Appendix C
Data Source and Accuracy Statements
Chapter 3 Transportation and the Economy
TABLE 3-1a & 3-1b. U.S. Gross Domestic Product Attributed to For-Hire
Transportation Services (Current and chained 1996 dollars)
TABLE 3-2a & 3-2b. U.S. Gross Domestic Product Attributed to Transportation-Related
Final Demand (Current and chained 1996 dollars)
TABLE 3-3a & 3.3b. U.S. Gross Domestic Demand Attributed to Transportation-Related
Final Demand (Current and chained 1996 dollars)
TABLE 3-4a & 3-4b. Contributions to Gross Domestic Product: Selected Industries
(Current and chained 1996 dollars)
TABLE 3-5. Gross Domestic Product by Major Social Function
Tables 3-1 through 3-5 present data on transportation's contributions to the
economy through consumption (or the money spent on transportation activity). The
Survey of Current Business (SCB) published by the U.S. Department of Commerce,
Bureau of Economic Analysis (BEA). The SCB is a monthly journal that contains
estimates of U.S. economic activity, including industry contributions to the Gross
Domestic Product (GDP). GDP is defined as the net value of the output of goods
and services produced by labor and property located in the United States. BEA
constructs two complementary measures of GDP-one based on income and the other
on expenditures (product). Together, they represent the National Income and Product
Accounts (NIPA), our nation's principle framework for macroeconomic estimates.
The product side results from the addition of labor, capital, and taxes for producing
output. Consumption derives from household, business, and government expenditures
and net foreign purchases.
Table 3-3 presents transportation's economic impact in a different form, Gross
Domestic Demand (GDD). Also derived from the national accounts, GDD is the sum
of personal consumption, gross private domestic investment, and government purchases.
GDD includes imports, but excludes exports, thus counting only what is consumed,
purchased, or invested in the United States.
GDP Methodology
The 1960 through 1985 data in table 3-1 are from the November 1993 issue of
the SCB. The 1990 through 1991 data and 1992 through 1996 data are from an August
1996 and November 1997 SCB issue respectively. The October 1999 issue introduced
a revised methodology for GDP estimates (Yuskavage 1996). This section describes
BEA's methodology for estimating transportation's share of GDP.
BEA's current-dollar estimates of GDP by industry rely on several sources,
including the Bureau of Labor Statistics (BLS), the Health Care Financing Administration,
and the Internal Revenue Service (IRS). Some of the tables in this chapter report
chained-dollar figures. BEA derived chained dollars by using the Fisher Ideal
Quantity Index to calculate changes between adjacent years (Parker and Triplett
1996; Landerfeld and Parker 1997). Annual changes are then chained to form a time
series that incorporates the effects of relative price and output composition
changes. Please refer to page 142 of the August 1996 issue of the Survey of Current
Business for the mathematical formulas (Yuskavage 1996). This method produced
separate estimates of gross output and intermediate inputs for a sector's GDP
calculation. BEA updated the reference year for the chained-dollar estimates from
1992 to 1996.
Transportation GDP in chained dollars was estimated using the double-deflation
method, which relies on a chain-type quantity index formula, and requires gross
output and intermediate input information. Principal source data for the transportation
categories include: 1) operating revenues of air carriers and Federal Express
from the U.S. Department of Transportation and public sources (air); 2) operating
revenues for Class I motor carriers from historical records of the Interstate
Commerce Commission and Census Bureau annual surveys (trucking and warehousing);
3) BEA personal consumption expenditures (PCE), BLS, and trade sources (local
and interurban passenger transit); 4) operating revenues for Class I railroads
and Amtrak (rail); and 5) other trade sources (pipelines). Data sources for water
were not provided (Yuskavage, 1996).
Table 3-1 reported current dollar estimates from various SCB issues. BEA derived
the 1991 data and subsequent years in four steps:
- BEA's benchmark input-output (I-O) tables produced input compositions for
1977, 1982, and 1987.
- BEA estimated 1978 through 1981 and 1983 through 1986 input compositions
by interpolating the 1977, 1982, and 1987 figures.
- BEA estimates the 1977 through 1987 imported and domestically imported shares
of each detailed input.
- BEA estimates the 1988 through 1994 input compositions based on the 1987
figures and the Economic Censuses of 1992.
