HIGHWAY OPERATIONS SPENDING AS A CATALYST FOR JOB GROWTH

Prepared for

Federal Highway Administration

Department of Transportation

**Prepared by**

## MacroSys Research and Technology

**Washington, DC**

## July 18, 2003

# Executive Summary

The creation of jobs is a major benefit of highway infrastructure
spending. Many models have been developed to estimate the number of jobs
created by spending on highway construction projects. In contrast,
spending on highway operations receives far less attention, even though
operations and maintenance have become relatively more important than
construction since the Interstate system was (largely) completed. The
number and nature of jobs created by spending on highway operations
differs significantly from jobs created by new construction. Each type
requires a different skill set and has a unique pay scale. A model that
projects the level of employment generated by highway operations funding
is needed. This new model will provide policymakers with employment
forecasts specific to highway operations projects, as distinct from
construction projects.

The research presented in this report provides such a model, based on
the Transportation Satellite Accounts. Many sources of data were
analyzed to develop the spending levels, employment structure, and
average employee compensation for major categories of highway operations
activities. The model's employment estimate includes direct hires in
highway operations and indirect employment through purchases of
commodities and services supporting highway operations.

In 2000, highway operations spending accounted for more than 15 percent
of total expenditures on state-administered highways, generating a total
of 184,854 full-time job equivalents. This equaled 17,810 jobs per
billion dollars spent, on average. Traffic supervision, toll collection,
and snow and ice removal were the three largest job-creating activities
associated with highway operations. Together, they accounted for about
65 percent of all jobs created by highway operations spending.

**Comparison of Employment Effects in Highway Operations and**

**Construction (full-time job equivalents per billion dollars\*)**

+---------------+----------+----------------+-----------+-----------+
|               | Highway  | Highway        | Highway   | JOBMOD    |
|               | Op       | Construction   | Con       |           |
|               | erations | (FHWA)         | struction | (Ve       |
|               |          |                | (BLS)     | rsion1.1) |
+---------------+----------+----------------+-----------+-----------+
| Direct        | 12,231   | 7,250          | NA        | NA        |
| employment    |          |                |           |           |
+---------------+----------+----------------+-----------+-----------+
| Indirect      | 5,579    | 18,080         | NA        | NA        |
| employment    |          |                |           |           |
+---------------+----------+----------------+-----------+-----------+
| Total         | 17,810   | 25,330         | 16,298    | 21,219    |
| employment    |          |                |           |           |
+---------------+----------+----------------+-----------+-----------+

Source: U.S. Department of Transportation, Federal Highway
Administration and U.S. Department of Labor, Bureau of Labor Statistics.
JOBMOD is a software program that estimates the economic impact of
highway construction.

\*All estimates are based on 2000 dollars, except for those from JOBMOD,
for which the information for a specific year cannot be found in the
materials available.

HIGHWAY OPERATIONS SPENDING AS A CATALYST FOR JOB GROWTH

The creation of new jobs is a benefit of highway infrastructure
investment. Economic models have been developed to estimate the number
and type of jobs created by highway construction spending both directly
(through contracts for construction labor and materials,) and indirectly
(through increased spending by hired labor and productivity gains to
society resulting from a new transportation facility.[^1]) To date,
however, no models exist that estimate job creation resulting from
spending on operations, except as a minor component of new construction.
To fill this important void, the Federal Highway Administration (FHWA)
sponsored research to develop a new model that will estimate the number
and types of jobs created through highway operations expenditures.

This paper summarizes the results of research done in this vein.
Specifically, the paper describes the structure of the new model,
discusses the model's data requirements, and explains the key steps
needed to process the required data.

**Research Results**

The number and types of jobs created through operations spending differ
significantly from those created through new construction (Appendix A).
Specifically, operations jobs are often more electronics based, less
dependent on the use of heavy equipment, and more labor intensive than
are construction jobs. The skill set required of staff working at a
traffic operations center open 24 hours a day, 7 days a week, is
fundamentally different from that required of a road construction crew.
Moreover, significant disparities in the number and type of jobs created
per level of expenditure will result in a substantially different ratio
of payroll to expenditures.

Operations expenditures on state-administered highways were
approximately \$10.4 billion in 2000, or 15.26 percent of total highway
spending (Table 1).

Table 1. Highway Operations Expenditure for State-Administered Highways

+----------------------------------------+--------------+--------------+
|                                        | Expenditure  | Percentage   |
|                                        |              | Of Total     |
|                                        | (Thousands   | Highway      |
|                                        | of Dollars)  | Expenditure  |
+========================================+==============+==============+
| **Capital outlay**                     | [44,069,138] | 70.44%       |
|                                        | {.underline} |              |
+----------------------------------------+--------------+--------------+
| Acquisition of right-of-way            | 3,115,876    |              |
+----------------------------------------+--------------+--------------+
| Preliminary and construction           | 6,470,094    |              |
| engineering                            |              |              |
+----------------------------------------+--------------+--------------+
| Highway construction and system        | 34,483,168   |              |
| preservation                           |              |              |
+----------------------------------------+--------------+--------------+
| **Physical Maintenance**               | [8,945,942]  | 14.30%       |
|                                        | {.underline} |              |
+----------------------------------------+--------------+--------------+
| **Highway Operations Expenditure**     | [9,543,848]  | 15.26%       |
|                                        | {.underline} |              |
+----------------------------------------+--------------+--------------+
| Traffic control operations             | 939,604      |              |
+----------------------------------------+--------------+--------------+
| Snow and ice removal                   | 1,139,028    |              |
+----------------------------------------+--------------+--------------+
| Other services                         | 479,972      |              |
+----------------------------------------+--------------+--------------+
| Toll collection facility               | 1,289,969    |              |
+----------------------------------------+--------------+--------------+
| Traffic supervision                    | 4,243,549    |              |
+----------------------------------------+--------------+--------------+
| Highway safety and driver education    | 706,608      |              |
+----------------------------------------+--------------+--------------+
| Vehicle inspection and vehicle size    | 744,918      |              |
| and weight enforcement                 |              |              |
+----------------------------------------+--------------+--------------+
| [Total expenditure of capital outlay,  | [62,558,928] | 100%         |
| physical maintenance, and highway      | {.underline} |              |
| operations]{.underline}                |              |              |
+----------------------------------------+--------------+--------------+
|                                        |              |              |
+----------------------------------------+--------------+--------------+
| [Total general administration and      | [5,473,540]  |              |
| research & planning]{.underline}       | {.underline} |              |
+----------------------------------------+--------------+--------------+
| General administration                 | 4,669,474    |              |
+----------------------------------------+--------------+--------------+
| Research and planning                  | 804,066      |              |
+----------------------------------------+--------------+--------------+
|                                        |              |              |
+----------------------------------------+--------------+--------------+
| [General administration and research   | [835,262]    | \*           |
| for highway operations]{.underline}    | {.underline} |              |
+----------------------------------------+--------------+--------------+
| General administration expenses        | 712,562      | \*           |
+----------------------------------------+--------------+--------------+
| Research and planning                  | 122,700      | \*           |
+----------------------------------------+--------------+--------------+

Data Source: U.S. Federal Highway Administration (2001) *Highway
Statistics 2000*, page IV-56. Washington, D.C.: U.S. Department of
Transportation.

\*Note: General administration and Research & Planning expenses for
highway operations are separated from their total expenses based on the
share of highway operations in the total expenditure of capital outlay,
physical maintenance, and highway operations.

As shown in Table 2**,** expenditures on highway operations in 2000
generated 184,854 full-time job equivalents (hereafter referred to as
jobs). This translates to 17,810 jobs per billion (2000) dollars spent
on average.

Table 2. Summary of the Analysis of the Employment Impact of Highway
Operations (full-time job equivalents)

  ---------------- -------------- -------------- --------- ------------ ------------ ------------
                   Total Spending Average Annual Direct    Employment   Total        Employment
                   (\$1,000)      Employee       Hiring    Impact from  Employment   Per Billion
                                  Compensation             spending on  Impact       Dollars
                                                           materials                 
                                                           and services              

  Highway and                                                                        
  traffic services                                                                   

  Traffic control  \$939,604      \$69,940       7,066     5,995        13,061       13,901
  operations                                                                         

  Snow and ice     \$1,139,028    \$36,886       17,510    2,936        20,446       17,950
  removal                                                                            

  Other services   \$479,972      \$32,376       9,029     1,593        10,622       22,130

  Toll collection  \$1,289,969    \$52,244       15,145    5,876        21,021       16,296
  facility                                                                           

  Administration                                                                     
  and research                                                                       

  General          \$712,562      \$50,555       8,337     5,186        13,523       18,978
  administration                                                                     

  Research and     \$122,700      \$68,432       779       829          1,608        13,105
  planning                                                                           

  Highway law                                                                        
  enforcement and                                                                    
  safety                                                                             

  Traffic          \$4,243,549    \$57,331       51,260    27,240       78,500       18,499
  supervision                                                                        

  Highway safety   \$706,808      \$41,195       6,633     5,072        11,705       16,560
  and driver                                                                         
  education                                                                          

  Vehicle          \$744,918      \$41,315       11,191    3,177        14,368       19,288
  inspection and                                                                     
  vehicle size and                                                                   
  weight                                                                             
  enforcement                                                                        

  Total            \$10,379,110                  126,950   57,904       184,854      17,810
  ---------------- -------------- -------------- --------- ------------ ------------ ------------

Traffic supervision accounted for the largest share (42.5 percent) of
newly created highway operations jobs, followed by toll collection (11.4
percent), and snow and ice removal (11.1 percent). These three
activities accounted for about 65 percent of the total jobs created as a
result of spending on highway operations. A detailed breakdown of
employment by activity and industry is provided in Table 3.

