportunity
to study how the relationship between changes in roadway supply and travel vary by the initial
conditions of roadway capacity (does adding capacity in an area of high roadway use affect travel
differently than adding capacity in an area of relatively low use?)
Table 2-2 provides average annual growth rates of key variables. The growth rates for several
key variables are significantly different across the different areas. While the growth rate in VMT
is between 3% and 4% per year in all areas, the growth rate in lane miles varies significantly,
ranging from 0.38% in Maryland to 0.87% in the DC/Baltimore area. The trends in North
Carolina, with VMT growing much faster than either population or lane miles, suggest that
average travel per person has increased significantly. However, the average VMT per lane mile
in North Carolina counties in 1995 (shown in Table 2-1) was still quite low compared to
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TABLE 2-2
AVERAGE ANNUAL GROWTH RATES OF KEY VARIABLES
(BY STATE AND AREA AND FIRST YEAR TO LAST YEAR OF AVAILABLE DATA)
Maryland
North Carolina
Virginia
DC Bait
All
Years of Data
1969 - 1996
1984 - 1997
1970- 1996
1970-1996
1985 - 1995
Population
1.72%
0.96%
1.32%
2.66%
1 10%
Population Density
1.72%
0.97%
1 33%
2.66%
1.11%
VMT
3.46%
3.46%
3.44%
4 16%
3.28%
Lane Miles
0.38%
0 58%
0.61%
0.87%
0.45%
Population per Lane Mile
1.34%
0.38%
0 71%
1.78%
0 65%
VMT per Lane Mile
3 07%
2.86%
2.81%
3.26%
2.82%
Income per Capita
1.50%
1 74%
1.87%
1 76%
1 42%
Jobs
2 52%
1.74%
1.94%
2.93%
1.93%
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Virginia, Maryland, and the DC/Baltimore area Clearly, the rapid growth in travel per person in
North Carolina has not (yet) resulted in roadway usage levels on a par with the other areas.
Several distributions of the counties in each study area by key variables are presented in Table 2-
3 The categories (low, medium and high) have been set somewhat arbitrarily, based mainly on
visual inspection and identification of data "clusters" that appear to fall into different categories
As with Tables 2-1 and 2-3, several potentially important differences can be seen across the study
areas. Nearly all counties in the DC/Baltimore area have relatively high population densities,
while in North Carolina less than half the counties do, and in Virginia, somewhat surprisingly,
more than three-quarters of the counties have a low population density. North Carolina and
Virginia have more counties that are in either the mid or high categories than the low category,
and DC/Baltimore is dominated by counties with high population and travel per lane mile. This
appears to correlate fairly strongly with low and high income per capita ratios in each area
The information in these three tables raises several questions and helps set the stage for the
following econometric (multiple regression) analysis, and may provide insights that can be used
in interpreting the results of that analysis.
One final piece of data analysis that deserves attention before presenting the results of the
econometric analysis is the basic relationships between the key variables. A correlation matrix
presenting correlation coefficients for the logs of the primary variables in the analysis, using the
full database encompassing the three states and DC, is shown in Table 2-4. A description of the
variable names is provided in Appendix A, Tables A-la and A-lb. A more complete set of
correlation matrices, with log, non-log, and first difference variables for the full data base and for
each study area separately, is presented in Appendix B. Table 2-4 is intended to provide an
example of the typical correlations between the variables in the analysis. It demonstrates that
there is a fairly strong correlation between each of the principal explanatory variables (lane miles
[LOGLM], population [LOGPOP], income [LOGPCI98], and employment [LOGJOBS]) and
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TABLE 2-3
DATA DISTRIBUTIONS (NUMBER OF COUNTIES IN EACH CATEGORY IN 1995)
Range
Maryland
North
Carolina
Virginia
DC Bait
All
# of Counties
23
100
96
16
220
Persons per Square Mile
Low
< 100
7
53
74
1
134
High
> 100
16
47
22
15
86
Population per Lane Mile
Low
< 100
6
30
44
0
80
Med
100 - 200
9
42
38
3
89
High
>200
8
28
14
13
51
VMT per Lane Mile
Low
<2000
2
33
24
0
59
Med
2000 - 5000
16
55
56
6
127
High
>5000
5
12
16
10
34
Income / Capita
Low
<20000
5
58
49
0
112
High
> 20000
18
42
47
16
108
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TABLE 2-4
ALL STATES LOGARITHMIC CORRELATION MATRIX
VARIABLE
DESCRIP
LOGVMT
LOGVCAP
LOGLM
LOGLMCAP
LOGVMTLM
LOGLMURB
LOGPOP
LOGPOPDN
LOGPCI98
LOGJOBS
LOGGAS98
LOGVMT
Coefficient
Std Error
N
1
0
2420
0 03744
0 0656
2420
0 86461
0 0001
2420
-0 70735
00001
2420
0 85887
00001
2420
-0 67331
0 0001
2420
0 92595
0 0001
2420
081501
0 0001
2420
0 59347
0 0001
2420
0 78446
0 0001
2420
0 00302
0 882
2420
LOGVCAP
Coefficient
Std Error
N
0 03744
0 0656
2420
1
0
2420
-0 00877
0 6662
2420
053135
0 0001
2420
0 07409
0 0003
2420
0 34676
00001
2420
-0 34272
0 0001
2420
-0 34428
0 0001
2420
010286
0 0001
2420
-0 23615
00001
2420
-0 06004
0 0031
2420
LOGLM
Coefficient
Std Error
N
0 86461
0 0001
2420
-0 00877
0 6662
2420
1
0
2420
-041741
0 0001
2420
0 48523
0 0001
2420
-0 47708
00001
2420
081613
00001
2420
0 57964
0 0001
2420
0 36472
0 0001
2420
0 71394
0 0001
2420
0 04508
0 0266
2420
LOGLMCAP
Coefficient
Std Error
N
-0 70735
0 0001
2420
0 53135
0 0001
2420
-0 41741
0 0001
2420
1
0
2420
-0 80546
0 0001
2420
0 78831
0 0001
2420
-0 86578
0 0001
2420
-0 9075
0 0001
2420
-0 50037
0 0001
2420
-0 68178
0 0001
2420
-0 0011
0 9567
2420
LOGVMTLM
Coefficient
Std Error
N
0 85887
00001
2420
0 07409
0 0003
2420
0 48523
0 0001
2420
-0 80546
0 0001
2420
1
0
2420
-0 6854
0 0001
2420
0 77941
0 0001
2420
0 82744
0 0001
2420
0 66099
00001
2420
0 63737
0 0001
2420
-0 0407
0 0453
2420
LOGLMURB
Coefficient
Std Error
N
-0 67331
0 0001
2420
0 34676
0 0001
2420
-0 47708
0 0001
2420
0 78831
0 0001
2420
-0 6854
oooot
2420
1
0
2420
-0 76402
00001
2420
-0 80957
0 0001
2420
-0 49226
0 0001
2420
-0 68868
0 0001
2420
-0 01255
05371
2420
LOGPOP
Coefficient
Std Error
N
0 92595
0 0001
2420
-0 34272
0 0001
2420
081613
0 0001
2420
-0 86578
00001
2420
0 77941
0 0001
2420
-0 76402
0 0001
2420
1
0
2420
0 8963
0 0001
2420
0 51904
0 0001
2420
0 82672
0 0001
2420
0 02553
0 2093
2420
LOGPOPDN
Coefficient
Std Error
N
081501
0 000)
2420
-0 34428
0 0001
2420
0 57964
0 0001
2420
-0 9075
0 0001
2420
0 82744
0 0001
2420
-0 80957
0 0001
2420
0 8963
0 0001
2420
1
0
2420
0 64643
0 0001
2420
0 74785
0 0001
2420
0 05157
00112
2420
LOGPCI98
Coefficient
Std Error
N
0 59347
0 0001
2420
010286
0 0001
2420
0 36472
0 0001
2420
-0 50037
0 0001
2420
0 66099
0 0001
2420
-0 49226
0 0001
2420
0 51904
0 0001
2420
0 64643
0 0001
2420
1
0
2420
0 49796
0 0001
2420
-0 02778
0 1719
2420
LOGJOBS
Coefficient
Std Error
N
0 78446
0 0001
2420
-0 23615
00001
2420
0 71394
0 0001
2420
-0 68178
0 0001
2420
0 63737
0 0001
2420
-0 68868
00001
2420
0 82672
0 000!
2420
0 74785
0 0001
2420
0 49796
0 0001
2420
1
0
2420
001814
0 3725
2420
LOGGAS98
Coefficient
Std Error
N
0 00302
0 882
2420
-0 06004
0 0031
2420
0 04508
0 0266
2420
-0 0011
0 9567
2420
-0 0407
0 0453
2420
-0 01255
0 5371
2420
0 02553
0 2093
2420
0 05157
00112
2420
-0 02778
0 1719
2420
001814
0 3725
2420
1
0
2420
-------
travel [LOGVMT], with the R coefficient for each of these variables with respect to VMT over
0.5. Further, multicollinearity between these variables is generally not a problem, with few cases
of coefficients among the basic variables above 0.5. The most severe case among the basic
variables is the combination of population and employment, which is over 0 8. Several
coefficients for respecifications of the basic variables are also above 0.5, such as VMT per lane
mile [LOGVMTLM] with income. Overall, multicollinearity does not appear to be a significant
problem in the analysis.
2-8
-------
3. RESULTS OF ECONOMETRIC ANALYSIS
In the econometric models tested in this analysis, base model specifications were first developed
for each study area, and then all areas together, using VMT as the dependent variable and lane
miles, population, income per capita, and employment as the potential explanatory variables.
These are reported below, followed by results for several variations on these base models that
introduce a lag structure and considerations of traffic levels on the results. Separate regressions
have been run for five geographic areas- Maryland, North Carolina, Virginia, the DC-Baltimore
extended metropolitan area, and the full database (all three states and Washington DC). The DC-
Baltimore extended metropolitan area is comprised of 16 suburban counties around and between
the two cities (but does not include the cities themselves - see Appendix C for a list of counties in
this area) The main reason for excluding the District of Columbia itself in the metro area
analysis is that data for DC is available only back to 1985; excluding it allows the analysis of the
metro area to use data extending as far back as 1970 However, DC is included in regressions
that include all areas together. These are referred to below and in the tables as "all states" runs
3.1 BASE MODEL RUN RESULTS
A summary of basic results for individual areas and all areas together is presented in Table 3-1.
As for all of the results presented in this section, more detailed tables with many more run
specifications are provided in Appendix A, Table 3-1 presents results for two basic
specifications, with separate results presented for each of the five study areas. The runs in
Appendix A are expanded to show additional specifications including different combinations of
variables and linear (non-logarithmic) as well as logarithmic specifications. Appendix D
contains a set of more detailed outputs for the runs shown in Table 3-1, including the intercept
coefficients for each county and year.
3-1
-------
TABLE 3-1
SUMMARY OF BASE RUN RESULTS
Dependent Variable
LOG(VMT)
State
AH States
Maryland
North Carolina
Virginia
DC - Baltimore
combined metro area
Years of Data
1985-1995
1969-1996
1985-1997
1970-1996
1970-1996
N
2420
2420
644
644
1300
1200
2592
2592
432
432
Adjusted R-Square
0710
0713
0 948
0.948
0 856
0 838
0 883
0 884
0 963
0 963
Intercept
est
451
221
3.38
3 19
4 85
4.24
4 90
3.89
6 09
5 27
t
9.23
3.01
7.77
4 62
7 80
4 11
20 0
9.82
13 6
5 73
Log (Lane Miles)
est.
0.587
0 564
0 451
0.451
0.475
0 435
0.506
0 508
0 331
0 327
t
124
11 9
801
8.00
9.79
8 02
15.5
15 6
6 17
6 10
Log (Population)
est.
0.520
0 569
0 659
0.655
0 560
0 585
0 507
0.504
0.518
0 502
t
13 6
14 3
24 2
22 0
107
9.39
25.7
25 6
170
160
Log (Income Per Capita)
est.
X
0.195
X
0.026
X
0.057
X
0 110
X
0 167
(1998$)
t
X
4 18
X
0 369
X
0 958
X
3 25
X
1 87
-------
Table 3-1 focuses on the two specifications that are, in a sense, the most basic. These are log-log
(linear in logs) models that include basic sets of explanatory variables lane miles and population,
one also with and one without income per capita. As shown in Table 3-1 and the more complete
set of runs in Appendix A, the coefficients on Jane miles and population are fairly consistent
across specification - adding measures of income and employment does not significantly alter
their value or level of significance.
The R-squared values in these regressions are generally extremely high - above 0.95. This is not
surprising in a fixed effect specification, as the county and year intercepts capture most of the
residual variation not accounted for by the continuous explanatory variables in the model As
shown in Appendix D, most county and year intercept coefficients are significant in most runs
The results across the 5 study areas are very consistent, in terms of both the statistical
significance and the coefficient values, with respect to the lane miles and population variables
Income per capita is more varied and much less significant1 The consistently strong significance
for population is not especially surprising, since the number of people living in an area is
expected to be a principal determinant of the level of vehicle traveJ in the area. The generally low
value and low significance for income per capita suggests that in most areas, increases in income
do not strongly correlate with increased vehicle travel (at least at the county level of analysis).
This also may reflect the fact that, quite often, greater distances must be covered in rural areas,
which also generally have lower income levels In addition, other recent analyses suggest that in
the U.S., although income has been an important estimator of travel levels in time series
analyses, from a cross-sectional point of view travel levels and annual household expenditure on
vehicle travel are relatively insensitive to income2.
1 With 60 or more degrees of freedom, a I value of about 2.0 or higher represents significance at the 95
percent confidence interval (2-tailed test)
2 Personal communication, Philip Patterson, U S. Dept of Energy, based on analysis DOE has done in
this area
3-3
-------
The coefficient for lane miles is perhaps surprisingly consistent across study area, and does not
vary significantly with the introduction of other variables, such as income (As shown in
Appendix A, it also does not vary significantly for most specifications that introduce other
variables or divide through VMT or lane miles by population.) The greatest deviation from the
"typical" coefficient value for lane miles is for the DC-Baltimore area. For each of the three
states and for the "ail states" runs, lane miles has a coefficient value between 0.43 and 0.59, the
values for DC-Baltimore are somewhat lower, about 0.33.
These results indicate that, after controlling for population and income, a ten percent increase in
lane miles correlates with 3% percent to 6% increase in daily VMT, at least in the mid-Atlantic
region Since these models do not include any lag structure, this result should be interpreted as a
short run response. The high t-statistics and low variation in results by area suggests that the
result is fairly robust. This is especially true considering the significant differences in the
characteristics of the different study areas, as discussed above in Section 2
The slightly lower lane miles coefficient for DC-Baltimore suggests that more densely populated
areas may not have quite as large a travel "rebound effect" as more outlying, rural counties (or at
least the average county in these states). This may reflect more mature land use patterns in these
areas, or more alternatives to car-based travel However, the availability of greater alternatives
could work in the other direction - by creating more options for people to avoid driving during
congested conditions, which could induce a greater return to autos once these conditions are
alleviated. The result may instead reflect a different kind of lane-mile addition and response than
is more typical in outlying areas - one that is related to the addition of new lanes on existing
roads, rather than new roads. If so, the scope for travel response may be, in percentage terms, not
as great as for an entirely new road. We explore this question, rural v urban rebound effect,
further below
For the "all states" regressions, the lane mile coefficient is actually slightly larger than for any of
the individual study areas: a 10% change in lane miles correlates with about a 5.6% to 5.9%
3-4
-------
increase in travel. This could indicate that the cross-sectional variation m the data (actually,
cross-regional variation) has a steeper slope than the variation within each state. This may also
reflect the difference in the number of years used in this regression relative to Virginia or
Maryland regressions
Overall, the basic regression results indicate a generally strong relationship between the number
of lane miles and the level of travel. However, this relationship may well vary over time, due to
the possibility of a lag time between an addition of lane-mile capacity and the different forms of
response of travelers to this increase, which could include both immediate increases in travel
(especially to lane mile additions that reduce congestion), and longer term responses, such as
increased development along uncongested corridors, relocations of individuals that result in
longer trips, etc.
Specifications also were tested that involve taking the first difference of all variables from year to
year. We conducted these as the differences of the logs of variables (year t minus year t-1),
which captures percentage changes through time A summary of the first difference results is
shown in Table 3-2
The results of these runs are somewhat more varied than the base runs, but still significant for
lane miles in eveiy study area (DC-Baltimore is significant only at about the 90% confidence
interval). However, the coefficient for the change in population on the change in travel was
insignificant in most areas. This may reflect an errors-in-variables problem in the year to year
change in population, since population levels are not actually measured each year but estimated
for years between the census. Such an error would appear much more prominently in a first
difference regression than in a regression using variable "levels" (such as the base regressions).
The R-squared values in these runs are quite low, generally less than 0.2. However, this is not
3 Note that years before 1985 were dropped in the "all stales" regressions since these years were not
available for North Carolina Keeping only the years available for all states preserves a balanced panel
data set. Analyses using all the years (not shown) does not alter the basic results
3-5
-------
TABLE 3-2
SUMMARY OF FIRST DIFFERENCE RUN RESULTS
Dependent Variable
LOG(VMT) Difference*
State
All States
Maryland
North Carolina
Virginia
DC Baltimore
Years of Data
1986-1995
1970-1996
1986-1997
1971-1996
1971-1996
N
2200
2200
621
621
1200
1100
2496
2496
416
416
Adjusted R-Square
0.053
0 055
0 175
0 181
0 129
0.131
0 184
0 186
0 328
0.328
Intercept
est
0.006
0 005
0 058
0 057
-0 020
-0 027
0.034
0031
0 068
0.064
t
0 275
0 238
3.01
2 95
-0 874
-1.11
2 72
2 43
3.97
3.26
Log (Lane Miles Difference)
est
0.434
0 433
0.517
0 527
0 609
0.612
0 149
0 145
0.153
0 154
t
5.84
5 83
3 40
3.47
6.95
6 77
3.56
3.45
1 66
1 66
Log (Population Difference)
est
0.067
0 075
0 114
0 243
0 281
0.372
0 117
0.143
0.347
0 379
t
0.485
0 535
0 423
0 877
0 989
1 17
2.21
2 67
1 88
1 92
Log (Income Per Capita
est.
X
0.023
X
0 257
X
0 095
X
0.103
X
0 062
Difference) (1998$)
t
X
0 334
X
2 03
X
1 02
X
2 73
K
0 454
* Difference denotes the differences of the logs of the variables (year t minus year t-1)
-------
uncommon for first difference runs, which tend to draw out the stochastic component of the
change in variables from year to year.
The coefficient on lane miles varies from a low of 0 15 (DC-Baltimore) to a maximum of 0 61
(North Carolina), a range that is slightly broader than, but not inconsistent with, the base run
results. The lane mile coefficients for Virginia are similar to those for DC-Baltimore, and much
lower than for Maryland and North Carolina. These are the two areas for which population is
significant, which may explain the difference in lane miles (and may indicate that growth in
travel is more population-driven in these areas than in the other states).
In general, the significant results for the first difference models, and the relatively similar
coefficients on lane miles for these models as for the base models (taken on levels rather than
differences), suggests that the coefficient estimates are relatively robust. It also indicates that the
base regressions do not suffer from significant bias due to autocorrelation.
3.2 SHORT/LONG RUN ELASTICITY RUN RESULTS
In order to separate the short and long run elasticity between lane miles and VMT, several lag
adjustment models were tested. EEA chose to use a distributed lag model structure for these
tests. This functional form allows the simultaneous estimation of short run and long run
elasticities, with the restriction that the effects are assumed to be strongest in the first year and
then decline through time. This would seem appropriate in areas where capacity expansion
reduces congestion, but it may not correctly capture the nature of the lag structure in areas where
roadway expansion triggers growth and development, which may be minor at first but increase in
intensity through time The approach also implicitly assumes that all variables in the model have
the same lag structure with respect to the dependent variable. While these restrictions may
introduce some bias into the estimation, the approach is appealing due to its econometric
simplicity and ease of interpretation. The distributed lag models were specified by introducing a
one-year lagged dependent variable into the specification. The resulting coefficients of the
distributed lag specification can be converted to estimates of short and long run elasticities (see,
3-7
-------
for example, Johnston, 1984) using the assumed short-long run relationship underlying the
distributed lag function
Table 3-3 presents the results of these regressions, for the same variable specifications as the
base runs, except for the addition of the one-year lagged dependent variable. The resulting
estimated short run and long run elasticities are presented at the bottom of each column
These runs show a high degree of significance overall, and for lane miles and population in every
study area. The short and long run elasticity calculation, shown at the bottom of the page,
indicates that there is a significant increase in the elasticity from short to long run in every areas,
although the difference is smallest in North Carolina, and largest in Virginia. The Virginia long
run elasticity is the highest elasticity found in any specification of EEA's analysis. Maryland
shows relatively low short-run and long run elasticities than North Carolina. The DC-Baltimore
results are similar to Virginia in the short run, but closer to North Carolina and Maryland in the
long run. Not surprisingly, the "all states" regression results are intermediate between those of
the individual states included in these runs.
While the runs for all the study areas show significance for lane miles, the variation across the
areas in terms of short run and long run elasticities is somewhat difficult to interpret. It probably
reflects variations in any number of factors that could not be captured in this analysis, such as the
detailed land use patterns in each area, types and locations of lane-mile additions, levels of
congestion on the corridors with lane miles added, etc Analysis of more detailed VMT and lane
mile data for these states (which may be available for some areas, but not from the state offices
that EEA worked with to obtain data), may provide further insights in this area.
3.3 TRAFFIC VOLUME AND POPULATION DENSITY MODEL RUN RESULTS
In theory, one would expect induced travel effects to be larger in an area with more congestion.
Any increase in existing road capacity would give a more than proportional decrease in travel
times (in the short-run). On the other hand, congested areas also tend to be fully developed, so
3-8
-------
TABLE 3-3
SUMMARY OF SHORT / LONG RUN ELASTICITY RESULTS
Dependent Variable
LOG(VMT)
State
All States
Maryland
North Carolina
Virginia
DC - Baltimore
Years of Data
1986-1995
1970-1996
1986-1997
1971-1996
1971-1996
N
2200
2200
621
621
1200
1100
2496
2496
416
416
Adjusted R-Square
0 826
0 830
0 960
0 960
0 899
0 890
0 965
0 965
0 985
0 985
Intercept
est.
2.72
0 727
1 48
1 28
4 70
461
0.489
0 118
1 27
0 754
t
5.97
1.07
3 62
204
8 28
5 09
3 31
0 531
3 59
1 26
Log (VMT)
est.
0 508
0 504
0 559
0 559
0 187
0 164
0 841
0 840
0 782
0 779
(lagged 1 year)
t
28.4
28.2
160
160
8 04
6 93
77.9
77.8
24.7
24 4
Log (Lane Miles)
est
0 355
0.338
0.215
0215
0 426
0.394
0 128
0 129
0 129
0 130
t
8 40
8 00
4 09
4.10
102
8.60
6 78
6 86
3.64
3 65
Log (Population)
est
0.175
0 227
0.288
0 284
0.367
0.373
0 086
0 086
0 097
0 095
t
4 80
5 87
8 55
8.05
761
6 54
7 03
6 99
3 69
3 58
Log (Income Per Capita)
est.
X
0.162
X
0 026
X
0 055
X
0.041
X
0 061
(1998$)
t
X
3 91
X
0 428
X
1 11
X
2 22
X
1 06
Short-Run Elasticity
0 355
0.338
0215
0215
0 426
0.394
0 128
0 129
0 129
0 130
Long-Run Elasticity
0 722
0681
0 488
0 489
0 525
0.471
0 808
0811
0 594
0.586
-------
one would expect fewer long run impacts from land use changes. To test these hypotheses, we
disaggregated the data based upon relative traffic levels (calculated as average daily VMT per
lane mile) as a proxy for congestion and also on different levels of population density Obviously
this is a simplification as congestion effects can be very time of day specific, but in general, the
greater the level of traffic or the greater the population density, the larger the level of congestion
The data was divided into three groups, defined as "low", "medium" and "high" levels of travel
per lane mile The data was divided with "low" being defined as below 2000 daily VMT per lane
mile, "medium" being between 2000 and 5000 daily VMT per lane mile, and "high" being above
5000 daily VMT per Jane mile The year 1990 was chosen as the base year for dividing counties
into groups The problem with using earlier years as a basis for making the allocation is that (a),
several areas' data extends back only to the mid 1980s and (b) most counties m Virginia and
North Carolina fall into the low density category before 1980 The overall split was 20 high
congestion counties, 120 low congestion counties, and 80 medium congestion counties.
The population density estimates were split by areas with less than 100 persons per square mile
defined as "low", 100 - 500 persons per square mile was "medium", and greater than 500
persons per square mile was "high" A level of 500 persons per square mile might not be
considered a high population density, but the vast majority of the counties in the analysis have
very low population densities With this split of the levels there were 16 counties in the "high"
category, 66 counties in the "medium" category, and 138 counties in the "low" category.
These estimates were done only for the "all states" model since some of the sub-categories for
individual states did not have enough counties within the cross-section. Interaction terms were
entered for the lane mile variables Results are shown in Tables 3-4 and 3-5 for models using
VMT/Lane mile and VMT/capita respectively.
In each table a base model and a distributed lag model is presented. The population density base
model suggests that areas with medium population density have the highest lane mile elasticities.
The congestion level model suggests slightly lower elasticities for the least congested areas, as
3-10
-------
TABLE 3-4
TRAFFIC VOLUME INTERACTION MODELS
All States model
Dependent variable = LOG(VMT)
Congestion Level
interaction
Congestion Level
interaction with
distributed lag
N
2420
2200
R-Square
0711
0.785
Intercept
est
2 728
0 996
t
(3.832)
(1 501)
Log (VMT) lagged 1 year
est
0 507
t
(28 416)
Log (Lane Miles, low VMT/LM ratio)
est
0 240
0 175
t
(3 151)
(2 533)
Confidence interval (95%)
0 091 -0.390
0 040-0 311
Log (Lane Miles, medium VMT/LM ratio)
est
0 530
0.356
t
(7 192)
(5.617)
Confidence interval (95%)
0 385 - 0 674
0 232-0 480
Log (Lane Miles, high VMT/LM ratio)
est
0 594
0 310
t
(7 846)
(4.676)
Confidence interval (95%)
0 446 - 0.743
0 180 - 0 440
Log (Population)
est
0.548
0213
t
(13.743)
(5 463)
Log (Income Per Capita)
est
0213
0 164
t
(4 467)
(3 899)
Long-Run Elasticity - Lane miles, low VMT/LM ratio
0.345
Long-Run Elasticity - Lane miles, medium VMT/LM ratio
0 702
Long-Run Elasticity - Lane miles, high VMT/LM ratio
0611
Note confidence interval provides the range of possible "actual" value for coefficient within 95% confidence interval
-------
TABLE 3-5
POPULATION DENSITY INTERACTION MODELS
All States mode
Dependent variable = LOG(VMT)
Population Density
interaction
Population Density
interaction with
distributed lag
N
2420
2200
R-Square
0711
0 785
Intercept
est
2515
0.889
t
(3 538)
(1 341)
Log (VMT) lagged 1 year
est.
0.506
t
(28 329)
Log (Lane Miles, low population density)
est
0 402
0.294
t
(6 079)
(5 011)
Confidence interval (95%)
0 272-0.531
0 179-0 409
Log (Lane Miles, medium population density)
est.
0.573
0.323
t
(8.496)
(5.447)
Confidence interval (95%)
0 441 - 0 705
0 207 - 0 440
Log (Lane Miles, high population density)
est
0404
0.210
t
(3 708)
(2 217)
Confidence interval (95%)
0.190-0617
0 024-0 395
Log (Population)
est
0.571
0 229
t
(14.260)
(5 914)
Log (Income Per Capita)
est
0.198
0 157
t
(4 186)
(3.744)
Long-Run Elasticity - Lane miles, low population density
0 581
Long-Run Elasticity - Lane miles, medium population density
0 638
Long-Run Elasticity - Lane miles, high population density
0415
Note confidence interval provides the range of possible "actual" value for coefficient within 95% confidence interval
-------
one would expect However, the coefficient values between the various lane mile interaction
terms are not statistically different, as shown by the overlap between the 95% confidence
intervals for the lane mile coefficients In other words, although the coefficients are statistically
different from zero (based on their t-statistics, they are not statistically different from each other).
The one exception is the base model with congestion level interactions that has a lower
coefficient value for areas with low congestion.
Although the results are inconclusive as to whether there are any differences in elasticities due to
existing population density and/or congestion effects, they suggest that there could be significant
differences in the relationship between lane miles and travel depending on the predominant
traffic levels and levels of congestion that are present If mid-traffic volume areas show the
highest correlation between lane miles and travel, it may suggest that in areas with modest traffic
volume, there is a high long run elasticity related to growth induced by roadway additions, while
in the higher traffic volume areas, this long run response is lower. In an effort to investigate this
possibility, EEA also estimated these "traffic volume" models using a distributed lag
specification, in order to estimate differences in short run and long run elasticity in each area
Tables 3-4 and 3-5 also show results for distributed lag models, with the long run elasticities
shown at the bottom of the column. These regressions also do not show significant differences in
the coefficients across the different data groupings, with no discernable pattern for the short-run
or long-run elasticity. The long run coefficients are highest for the counties with mid-traffic
volumes and mid-population density, but the coefficients are not statistically different that those
for the highest traffic volume / densest counties
These results suggest that further analysis is needed to identify differences in the VMT/lane mile
relationships in areas of low versus high levels of population and traffic It may be necessary to
use data that distinguishes between lane miles added onto existing capacity (such as road
widenings and restripings) and entirely new roadways or major upgrades, information which was
not available for the data used in this analysis. Such a distinction may help explain urban / rural
3-13
-------
differences, since urban capacity expansion tends to be oriented toward road widenings while
rural expansion tends to be focused on new roadways and major upgrades that may attract new
development. Another potential source of "noise" in the data is the presence of non-local traffic,
which may be a high percentage of total traffic on some roadways, especially on rural interstates.
High levels of through-traffic may explain the relatively high short-term elasticities we are
obtaining for rural counties For example, new highways may attract through-users relatively
quickly, while this may be less important for upgrades to other primary roads These may take
longer to attract increased traffic, as new development may often play a more important role in
these cases. If so, the net effects would be washed out in the data we have used in this study,
which include the total travel from all state-maintained primary roads in each county.
3-14
-------
4. SUMMARY AND CONCLUSIONS
The results of HEA's analysis indicate that there is a significant relationship between the level of
highway capacity, as measured by lane miles, and the level of travel, measured by daily VMT, in
the mid-Atlantic region of the U.S After accounting for other important determinants of travel,
such as population and income, the estimated elasticity between lane miles and VMT is in the
vicinity of 0.3 to 0.6, with an average value around 0 5. Breaking this into short run and long run
terms, the elasticity is in the range of 0.1 to 0.4 short run, with an average value around 0.25, and
0.5 to 1.0 Jong run, with an average value around 0.7 Although there is some variation across
study area and specification, there is a surprising degree of consistency in both the significance
and the value of the lane mile coefficient across all the regressions EEA conducted.