For intermediate input estimations, BEA deflates each of the current-dollar
inputs. (BEA deflates import and domestic production separately.) For deflation,
quantities are approximated by real values (expressed at present with 1996 as
the base period) that are calculated by dividing the current-dollar value of the
component by its price index. BEA develops estimates for import prices with data
from a variety of sources, but primarily from the BLS import price series.
Reliability and Accuracy
BEA views GDP as a reliable measure of output because of the source data underlying
the estimates. The following reliability comments are based on the Valliant (1993)
SCB article and Ritter (2000). GDP data originate from three types of sources.
The foundational data come first from the economic censuses conducted every five
years. These approach complete enumerations of sectoral activity in state and
local governments, manufacturing, services, retail trade, wholesale trade, construction,
transportation, communications and utilities, mining, finance, insurance, and
real estate. Annual estimates form the second tier of GDP data and emanate form
sources such as IRS tax returns and smaller surveys of establishments. The Annual
Retail Trade Survey, for instance, forms one of the major components of the annual
estimates. The U.S. Census Bureau collects sales and end-of-year inventory data
from about 22,000 retail firms totaling $2 trillion of the $8.8 trillion GDP amount.
While considered reliable by many economists, sampling variability may introduce
errors into these annual estimates. Moreover, the Census Bureau imputes (substitutes
estimates for missing or clearly incorrect data) about 11 percent of reported
national annual retail sales because of accounting inconsistencies or raw survey
data errors. The third component of the GDP flows from quarterly estimates.
In the October 1993 SCB, Valliant described the reliability and accuracy of
the quarterly estimates of GDP, providing insights into the pre-1985 data in terms
of dispersion and bias. BEA followed a schedule that produced three successive
"current" estimates; advanced, preliminary, and final. BEA analysts developed
a dispersion and bias measure based on the difference between these three estimates.
Dispersion is the average of the absolute values of the revisions, or, the
difference between P, representing the percentage change in the current estimates,
and L representing the percentage change in the latest available estimates, divided
by n, representing the number of quarterly changes. Bias is the average of the
revisions. According to the October 1993 SCB, dispersion averaged 1.6 percent
from 1958 to 63 and dropped to 1.1 percent for 1968 to 1972. BEA stated that these
declines in dispersion correspond with more accurate initial and final estimates
subsequent to the late 1950s.For years after 1973 until 1991, the BEA concluded
that more accurate source data for preliminary and final estimates did not improve
reliability by much. BEA also determined that bias was not large enough from 1978
to 1991 to be significant under normality assumptions at the five- percent confidence
level. Overall, for the period beginning in 1978 and covering the 1985 data from
table 3-1, the BEA concluded there was no evidence of reliability increases. BEA
also questioned its own estimating procedures and, in particular, the use of disparate
sources of data, which may explain why reliability levels have not increased.
The NIPA framework also undergoes major updates referred to as comprehensive,
or benchmark revisions. Eleven of these have been completed including one in 1996
and most recently on October 28, 1999 that provided the data for tables 3-1 through
3-5.The major change encompassed a definitional change reflecting our evolving
economic system. Software became a business investment rather than just a "purchased
input," or the equivalent of raw material. Unless the company increased the price
of its product to cover software purchases, no impact registered in the GDP. With
this benchmark revision, the Census Bureau increased the 1996 estimate by $115
billion, or 1.5 percent--the amount of software investments made in that year.
Another change involved the Census Bureau's interpretation of the value of "unpriced"
banking services such as ATM (automatic teller machine) contributions to an establishment's
productivity. Previously, banking service productivity relied only on an index
constructed from labor input. Economists argued that this ignored productivity
gains from technological improvements such as ATMs and electronic banking. The
BLS developed a productivity based instead of bank transactions, and this was
used in the 1999 revision. For more detail, readers should refer to Moulton and
Seskin (1999).
Sources of Error for GDP Estimates
The GDP estimates can contain several kinds of error. One source of error arises
from estimates based on preliminary or incomplete tabulations of source data or
BEA judgment in the absence of data. Errors may also arise because of sampling
errors and biases in monthly, quarterly, annual, or periodic tabulations. Another
source of potential error may arise when data are seasonally adjusted. Readers
should refer to the October 1993 SCB issue for more detail (Young 1993).