Table 3. Employment Impact of Highway Operations by Activity and
Industry (full-time job equivalents)

  ---------------- --------- --------- ---------- --------- ---------------- ---------- ------------- --------- ------------ -------
                   Traffic   Snow and  Other      Toll      General          Research   Traffic       Highway   Vehicle      Total
                   Control   Ice       Services   Highway   Administration   and        Supervision   Safety    Inspection   
                             Removal                                         planning                                        

  Agricultural,    33        12        112        51        19               5          16            24        15           287
  forestry, and                                                                                                              
  fishery services                                                                                                           

  Metallic ores    4         14        1          5         1                0          1             1         1            28
  mining                                                                                                                     

  Coal mining      4         6         1          21        6                1          2             4         2            48

  Crude petroleum  18        110       27         116       28               4          12            39        109          464
  and natural gas                                                                                                            

  Nonmetallic      4         67        8          45        4                1          3             3         5            140
  minerals mining                                                                                                            

  Construction     92        59        53         1,513     162              18         29            99        256          2,281

  Fabricated metal 91        39        30         123       25               7          136           58        27           537
  products and                                                                                                               
  transportation                                                                                                             
  equipment                                                                                                                  

  Food and kindred 9         23        4          7         16               2          28            9         9            107
  products                                                                                                                   

  Tobacco products 0         0         0          0         0                0          1             0         0            1

  Textile and      13        10        11         51        15               3          37            13        7            159
  apparel products                                                                                                           

  Lumber and wood  32        17        13         177       22               8          12            35        33           350
  products                                                                                                                   

  Furniture and    2         1         0          2         0                0          1             2         1            10
  fixtures                                                                                                                   

  Paper products   59        33        16         29        16               33         32            110       19           347

  Printing and     191       29        34         50        35               99         24            640       109          1,211
  publishing                                                                                                                 

  Chemicals and    36        892       71         140       25               10         58            33        19           1,282
  allied products                                                                                                            

  Petroleum        5         23        8          40        8                1          2             12        42           139
  refining and                                                                                                               
  related products                                                                                                           

  Rubber and       78        48        19         94        16               8          169           47        19           499
  miscellaneous                                                                                                              
  plastics                                                                                                                   
  products                                                                                                                   

  Footwear,        1         0         0          1         1                0          48            4         0            56
  leather, and                                                                                                               
  leather products                                                                                                           

  Stone, clay, and 30        349       6          106       13               6          17            11        17           555
  glass products                                                                                                             

  Primary metal    77        33        12         86        13               3          20            23        16           283
  industries                                                                                                                 

  Industrial       506       46        20         219       25               13         35            41        22           927
  machinery and                                                                                                              
  equipment                                                                                                                  

  Electronic and   571       17        21         114       20               10         31            42        22           849
  other electric                                                                                                             
  equipment                                                                                                                  
  ---------------- --------- --------- ---------- --------- ---------------- ---------- ------------- --------- ------------ -------

Table 3. Employment Impact of Highway Operations by Activity and
Industry (full-time job equivalents), cont.

  ---------------- --------- --------- ---------- --------- ---------------- ---------- ------------- --------- ------------ ---------
                   Traffic   Snow and  Other      Toll      General          Research   Traffic       Highway   Vehicle      Total
                   Control   Ice       Services   Highway   Administration   and        Supervision   Safety    Inspection   
                             Removal                                         planning                                        

  Instruments and  24        9         4          12        11               3          18            19        5            105
  related products                                                                                                           

  Miscellaneous    12        5         3          21        8                2          17            33        7            107
  manufacturing                                                                                                              

  Railroad,        44        44        47         102       22               8          35            46        38           386
  pipelines, state                                                                                                           
  and local                                                                                                                  
  transit, and                                                                                                               
  transportation                                                                                                             
  services                                                                                                                   

  Motor freight    76        124       72         146       29               15         44            89        33           629
  transportation                                                                                                             
  and warehousing                                                                                                            

  Water            3         4         2          5         3                1          17            6         2            42
  transportation                                                                                                             

  Air              76        20        93         27        18               13         16            52        76           391
  transportation                                                                                                             

  Communications   159       19        29         65        25               12         49            150       73           580

  Electric, gas,   37        60        14         182       38               6          22            43        22           424
  and sanitary                                                                                                               
  services                                                                                                                   

  Wholesale trade  514       241       207        327       79               41         138           222       198          1,966

  Retail trade     106       24        19         253       33               8          13            99        50           605

  Finance          136       41        49         196       48               13         56            111       86           736

  Insurance        36        19        31         108       7                5          23            47        144          420

  Real estate      66        17        25         27        9                16         13            95        86           353

  Hotels and       130       41        33         52        14               18         189           107       184          769
  lodging places                                                                                                             

  Personal and     38        14        11         15        16               4          13            25        10           145
  repair services                                                                                                            
  (except auto)                                                                                                              

  Business         2,199     329       368        1,161     238              336        291           2,225     1,155        8,303
  services                                                                                                                   

  Eating and       150       42        39         54        -24\*            19         140           115       179          715
  drinking places                                                                                                            

  Automotive       61        20        43         28        13               7          118           49        15           353
  repair and                                                                                                                 
  services                                                                                                                   

  Amusements       48        12        15         19        -8\*             5          12            213       40           357

  Health services  1         1         1          2         -387\*           1          2             3         2            -375

  Educational and  221       23        21         83        -238\*           63         84            71        26           355
  social services,                                                                                                           
  and membership                                                                                                             
  organizations                                                                                                              

  General          0         0         0          0         4,766            0          25,214        0         0            29,979
  government                                                                                                                 
  industry                                                                                                                   

  **Direct hire**  7,066     17,510    9,029      15,145    8,337            779        51,260        6,633     11,191       126,950

  **Total**        13,061    20,446    10,622     21,021    13,523           1,608      78,500        11,705    14,368       184,854
  ---------------- --------- --------- ---------- --------- ---------------- ---------- ------------- --------- ------------ ---------

\*Note: Negative numbers indicate that the services of these industries
are provided rather than purchased by general government industry, which
is used as a proxy for general administration for highway operations.
Then, a negative employment impact is generated.

In terms of jobs created per billion dollars spent, the "Other Services"
category ranked the highest. "Other Services" includes erosion
prevention, litter removal, and highway beautification. The vehicle
inspection and vehicle size and weight enforcement category, and the
general administration category also showed employment gains resulting
from operations expenditures.

For comparison purposes, the results of three similar studies on highway
construction are presented in Table 4, which shows adjusted estimates of
the effects on employment of federally aided highway construction
investment, as originally reported in a 1996 FHWA study (Keane, 1996b).
The total number of direct and indirect jobs created per billion (2000)
dollars spent[^2] was 25,330, adjusting for inflation. The original
estimates were based on 1995 dollars.

Table 4. Employment Impacts of Investment in Federally Aided Highway

  ------------------------------ ----------------------------------------
  Type of Employment             Jobs Created Per Billion (2000)
                                 Dollars\*

  Direct                         7,250

  Indirect                       18,080

  Subtotal                       25,330

  Induced                        13,308

  Total                          38,638
  ------------------------------ ----------------------------------------

Source: Keane (1996b) The Economic Importance of the National Highway
System. *Public Roads*, Vol. 59, No. 4 (available online).

\*Note: These are adjusted numbers for which the BEA gross domestic
product implicit price deflators are used. The original employment
numbers are based on 1995 dollars. It is assumed that the same
employment is required for the same work. However, one billion 1995
dollars spending is inflated into 1.0896 billion 2000 dollars. The
employment numbers in this table are derived through the division of the
original employment numbers by 1.0896.