The results using the entire database ("all states" runs) are generally close to those for the
individual states, and there is relatively little difference between the results for each state,
especially in the base runs. However, a somewhat surprising result is that the relationship
between lane miles and travel appears to yield a lower elasticity for more urbanized areas
(namely the DC-Baltimore extended metropolitan area), than for the study areas that contain
many rural counties (all three of the states).
While the base specifications and distributed lag specifications provide stable and highly
significant coefficients, for the most part, EEA's efforts to analyze the data on the basis of traffic
volume and population density have failed to produce conclusive inferences. These regressions
produced significant relationships between travel and highway capacity for each of several areas
that vary by the level of traffic volume and population density, but little difference in the
relationships across the different area types
4-1
-------
In summary, the results of EEA's analysis suggest that there is a strong relationship between the
level of lane miles and levels of travel, although this does not prove causality. Even with the
significant results for lagged models, suggesting that increases in lane miles tend to come before
increases in travel, it could be argued that planners are simply doing their jobs and properly
anticipating future growth in travel by providing the new roadway capacity ahead of time More
research into travel response in congested v uncongested conditions, and long term growth in
areas with roadway expansions, may shed more light on this very difficult question
This research indicates a number of different avenues for potential additional research.
Certainly, the study of additional states and metropolitan areas will add to the body of literature
and may help improve the understanding of how the relationship between lane miles and travel is
affected by characteristics that can be isolated in each area. However, perhaps more interesting
would be a deeper analysis of the potential variations in the VMT/Jane mile relationship in the
current study areas (or other areas), including an analysis of what kind of lane miles are being
added in different counties, and how this relates to the types of responses in these counties
General growth patterns and land use patterns would also be interesting correlates. However, the
major problem in conducting such an analysis is that more detailed data would be needed. It may
be difficult to obtain most of this data from many state agencies, but may be available in some
cases. In any case, it is an area of research that is worth investigating in the future An even
more disaggregate analysis, such as within a metropolitan area with data at the roadway level of
aggregation, may allow for greater separation of various effects. The problem at this level, of
course, is separating roadway segment-specific effects (which may be offset by changes in other
roadway segments) from regional effects that are closer to representing "equilibrium" results.
4-2
-------
REFERENCES
EEA, 1998, "Measuring Induced Demand and Emissions Impacts from Transportation Facilities-
Database Documentation and Preliminary Analysis", Energy and Environmental Analysis,
prepared for EPA, Office of Policy Planning and Evaluation, under subcontract to Industrial
Economics Incorporated.
Hansen, Mark, and Yuanlin Huang, 1997, "Road Supply and Traffic in California Urban Areas",
Transportation Research - A. Volume 31, No. 3, pp. 205-218.
Johnston, J., 1984, Econometric Methods. McGraw Hill, New York
Noland, Robert B., 1999, "Relationships Between Highway Capacity and Induced Vehicle
Travel", paper presented at the 78th Annual Meeting of the Transportation Research Board,
Washington D C., paper no. 991069
R-i
-------
APPENDIX A: DETAILED RUN RESULTS
This appendix contains the following tables and run results:
Table A-l a-b.
Table A-2 a-c.
Table A-3 a-c.
Table A-4 a-c.
Table A-5 a-c.
Table A-6 a-c.
Table A-7
Table A-8
Description of Variables Used in the Analysis
Base Run Results. The sub-tables for Table A-2, and for the sets of Tables
A-3 through A-6 in Appendix A, are as follows.
Table A-2a. Base Run Results - Maryland
Table A-2b Base Run Results - North Carolina
Table A-2c. Base Run Results - Virginia
First Difference Runs
Elasticity Runs (short / long run)
Traffic Volume Runs (low / mid / high volume)
Traffic Volume Elasticity Runs
Traffic Volume Runs (low / mid / high volume), Alternative Method
Traffic Volume / Elasticity Runs, Alternative Method
-------
TABLE A-la
DESCRIPTION OF VARIABLES
FOR ALL STATES
Variable.
Description
VMT
vehicle miles travelled
VMT_CAP
VMT per capita
LM
lane miles
LM_CAP
lane miles per capita
VMT_LM
VMT per lane mile
LMCAPURB
LM_CAP* Urban
(where Urban = 1 if population density is over 100 people/sq, mile)
POP
population
POPDEN
population density
PCI_98
income per capita in 1998$
JOBS
employment by place of work
GAS_PR98
statewide price of gasoline in 1998$
LOG VMT
Log(VMT)
LOGVCAP
Log(VMTCAP)
LOGLM
Log(LM)
LOGLMCAP
Log(LM_CAP)
LOGVMTLM
Log(VMT_LM)
LOGLMURB
Log(LMCAPURB)
LOGPOP
Log(POP)
LOGPOPDN
Log(POPDEN)
LOGPCI98
Log(PCI_98)
LOGJOBS
Log(JOBS)
LOGGAS98
Log(GAS_PR98)
-------
TABLE A-lb
DESCRIPTION OF FIRST DIFFERENCE VARIABLES
FOR ALL STATES
Variable:
Description:
VMTDIFF
First difference - VMT
VCAPDIFF
First difference - VMT per capita
LMDIFF
First difference - lane miles
LCAPDIFF
First difference - lane miles per capita
POPDIFF
First difference - population
PCIDIFF
First difference - per capita income in 1998$
JOBDIFF
First difference - employment by place of work
L_VMTDFF
Log of first difference - VMT
L_VCPDFF
Log of first difference - VMT per capita
L_LMDIFF
Log of first difference - lane miles
L_LMCDFF
Log of first difference - lane miles per capita
L_POPDFF
Log of first difference - population
L_PCIDFF
Log of first difference - per capita income in 1998$
L_JOBDFF
Log of first difference - employment by place of work
-------
TABLE A-2a
BASE RUN RESULTS - MARYLAND
Dependent Variable
VMT/CAP
LOG( VMT/CAP)
Logs of Independent Variables''
no
no
no
no | no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
644
644
644
644 644
644
644
644
644
644
644
644
644
644
Adjusted R-Square
0931
0 932
0 936
0 932 | 0 938
0 938
0 934
0951
0951
0 951
0 951
0 953
0 953
0 953
INTERCEPT
est
102
871
9 32
9 47
5 99
7 20
2 40
4 15
3 38
3 70
3 19
4 87
3 14
3 75
t
20 6
124
13 6
8 80
5 31
604
102
330
7 77
5 95
4 62
6 60
135
6 16
LM_CAP
est
X
190
236
177
313
242
X
0 359
0451
0 366
0451
0 333
0 466
0 463
t
X
3 05
391
2 80
4 94
361
X
14 1
801
134
800
5 65
14 3
14 2
POP
est
X
X
-1 98E-05
X
-2 78E-05
-4 I4E-05
X
X
0 111
X
0 106
-0 224
X
X
t
X
X
-6 61
X
-7 58
-7 06
X
X
1 84
X
1 73
-2 65
X
X
PCI_98
est
X
X
X
-5 35E-05
2 51E-04
2 43E-04
X
X
X
0 051
0 026
-0 092
X
-0 078
t
X
X
X
-0 932
3 70
3 59
X
X
X
0 736
0 369
-1 27
X
-1 09
JOBS
est
X
X
X
X
X
1 49E-05
X
X
X
X
X
0 247
0 152
0 164
t
X
X
X
X
X
2 96
X
X
X
X
X
5 56
5 10
5 16
Dependent Variable
VMT
LOG(VMT)
Logs of Independent Variables'
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
644
644
644
644
644
644
644
644
644
644
644
644
644
644
Adjusted R-Square
0 931
0 964
0 977
0 967
0977
0 991
0 989
0 990
0 995
0 991
0 995
0 995
0 995
0 995
INTERCEPT
est
58428
-7159437
-5107831
-8401708
-4751878
-1791609
134
9 83
3 38
3 79
3 19
4 87
651
7 25
t
0 250
-20 2
-169
-22 I
-124
-6 70
448
20 2
7 77
4 08
4 62
6 60
167
9 80
LM
est
X
15874
9347
14892
9214
4310
X
0 585
0451
0 558
0 451
0 333
0 21 1
0 203
I
X
23 2
145
22 2
14 1
953
X
741
801
7 38
8 00
5 65
3 46
3 32
POP
est
X
X
18 6
X
195
-2 63
X
X
0 659
X
0 655
0 443
X
X
t
X
X
18 7
X
166
-2 44
X
X
24 2
X
22 0
9 24
X
X
PCL98
est
X
X
X
136
-27 6
-168
X
X
X
0 653
0 026
-0 092
X
-0 091
t
X
X
X
7 24
-1 50
-1 41
X
X
X
751
0 369
-1 27
X
-1 18
JOBS
est
X
X
X
X
X
27 0
X
X
X
X
X
0 247
0 557
0 573
t
X
X
X
X
X
28 9
X
X
X
X
X
5 56
22 1
199
-------
TABLE A-2b
BASE RUN RESULTS - NORTH CAROLINA
Dependent Variable
VMT/CAP
LOG (VMT/CAP)
Logs of Independent Variables''
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
1300
1300
1300
1200
1200
1200
1300
1300
1300
1200
1200
1200
1200
1200
Ad lusted R-Square
0 944
0 945
0 945
0 944
0945
0 945
0 957
0961
0 961
0 961
0 961
0 961
0 961
0 961
INTERCEPT
est
13 1
118
14 1
109
129
13 1
2 60
5 17
4 85
4 45
4 24
4 95
3 39
3 31
t
28 8
21 8
17 9
721
8 18
691
128
23 9
7 80
6 43
4 1 1
4 77
6 82
4 40
LM CAP
est
X
357
328
306
261
260
X
0 459
0 475
0 426
0 435
0 438
0 495
0 493
t
X
4 47
4 13
3 32
2 83
281
X
119
9 79
9 49
8 02
8 15
109
102
POP
est
X
X
-2 10E-05
X
-2 49E-05
-2 87E-05
X
X
0 035
X
0 020
-0 204
X
X
t
X
X
-401
X
-4 12
-1 50
X
X
0 537
X
0 266
-2 29
X
X
PCI 98
est
X
X
X
5 82E-05
9 87E-05
9 41E-05
X
X
X
0 055
0 057
-0 037
X
0 008
t
X
X
X
0 760
1 29
1 18
X
X
X
0 929
0 958
-0 592
X
0 134
JOBS
est
X
X
X
X
X
4 40E-06
X
X
X
X
X
0 257
0 180
0 179
t
X
X
X
X
X
0212
X
X
X
X
X
4 35
3 82
3 70
Dependent Variable
VMT
LOG(VMT)
Logs of Independent Variables'
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
1300
1300
1300
1200
1200
1200
1300
1300
1300
1200
1200
1200
1200
1200
Ad lusted R-Square
0 958
0 969
0 991
0 973
0 992
0993
0 994
0 995
0 995
0 995
0 995
0 995
0 995
0 995
INTERCEPT
est
1505208
-1370819
-1824418
-1053630
-1695994
-936079
142
10 8
4 85
120
4 24
4 95
6 81
8 19
i
20 8
-9 03
-22 08
-4 90
-1478
-7 47
671
36 1
7 80
187
4 II
4 77
12 3
11 1
LM
est
X
7358
2251
6277
2006
2157
X
0 567
0 475
0 542
0 435
0 438
0 468
0 479
t
X
2 0 8
105
17 3
960
no
X
11 3
9 79
9 84
8 02
8 15
8 75
8 96
POP
est
X
X
23 4
X
23 0
9 23
X
X
0 560
X
0 585
0 357
X
X
I
X
X
53 5
X
52 6
7 54
X
X
107
X
9 39
4 42
X
X
PCI 98
est
X
X
X
5 37
4 208
-182
X
X
X
-0 111
0 057
-0 037
X
-0 159
t
X
X
X
0 558
-0 041
-3 62
X
X
X
-1 89
0 958
-0 592
X
-2 79
JOBS
est
X
X
X
X
X
157
X
X
X
X
X
0 257
0414
0 425
t
X
X
X
*
%
J) 9
X
X
X
X
X
4 35
9 12
9 36
-------
TABLE A-2c
BASE RUN RESULTS - VIRGINIA
Dependent Variable
VMT/CAP
LOG( VMT/CAP)
Logs of Independent Variables7
no
no
no
no
no
no
yes
Yes
yes
yes
yes
yes
yes
yes
N
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
Ad|usted R-Square
0 884
0 887
0 889
0 887
0 890
0 890
0 930
0 947
0 946
0 947
0947
0 947
0 947
0 947
INTERCEPT
est
14 4
9 13
10 J
8 17
7 47
7 52
2 72
4 99
4 90
3 97
3 89
3 88
4 58
3 82
(
15 6
8 22
9 13
6 03
5 56
560
106
57 7
20 0
122
9 82
981
32 4
II 6
LM.CAP
est
X
524
500
531
517
509
X
0 496
0 506
0 498
0 508
0510
0 519
0517
(
X
8 44
8 11
8 52
8 38
8 17
X
21 2
155
27 4
15 6
15 7
27 0
27 0
POP
est
X
X
-3 39E-05
X
-3 94E-05
-3 90E-05
X
X
0013
X
0013
-0 009
X
X
l
X
X
-6 86
X
-7 63
-7 52
X
X
0 385
X
0 366
-0 261
X
X
PCL98
est
X
X
X
8 26E-05
2 43E-04
2 48E-04
X
X
X
0 110
0 M0
0 0S9
X
0 089
t
X
X
X
1 24
3 53
3 59
X
X
X
3 25
3 25
2 56
X
2 57
JOBS
est
X
X
X
X
X
-4 63E-06
X
X
X
X
X
0 048
0 055
0 047
I
X
X
X
X
X
-0 949
X
X
X
X
X
3 04
3 64
3 05
Dependent Variable
VMT
LOG(VMT)
Logs of Independent Variables''
no
no
no
no
no i no
yes
yes
yes
yes
yes
yes
yes
ves
N
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
2592
Adiusted R-Square
0 873
0916
0 985
0 923
0 985
0 985
0 982
0 984
0 987
0 984
0 987
0 987
0 985
0 985
INTERCEPT
est
339296
-2371133
-930863
-2927310
-1035005
-1018985
129
9 16
4 90
7 78
3 89
3 88
7 54
7 03
t
4 12
-23 4
-20 4
-27 9
-20 6
-20 4
475
45 2
20 0
189
9 82
981
31 5
17 3
LM
est
X
10274
3244
9599
3229
3193
X
0 667
0 506
0 668
0 508
0510
0 646
0 647
t
X
35 6
23 1
34 1
23 1
22 9
X
18 5
15 5
18 6
156
157
184
IS 4
POP
est
X
X
186
X
IB 3
18 3
X
X
0 507
X
0 504 0 480
X
X
t
X
X
105
X
100
101
X
X
25 7
X
25 6 22 6
X
X
PCl_98
est
X
X
X
68 1
105
9 42
X
X
X
0 147
0 110 ¦ 0 089
X
0 059
t
X
X
X
]4 5
4 85
4 36
X
X
X
3 84
3 25 ! 2 56
X
t 55
JOBS
est
X
X
X
X
X
0 908
X
X
X
X
X
0 048
0 185
0 180
t
X
X
X
X
X
6 00
X
X
X
X
X
3 04
11 8
113
-------
TABLE A-3a
FIRST DIFFERENCE RUNS RESULTS - MARYLAND
Dependent Variable
VMT/CAP FIRST DIFF
LOG(VMT/CAP) FIRST DIFF
Logs of Independent Variables9
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
621
621
621
621
621
621
621
621
621
621
621
621
621
621
Ad lusted R-Square
0 040
0 065
0 065
0 070
0 070
0 069
0 073
0 102
0 102
0 108
0 107
0 108
0 104
0 108
INTERCEPT
est
0 943
0 797
0814
0 784
0 800
0 795
0 070
0 059
0 058
0 057
0 057
0 057
0 059
0 057
t
2 20
1 88
1 91
1 85
1 89
1 87
3 61
304
301
2 97
2 95
2 96
3 05
2 98
LM_CAP DIFF
est
X
1056
1040
1024
1009
1011
X
0 599
0 517
0 577
0 527
0 522
0610
0 586
t
X
4 02
3 94
3 90
3 83
3 84
X
4 38
3 40
4 22
3 47
344
4 46
4 28
POP DIFF
est
X
X
-2 56E-05
X
-2 41E-05
-2 27E-05
X
X
-0 369
X
-0 231
-0 311
X
X
t
X
X
-1 02
X
-0 967
-0 884
X
X
-1 23
X
-0 753
-0 987
X
X
PCI.98 DIFF
est
X
X
X
3 18E-04
3 14E-04
3 19E-04
X
X
X
0 278
0 257
0 206
X
0 243
t
X
X
X
2 13
2 10
2 11
X
X
X
2 26
2 03
1 54
X
1 89
JOBS DIFF
est
X
X
X
X
X
-5 5OE-06
X
X
X
X
X
0 126
0 162
0 100
i
X
X
X
X
X
-0 242
X
X
X
X
X
1 11
1 53
0910
Dependent Variable
VMT FIRST DIFF
LOG(VMT) FIRST DIFF
Logs of Independent Variables7
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
621
621
621
621
621
621
621
621
621
621
621
621
621
621
Ad|usted R-Square
0 396
0 429
0 439
0 430
0440
0 453
0 105
0 122
0 120
0 126
0 125
0 126
0 125
0 127
INTERCEPT
est
69018
49959
47112
48852
45893
51493
0 064
0 057
0 058
0 056
0 057
0 057
0 058
0 056
t
1 84
1 36
1 30
1 33
1 26
1 43
3 32
2 98
301
2 89
2 95
2 96
3 01
2 93
LM DIFF
est
X
2879
2704
2902
2727
2826
X
0 522
0517
0 536
0 527
0 522
0 514
0 527
t
X
584
5 50
5 89
5 55
5 82
X
344
3 40
3 54
3 47
3 44
3 39
3 48
POP DIFF
est
X
X
7 15
X
7 23
5 26
X
X
0 114
X
0 243
0 168
X
X
t
X
X
3 33
X
3 37
241
X
X
0 423
X
0 877
0 589
X
X
PCI 98 DIFF
est
X
X
X
174
186
124
X
X
X
0 232
0 257
0 206
X
0 183
t
X
X
X
1 35
1 45
0 975
X
X
X
1 88
2 03
1 54
X
1 43
JOBS DIFF
est
X
X
X
X
X
7 43
X
X
X
X
X
0 126
0 187
0 142
t
X
X
X
X
X
3 87
X
X
X
X
X
1 11
1 78
1 29
-------
TABLE A-3b
FIRST DIFFERENCE RUNS RESULTS - NORTH CAROLINA
Dependent Variable
VMT/CAP FIRST DIFF
LOG(VMT/CAP) FIRST DIFF
Logs of Independent Variables'?
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
1200
1200
1200
1100
1100
1100
1200
1200
1200
1100
1100
1100
1100
1 100
Adiusied R-Square
0 020
0 052
0053
0 061
0 062
0 061
0 025
0071
0 070
0 070
0 069
0 069
0 070
0 070
INTERCEPT
est
-0 486
-0 495
-0 407
-0 638
-0 535
-0 529
-0 020
-0 021
-0 020
-0 027
-0 027
-0 027
-0 025
-0 028
t
-I 08
-1 12
-0 909
-I 37
-1 13
-1 12
-0 869
-0 933
-0 874
-1 14
-1 11
-1 13
-1 08
-1 18
LM CAP D1FF
est
X
865
850
839
826
825
X
0618
0 609
0614
0612
0613
0 624
0617
t
X
6 13
6 00
5 83
5 73
5 72
X
7 39
6 95
7 05
6 77
6 78
7 18
7 08
POP DIFF
est
X
X
-7 65E-05
X
-8 17E-05
-7 80E-05
X
X
-0 110
X
-0 016
-0 056
X
X
t
X
X
-1 25
X
-1 268
-1 198
X
X
-0 372
X
-0 048
-0 168
X
X
PCI_98 DIFF
est
X
X
X
1 38E-04
1 23E-04
1 32E-04
X
X
X
0 096
0 095
0 068
X
0 072
t
X
X
X
I 34
1 18
1 23
X
X
X
1 06
1 02
0 689
X
0 753
JOBS DIFF
est
X
X
X
X
X
-1 25E-05
X
X
X
X
X
0 089
0 1 10
0 086
t
X
X
X
X
X
-0 367
X
X
X
X
X
0 832
1 10
0 816
Dependent Variable
VMT FIRST DIFF
LOG(VMT) FIRST DIFF
Logs of Independent Variables'7
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
1200
1200
1200
1100
1100
1 100
1200
1200
1200
noo
1100
1100
1100
1 100
Adiusted R-Square
0 376
0 422
0 425
0 430
0 431
0 430
0 037
0 077
0 077
0 075
0075
0 075
0 075
0 075
INTERCEPT
est
34756
22734
13029
22560
17838
17828
-0010
-0017
-0 020
-0 022
-0 027
-0 027
-0 022
-0 023
I
1 39
0 942
0 535
0 973
0 758
0 757
-0 431
-0 755
-0 874
-0 934
-1 11
-1 13
-0 927
-0 979
LM DIFF
est
X
2507
2470
2275
2260
2260
X
0 609
0 609
0613
0612
0613
0615
0614
t
X
9 29
9 17
8 98
891
8 90
X
6 95
6 95
6 78
6 77
678
681
6 79
POP DIFF
est
X
X
8 62
X
3 82
381
X
X
0281
X
0 372
0331
X
X
t
X
X
2 59
X
1 20
1 18
X
X
0 989
X
1 17
1 03
X
X
PCI 98 DIFF
est
X
X
X
-1 92
-1 14
-I 16
X
X
X
0 071
0 095
0 068
X
0 041
t
X
X
X
-0 374
-0 221
-0 217
X
X
X
0 777
1 02
0 689
X
0 436
JOBS DIFF
est
X
X
X
X
X
0 020
X
X
X
X
X
0 089
0 119
0 105
I
X
X
X
X
X
0012
X
X
X
X
X
0 832
1 19
1 00
-------
TABLE A-3c
FIRST DIFFERENCE RUNS RESULTS - VIRGINIA
Dependent Variable
VMT/CAP FIRST DIFF
LOG(VMT/CAP) FIRST DIFF
Logs of Independent Variables'
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
R-Square
0217
0 229
0 243
0 233
0 246
0 246
0 174
0 226
0 264
0 231
0 266
0 267
0 226
0 231
Adiusted R-Square
0 177
0 189
0 204
0 194
0 207
0 207
0 132
0 186
0 226
0 191
0 228
0 228
0 187
0 191
INTERCEPT
est
0 076
0 172
0 278
0 092
0 204
0 203
0008
0018
0 034
0013
0 031
0 030
0017
0 013
t
0 237
0 541
0 881
0 289
0 647
0 645
0 580
1 39
2 72
1 05
2 43
2 40
1 33
1 03
LM_CAP DIFF
est
X
331
266
308
248
248
X
0 431
0 149
0411
0 145
0 145
0 433
0413
t
X
5 99
4 78
5 56
4 45
4 45
X
126
3 56
120
3 45
3 47
12 7
12 0
POPDIFF
est
X
X
-1 63E-04
X
-1 56E-04
-1 56E-04
X
X
-0 734
X
-0712
-0 721
X
X
t
X
X
-6 67
X
-6 40
-6 37
X
X
-11 0
X
-10 6
-107
X
X
PC1_98 DIFF
est
X
X
X
2 23E-04
1 93E-04
1 94E-04
X
X
X
0 151
0 103
0 091
X
0 147
t
X
X
X
3 81
3 32
3 31
X
X
X
3 96
2 73
2 39
X
3 78
JOBS DIFF
est
X
X
X
X
X
-2 18E-06
X
X
X
X
X
0 048
0 041
0 020
t
X
X
X
X
X
-0 109
X
X
X
X
X
1 61
1 34
0 668
Dependent Variable
VMT FIRST DIFF
LOG(VMT) FIRST DIFF
Logs of Independent Variables''
no
no
no
no
no
no
yes
yes
yes
yes
yes
yes
yes
yes
N
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
2496
R-Square
0 466
0 472
0 501
0 472
0 501
0 503
0 208
0212
0214
0214
0216
0217
0214
0214
Adiusted R-Square
0 439
0 445
0 475
0 445
0 476
0 477
0 168
0 172
0 173
0 173
0 176
0 176
0 173
0 173
INTERCEPT
est
9641
8705
994
8260
-361
-0 293
0 039
0 038
0 034
0 036
0 031
0 030
0 037
0 035
I
0 824
0 747
0 088
0708
-0 032
0 000
3 12
3 03
2 72
2 85
2 43
2 40
2 93
2 78
LM DIFF
est
X
726
666
724
660
665
X
0 152
0 149
0 148
0 145
0 145
0 152
0 149
t
X
4 88
461
4 86
4 56
460
X
3 62
3 56
3 54
3 45
3 47
3 63
3 56
POP DIFF
est
X
X
102
X
10 3
10 1
X
X
0 117
X
0 143
0 133
X
X
t
X
X
11 7
X
1 1 9
116
X
X
2 21
X
2 67
2 47
X
X
PCI 98 DIFF
est
X
X
X
1 36
3 78
3 20
X
X
X
0 084
0 103
0 091
X
0 072
I
X
X
X
0 633
1 80
I 52
X
X
X
2 27
2 73
2 39
X
1 93
JOBS DIFF
est
X
X
X
X
X
1 74
X
X
X
X
X
0 048
0 066
0 057
t
X
X
X
X
X
2 42
X
X
X
X
X
1 61
2 25
1 91
-------
TABLE A-4a
ELASTICITY RUNS (SHORT / LONG RUN) - MARYLAND
Dependent Variable
LOG(VMT/CAP)
N
621
621
621
621
621
621
621
Adiusted R-Square
0 964
0 964
0 964
0 964
0 965
0 965
0 965
INTERCEPT
est
1 91
1 37
1 42
1 05
1 85
1 41
1 48
I
105
3 32
2 53
1 66
2 68
5 79
2 65
Log (VMT/CAP)
est
0 556
0 552
0 556
0 553
0 529
0 533
0 533
lagged 1 year
l
159
15 8
159
15 8
14 8
15 1
15 0
Log (LM_CAP)
est
0 159
0 225
0 166
0 226
0 191
0 229
0 229
t
6 20
4 28
6 17
4 29
3 56
6 70
6 69
Log (POP)
est
X
0 079
X
0 072
-0 068
X
X
t
X
1 45
X
1 31
-0 914
X
X
Log (PCL98)
est
X
X
0 055
0 042
-0015
X
-0 010
t
X
X
0910
0 678
-0 239
X
-0 149
Log (JOBS)
est
X
X
X
X
0 116
0 089
0 091
t
X
X
X
X
2 78
3 08
2 94
Short-Run Elasticity
0.159
0.225
0.166
0.226
0.191
0.229
0.229
Long-Run Elasticity
0.357
0.503
0.374
0.505
0.406
0.491
0.491
Dependent Variable
LOG(VMT)
N
621
621
621
621
621
621
621
Adiusted R-Square
0 996
0 997
0 996
0 996
0 997
0 996
0 996
INTERCEPT
est
2 30
1 48
0916
1 28
1 97
251
2 68
t
5 45
3 62
1 39
204
2 87
6 20
3 92
Log (VMT)
est
0 768
0 559
0 747
0 559
0 537
0 593
0 592
lagged 1 year
t
29 1
160
27 3
160
149
17 2
17 1
Log (LM)
est
0 143
0215
0 153
0215
0 187
0 125
0 123
t
260
4 09
2 80
4 10
3 48
2 37
2 33
Log (POP)
est
X
0 288
X
0 284
0214
X
X
t
X
8 55
X
8 05
4 69
X
X
Log (PCI_98)
est
X
X
0 168
0 026
-0 023
X
-0 020
t
X
X
2 73
0 428
-0 352
X
-0 307
Log (JOBS)
est
X
X
X
X
0 101
0 222
0 227
t
X
X
X
X
2 40
7 45
6 89
Short-Run Elasticity
0.143
0.215
0.153
0.215
0.187
0.125
0.123
Long-Run Elasticity
0.617
0.488
0.606
0.489
0.403
0.307
0.302
-------
TABLE A-4b
ELASTICITY RUNS (SHORT / LONG RUN) - NORTH CAROLINA
Dependent Variable
LOG( VMT/CAP)
N
1200
1200
1100
1100
1100
1100
1100
Ad]usied R-Square
0 976
0 976
0 977
0 977
0 977
0 977
0 977
INTERCEPT
est
4 55
4 75
3 93
4 70
5 03
3 96
3 55
t
21 3
8 38
6 68
5 19
5 50
8 96
5 53
Log (VMT/CAP)
est
0 IS6
0 185
0 162
0 162
0 154
0 158
0 158
lagged 1 year
t
7 97
7 95
6 83
6 83
6 46
6 63
6 63
Log (LM_CAP)
est
0 438
0 429
0 424
0 396
0 402
0 458
0 446
t
129
10 3
11 0
8 65
8 79
11 6
108
Log (POP)
est
X
-0 022
X
-0 072
-0 174
X
X
t
X
-0 387
X
-1 12
-2 27
X
X
Log (PCI_98)
est
X
X
0 061
0 051
0 005
X
0 044
t
X
X
1 23
1 03
0 091
X
0 867
Log (JOBS)
est
X
X
X
X
0 123
0 070
6 13E-02
t
X
X
X
X
2 44
1 69
1 44
Short-Run Elasticity
0.438
0.429
0.424
0.396
0.402
0.458
0.446
Long-Run Elasticity
0.538
0.526
0.506
0.473
0.475
0.543
0.530
Dependent Variable
LOG(VMT)
N
1200
1200
1100
1100
1100
1 100
1100
Ad|usted R-Square
0 997
0 997
0 997
0 997
0 997
0 997
0 997
INTERCEPT
est
8 06
4 70
9 02
4610
4 937
6 69
7 40
t
22 1
8 28
14 60
5 09
5 40
12 96
11 03
Log (VMT)
est
0 238
0 187
0 206
0 164
0 156
0 174
0 169
lagged 1 year
t
104
80
8 9
69
6 5
7 3
7 1
Log (LM)
est
0455
0 426
0 432
0 394
0400
0418
0 424
t
10 66
1021
9 32
8 60
8 74
9 17
9 29
Log (POP)
est
X
0 367
X
0 373
0 275
X
X
t
X
761
X
6 54
3 93
X
X
Log (PCI_98)
est
X
X
-0039
0 055
0 009
X
-0 080
t
X
X
-0 789
1 11
0 18
X
-1 65
Log (JOBS)
est
X
X
X
X
0 121
0 226
0 237
I
X
X
X
X
2 39
5 53
5 72
Short-Run Elasticity
0.455
0.426
0.432
0.394
0.400
0.418
0.424
Long-Run Elasticity
0.597
0.525
0.545
0.471
0.474
0.506
0.511
-------
TABLE A-4c
ELASTICITY RUNS (SHORT! LONG RUN) - VIRGINIA
Dependent Variable
LOG(VMTZCAP)
N
2496
2496
2496
2496
2496
2496
2496
Adiusted R-Square
0 984
0 984
0 984
0 984
0 984
0 984
0 984
INTERCEPT
est
1 02
0 723
0 806
0512
0515
0 884
0 754
t
139
4 72
4 25
2 21
2 22
9 19
3 94
Log (VMT/CAP)
est
0817
0817
0816
0816
0815
0815
0815
lagged 1 year
t
73 2
73 3
73 0
73 1
73 0
73 0
72 9
Log (LM_CAP)
est
0 112
0 147
0 113
0 147
0 148
0 120
0 120
t
9 54
7 45
9 60
7 49
7 53
9 76
9 75
Log (POP)
est
X
0 045
X
0 045
0 038
X
X
I
X
221
X
2 21
1 83
X
X
Log (PCI_98)
est
X
X
0 024
0 023
0017
X
0015
t
X
X
1 23
1 21
0 854
X
0 783
Log (JOBS)
est
X
X
X
X
0014
0019
0018
t
X
X
X
X
1 57
2 21
2 00
Short-Run Elasticity
0.112
0.147
0.113
0.147
0.148
0.120
0.120
Long-Run Elasticity
0.609
0.801
0.611
0.802
0.803
0.650
0.649
Dependent Variable
LOG(VMT)
N
2496
2496
2496
2496
2496
2496
2496
Adiusted R-Square
0 996
0 997
0 996
0 997
0 997
0 996
0 996
INTERCEPT
est
0 891
0 489
0 492
0 118
0 121
0719
0 448
t
6 49
331
2 25
0 531
0 541
4 93
2 05
Log (VMT)
est
0 876
0 841
0 875
0 840
0 840
0 868
0 868
lagged 1 year
t
90 0
77 9
89 8
77 8
77 6
87 2
87 2
Log (LM)
est
0 134
0 128
0 t35
0 129
0 130
0 135
0 136
t
7 02
6 78
7 09
6 86
6 88
7 10
7 14
Log (POP)
est
X
0 086
X
0 086
0 082
X
X
t
X
7 03
X
6 99
6 34
X
X
Log (PCI_98)
est
X
X
0 044
0 041
0 037
X
0 032
t
X
X
2 35
2 22
1 97
X
1 66
Log (JOBS)
est
X
X
X
X
0 008
0 028
0 025
t
X
X
X
X
0 920
3 48
3 05
Short-Run Elasticity
0.134
0.128
0.135
0.129
0.130
0.135
0.136
Long-Run Elasticity
1.08
0.808
1.08
0.811
0.811
1.02
1.03
-------
TABLE A-5a
TRAFFIC VOLUME RUNS (LOW / MID / HIGH VOLUME ) - MARYLAND
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT/CAP)
LOG(VMT/CAP)
LOG(VMT/CAP)
LOG(VMTZCAP)
N
644
644
644
195
195
195
330
330
330
119
119
119
Adjusted R-Square
0 934
0 951
0951
0 960
0 965
0 964
0939
0951
0 951
0 955
0 982
0 986
INTERCEPT
esi
2 40
4 15
3 70
221
3 81
4 62
2 48
4 30
4 84
2 31
6 II
1 I 7
t
102
330
5 95
51 9
105
3 60
39 9
189
4 29
57 2
184
105
Log (LM_CAP)
est
X
0 359
0 366
X
0 304
0 308
X
0 382
0 371
X
0 624
0 585
t
X
14 1
134
X
444
4 47
X
8 23
7 22
X
11 5
12 1
Log (POP)
est
X
X
X
X
X
X
X
X
X
X
X
X
t
X
X
X
X
X
X
X
X
X
X
X
X
Log (PCI_98)
est
X
X
0 051
X
X
-0 083
X
X
-0 062
X
X
-0 589
i
X
X
0 736
X
X
-0 660
X
X
-0 484
X
X
-5 18
Traffic Volume Classifications
Low Volume - VMT/LM < 2000
Mid Volume - 2000< VMT/LM < 5000
High Volume - VMT/LM > 5000
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependem Variable
LOG(VMT)
LOG(VMT)
LOG(VMT)
LOG(VMT)
N
644
644
644
644
195
195
195
195
330
330
330
330
119
119
119
119
Adjusted R-Square
0 989
0 990
0 995
0 995
0 972
0 973
0 976
0 976
0 974
0 974
0 983
0 983
0 987
0 989
0992
0 993
INTERCEPT
est
134
9 83
3 38
3 19
13 5
125
7 39
7 55
132
II 7
3 92
4 45
15 1
II 9
8 42
II 9
t
448
20 2
7 77
4 62
321
22 8
6 40
4 87
192
124
391
2 93
483
13 8
8 99
10 2
Log (LM)
est
X
0 585
0 451
0 451
X
0 176
0 135
0 137
X
0 263
0 429
0417
X
0 481
0 370
0 535
t
X
741
801
800
X
1 95
1 60
1 59
X
1 68
3 34
3 18
X
3 76
3 37
4 99
Log (POP)
est
X
X
0 659
0 655
X
X
0 470
0 471
X
X
0 628
0 638
X
X
0 329
0 404
t
X
X
24 2
22 0
X
X
4 90
4 88
X
X
120
II 3
X
X
5 93
7 56
Log(PCI_98)
est
X
X
X
0 026
X
X
X
-0 019
X
X
X
-0 060
X
X
X
-0 557
t
X
X
X
0 369
X
X
X
-0 154
X
X
X
-0 469
X
X
X
-4 3!