NIPA and Transportation-Related Final Demand
For table 3-2, transportation-related final demand (TRFD) is from NIPA reported
in the SCB. It represents the sum of all consumer and government expenditures
for transportation purposes, plus the value of goods and services purchased by
business as investment for transportation purposes. Since TRFD includes only expenditures
on the final products of the economy, it is comparable to GDP and provides a measure
of transportation's importance from a consumption perspective.
NIPA tables report the composition of production and the distribution of incomes
earned in production. The totals of these produce a GDP estimate that should theoretically
be equal, but there is always a difference referred to as the "statistical discrepancy."
NIPA is based on four subaccounts of national economic activity. These include
1) the personal income and outlay account, 2) the gross savings and investment
account, 3) the government receipts and expenditures account, and 4) the foreign
transactions account.
Personal Consumption Expenditures (PCE) for transportation include 1) road
motor vehicles, such as new and used automobiles, and motorcycles; 2) motor vehicle
parts, such as tires, tubes, accessories; 3) motor fuels and lubricants; and 3)
transportation services, such as repair, greasing, washing, parking, storage,
rental, leasing, tolls, insurance, and purchased local and intercity transportation
services. Motor vehicles used primarily for recreation, boats, noncommercial trailers,
and aircraft are excluded.
Gross private domestic fixed investment in transportation includes private
purchases of transportation structures and equipment. Transportation structures
include railroads and petroleum pipelines. Transportation equipment consists of
automobiles, trucks, buses, truck trailers, aircraft, ships and boats, and railroad
equipment.
Goods and services that are counted as part of transportation-related exports
include 1) civilian aircraft, engines, and parts; 2) road motor vehicles, engines,
and parts; 3) passenger fares, including receipts of U.S. air and ocean/cruise
carriers for transporting non-U.S. residents between the United States and foreign
countries or between two foreign points; and 4) other transportation. The total
for road motor vehicles, engines and parts excludes boats, aircraft, and noncommercial
trailers. Other transportation includes 1) the freight revenues of U.S.-operated
ocean, air, and other carriers (e.g., rail, pipeline, and Great Lakes shipping)
for international transport of U.S. exports and for transporting foreign freight
between foreign points; 2) port expenditure receipts (representing payments for
goods and services purchased in the United States by foreign-operated carriers);
and 3) receipts of U.S. owners from foreign operators for the charter of vessels
and rental of freight cars and containers.
Goods and services that are counted as part of transportation-related imports
include 1) civilian aircraft, engines, and parts; 2) road motor vehicles, engines,
and parts; 3) passenger fares, including payments to foreign air and ocean/cruise
carriers for the transportation of U.S. residents between the United States and
foreign countries or between two foreign points; and 4) other transportation.
The total for road motor vehicle, engines and parts excludes boats, aircraft,
and non-commercial trailers. Other transportation includes 1) freight revenues
of foreign-operated ocean, air, and other carriers (e.g., rail, pipeline, and
Great Lakes shipping) for international transport of U.S. imports and for the
transportation of foreign freight between foreign points; 2) port expenditure
receipts (representing payments for goods and services purchased in foreign countries
by U.S.-operated carriers); and 3) payments to foreign owners from U.S. operators
for the charter of vessels and rental of freight cars and containers.
Transportation-related government purchases include federal, state, and local
purchases of transportation services, and government expenditures on transportation-related
structures and equipment. Federal, state, and local purchases represent the sum
of consumption expenditures and gross inventory. Defense-related purchases include
expenditures on the transportation of materials (care and movement of goods by
water, rail, truck, and air); the rental of trucks and other transportation equipment
and warehousing fees; and travel of persons (care and movement of Department of
Defense military civilian employees), including tickets for all modes of travel,
per diem, taxi fares, automobile rental, and mileage allowances for privately
owned vehicles.
Further References
This data source and accuracy statement is based on several papers that have
appeared in the SCB. Data users who desire more methodological detail can refer
to the list of references at the end of this chapter.