Table 5 shows the adjusted estimates of employment in several
construction-related activities reported by the Bureau of Labor
Statistics (BLS) (Keane, 1996b). The adjusted estimates of total direct
and indirect employment, based on 2000 dollars, show that 16,298 jobs
were created per billion (2000) dollars spent. The original estimates
were based on 1982 dollars.

Table 5. Employment Impacts of Construction-Related Activities

  ----------------------------------- -----------------------------------
  Type of Activities                  Total Direct and Indirect
                                      Employment Impacts Per Billion
                                      (2000) Dollars\*

  Private multi-family housing        15,362

  Private single-family housing       13,512

  General Hospitals                   15,688

  Elementary and Secondary Schools    14,761

  Federally Aided Highway             16,298

  Sewer-Line Work                     14,615

  Sewer-Plant Work                    14,225

  College Housing                     14,520

  Civil Work, Land                    12,960

  Civil Work, Dredging                14,109

  Public Housing                      15,133

  Federal Office Building             15,265

  Commercial Office Building          13,734
  ----------------------------------- -----------------------------------

JOBMOD, a software program developed by the Boston University Center for
Transportation Studies and Battelle, generated an estimate of 21,219
jobs created per billon dollars of highway construction expenditures.
Table 6 compares the results of these three studies.

Table 6. Comparison of Employment Impact of Highway Operations\
and Construction Spending (full-time job equivalents per billion
dollars\*)

+----------+-----------+----+-----------+----+-----------+------------+
|          | Highway   |    | Highway   |    | Highway   | JOBMOD     |
|          | O         |    | Con       |    | Con       |            |
|          | perations |    | struction |    | struction | (version   |
|          |           |    | (FHWA)    |    | (BLS)     | 1.1)       |
+----------+-----------+----+-----------+----+-----------+------------+
|          | E         | \% | E         | \% | E         | Employment |
|          | mployment |    | mployment |    | mployment |            |
+----------+-----------+----+-----------+----+-----------+------------+
| Direct   | 12,231    | 68 | 7,250     | 28 | NA        | NA         |
| em       |           | .7 |           | .6 |           |            |
| ployment |           |    |           |    |           |            |
+----------+-----------+----+-----------+----+-----------+------------+
| Indirect | 5,579     | 31 | 18,080    | 71 | NA        | NA         |
| em       |           | .3 |           | .4 |           |            |
| ployment |           |    |           |    |           |            |
+----------+-----------+----+-----------+----+-----------+------------+
| Total    | 17,810    | 1  | 25,330    | 1  | 16,298    | 21,219     |
| em       |           | 00 |           | 00 |           |            |
| ployment |           |    |           |    |           |            |
+----------+-----------+----+-----------+----+-----------+------------+

NA, not available.

\*All estimates are based on 2000 dollars, except for that of JOBMOD for
which the information of a specific year cannot be found in the
materials available.

By comparison, the average total number of jobs created directly and
indirectly by highway operations expenditures is estimated to be 17,810
per billion (2000) dollars. While this employment figure is less than
the adjusted numbers generated in the 1996 FHWA construction study
(25,330) and by the JOBMOD method (21,219), it is greater than the
adjusted BLS estimate (16,298.)

This study suggests that spending on highway operations generates more
direct employment but much less indirect employment than does spending
on highway construction per dollar. Almost 70 percent of the jobs
generated by way of highway operations spending are direct hires. In
contrast, more than 70 percent of the jobs generated through highway
construction spending are indirect hires. This suggests that highway
operations is more labor intensive but has less interdependence with
other industries than highway construction.

Several caveats to the above conclusion must be noted. First, the
analysis does not capture all the employment effects of highway
operations spending. It is limited to spending on labor (direct
employment) and spending on input purchases (direct and indirect
employment.) The induced effect realized through household spending and
the enabling effect through transportation network improvements are not
included here. The effect on employment would logically be larger if
induced and enabling effects were captured. Therefore, the estimated
number of full-time job equivalents in this analysis is likely a
conservative estimate.

Second, spending structures used for highway operations, with the
exception of snow and ice removal, are borrowed from proxy industries
because data on highway operations spending structures are either
limited or unavailable. While the use of the proxies was necessary, real
highway operations spending structures might be quite different. Third,
average employee compensation is estimated based on proxy occupations or
industries. As above, real compensation in highway operations may be
different.

Finally, employment-output ratios are based on single-year data. The
model assumed that these ratios do not vary over time. The methodology
used implies that the observed year's data are representative of the
relationship between employment and output in an average year. In
reality, however, employment-output ratios change over time because of
changes in economic conditions. Because of these caveats, the number of
full-time job equivalents estimated in this analysis should be
considered a best guess..

# General Approaches to Analyzing Employment Effects

## [Key Measures]{.underline} 

This analysis seeks to determine the total effect on employment levels
resulting from spending on highway operations. The key to this
definition is the cause and effect relationship between highway
operations spending and changes in the level of employment. Identifying
and quantifying this relationship is the essence of any assessment
effort.

The effect on total employment level is traditionally considered the
combination of the direct, indirect, induced, and enabling effects of
the spending. These classifications of effects are distinguished by the
nature of their linkage to the original cause.

Take as an example the output effect of a highway infrastructure
project. The project will require purchases of, say, concrete, steel,
and asphalt, and will generate income for, say, construction workers. It
can also be assumed that the project will lead to improvements in the
highway network. Accordingly, the direct effect in this example is
represented by the output required to satisfy the completion of the
project (e.g., construction jobs, steel plant jobs); the indirect effect
is represented by the output required to support the project
construction (e.g., iron mining jobs); the induced effect is represented
by the output required to satisfy demand spurred by empowered consumers
(e.g., retail jobs); and the enabling effect is represented by the
output produced in response to an improved highway network due to the
highway project (e.g., trucking jobs).

In other words, the direct, indirect, and induced effects relate to the
highway project funding as the original source of employment, while the
enabling effects relate to the highway itself as the source of
additional employment levels. The former (three) can be thought of as
demand-side effects and the latter (one) a supply-side effect.
Demand-side effects result directly from funds spent on a project, while
supply-side effects arise from the improvements in productive processes
realized upon project completion.

Highway operations projects differ from highway investment projects in
many ways, including the initial spending or purchase patterns
associated with each. For example, in a highway operations project,
relatively more operational spending may go to labor while relatively
more investment spending may go to materials as compared to a highway
construction project. Nevertheless, highway operations projects affect
labor and output in a manner similar to highway investment projects.
Specifically, highway operations projects result in direct increases in
employment. Furthermore, highway operations spending normally entails
the direct purchase of materials such as computers, phones, and other
office supplies. Labor is needed to produce the needed materials. .
These are all direct impacts on labor. Additional goods (and services)
must be produced (and provided) to facilitate the production of
materials directly supporting highway operations projects. The
production of such additional goods and services requires more labor,
which represents the indirect impact of a project on labor. Further
indirect impacts may ripple through the economy. The increased
employment supporting highway operations projects increases the wealth
of affected workers and thus leads to more personal consumption spending
on goods and services. The labor employed in producing thegoods and
services for which there is increased demand represents induced
employment. Highway operations projects also facilitate more efficient
personal transport and freight movement that enable more productive
activities throughout the entire economy and result in changes in
overall employment. Figure 1 provides an overview of the effect of
highway operations spending on employment.

Figure 1. Employment Effect of Highway Operations Spending

Key: 1. Direct Effect 2. Indirect Effect 3. Enabling Effect 4. Induced
Effect

The direct effect works through two channels: direct purchase of goods
and services and direct hire of labor (arrows labeled "1" on figure 1).
Except for the direct hire, all employment impact works through industry
output. Purchase of goods and services, efficiency gain, and consumption
spending all lead to increased industrial output, which in turn results
in additional employment of labor.

## [Alternative Methods]{.underline}

## Historically, researchers have used three methodologies to estimate the effect of highway investments on the economy, including changes in employment levels. They are: 1) the Input-Output (IO) approach, 2) the structural model approach, and 3) the aggregate production/cost function approach. The different approaches require different input data and produce output in different forms. Each of the three approaches can be adapted for use in assessing the effect of highway operations spending. [^3]

### Input-Output Analysis

The standard IO approach lends itself most readily to the measurement of
direct, indirect, and induced effects. In fact, these effects are often
defined as inherent IO concepts because each corresponds exactly to one
IO quantity. The direct effect is the vector of goods and services on
which the initial spending is made; the indirect effect is the sum of
total commodity multipliers for industries minus the direct effect; and
the induced effect is the sum of total commodity multipliers for
households. Commodity multipliers here refer to all multipliers except
for income multipliers in the IO system with an endogenous household
sector. A commodity multiplier is the additional output of the commodity
that is produced in response, directly and indirectly, to one dollar's
worth of initial spending. Since the initial spending triggers a chain
reaction that affects all commodity production, all commodity
multipliers must be summed to measure the total effect corresponding to
each category of spending. Because a total multiplier includes both
direct and indirect effect, the indirect effect must be isolated. With
the exception of direct hire employment, total employment effect is
determined through output effects, as shown in Figure 1. Output impact
is thus used to illustrate these IO quantities. Only the commodity
multipliers are included in output impact.[^4]

The most crucial step in the IO method is the estimation of the direct
output effect, which is often presented as a vector of goods and
services directly purchased with the total spending. Multiplying a
standard input structure or spending structure by the total spending on
goods and services provides the vector of direct output effect. The
spending structure differs between different types of operations. Using
the direct output effect vector, the standard Leontief equation[^5] can
be used to estimate the indirect effect. The induced effect is
calculated using the same procedure, with an adjustment to the commodity
and industry-based IO tables to include a household sector and labor
commodity in the intermediate section. The direct effect vector must
also include an element for household income, which is equal to the
direct spending on labor for highway operations.