-------
TABLE A-5b
TRAFFIC VOLUME RUNS (LOW / MFD / HIGH VOLUME ) ¦ NORTH CAROLINA
ALL
LOW VOLUME
MID VOLUME
HICjH volume.
Dependent Vmable
LOtKVMT/CAPi
LOGiVMT'CAP)
LOGiVMT'CAP)
LOGiVMT'CAP)
N
1300
1300
1200
500
500
435
701
701
640
99
99
85
AdjiKttd li-Squire
0 957
0 961
0 961
C949
0
0 954
09 JO
0976
0 978
a?65
0930
0982
INTERCEPT
est
260
5 17
4 45
2 52
4 17
2 OS
2 67
444
7 96
2 55
596
7 29
I
128
219
643
120
150
2 26
144
31 6
8 34
51 6
125
2 93
Log (LM_CAP)
est
X
0459
0426
X
0 368
0258
X
0 330
0 573
X
0617
0581
t
X
119
9 49
X
5 97
3 48
X
127
964
X
7 20
6 57
Log (POP)
esl
X
X
X
X
X
X
X
X
X
X
X
X
t
X
X
X
X
X
X
X
X
X
X
X
X
Log (PCI.98)
est
X
X
0055
X
X
O 168
X
X
-0 2(8
X
X
¦0 129
I
X
X
0929
X
X
2 12
X
X
-2 54
X
X
-0 497
TrafTit Volume Classifications
Low Volume- VMT/LM <2000
Mid Volume - 2000< VMT/LM < 5000
High Volume - VMT/LM > 5000
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT)
LOG(VMT)
LOG(VMT)
LOG(VMT)
N
I3CO I 1300
1300
1200
500
500
500
475
701
701
701
640
99
99
99
85
Adjusted R-Sq jare
0 994
0 995
0995
0 995
0 9&0
0991
0992
0 992
0 991
0 992
0993
0 993
0 992
0 995
0 996
0 997
INTERCEPT
esl
142
106
4 85
4 24
122
102
2 54
2 29
142
105
6 29
10 1
14 0
9 28
4 15
S 27
t
671
36 1
7 80
4 11
558
23 7
2 16
I 55
732
28 9
704
609
265
130
3 10
1 91
Log (LM)
est
X
0567
0475
0 435
X
0389
0439
0 247
X
0612
0 523
0532
X
0 799
0716
0 684
i
X
II 3
9 79
8 02
X
4 69
5 54
2 59
X
100
8 39
8 20
X
664
6 55
6 28
Log (POP)
est
X
X
0 560
0 585
X
X
0763
0 725
X
X
0412
0 309
X
X
0490
0 549
I
X
X
107
9 39
X
X
6 89
5 97
X
X
5 16
3 21
X
X
4 35
4 57
Log (PCL98)
est
X
X
X
0 057
X
X
X
0 169
X
X
X
-0 268
X
X
X
-0 164
t
X
X
X
0 958
X
X
X
2 12
X
X
X
-2 93
X
X
X
-0 635
-------
TABLE A-5c
TRAFFIC VOLUME RUNS (LOW / MID 1 HIGH VOLUME) - VIRGINIA
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOC(VMT/CAP)
LOG(VMTZCAP)
LOG(VMT/CAPj
LOG(VMTVCAP)
N
2592
2592
2592
1352
1352
1352
1054
1054
1054
186
186
186
Adjusted R-Square
0910
0 947
0 947
0 923
0910
0 940
0 961
0 971
0 972
0960
0 984
0984
INTERCEPT
est
2 72
4 99
3 97
271
564
5 94
2 80
4 94
1 34
2 83
658
8 84
t
106
57 7
122
75 7
35 7
152
81 8
39 6
2 40
35 4
25 0
6 41
Log (LM_CAP)
est
X
0 496
0 498
X
0 635
0 634
X
0478
0 504
X
0 692
0 689
t
X
27 2
27 4
X
189
189
X
17 7
18 8
X
146
146
Log (POP)
est
X
X
X
X
X
X
X
X
X
X
X
X
t
X
X
X
X
X
X
X
X
X
X
X
X
Log (PCL98)
est
X
X
0 110
X
X
-0 033
X
X
0 398
X
X
-0 234
I
X
X
3 25
X
X
-0 853
X
X
664
X
X
-1 67
Traffle Volume Classifications
Low Volume - VMT/LM < 2000
Mid Volume - 2000< VMT/LM < 5000
High Volume- VMT/LM > 5000
ALL
LOW VOLUME
MfD VOLUME
HIGH VOLUME
Dependent Variable
LOG
-------
TABLE A-6a
TRAFFIC VOLUME / ELASTICITY RUNS - MARYLAND
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT/CAP)
LOG( VMT/CAP)
LOG(VMTZCAP)
LOG(VMT/CAP)
N
621
621
177
177
325
325
119
119
Adjusted R-Square
0 964
0 964
0 962
0 962
0 961
0961
0 990
0 990
INTERCEPT
est
1 91
1 42
2 78
3 48
2 33
1 83
2 19
5 07
t
105
2 53
5 49
2 32
8 03
1 78
4 14
3 62
Log (VMT/CAP)
est
0 556
0 556
0 273
0 275
0 486
0 489
0 640
0 544
lagged 1 year
t
159
15 9
3 19
3 20
9 73
971
8 40
6 30
Log (LM_CAP)
est
0 159
0 166
0215
0 219
0 203
0211
0 217
0 262
t
6 20
6 17
2 75
2 78
4 58
4 45
344
404
Log (POP)
est
X
X
X
X
X
X
X
X
t
X
X
X
X
X
X
X
X
Log (PCI_98)
est
X
0 055
X
-0 071
X
0 056
X
-0 242
t
X
0910
X
-0 494
X
0 499
X
-2 22
Short-Run Elasticity
0.159
0.166
0.215
0.219
0.203
0.211
0.217
0.262
Long-Run Elasticity
0.357
0.374
0.296
0.302
0.395
0.413
0.604
0.575
Traffic Volume Classifications
Low Volume - VMT/LM < 2000
Mid Volume - 2000< VMT/LM < 5000
High Volume - VMT/LM > 5000
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT)
LOG(VMT)
LOG(VMT)
LOG(VMT)
N
621
621
621
177
177
177
325
325
325
119
119
119
Adjusted R-Square
0 996
0 997
0 996
0 972
0 974
0 973
0 985
0 987
0 986
0 995
0 996
0 996
INTERCEPT
est
2 30
1 48
1 28
8 62
5 82
6 22
4 76
2 86
261
2 40
2 40
4 57
t
5 45
3 62
2 04
7 10
3 98
3 19
5 56
3 14
1 92
2 39
2 45
3 37
LAG VMT
est
0 768
0 559
0 559
0 322
0 231
0 232
0 649
0 500
0 501
0 765
0 668
0 597
t
29 1
160
160
3 79
2 66
2 66
15 5
9 88
9 85
11 3
8 63
7 29
LM
est
0 143
0215
0215
0 100
0 088
0 091
-0 001
0 140
0 145
0 182
0 182
0 275
t
2 60
4 09
4 10
1 04
0 943
0 970
-0 010
1 20
1 22
2 13
2 18
301
POP
est
X
0 288
0 284
X
0 362
0 361
X
0 280
0 275
X
0 114
0 170
t
X
8 55
8 05
X
3 20
3 17
X
4 89
4 50
X
2 40
3 23
PCI 98
est
X
X
0 026
X
X
-0 044
X
X
0 028
X
X
-0 248
t
X
X
0 428
X
X
-0310
X
X
0 248
X
X
-2 25
Short-Run Elasticity
0.143
0.215
0.215
0.100
0.088
0.091
-0.001
0.140
0.145
0.182
0.182
0.275
Lone-Run Elasticity
0.617
0.488
0.489
0.147
0.114
0.119
-0.003
0.280
0.291
0.775
0.547
0.682
-------
TABLE A-6b
TRAFFIC VOLUME / ELASTICITY RUNS - NORTH CAROLINA
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT/CAP)
LOG(VMT/CAP)
LOG(VMT/CAP)
LOG( VMT/CAP)
N
1200
1100
452
427
652
591
96
82
Adjusted R-Square
0 976
0 977
0 963
0 965
0 984
0984
0 980
0 983
INTERCEPT
est
4 55
3 93
4 37
1 16
4 08
6 78
4 95
3 63
t
21 3
6 68
150
1 35
123
7 60
6 87
1 25
Log (VMT/CAP)
est
0 186
0 162
0 047
0031
0 301
0 268
0 226
0 224
lagged 1 year
t
7 97
6 83
1 37
0 894
8 24
7 14
2 07
1 93
Log (LM_CAP)
est
0438
0 424
0 442
0321
0 406
0449
0 528
0 527
t
129
11 0
7 50
4 66
7 74
800
5 37
5 58
Log (POP)
est
X
X
X
X
X
X
X
X
t
X
X
X
X
X
X
X
X
Log (PCI_98)
est
X
0 061
X
0 284
X
-0 240
X
0 152
t
X
1 23
X
3 77
X
-3 11
X
0 549
Short-Run Elasticity
0.438
0.424
0.442
0.321
0.406
0.449
0.528
0.527
Lone-Run Elasticity
0.538
0.506
0.464
0.331
0.582
0.614
0.683
0.680
Traffic Volume Classifications
Low Volume - VMT/LM < 2000
Mid Volume - 2000< VMT/LM < 5000
High Volume - VMT/LM > 5000
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG (VMT)
LOG(VMT)
LOG(VMT)
LOG(VMT)
N
1200
1200
1100
452
452
427
652
652
591
96
96
82
Adiusted R-Square
0 997
0 997
0 997
0 993
0 994
0 994
0 995
0 995
0 995
0 996
0 996
0 997
INTERCEPT
est
8 06
4 70
461
8 46
1 57
0 467
6 90
4 68
9 30
5 46
3 42
2 24
t
22 11
8 28
5 09
15 3
1 35
0 328
13 2
5 46
5 89
4 17
2 32
0715
LAG VMT
est
0 238
0 187
0 164
0 095
0 045
0 029
0 340
0311
0 275
0 356
0 226
0 225
t
104
80
69
2 69
1 31
0 847
9 54
8 54
7 36
351
2 08
1 96
LM
est
0 455
0 426
0 394
0491
0 550
0 352
0 408
0 373
0 392
0612
0610
0 601
t
10 66
1021
8 60
641
751
4 06
7 01
6 35
6 45
5 01
521
5 31
POP
est
X
0 367
0 373
X
0 745
0710
X
0 246
0 138
X
0 337
0 344
t
X
761
6 54
X
664
5 80
X
3 25
1 51
X
264
2 37
PCI_98
est
X
X
0 055
X
X
0 280
X
X
-0 300
X
X
0 119
t
X
X
1 107
X
X
3 69
X
X
-3 62
X
X
0 424
Short-Run Elasticity
0.455
0.426
0.394
0.491
0.550
0.352
0.408
0.373
0.392
0.612
0.610
0.601
Long-Run Elasticity
0.597
0.525
0.471
0.543
0.577
0.362
0.618
0.541
0.540
0.951
0.789
0.775
-------
TABLE A-6c
TRAFFIC VOLUME / ELASTICITY RUNS - VIRGINIA
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT/CAP)
LOG(VMT/CAP)
LOG (VMT/CAP)
LOG(VMT/CAP)
N
2496
2496
1272
1272
1040
1040
184
184
Adiusted R-Square
0 984
0 984
0 976
0 976
0 987
0 987
0 992
0 992
INTERCEPT
est
1 02
0 806
1 85
1 97
1 47
0 244
264
2 62
t
139
4 25
130
7 08
11 3
0 642
6 58
2 24
Log (VMT/CAP)
est
0817
0816
0 739
0 738
0 730
0717
0 636
0 637
lagged 1 year
t
73 2
73 0
41 1
41 1
35 1
34 0
II 6
11 3
Log (LM_CAP)
est
0 112
0 113
0 245
0 245
0 159
0 175
0 297
0 297
I
9 54
9 60
9 93
991
781
8 43
5 92
5 82
Log (POP)
est
X
X
X
X
X
X
X
X
t
X
X
X
X
X
X
X
X
Log (PCI_98)
est
X
0 024
X
-0 013
X
0 143
X
0 002
t
X
1 23
X
-0 506
X
3 44
X
0016
Short-Run Elasticity
0.112
0.113
0.245
0.245
0.159
0.175
0.297
0.297
Long-Run Elasticity
0.609
0.611
0.939
0.936
0.588
0.617
0.818
0.818
Traffic Volume Classifications
Low Volume - VMT/LM < 2000
Mid Volume - 2000< VMT/LM < 5000
High Volume - VMT/LM > 5000
ALL
LOW VOLUME
MID VOLUME
HIGH VOLUME
Dependent Variable
LOG(VMT)
LOG(VMT)
LOG(VMT)
LOG(VMT)
N
2496
2496
2496
1272
1272
1272
1040
1040
1040
184
184
184
Adjusted R-Square
0 996
0 997
0 997
0 993
0 993
0 993
0 992
0 992
0 992
0 995
0 995
0 995
INTERCEPT
est
0 89
0 49
0 12
1 90
1 51
1 52
1 83
1 35
0 26
3 06
2 85
3 86
t
6 49
3 31
0 53
7 56
4 02
3 50
6 76
4 70
064
4 62
4 06
2 90
LAG VMT
est
0.876
0 841
0 840
0 769
0 764
0 764
0 806
0 763
0 747
0 673
0 656
0 646
t
90 0
77 9
77 8
44 67
43 20
43 11
44 1
37 59
36 25
11 9
10 99
10 64
LM
est
0.134
0 128
0 129
0 199
0 203
0 203
0 125
0 125
0 122
0 258
0 260
0 262
t
7 02
6 78
6 86
5 77
5 868
5 865
3 741
3 77
371
4 33
4 35
4 38
POP
est
X
0 086
0 086
X
0 042
0 042
X
0 103
0 094
X
0 041
0041
t
X
7 03
6 99
X
1 36
1 36
X
4 66
4 25
X
0 90
0 92
PCL98
est
X
X
0041
X
X
-0 001
X
X
0 149
X
X
-0 093
t
X
X
2215
X
X
-0 040
X
X
3 688
X
X
-0 89
Short-Run Elasticity
0.134
0.128
0.129
0.199
0.203
0.203
0.125
0.125
0.122
0.258
0.260
0.262
Long-Run Elasticity
1.078
0.808
0.811
0.863
0.860
0.860
0.647
0.528
0.483
0.790
0.757
0.742
-------
TABLE A-7
SUMMARY OF TRAFFIC VOLUME RUNS, ALTERNATIVE METHOD
LOW VOLUME RUNS
Dependent Variable
LOG(VMT)
Slate
All Stales
Maryland
North Carolina
Virginia
DC - Baltimore
Years of Data
1985-1995
1969-1996
1985-1997
1970-1996
1970-1996
N
880
880
84
84
520
480
999
999
X
X
Adjusted R-Square
0980
0 980
0 927
0926
0 986
0 986
0 968
0 968
X
X
Intercept
est
4 07
3 19
7 22
709
3 94
221
3 46
4 39
X
X
I
3 31
2 19
2 62
241
3 67
1 39
4 33
4 89
X
X
Log (Lane Miles)
est
0 475
0 449
0 143
0 147
0 428
0 296
0 676
0 679
X
X
i
4 61
4 26
0 805
0 808
501
2 98
9 34
9 40
X
X
Log (Population)
est
0 606
0619
0 440
0415
0 628
0 660
0 529
0 540
X
X
(
6 18
6 27
1 24
1 02
6 07
5 45
8 82
900
X
X
Log (Income Per Capua)
est
X
0 093
X
0 036
X
0 222
X
-0 114
X
X
(1998$)
l
X
1 14
X
0 131
X
2 29
X
-2 24
X
X
MID VOLUME RUNS
Dependent Variable
LOG(VMT)
Slate
All Stales
Maryland
North Carolina
Virginia
DC - Baltimore
Years of Daia
1985-1995
1969-1996
1985-1997
1970-1996
1970-1995
N
f 320
1320
420
420
720
660
1350
1350
189
189
Adjusted R-Square
0 990
0990
0 985
0 985
0 993
0 994
0 982
0 983
0 983
0 984
Intercept
est
5 24
1 36
0 092
-0 771
5 00
6 96
5 48
1 98
1 36
-3 79
i
8 28
1 42
0 136
-0 797
631
5 06
18 7
4 09
1 42
-2 04
Log (Lane Miles)
est
0 707
0 662
0 798
0815
0 542
0 558
0 523
0512
0 434
0 375
l
103
9 67
8 68
8 77
8 79
844
130
132
560
4 83
Log (Population)
est
0 387
0 468
0 764
0 744
0512
0 464
0 439
0423
0 875
0 880
l
8 24
960
20 9
185
7 43
5 75
196
19 4
9 56
9 90
Log (Income Per Capua)
est
X
0 334
X
0 104
X
-0 153
X
0 399
X
0 553
(1998$)
i
X
5 38
X
1 25
X
-1 91
X
8 96
X
3 20
HIGH VOLUME RUNS
Dependent Variable
LOG(VMT)
Stale
All Slates
Maryland
North Carolina
Virginia
DC - Baltimore
Yeais of Data
1985-1995
1969-1996
1985-(997
1970-1996
1970-1996
N
220
220
140
140
65
60
243
243
243
243
Adjusted R-Square
0 994
0 995
0 994
0 995
0 993
0 995
0 983
0 983
0 996
0 996
Intercept
esi
2 95
-0 732
5 42
9 58
5 28
891
0 966
134
821
9 48
t
2 96
-0 348
7 23
840
4 05
3 15
17 3
7 12
16 8
106
Log (Lane Miles)
esi
0 568
0 560
0 435
0 480
0601
0 535
0 210
0 184
0 241
0 244
t
8 31
8 23
4 17
500
6 87
657
2 77
241
3 15
321
Log (Population)
esi
0683
0 740
0 532
0 638
0461
0 587
0 220
0 187
0 381
0 392
t
8 78
8 98
18 1
179
4 32
544
3 83
3 18
14 0
140
Log (Income Per Capita)
est
X
0 296
X
-0 603
X
-0474
X
-0 342
X
-0 148
t1998$)
t
X
1 98
X
-4 57
X
-1 68
X
-2 09
X
-1 70
-------
TABLE A-8
SUMMARY OF TRAFFIC VOLUME / ELASTICITY RUNS, ALTERNATIVE METHOD
LOW VOLUME
Dependent Variable
LOG(VMT)
State
All Stales
Maryland
North Carolina
Virginia
DC - Baltimore
Years of Data
1986-1991
1970-1996
1986-1997
1971-1996
1971-1996
N
800
800
81
81
480
440
962
962
X
X
Adjusted R-Square
0 987
0 987
0 920
0918
0 993
0 993
0 989
0 989
X
X
Intercept
est
2 34
0 138
6 45
6 51
3 33
1 23
0 549
0 576
X
X
I
204
0 101
2 19
2 07
3 68
0 981
1 OS
1 02
X
X
Log(VMT)
est
0417
0417
0 204
0 206
0 092
0 066
0 804
0 804
X
X
(lagged 1 year)
I
138
13 9
1 39
I 38
2 66
1 93
41 1
40 8
X
X
Log (Lane Miles)
est
0 329
0 268
0 156
0 154
0 456
0 295
0 161
0 161
X
X
t
341
2 73
0 848
0812
6 55
3 75
3 36
3 36
X
X
Log (Population)
est
0 328
0 370
0 258
0 269
0 555
0 592
0 104
0 105
X
X
t
3 60
4 03
0 675
0 632
6 36
5 97
2 73
2 72
X
X
Log (Income Per Capita)
est
X
0 217
X
-0018
X
0 302
X
-0 003
X
X
(1998$)
t
X
2 94
X
-0063
X
4 02
X
-0 113
X
X
Short-Run Elasticity
0 329
0 268
0 156
0 154
0 456
0 295
0 161
0 161
X
X
Long-Run Elasticity
0 565
0 460
0 196
0 193
0 502
0316
0 823
0 824
X
X
MID VOLUME
Dependent Variable
LOG(VMT)
Stale
All States
Maryland
North Carolina
Virginia
DC - Baltimore
Years of Data
1986-1995
1970-1996
1986-1997
1971-1996
1971-1996
N
1200
1200
405
405
660
605
1300
1300
182
182
Adjusted R-Square
0 994
0 994
0 990
0 990
0 995
0 996
0 995
0 995
0 991
0 991
Intercept
est
2 39
1 70
¦O 133
-0 540
3 78
7 96
0 519
-0 271
0 185
-2 62
t
4 19
1 98
-0 229
-0 636
4 86
5 90
2 88
-1 01
0 257
-1 77
Log(VMT)
est
0618
0614
0 561
0 559
0 341
0 297
0 845
0 833
0 728
0 697
(lagged 1 year)
(
26 5
26 0
13 1
130
10 1
8 52
58 6
56 7
12 1
II 4
Log (Lane Miles)
est
0 405
0 400
0 365
0 376
0 380
0418
0 137
0 141
0 140
0 129
t
7 06
6 94
4 24
4 29
6 78
7 04
600
6 23
2 21
2 07
Log (Population)
est
0 039
0 058
0 348
0341
0 284
0 189
0 074
0 075
0 249
0 286
t
0904
1 26
7 62
7 23
4 18
2 37
544
5 57
2 84
3 25
Log (Income Per Capita)
est
X
0 057
X
0 047
X
-0 273
X
0 097
X
0 290
(1998$)
t
X
1 08
X
0 658
X
-3 78
X
3 96
X
2 16
Shon-Run Elasticity
0 405
0 400
0 365
0 376
0 380
0418
0 137
0 141
0 140
0 129
Long-Run Elasticity
1 06
1 04
0 831
0 852
0 576
0 594
0 885
0 846
0514
0 428
HIGH VOLUME
Dependent Variable
LOG(VMT)
State
All States
Maryland
North Carolina
Virginia
DC - Baltimore
Years of Data
1986-1995
1970-1996
1986-1997
1971-1996
1971-1996
N
200
200
135
135
60
55
234
234
234
234
Adjusted R-Square
0 997
0 997
0 997
0 997
0 993
0 994
0996
0 996
0999
0999
Intercept
est
0 945
-1 43
2 38
3 49
5 08
5 71
0 736
1 56
1 80
2 36
1
1 13
-0817
3 36
3 16
3 19
1 63
1 75
1 50
3 77
3 50
Log (VMT)
est
0 673
0 663
0 645
0 608
0 197
0 172
0 897
0 893
0751
0 748
(lagged 1 year)
t
II 2
110
103
8 85
1 47
1 28
27 6
27 1
188
187
Log (Lane Miles)
est
0 229
0 229
0 162
0 194
0 536
0 501
0 105
0 101
0 175
0 176
t
3 65
3 68
2 05
2 35
4 94
5 10
2 88
2 75
3 83
3 85
Log (Population)
est
0 206
0 255
0 156
0 2CM
0 283
0 376
0 011
0004
0070
0 075
1
2 62
3 02
3 77
3 70
206
2 43
0 391
0 115
3 07
3 23
Log (Income Per Capita)
est
0 206
0 187
X
-0 143
X
-0 119
X
-0069
X
-0061
(1998$)
t
2 62
1 54
X
-1 31
X
-0 353
X
-0 865
X
-1 19
Shon-Run Elasticity
0 229
0 229
0 162
0 194
0 536
0 501
0 105
0 101
0 175
0 176
Long-Run Elasticity
0 699
0 680
0 457
0 495
0 667
0 605
1 02
0 942
0 702
0 699
-------
APPENDIX B: CORRELATION MATRICES
This appendix contains four sets of correlation matrices for each study area: one for logs and one
for non-log variables, for each of the basic variables and the first-difference forms of the
variables The following pages contain 24 tables, 4 for each of the five study areas.
-------
ALL STATES LINEAR CORRELATION MATRIX
VARIABLE
DESCRIP
VMT
VMT.CAP
LM
LM_CAP
VMT.LM
LMCAPURB
POP
POPDEN
PCI 98
JOBS
GAS PR98
VMT
Coefficient
Sid Error
N
1
0
2420
-0 08692
0 0001
2420
0 82329
0 0001
2420
-0 39539
0 0001
2420
0 8045
0 000!