TABLE 3-6. National Transportation and Economic Trends
The Statistical Abstract of the United States published by the U.S. Department
of Commerce, Census Bureau, is the source of the population data. The Current
Population Reports are the source of the Abstract's data that are collected through
the Current Population Survey (CPS). This is a monthly survey administered by
the Census Bureau of a scientifically selected sample representative of the noninstitutional
civilian population in 754 areas covering every state and the District of Columbia.
Like other surveys, the CPS is subject to sampling error. Readers should note
that estimates based on the CPS may not agree with census counts because different
procedures are used. Changes in the CPS also mean that annual comparisons must
be made with caution. For instance, in 1994, the CPS methodology was dramatically
changed, and the estimates began to incorporate 1990 census population controls,
adjusted for the estimated undercount.
Industrial production data come from the Industrial Production Index, produced
by the Board of Governors of the Federal Reserve System and published in the Economic
Report of the President. For annual figures, individual industrial production
(IP) indexes are constructed from a variety of sources, including the quinquennial
Censuses of Manufactures and Mineral Industries; the Annual Survey of Manufactures,
prepared by the Census Bureau; the Minerals Yearbook, prepared by the U.S. Department
of the Interior; and publications of the U.S. Department of Energy. The Federal
Reserve Board (FRB) uses these data in a modeling framework to produce estimates
of industrial production. Below are brief discussions on three major sources for
the IP indexes; the survey of manufactures, the census of manufactures, and the
electric utility survey.
Annual Survey of Manufacturers
The Census Bureau conducts a mail survey of approximately 55,000 manufactures
with three different sample strata. The sampling frame is based on previously
surveyed firms and is updated annually based partially on IRS administrative records
and other sources. Large manufactures (shipments > $500 million, and > 250
employees), some computer manufacturing firms, and all remaining firms with at
least 250 employees are selected. Establishments with employment generally ranging
from 20 to 250 employees are sampled with a probability proportional to a composite
measure of establishment size. Approximately 5,000 of the smallest firms (5 to
20 employees) are also sampled and receive a shorter survey instrument. Additional
information on the survey, readers should refer to www.census.gov/econ/www/ma0300.html.
Census of Manufacturers
The Census of Manufactures collects data through mail surveys from approximately
237,000 multiunit and single-unit firms with a minimum payroll figure. This census
is supplemented by IRS administrative data from over 142,000 firms not contacted
by mail. For additional information on the census, readers should refer to www.census.gov/econ/www/ma0100.html.
Electric Utility Survey
Since 1971, the FRB has conducted the Monthly Survey of Industrial Electricity
Use based on responses from utilities and manufacturing and mining firms that
are cogenerators. This survey is the basis for estimates of the amount of electricity
power used by 120 industrial sectors. More than 40 industrial production series
estimates are based on data from this survey and compose 28 percent of the Industrial
Production Index in 1994 value-added proportions.
Survey responses are voluntary and are gathered from a panel of 175 utilities
and 186 cogenerating companies with a monthly response rate near 95 percent. In
1992, an additional 71 new cogenerators joined the panel. This resulted, according
to an FRB statistical analysis, in a decrease of the standard deviation of errors
for electricity growth rates from 3.0 to 1.9 percentage points. Overall, the estimates
for total power use produce a standard error of about 0.5 percentage points. The
panel accounts for approximately 73 percent of industrial electric power use in
the United States.
The Survey of Current Business, published by the U.S. Department of Commerce,
Bureau of Economic Analysis, is the source of GDP estimates. Readers should refer
to the source and accuracy statement for tables 3-1 through 3-5 for information
on GDP estimates.
TABLE 3-7. Passenger and Freight Transportation Expenditures
Detailed information from the source was not available at the time of publication.
Readers should contact the Eno Transportation Foundation, Inc. directly for information
about methodologies and reliability.
TABLE 3-8. Sales Price of Transportation Fuel to End-Users
The U.S. Department of Energy, Energy Information Administration's (EIA's)
Annual Review 2000, tables 5.20 and 5.21, provided price data, except for railroad
fuel. Pre-1981 data were reported by the EIA from Bureau of Labor Statistics reports.
Beginning in 1983, the EIA administered a series of surveys to collect data on
petroleum prices, market distribution, supply, and demand. The EIA-782 series
encompasses three surveys: 1) Form EIA-782A, Refiners'/Gas Plant Operators' Monthly
Petroleum Product Sales Report; 2) Form EIA-782B, Resellers'/Retailers' Monthly
Petroleum Product Sales Report; and 3) Form EIA-782C, Monthly Report of Prime
Supplier Sales of Petroleum Products Sold for Local Consumption.