The relationship between upstream and downstream industries may be
quantified using a supply-side IO approach. While increased demand by a
downstream industry certainly will stimulate more production by an
upstream industry, increased production by an upstream industry may also
stimulate production in the downstream industry. In the case of highway
operations, an improved highway system may serve to reduce the level of
friction between upstream and downstream industries and lead to
reductions in the cost of finished goods, and ultimately serve to
stimulate economic growth. This is particularly true in a
supply-constrained economy. This supply-side effect may be called the
enabling effect. As the following discussion will show, this supply-side
measure does not reveal the full magnitude of the enabling effect.

### Structural Model

The IO approach focuses on the linkages among industries in the form of
input and output. Industry increases production in response to an
increase in demand. Likewise, industry increases input requirements in
preparation for or in response to increased demand for production.
Although this interaction between and among industries is important,
there are other influences on industry supply and demand. Individual
companies may respond in different ways to an event such as a
technological breakthrough, or the opening of a new market. This type of
event can be thought of as an enabling effect, and is particularly
important in assessing the effect of highway operations spending.
Improvements to the highway system tend to result in market expansion.
The IO approach does not capture this type of enabling effects.

A structural model is a more appropriate approach than the IO model. A
structural model accounts for the interactivity between economic
variables. In other words, a structural model provides a framework for
definition of underlying economic relationships and makes possible the
simultaneous determination of a wide variety of related variables.

For example, a more efficient highway system will likely result in
reduced transportation costs. Industries will respond to cheaper
transportation by reorganizing their logistics chains, buying more
transportation services and reducing inventories and storage
facilities.. These changes will result in changes in employment levels
across a number of industries. A structural model can be designed to
capture this effect by including equations relating highway operational
characteristics with variables for transportation cost and inventory and
storage, for example. Specifying and estimating valid structural
equations between and among these variables are challenging tasks, but a
structural modeling approach recognizes the relationships.

In theory, a structural model can be designed for the whole economy or
for any subset: a Computable General Equilibrium (CGE) model seeks to
explain the former, and a partial equilibrium model for the
transportation sector is an example of the latter. A CGE model is needed
to capture the full magnitude of an impact felt throughout the entire
economy, and may include a full set of IO relations as components. The
specification of other components of a CGE model depends on specific
issues at hand, data availability, and modeling strategies.

### Production/Cost Function

A production function relates total output to total inputs. In the case
of a transportation project, inputs include the elements discussed
earlier in this report, including labor costs, private capital
investment, and public transportation infrastructure and operations
investment, among others, while outputs may be measured by the number of
new employees, for example. For each unit of input, the production
function determines the level of output to be expected. A cost function,
on the other hand, relates total cost to total output (as measured by
new jobs, for example.) For each unit of output gained, the cost
function determines the level of cost per unit of output produced. Both
production and cost functions are essentially single equation
approaches. Each relates a variable affected by changes to another
variable in one equation. Two or more production and/or cost functions
may be combined (aggregated) to explain chain-reaction effects.
Aggregate production functions are often used to examine private output
growth and productivity changes. In contrast, cost functions are often
used to estimate cost reduction and productivity effects and to derive
factor demand.[^6]

As noted above, both production and cost functions can be derived
(estimated) for the economy as a whole, for an individual industry, or
for a group of related industries. The key to the accurate assessment of
the effect of highway operations spending on highway employment is the
treatment of highway operations spending as an independent variable in
the primary production function.

To review, in addition to the types of obstacles that must be overcome
with any methodology, such as model specification and data development,
the use of production and cost functions as an approach for employment
change assessment poses further challenges. For example, the
relationship between changes in inputs and/or cost (e.g., operations
spending) and changes in output (e.g., ton-miles) must be properly
determined before the ultimate output metric (e.g., new jobs) and the
relationship between that metric and output level (e.g., ton-miles) can
be defined.

# Model Used in Analyzing the Effect of Highway Operations Spending on Employment 

An IO model was used to estimate the effect highway operations spending
has on employment. There are two reasons for choosing an IO model for
this analysis. First, the model facilitates the estimation of direct,
indirect, and induced effects on employment of highway operations
expenditures. Second, the IO model produces consistent estimates within
an integrated system, it provides industry-level details, and it serves
as an information base as well as an analytical tool.

The IO model is one of the most frequently used methods in economic
analysis and has been widely used in analyzing highway-related
infrastructure and maintenance investments. Therefore, the use of an IO
model in this analysis has the added benefit of providing estimates of
employment generation that are conceptually comparable with those for
other highway investment projects.

## [Model Structure]{.underline}

Using the Transportation Satellite Account[^7] as its basis, the IO
model is comprised of five interrelated components (Figure 2).

-   An IO "make" table provides information on goods and services
    produced by each industry in the U.S. economy.

-   An IO "use" table presents information on goods and services used by
    each industry in the U.S. economy. Thus, the "make" and "use" tables
    together provide a complete characterization of inter-industry
    relationships and serve as the basis for all IO analyses including
    assessment of employment effects.

-   The spending structure vector contains information on purchase or
    spending patterns for highway operations. This vector consists of
    the same number of commodities as the IO "use" table. Each value
    represents the share of spending on the corresponding commodity for
    highway operation purposes.

-   The employment-output ratios vector provides information on
    employment impact per unit of output for each industry. The vector
    contains a separate element for each industry in the IO "use" table
    (industrial multipliers) with each element's value equal to the unit
    employment level for the corresponding industry.

-   Average employee compensation value provides single or multiple
    parameters for converting payments to employees, including wages or
    salaries and benefits, into jobs directly created through highway
    operations projects.

Figure 2. Model Structure

The left-most box and arrow in the graphic above are displayed with
dotted lines to signify that basic input data from the underlying IO
tables will not be transparent to the end users of the model. The reason
for this is as follows: First, basic IO "make" and "use" tables do not
have direct use to the end users except for providing input data to
derive multipliers. Second, deriving multipliers from basic IO tables
involves complicated matrix manipulations. Third, multipliers do not
fluctuate very much over time provided that the analytical period is not
too far removed from the IO base period. Nevertheless, the IO tables
should be provided along with other components in Figure 2 to enforce
data consistency and facilitate data updating.

## [Research Scope and Data Requirements]{.underline}

The above model includes all aspects of highway operations employment
and provides general guidance. Because of limited resources, the induced
and enabling effects were not considered in this analysis, as has been
the case with most previous studies of similar kind. The employment
effects estimated in this analysis include direct hires and indirect
hires realized through the purchase of goods and services explicitly
supporting highway operations. The analysis is further limited to
highway operations expenditures on state-administered highways.

Based on the basic model and the research scope, the following are data
required to estimate the employment effects of spending on highway
operations.

-   Industrial multipliers

-   Spending structure of highway operations activities

-   Employment-output ratios by industry

-   Average employee compensation in each highway operations activity

-   Expenditures on highway operations

Except for industrial multipliers, which are available from the
Transportation Satellite Accounts, there are no readily available data
for other required elements. Therefore, the spending structures of
highway operation activities, employment-output ratios by industry, and
average employee compensation must be developed from a variety of data
sources.

The development of the spending structures of highway operations
activities is a major challenge, requiring input as to what goods and
services are used in those activities. There are potentially two ways to
overcome this difficulty. One way is to conduct a survey of spending
structures underlying highway operations activities across states. This
approach is time consuming and in fact impractical given resource
constraints. The other way is to borrow the spending structures of
similar industries from the Bureau of Economic Analysis (BEA)
input-output analysis. The latter approach has been adopted in this
analysis.

Another challenge is the development of employment-output ratios by
industry. Although the effect on output comes directly from the analysis
within an IO model, additional data are needed to link the effect to
employment. Since IO models produce the effects at the industry level,
it is highly preferable to build the output-employment links at the
industry level as well. Fortunately, data on industrial output and
employment are available for the development of employment-output
ratios.