2420
0 19113
0 0001
2420
0 96957
0 0001
2420
0 4787
0 0001
2420
0 62362
0 0001
2420
0 72788
00001
2420
0 0451
0 0265
2420
VMT.CAP
Coefficient
Std Error
N
-0 08692
0 0001
2420
1
0
2420
-0 06522
0 0013
2420
0 50663
0 0001
2420
-0 00042
0 9835
2420
-0 16712
0 0001
2420
-0 2157
0 0001
2420
-0 12968
0 0001
2420
0 05275
0 0095
2420
-0 13545
0 0001
2420
-0 0561
0 0058
2420
LM
Coefficient
Std Error
N
0 82329
0 0001
2420
-0 06522
0 0013
2420
1
0
2420
-0 3359
00001
2420
0 50023
0 0001
2420
0 29908
0 0001
2420
0 77997
0 0001
2420
0 34915
0 0001
2420
0 4396
0 0001
2420
0 66948
0 0001
2420
0 06598
0 0012
2420
LM_CAP
Coefficient
Std Error
N
-0 39539
0 0001
2420
0 50663
0 0001
2420
-0 3359
0 0001
2420
1
0
2420
-051941
0 0001
2420
-0 43812
0 0001
2420
-0 42876
00001
2420
-0 24353
0 0001
2420
-0 32282
0 0001
2420
-0 29362
0 0001
2420
001 111
0 5848
2420
VMT_LM
Coefficient
Std Error
N
0 8045
0 0001
2420
-0 00042
0 9835
2420
0 50023
0 0001
2420
-0 51941
0 0001
2420
1
0
2420
0 25851
0 0001
2420
0 78358
00001
2420
0 49497
0 0001
2420
0 70688
0 0001
2420
0 51314
0 0001
2420
-0 02173
0 2852
2420
LMCAPlfRB
Coefficient
Std Error
N
0 19113
0 0001
2420
-0 16712
0 0001
2420
0 29908
0 0001
2420
-0 43812
0 0001
2420
0 25851
0 0001
2420
1
0
2420
0 1676
0 0001
2420
0 05496
0 0068
2420
0 24089
0 0001
2420
0 17151
0 0001
2420
0 00712
0 7263
2420
POP
Coefficient
Std Error
N
0 96957
0 0001
2420
-0 2157
0 0001
2420
0 77997
0 0001
2420
-0 42876
00001
2420
0 78358
0 0001
2420
0 1676
0 0001
2420
1
0
2420
0 54264
00001
2420
060104
0 0001
2420
0 7633
0 0001
2420
0 06766
0 0009
2420
POPDEN
Coefficient
Std Error
N
0 4787
0 0001
2420
-0 12968
0 0001
2420
0 34915
0 0001
2420
-0 24353
0 0001
2420
0 49497
0 0001
2420
0 05496
0 0068
2420
0 54264
00001
2420
1
0
2420
0 49802
0 0001
2420
0 65324
0 0001
2420
0 11776
0 0001
2420
PCI_98
Coefficient
Std Error
N
0 62362
0 0001
2420
0 05275
0 0095
2420
0 4396
0 0001
2420
-0 32282
00001
2420
0 70688
00001
2420
0 24089
0 0001
2420
0 60104
0 0001
2420
049802
0 0001
2420
1
0
2420
0 51463
0 0001
2420
-0 01022
06153
2420
JOBS
Coefficient
Std Error
N
0 72788
0 0001
2420
-0 13545
0 0001
2420
0 66948
0 0001
2420
-0 29362
0 0001
2420
051314
0 0001
2420
0 17151
0 0001
2420
0 7633
00001
2420
0 65324
00001
2420
0 51463
0 0001
2420
1
0
2420
0 0795
0 0001
2420
GAS.PR98
Coefficient
Std Error
N
0 0451
00265
2420
-0 0561
0 0058
2420
0 06598
0 0012
2420
001111
0 5848
2420
-002173
0 2852
2420
000712
0 7263
2420
0 06766
0 0009
2420
011776
0 0001
2420
-0 01022
06153
2420
0 0795
0 0001
2420
1
0
2420
-------
ALL STATES LOG CORRELATION MATRIX
VARIABLE
DESCRIP
LOGVMT
LOGVCAP
LOGLM
LOGLMCAP
LOGVMTLM
LOGLMURB
LOGPOP
LOGPOPDN
LOGPCI98
LOGJOBS
LOGGAS98
LOGVMT
Coefficient
Std Error
N
1
0
2420
0 03744
0 0656
2420
0 86461
0 0001
2420
-0 70735
0 0001
2420
0 85887
00001
2420
-0 67331
0 0001
2420
0 92595
0 0001
2420
0 81501
0 0001
2420
0 59347
0 0001
2420
0 78446
0 0001
2420
0 00302
0 882
2420
LOGVCAP
Coefficient
Std Error
N
0 03744
0 0656
2420
1
0
2420
-0 00877
0 6662
2420
0 53135
0 0001
2420
0 07409
0 0003
2420
0 34676
0 0001
2420
-0 34272
0 0001
2420
-0 34428
0 0001
2420
010286
0 0001
2420
-0 23615
0 0001
2420
-0 06004
00031
2420
LOGLM
Coefficient
Std Error
N
0 86461
0 0001
2420
-0 00877
0 6662
2420
1
0
2420
-041741
0 0001
2420
0 48523
0 0001
2420
-0 47708
0 0001
2420
081613
0 000!
2420
0 57964
0 0001
2420
0 36472
0 0001
2420
0 71394
0 0001
2420
0 04508
0 0266
2420
LOGLMCAP
Coefficient
Std Error
N
-0 70735
0 0001
2420
0 53135
0 0001
2420
-041741
0 0001
2420
1
0
2420
-0 80546
0 0001
2420
0 78831
0 0001
2420
-0 86578
0 0001
2420
-0 9075
00001
2420
-0 50037
0 0001
2420
-0 68178
0 0001
2420
-0 0011
0 9567
2420
LOGVMTLM
Coefficient
Std Error
N
0 85887
0 0001
2420
0 07409
0 0003
2420
0 48523
0 0001
2420
-0 80546
0 0001
2420
1
0
2420
-0 6854
0 0001
2420
0 77941
0 0001
2420
0 82744
0 0001
2420
0 66099
0 0001
2420
0 63737
0 0001
2420
-0 0407
0 0453
2420
LOGLMURB
Coefficient
Std Error
N
-0 67331
0 0001
2420
0 34676
00001
2420
-0 47708
0 0001
2420
0 78831
0 0001
2420
-0 6854
0 0001
2420
1
0
2420
-0 76402
0 0001
2420
-0 80957
0 0001
2420
-0 49226
0 0001
2420
-0 68868
0 0001
2420
-0 01255
05371
2420
LOGPOP
Coefficient
Std Error
N
0 92595
00001
2420
-0 34272
0 0001
2420
081613
00001
2420
-0 86578
0 0001
2420
0 77941
0 0001
2420
-0 76402
0 0001
2420
1
0
2420
0 8963
00001
2420
051904
0 0001
2420
0 82672
0 0001
2420
0 02553
0 2093
2420
LOGPOPDN
Coefficient
Std Error
N
081501
0 0001
2420
-0 34428
0 0001
2420
0 57964
0 0001
2420
-0 9075
0 0001
2420
0 82744
0 0001
2420
-0 80957
0 0001
2420
0 8963
0 0001
2420
1
0
2420
0 64643
0 0001
2420
0 74785
0 0001
2420
0 05157
00112
2420
LOGPCI98
Coefficient
Std Error
N
0 59347
0000!
2420
010286
00001
2420
0 36472
0 0001
2420
-0 50037
0 0001
2420
0 66099
0 0001
2420
-0 49226
0 0001
2420
051904
0 0001
2420
0 64643
0 0001
2420
1
0
2420
0 49796
0 0001
2420
-0 02778
0 1719
2420
LOGJOBS
Coefficient
Std Error
N
0 78446
0 0001
2420
-0 23615
0 0001
2420
071394
00001
2420
-0 68178
0 0001
2420
0 63737
0 0001
2420
-0 68868
0 0001
2420
0 82672
0 0001
2420
0 74785
0 0001
2420
0 49796
0 0001
2420
1
0
2420
001814
0 3725
2420
LOGGAS98
Coefficient
Std Error
N
000302
0 882
2420
¦0 06004
00031
2420
0 04508
0 0266
2420
-0 0011
0 9567
2420
-0 0407
0 0453
2420
-0 01255
0 5371
2420
0 02553
0 2093
2420
005157
00112
2420
-0 02778
0 1719
2420
001814
0 3725
2420
1
0
2420
-------
MARYLAND LINEAR CORRELATION MATRIX
VARIABLE
DESCRIP
VMT
VMT_CAP
LM
LM.CAP
VMT LM
LMCAPURB
POP
POPDEN
PCI 98
JOBS
GAS PR98
VMT
Coefficient
Std Error
N
1
0
690
-0 21738
0 0001
644
0 91809
0 0001
690
-0 60944
0 0001
644
0 94929
00001
690
-0 12624
0 0013
644
0 9639
0 0001
644
0 9563
0 0001
644
06158
0 0001
644
0 96559
0 0001
644
-0 08912
0 0293
598
VMT_CAP
Coefficieni
Std Error
N
-0 21738
0 0001
644
1
0
644
-0 24656
0 0001
644
0 56086
0 0001
644
-0 15526
0 0001
644
-0 23675
0 0001
644
-0 35217
00001
644
-0 34519
00001
644
0 1759
0 0001
644
-0 29297
0 0001
644
-0 12519
0 0022
598
LM
Coefficient
Std Error
N
0 91809
00001
690
-0 24656
0 0001
644
1
0
690
-0 58724
0 0001
644
0 83425
0 0001
690
-0 01862
0 6373
644
092517
0 0001
644
0 89412
0 0001
644
0 48571
0 0001
644
0 88655
0 0001
644
-0 01754
0 6685
598
LM_CAP
Coefficient
Std Error
N
-0 60944
00001
644
0 56086
0 0001
644
-0 58724
0 0001
644
1
0
644
-0 70844
0 0001
644
-0 3865
00001
644
-0 63403
0 0001
644
-0 66935
0 0001
644
-0 44335
0 0001
644
-0 59559
0 0001
644
0 05412
0 1863
598
VMT_LM
Coefficient
Std Error
N
0 94929
0 0001
690
-0 15526
0 0001
644
0 83425
00001
690
-0 70844
0 0001
644
1
0
690
-0 05768
0 1437
644
0 896
0 0001
644
0 92885
0 0001
644
0 74436
0 0001
644
0 90848
0 0001
644
-0 13961
0 0006
598
LMCAPURB
Coefficient
Std Error
N
-0 12624
00013
644
-0 23675
0 0001
644
-0 01862
0 6373
644
-0 3865
0 0001
644
-0 05768
0 1437
644
1
0
644
-0 13938
0 0004
644
-0 11521
0 0034
644
001188
0 7635
644
-0 15382
0 0001
644
0 00223
0 9565
598
POP
Coefficient
Std Error
N
0 9639
0 0001
644
-0 35217
0 0001
644
0 92517
0 0001
644
-0 63403
0 0001
644
0 896
00001
644
-0 13938
00004
644
1
0
644
0 97996
0 0001
644
0 55086
00001
644
0 96948
0 0001
644
-0 03474
0 3964
598
POPDEN
WASHINGTON1
Coefficient
Std Error
N
0 9563
00001
644
-0 34519
00001
644
089412
0 0001
644
-0 66935
0 0001
644
0 92885
0 0001
644
-0 11521
0 0034
644
0 97996
0 0001
644
1
0
644
0601 18
0 0001
644
0 95309
0 0001
644
-0 04277
0 2964
598
PCI_98
Coefficient
Std Error
N
06158
0 0001
644
0 1759
0 0001
644
0 48571
0 0001
644
-0 44335
00001
644
0 74436
0 0001
644
001188
0 7635
644
0 55086
0 0001
644
0 60118
0 0001
644
1
0
644
0 63565
0 000!
644
-0 26147
0 0001
598
JOBS
Coefficient
Std Error
N
0 96559
0 0001
644
-0 29297
0 0001
644
0 88655
0 0001
644
-0 59559
0 0001
644
0 90848
0 0001
644
-0 15382
0 0001
644
0 96948
0 0001
644
0 95309
0 0001
644
0 63565
0 0001
644
1
0
644
-0 06298
0 1239
598
GAS_PR98
Coefficient
Std Error
N
-0 08912
0 0293
598
-0 12519
0 0022
598
-001754
0 6685
598
0 05412
0 1863
598
-0 13961
0 0006
598
0 00223
0 9565
598
-0 03474
0 3964
598
-0 04277
0 2964
598
-0 26147
00001
598
-0 06298
0 1239
598
1
0
598
-------
MARYLAND LOG CORRELATION MATRIX
VARIABLE
DESCRIP
LOGVMT
LOGVCAP
LOGLM
LOGLMCAP
LOGVMTLM
LOGLMURB
LOGPOP
LOGPOPDN
LOGPC198
LOGJOBS
LOGGAS98
LOGVMT
Coefficient
Std Error
N
1
0
690
-0 18107
0 0001
644
091413
0 0001
690
-0 88674
0 0001
644
0 95363
0 0001
690
-0 73392
0 0001
644
095819
0 0001
644
0 92606
0 0001
644
0 67929
0 0001
644
0 96486
0 0001
644
-0 094
0 0215
598
LOGVCAP
Coefficient
Std Error
N
-0 18107
0 0001
644
]
0
644
-0 24475
0 0001
644
054396
0 0001
644
-0 11307
0 0041
644
0 52899
0 0001
644
-0 45489
0 0001
644
-0 44225
00001
644
0 17114
0 0001
644
-0 37085
0 0001
644
-0 14071
0 0006
598
LOGLM
Coefficient
Std Error
N
0914)3
0 0001
690
-0 24475
00001
644
1
0
690
-0 74972
0 0001
644
O 74971
0 0001
690
-0 64547
0 0001
644
0 90317
0 0001
644
081807
0 0001
644
0 48292
0 0001
644
0 89734
0 0001
644
-0 01397
0 7332
598
LOGLMCAP
Coefficient
Std Error
N
-0 88674
0 0001
644
0 54396
0 0001
644
-0 74972
0 0001
644
1
0
644
-0 89524
0 0001
644
0 84696
0 0001
644
-0 96121
0 0001
644
-0 96537
0 0001
644
-0 561 15
0 0001
644
-0 93657
0 0001
644
0 05928
0 1477
598
LOGVMTLM
Coefficient
Std Error
N
0 95363
0 0001
690
-0 11307
0 0041
644
0 74971
0 0001
690
-0 89524
0 0001
644
1
0
690
-0 72197
0 0001
644
0 8966
0 0001
644
0 90824
0 0001
644
0 75533
oooot
644
0 91205
0 0001
644
-0 14563
0 0004
598
LOGLM URB
Coefficient
Std Error
N
-0 73392
0 0001
644
0 52899
0 0001
644
-0 64547
0 0001
644
084696
0 0001
644
-0 72197
0 0001
644
1
0
644
-0 81847
0 0001
644
-O 84887
0 0001
644
-0 46414
0 0001
644
-0 77243
0 0001
644
0 03351
04134
598
LOG POP
Coefficient
Std Error
N
0 95819
0 0001
644
-0 45489
00001
644
0 90317
0 0001
644
-0 96121
0 0001
644
0 8966
0 0001
644
-0 81847
0 0001
644
1
0
644
0 96723
00001
644
0 56531
0 0001
644
0 98159
0 0001
644
-0 04427
0 2798
598
LOGPOPDN
Coefficient
Std Error
N
0 92606
0 0001
644
-0 44225
0 0001
644
0 81807
0 0001
644
-0 96537
0 0001
644
0 90824
0 0001
644
-0 84887
0 0001
644
0 96723
0 0001
644
1
0
644
0 62805
0 0001
644
0 94619
0 0001
644
-0 04774
0 2438
598
LOG PC 198
Coefficient
Std Error
N
0 67929
0 0001
644
0 17114
0 0001
644
0 48292
0 0001
644
-0 56115
0 0001
644
0 75533
0 0001
644
-0 46414
0 0001
644
0 56531
0 0001
644
0 62805
0 0001
644
1
0
644
0 62798
0 0001
644
-0 27684
0 0001
598
LOGJOBS
Coefficient
Std Error
N
0 96486
0 0001
644
-0 37085
0 0001
644
0 89734
0 0001
644
-0 93657
0 0001
644
0 91205
00001
644
-0 77243
0 0001
644
0 98159
0 0001
644
094619
0 0001
644
0 62798
0 0001
644
1
0
644
-0 08399
004
598
LOGGAS98
Coefficient
Std Error
N
-0 094
00215
598
-0 14071
0 0006
598
-0 01397
0 7332
598
0 05928
0 1477
598
-0 14563
00004
598
0 03351
04134
598
-0 04427
0 2798
598
-0 04774
0 2438
598
-0 27684
0 0001
598
-0 08399
004
598
1
0
598
-------
NORTH CAROLINA LINEAR CORRELATION MATRIX
VARIABLE
DESCR1P
VMT
VMT_CAP
LM
LM_CAP
VMT_LM
LMCAPURB
POP
POPDEN
PCI 98
JOBS
GAS PR98
VMT
Coefficient
Std Error
N
1
0
1300
-0 04205
0 1297
1300
0 82042
0 0001
1300
-0 49122
0 0001
1300
0 85676
0 0001
1300
0 30401
0 0001
1300
0 95087
0 0001
1300
0 84075
00001
1300
0 66684
0 0001
1200
0 93827
0 0001
1200
-0 0668
0 0267
1 100
VMT_CAP
Coefficient
Std Error
N
-0 04205
0 1297
1300
1
0
1300
0 04346
0 1173
1300
0 47094
0 0001
1300
-0 0385
0 1654
1300
-0 13099
0 0001
1300
-0 25199
0 0001
1300
-0 29147
0 0001
1300
0069
00168
1200
-0 22555
0 0001
1200
-0 12966
0 0001
1100
LM
Coefficient
Std Error
N
0 82042
0 0001
1300
0 04346
0 1173
1300
1
0
1300
-0 35139
0 0001
1300
0 56253
0 0001
1300
0 36466
0 0001
1300
0 74809
00001
1300
0 55785
0 0001
1300
0 43639
0 0001
1200
068519
0 0001
1200
-0 02231
0 4597
1100
LM_CAP
Coefficient
Std Error
N
-0 49122
0 0001
1300
0 47094
0 0001
1300
-0 35139
0 0001
1300
1
0
1300
-0 68488
0 0001
1300
-049925
oooot
1300
-0 53478
00001
1300
-0 5833
0 0001
1300
-0 44481
0 0001
1200
-0 4736
0 0001
1200
0 00821
0 7857
1 100
VMT_LM
Coefficient
Sid Error
N
0 85676
0 0001
1300
-0 0385
0 1654
1300
0 56253
0 0001
1300
-0 68488
0 0001
1300
1
0
1300
0 39326
0 000!
1300
0 80864
0 0001
1300
0 85584
0 0001
1300
0 75909
0 0001
1200
0 79056
0 0001
1200
-0 10622
00004
1100
LMCAPURB
Coefficient
Std Error
N
0 30401
0 0001
1300
-0 i 3099
0 0001
1300
0 36466
0 0001
1300
-0 49925
00001
1300
0 39326
0 0001
1300
!
0
1300
025137
0 0001
1300
0 26798
0 0001
1300
0 27606
0 0001
1200
019083
0 0001
1200
-0014
0 6429
1100
POP
Coefficient
Std Error
N
0 95087
0 0001
1300
-0 25199
0 0001
1300
0 74809
0 0001
1300
-0 53478
0 0001
1300
0 80864
0 0001
1300
025137
0 0001
1300
1
0
1300
0 89703
0 0001
1300
0 61922
0 0001
1200
0 98302
0 0001
1200
-0 02081
0 4906
1100
POPDEN
WASHINGTOh
Coefficient
Std Error
N
0 84075
0 0001
1300
-0 29147
0 0001
1300
0 55785
0 0001
1300
-0 5833
0 0001
1300
0 85584
0 0001
1300
0 26798
0 0001
1300
0 89703
0 0001
1300
1
0
1300
0 65562
0 0001
1200
0 89511
0 0001
1200
-0 02155
0 4752
1100
PCI_98
Coefficient
Std Error
N
0 66684
00001
1200
0 069
00168
1200
0 43639
00001
1200
-0 44481
0 0001
1200
0 75909
0 0001
1200
0 27606
0 0001
1200
061922
0 0001
1200
0 65562
0 0001
1200
1
0
1200
0 63481
0 0001
1200
-0 21025
0 0001
1100
JOBS
Coefficient
Std Error
N
0 93827
0 0001
1200
-0 22555
0 0001
1200
0 68519
0 0001
1200
-0 4736
0 0001
1200
0 79056
0 0001
1200
0 19083
0 0001
1200
0 98302
0 0001
1200
0 8951 1
0 0001
1200
0 63481
0 0001
1200
1
0
1200
-0 02772
0 3583
1100
GAS_PR98
Coefficient
Std Error
N
-00668
0 0267
1100
-0 12966
0 0001
1100
-0 02231
0 4597
1100
000821
0 7857
1100
-0 10622
0 0004
1100
-0014
0 6429
1100
-0 02081
0 4906
1100
-0 02155
0 4752
1100
-0 21025
00001
1100
-0 02772
0 3583
1100
1
0
1100
-------
NORTH CAROLINA LOG CORRELATION MATRIX
VARIABLE
DESCRIP
LOGVMT
LOGVCAP
LOGLM
LOGLMCAP
LOGVMTLM
LOGLMURB
LOGPOP
LOGPOPDN
LOGPCI98
LOGJOBS
LOGGAS98
LOGVMT
Coefficient
Std Error
N
1
0
1300
006178
0 0259
1300
0 88381
0 0001
1300
-0 69707
0 0001
1300
0 86048
0 0001
1300
-0 66181
0 0001
1300
0 94153
0 0001
1300
0 81843
0 0001
1300
0 62724
0 0001
1200
0 9238
0 0001
1200
-0 07057
00192
1100
LOGVCAP
Coefficient
Std Error
N
0 06178
0 0259
1300
1
0
1300
0 08775
0 0015
1300
0 52847
0 0001
1300
0 01706
0 5389
1300
0 35573
0 0001
1300
-0 27813
0 0001
1300
-0 36771
0 0001
1300
0 08913
0 002
1200
-0 27607
0 0001
1200
-0 14462
0 0001
1100
LOGLM
Coefficient
Std Error
N
0 88381
0 0001
1300
0 08775
00015
1300
1
0
1300
-0 3957
0 0001
1300
0 52215
0 0001
1300
-0 44104
0 0001
1300
0 82094
0 0001
1300
057315
0 0001
1300
0 40627
0 0001
1200
0 79421
0 0001
1200
-0 0198
0 5119
1100
LOGLMCAP
Coefficient
Std Error
N
-0 69707
0 0001
1300
0 52847
0 0001
1300
-0 3957
0 0001
1300
1
0
1300
-0 83981
0 0001
1300
0 80971
0 0001
1300
-0 84925
00001
1300
-0 93649
0 0001
1300
-0 54518
0 0001
1200
-0 84227
0 0001
1200
0 01279
06718
1 100
LOGVMTLM
Coefficient
Std Error
N
0 86048
0 0001
1300
0 01706
0 5389
1300
0 52215
0 0001
1300
-0 83981
0 0001
1300
1
0
1300
-0 72615
0 0001
1300
0 82235
0 0001
1300
0 86782
0 0001
1300
0 70093
0 0001
1200
0 81804
0 0001
1200
-0 1074
0 0004
1 100
LOGLMURB
Coefficient
Std Error
N
-0 66181
0 0001
1300
0 35573
0 0001
1300
-0 44104
0 0001
1300
0 80971
0 0001
1300
-0 72615
0 0001
1300
1
0
1300
-0 757
0 0001
1300
-0 82488
0 0001
1300
-0 49484
0 0001
1200
-0 76544
0 0001
1200
0 01676
0 5787
1 100
LOGPOP
Coefficient
Std Error
N
0 94153
0 0001
1300
-0 27813
0 0001
1300
0 82094
0 0001
1300
-0 84925
0 0001
1300
0 82235
0 0001
1300
-0 757
0 0001
1300
1
0
1300
091178
0 0001
1300
0 57293
0 0001
1200
098108
0 0001
1200
-0 01938
0 5208
1100
LOGPOPDN
Coefficient
Std Error
N
0 81843
00001
1300
-0 36771
0 0001
1300
057315
00001
1300
-0 93649
0 0001
1300
0 86782
0 0001
1300
-0 82488
0 0001
1300
091178
00001
1300
1
0
1300
0 63334
00001
1200
0 90817
0 0001
1200
-0 02172
0 4717
1 100
LOGPCI98
Coefficient
Std Error
N
0 62724
0 0001
1200
008913
0 002
1200
0 40627
00001
1200
-0 54518
0 0001
1200
0 70093
0 0001
1200
-0 49484
0 0001
1200
0 57293
0 0001
1200
0 63334
0 0001
1200
1
0
1200
0 60828
0 0001
1200
-0 22481
0 0001
1100
LOG JOBS
Coefficient
Std Error
N
0 9238
0 0001
1200
-0 27607
00001
1200
0 79421
00001
1200
-0 84227
0 0001
1200
0 81804
00001
1200
-0 76544
0 0001
1200
0 98108
0 0001
1200
0 90817
0 0001
1200
0 60828
0 0001
1200
1
0
1200
-0 03237
0 2835
1100
LOGGAS98
Coefficient
Std Error
N
-0 07057
00192
1100
-0 14462
0 0001
1100
-0 0198
05119
1100
0 01279
06718
1100
-0 1074
00004
1100
0 01676
0 5787
1100
-001938
0 5208
1100
-0 02172
0 4717
1100
-0 22481
00001
1100
-0 03237
0 2835
1 100
1
0
1100
-------
VIRGINIA LINEAR CORRELATION MATRIX
VARIABLE
DESCRIP
VMT
VMT_CAP
LM
LM_CAP
VMT LM
POP
POPDEN
LMCAPURB
PCI 98
JOBS
GAS PR98
VMT
Coefficient
Std Error
N
1
0
2592
0 03891
0 0476
2592
0 55366
0 0001
2592
-0 32195
0 0001
2592
0 90035
0 0001
2592
0 9521
0 0001
2592
0 39245
0 0001
2592
018831
0 0001
2592
0 58725
0 0001
2592
023317
0 0001
2592
-0 10553
0 0001
2496
VMT_CAP
Coefficient
Std Error
N
0 03891
0 0476
2592
1
0
2592
015689
0 0001
2592
0 42236
0 0001
2592
0 08566
0 0001
2592
-0 15553
0 0001
2592
-0 12567
0 0001
2592
-0 08391
0 0001
2592
015583
0 0001
2592
0 00408
0 8356
2592
-0 19394
0 0001
2496
LM
Coefficient
Std Error
N
0 55366
0 0001
2592
0 15689
0 0001
2592
1
0
2592
-0 14584
0 0001
2592
0 34566
0 0001
2592
0 45065
0 0001
2592
0 08653
0 0001
2592
0 13202
0 0001
2592
0 27278
0 0001
2592
0 29103
0 0001
2592
-0 02114
0 291
2496
LM_CAP
Coefficient
Std Error
N
-0 32195
0 000!
2592
0 42236
00001
2592
-0 14584
00001
2592
1
0
2592
-0 44551
0 0001
2592
-0 34932
0 0001
2592
-0 23626
0 0001
2592
-0 3398
0 0001
2592
-0 28684
0 0001
2592
-0 09538
0 0001
2592
001886
0 3463
2496
VMT_LM
Coefficient
Std Error
N
0 90035
0 0001
2592
0 08566
00001
2592
0 34566
0 0001
2592
-0 44551
0 0001
2592
1
0
2592
0 85788
0 0001
2592
0 54955
0 0001
2592
0 27931
0 0001
2592
0 6808
0 0001
2592
0 26182
0 0001
2592
-0 14992
0 0001
2496
POP
Coefficient
Std Error
N
0 9521
00001
2592
-0 15553
0 0001
2592
0 45065
00001
2592
-0 34932
00001
2592
0 85788
0 0001
2592
1
0
2688
0 45255
0 0001
2688
O15074
0 0001
2592
051921
0 0001
2592
0 18822
0 0001
2592
-0 02796
0 1626
2496
POPDEN
Coefficient
Std Error
N
0 39245
0 0001
2592
-0 12567
0 0001
2592
0 08653
0 0001
2592
-0 23626
0 0001
2592
0 54955
00001
2592
0 45255
0 0001
2688
1
0
2688
0 08905
0 0001
2592
0 51299
0 0001
2592
0 33269
0 0001
2592
-001312
05125
2496
LMCAPURB
WASHINGTOI1
Coefficient
Std Error
N
018831
0 0001
2592
-0 08391
0 0001
2592
0 13202
00001
2592
-0 3398
0 0001
2592
0 27931
0 0001
2592
015074
00001
2592
0 08905
0 000!
2592
1
0
2592
0 27647
0 0001
2592
0 25523
0 0001
2592
-0 02035
0 3094
2496
PCI_98
Coefficient
Std Error
N
0 58725
0 000!