EIA developed a method for comparing data from the new surveys with older information
gathered by various methods. As a result, a number of adjustment factors were
developed and used to "backcast" price estimates. Readers who require a more detailed
description of this methodology should refer to EIA's petroleum data publications
web page (www.eia.doe.gov/oil_gas/petroleum/pet_frame.html)
and the explanatory notes section.
Changes in sample elements or collection methods may affect data continuity.
Two regulatory changes affected data collection in October 1993.The Clean Air
Act Amendments of 1990 required that oxygenated gasoline be sold in the winter
months in ozone nonattainment areas. Thus, the EIA-782 forms were modified to
collect information on fuels divided among conventional, oxygenated, and reformulated
categories. Second, requirements for the production and selling of low-sulfur
diesel were required and necessitated the separation of diesel fuel into high-
and low-sulfur categories. Moreover, surveys prior to October 1993 did not include
propane. The EIA followed several different sampling designs during two periods
in the 1980s and thus, there may be some price estimate discontinuity for periods
between December 1983 and January 1984 as well as between August and September
of 1988.
Data Collection
The 782 series occurs on a monthly schedule via mail. The 782A and 782C surveys
reflect a census of about 115 and 190 firms, respectively. The 782B samples about
2,000 firms. The EIA first stratifies by sales volume for the form 782B survey
to ensure that dealers with 5 percent or more of the market are captured with
certainty. The remaining elements of the frame were assigned a probability of
selection to form a 2,200 firm survey. These "noncertainty" companies were poststratified
by geographic area and type of sales category.
Data Reliability
EIA has studied its sampling effects on reliability and determined that the
sample size of 2,000 should yield a less than 1-percent price coefficient of variation
in its estimates. Errors can arise because of nonresponse, but an EIA official
indicated that the response rates for the 1997-1999 782A, B, and C surveys averaged
95 percent, 86 percent, and 96 percent, respectively. Because survey data invariably
contain incomplete data (because of reporting errors or nonresponse), EIA estimates
or "imputes" missing data. Readers requiring imputation algorithms should refer
to the 782 series explanatory notes referred to above.
TABLE 3-9. Price Trend of Gasoline v. Other Consumer Goods and Services
Data in this table were reproduced from the American Petroleum Institute's
(API) Basic Petroleum Data Book. API noted that data reported prior to 1981 was
obtained from Platt's Oil Price Handbook and Oilmanac. Platt's is part of Standard
and Poor's, and an independent third party organization that tracks the petroleum
industry. Platt's reported the retail price of gasoline based on telephone interviews
with gas stations in 55 cities. More detailed historical information on their
data collection methods could not be ascertained and the data's reliability is
uncertain. API reported the Bureau of Labor Statistics (BLS) as its data source
for 1981 to 1998 retail gasoline prices. The remainder of this section discusses
the BLS Consumer Price Index (CPI) data collection and estimation methods used
to derive the average retail price of gasoline.
BLS uses the CPI as a measure of average price changes paid by urban consumers
for a fixed basket of goods and services. BLS estimates the CPI with a survey-based
approach. Survey results define a categorization of goods and services, a representative
sample of items to track, and weights according to the consumption of an average
consumer during a base period.
Sample Design
BLS relies on two sampling frames for their CPI estimates. One represents the
universe of retail outlets from which households may purchase defined groups of
commodities and services including gasoline. A second represents households across
urban areas. Moreover, the household frame is based on an "urban-consumer" population
and consists of households in Metropolitan Statistical Areas (MSA's) and in urban
places with more than 2,500 inhabitants. This "all urban" CPI (CPI-U) provides
the estimates for retail gasoline prices shown in table 3-9.Thus, this frame does
not represent non-urban consumers.
For the retail outlet sampling frame, BLS relies on the Point-of-Purchase Survey
(CPOPS) conducted by the Census Bureau in 94 Primary Sampling Units (PSUs) identified
by BLS. PSUs are based on urban counties, groups of contiguous urban counties,
or MSAs. For the household sample, a noncompact clustering procedure was employed
which dispersed households evenly within a Census enumeration district (ED). More
detailed sampling design information can be found in BLS's Handbook of Methods
at http://stats.bls.gov/opub/hom/homhome.htm.