Finally, average employee compensation is required for model
implementation. This element is independent of the underlying IO model.
It is necessary for the estimation of the number of jobs directly
generated by the payment of employee compensation.

## Data Sources Used in the Analysis 

The types and sources of data used in this analysis are listed below:

-   Expenditures on highway operations by activity: U.S. Federal Highway
    Administration (2001) *Highway Statistics*.

-   Industrial multipliers (2-digit IO industry level): U.S. Bureau of
    Transportation Statistics and Bureau of Economic Analysis (2000)
    *Transportation Satellite Accounts for 1996*.

-   Spending structure in highway operations: U.S. Bureau of Economic
    Analysis (1992b) Input-Output Tables; and U.S. Federal Highway
    Administration (1998) *Test and Evaluation Project No. 28:
    Anti-icing Technology, Field Evaluation Report* (Publication No.:
    FHWA-RD-97-132).

-   National employment by industry: U.S. Bureau of Labor Statistics:
    *National Employment, Hours, and Earnings* (Employees on Nonfarm
    Payroll by Industry (2-digit SIC) in 1996, seasonally adjusted).

-   Industrial output (2-digit IO industry level): U.S. Bureau of
    Economic Analysis (2000) *Transportation Satellite Accounts for
    1996*, The Make of Commodities by Industry table.

-   Average annual wage by occupation: U.S. Bureau of Labor Statistics,
    *Occupational Employment Statistics: 2000 National Occupational
    Employment and Wage Estimates*.

-   Average annual wage by industry: U.S. Bureau of Labor Statistics,
    *Occupational Employment Statistics: 2000 National Industry-Specific
    Occupational Employment and Wage Estimates* (2000 National 3-digit
    SIC Estimates for SICs 071 to 903*)*.

-   Benefit-compensation ratios: U.S. Bureau of Labor Statistics,
    *National Compensation Survey: Employer Cost for Employee
    Compensation*.

-   State and local government expenditure: U.S. Bureau of the Census,
    *State and Local Government Finance Data*.

-   State and local government employment: U.S. Bureau of the Census
    (2000b) *State and Local Government Public Employment and Payroll
    Data*.

-   Full-time sworn state police officers: U.S. Bureau of Justice
    Statistics (2000) *Law Enforcement Management and Administrative
    Statistics, 1999: Data for Individual State and Local Agencies with
    100 or More Officers*.

-   Average employee compensation in toll collection: Illinois State
    Toll Highway Authority (2000) *Alternatives for Restructuring the
    Tollway System: A Report to the Governor*.

## Keys Steps in Data Processing 

This analysis includes the direct effect of operations spending on
employment and the indirect effect on employment through supporting
industries. The number of jobs derived in this analysis is the number of
full-time job equivalents rather than full-time job positions. The
temporal scope of data used in this analysis is approximately 10 years.
It is assumed that no changes in technology affecting the highway
operations have occurred.

The major procedures undertaken in the analysis are as follows:

-   Converted SIC-based industrial employment into two-digit IO level
    industrial employment.

-   Developed the employment-output ratios by industry.

-   Adjusted the industrial multipliers from TSA for 1996 in order to
    match the developed employment-output ratios by industry.

-   Developed the spending structure, i.e., the input structure of each
    activity including traffic control operations, snow and ice removal,
    toll collection, other services, traffic supervision, highway safety
    and driver education, vehicle inspection and vehicle size and weight
    enforcement, general administration, and research and planning.

-   Disaggregated the total U.S. highway operations spending in each
    activity into corresponding categories of inputs.

-   Determined the average annual employee compensation for each
    activity.

-   Calculated direct hiring based on the derived labor cost and average
    annual employee compensation for each activity.

-   Calculated the indirect impact of each activity: First, calculated
    the impact of input purchases on industrial output. Second,
    multiplied the industrial output change with employment-output
    ratios to obtain the number of jobs created through the purchases of
    commodities and services.

-   Obtained the number of jobs by summing the number of direct hires
    and the number of jobs created through the purchases of goods and
    services.

# Development of Spending Structures, Average Employee Compensation, and Employment-Output Ratios

The development of the spending structure, employee compensation, and
employment-output ratios is critical to this analysis. The methods and
procedures used in processing and analyzing the data are described
below.

## [Spending Structure]{.underline}

No data for spending structure in highway operations activities are
readily available. Therefore, proxies were used to approximate the
spending structure for each highway operations activity. The major
source of data utilized was BEA's 1992 Input-Output data. Similar
industries were selected from the BEA data as proxies for eight of nine
highway operation activities. For snow and ice removal, the proxy
spending structure was garnered from the "Anti-icing Technology, Field
Evaluation Report" published by FHWA in 1998. Justification for the use
of these data as proxies for the spending structure for highway
operations activities is rests on the assumption that technological
relationships between commodity inputs in each of highway operations
activities have been stable.

The calculation of spending structures includes all commodity inputs and
employee compensation. For the selected industries that have data on
both commodity inputs and employee compensation, the derivation of their
spending structure is straightforward; the share of each input is the
ratio of the value of the input to the sum of all commodity inputs and
employee compensation. For industries bereft of data on employee
compensation, the share of employee compensation must be derived on the
basis of estimated employee compensation. That is, where employee
compensation data is lacking in the IO model, an estimation of employee
compensation is specifically stated.

Highway operations activities are categorized into three groups: 1)
highway and traffic services, 2) administration and research, and 3)
highway law enforcement and safety. The spending structure of each
activity was determined as follows:

### Highway and Traffic Services

There are four types of highway and traffic services. They Are: 1)
traffic control operations, 2) snow and ice removal, 3) toll collection
facility, and 4) other services (e.g., beautification, erosion
prevention, litter control).

-   Traffic control operations: Two IO industries were combined to serve
    as the proxy for traffic control operations; the first is 'Electric
    Utilities Repair and Maintenance and Construction', and the second
    is 'Computer Programming, Data Processing, and Other Computer
    Related Services.'

-   Toll collection: IO industry 'State and Local Government Toll
    Highways' was used as a proxy for toll collection.

-   Other services: IO industry 'Landscape and Horticultural Services'
    was used as a proxy for "Other Services."

-   Snow and ice removal: The spending structure of snow and ice removal
    was derived using the data from the report on "Anti-icing
    Technology" (See Appendix C).

### Administration and Research

Two categories of activities are included in Administration and
Research. They are: 1) general administration, and 2) research and
planning. In FHWA's annual report *Highway Statistics,* expenditures in
these categories are not exclusively for highway operations. Rather,
they cover highway construction, maintenance, and operations. Thus, the
portion of the expenditures on highway operations needed to be isolated.
Expenditures on administration and research for highway operations were
separated from the total expenditures on administration and research
(including construction and maintenance) according to the ratio of
highway operations to total expenditure. This was approximately 15
percent in 2000. Table 1 shows highway expenditures by percentage for
construction, maintenance, and operations; total expenditures on
administration and research; and administration and research
expenditures for highway operations.

The spending structure of state and local government, including
government enterprises (98C, 99C, and 79) was used as a proxy for the
commodity input structure of general administration. However, as no data
on employee compensation for state and local government were available
in the BEA 1992 Input-Output tables, compensation levels were estimated
using data on state and local government finance and public employment
and payroll published by U.S. Census Bureau and data on employee
compensation from BLS. In state and local government finance, the total
expenditure of current operations includes general administration of
state and local government and government enterprises. Government
enterprises accounted for roughly 13 percent of the total commodity
purchases by state and local government enterprises in 1992. For
consistency, the data on state and local government and government
enterprises in the IO data were combined to approximate the spending
structure of general administration.

Total employee compensation also needed to be estimated in order to
determine the share of employee compensation in current state and local
government operations. The Census Bureau provides data for full-time
employment equivalents and for total expenditures on current operations,
wages and salaries of state and local government. However, the Census
Bureau's definition of "wages and salaries" is different from employee
compensation in that it does not include all employee benefits. Thus, it
is broader than the definition of wage used by the BLS.

Average annual employee compensation for state and local government was
estimated using the average wages of state and local government and the
benefit-compensation ratios of state and local government from BLS.
Specifically, an average annual wage for state and local government was
computed based on the data from the 2000 National Industry-Specific
Occupational Employment and Wage Estimates (2000 National 3-digit SIC
estimates for SICs 071 to 903,) as published by BLS. The average annual
wage for state and local government employees is a weighted average of
the industry average wages of state government and local government,
adjusted with a benefit-compensation ratio of 29.2 percent in 2000.
Next, average annual employee compensation and the full-time equivalent
employment of state and local government are used to derive the total
employee compensation of state and local government. The share of
employee compensation is the ratio of the estimated total employee
compensation to the total expenditure of state and local government on
current operations. The estimated share of employee compensation was
59.15 percent based on the data in 2000.