2592
0 15583
0 0001
2592
0 27278
0 0001
2592
-0 28684
0 0001
2592
0 6808
0 0001
2592
051921
00001
2592
0 51299
0 0001
2592
0 27647
0 0001
2592
1
0
2592
0 29194
0 0001
2592
-0 24474
0 0001
2496
JOBS
Coefficient
Std Error
N
023317
0 0001
2592
0 00408
0 8356
2592
0 29103
0 0001
2592
-0 09538
0 0001
2592
026182
0 0001
2592
0 18822
0 0001
2592
033269
0 0001
2592
0 25523
0 0001
2592
0 29194
0 0001
2592
1
0
2592
-0 05017
00122
2496
GAS_PR98
Coefficient
Std Error
N
-0 10553
0 0001
2496
-0 19394
0 0001
2496
-0 02114
0 291
2496
0 01886
0 3463
2496
-0 14992
00001
2496
-0 02796
0 1626
2496
-001312
05125
2496
-0 02035
0 3094
2496
-0 24474
0 0001
2496
-0 05017
0 0122
2496
1
0
2496
-------
VIRGINIA LOG CORRELATION MATRIX
VARIABLE
DESCRIP
LOGVMT
LOGVCAP
LOGLM
LOGLMCAP
LOGVMTLM
LOGPOP
LOGPOPDN
LOGLMURB
LOG PC/98
LOGJOBS
LOGGAS98
LOGVMT
Coefficient
Std Error
N
1
0
2592
0 26044
00001
2592
0 77408
0 0001
2592
-0 62378
0 0001
2592
0 86651
0 0001
2592
0 87958
00001
2592
0 70391
0 0001
2592
-0 56678
0 0001
2592
0 56353
0 0001
2592
0 55452
0 0001
2592
-0 14549
0 0001
2496
LOGVCAP
Coefficient
Std Error
N
0 26044
0 0001
2592
1
0
2592
019073
0 0001
2592
0 44844
0 0001
2592
0 23425
0 0001
2592
-0 23025
0 0001
2592
-0 26103
0 0001
2592
019071
0 0001
2592
0 22463
0 0001
2592
-0 03382
0 0852
2592
-0 22887
0 0001
2496
LOGLM
Coefficient
Std Error
N
0 77408
0 0001
2592
0 19073
0 0001
2592
1
0
2592
-0 19954
00001
2592
0 35474
0 0001
2592
0 68623
0 0001
2592
0 32041
00001
2592
-0 25436
0 0001
2592
0 22439
0 0001
2592
0 48373
0 0001
2592
-0 01904
0 3417
2496
LOGLMCAP
Coefficient
Std Error
N
-0 62378
0 0001
2592
0 44844
00001
2592
-0 19954
0 0001
2592
1
0
2592
-0 7639
0 0001
2592
-0 84969
0 0001
2592
-0 89678
0 0001
2592
071178
0 0001
2592
-0 45339
0 0001
2592
-0 42472
0 0001
2592
0 03 183
0 11 19
2496
LOGVMTLM
Coefficient
Std Error
N
0 86651
0 0001
2592
0 23425
00001
2592
0 35474
0 0001
2592
-0 7639
00001
2592
1
0
2592
0 75794
0 0001
2592
0 78693
0 0001
2592
-0 63649
0 0001
2592
0 65533
0 0001
2592
0 43753
0 0001
2592
-0 20026
0 0001
2496
LOGPOP
Coefficient
Std Error
N
0 87958
0 0001
2592
-0 23025
0 0001
2592
0 68623
0 0001
2592
-0 84969
0 0001
2592
0 75794
0 0001
2592
1
0
2688
0 839
0 0001
2688
-0 66524
00001
2592
0 45731
0 0001
2592
0 57557
0 0001
2592
-0 0339
0 0904
2496
LOGPOPDN
Coefficient
Std Error
N
0 70391
0 0001
2592
-0 26103
0 0001
2592
0 32041
0 0001
2592
-0 89678
0 0001
2592
0 78693
0 0001
2592
0 839
0 0001
2688
1
0
2688
-0 77879
0 0001
2592
0 58345
0 0001
2592
0 47825
0 0001
2592
-0 03202
0 1097
2496
LOGLMURB
Coefficient
Std Error
N
-0 56678
0 0001
2592
0 19071
0 0001
2592
-0 25436
0 0001
2592
071178
0 0001
2592
-0 63649
0 0001
2592
-0 66524
0 0001
2592
-0 77879
0 0001
2592
1
0
2592
-0 48651
0 0001
2592
-0 47159
0 0001
2592
0 03459
0 0841
2496
LOGPCI98
Coefficient
Std Error
N
0 56353
00001
2592
0 22463
00001
2592
0 22439
0 0001
2592
-0 45339
0 0001
2592
0 65533
0 0001
2592
0 45731
0 0001
2592
0 58345
0 0001
2592
-0 48651
0 0001
2592
1
0
2592
0 35982
0 0001
2592
-0 26565
0 0001
2496
LOGJOBS
Coefficient
Std Error
N
0 55452
0 0001
2592
-0 03382
0 0852
2592
0 48373
oooot
2592
-0 42472
0 0001
2592
0 43753
0 0001
2592
0 57557
0 0001
2592
0 47825
0 0001
2592
-0 47159
0 0001
2592
0 35982
0 0001
2592
1
0
2592
-0 0526
0 0086
2496
LOGGAS98
Coefficient
Std Error
N
-0 14549
0 0001
2496
-0 22887
0 0001
2496
-0 01904
0 3417
2496
003183
0 1119
2496
-0 20026
0 0001
2496
-0 0339
0 0904
2496
-0 03202
0 1097
2496
0 03459
0 0841
2496
-0 26565
0 0001
2496
-0 0526
0 0086
2496
1
0
2496
-------
WASHINGTON DC - BALTIMORE EXPANDED AREA LINEAR CORRELATION MATRIX
VARIABLE
DESCRIP
VMT
VMT_CAP
LM
LM_CAP
VMT_LM
LMCAPURB
POP
POPDEN
PCI 98
JOBS
GAS PR98
VMT
Coefficient
Std Error
N
1
0
432
-0 14647
0 0023
432
0 7998
0 0001
432
-0 60754
0 0001
432
0 68558
0 0001
432
-041412
0 0001
432
0 95753
00001
432
0 19561
00001
432
0 46782
0 0001
432
079152
0 0001
432
-0 13743
0 005
416
VMT.CAP
Coefficient
Std Error
N
-0 14647
0 0023
432
1
0
432
-0 11223
0 0196
432
0 45937
0 0001
432
-0 15497
00012
432
015601
0 0011
432
-0 33722
0 0001
432
-0 33695
0 0001
432
-0 01039
0 8295
432
-0 23648
0 0001
432
-0 21804
0 0001
416
LM
Coefficient
Std Error
N
0 7998
0 0001
432
-0 11223
0 0196
432
1
0
432
-03123
0 0001
432
0 17633
0 0002
432
-0 10297
0 0324
432
0 76424
0 0001
432
-0 05002
0 2996
432
012226
0011
432
0 78872
0 0001
432
-0 00424
09313
416
LM_CAP
Coefficient
Std Error
N
-0 60754
0 0001
432
0 45937
0 0001
432
-0 3123
0 0001
432
1
0
432
-0 73244
0 0001
432
0 6124
0 0001
432
-0 67736
0 0001
432
-051616
0 0001
432
-0 52932
0 0001
432
-0 56222
0 0001
432
0 08767
0 0741
416
VMT_LM
Coefficient
Std Error
N
0 68558
0 0001
432
-0 15497
0 0012
432
0 17633
0 0002
432
-0 73244
0 0001
432
1
0
432
-0 55057
00001
432
069815
0 0001
432
0 49507
0 0001
432
0 64961
0 0001
432
0 3551
0 0001
432
-0 20835
0 0001
416
LMCAPURB
Coefficient
Std Error
N
-0 41412
0 0001
432
0 15601
0 0011
432
-0 10297
0 0324
432
0 6124
0 0001
432
-0 55057
0 0001
432
1
0
432
-0 46833
0 0001
432
-0 3778
0 0001
432
-0 46366
0 0001
432
-0 38071
0 0001
432
0 11576
00182
416
POP
Coefficient
Std Error
N
0 95753
0 0001
432
-0 33722
0 0001
432
0 76424
0 0001
432
-0 67736
0 0001
432
069815
0 0001
432
-0 46833
0 0001
432
1
0
432
0 24757
0 0001
432
043146
0 0001
432
0 77097
0 0001
432
-0 05667
0 2488
416
POPDEN
Coefficient
Std Error
N
0 19561
0 0001
432
-0 33695
0 0001
432
-0 05002
0 2996
432
-051616
0 0001
432
0 49507
0 0001
432
-0 3778
0 0001
432
0 24757
0 0001
432
1
0
432
0 5747
0 0001
432
0 35694
0 0001
432
-0 05136
0 296
416
PCI_98
Coefficient
Std Error
N
0 46782
00001
432
-0 01039
0 8295
432
012226
0011
432
-0 52932
0 0001
432
0 64961
0 0001
432
-0 46366
0 0001
432
0 43146
0 0001
432
0 5747
0 0001
432
1
0
432
0 45311
0 0001
432
-0 28934
0 0001
416
JOBS
Coefficient
Std Error
N
079152
0 0001
432
-0 2 3648
0 000!
432
0 78872
0 0001
432
-0 56222
0 0001
432
0 3551
0 0001
432
-0 38071
0 0001
432
0 77097
00001
432
0 35694
0 0001
432
045311
0 0001
432
1
0
432
-0 06843
0 1636
416
GAS_PR98
Coefficient
Std Error
N
-0 13743
0 005
416
-0 21804
0 0001
416
-0 00424
09313
416
0 08767
0 0741
416
-0 20835
0 0001
416
011576
00182
416
-0 05667
0 2488
416
-0 05136
0 296
416
-0 28934
0 0001
416
-0 06843
0 1636
416
1
0
416
-------
WASHINGTON DC - BALTIMORE EXPANDED AREA LOG CORRELATION MATRIX
VARIABLE
DESCRIP
LOGVMT
LOGVCAP
LOGLM
LOGLMCAP
LOGVMTLM
LOGLMURB
LOGPOP
LOGPOPDN
LOGPCI98
LOGJOBS
LOGGAS98
LOGVMT
Coefficient
Std Error
N
1
0
432
-0 09649
0 045
432
0 7674
0 0001
432
-0 71429
00001
432
0 78461
0 0001
432
-0 56761
00001
432
0 95235
0 0001
432
0 69985
0 0001
432
051532
0 0001
432
0 815
0 0001
432
-0 14989
0 0022
416
LOGVCAP
Coefricient
Std Error
N
-0 09649
0 045
432
1
O
432
-0 04554
0 3451
432
0 52294
00001
432
-0 10328
00319
432
0 46992
00001
432
-0 39547
0 0001
432
-0 47049
0 0001
432
000765
0 8741
432
-0 26984
0 0001
432
-0 23704
0 0001
416
LOGLM
Coefficient
Std Error
N
0 7674
00001
432
-0 04554
0 3451
432
1
0
432
-0 1951
0 0001
432
0 20458
0 0001
432
-0 28444
0 0001
432
0 7221
0 0001
432
0 28384
0 0001
432
0 11688
00151
432
0 67326
0 0001
432
0 00272
0 9558
416
LOGLMCAP
Coefficient
Std Error
N
-0 71429
00001
432
0 52294
0 0001
432
-0 1951
0 0001
432
1
0
432
-0 90182
0 0001
432
0 71103
0 0001
432
-0 81938
0 0001
432
-0 88478
0 0001
432
-0 57401
0 0001
432
-0 62557
0 0001
432
0 09498
0 0529
416
LOGVMTLM
Coefficient
Std Error
N
0 78461
0 0001
432
-0 10328
00319
432
0 20458
0 0001
432
-0 90182
0 0001
432
1
0
432
-0 59149
0 0001
432
0 75567
0 0001
432
0 79396
00001
432
0 6737
0 0001
432
0 5932
0 0001
432
-0 23156
0 0001
416
LOGLMURB
Coefficient
Std Error
N
-0 56761
0 0001
432
0 46992
0 0001
432
-0 28444
0 0001
432
0 71103
0 0001
432
-0 59149
0 0001
432
1
0
432
-0 66778
0 0001
432
-0 73844
0 0001
432
-0 31984
0 0001
432
-0 5307
0 0001
432
0 00172
0 9721
416
LOGPOP
Coefficient
Std Error
N
0 95235
00001
432
-0 39547
0 0001
432
0 7221
0 0001
432
-0 81938
0 0001
432
0 75567
0 0001
432
-0 66778
0 0001
432
1
0
432
0 78998
0 0001
432
0 47319
0 0001
432
0 83476
0 0001
432
-0 06554
0 1822
416
LOGPOPDN
Coefficient
Std Error
N
0 69985
0 0001
432
-0 47049
00001
432
0 28384
0 0001
432
-0 88478
0 0001
432
0 79396
0 0001
432
-0 73844
0 0001
432
0 78998
0 0001
432
1
0
432
060191
0 0001
432
0 77707
0 0001
432
-0 06806
0 1659
416
LOGPCI98
Coefficient
Std Error
N
051532
0 0001
432
0 00765
0 8741
432
0 11688
00151
432
-0 57401
0 0001
432
0 6737
0 0001
432
-0 31984
0 0001
432
047319
0 0001
432
0 60191
0 0001
432
1
0
432
0 42252
0 0001
432
-0 30171
0 0001
416
LOGJOBS
Coefficient
Std Error
N
0815
00001
432
-0 26984
oooot
432
0 67326
0 0001
432
-0 62557
0 0001
432
0 5932
0 0001
432
-0 5307
0 0001
432
0 83476
0 0001
432
0 77707
0 0001
432
042252
0 0001
432
1
0
432
-0 06424
0 191
416
LOGGAS98
Coefficient
Std Error
N
-0 14989
0 0022
416
-0 23704
0 0001
416
0 00272
0 9558
416
0 09498
0 0529
416
-0 23156
0 0001
416
0 00172
0 9721
416
-0 06554
0 1822
416
-0 06806
0 1659
416
-0 30171
0 0001
416
-0 06424
0 191
416
1
0
416
-------
ALL STATES LINEAR FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
VMTDEFF
VCAPDIFF
LMDIFF
LCAPDIFF
POPDIFF
PCIDIFF
JOBDIFF
VMTDIFF
Coefficient
Std Error
N
1
0
2200
0 38789
0 0001
2200
0 3149
0 0001
2200
0 03576
0 0935
2200
0 57387
0 0001
2200
0 09017
0 0001
2200
0 33974
0 0001
2200
VCAPDIFF
Coefficient
Std Error
N
0 38789
0.0001
2200
1
0
2200
0 07936
0 0002
2200
0 14756
0 0001
2200
-0 05762
0 0069
2200
0 09656
0 0001
2200
-0 00728
07331
2200
LMDIFF
Coefficient
Std Error
N
0 3149
0 0001
2200
0 07936
0 0002
2200
1
0
2200
0 44658
0 0001
2200
023122
0 0001
2200
0 0325
0 1275
2200
0 125
0 0001
2200
LCAPDIFF
Coefficient
Std Error
N
0 03576
0 0935
2200
014756
0 0001
2200
0 44658
0 0001
2200
1
0
2200
-0 06799
0 0014
2200
010405
0 0001
2200
-0 00464
0 8277
2200
POPDIFF
Coefficient
Std Error
N
0 57387
0 0001
2200
-0 05762
0 0069
2200
0 23122
0 0001
2200
-0 06799
0 0014
2200
1
0
2200
0 05723
0 0073
2200
0 47917
0 0001
2200
PCIDIFF
Coefficient
Sid Error
N
0 09017
0 0001
2200
0 09656
0 0001
2200
0 0325
0 1275
2200
0 10405
0 0001
2200
0 05723
0 0073
2200
1
0
2200
0 23797
0 0001
2200
JOBDIFF
Coefficient
Std Error
N
0 33974
0 0001
2200
-0 00728
0 7331
2200
0 125
0 0001
2200
-0 00464
0 8277
2200
047917
0 0001
2200
0 23797
0 0001
2200
1
0
2200
-------
ALL STATES LOG FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
L_VMTDFF
L_VCPDFF
L.LMDIFF
L_LMCDFF
L POPDFF
L PCIDFF
L JOBDFF
L_VMTDFF
Coefficient
Std Error
N
1
0
2200
0 97252
0 0001
2200
0 14691
0 0001
2200
0 06234
0 0034
2200
0 09155
0 0001
2200
006131
0 004
2200
0 08969
0 0001
2200
L_VCPDFF
Coefficient
Std Error
N
0 97252
0 0001
2200
1
0
2200
0 13666
0 0001
2200
019919
0 0001
2200
-0 14282
0 0001
2200
0 09949
0 0001
2200
0 03271
0 1251
2200
L_LMDIFF
Coefficient
Std Error
N
0 14691
0 0001
2200
0 13666
0 0001
2200
1
0
2200
0 78549
0 0001
2200
0 04002
0 0606
2200
0 02918
0 1712
2200
0 03563
0 0948
2200
L_LMCDFF
Coefficient
Std Error
N
0 06234
0 0034
2200
0 19919
0 0001
2200
0 78549
0 0001
2200
I
0
2200
-0 58695
0 0001
2200
0 12576
0 0001
2200
-0 12065
0 0001
2200
L_POPDFF
Coefficient
Std Error
N
009155
0 0001
2200
-0 14282
0 0001
2200
0 04002
0 0606
2200
-0 58695
0 0001
2200
1
0
2200
-0 16487
0 0001
2200
024141
0 0001
2200
L_PCIDFF
Coefficient
Std Error
N
006131
0 004
2200
0 09949
0 0001
2200
0 02918
0 1712
2200
0 12576
0 0001
2200
-0 16487
0 0001
2200
1
0
2200
0 28437
0 0001
2200
L_JOBDFF
Coefficient
Std Error
N
0 08969
0 0001
2200
0 03271
0 1251
2200
0 03563
0 0948
2200
-0 12065
0 0001
2200
0 24141
0 0001
2200
0 28437
0 0001
2200
I
0
2200
-------
MARYLAND LINEAR FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
VMTDIFF
VCAPDIFF
LMDIFF
LCAPDIFF
POPDIFF
PCIDIFF
JOBDIFF
VMTDIFF
Coefficient
Std Error
N
1
0
644
041076
0 0001
621
0 34863
0 0001
644
0 12496
0 0018
621
0 45941
0 0001
621
0 2036
0 0001
621
0 50973
0 0001
621
VCAPDIFF
Coefficient
Std Error
N
0 41076
0 0001
621
1
0
621
0 13367
0 0008
621
0 14929
0 0002
621
-0 03188
0 4278
621
0 14488
0 0003
621
0 02809
0 4848
621
LMDIFF
Coefficient
Std Error
N
0 34863
0 0001
644
0 13367
0 0008
621
1
0
644
0 53595
0 0001
621
0 25857
0 0001
621
-0 01495
07101
621
0 15803
00001
621
LCAPDIFF
Coefficient
Std Error
N
012496
0 0018
621
0 14929
0 0002
621
0 53595
0 0001
621
1
0
621
0 01447
07189
621
-0 03601
0 3704
621
0 08858
0 0273
621
POPDIFF
Coefficient
Std Error
N
0 45941
0 0001
621
-0 03188
0 4278
621
0 25857
0 0001
621
0 01447
07189
621
1
0
621
010656
0 0079
621
0 56192
0 0001
621
PCIDIFF
Coefficient
Std Error
N
0 2036
0 0001
621
014488
0 0003
621
-001495
07101
621
-0 03601
0 3704
621
010656
0 0079
621
1
0
621
0 32593
0 0001
621
JOBDIFF
Coefficient
Std Error
N
0 50973
0 0001
621
0 02809
0 4848
621
015803
0 0001
621
0 08858
0 0273
621
0 56192
0 0001
621
0 32593
0 0001
621
1
0
621
-------
MARYLAND LOG FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
L VMTDFF
L_VCPDFF
L_LMDIFF
L_LMCDFF
L POPDFF
L PCIDFF
L.JOBDFF
L_VMTDFF
Coefficient
1
0 9722
019222
0 03934
015981
0 1722
0 18458
Std Error
0
0 0001
0 0001
0 3277
0 0001
0 0001
0 0001
N
644
621
644
621
621
621
621
L_VCPDFF
Coefficient
0 9722
1
0 16248
018343
-0 07579
017514
0 08841
Std Error
0 0001
0
0 0001
0 0001
0 0591
0 0001
0 0276
N
621
621
621
621
621
621
621
L_LMDIFF
Coefficient
0 19222
016248
1
071713
012014
-0 04817
0 07752
Std Error
0 0001
0 0001
0
0 0001
0 0027
0 2307
0 0535
N
644
621
644
621
621
621
621
L_LMCDFF
Coefficient
0 03934
0 18343
071713
1
-0 60573
-0 03504
-0 22801
Std Error
0 3277
0 0001
0 0001
0
0 0001
0 3833
0 0001
N
621
621
621
621
621
62!
621
L_POPDFF
Coefficient
0 15981
-0 07579
0 12014
-0 60573
1
-0 00507
041329
Std Error
0 0001
0 0591
0 0027
0 0001
0
0 8996
0 0001
N
621
621
621
621
621
621
621
L PCIDFF
Coefficient
0 1722
0 17514
-0 04817
-0 03504
-0 00507
1
0 47135
Std Error
0 0001
0 0001
0 2307
0 3833
0 8996
0
0 0001
N
621
621
621
621
621
621
621
LJOBDFF
Coefficient
018458
0 08841
0 07752
-0 22801
041329
047135
I
Std Error
0 0001
0 0276
0 0535
0 0001
0 0001
0 0001
0
N
621
621
621
621
621
621
62!
-------
NORTH CAROLINA LINEAR FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
VMTDIFF
VCAPDIFF
LMDIFF
LCAPDIFF
POPDIFF
PCIDIFF
JOBDIFF
VMTDIFF
Coefficient
Std Error
N
1
0
1200
048262
0 0001
1200
0 33826
0 000I
1200
0 03168
0 2728
1200
0 56975
0 0001
1200
0 03382
0 2625
1100
0 49054
0 0001
1100
VCAPDIFF
Coefficient
Std Error
N
0 48262
0 0001
1200
1
0
1200
0 16071
0 0001
1200
0 16877
0 0001
1200
-0 02249
0 4363
1200
0 03286
0 2762
1 100
-0 01695
0 5744
1 100
LMDIFF
Coefficient
Sid Error
N
0 33826
0 0001
1200
016071
0 0001
1200
1
0
1200
0 5237
0 0001
1200
0 23022
0 0001
1200
0 0341
0 2585
1100
0 17283
0 000!
1100
LCAPDIFF
Coefficient
Std Error
N
0 03168
0 2728
1200
0 16877
0 0001
1200
0 5237
0 0001
1200
1
0
1200
-0 06802
0 0184
1200
0 07177
00173
1100
-0 02242
0 4576
1100
POPDIFF
Coefficient
Std Error
N
0 56975
0 0001
1200
-0 02249
0 4363
1200
0 23022
0 0001
1200
-0 06802
00184
1200
1
0
1200
0 0066
0 827
1100
0 77536
0 0001
1100
PCIDIFF
Coefficient
Std Error
N
0 03382
0 2625
1100
0 03286
0 2762
1100
0 0341
0 2585
1100
007177
00173
1100
0 0066
0 827
1100
1
0
1100
0 22412
0 0001
1100
JOBDIFF
Coefficient
Std. Error
N
0 49054
0 0001
1100
-0 01695
0 5744
1100
0 17283
00001
1100
-0 02242
0 4576
1100
0 77536
0 0001
1100
0 22412
0 0001
1100
1
0
1100
-------
NORTH CAROLINA LOG FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
L_VMTDFF
L_VCPDFF
L_LMDIFF
L_LMCDFF
L POPDFF
L PCIDFF
L JOBDFF
L_VMTDFF
Coefficient
Std Error
N
1
0
1200
0 98673
0 0001
1200
021371
0 0001
1200
0 15035
0 0001
1200
0 10502
0 0003
1200
-0 00717
08123
1100
0 0783
0 0094
1 100
L.VCPDFF
Coefficient
Std Error
N
0 98673
0 000!
1200
1
0
1200
0 20375
0 0001
1200
021418
0 0001
1200
-0 05782
0 0452
1200
002477
04118
1100
0 03768
02118
1 100
L_LMDIFF
Coefficient
Std Error
N
0 21371
0 0001
1200
0 20375
0 0001
1200
1
0
1200
0 89429
0 0001
1200
0 06606
0 0221
1200
0 00634
0 8336
1100
0.02988
0 3221
1100
L_LMCDFF
Coefficient
Std Error
N
0 15035
0 0001
1200
021418
0 0001
1200
0 89429
0 0001
1200
1
0
1200
-0 38742
0 0001
1200
0 09309
0 002
1100
-0 08375
0 0054
1100
L_POPDFF
Coefficient
Std Error
N
0 10502
0 0003
1200
-0 05782
0 0452
1200
0 06606
0 0221
1200
-0 38742
0 0001
1200
1
0
1200
-0 19989
0 0001
1100
0 25564
0 0001
1 100
L_PCIDFF
Coefficient
Std Error
N
-0 00717
0 8123
1100
0 02477
04118
1100
0 00634
0 8336
1100
0 09309
0 002
1100
-0 19989
0 0001
1100
1
0
1100
0 32727
0 0001
1100
L.JOBDFF
Coefficient
Std Error
N
0 0783
0 0094
1100
0 03768
02118
1100
0 02988
0 3221
1100
-0 08375
0 0054
1100
0 25564
0 0001
1100
0 32727
0 0001
1100
1
0
1100
-------
VIRGINIA LINEAR FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
VMTDIFF
VCAPDIFF
LMDIFF
LCAPDIFF
POPDIFF
PCIDIFF
JOBDIFF
VMTDIFF
Coefficient
Std. Error
N
1
0
2496
0 36432
0 0001
2496
0 17613
0 0001
2496
-0 00962
0 6309
2496
0 62506
0 0001
2496
0 11954
0 0001
2496
0 12971
0 0001
2496
VCAPDIFF
Coefficient
Std. Error
N
0 36432
0 0001
2496
1
0
2496
0 02205
0 2708
2496
0 11746
0 0001
2496
-0 09857
0 0001
2496
021239
00001
2496
001547
0 4399
2496
LMDIFF
Coefficient
Std Error
N
0 17613
0 0001
2496
0 02205
0 2708
2496
1
0
2496
0 47251
0 0001
2496
0 15345
00001
2496
001582
0 4294
2496
0 02024
03121
2496
LCAPDIFF
Coefficient
Std Error
N
-0 00962
0 6309
2496
0 11746
0 0001
2496
0 47251
0 0001
2496
1
0
2496
-0 10848
0 0001
2496
0 07083
0 0004
2496
-0 03677
0 0663
2496
POPDIFF
Coefficient
Std Error
N
0 62506
00001
2496
-0.09857
0 0001
2496
0 15345
0 0001
2496
-0 10848
0 0001
2496
I
0
2592
003617
0 0708
2496
0 11388
0 0001
2496
PCIDIFF
Coefficient
Std Error
N
011954
oooot
2496
0 21239
0 0001
2496
001582
0 4294
2496
0 07083
0 0004
2496
0 03617
0 0708
2496
1
0
2496
0 13472
0 0001
2496
JOBDIFF
Coefficient
Std Error
N
0 12971
0 0001
2496
0 01547
0 4399
2496
0 02024
03121
2496
-0 03677
0 0663
2496
0 11388
0 0001
2496
0 13472
0 0001
2496
1
0
2496
-------
VIRGINIA LOG FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
L.VMTDFF
L_VCPDFF
L_LMDIFF
L_LMCDFF
L POPDFF
L PCIDFF
L JOBDFF
L_VMTDFF
Coefficient
Std Error
N
1
0
2496
091514
0 0001
2496
0 07767
0 0001
2496
-0 03247
0 1048
2496
012938
0 0001
2496
0 23081
0 0001
2496
0 1149
0 0001
2496
LJVCPDFF
Coefficient
Std Error
N
091514
0 0001
2496
1
0
2496
0 04393
0 0282
2496
0 23283
0 0001
2496
-0 28135
0 0001
2496
0 25566
0 0001
2496
0 0491 1
00141
2496
L_LMDIFF
Coefficient
Std Error
N
0 07767
0 0001
2496
0 04393
0 0282
2496
1
0
2496
0 70778
0 0001
2496
0 07682
0 0001
2496
0 02578
0 1979
2496
0 00931
0 6419
2496
L_LMCDFF
Coefficient
Std Error
N
-0 03247
0 1048
2496
0 23283
0 0001
2496
0 70778
0 0001
2496
1
0
2496
-0 64998
0 0001
2496
0 07594
00001
2496
-0 101 1
0 0001
2496
L_POPDFF
Coefficient
Std Error
N
0 12938
0 0001
2496
-0 28135
0 0001
2496
0 07682
0 0001
2496
-0 64998
0 0001
2496
1
0
2592
-0 07944
0 0001
2496
015271
0 0001
2496
L_PCIDFF
Coefficient
Std Error
N
0 23081
0 0001
2496
0 25566
0 0001
2496
0 02578
0 1979
2496
0 07594
0 0001
2496
-0 07944
0 0001
2496
1
0
2496
0 2646
0 0001
2496
LJOBDFF
Coefficient
Std Error
N
0 ! 149
0 0001
2496
0 04911
00141
2496
0 00931
0 6419
2496
-0 1011
0 0001
2496
0 15271
0 0001
2496
0 2646
0 0001
2496
1
0
2496
-------
WASHINGTON DC - BALTIMORE EXPANDED METROPOLITAN AREA
LINEAR FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
VMTDIFF
VCAPDIFF
LMDIFF
LCAPDIFF
POPDIFF
PCIDIFF
JOBDIFF
VMTDIFF
Coefficient
Std Error
N
1
0
416
0 50541
00001
416
0 29599
0 0001
416
018305
0 0002
416
0 44819
0 0001
416
0 22042
0 0001
416
0 35381
0 0001
416
VCAPDIFF
Coefficient
Std Error
N
0 50541
0 0001
416
1
0
416
0 11658
0 0174
416
0 07138
0 1462
416
-0 03943
0 4225
416
0 28769
0 0001
416
0 09095
0 0638
416
LMDIFF
Coefficient
Std Error
N
0 29599
0 0001
416
0 11658
00174
416
1
0
416
0 56977
0 0001
416
0 17572
0 0003
416
-001018
0 836
416
0 07875
0 1087
416
LCAPDIFF
Coefficient
Std Error
N
0 18305
0 0002
416
0 07138
0 1462
416
0 56977
0 0001
416
1
0
416
0 0861
0 0794
416
-0 0083
0 866
416
014021
0 0042
416
POPDIFF
Coefficient
Std Error
N
044819
0 0001
416
-0 03943
0 4225
416
017572
0 0003
416
0 0861
0 0794
416
1
0
416
0 09002
0 0666
416
0 24559
0 0001
416
PCIDIFF
Coefficient
Std Error
N
0 22042
0 0001
416
0 28769
0 0001
416
-001018
0 836
416
-0 0083
0 866
416
0 09002
0 0666
416
1
0
416
0 29592
0 0001
416
JOBDIFF
Coefficient
Std Error
N
0 35381
0 0001
416
0 09095
0 0638
416
0 07875
0 1087
416
0 14021
0 0042
416
0 24559
0 0001
416
0 29592
0 0001
416
1
0
416
-------
WASHINGTON DC - BALTIMORE EXPANDED METROPOLITAN AREA
LOG FIRST DIFFERENCES CORRELATION MATRIX
VARIABLE
DESCRIP
L.VMTDFF
L_VCPDFF
L_LMDIFF
L LMCDFF
L_ POPDFF
L PC1DFF
L.JOBDFF
LVMTDFF
Coefficient
1
0 92897
006175
-0 10456
0 24646
0 29974
0 24666
Std Error
0
0 0001
0 2088
0 033
0 0001
0 0001
0 0001
N
416
416
416
416
416
416
416
LVCPDFF
Coefficient
0 92897
1
0 04094
0 11494
-0 12977
0 3074
0 13518
Std Error
0 0001
0
0 405
0019
0 008
0 0001
0 0058
N
416
416
416
416
416
416
416
L_LMDIFF
Coefficient
006175
0 04094
1
0 77867
0 05822
-0 02857
-0 00205
Std Error
0 2088
0 405
0
0 0001
0 2361
0 5611
0 9667
N
416
416
416
416
416
416
416
L_LMCDFF
Coefficient
-0 10456
0 11494
0 77867
1
-0 58103
-0 02208
-0 19451
Std Error
0 033
0019
0 0001
0
0 0001
0 6534
0 0001
N
416
416
416
416
416
416
416
L POPDFF
Coefficient
0 24646
-0 12977
0 05822
-0 58103
1
-0 00193
0 30682
Std Error
0 0001
0 008
0 2361
0 0001
0
0 9687
0 0001
N
416
416
416
416
416
416
416
L_PCIDFF
Coefficient
0 29974
0 3074
-0 02857
-0 02208
-0 00193
1
0 39108
Std Error
0 0001
0.0001
0 5611
0 6534
0 9687
0
0 0001
N
416
416
416
416
416
416
416
L JOBDFF
Coefficient
0 24666
0 13518
-0 00205
-0 19451
0 30682
0 39108
1
Std Error
0 0001
0 0058
0 9667
00001
0 0001
00001
0
N
416
416
416
416
416
416
416
-------
APPENDIX C: DATA LISTING FOR DC AND
DESCRIPTION OF DC METRO AREA
This appendix provides a full listing of the data for the District of Columbia used in the analysis
It also provides a listing of the counties included in the DC/Baltimore extended metro area. The
tables in this appendix are as follows.