Prices for the goods and services used to calculate the CPI are collected in
91 PSUs located in 85 urban areas throughout the country. The sample size for
the CPOPS totals about 21,000 retail and service establishments-supermarkets,
department stores, gasoline stations, hospitals, etc. Food, fuels, and a few other
items are priced monthly in all 85 locations. BLS field representatives collect
all price information through visits or telephone calls in the household surveys.
Price changes are computed based on a sample of outlets selected from locations
identified by consumers. Specific sample items are then selected from each sample
outlet to ensure that the market basket is representative of where households
shop.
Estimation
BLS routinely updates its price estimates for specific items among the collection
of goods and services, for example, a new car model year. BLS employs three techniques
to produce new price estimates. First, an item that is directly comparable to
the previous discontinued good will be used to provide a price estimate. However,
a substitute item may be inappropriate when goods change slightly in their characteristics.
BLS relies on Hedonic regression modeling as a second "quality adjustment" for
price estimates. This statistical technique can model the importance of various
quality characteristics that add value to a particular good (the fiber content
and construction of apparel products for instance). A researcher can estimate
a Hedonic regression model that identifies the factors most important is determining
the price of a good, and BLS field representatives will note these in their data
collection. Imputation is a third quality adjustment used for "noncomparable"
substitutions where BLS estimates the price change from previous averages. Detailed
algorithms can be found in chapter 17 of the BLS Handbook of Methods at http://stats.bls.gov/opub/hom/homhome.htm.
Effective January 1999, BLS began using a new formula for calculating the basic
components of the Consumer Price Index for all Urban Consumers (CPI-U) and the
Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). The
new formula, the geometric mean estimator, is used in index categories that comprise
approximately 61 percent of total consumer spending represented by the CPI-U.
Based on BLS research, it is expected that use of the new formula will reduce
the annual rate of increase in the CPI by approximately 0.2 percentage point per
year. Additional information on this change was published in the April 1998 CPI
Detailed Report and is available on the Internet at http://stats.bls.gov/cpihome.htm.
Accuracy
One of the CPI's limitations is that it represents price movements for urban
residents and may not correctly represent nonurban consumption patterns. The CPI
may also contain sampling error because it is estimated from a sample of consumer
purchases. Nonsampling error may occur if respondents provide BLS field representatives
with inaccurate or incomplete information. Another potential source of error identified
by BLS may occur because of a time lag between the Point-of-Purchase Survey and
the initiation of price collection for commodities and services at resampled outlets.
Because of the time lag, the products offered by the outlet at the time pricing
is initiated may not coincide with the set from which the CPOPS respondents were
purchasing.
The CPI is also subject to response error when data are not collected because
of non-response. BLS established a nonresponse auditing program in 1986.It reported
that response rates in 1990 for transportation commodities and services were above
90 percent.
Bias
Four categories of bias were identified in the BLS report, Measurement Issues
in the Consumer Price Index, published in 1997.First, because of the fixed-weight
nature of the index, the CPI creates substitution bias by placing too much weight
on items measured in previous surveys from which consumers may have shifted away.
Second, the study found that the index did not account for consumers switching
to discount stores. Third, a quality change bias was also identified when the
differences between goods priced in two different periods cannot be accurately
measured nor deduced from the accompanying price difference between the goods.
Finally, the report noted that the CPI also had a new product bias because the
index inadequately reflected consumer value of products introduced into the market.
The commission concluded that the CPI overstated the true cost-of-living change
by 1.1 percentage points per year.
TABLE 3-10. Producer Price Indices for Transportation Services
TABLE 3-11. Producer Price Indices for Transportation Equipment
Data shown in these tables are drawn from annual issues of The Supplement to
Producer Price Indexes published by the Bureau of Labor Statistics (BLS) in the
U.S. Department of Labor. These indexes represent a measure of outputs in all
goods-producing American industries as well as partial coverage of service industries
including transportation. BLS defines a price as the net revenue accrued to a
specified production establishment from a specified kind of buyer for a specific
product shipped under specific transaction terms on a specified day of the month.