The share of "wages and salaries" in the expenditure of current
operations was relatively stable over the 1992 to 2000 period, ranging
from 43 percent to 46 percent. BLS data show the benefit-compensation
ratio to have been in the neighborhood of 30 percent with a deviation of
less than one percentage point. This suggests that the share of employee
compensation in state and local government is also quite stable.
Therefore, it was deemed to be reasonable to apply the estimated share
of employee compensation in 2000 to the BEA 1992 Input-Output data for
state and local government to arrive at a spending structure for state
and local government.

The IO industry Noncommercial Research Organization was used as a proxy
for the function of research and planning in highway operations.

### Highway Law Enforcement and Safety

Four types of activities are included in this category of highway
operations: 1) traffic supervision, 2) highway safety and driver
education, 3) vehicle inspection, and 4) vehicle size and weight
enforcement. 'State and Local Government - Police' is used as a proxy
for the structure of commodity purchases in traffic supervision.
However, there are no available statistics on the number of police
specifically engaged in traffic supervision. For this analysis, it is
assumed that all full-time sworn police officers in field operations are
involved in traffic supervision. Total employee compensation for traffic
supervision in 2000 was calculated using the adjusted average annual
compensation for a police officer. The share of total compensation for
state highway traffic supervision was combined with the data on State
and Local Government Police Consumption to derive the spending structure
of traffic supervision.

IO industry Social Services is used as a proxy for highway safety and
driver education. Vehicle inspection and vehicle size and weight
enforcement were combined and treated as one activity. Fixed Facilities
and Inspection and Weighing Services for Motor Vehicle Transport
industry was used as a proxy for the combined activity.

## [Average Annual Employee Compensation]{.underline}

Two steps were involved in estimating average employee compensation. The
first step was to identify an appropriate proxy occupation or industry
for each highway operations activity. The second was to translate an
average wage into average compensation using an appropriate
benefit-compensation ratio. Table 7 provides a summary of the estimation
of average annual employee compensation for all of highway operations
activities.

Table 7. Wage and Compensation Data

+-----------+------+-----------------+------+-----------+-----------+
| A         | Sou  | Proxy           | Wage | Be        | Average   |
| ctivities | rces | Occupation or   | (\$) | nefit-Com | Annual    |
|           | of   | Industry Wage   |      | pensation | Com       |
|           | W    |                 |      | Ratio (%) | pensation |
|           | ages |                 |      | (4)       |           |
+===========+======+=================+======+===========+===========+
| Traffic   | \    | Weighted        | 52   | 25.5      | 69,940    |
| control   | (1\) | Average Wage of | ,105 |           |           |
| o         |      | SIC 173 and     |      |           |           |
| perations |      | 737, industry   |      |           |           |
|           |      | total           |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Snow and  | \    | Highway         | 27   | 25.5      | 36,886    |
| ice       | (2\) | maintenance     | ,480 |           |           |
| removal   |      | workers         |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Other     | \    | SIC 078         | 24   | 25.5      | 32,376    |
| services  | (1\) | Landscape and   | ,120 |           |           |
|           |      | horticultural   |      |           |           |
|           |      | services,       |      |           |           |
|           |      | industry total  |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Toll      | \    | Illinois Toll   | 3    |           | 52244     |
| c         | (3\) | Industry        | 7866 |           |           |
| ollection |      | Average         | (5)  |           | \(6\)     |
+-----------+------+-----------------+------+-----------+-----------+
| General   | \    | Weighted        | 35   | 29.2      | 50,555    |
| admin     | (1\) | average wage of | ,793 |           |           |
| istration |      | State and Local |      |           |           |
|           |      | Government (SIC |      |           |           |
|           |      | 902 and 903),   |      |           |           |
|           |      | industry total  |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Research  | \    | SIC 873         | 48   | 29.2      | 68,432    |
| and       | (1\) | Research,       | ,450 |           |           |
| planning  |      | development,    |      |           |           |
|           |      | and testing     |      |           |           |
|           |      | services,       |      |           |           |
|           |      | industry total  |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Traffic   | \    | Sheriff and     | 40   | 29.2      | 57,331    |
| su        | (2\) | police\'s       | ,590 |           |           |
| pervision |      | patrol officers |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Highway   | \    | SIC 839 Social  | 30   | 25.5      | 41,195    |
| safety    | (1\) | Services, not   | ,690 |           |           |
| and       |      | elsewhere       |      |           |           |
| driver    |      | classified,     |      |           |           |
| education |      | industry total  |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+
| Vehicle   | \    | Automotive      | 30   | 25.5      | 41,315    |
| i         | (2\) | service         | ,780 |           |           |
| nspection |      | technicians and |      |           |           |
|           |      | mechanics       |      |           |           |
+-----------+------+-----------------+------+-----------+-----------+

Sources: (1). U.S. Bureau of Labor Statistics: 2000 National
Industry-Specific Occupational Employment and Wage Estimates (3-digit).
(2). U.S. Bureau of Labor Statistics: 2000 Occupational Employment and
Wage Estimates. (3). The average wage and compensation are estimates
based on The Report by Illinois Toll Highway Authority (2000). (4)
Benefit-compensation ratio is from U.S. Bureau of Labor Statistics:
Employer\'s Cost for Employee Compensation in 2000. In 2000,
benefit-compensation ratio for state and local government is 29.2% and
for service-producing industries 25.5%. (5) This number is the average
payment to employees, exclusive of FICA/Retirement and Insurance
benefits. (6) Weighted average payroll (including FICA/retirement)+
average insurance benefits = 46127 + (7633922/1248) = \$52,244.

With the exception of toll collection, the average employee compensation
for all highway operation activities is based on the *2000 Occupational
Employment and Wage Estimates* (U.S. Bureau of Labor Statistics) or
*2000 National Industry-Specific Occupational Employment and Wage
Estimates* (U.S. Bureau of Labor Statistics). An occupational average
wage was used when an occupation was identified as being a highway
operation activity. Otherwise, the average wage of a corresponding
industry was used in lieu of a highway operations activity. As indicated
in Table 7, occupational wages are used as proxies for average wages for
snow and ice removal, traffic supervision, and vehicle inspection and
vehicle size and weight enforcement. Industrial average wages are used
as proxies for average wages in traffic control operations, other
services, general administration, research and planning, and highway
safety and driver education.

The average wage was converted to average employee compensation using
appropriate benefit-employee compensation ratios published by BLS. The
benefit-compensation ratio for state and local government was applied to
general administration, research and planning, and traffic supervision.
The benefit-compensation ratio for private sector service-producing
industry was applied to traffic control operations, snow and ice
removal, other services, highway safety and driver education, and
vehicle inspection.

Average employee compensation for toll collectors was calculated using
data from a report by Illinois Toll Highway Authority (2000). It is a
cross-occupational average from the Illinois Toll Highway Authority. The
national average wage or compensation for toll highway employees is not
available.

## *Employment-Output Ratios*

The employment-output ratios equal employment per unit of industrial
output. They were developed using industrial output data from U.S.
Transportation Satellite Accounts for 1996 (U.S. Bureau of
Transportation Statistics and Bureau of Economic Analysis, 2000) and the
1996 seasonally adjusted non-farm employment data from U.S. Bureau of
Labor Statistics. The industrial output is based on two-digit
input-output industry codes. Industrial employment is based on two-digit
SIC codes. Annual employment is an average of the seasonally adjusted
monthly employment. In order to compute employment-output ratios, the
two data sets were adjusted accordingly so as to be compatible with one
another.

**References**

AASHTO (American Association of State Highway and Transportation
Officials) (1999) *Maintenance Manual: The Maintenance and Management of
Roadways and Bridges*. Washington, D.C.

Babcock, M.W. and Bratsberg, B. (1997) *Economic Impacts of the Kansas
Comprehensive Highway Program*. Report Prepared for Kansas Department of
Transportation, Department of Economics, Kansas State University.

Burgess and Niple, Ltd., et al. (1998) *Final Report: I-71 Corridor
Transportation Study*. Prepare for Ohio-Kentucky-Indiana Regional
Council of Governments.

BUCTS and Battelle (Boston University Center for Transportation Studies
and Battelle Memorial Institute) (2001) *JOBMOD, A Model for Estimating
Federal-aid Highway Program Income and Employment Impacts*. Washington,
D.C.: Federal Highway Administration.

Keane, T. (1996a) *Highway Infrastructure Investment and Job Creation*.
Publication No. FHWA-PL-96-015. Federal Highway Administration, U.S.
Department of Transportation. Washington, DC.