Table C-l. Listing of counties in DC / Baltimore extended area
Table C-2. DC database printout
-------
TABLE C-l
LISTING OF COUNTIES IN
DC-BALTIMORE EXTENDED AREA
ANALYSES
MARYLAND
VIRGINIA
Anne Arundel
Arlington
Baltimore
Fairfax
Calvert
Fauquier
Carroll
Loudon
Charles
Prince William
Frederick
Stafford
Harford
Howard
Montgomery
Prince George's
-------
TABLE C-2 WASHINGTON DC DATABASE PRINTOUT
TRAVEL DATA
YEAR
LM
LM UC*
LM_ADJ **
VMT
VMT UC *
VMT ADJ **
1995
3,376
2,306
1,070
9,493.151
2,098,630
7,394,521
1994
2,708
1,638
1,070
9,446,575
1,945,205
7,501,370
1993
2,435
1,365
1,070
9,547,945
1,972,603
7,575,342
1992
2,714
1,644
1,070
9,758,904
1,917,808
7,841,096
1991
2,703
1,651
1,052
9,397,260
1,857,534
7,539,726
1990
2,695
1,643
1,052
9,334,247
1,854,795
7,479,452
1989
1,371
331
1,040
9,353,425
1,854,795
7,498,630
1988
1,349
332
1,017
9,328,767
1,841,096
7,487,671
1987
1,334
326
1,008
9,227,397
1,764,384
7,463,014
1986
1,350
338
1,012
9,005,479
1,704,110
7,301,370
1985
1,370
356
1,014
8,830,137
1,742,466
7,087,671
1984
1,389
359
1,030
8,805,479
1,816,438
6,989,041
* Urban Collector Lane Miles / VMT
** Adjusted Lane Miles / VMT - do not include urban collector data for reasons discussed in text
DEMOGRAPHIC DATA
YEAR
POP
POPDEN
GAREA
PCI
LABOR
EMPLOY
UNEMPLOY
JOBS
GASPRICE
1995
554,256
9,027
61 40
31,176
284,142
258,833
25,309
733,232
1 101
1994
567,013
9,235
61 40
30,348
299,530
275,034
24,496
747,791
1 085
1993
578,127
9,416
61 40
29,697
307,378
280,873
26,505
767,792
1 173
1992
585,794
9,541
61 40
29,227
310,124
283,586
26,538
768,148
1 217
1991
594,301
9,679
61 40
27,792
314,607
289,945
24,661
774,905
1 303
1990
603,6(8
9,831
61.40
27,380
329,162
307,369
21,793
786,573
1 425
1989
624,168
10,166
61 40
26,051
315,000
299,000
16,000
777,829
1 324
1988
630,432
10,268
61 40
25,259
332,000
315,000
16,000
769,851
1 279
1987
636,930
10,373
61 40
23,558
330,000
310,000
21,000
746,085
1 258
1986
638,269
10,395
61 40
22,821
323,000
298,000
25,000
732,726
1 259
1985
634,549
10,335
61 40
22,293
324,000
296,000
27,000
713,254
1 621
1984
633,382
10,316
61 40
21,827
321,000
292,000
29,000
698,919
1 692
-------
APPENDIX D: COMPLETE LISTING FOR BASE RUNS
The following run listings relate to the runs presented in Table 3-1, page 3-2 (all five study
areas). They include the intercept coefficients for these models.
-------
ALL COUNTIES LOG REGRESSION (INCLUDING WASHINGTON DC)
Model MODEL1
Dependent Variable LOGVMT
Analysis of Variance
Sunt of
Mean
Source
DF
Squares
Square
F Value
Prob>F
Model
231
2476.00137
10 71897
1774 190
0 0001
Error
2188
13 21905
0 00604
C Total
2419
2489.30041
Root MSE
0
07773 R-square
0 9947
Dep Mean
13
45050 Ad3
R-sq
0 9941
C V
0
57754
-------
ALL COUNTIES LOG REGRESSION I INCLUDING WASHINGTON DCI
Parameter Estimates
Parameter Standard T for HO
Variable DF
Estimate
Error
Parameter-0
Prob >
|T|
INTERCEP l
4
507597
0
48831683
9
231
0
0001
LOGLM i
0
507263
0
04729827
12
416
0
0001
LOGPOP l
0
519973
0
03818200
13
618
0
0001
YR 1986 1
0
020195
0
00741931
2
722
0
0065
YR 1987 1
0
062026
0
00746200
8
313
0
0001
YR 1988 1
0
1118S6
0
00752326
14
868
0
0001
YR_1989 1
0
146675
0
00760849
19
278
0
0001
YR 1990 1
0
152479
0
00770586
19
787
0
0001
YR 1991 1
0
161847
0
00789412
20
502
0
0001
YR_1992 1
0
198955
0
00810659
24
542
0
0001
YR_1993 l
0
218829
0
00832352
26
290
0
0001
YR 1994 1
0
237531
0
00860552
27
602
0
0001
YR 1995 I
0
252312
0
0C886717
29
582
0
0001
MDANMEAR 1
0
422805
0
07731033
5
469
0
0001
MDBALTTM 1
0
421511
0
09591121
4
395
0
0001
MDCALVER 1
0
183778
0
04225013
4
350
0
0001
MDCAROLI I
-0
07B243
0
05479928
-1
428
0
1535
MDCARROL 1
0
007738
0
03885937
2
258
0
0241
MDCECIL 1
-0
033707
0
03437522
-0
981
0
3269
MDCHARLE 1
0
0B6591
0
03497409
2
476
0
0134
MDDORCHE 1
-0
081911
0
05241145
-1
563
0
1182
MDFREDER 1
0
329766
0
04851943
6
797
0
0001
MDGARRET 1
-0
064957
0
04 977609
-1
305
0
1920
MDHARFOR 1
-0
011691
0
04711814
-0
248
0
8041
MDHOWARD 1
0
611405
0
04742235
12
893
0
0001
MDKENT 1
-0
152430
0
06464479
-2
35 B
0
0185
MDMONTGO 1
0
361121
0
09747666
3
705
0
0002
MDPRNCGE 1
0
465586
0
09861418
4
721
0
0001
MDQUEENA 1
0
362219
0
04528363
7
999
0
0001
MDSTMARY l
-0
048321
0
03379238
-1
430
0
1529
MDSOMERS 1
0
097008
0
06421800
1
511
0
1310
MDTAIiBOT 1
0
441113
0
05204627
8
475
0
0001
MDVTASHIN 1
0
266961
0
03975223
6
716
0
0001
MDWICOMI 1
0
060447
0
03421068
1
767
0
0774
MDWORCES 1
0
235318
0
04333126
5
431
0
0001
NCALAMAN 1
0
128838
0
03933654
3
27S
0
0011
NCALEXAN 1
-0
240257
0
09278951
-2
5B9
0
0097
NCALLEGH 1
-0
659206
0
09575930
-6
884
0
0001
NCANSON 1
-0
186396
0
05836345
-3
194
0
0014
NCASHE 1
-0
450838
0
06378146
-7
068
0
0001
NCAVERY 1
0
077077
0
08249318
0
934
0
3502
NCBEAUFO 1
-0
327488
0
04065115
-e
056
0
0001
KCBERTIE 1
-0
244214
0
.06105171
-4
000
0
0001
NCBLADEN 1
-0
330234
0
04930441
-6
698
0
0001
NCBRUNSW 1
0
.226192
0
03619152
6
250
0
0001
NCBUNCOM 1
0
207703
0
04732901
4
388
0
0001
NCBURKE 1
0
113359
0
03604609
3
145
0
0017
NCCABARK 1
0
204312
0
04133466
4
94 3
0
0001
NCCALDWE 1
-0
174021
0
04249783
-4
095
0
0001
NCCAMDEK 1
0
120017
0
11878401
1
010
0
3124
NCCARTER 1
0
275739
0
04504085
6
122
0
0001
NCCASWEtj 1
-0
.482002
0
06501123
-7
414
0
0001
NCCATAWB 1
0
121530
0
04388233
2
769
0
0057
-------
i . JNTI__ __ J REl DN JING ___ _ -flGTC
Parameter Standard T for HO
Variable DF
Estimate
Error
Pararr.eter-0
Prob >
|T|
NCCHATHA 1
-0
mm
0
04533738
-2
4 52
0
0143
NCCHEROK 1
-0
263 564
0
06624544
-3
979
0
0001
NCCHOWAN 1
-0
330985
0
09878293
-3
351
0
0008
HCCLAY 1
-0
228178
0
12517207
-1
823
0
06B5
NCCLEVEL 1
-0
068654
0
03423231
-2
006
0
0450
NCCOLUMB 1
-0
315394
0
03706845
-B
508
0
0001
NCCRAVEN 1
-0
0S80Q4
0
03584053
-1
621
0
1052
NCCUMBER 1
-0
203773
0
05976813
-3
409
0
0007
NCCURRIT 1
0
289096
0
00165888
3
540
0
0004
KCDARE l
0
446452
Q
059721Q0
7
476
0
0001
NCDAVIDS 1
-0
019523
0
03880910
-0
503
0
6150
NCDAVIE 1
0
325852
0
05938019
5
582
0
0001
NCDUPLIN 1
-0
221223
0
04 041200
-5
474
0
0001
NCDURHAM 1
0
321519
0
04960478
6
615
0
0001
WCEDGECC 1
-0
402210
0
03559B99
-11
298
0
0001
NCFORSYT l
0
171164
0
05845597
2
928
0
0034
NCFRANKL 1
-0
242085
0
04719417
-5
130
0
0001
NCGASTON 1
0
101537
0
04645107
2
186
0
02B9
NCGATES 1
-0
235383
0
09610154
-2
447
0
0145
NCGRAHAM 1
-0
793261
0
11275362
-7
035
0
0001
MCGRANVI 1
0
129602
0
04655675
2
784
0
0054
NCGRBENE 1
-0
190435
0
07839859
-2
429
0
0152
NCGUILFO 1
0
102117
0
06925256
1
475
0
1405
NCHALIFA 1
-0
071368
0
03509529
-2
034
0
0421
MCHARNET 1
-0
053667
0
03542274
-1
515
0
1299
NCHAYWOO 1
0
295887
0
03769300
7
850
0
0001
NCHENDER 1
0
174935
0
04562367
3
834
0
0001
MCHERTFO 1
-0
2883B3
0
06592739
-4
374
0
0001
NCHOKE l
-0
128730
0
08381568
-1
536
0
1247
MCHYDE 1
-0
669719
0
1114Q138
-6
012
0
0001
HCIREDEL 1
0
384634
0
03436358
11
193
0
0001
NCJACKSO 1
0
041654
0
05348948
0
779
0
4362
NCJOHNST 1
0
1B7686
0
03754598
4
999
0
0001
NCJONES 1
0
187687
0
09277487
2
023
0
0432
MCLEE 1
0
.104144
0
05B22119
1
789
0
0738
NCLENOIR 1
-0
091430
0
04041405
-2
262
0
0238
NCLINCOL 1
-0
0B9234
0
05412373
-1
649
0
0994
NCHACON 1
-0
167100
0
06436680
-2
596
0
0095
NCMADISO 1
-0
548728
0
06950712
-7
895
0
0001
NCMART1N 1
-0
239596
0
0568664 7
-4
213
0
0001
NCMCDOWE 1
0
.257558
0
04686416
5
496
0
0001
NCMECKLE 1
0
.234267
0
00117526
2
8B6
0
0039
NCMITCHE 1
-0
397092
0
08569804
-4
634
0
0001
NCWOSTGO 1
-0
063392
0
05832145
-1
173
0
2411
NCMOORE 1
-0
218107
0
03648264
-5
978
0
0001
MCNASH 1
0
.140097
0
03549178
3
947
0
0001
ncwewhan 1
0
049091
0
047481B6
1
051
0
2935
NCKORTHA 1
0
044 000
0
060749 93
0
724
0
4690
NCONSLOW 1
-0
264479
0
04407635
-6
000
0
0001
NCORANGE 1
0
254 979
0
042489S7
6
001
0
0001
NCPAML3C 1
-0
175495
0
10024679
-1
751
0
OB01
NCPASQXJO 1
-0
241201
0
07522154
-3
207
0
0014
KCPENDER 1
-0
007097
0
O48096Q7
-0
145
0
9 84 6
NCPERQUI 1
-0
047153
0
11720941
-0
402
0
6875
WCPBRSON 1
-0
44 8-820
0
06100289
-7
357
0
0001
-------
AIiLi COUNTIES LOG REGRESSION (IHCLUDING WASHIHGTON DC)
Parameter
Standard
T for HO
Variable DF
estimate
ErroT
Parameter»0
Prob > |T|
NCPITT 1
-0 300061
0 03625839
-8 276
0 0001
NCPOLK 1
0 13 9885
0 08652077
2 195
0 0283
kcrandol 1
-0 073256
0 03570654
-2.052
0 0403
NCRICHMO 1
-0 224960
0 04734208
-4 752
0 0001
NCROBESO 1
0 060501
0 03934801
1 538
0 1243
NCROCKIN 1
-0 173580
0 03356732
-S.17J
0 0001
NCROWAN l
0 006396
0 04068309
0 206
0 8365
WCRUTHER 1
-0 205965
0 04257155
-6 717
0 0001
NCSAMPSO 1
-0 193097
0 03729535
-5 178
0 0001
NCSCOTIa 1
-0 066229
0 05045163
-1 475
0.1403
NCSTANtY 1
-0 245212
0 04617735
-5 310
0 0001
NCSTOKES 1
-0 617348
0 04888329
-12 629
0 0001
NCSURRY l
0 134165
0 03526513
3 805
0 0001
NCSWAIN l
-0 100731
0 09359294
-1 076
0 2819
NCTRAHSY 1
-0 1374B3
0 06269735
-2 193
0 0284
NCTYHRKL 1
-0 355414
0 13516324
-2 630
0.0086
NCTINIQtt l
-0 17820S
0 03568400
-4 994
O 0001
NCVANCK 1
O 055169
0 05869031
0 937
0.3488
NCWAKE l
0.164 941
0 07581480
2 176
0 0297
NCWARRlTN 1
-0 270999
0 07400939
-3 7 70
0 0OG2
HCWASHIN 1
-0 071278
0 09935444
-0 798
0 4251
KCWATAUG 1
0 027467
0 05965659
0 460
0 6453
KCWAVWE 1
-0 236497
0 03650X29
-6 409
0 0001
NCWILKES 1
-0 117247
0 04044287
-2 899
0 0036
NCWILSON 1
0 070324
0 03439443
2 045
0 0410
KCYADKIn 1
0 230077
0 05965021
3 991
0 0001
NCYANCBY 1
-0 384413
0 08104149
-4 743
0.0001
VAACCOMA 1
0 184790
0 05265450
3 509
0 0005
VAALBEMa 1
0 317127
0 03349*95
9 467
0 0001
VAALLECJH 1
0 .167846
0.07S62410
2 219
0.0266
VAAMELlA 1
0 208492
0 10737763
1 942
0 0523
VAAMHERS 1
0 045105
0 06033723
0 74 8
0 454B
vaappoma 1
0,114015
0 09328534
1 222
0.2216
VAARLING 1
0 64081B
0 06342455
10 104
0 0001
VAAUGUST 1
0 397282
0 03530507
11 254
0 0001
VABATH 1
-0 473295
0 11770195
-4 021
0 0001
VABEDFOR 1
-0 035141
0 04064453
-0 865
0 3874
VABLANU 1
0 584650
0 10152305
5 759
0 0001
VABOTETTO 1
0 612080
0 05452601
11 225
0 0001
VABRUNSW 1
0 1634 04
0 06874154
2 377
0 0175
VABUCHAN 1
-0 086249
0 06546151
-1 316
0 1878
VABUCKlN 1
-0 168968
0 03338037
-2 027
0 0428
VACAMPBE 1
0 123716
0 04326560
2 859
0 0043
VACAROLI 1
0 788207
0 06187653
12 738
0 0001
VACARROL 1
0 264704
0 05494&54
4 817
0 0001
VACHARX.E 1
0 121326
0.12376^66
0 940
0 3271
VACHARLO 1
-0 241464
0 - 08064124
-2 994
0 0026
VACHESTE 1
0 3294 75
-------
^ujij wUNTIeij uvvj RE(j{ujgoiOK (nruniNGTO^ ia./
Parameter Standard T for HO.
Variable OF
Estimate
Error
Parameters
Prob >
|T|
VAFAIRFA 1
0
&01702
0
09667513
8
293
0
0001
VAFAUQUI 1
0
412666
0
03918922
10
530
0
0001
VAFLOYD 1
-0
264809
0
10106858
-2
620
0.
0089
VAFLUVAN 1
-0
228937
0
10223993
-2
239
0
0252
VAFRANKL 1
0
095995
0
05291128
1
814
0
0698
VAFREDER 1
0
435250
0
03961419
10
932
0
0001
VAGILES 1
-0
018914
0
0737268B
-0
257
0
7976
VAGLOUCE 1
0
367983
0
06693261
5
498
0
0001
VAGOOCHL 1
0
S87213
0
07487080
7
84 3
0.
0001
VAGRAYSO 1
-0
578012
0
07479579
-7
728
0
0001
VAGREENE 1
0
285423
0
11788301
2
421
0
0155
VAGREENS 1
0
873455
0
09921389
8
804
0
0001
VAHALIFA 1
-0
195152
0
04670268
-4
179
0
0001
VAHANOVE 1
0
567580
0
03489967
16
837
0
0001
VAHENRIC 1
0
227994
0
05232206
4
358
0
0001
VAHENRY 1
0
002495
0
04243985
0
059
0
9531
VAHIGKLA 1
-0
577207
0
13911055
-4
149
0
0001
VAISLEWI 1
0
390586
0
06398077
6
105
0
0001
VAJAMESC 1
0
427046
0
06232127
6
852
0
0001
VAKINGQU 1
-0
005020
0
11284663
-0
044
0
9645
VAKINGGE 1
0
359851
0
08312938
4
329
0
0001
VAKINGWI 1
0
085449
0
10298644
0
830
0.
4068
V ALAN CAS 1
-0
155962
0
10070598
-1
54 9
0
1216
VALEE 1
-0
173554
0
06340447
-2
737
0
0062
VALOUDON 1
0
244444
0
04144365
S
898
0
0001
VALOUISA 1
0
300475
0
06226578
4
826
0
0001
VALUNENB 1
-0
479232
0
09794486
-4
893
0
0001
VAMADISO 1
0
188790
0
09149449
2
063
0
0392
VAMATHEW 1
0
31S546
0
12433403
2
538
0
0112
VAMECKLE 1
-0
043806
0
04857008
-0
902
0
3672
VAMIDDLE 1
0
490134
0
10539168
4
651
0
0001
VAMONTGO 1
0
268208
0
04302540
6
234
0
0001
VANELSON 1
-0
049606
0
07868044
-0
630
0
5284
VANEWKEN 1
0
997190
0
08492909
11
741
0
0001
VANORTHA 1
0
126622
0
08815797
1
436
0
1511
VANORTHU 1
0
012263
0
10665125
0
115
0
9085
VANOTTOM 1
-0
199292
0
07621011
-2
615
0
0090
VAORANGB 1
-0
003375
0
07079780
-0
04 8
0
9620
VAPAGE 1
-0
373774
0
08037895
-4
650
0
0001
VAPATRIC 1
-0
312096
0
07652515
-4
078
0
0001
VAPITTSY 1
-0
243763
0
03566235
-6
835
0
0001
VAPOWHAT 1
-0
037064
0
09152330
-0
405
0
6855
VAPRNCED 1
-0
032782
0
07203953
-0
450
0
6527
VAPRNCGE 1
0
557071
0
06732203
8
275
0
0001
VAPRNCWI 1
0
486253
0
06031362
8
062
0
0001
VAPULASK 1
0
161800
0
05580810
2
899
0
0038
VARAPPAH 1
-0
216539
0
10226038
-2
118
0
0343
VARICHMO 1
0
280975
0
11740408
2
393
0
0168
VAROAWOK 1
0
519495
0
0463477B
11
209
0
0001
VAROCKBR 1
0
649031
0
06257040
10
373
0
0001
VAROCKIN 1
0
118617
0
03481585
3
407
0
0007
VARUSSEL 1
0
016458
0
05519387
0
298
0
7656
VASCOTT 1
-0
020491
0
06049744
-0
339
0
7349
V AS HEN AN 1
0
434369
0
04914304
8
839
0
0001
V AS MYTH 1
0
100207
0
05318617
1
884
0
0597
-------
ALL COUNTIES LOG REGRESSION [INCLUDING WASHINGTON DC1
Parameter
Standard
T for HO:
Variable
DF
Estimate
Error
Parameter«0
Prob > |T|
VASOUTHA
1
0.163450
0 07080441
2.308
0.0211
VASPOTSY
1
0.576666
0.04729181
12.194
0.0001
VASTAFFO
1
0.740435
0.04601066
15.422
0 0001
VASURRY
1
-0.147539
0 12104506
-1.219
0.2230
VASUSSEX
1
0.677467
0 08440211
8.027
0.0001
VATAZEWB
1
-0 153227
0.04128956
-3.711
0.0002
VAWARREN
1
0.087642
0 07637712
1 147
0.2513
VAWASHIN
1
0.229952
0.04061402
5.662
0.0001
VAWESTMO
1
-0.7515B2
0 07005920
-10.728
0.0001
VAWISE
1
-0.178450
0 04683239
-3.810
0.0001
VAWYTHE
1
1.076086
0.07586208
14.IBS
0.0001
VAYORK
1
0.685535
0 05905185
11.609
0 0001
VASOFFOL
1
0 328637
0 04025034
8.165
0.0001
WASHDC
1
0.173034
0 08847046
1.956
0.0506
-------
A NTII REC N ( ING
Model MODEL1
Dependent Variable LOGVMT
Source
Model
Error
C Total
Root MSE
Dep Mean
C V
Analysis of Variance
Sum of Mean
DF Squares Square
232 2476 18627 10 67322
2187 13 11415 0 00600
2419 2489 30041
0 07744 R-square
13 45850 Adj R-sq
0 57537
JGT01
F Value Prob>F
1779 935 0 0001
9947
9942
-------
ALL COUNTIES LOG REGRESSION (INCLUDING WASHINGTON DC)
Parameter Estimates
Parameter
Standard
T Cor HO
Variable DF
Estimate
Error
Parameter*0
Prob >
1T |
INTERCEP 1
2
207920
0
73415275
3
007
0
0027
LOGLM 1
0
563626
0
04745869
11
876
0
0001
LOGPOP l
0
563862
0
03979429
14
295
0.
0001
LOGPCI98 1
0
195366
0
04671029
4
183
0
0001
YR 1986 1
0
010912
0
007717S5
1
414
0
1575
YR 1987 1
0
04 8 941
0
00806573
6
068
0,
0001
YR 1968 1
0
092404
0
00882077
10
476
0
0001
YR 1989 1
0
122677
0
00950663
12
904
0
0001
YR 1990 1
0
129479
0
00944328
13
711
0
0001
YR 1991 1
0
141308
0
009271S4
15
241
0
0001
YR 1992 1
0
174701
0
00993127
17
599
0
0001
YR_1993 1
0
191144
0
01061018
18
015
0
0001
YR 1994 1
0
206360
0
01135965
18
166
0
0001
YR_199S 1
0
227435
0
01214803
18
722
0
0001
MDANNEAR 1
0
278170
0
08442747
3
295
0
0010
MDBALTIM 1
0
246324
0
10432891
2
361
0
0183
MDCALVER 1
0
129706
0
04403237
2
946
0
0033
MDCAROLI 1
¦0
031942
0
05570495
-0
573
0
5664
MD CARROL 1
-0
001785
0
04423664
-0
040
0
9678
MD CECIL 1
-0
066290
0
03512124
-1
887
0
0592
MDCHARLE 1
0
025919
0
03774200
0
687
0
4923
MD DOR CHE 1
-0
060059
0
05247574
-1
145
0
2525
MDFREDER 1
0
256114
0
05144525
4
978
0
0001
MDGARRET 1
0
003250
0
05220210
0
062
0
9504
MDHARFOR 1
-0
104382
0
05190982
-2
011
0
0445
MDHOWARD 1
0
456624
0
06001281
7
609
0
0001
MDKENT 1
-0
139822
0
06447301
-2
169
0
0302
MDMONTGO 1
0
120164
0
11291390
1
064
0
2874
MDPRNCGE l
0
317558
0
10442501
3
041
0
0024
MDQDEENA 1
0
338572
0
04546679
7
447
0
0001
MDSTMARY 1
-0
0692-18
0
03405579
-2
Q50
0
0405
MDSOMERS 1
0
112374
0
06646644
2
5 93
0
0096
MDTALBOT 1
0
371311
0
05447081
6
017
0
DOG 1
KDWASHIN 1
0
237498
0
04 022485
5
904
0
0001
MDWICOMI 1
0
036263
0
03456943
1
04 9
0
2943
KDWORCES 1
0
214989
0
04 344162
4
949
0
0001
NCAIAMAN 1
0
077302
0
04108053
1
882
0
0600
KCALEXAN 1
-0
235078
0
09245003
-2
54 3
0
0111
NCALLEGH 1
-0
566190
0
09795776
-5
780
0
0001
WCANSON 1
-0
121025
0
06020871
-2
010
0
0445
NCASHE 1
-0
386301
0
Q6S3B901
-5
90S
0
OG01
NCAVERY 1
0
145990
0
OB381931
1
742
0
0817
NCBSAUFD 1
-0
292611
0
04134836
-7
077
0
00D1
NCESRTIE 1
-0
152065
0
06469019
-2
351
0
0188
NCBLADEH 1
-0
247016
0
05299635
-4
661
0
0001
NCBRUNSW 1
0
25B371
0
036&9273
7
017
0
0001
NCBUNCOM 1
0
145125
0
04946644
2
934
0
0034
NCBURKE 1
0
104772
0
03596963
2
913
0
0036
NCCABARR 1
0
150393
0
04315045
3
485
0
0005
NCCALDWE 1
-0
182378
0
04238568
-4
303
0
0001
NCCAMDEN 1
0
226503
0
12104656
1
871
0
0615
NCCARTER 1
0
279695
0
04488201
6
232
0
0001
nccaswel 1
-0
394241
0
06808168
-S
791
0
0001
-------
Aul uuvjNTIds LAAa REGru^diUN [ini-ijuuING nA^fiiWGTCn
Parameter Standard T for HO
Variable DF
Estimate
Error
Parameters
Prob >
|T|
NCCATAWB 1
0
050599
0
04689193
1
079
0
2807
NCCHATHA 1
-0
118869
0
04520488
-2
630
0
0086
NCCHEROK 1
-0
167450
0
0699B344
-2
396
0
0167
NCCKOWAN l
-0
272899
0
09938780
-2
746
0
0061
NCCLAY 1
-0
125698
0
12708723
-0
989
0
3227
KCCLEVEL 1
-c
060389
0
03421924
-2
34 9
0
0189
NCCOLUMB l
-0
267357
0
03857426
-6
913
0
0001
KCCRAVEN 1
-0
068234
0
03578857
-1
907
0
0567
NCCUMBER 1
-0
250157
0
06056805
-4
130
0
0001
NCCURRIT 1
0
348372
0
08257807
4
219
0
0001
NCDARB 1
0
474914
0
05988505
7
930
0
0001
NCDAVIDS 1
-0
055791
0
03962408
-1
4 08
0
1593
NCDAVIE 1
0
310398
0
05827863
5
326
0
0001
NCDUPLIN l
-0
176664
0
04164621
-4
242
0
0001
NCDURHAM 1
0
225065
0
05363371
4
196
0
0001
NCEDGECO l
-0
370984
0
03624288
-10
236
0
0001
NCFORSYT 1
0
041565
0
06596706
0
630
0
5287
NCFRANKL, l
-0
196663
0
04824445
-4
081
0
0001
NCGASTON 1
0
045355
0
04B18701
0
941
0
3467
NCGATES 1
-0
131951
0
09896101
-1
333
0
1826
NCGRAHAM l
-0
646205
0
11770490
-5
490
0
0001
NCGRANVI l
0
171257
0
04 743943
3
610
0
0003
NCGREENE 1
-0
117623
0
08002132
-1
470
0
1417
NCGUILFO 1
-0
021411
0
07504870
-0
285
0
7754
NCHALIFA 1
-0
022191
0
03680775
-0
602
0
5475
NCHARNET 1
-0
022657
0
03606041
-0
628
0
5299
NCHAYWOO 1
0
313228
0
03777992
6
291
0
0001
NCHENDER 1
0
124036
0
04705361
2
636
0
0084
NCHERTFO 1
-0
206085
0
06856434
-3
006
0
0027
NCHOKE l
-0
034689
0
08647571
-0
401
0
6884
KCHYDE 1
-0
540033
0
11518245
-4
695
0
0001
NCIREDEL 1
0
355319
0
03494488
10
160
0
0001
NCJACKSO 1
0
109696
0
05571687
1
969
0
0491
NCJOHNST 1
0
185511
0
03740887
4
959
0
0001
NCJONES 1
0
265973
0
09430335
2
820
0
0048
NCLEE 1
0
085530
0
05817345
1
470
0
1416
NCLENOIR 1
-0
086475
0
04028001
-2
147
0
0319
NCLINCOL 1
-0
099003
0
05397144
-1
834
0
0667
NCMACON 1
-0
122025
0
06502482
-1
877
0
0607
NCMADISO 1
-0
453299
0
07290860
-6
217
0
0001
NCMARTIN 1
-0
177171
0
05858632
-3
024
0
0025
NCMCDOWE 1
0
305391
0
04806882
6
.353
0
0001
NCMECKLE 1
0
073802
0
08950994
0
825
0
4097
NCMITCHE 1
-0
318418
0
08742441
-3
642
0
0003
NCMONTGO 1
0
.001634
0
06046695
0
027
0
9784
NCMOORE 1
-0
266225
0
03812320
-6
983
0
0001
NCNASH 1
0
125855
0
03S52235
3
543
0
0004
KCKEWHAN 1
•
-------
ALL COUNTIES LOG REGRESSION (INCLUDING WASHINGTON T>C1
Parameter
Standard
T for HO
Variable DF
Estimate
Error
Parameter«0
Prob »
1T |
NCPERSON l
-0
417154
0
06124401
-6
811
0
0001
NCPITT l
-0
318993
0
03640512
-8
762
0
0001
NCPOLK 1
0
104485
0
08620617
2
140
0
0325
NCRANDOL l
-0
100299
0
03615546
-2
774
0
0056
NCRICHMO 1
-0
185860
0
04808220
-3
86S
0
0001
NCROBESO 1
0
10342B
0
04052261
2
552
0
0108
NCROCKIN 1
-0
182838
0
03351468
-5
455
0
0001
NCROWAN 1
-0
025091
0
04131463
-0
607
0
5437
NCRUTHER 1
-0
272404
0
04253575
-6
404
0
0001
NCSAMPSO 1
-0
162693
0
03785999
-4
297
0
0001
HCSCOTIA 1
-0
042436
0
05916644
-0
717
0
4733
NCSTANLY l
-0
244083
0
04600507
-5
306
0
0001
NCSTOKES 1
-0
598093
0
04891720
-12
227
0
0001
NCSURRY 1
0
128987
0
03515493
3
669
0
0002
NCSWAIN 1
0
028754
0
09824732
0
293
0
7698
NCTRANSY l
-0
118993
0
06261861
-1
900
0
0575
NCTYRREL 1
-0
212297
0
13893620
-1
528
0
1267
NCUNION 1
-0
207169
0
03621651
-5
720
0
0001
NCVANCE l
0
080923
0
05899134
1
372
0
1703
NCWAKE l
0
017668
0
08333497
0
212
0
8321
NCWARREM 1
-0
168658
0
07B30952
-2
154
0
0314
NCWASHIN 1
0
003722
0
09080761
0
041
0
9673
NCWATAUG 1
0
063313
0
06004971
1
054
0
2918
NCWAYNE l
-0
235597
0
03676361
-6
408
0
0001
NCWILKES 1
-0
117586
0
04029137
-2
918
0
0036
NCWILSON 1
0
059813
0
03435756
1
741
0
0818
NCYADKIM 1
0
257683
0
05961124
4
323
0
0001
NCYANCEY 1
-0
294530
0
08354884
-3
525
0
0004
VAACCOMA 1
0
218342
0
05306698
4
114
0
0001
VAALBEMA 1
0
254569
0
03656996
6
961
0
0001
VAALLEGH 1
0
239382
0
07725768
3
098
0
0020
VAAMELIA 1
0
274413
0
10813002
2
538
0
0112
VAAMHERS 1
0
093417
0
06121086
1
526
0
1271
VAAPPOMA 1
0
179733
0
09425459
1
907
0
0567
VAARLING 1
0
435563
0
08000529
5
444
0
0001
VAAUGUST 1
0
390339
0
03520892
11
086
0
0001
VABATH 1
-0
394013
0
11875265
-3
325
0
0009
VABEDFOR 1
-0
047206
0
04059481
-1
163
0
2450
VABLAND 1
0
730709
0
10700117
6
829
0
0001
VABOTETO 1
0
640375
0
05474126
11
696
0
0001
VABRUMSW 1
0
274489
0
07345360
3
737
0
0002
VABUCHAN 1
-0
048249
0
065B4599
-0
733
0
4638
VABUCKIN 1
-0
070269
0
08635598
-0
814
0
4159
VACAMPBE 1
0
107830
0
04327048
2
492
0
0128
VACAROLI 1
0
844188
0
06308089
13
383
0
0001
VACARROli 1
0
333075
0
05713112
5
830
0
0001
VACHARLE 1
0
198466
0
12467650
1
592
0
1116
VACHARLO 1
-0
135041
0
0642720?