BLS collects this data series through surveys of a sample of establishments that
report their prices from economic transactions.
Data Collection
A BLS field economist visits an establishment or cluster of establishments
selected for price sampling. The economist uses a disaggregation procedure to
select a sample of transactions from all the establishment's revenue-producing
activities. This disaggregation procedure assigns a probability of selection to
each shipping or receipt category proportionate to its value within a reporting
unit. In most cases, the final price index produced by the BLS requires that 1)
there are at least three different respondents to a survey, 2) at least two reporting
units provide price information in a given month, and 3) no single respondent
accounts for 50 percent or more of the weight for a given item.
BLS regional offices review field data for consistency and completeness. The
national office then conducts a final review and a survey is then tailored specifically
to establishments or clusters of establishments. BLS refers to these as repricing
schedules and sends them to reporting establishments on a regular basis. Most
prices refer to a reporting schedule on a particular day of the month, usually,
the first Tuesday or the 13th of a month.
Estimation
BLS collects prices for over 100,000 items. It utilizes several different weighting
schemes for the numerous indexes produced because some products will have a greater
effect on the movement of groupings of individual products. BLS utilizes the net
output of shipment values as weights for the 4-digit SIC industries. Net output
values include only shipments from establishments in one industry to other industry
establishments and, thus, differ from gross shipment values. The latter would
include shipments among establishments in the same industry, even if those establishments
are separate firms. BLS also makes seasonal adjustments if statistical tests and
economic rationale justify them, and imputes data when a participating company
does not deliver a price report. BLS bases the missing price estimation on the
average of price changes for similar products reported by other establishments.
Accuracy
As in all surveys, the accuracy of producer price indexes depends on the quality
of information voluntarily provided by participating establishments. One of the
accuracy concerns of BLS revolves around the preferred use of realistic transaction
prices (including discounts, premiums, rebates, allowances, etc.) rather than
list or book prices. Before BLS fully changed its data collection method in 1986,
a survey indicated that about 20 percent of traditional commodity indexes were
based on list prices. The newer and more systematic methodology decreased the
use of list prices. BLS documentation (available at http://stats.bls.gov/opub/hom)
provided no more details on sampling error, response rates, or the availability
of generalized variance parameters or techniques for estimating them.
TABLE 3-12. Personal Expenditures by Category
TABLE 3-13. Personal Consumption Expenditures on Transportation by Subcategory
Data used in these tables are from the Bureau of Labor Statistics, Annual Report
of Consumer Expenditure Survey. The Consumer Expenditure Survey (CEX) collects
information from U.S. households and families on their buying habits (expenditures),
income, and consumer characteristics. The strength of the survey is that it allows
data users to relate the expenditures and income of consumers to the characteristics
of those consumers. BLS uses 11 standard characteristics to classify consumers,
including income, before-tax income class, age, size of the consumer unit, composition
of the consumer unit, number of earners, housing tenure, race, type of area (urban
or rural), region, and occupation.
The CEX is a national probability sample of households. The sampling frame
(i.e., the list from which housing units are chosen) for this survey is generated
from the 1990 census 100-percent detail file, which is augmented by a sample drawn
from new construction permits. Coverage improvement techniques are also utilized
to eliminate recognized deficiencies in the census.
Data Collection
The current survey consists of two separate surveys (Interview and Diary),
each utilizing a different data collection technique and sample. Data is collected
for each survey from approximately 5,000 households. In the Interview survey,
each consumer unit (CU) in the sample is interviewed every three months over five
calendar quarters. The interviewer uses a structured questionnaire to collect
both the demographic and expenditure data in the Interview survey. The interviewer
collects the demographic data in the Diary survey whereas the respondent enters
the expenditure data on the diary form. Both surveys accept proxy responses from
any eligible household member who is at least 16 years old if an adult is not
available after a few attempts to contact that person. The respondent family completes
the Diary (or recordkeeping) survey at home for two consecutive one-week periods.
A reinterview program for the CEX provides quality control. The program provides
a means of evaluating individual interviewer performance to determine how well
the procedures are being carried out in the field. A member of the supervisory
staff conducts the reinterview. Subsamples of approximately 6 percent of households
in the Interview survey and 17 percent in the Diary survey are reinterviewed on
an ongoing basis. A new diary form with more categories and expanded use of cues
for respondents was introduced in 1991, based on results from earlier field and
laboratory studies.