Keane, T. (1996b) The Economic Importance of the National Highway
System. *Public Roads*, Vol. 59, No. 4. Retrieved from:
http://www.tfhrc.gov/pubrds/ spring96/p96sp16.htm, on May 4, 2003.

######## Liew, C.K., and C.J. Liew. (1984) Measuring the development impact of a proposed transportation system. *Regional Science and Urban Economics*, Vol. 14, 175-98.

Illinois State Toll Highway Authority (2000) *Alternatives for
Restructuring the Tollway System: A Report to the Governor*. Retrieved
from: http://www.illinoistollway.com/News/Documents/GovernorsReport.pdf,
on February 5, 2003.

Minnesota IMPLAN Group (MIG), Inc. (1999) *IMPLAN Professional Users
Guide*. Stillwater, Minn.

Politano, A.L. and C. Roadifer. (1989) Regional Economic Impact Model
for Highway Systems. *Transportation Research Record 1229*.
Transportation Research Board, National Research Council. Washington,
DC.

RESI -- A Research Institute of Towson University (1998) *The Economic
Impact of Maryland highway Investment*. Prepared for the Maryland State
Highway Administration. Baltimore, MD.

Regional Science Research Corporation (1996) *PC I-O User's Manual*.
Hightstown, N.J.

Stokes, R.W., N. Pinnoi, and E.J. Washington. (1991) *Economic
Development Impacts of Expenditures for State Highway Improvements in
Texas*. Texas Transportation Institute, Texas A&M University for the
Texas Department of Transportation. Austin, T.X..

Texas Transportation Institute (1991) *Economic Assessment of the
Proposed Improvement of US Highway 287 in Wichita Falls*. Texas
Department of Transportation. Austin, TX.

Texas Department of Transportation (1998) *Economic Impact of
Developments of the Texas trunk System*. Austin, TX.

Thompson, E., E. Berger, D. Black, A. Chanra, and K. Gitings. (1997)
*Economic Impact Assessment of a Southern Kentucky Corridor (I-66)*.
Center for Business and Economic Research, University of Kentucky.
Lexington, KY.

Treyz, G., D. Rickman, and G. Shao. (1992) The REMI economic-demographic
forecasting and simulation model. *International Regional Science
Review*, Vol. 14, No. 3, 221-53.

University of North Carolina at Charlotte (1991) *Interstate 40 Economic
Impact Study: Technical Report*. North Carolina Department of Economic
and Community Development. Raleigh, NC.

University of North Carolina at Charlotte (1999) *Economic Impacts of
the Monroe**-**Gastonia Connector***.** North Carolina Department of
Economic and Community Development**.** Raleigh**,** NC**.**

U.S. Bureau of Census: *State and Local Government Finance Data*.
Retrieved from: http://www.census.gov/govs/www/financegen.html, on March
11, 2003.

U.S. Bureau of the Census (2000a) *Government Finance and Employment
Classification Manual*. Retrieved from: http://www.census.gov, in
November 2002.

U.S. Bureau of Census (2000b) *State and Local Government Public
Employment and Payroll Data*. Retrieved from:
http://www.census.gov/govs/apes/00stlall.xls, on March 18, 2003.

U.S. Bureau of Economic Analysis (1992a) *Regional Multipliers: A User
Handbook for the Regional Input-Output Modeling System (RIMS II), 2nd
edition*. U.S. department of Commerce, Washington, D.C.

U.S. Bureau of Economic Analysis (1992b) Input-Output Tables.

U.S. Bureau of Justice Statistics (2000) Law Enforcement Management and
Administrative Statistics, 1999: Data for Individual State and Local
Agencies with 100 or More Officers. Washington, D.C.: U.S. Department of
Justice.

U.S. Bureau of Labor Statistics: *National Employment, Hours, and
Earnings* (Employees on Nonfarm Payroll by Industry in 1996, seasonally
adjusted). Retrieved from:
http://www.bls.gov/webapps/legacy/cesbtab1.htm, on January 21, 2003.

U.S. Bureau of Labor Statistics: *Occupational Employment Statistics:
2000 National Occupational Employment and Wage Estimates*. Retrieved
from: http://www.bls.gov/oes/oes_dl.htm, on January 27, 2003.

U.S. Bureau of Labor Statistics: *Occupational Employment Statistics:
2000 National Industry-Specific Occupational Employment and Wage
Estimates (*2000 National 3-digit SIC Estimates for SICs 071 to 903*)*.
Retrieved from: http://www.bls.gov/oes/oes_dl.htm, on March 6, 2003.

U.S. Bureau of Labor Statistics: *National Compensation Survey: Employer
Cost for Employee Compensation*. Retrieved from:
http://www.bls.gov/ncs/home.htm, on March 31, 2003.

U.S. Bureau of Transportation Statistics and Bureau of Economic Analysis
(2000) U.S. Transportation Satellite Accounts for 1996. Retrieved from:
http://www.bea.gov, on January 23, 2003.

U.S. Federal Highway Administration (2001). *Highway Statistics 2000*.
Washington, D.C.: U.S. Department of Transportation.

U.S. Federal Highway Administration (2000) *Guide to Reporting Highway
Statistics*. Retrieved from: http://www.fhwa.dot.gov/, in November 2002.

U.S. Federal Highway Administration (1998) *Test and Evaluation Project
No. 28: Anti-icing Technology, Field Evaluation Report* (Publication
No.: FHWA-RD-97-132). Washington, D.C.: U.S. Department of
Transportation.

Weisbrod, G. (2000) *Current Practices for Assessing Economic
Development Impacts from Transportation Investments, A Synthesis of
Highway Practice*. National Cooperative Highway Research Program (NCHRP)
Synthesis 290. Washington, DC.: Transportation Research Board, National
Research Council.

Wilbur Smith Associates (1995) *Economics Impact Study of CSX
Intermodal's New Atlanta Terminal*. CSX International. Richmond, VA.

Appendix A. Examples of Highway Operations by Type

*Administration and Research*

[Administration]{.underline}: Administration of highway programs by
federal, state and local highway agencies such as the Federal Highway
Administration, National Highway Traffic Safety Administration, and
their corresponding state and local level agencies. Examples of
operations expenditure for these agencies include salaries and benefits
of employees; office expenses such as supplies, rent, communication,
travel, insurance, utilities and miscellaneous expenses; and contractual
services and supplies; etc.

[Research and Planning]{.underline}: Highway planning, staff training,
research and development, and investigation, including laboratory and
field research in road and bridge materials and design, traffic
research, and technical and financial studies, etc.

*Highway and Traffic Services*

[Traffic control operations]{.underline}: These include operations of
intelligent and other traffic control and surveillance systems that are
designed to monitor and control traffic by managing vehicle flow on
streets and highways. These systems consist of traffic signal control;
freeway, tunnel and bridge surveillance and control; electronic message
boards; video monitoring; traffic information radio stations; motorist
aid; and toll-free drawbridges, tunnels and ferries; etc.

[Snow and ice removal]{.underline}: Removal of snow and ice from
roadway, roadside, and shoulders; sanding and chemical applications;
erection and removal of snow fences; and opening of inlets clogged with
snow and ice, etc.

[Other services]{.underline}: Highway beautification; junkyard control
and roadside cleaning operations; control of outdoor advertising; litter
pickup, mowing, and tree trimming; air quality monitoring; vegetation
management; and erosion control programs; etc.

*Highway Law Enforcement and Safety*

[Traffic supervision]{.underline}: This covers highway patrol activities
providing traffic supervision: enforcement of traffic laws, supervision
and direction of traffic, accident investigation, and incidental service
functions, etc.

[Highway traffic and driver safety]{.underline}: These include safety
programs and similar activities related to the promotion of highway
safety and traffic accident prevention, whether conducted by the state
or local highway agency, the highway patrol, a traffic safety commission
or other state agency. These also include such activities as driver
education and driver awareness, motorcycle safety, drunk or impaired
driving, accident reduction, and emergency medical services for highway
accident victims, etc.

[Vehicle inspection]{.underline}: Inspecting vehicles, operating
inspection stations, and other activities related to periodic motor
vehicle inspections programs; motor vehicle emissions inspection; and
motor carrier safety inspection; etc.

[Vehicle size and weight enforcement]{.underline}: Operating
truck-weighing stations, operating other devices involved in the
enforcement of vehicle, and equipment and size and weight limitations on
highways, etc.