-1
602
0
1092
VACHESTE 1
0
203697
0
05921127
3
440
0
0006
VACLARKE 1
0
330815
0
09230720
3
584
0
0003
VACRAIG 1
-0
554361
0
12881927
-4
303
0
0001
VACULPEP 1
0
112270
0
06658154
1
686
0
0919
VACUMBER 1
-0
191305
0
11409077
-1
677
0
0937
VADICKEN 1
-0
211832
0
08206962
-2
5B1
0
0099
VADINWID 1
0
316791
0
05952769
5
322
0
0001
-------
ALL COUNTIES LOG REGRESSION (IW-LULIING WASHINGTON m.i
Parameter
Standard
T for HO
Variable DF
Estimate
Error
Parameter«0
Prob
|T|
VAESSEX 1
0
377S21
0
09965488
3
788
0
0002
VAFAIRFA 1
0
551726
0
11334987
4
867
0
0001
VAFAUQUI 1
0
335366
0
04319577
7
764
0
0001
VAFLOYD 1
-0
166730
0
10240566
-1
823
0
0684
VAFLUVAN 1
-0
192245
0
10223383
-1
880
0
0602
VAFRANKL 1
a
114360
0
0523S5S2
2
162
0
0307
VAFREDER 1
0
422036
0
03979059
10
606
0
0001
VAGILES 1
0
043855
0
07496803
0
565
0
5586
VAGLOUCB 1
0
3699 Q4
0
0666S317
5
546
0
0001
VAGOOCHL 1
0
567303
0
07474193
7
590
0
C001
VAGRAYSO 1
-0
481509
0
07759361
-6
283
0
0001
V AG RE EKE 1
0
347*64
0
11837424
2
935
0
0034
VAGREENS 1
0
968 881
O.10144110
9
551
0
0001
VAHALIFA 1
-0
13&475
0
04946076
-2
857
0
0043
VAHANOVE l
0
527940
0
03758004
14
048
0
0001
VAHENRIC 1
0
093294
0
06127225
1
523
0
1280
VAHENRY l
-0
015391
0
04249649
-0
362
0
7173
VAHIGHLA 1
-0
439515
0
14244554
-3
085
0
0021
VAISLEWI l
0
398971
0
06377249
6
256
0
0001
VAJAMESC 1
0
381979
0
06301573
6
062
0
0001
VAKINGQU 1
0
082376
0
11434903
0
720
0
4714
VAKINGGE 1
0
380152
0
08295993
4
582
0
0001
VAKINGWI 1
0
104418
0
10270064
1
017
0
3094
VAIiANCAS 1
-0
170858
0
10039173
-1
702
0
0889
VALEE 1
-0
077331
0
06722584
-1
150
0
2501
VALOUDON 1
0
125097
0
05018916
2
493
0
0128
VALOUISA 1
0
343892
0
06289457
5
468
0
0001
VALUNENB 1
-0
383749
0
10021269
-3
629
0
0001
VAMADISO 1
0
267463
0
09307212
2
874
0
0041
VAMATHEM 1
0
325433
0
12389059
2
627
0
0087
VAMECXLE a
0
008416
0
04997296
0
168
0
8663
VAMIDDLE 1
0
524410
0
10531602
4
979
0
0001
VAMONTGQ 1
0
279682
0
04295185
6
512
0
0001
VANBLSON 1
0
028409
0
08057428
0
353
0
7244
V ANEW KEN 1
1
039076
0
08520140
12
196
0
0001
VANORTHA 1
0
1946B2
0
08932228
2
180
0
0294
VANORTHU 1
0
.036886
0
10641450
0
347
0
7299
VANOTTGW 1
-0
123468
0
07805880
-1
582
0
1139
VAORANGE 1
0
018677
0
07072924
0
264
0
7918
VAPAGE 1
-0
332779
0
00067532
-4
125
0
0001
VAPATRIC 1
-0
246340
0
07784244
-3
165
0
0016
VAPITTSY 1
-0
231411
0
03565122
-6
491
0
0001
VAPCWHAT 1
-0
001632
0
09157296
-O
018
0
9858
VAPRNCED 1
0
059840
0
07587030
0
789
0
4304
VAPRNCGE 1
0
584 872
0
06739826
8
678
0
0001
VAPRNCWI 1
0
.366918
0
06651747
5
516
0
0001
VAPULASK 1
0
.199217
0
05631404
3
538
0
0004
VARAPPAH 1
-a
157794
0
10264073
-1
534
0
1251
VARICHMO 1
0
358019
0
11840569
3
024
0
0025
VAROANOK 1
0
433870
0
05050896
8
590
0
0001
VAROCKBR 1
0
724789
0
06491409
11
165
0
0001
VAROCKIN 1
0
114477
0
03469948
3
299
0
0010
VARUSSEL 1
0
090892
0
05779517
1
573
0
1159
VASCOTT 1
0
062646
0
063463B6
0
987
0
3237
V ASHEN AN 1
0
449246
0
04908789
9
152
0
0001
-------
hLXi COUNTIES LOG REGRESSIOM (INCLUDING WASHINGTON DC)
Parameter
Standard
T for HD;
Variable DF
Estimate
Error
Paranneter-0
Frob >
in
VASMYTH 1
0.147100
0.05416002
2.716
~ .
0067
VASOUTHA l
0.208424
0.0713530 8
2 921
0.
003S
VASFOTSY 1
0 530249
0,04840395
10.955
0.
0001
VASTAFFO 1
0.699559
0 04031894
14.330
0.
0001
VASTORY 1
-0.063084
0 12223878
-0.523
0.
6013
VASUSSEX l
0.763233
0 08655005
8 .818
0.
0001
VATAZEWE 1
-0.123650
0.04173824
-2.963
0
0031
VAWARREN 1
0.088696
0.07609128
1.166
0
2439
VAWASKIN 1
0.247597
0.04068113
6.086
0
0001
VAWESTKO l
-0 685391
0.07156831
-9.577
0
0001
VAWISE 1
-0.152944
0.04705370
-3.250
0
0012
VAWYTHB l
1.107627
0.07595306
14 583
0
0001
VAYORJC 1
0 631247
0.06024537
10.478
0
.0001
VASUFFOt l
0.319469
0.04015910
7.956
0
0001
WASHDC 2
-0.030663
0.20069218
-0.304
0
7612
-------
M/UtXUAND COUNT I Kb LOj KJSOKBSSiUH
Model. M0DEL1
Dependent Variable- LOGVMT
Source
Model
Error
C Total
DF
51
592
643
Analysis of Variance
Sum of
Squares
673 62470
3 16099
676.78569
Mean
Square
13 20833
0 00534
Root MSB
Dep Mean
C V
0.07307
14 16633
0.51581
R-square
Adj R-aq
F Value
2473 698
Prcb>F
0 00D1
0 9953
0 9949
-------
MARYLAND COUNTIES LOG REGRESSION
Parameter Estimates
Parameter Standard T for HO
Variable DF
Estimate
Error
Parameters
Prob >
1 TI
INTERCEP 1
3.384472
0
43564161
7
769
0
0001
LOGLM l
0 451239
0
05630867
8
014
0.
0001
LOGPOP l
0 659392
0
02722223
24
223
0
0001
YR 1970 1
0 059339
0
02155613
2
753
0.
0061
YR 1971 1
0 107554
0
02163005
4
972
0
0001
YR 1972 1
0 140056
0
02166655
6
464
0
0001
YR~1973 l
0 192819
0
02173125
a.
873
0
0001
YR 1974 1
0 173953
0
02103087
7
968
0
0001
YR 197S 1
0.242054
0
02197282
11
016
0
0001
YR~1975 1
0 272086
0
02211410
12
304
0
0001
YR-1977 l
0 268203
0
02222318
12
069
0
0001
YR~1978 1
0 336757
0
02234084
15
074
0
0001
YR~~1$79 1
0 324100
0,
02243413
14
450
0
0001
YR~19B0 1
0 342304
0
02251620
15
203
0
0001
YR 1991 1
0 359171
0
02260521
15
689
0
0001
YR 1982 1
0 357255
0
02264867
15
774
0
0001
YR~19B3 1
0 416821
0
02273142
18
337
0
0001
YR 1904 1
0 433596
0
02286570
18
963
0
0001
YR 1985 1
0 474017
0
02302536
20
587
0
0001
YR 1906 1
0.514443
0
02328247
22
096
0
0001
YR 1907 1
0 552630
0
02360608
23
410
0
0001
YR 1908 1
0 570250
0
02383452
23
925
0
0001
YR 1909 1
0 560128
0
02408274
24
089
0
0001
YR~1990 1
0 601950
0
02434215
24
729
0
0001
YR~1991 1
0 614654
0
02459094
24
995
0
0001
YR~1992 1
0 605767
0
02400347
24
423
0
0001
YR 1993 1
0 567581
0
02495715
23
544
0
0001
YR_1994 1
0 573494
0
02514664
22
806
0
0001
YR-1995 1
0 578664
0
02533073
22
844
0
0001
YR 1996 1
0.590786
0
02552950
23
141
0
0001
ANNE AR UN 1
0 259995
0
0568B917
4
570
0
0001
BALTIMOR 1
0 200230
0
07695523
2
602
0
0095
CALVERT 1
O 061386
0
03988692
1
539
0
1243
CAROLINE 1
-0 014360
0
04399737
-0
326
0
7443
CARROLL 1
-0 038871
0
02081856
-1
867
0
0624
CECIL 1
-0 004837
0
02111509
-0
229
0
8189
CHARLES 1
0 045465
0
02001806
2
271
0
.0235
DORCHEST 1
-0 030058
0
04056104
-0
93S
0
3485
FREDERIC 1
0 272858
0
04052517
6
733
0
0001
GARRETT 1
0 066637
0
03575891
1
863
0
0629
HARFORD 1
-0 099580
0
02837145
-3
510
0
.0005
HOWARD 1
O 4 98216
0
02489466
20
013
0
0001
KENT 1
-0 049903
0
0475B551
-1
049
0
.2947
MONTGOME 1
0 185748
0
07324793
2
536
0
0115
PRINCEGE 1
0 231797
0
07911833
2
930
0
0035
OUEENANN 1
O 466322
0
03S42492
23
263
0
0001
STMARYS 1
-0 129395
0
,02115792
-6
.116
0
0001
SOMERSET 1
0 222002
0
05464919
4
062
0
0001
TALBOT 1
0.510174
0
04152211
12
287
0
.0001
WASHINGT 1
0 183256
0
03057296
5
994
0
0001
WICOMICO 1
0 052422
0
02179146
2
406
0
0165
WORCESTE 1
0.302824
0
03157484
9
591
0
0001
-------
MARYLAND COUNTIES LOG REGRESSION
Model: MODEL1
Dependent Variable LOGVMT
Analysis of Variance
Sum o £
Mean
Source
DF
Squares
Square
F Value
Prob>F
Model
52
6*73 62543
12 95434
2422 590
0 0001
Error
591
3 16026
0 00535
C Total
64 3
676.78569
Root MSB 0.07313 R-aquare 0 9953
Dep Mean 14 16633 Adj R-sq 0 9949
C V 0.51619
-------
MARYLAND COUNTIES LOG REGRESSION
Variable DF
INTERCEP l
LOG 1/1 1
LOGPOP l
LOGPCI98 1
YR_1970 1
YR~1971 l
YR_1972 1
YR_1973 1
YR_1974 l
YR_1975 I
YR 1976 1
YR~1977 1
YR_1978 1
YR_1979 l
YR_19B0 1
YR_1981 l
YR_1982 l
YR1983 1
YR_19B4 l
YR_19B5 1
YR_19B6 1
YR__19B7 l
YR~19B8 1
YR_1989 1
YR_1990 l
YR_1991 1
YR_1992 1
YR_1993 1
YR_1994 1
YR_1995 1
YR_1996 1
ANNEARUN 1
BALTIMOR 1
CALVERT 1
CAROLINE 1
CARROLL 1
CECIL 1
CHARLES 1
DORCHEST l
FREDERIC 1
GARRETT 1
HARFORD 1
HOWARD 1
KENT 1
MONTGOME 1
PRINCEGE 1
QUE ENANN 1
STMARYS 1
SOMERSET 1
TALBOT 1
WASHINGT 1
WICOMICO 1
WORCESTB 1
Parameter Estimates
Parameter
Standard
T for HO-
Estimate
Error
Parameter-0
Prob > |T|
3
186858
0
69022704
4
617
0
0001
0
451056
0
05635196
B
004
0.
0001
0
654 949
0
02978043
21
993
0
0001
0
026074
0
07060452
0.
369
0.
.7120
0
059153
0
02157769
2
741
0
0063
0
107143
0
02167440
4
943
0
0001
0
138191
0
02226263
6
207
0
0001
0
109500
0
02353059
8
053
0
0001
0
171356
0
02295066
7
466
0
0001
0
239932
0
02272705
10
557
0
0001
0
269360
0
02332926
11
546
0
0001
0
265461
0
02344640
11
322
0
0001
0.
. 333057
0
02450019
13
594
0
0001
0
320733
0
02431423
13
191
0
0001
0
339552
0
02373337
14
.307
0
0001
0
356174
0
024C336S
14
. 820
0
0001
0
354163
0
02416277
14
.657
0
0001
0
412701
0
02533644
16
289
0
0001
0
427758
0
02781201
15
380
0
0001
0
467300
0
02935604
15
9 IB
0
0001
0
506615
0
0314997£>
16
083
0
0001
0
544246
0
03276460
16.
.611
0
0001
0
561261
0
0240=010
16
469
0
0001
0
570873
0
03477056
16
418
0
0001
0
593067
0
03423487
17
323
0
0001
0
606558
0
03295776
18
4 04
0.
0001
0
597837
0
03281975
18
216
0
0001
0
579623
0
03298670
17
571
0
0001
0
565160
0.
.03380301
16,
.719
0
0001
0
570174
0
03422189
16
661
0
0001
0
582066
0
03478966
16
731
0
0001
0
256983
0
05699665
4
544
0
0001
0
199149
0
07706712
2
584
0
0100
0
051876
0
04750251
1
092
0
2752
-0
016493
0
04542975
-O
407
0
6841
-0
044324
0
02S53509
-1,
,736
0
0831
-0
006687
0
02356280
-0
369
0
712S
0.
f 041599
0
02260309
1
840
0
0662
-0
043245
0
04295294
-1
007
0
3144
0
269628
0
04148748
6
499
0
0001
0
065728
0
03586954
1
832
0
0674
-0
102381
c
02930612
-3
484
0
0005
0
487471
0
03630582
12
726
0.
. 0001
-0
060617
0
05576232
-1
087
0
2775
0.
. 177214
0
07685726
2
306
0
0215
0
234589
0
07953612
2.
.949
0
0033
0
4 55222
0
04645886
9.
798
0
0001
-0
131237
0.
02175300
-6
033
0
0001
0
221009
0
05475512
4
036
0
0001
0
494238
0
05990754
8
250
0
0001
0
183565
0
03060669
5,
.998
0
0001
0
049692
0
02302646
2
158
0
0313
0
294623
0
03862094
7
629
0
0001
-------
HO. _JOLl JNTI— REC "N <
Model- MODEL1
Dependent Variable LOGVMT
Source
Model
Error
C Total
DP
Analysis of Variance
Sum of
Squares
113 1154 34514
1186 5 05253
1299 1159 39768
Mean
Square
10 21544
0 00426
Root MSB
Dep Mean
C V
0 06527
13.48512
0 48401
R-square
Adj R-sq
* RC ILY)
p Value
2397 910
0 9956
0.9952
Prob>P
0 0001
-------
NORTH CAROLINA COUNTIES LOG REGRESSION (PRIMARY ROADS ONLY)
Parameter Estimates
Parameter Standard T for HO
Variable DP
Estimate
Error
Parameter-0
Prob >
1T |
INTERCEP 1
4 852777
0
62191229
7
B03
0
0001
LOGLM 1
0 474944
0
04852260
9
788
0
0001
LOGPOP 1
0 559822
0
05227269
10
710
0
0001
YR_1986 l
-0 020903
0
00923843
-2
263
0
0238
YR_1987 1
0.017598
0
00927066
1.
89S
0
0579
YR_1988 1
0 075987
0
00932504
8
14 9
0
0001
YR_198 9 1
0.131392
0
00939117
13
991
0
0001
YR 1990 1
0 136437
0
00947242
14
404
0.
0001
YR 1991 1
0 168549
0
00962922
17
504
0
0001
YR_1992 1
0 206690
0
00981055
21
068
0
0001
YR 1993 1
0 219318
0
01004797
21
827
0
0001
YR 1994 1
0 251674
0
01040884
24
179
0
0001
YR 1995 1
0 290803
0
01071671
27
136
0
0001
YR_1996 1
0 324428
0
01117022
29
044
0
0001
YR~"l997 1
0 33S543
0
01148593
29
213
0
0001
ALEXANDE 1
-0 454282
0
09392197
-4
837
0
0001
ALLEGHAN 1
-0 774820
0
12955933
-5
980
0
0001
ANSON 1
-0 275994
0
08255505
-3
343
0
0009
ASHE 1
-0 570240
0
08559684
-6
662
0
0001
AVERY 1
-0 067627
0
10706097
-0
627
0
5308
BEAUFORT 1
-0 410198
0
05599194
-7
326
0
0001
BERTIE 1
-0 312929
0
09037027
-3
463
0
0006
BLADEN 1
-0 354567
0
07821693
-4
533
0
0001
BRUNSWIC 1
0 129679
0
04737147
2
737
0
0063
BUNCOMBE 1
0 124432
0
04255731
2
924
0
0035
BURKE 1
0 001483
0
03138571
0
047
0
9623
CABARRUS 1
0 078716
0
02686507
2
930
0
0035
CALDWELL 1
-0 314681
0
03522047
-8
935
0
0001
CAMDEN 1
-0 026414
0
15606318
-0
169
0
8656
CARTERET 1
0 124117
0
04589615
2
704
0
0069
CASWELL 1
-0.588852
0
08872670
-6
637
0
0001
CATAWBA 1
-0 029817
0
02733977
-1
091
0
2757
CHATHAM 1
-0 233364
0
05816269
-4
012
0
0001
CHEROKEE 1
-0 366402
0
08991886
-4
075
0
0001
CHOWAN 1
-0 526179
0
11894727
-4
424
0
0001
CLAY 1
-0 440942
0
15245754
-2
892
0
.0039
CLEVELAN 1
-0 173259
0
03002163
-5
771
0
0001
COLUMBUS 1
-0 375060
0
05431958
-6
.905
0
0001
CRAVEN 1
-0 177340
0
02960896
-5
989
0
.0001
CUMBERLA 1
-0.303618
0
05699074
-5
327
0
0001
CURRITUC 1
0.1410B3
0
10905493
1
294
0
1960
DARE 1
0 358334
0
08563005
4
185
0
0001
DAVIDSON 1
-0 108582
0
03097858
-3
.505
0
.0005
DAVIE 1
0 203304
0
07485969
2
716
0
.0067
DUPLIN 1
-0 268071
0
06115541
-4
383
0
0001
DURHAM 1
0 191450
0
03658848
5
.233
0
0001
EDGECOMB 1
-0 492902
0
04384865
-11
241
0
0001
FORSYTH 1
0 057503
0
05390989
1
067
0
2863
FRANKLIN 1
-0 346201
0
06062868
-5
710
0
0001
GASTON 1
-0 010187
0
03623784
-0
281
0
.7787
GATES 1
-0 361967
0
13014090
-2
781
0
.0055
GRAHAM 1
-0 937659
0
14557531
-6
441
0
0001
GRANVILL 1
0.022450
0
.05901056
0
380
0
.7037
-------
tfORln uwJLIN.. wvW..tIEb laaj rtEGRaoa-iun (PKapiaki ROAlo unliY)
Variable DF
GREENE
GUILFORD
HALIFAX
HARNETT
HAYWOOD
HENDERSO
HERTFORD
HOKE
HYDE
IREDELL
JACKSON
JOHNSTON
JONES
LEE
LENOIR
LINCOLN
MACON
MADISON
MARTIN
MCDOWELL
MECKLENB
MITCHELL
MONTGOKE
MOORE
NASH
NEWHANOV
NORTHAMP
ONSLOW
ORANGE
PAMLICO
PASQUOTA
PENDER
PERQUIMA
PERSON
PITT
POLK
RANDOLPH
RICHMOND
ROBESON
ROCKINGH
ROWAN
RUTHERFO
SAMPSON
SCOTLAND
STANLY
STOKES
SURRY
SWAIN
TRANSYLV
TYRRELL
UNION
VANCE
WAKE
WARREN
WASHINGT
Parameter
Standard
T for HO.
Estimate
Error
Parameter«0
Prob >
• |T|
-0.
322067
0
10359988
-3
109
0
0019
0
015606
0
07086893
0-
220
0
8257
-0
127642
0
04832064
-2
642
0
0084
-0
151904
0
03466217
-4
382
0
0001
0
210910
0
05106389
4
287
0
0001
0
010876
0
03709047
0
293
0
7694
-0
421712
0
08628835
-4
887
0
0001
-0
329239
0
09227203
-3
568
0
0004
-0.
,769543
0
15707353
-4
899
0
0001
0
313124
0
03270748
9
573
0
0001
-0
039605
0.
.07586428
-0
523
0.6010
0
154765
0
04496329
3
442
0
0006
0
083335
0
12978904
0
642
0
5209
-0
066894
0
05998164
-1
. 115
0
26S0
-0
215791
0
04168376
-5
177
0
0001
-0
265999
0
05161626
-5
153
0
0001
-0
297609
0
08260690
-3
603
0
0003
-0
631069
0
09851259
-6
406
0
0001
-0.
.338561
0
07928852
-4
270
0
0001
0
138399
0
06241211
2
218
0
0268
0.
. 142858
0
0B758794
1
631
0
1031
-0.
.550911
0
11038008
-4
991
0
0001
-0.
.154045
0
08332869
-1
849
0
0648
-0
316897
0.
.04012582
-7,
.898
0
0001
0
089492
0
04304191
2
079
0
0378
-0
127B48
0
03007214
-4
251
0
0001
-0
038493
0
08911113
-0
432
0
6658
-0
412699
0
02936072
-14
056
0
0001
0
117156
0
02810739
4.
.168
0
0001
-0.
.350541
0
12512088
-2,
.802
0.
.0052
-0.
.448519
0
07928607
-5
657
0
0001
-0.
.040302
0
07503251
-0.
.537
0
5913
-0.
.2*77707
0
13729138
•2
023
0
0433
-0.
.582866
0
07268394
>8
019
0
0001
-0.
.3827*74
0
03289150
-11
637
0
0001
0
045632
0
10926553
0.
.418
0
6763
-0.
.156691
0
03065072
-s
112
0
0001
-0
352612
0
05341740
-6
601
0
0001
0
009167
0
04134323
0
222
0
B246
-0
253853
0
03272082
-7.
.758
0
0001
-0,
.113342
0
02588007
-4
380
0
0001
-0,
.422249
0
04261152
-9
909
0
0001
-0
242563
0
05452665
-4
449
0
0001
-0
.229340
0
06792183
-3
.377
0
0008
-0
377658
0
04732003
-7
981
0
0001
-0
730350
0
06023559
-12
125
0
0001
0
046308
0
03931930
1
178
0
.2391
-0
234695
0
12257270
-1
915
0.
. 0558
-0
.273623
0
07941144
-3
446
0.
.0006
-0
.516641
0
17B78293
-2
.890
0.
.0039
-0
289758
0
02831952
-10
.232
0
0001
-0
.103256
0
06310383
-1
. 636
0
1020
0
.069966
0
08095530
0
. 864
0
3876
-0
.392074
0
09903389
-3
.959
0.
.0001
-0
222636
0
11339172
-1
.963
0
04 98
-------
NORTH CAROLINA COUNTIES LOG REGRESSION (PRIMARY ROADS ONLY)
Variable DF
WATAUGA
WAYNE
WILKES
WILSON
YADKIN
YANCEY
Parameter
Estimate
-0.130110
-0.357276
-0.243925
-0.027524
0 096216
-0.519649
Standard
Error
0.06486641
0.02621529
0 04015156
0.03774486
0.07106631
0.10549447
T for HO:
Parameter-0
-2.006
-13.629
-6.075
-0.729
1.354
-4.926
Prob
IT |
0.0451
0.0001
0.0001
0.4660
0.1760
0.0001
-------
Model* MODELl
Dependent Variable- LOGVMT
ORT1
lin;
'IBS
SGRi
(PR
Analysis of Variance
Source
Model
Error
c Total
DF
113
1066
1199
Sum of
Squares
1058.73544
4 66152
1063.39696
Mean
Square
9 36934
0.00429
Root MSB
Dep Mean
C V
0.06552 R-square
13 4660B Adj R-sq
0.48653
ROAI '}
P Value Prob>F
2182.786 0 0001
9956
9952
-------
WORTH CAROLINA COUNTIES LOG REGRESSION (PRIMARY ROADS ONLY I
Variable DF
INTERCEP
LOGLM
LOGPOP
LOGPCI98
YR__1986
YR~1987
YR_1900
YR_1989
YR_1990
YR_1991
YR_1992
YR_1993
YR_1994
YR_19 9 S
YR_1996
ALEXANDE
ALLEGHAN
ANSON
ASHE
AVERY
BEAUFORT
BERTIE
BLADEN
BRUNSWIC
BUNCOMBE
BURKE
CABARRUS
CALDWELL
CAMDEN
CARTERET
CASWELL
CATAWBA
CHATHAM
CHEROKEE
CHOWAN
CLAY
CLEVELAN
COLUMBUS
CRAVEN
CUMBERLA
CURRITUC
DARE
DAVIDSON
DAVIE
DUPLIN
DURHAM
EDGECOMB
FORSYTH
FRANKLIN
GASTON
GATES
GRAHAM
Parameter Estimates
Parameter
Standard
T for HO-
Estimate
Error
Parameter»0
Prob > |T|
4
242007
1
03268853
4
108
0
0001
0
434538
0
05420386
8
017
0
0001
0
5B5011
0
06231359
9
388
0
0001
0
056924
0
05940959
0
958
0 .
.3382
-0
023705
0
00974034
~2
434
0
0151
0
013958
0
010144 B3
1
376
0
1691
0
070336
0
01132153
6
213
0
0001
0
124368
0
01231221
10
101
0
0001
0
129553
0
01244942
10
.406
0
0001
0
161899
0
01248450
12
.968
0
0001
0
198603
0
01371256
14
483
0
0001
0
209684
0
01509294
13
.893
0
0001
0
241577
0
01599959
15
099
0
0001
0
279203
0
01746163
15
990
0
0001
0
311663
0
01894133
16
4 54
0
.0001
-0
480652
0
10724600
-4
482
0
0001
-0
737722
0
15529357
-4
751
0
0001
-0
235851
0
.10142226
-2
325
0
0202
-0
528601
0
10464426
-5
051
0
0001
-0
036317
0
12897693
-0
282
0
7783
-0
374608
0
06917426
-S
415
0
0001
-0
262281
0
11336522
-2
314
0
0209
-D
293319
0
09896047
-2
964
0
0031
D
176436
0
06017137
2
932
0
0034
0
138348
0
04706161
2
94 0
0
0034
0.
>018816
0
03672596
0
512
0
6085
0
064857
0
02613524
2
305
0
0213
-0
308292
0
04066845
-7
.581
0
0001
0
.008680
0
18581901
0
047
0
9627
0
145959
D
&S42SQ35
2
697
0
0073
-0
54B266
0.
11091861
-4
943
0
0001
-0.
.038458
0
02937679
-1
309
0
1908
-0
210197
0
06752182
-3.
. 113
0
0019
-0.
.325603
0.
11352492
-2
070
0
0042
-0
509207
0
13951184
-3
650
0,
. 0003
-0
422668
0
18070145
-2
339
0
0195
-0,
.149140
0
03475667
-4
291
0
0001
-0
322477
0
06881165
-4
686
0
0001
-0
160997
0
03434432
-4
688
0
0001
-0
293959
0
06375880
-4
610
0.
.0001
0
186653
0
13019194
1
434
0
1520
0
400691
0.
. 10186082
3
933
0
0001
-0
097033
0
03348358
-2
898
0
0038
0.
, 211979
0
08566064
2
. 47S
0
0135
-0
228323
0
07547469
-3
025
0
0025
0
172240
0
04291114
4
014
0
0001
-0
460266
0
05542280
-8
305
0.
.0001
0
037456
0
06597658
0
568
0
5704
-0
319608
0
07589196
-4
211
0.
0001
-0
008254
0
03982488
-0
207
0
8359
-0
316852
0
15745430
-2.
.012
0
0444
-0
902848
0
17806854
-5
04 8
0
0001
-------
rJORTtt
wvwLINit wwnflES
1AAJ
i\EGRL>jo a mi
(PRiruwi
ROAuo
vnu?)
Parameter
Standard
T for HO
Variable
DF Estimate
Error
Parameter«0
Prob >
|T|
GRAKVILL
1 0
052804
0
07341271
0
719
0.
4721
GREENE
1 -0.
290678
0
12527803
-2
320
0
0205
GUILFORD
1 0
009629
0
08370793
0.
115
0
9084
HALIFAX
1 -0
002676
0
0629B339
-1
313
0
1896
HARNETT
1 -0
124 630
0
04636056
-2
693
0
0072
HAYWOOD
1 0
252748
0
06181919
4
089
0
0001
HENDERSO
1 0
011811
0
04023815
0
294
0
7692
HERTFORD
1 -0
380291
0
10720361
-3
547
0
0004
HOKE
1 -0
308427
0
11496476
-2
683
0.