**Appendix B. Comprehensive Regional IO Models**

Among the widely used comprehensive regional IO models are the BEA RIMS
II multipliers (U.S. Bureau of Economic Analysis, 1992a), the Minnesota
IMPLAN Group, Inc. (MIG) IMPLAN Pro model (Minnesota IMPLAN Group (MIG)
Inc., 1999), the Regional Science Research Corporation (RSRC) PC I-O
model (Regional Science Research Corporation, 1996), and the Regional
Economic Models, Inc. REMI Policy Insight model (Treyz, Rickman, and
Shao, 1992). IO models are often used for both the assessment of an
existing highway system (Babcock and Bratsberg, 1997; Keane, 1996a;
Politano and Roadifer, 1989; RESI, 1998; Stokes, Pinnoi, and Washington,
1991; and Texas Department of Transportation, 1998) and the analysis of
proposed projects (Burgess and Niple Ltd, 1998; Liew and Liew, 1984;
Stokes, Pinnoi, and Washington, 1991; Wilbur Smith Associates, 1995;
Texas Transportation Institute, 1991; Thompson et al., 1997; and
University of North Carolina at Charlotte, 1991, 1999). They are also
used by the FHWA in highway investment impact analysis (Keane, 1996b;
BUCTS and Battelle, 2001).

# Appendix C. SPENDING STRUCTURE OF SNOW AND ICE REMOVAL

The analysis of the spending structure of snow and ice removal is based
on the data from the report on anti-icing technology (U.S. Federal
Highway Administration, 1998), which provides data on spending on snow
and ice removal for five of the 15 participating states in the test and
evaluation of anti-icing technology. The five states are California,
Nevada, New Hampshire, New York, and Wisconsin. Three types of
information in the report are useful to our analysis: spending on labor,
equipment, materials, and total costs in snow and ice removal;
information on prices of some inputs; and information on total amount of
materials and volume ratios of chemicals to abrasives in materials.

The data are available for both test and control sections of highways.
The major difference between test and control sections is in the
materials used during the tests. New materials were used in test
sections but conventional ones such as salt and sand or other abrasives
were used in control sections. Online research shows that the use of
conventional technology is still a normal practice in snow and ice
removal. For example, both Virginia and Montgomery County of Maryland
are still using a salt/sand mix in snow and ice removal. Therefore, the
data on control sections are used in our analysis because they are based
on conventional technology in snow and ice removal.

## Procedures of the Analysis

First, spending patterns in labor, equipment and materials across five
states are calculated based on the data in Tables 59-63 of the 1998 U.S.
Federal Highway Administration report. Due to the differences in the
number of observations across the five states, state averages for each
category are calculated and then summed by category. The average
percentages of spending on labor, equipment and materials are then
calculated (Table 1).

To be consistent with the data for California, New Hampshire, Wisconsin
and Nevada, data on materials in New York were adjusted to eliminate the
cost for clean up (see discussion below). Nevada has data with and
without clean-up cost.

Second, spending on materials is separated into two categories: salt and
abrasives (Table 2). Third, a spending structure of snow and ice removal
was obtained with four categories: labor, equipment, salt, and abrasives
(Table 3).

Table 1. Average Spending Structure of Snow and Ice Removal\
with Three Categories

+--------+-------+------+------------+-------+-------+-------+------+
|        | Calif | Ne   | New        | New   | Wisc  | Total | \%   |
|        | ornia | vada | Hampshire  | York  | onsin |       |      |
|        |       |      |            |       |       |       |      |
|        | Av    | Ave  | Average    | Av    | Av    |       |      |
|        | erage | rage |            | erage | erage |       |      |
+--------+-------+------+------------+-------+-------+-------+------+
| Labor  | \$1   | \$22 | \$70.52    | \$2,0 | \$1   | \$2,6 | 56   |
|        | 27.79 | 1.31 |            | 44.51 | 61.65 | 25.78 | .70% |
+--------+-------+------+------------+-------+-------+-------+------+
| Equ    | \$    | \$15 | \$59.88    | \$4   | \$1   | \$8   | 18   |
| ipment | 59.57 | 1.90 |            | 26.51 | 36.60 | 34.47 | .02% |
+--------+-------+------+------------+-------+-------+-------+------+
| Mat    | \$    | \$34 | \$96.23    | \$6   | \$    | \$1,1 | 25   |
| erials | 60.74 | 7.08 |            | 09.05 | 57.41 | 70.51 | .28% |
+--------+-------+------+------------+-------+-------+-------+------+
| Total  | \$2   | \$72 | \$226.63   | \$3,0 | \$3   | \$4,6 | 100  |
|        | 48.11 | 0.30 |            | 80.08 | 55.66 | 30.77 | .00% |
+--------+-------+------+------------+-------+-------+-------+------+

Table 2. Average Structure of Spending on Materials

+-------+-------+------+------------+-------+-------+-------+------+
|       | Calif | Ne   | New        | New   | Wisc  | Total | \%   |
|       | ornia | vada | Hampshire  | York  | onsin |       |      |
|       |       |      |            |       |       |       |      |
|       | Av    | Ave  | Average    | Av    | Av    |       |      |
|       | erage | rage |            | erage | erage |       |      |
+-------+-------+------+------------+-------+-------+-------+------+
| Salt  | \$    | \$24 | \$89.86    | \$5   | \$    | \$9   | 84   |
|       | 27.94 | 1.12 |            | 72.32 | 57.41 | 88.66 | .47% |
+-------+-------+------+------------+-------+-------+-------+------+
| Abra  | \$    | \$10 | \$6.37     | \$    | \     | \$1   | 15   |
| sives | 32.80 | 5.96 |            | 36.64 | $0.00 | 81.77 | .53% |
+-------+-------+------+------------+-------+-------+-------+------+
| Total | \$    | \$34 | \$96.23    | \$6   | \$    | \$1,1 | 100  |
|       | 60.74 | 7.08 |            | 08.96 | 57.41 | 70.43 | .00% |
+-------+-------+------+------------+-------+-------+-------+------+

Table 3. Average Spending Structure of Snow and Ice Removal

  --------------------------- ---------------------- ---------------------
                              Average                Average

  Labor                       56.70%                 56.70%

  Equipment                   18.02%                 18.02%

  Materials                   25.28%                 

  Salt                                               21.35%

  Abrasives                                          3.93%

  Total                       100.00%                100.00%
  --------------------------- ---------------------- ---------------------

## 

## Spending on Materials

Materials used in snow and ice removal include two major categories:
salt (different types) and abrasives (sand or cinders). The amount and
price of and spending on each category is provided in Tables 59-63 in
the 1998 U.S. Federal Highway Administration report. According to the
ratio of salt/sand ratios for each state (Table 2), spending on
materials is separated into two sub-categories: salt and abrasives.

Four of the five states have data on spending on materials that do not
include clean-up cost. New York's spending on materials, however, does
include clean-up cost. The costs for salt and sand is calculated based
on the ratio of salt to sand and the price information for salt and
sand.[^8] Then, the sum of costs for salt and sand is deducted from
total spending on materials. The remainder is the cost for cleanup of
sand. In order to be comparable across state, the cleanup cost is
deducted from the spending for materials and from the total spending for
snow and ice removal. The final data for the five states does not
include clean-up costs, and they are comparable in terms of the
composition of spending.

In the case of Nevada, there is no price information for salt or sand.
The price for salt in California (\$55.00/t) is used to separate
spending on salt from total spending on materials.

[^1]: See Weisbrod (2000) for a comprehensive review of the literature
    on the impact analysis of transportation investment.

[^2]: Induced employment was also estimated in the FHWA study but is
    excluded here for comparison purposes.

[^3]: A general discussion of these approaches is provided below for
    conceptualization purposes. This report only provides estimates of
    traditional impact measures based on IO approach.

[^4]: Going from output impact to employment impact and handling direct
    employment impact through direct hire requires technical steps
    outside the IO framework. Discussion follows below.

[^5]: In the Leontief model, there are a finite number of industries
    producing a finite number of different products, such that the input
    equals the output, or consumption equals production.

[^6]: One disadvantage of both production and cost function approaches
    is that neither models the underlying mechanism that relates highway
    investments to cost reductions or productivity increases. Factors
    such as mobility, accessibility, and business inventory management
    are intuitive elements within the mechanisms. Importantly, however,
    solid conceptual and empirical understanding is currently lacking in
    that area.

[^7]: The Transportation Satellite Account (TSA) is an extension of the
    Input-Output tables of the United States. Developed by BTS and BEA,
    it identifies and measures transportation activities by
    establishments engaged in transportation as a secondary activity
    (in-house transportation) and those engaged in transportation as a
    primary activity (for-hire). TSA identifies detailed expenditure
    flows with their commensurate material and labor flows. Expenditures
    on labor, material, and other components for operations can be
    extracted from the TSA by industry and translated into number of
    jobs.

[^8]: There is no price information for New York in the 1998 U.S.
    Federal Highway Administration report. The average price of
    abrasives in California and New Hampshire (\$7.58/t) are used in the
    analysis. This may bring error into the computation because the
    price of sand in New York could be quite different from the average.
    The difference between the price of abrasives in California and New
    Hampshire is \$7.44, which is substantial.