0074
HYDE
1 -0
705379
0
18933152
-3
726
0
0002
IREDELL
1 0
330902
0
03608671
9
170
0
0001
JACKSON
1 0
00116B
0
09493050
0
012
0
9902
JOHNSTON
1 0
138893
0
05192949
3
637
0
0003
JONES
1 0
125218
0
15409289
0
813
0
4166
LEE
1 -0
065971
0
06799164
-0
970
0
3321
LENOIR
1 -0
195808
0
04955491
-3
951
0
0001
LINCOLN
1 -0
255821
0
05930152
-4
314
0
0001
MACON
I -0
264660
0
09952423
-2
659
0
0079
MADISON
1 -0
560492
0
12253758
-4
803
0
0001
MARTIN
1 -0
299843
0
09770958
-3
069
0
0022
MCDOWELL
1 0
187464
0
07795322
2
405
0
0163
MECKLENB
1 0
112393
0
10573351
1
063
0
2880
MITCHELL
1 -0
517632
0
13277840
-3
898
0
0001
MONTGOME
1 -0
X13S35
0
10313784
-1
101
0
2712
MOORE
1 -0
312524
0
04450906
-7
022
0
0001
NASH
1 0
120954
0
04914709
2
461
0
0140
NEWHANOV
1 -0
136790
0
03213951
-4
256
0
0001
NORTHAMP
1 0
015015
0
11177683
0
134
0
8932
ONSLOW
1 -0
389832
0
03596810
-10
838
0
0001
ORANGE
1 0
099748
0
03080438
3
238
0
0012
PAMLICO
I -0
330769
0
14836699
-2
229
0
0260
PASQUOTA
1 -0
437627
0
09256921
-4
728
0
0001
PENDER
1 0
006288
0
09391180
0
067
0
9466
PERQUIMA
1 -0
262982
0
16281874
-1
615
0
1066
PERSON
1 -0
568641
0
OB659430
-6
567
0
0001
PITT
1 -0
356579
0
03671548
-9
712
0
0001
POLK
1 0
047791
0
12529023
0
381
0
7030
RANDOLPH
1 -0
139951
0
03361630
-4
163
0
0001
RICHMOND
1 -0
329412
0
06673992
-4
936
0
0001
ROBESON
1 0
060568
0
05355921
1
131
0
2584
ROCKINGH
I -0
231901
0
03802996
-6
098
0
0001
ROWAN
1 -0
116841
0
02752108
-4
246
0
.0001
RUTHERFO
1 -0
401741
0
05174368
-7
764
0
0001
SAMPSON
1 -0
202130
0
06675218
-3
028
0
0025
SCOTLAND
1 -0
211651
0
08267358
-2
560
0
0106
STANLY
i -a
370270
0
05545844
-6
677
0
0001
STOKES
1 -0
.713682
0
07218364
-9
887
0
0001
SURRY
1 0
065843
0
04617097
1
426
0
1541
SWAIN
1 -0
193602
0
15209951
-1
273
0
2033
TRANSYLV
1 -0
252570
0
09306142
-2
714
0
0068
TYRRELL
1 -0
459749
0
21397786
-2
14 9
0
0319
UNION
1 -0
279454
0
03139621
-8
901
0
0001
VANCE
1 -0
090941
0
07521120
-1
209
0
2269
WAKE
1 0
058160
0
09661827
0
602
0
5473
WARREN
1 -0
351191
0
12479687
-2
814
0
0050
-------
NORTH CAROLINA COUNTIES LOG REGRESSION (PRIMARY ROADS ONLY)
Variable DP
Parameter
Estimate
-0 200326
-D 11*7204
-0.334311
-0.225160
-0.001913
0.110196
-0.4B4492
Standard
Error
0.13S300S0
0 01B39499
0.03185602
0.04141566
0.04364529
0.0B39B633
0 12896225
T for HO:
Parameter-0
-1.481
-1.495
-10.495
-4.149
-0.181
1.312
-3.151
Prob > |T|
0.1390
0.1352
0.0001
0.0001
0 8562
0.1898
0.0002
-------
Model. M0DEL1
Dependent Variable LOGVMT
PJIA ES GREl
Analysis of Variance
Source
Model
Error
C Total
DF
Sum of
Squares
123 2163.62051
2468 26.70659
2591 2190.32710
Mean
Square
17 59041
0 01082
P Value
1625 559
Prok»F
0.0001
Root MSB
Dep Mean
C V
0 10402 R-square
12 95902 Adj R-sq
0 80272
0 9678
0.9872
-------
VIRGINIA COUNTIES LOG REGRESSION
Parameter Estimates
Parameter Standard T for HO
Variable DP
Estimate
Error
Parameter-0
Prob >
|T|
INTERCEP i
4.
903998
0
24459659
20
049
0
0001
LOGLM 1
0
506314
0
03269729
15
485
0.
0001
LOG POP 1
0
507106
0
01975764
25
666
0
0001
YR_1971 1
0
021943
0
01503921
1
459
0
1447
YR~1972 1
0
078041
0
01507051
5
178
0
0001
YR 1973 1
0
120630
O
01S12123
7
978
0
0001
YR 1974 1
0
077302
0
01519424
5
088
0
0001
YR 1975 1
0
105404
0
01528148
6
B98
0
0001
YR_1976 1
0
147884
0
01535101
9
634
0
0001
YR_1977 l
0
178758
0
01543777
11
579
0
0001
YR 1978 1
0
219655
0
01555828
14
118
0
0001
YR 1979 1
0
219111
0
01564082
14
009
0
0001
YR_1980 1
0
192815
0
01568276
12
295
0
0001
YR_1981 1
0
198945
0
01572768
12
64 9
0
0001
YR 1982 1
0
219414
0
01577647
13
908
0
0001
YR_1903 1
0
251050
0
01580464
15
885
0
0001
YR_1904 1
0
306306
0
01504359
19
333
0
0001
YR 1985 1
0
352296
0
01588993
22
171
0
0001
YR_1986 1
0
410374
0
01594160
25
742
0
0001
YR_1987 1
0
457387
0
01604286
28
510
0
0001
YR 1988 1
0
506266
0
01610099
31
443
0
0001
YR_1989 1
0
525995
0
01618535
32
498
0
0001
YR_1990 1
0
529351
0
01626658
32
542
0
0001
YR 1991 1
0
514269
0
01639924
31
359
0
0001
YR_1992 1
0
561919
0
01654889
33
955
0
0001
YR_1993 1
0
598735
0
01665276
35
954
0
0001
YR 1994 1
0
612382
0
01677854
36
498
0
0001
YR_1995 1
0
627221
0
01689761
37
119
0
0001
YR_1996 1
0
64 9412
0
01698008
38
246
0
0001
ALBEMARL 1
0
150782
0
03409587
4
422
0
0001
ALLEGHAN 1
-0
106481
0
03287207
-3
239
0
0012
AMELIA 1
-0
065855
0
04551381
-1
447
0
1480
AMHERST 1
-0
098310
0
02929621
-3
356
0
0008
APPOMATT 1
-0
124334
0
03951847
-3
146
0
0017
ARLINGTO 1
0
42219B
0
04623780
9
131
0
0001
AUGUSTA 1
0
286944
0
03535339
a
116
0
0001
BATH 1
-0
603252
0
04719268
-12
783
0
0001
BEDFORD 1
-0
153523
0
02960387
-5
.186
0
0001
BLAND 1
0
153885
0
04211595
3
654
0
0003
BOTETOUR 1
0
391678
0
02962423
13
222
0
0001
BRUNSWIC 1
-0
008014
0
03185232
-0
251
0
8016
BUCHANAN 1
-0
210668
0
03247370
-6
487
0
0001
BUCKINGH 1
-0
247424
0
03486051
-7
. 098
0
.0001
CAMPBELL 1
0
012720
0
02932857
0.434
0
6645
CAROLINE 1
0
638889
0
03146182
20
307
0
0001
CARROLL 1
-0
118877
0
02854657
-4
164
0
0001
CHARLES 1
-0
350471
0
05597644
-6
261
0
0001
CHARLOTT 1
-0
383392
0
03376046
-11
356
0
0001
CHESTERF 1
0
185549
0
04211999
4
405
0
0001
CLARKE 1
0
092252
0
.04063267
2
.270
0
.0233
CRAIG 1
-0
962138
0
05303677
-18
141
0
,0001
CULPEPER 1
-0
108313
0
03121287
-3
470
0
, 0005
CUMBERLA 1
-0
457245
0
.04839308
-9
.449
0
0001
-------
IA i.
IS I
res:
Parameter
Standard
T for HO
Variable DP
Estimate
Error
Parameter-0
Prob >
1TI
DICKENSO 1
-0 479202
0
03456219
-13
865
0
0001
DINWIDDI 1
0 103462
O
02966179
3
488
0
0005
ESSEX 1
0 062416
0
04101660
1
522
0
1282
FAIRFAX 1
0 756 385
0.
0660714 9
11.
448
0
0001
FAUQUIER l
0 251002
O
02897124
8.
664
0
0001
FLOYD 1
-0 520774
0
04410606
-11
B07
0
0001
FLUVANNA 1
-0.435221
0
046 03077
-9
455
0
0001
FRANKLIN 1
-0.091032
0
02903257
-3
136
0
0017
FREDERIC 1
0 267018
0
0301073fi
8
869
0
0001
GILES 1
-0 196230
0
03168205
-6
194
0
0001
QLOUCEST 1
0 100062
0
03289075
3
043
0
0024
GOOCHLAN 1
0.331881
0
03336188
9
948
0
0001
GRAYSON 1
-0 672942
0
03186803
-21
117
0
0001
GREEKS 1
0 049417
0
05584599
0
885
0
3763
GREENSVI 1
0 575399
0
04178496
13
770
0
0001
HALIFAX 1
-0 283947
0
03006740
-9
444
0
0001
HANOVER 1
0.422235
0
03112330
13
567
0
0001
HENRICO 1
0 119102
0
04697394
2
535
0
0113
HENRY 1
-0 107632
0
0307286^
-3
503
0
0005
HIGHLAND 1
-0 701376
0
05747350
-12
203
0
0001
ISLEWIGH 1
O 220181
0
03058546
7
199
0
0001
JAMESCTY 1
0 175013
0
03102314
5
641
0
0001
KINGQUEE 1
-0 276252
0
04664787
-5
922
0
0001
KINGGEOR 1
0.145245
0
0360093&
4
034
0
0001
KINGWILL l
-0.272034
0
04508354
-6
034
0
0001
LANCASTE 1
-0 312202
0
04 345171
-7
105
0
0001
LEE 1
-0 319424
0
02957219
-10
802
0
0001
LOUDON 1
0 020630
0
03182479
0
64 8
0
5169
LOUISA 1
0.057002
0
03021003
1
886
0
0594
LUNENBUR 1
-0 724187
0
04113459
-17
605
0
0001
MADISON 1
-0.047370
0
0383384ft
-1
236
0
2167
MATHEWS 1
-0 142093
0
05713166
-2
SOI
0
0124
MECKLENB 1
-0 209084
0
03122S73
-6
696
0
0001
MIDDLESE 1
0 151295
0
04585450
3
299
0
0010
MONTGOME 1
0.003718
0
03169112
2
.642
0
OOB3
NELSON 1
-0 239219
0
03340672
-7
161
0
0001
NEWXENT 2
0 782966
0
03753853
20
058
0
0001
NORTHAMP 1
-0.123872
0
03603723
-3
437
0
0006
NORTHUMB 1
-0.210390
0
04791172
-4
558
0
0001
NOTTOWAY 1
-0.397718
0
03239285
-12
278
0
0001
ORANGE 1
-0.163149
0
03193223
-5
.109
0
.0001
PAGE 1
-0.582768
0
03686181
-15
B10
0
0001
PATRICK 1
-0 512657
0
.03250935
-15
770
0
0001
PITTSYLV I
-0.346190
0
03314163
-10
446
0
0001
POWHATAN 1
-0 293153
0
04106649
-7
136
0
0001
PRINCEED 1
-0 22B481
0
03178104
-7
.189
0
0001
PRINCEGE 1
0 . 324370
0
03177059
10
210
0
0001
PHINCEWJ I
O 360030
0
04 338184
8
299
0
0001
PULASKI 1
-0 049555
0
02951896
-1
679
0
0933
RAPPAHAN 1
-0.406489
0
.04264531
-9
.532
0
0001
RICHMOND 1
0.0423B5
0
05165076
0
.821
0
.4119
ROANOKE 1
0 338431
0
03349456
10
104
0
0001
ROCKBRID 1
0 4 00324
0
03501542
11
433
0
OCOl
ROCKINGH 1
0 023925
0
03383805
0
707
0
4796
RUSSELL 1
•0 101938
0
02844604
-3
.584
0
0003
-------
VIRGINIA COUNTIES LOG REGRESSION
Parameter
Standard
T for HO;
Variable
DP
Estimate
Error
Parameter-0
Prob > |T|
SCOTT
1
-0.239434
0.02878356
-8.318
0.0001
SHENANDO
1
0.212041
0 02925246
7,249
0.0001
SMYTH
1
-0.140626
0.02838379
-4.954
0.0001
SOUTHAMP
1
-0.001724
0.03092376
-0.056
0.9556
SPOTSYLV
1
0.531219
0.02906545
18.277
0 0001
STAFFORD
1
0 653263
0.03063177
21.326
0.0001
SURRY
1
-0.362771
0.05157083
-7.034
0.0001
SUSSEX
1
0 482467
0.03511206
13.741
0.0001
TAZEWELL
1
-0 322491
0.02967195
-10.869
0.0001
WARREN
1
-0.217397
0 03733369
-5.823
0.0001
WASHINGT
1
0.076901
0.03007988
2.557
0.0106
WBSTHORE
1
-0.82004B
0.03230010
-25.388
0.0001
WISE
1
-0.313518
0.02889791
-10.849
0.0001
WYTHE
1
0.628983
0.03415531
18 .415
0.0001
YORK
1
0.328916
0.03195773
10.292
0.0001
SUFFOLK
1
0.107918
0.02988425
3 .611
0.0003
-------
Model; MODEL1
Dependent Variable. LOGVMT
NIA ..»IBS ..JGRE
Analysis of Variance
Source
Model
Error
C Total
DF
Sum o£
Squares
124 2163 73405
2467 26 59305
2S91 2190 32710
Mean
Square
17 44947
0 01078
Root MSB
Dep Mean
C V.
0 10362
12 95902
0 80117
R-square
Adj R-sq
F Value
1618.763
Prob>F
0*0001
0 9879
0 9872
-------
VIRGINIA COUNTIES LOG REGRESSION
Parameter Estimates
Parameter
Standard
T for HO-
Variable DF
Estimate
Error
Parameter-0
Prob >
1T |
INTERCEP l
3
891537
0
39612725
9
824
0
0001
LOGI/«5 1
0
508289
0
03264000
IS
573
0
0001
LOGPOP 1
0
504424
0
01973690
25.
557
0
0001
LOGPCI98 I
0
110210
0
03395794
3
245
0
0012
YR_1971 1
0
019124
0
01503536
1
272
0
2035
YR~1972 1
Q
066768
0
01543734
4
325
0
0001
YR 1973 1
0
102396
0
01610389
6
358
0
0001
YR 1974 1
0
059923
0
0160B257
3
726
0
0002
YR_1975 1
0
039929
0
01598002
5
628
0
0001
YR 1976 1
0
127535
0
01655478
7
704
0
0001
YR 1977 l
0
155900
0
01695418
9
189
0
0001
YR 1970 l
0
191140
0
01784163
10
713
0
0001
YR 1979 1
0
190708
0
01789657
10
656
0
0001
YR 19S0 1
0
165910
0
01771228
9
367
0
0001
YR 1981 1
0
171537
0
01782490
9
623
0
0001
YR 1982 1
0
192914
0
01773716
10
876
0
0001
YR~1983 1
0
220066
0
01843315
11
935
0
0001
YR 1984 1
0
267600
0
01980627
13
511
0
0001
YR 1985 1
0
311250
0
02028469
15
344
0
0001
YR_19B6 1
0
364516
0
02127926
17
130
0
0001
YR 1987 1
0
409649
0
02174269
ie
841
0
0001
YR 1988 1
0
456034
0
02231145
20
439
0
0001
YR 1989 1
0
473S99
0
02283837
20
737
0
0001
YR 1990 1
0
478434
0
02257693
21
191
0
0001
YR 1991 1
0
465978
0
02212010
21
066
0
0001
YR_1992 1
0
512368
0
02249266
22
779
0
0001
YR 1993 1
0
548312
0
02275140
24
100
0
0001
YR 1994 1
0
559764
0
02330956
24
015
0
0001
YR_1995 1
0
573436
0
02364486
24
252
0
0001
YR 1996 1
0
594937
0
02365266
24
942
0
0001
ALBEMARL 1
0
115910
0
0356B527
3
248
0
0012
ALLEGHAN 1
-0
112438
0
03286005
-3
422
0
0006
AMELIA 1
-¦o
0675.85
0
04 542928
-1
4B8
0
1370
AMHERST 1
-0
090437
0
02934 025
-3
0B2
0
0021
A?PCMATT 1
-0
126513
0
03944808
-3
207
0
0014
ARLINGTO 1
a
338038
0
05293533
6
386
0
0001
AUGUSTA 1
0
268546
0
03573777
7
514
0
0001
BATH 1
-0
624279
0
04754528
-13
130
0
0001
BEDFORD 1
-0
171587
0
03006656
-5
707
0
0001
BLAND 1
0
167863
0
04225493
3
973
0
0001
BOTETOUR 1
0
376176
0
02995054
12
560
0
0001
BRUNSWIC 1
0
004311
0
03205662
0
134
0
8930
BUCHANAN 1
-0
213942
0
03242685
-6
598
0
0001
BUCKINGH 1
-0
232868
0
03508128
-6
.638
0
0001
CAMPBELL 1
-0
C06277
0
02985161
-0
210
0
8335
CAROLINE 1
0
629912
0
031522$5
19
993
D
0001
CARROLL 1
-0
105564
0
02878537
-3
667
0
0003
CHARLES 1
-0
353603
0
055B7698
-6
328
0
0001
CHARLOTT 1
-0
373313
0
03383826
-11
.032
0
0001
CHESTERF 1
0
139671
0
04435197
3
14 9
0
0017
CLARKE 1
0
056445
0
04202843
1
34 3
0
1794
CRAIG 1
-0
959358
0
05294156
-18
121
0
0001
CULPEPER 1
-0
128283
0
03175460
-4
040
0
0001
-------
.YIA
.-3REI
Variable DP
CUKBERLA
DICKENSO
DINWIDDI
ESSEX
FAIRFAX
FAUQUIER
FLOYD
FLUVANNA
FRANKLIN
FREDERIC
GILES
GLOUCEST
GOOCHLAN
GRAYSON
GREENE
GREENSVI
HALIFAX
HANOVER
HENRICO
HENRY
HIGHLAND
ISLEWIGH
JAMESCTY
KINGQUEE
KINGGEOR
KINGWILL
LAN CASTE
LEE
LOUDON
LOUISA
LUNENBUR
MADISON
MATHEWS
MECKLENB
MIDDLESE
MONTGOME
NELSON
NEW KENT
NORTHAMP
NORTHUMB
NOTTOWAY
ORANGE
PAGE
PATRICK
PITTSYLV
POWHATAN
PRINCEED
PRINCEGE
PRINCEWI
PULASKI
RAPPAHAN
RICHMOND
ROANOKE
ROCKBRID
ROCKINGH
Parameter
Estimate
-0 448047
-0 483307
0 090172
0 056289
0 686269
0 201156
-0 513895
*0 440139
-0 091461
0 245S16
-0.197607
O 080524
0 288913
-0 659185
0 053318
0 581644
-0 279351
0 384212
0 070288
-0 120557
-0.701709
0 201911
0 142379
-0 285294
0 105915
-0 300691
•0 348842
-0 294875
-0 033306
0 044635
-0 712702
-0 043723
-0 167340
-0 208047
0 128407
0 092233
-0 235839
0 753520
-0 117153
-0 238095
-0 400317
-0 182246
-0 584082
-0 510212
-0 352444
-0 302253
-0 214573
0 323337
0 330905
-0 045803
-0 428106
0 036420
0 304952
0 400302
0 014036
Standard
Error
0 04836296
0.034518B2
0 02988653
0.04098111
0 06939297
03274133
04407212
04596711
02B97696
.03077108
03162468
03337593
03583306
0. 03208786
0.05575140
0 04174887
0.03004290
0 03319917
04923693
03092700
05736291
03104127
03255512
04664133
03755244
04585484
04481338
03046914
03584836
03039962
0.04120760
0 03828115
0 05751705
O 03116724
0.04630635
0 03173871
0 03335865
0 03854918
0.03602736
0 04820334
03234038
.03240942
03679305
03245549
03313390
04108320
03200799
03171086
04421846
02948479
04308120
05158405
03498546
03494799
03390868
T for HO
meter-0
Prob >
1 T |
-9
260
0.
0001
-14
001
0
0001
3
017
0
0026
1
374
0
1697
9
890
0.
0001
6
144
0
0001
-11
660
0
0001
-9.
.575
0
0001
-3
156
0.
0016
7
979
0.
.0001
-6
.249
0
0001
2
.413
0
0159
8
063
0,
.0001
-20
543
0
0001
0
956
0
3390
13
932
0
0001
-9
.298
0
0001
11
.573
0
0001
1
.426
0
1535
-3
.898
0
0001
-12
233
0
0001
6
505
0
0001
4
373
0
0001
-6
117
0
0001
2
927
0
0035
-6
557
0
0001
-7
784
0
0001
-9
678
0
0001
-0
.929
0
3529
1
.468
0
1422
-17
295
0
0001
-1
142
0.
.2535
-2
909
0
0037
-6
675
0
0001
2
773
0.
.0056
2
906
0
0037
-7
070
0
0001
19
547
0
0001
-3
252
0
0012
-4
939
0
0001
-12
378
0
0001
-5
623
0
0001
-15
875
0
0001
-15
720
0
.0001
-10
637
0
0001
-7
357
0
0001
-6
704
0
0001
10
.198
0
0001
7
483
0
0001
-1
553
0
1204
-9
937
0
0001
0
.706
0
4802
6
717
0
0001
11
4 54
0
0001
0
415
0
6779
-------
VIRGINIA COUNTIES I/X5 REGRESSION
Parameter
Standard
T for HO;
Variable
DF
Estimate
Error
Parameter°o
Prob > |T|
RUSSELL
1
-0.090558
0. 02B6Q697
-3.166
0.0016
SCOTT
1
-0.222263
0 02921125
-7.609
0.0001
SHENANDO
1
0 195317
0 - 02964736
6.588
0.0001
SMYTH
1
-0.131771
0 02846516
-4.629
0.0001
SOUTHAMP
1
-0.003987
0.030B77Q8
-0.129
0 8973
SPOTSYLV
1
0.502514
0.03032785
16.569
0.0001
STAFFORD
1
0 623017
0.03154692
19.907
0.0001
SURRY
1
-0.359599
0.05148079
-6.985
0.0001
SUSSEX
1
0.477271
0.03508099
13.605
0 0001
TAZEWELL
1
-0 326918
0.02964622
-11.027
0.0001
WARREN
X
-0.234242
0 03762155
-6.226
0 0001
WASHINGT
1
0 074176
0.03003370
2.470
0.0136
WESTMORE
1
-0.S28030
0.03233157
-25 611
0.0001
WISE
1
-0.323275
0.02899852
-11.148
0.0001
WYTKS
1
0.630549
0.034 09341
18.498
0.0001
YORK
1
0.295302
0.03353560
0.806
0 0001
SUFFOLK
1
0.092717
0.03019218
3.071
0.0022
-------
IjTIMuiVX* Ou3URIji3
REG,
iwN — mi n^JT W/i
uC
Model: M00EL1
Dependent Variable: LOGVMT
Source
Model
Error
C Total
DF
43
388
431
Analysis of Variance
Sum of
Squares
392 60684
1.96868
394 57552
Mean
Square
9 13039
0 00507
Root MSE
Dep Mean
C V.
0.07123
14 76357
0 48248
R-square
Adj R-sq
F Value
1799 475
0.9950
0 9945
Prob>F
0.0001
Parameter Estimates
Parameter Standard T for HO
Variable DF
Estimate
Error
Parameter-0
Prob > |T|
INTERCEP 1
6
091677
0
44669831
13
637
0
0001
LOGLM 1
0
331473
0
05370070
6
173
0
0001
LOGPOP 1
0
517561
0
03045897
16
992
0
0001
ANNEARUN 1
0
240031
0
0709*3928
3
382
0
0008
ARLINGTO 1
0
008511
0
02543845
0
335
0
7381
BALTIMOR 1
0
298375
0
0905*3449
3
294
0
0011
CARROLL 1
-0
322518
0
03759505
-8
579
0
0001
CALVERT 1
-0
424018
0
04B64306
~8
717
0
0001
CHARLES 1
-0
263211
0
04629554
-5
685
0
0001
FAIRFAX 1
0
482998
0
05455135
8
854
0
0001
FAUQUIER 1
-0
062849
0
04 957812
-1
268
0
2057
FREDERIC 1
0
091325
0
06726887
1
358
0
1754
HARFORD 1
-0
299494
0
04 541410
-6
595
0
0001
HOWARD 1
0
274655
0
04467076
6
14 8
0
0001
LOUDON 1
-0
316845
0
03430075
-9
237
0
0001
MONTGOME 1
0
266135
0
08598282
3
118
0
0020
PRINCEGE 1
0
343413
0
09297815
3
693
0
0003
STAFFORD 1
0
267465
0
04467290
5
987
0
0001
YR 1971 1
0
057373
0
02524995
2
272
0
0236
YR_1972 1
0
0982B3
0
02533836
3
879
0
0001
YR_1973 1
0
149865
0
02546889
5
884
0
0001
YR~1974 1
0
096227
0
02569201
3
745
0
0002
YR_1975 1
0
126089
0
02588873
4
870
0
0001
YR_1976 1
0
187814
0
0260B456
7
200
0
0001
YR 1977 1
0
225404
0
02631266
8
566
0
0001
YR 1978 1
0
.259228
0
02662892
9
735
0
0001
YR_1979 1
0
218323
0
02693220
8
106
0
0001
YR_1980 1
0
.230214
0
02724825
8
449
0
0001
YR~~1981 1
0
243661
0
02752056
8
854
0
0001
YR_1982 1
0
240435
0
02777133
8
658
0
0001
YR 1983 1
0
313045
0
02801370
11
175
0
0001
YR_1984 1
0
347244
0
02836128
12
244
0
0001
YR_1985 1
0
411246
0
02873182
14
313
0
0001
YR~1986 1
0
459197
0
02935065
15
645
0
0001
YR~"l987 1
0
504231
0
03011369
16
744
0
0001
YR 1988 1
0
537744
0
03064527
17
547
0
0001
YR 1989 1
0
561535
0
03117281
18
014
0
0001
YR 1990 1
0
582731
0
03169154
18
388
0
0001
YR_1991 1
0
609667
0
03226303
18
897
0
0001
YR 1992 1
0
607976
0
03297155
18
439
0
0001
YR 1993 1
0
618756
0
03335504
18
551
0
0001
YR 1994 1
0
640312
0
03381607
18
935
0
0001
YR 1995 1
0
641755
0
03440016
18
656
0
0001
YR 1996 1
0
655864
0
03486786
18
810
0
0001
-------
DC BALTIMORE SUBURBS LOG REGRESSION - WITHOUT WASH DC
Model MODEL!
Dependent Variable. LOGVMT
Source DF
Model 44
Error 3 87
C Total 431
Analysis of Variance
Sum of Mean
Squares Square
392.62437 8 92328
1 9S11S 0.00504
394.57552
P Value Prob>p
1769 887 0 0001
Root MSE 0.07101 R-square 0 9951
Dep Mean 14 7S3S7 Adj R-Sq 0 9945
C V. 0 48035
Parameter Estimates
Variable DF
Parameter
Estimate
Standard
Error
T for HO-
Parameters
Prob > |T|
INTERCEP 1
4
602672
0
87700204
5
339
0
0001
LOGLM 1
0
326651
0
05359247
6
095
0
0001
LOG POP l
0
502314
0
03144371
15
975
0
0001
LOGPCI90 1
0
166996
0
08954066
1
865
0
0630
ANNEARUN 1
0
240367
0
07075395
3
397
0
0008
ARLINGTO 1
-0
077107
0
05244038
-1
470
0
1423
BALTIMOR 1
0
291970
0
09035198
3
231
0
0013
CARROLL 1
-0
335439
0
03011075
-8
802
0
0001
CALVERT 1
-0
452316
0
05000784
-8
903
0
0001
CHARLES 1
-0
262036
0
04615272
-S
678
0
0001
FAIRFAX 1
0
441057
0
05804537
7
495
0
0001
FAUQUIER 1
-0
109000
0
05527051
-1
972
0
0493
FREDERIC 1
0
092552
0
06705634
1
380
0
1683
HARFORD 1
-0
299937
0
04527041
-6
625
0
0001
HOWARD l
0
225294
0
05180155
4
349
0
0001
LOUDON 1
-0
364042
0
04253911
-8
558
0
0001
MONTGC'ME 1
0
214271
0
09044552
2
369
0
0183
PRINCEGE l
0
361724
0
09320130
3
881
0
0001
STAFFORD 1
0
257180
0
044 87120
5.
732
0
0001
YR 19?1 1
0
€50642
0
02542712
1
992
0
0471
YR_1972 1
0
083213
Q
02651911
3
136
0
0018
YR 1973 1
0
127607
0
02803538
4
555
0
0001
YR 1974 1
0
077033
0
02760129
2
791
0
0055
YR 1975 1
0
109979
0
02721404
4
041
0
0001
YR_1976 1
0
166023
0
02850672
5
824
0
0001
YR 1977 1
0
201192
0
02926655
6
874
0
0001
YR_1978 1
0
228834
0
03114053
7
347
0
0001
YR 1979 1
0
188002
0
03138637
5
990
0
0001
YR_1980 1
0
200179
0
03157767
6
339
0
0001
YR_198l 1
0
212854
0
03202239
6
647
0
0D01
YR 19B2 1
0
209036
0
0324 0055
6
452
0
0001
YR_19B3 1
0
273926
0
03492574
7
843
0
0001
YR~1984 1
0
299141
0
03827017
7
817
0
0001
YR_1985 1
0
356610
0
04097093
0
704
0
0001
YR 1986 1
0
398190
0
04308844
9
073
0
0001
YR_1987 1
0
439465
0
04590447
9
573
0
0001
YR 1980 1
0
468949
0
04709601
9
791
0
0001
YR 1989 1
0
490856
0
04901023
10
015
0
0001
YR_199Q 1
0
515320
0
04B00674
10
734
0
0001
YR 1991 1
0
547422
0
04635020
11
811
0
0001
YR_1992 1
0
546353
0
04660644
11
723
0.
0001
YR 1993 1
0
555932
0
04733246
11
745
0
0001
YR_1994 1
0
575704
0
04833704
11
910
0
0001
YR~1995 1
0
575742
0
0492B408
11
682
0
0001
YR 1996 1
0
588936
0
04995964
11
708
0
0001
------- |