Estimation
Missing or invalid data on demographic or work experience are imputed. No imputation
is done for missing data on expenditures or income. Selected portions of the Diary
data are also adjusted by automated imputation and allocation routines when respondents
report insufficient detail to meet publication requirements. These procedures
are performed annually on the data. The imputation routines assign qualifying
information to data items when there is clear evidence of invalid nonresponse.
The statistical estimation of the population quantities of interest, such as
the average expenditure on a particular item by a CU or the total number of CUs
in a particular demographic group, is conducted via a weighting scheme. Each CU
included in the survey is assigned a weight that is interpreted as representing
the number of similar families in the universe of interest, the U.S. civilian
noninstitutional population. Readers should refer to http://stats.bls.gov/opub/hom/homch16_c.htm
for the detailed weighting method.
Beginning with 1997 data, BLS introduced a new calibration method to compute
weights in the Consumer Expenditure Survey. The weights are calculated using a
model-assisted, design-based regression estimator.
Accuracy
The Consumer Expenditures Survey is a sample survey and hence is subject to
two types of errors, nonsampling and sampling. Nonsampling errors can be attributed
to many sources, such as differences in the interpretation of questions, inability
or unwillingness of the respondent to provide correct information, mistakes in
recording or coding the data obtained, and other errors of collection, response,
processing, coverage, and estimation for missing data. The full extent of nonsampling
error is unknown. Sampling errors occur because the survey data are collected
from a sample and not from the entire population. Tables with coefficients of
variation and other reliability statistics are available on request from the national
office. However, because the statistics are shown at the detailed item level,
the tables are extensive.
TABLE 3-14. Cost of Owning and Operating an Automobile
Your Driving Costs produced by the American Automobile Association (AAA) provided
the data for this table. Prior to 1985, the cost figures are for a mid-sized,
current model, American car equipped with a variety of standard and optional accessories.
After 1985, the cost figures are for a composite of three current model American
cars:
- A 1999 Chevrolet Cavalier LS,
- A 1999 Ford Taurus GL, and
- A 1999 Mercury Grand Marquis GS.
Thus, the estimates are not reliable estimates for all cars.
Fuel costs were based on an average price of $1.34 per gallon of regular unleaded
gasoline, weighted 20 percent full-serve and 80 percent self-serve. Insurance
figures were based on personal use of vehicles driven less than 10 miles to or
from work, with no young drivers. Normal depreciation costs were based on the
vehicle's trade-in value at the end of four years or at 60,000 miles. American
Automobile Association (AAA) analysis covers vehicles equipped with standard and
optional accessories, including automatic transmission, air conditioning, power
steering, power disc brakes, AM/FM stereo, driver-and passenger side air bag,
anti-lock brakes, cruise control, tilt steering wheel, tinted glass, emission
equipment and rear window defogger.
TABLE 3-15a & 3-15b. Average Passenger Fare (Current and chained 1996
dollars)
TABLE 3-18. Total Operating Revenues
Air
The U.S. Department of Transportation, Bureau of Transportation Statistics
(BTS), Office of Airline Information, reports passenger fares and operating revenues
in its publication Air Carrier Financial Statistics. These numbers are based on
100 percent reporting by large certificated air carriers. Minor errors from nonreporting
may occur but amount to less than one percent of all passenger or freight activity.
The figures do not include data for all airlines; such as most scheduled commuter
airlines and all nonscheduled commuter airlines.
Class I Bus
Class I passenger motor carriers are required to report financial and operating
information to BTS using form MP-1.(Prior to 1996, Class I carriers were required
to report to the Interstate Commerce Commission.) Class I passenger motor carriers
are defined as those having annual gross operating revenues, as adjusted for inflation,
of $5,000,000 or more. This table does not include Class I carriers whose data
had not been received at the time of publication. Thus, these data do not represent
total Class I passenger motor carrier activity.
Transit
The American Public Transit Association (APTA) reports these figures, which
are based on the annual National Transit Database report published by the USDOT,
Federal Transit Administration (FTA).Section 15 of the Federal Transit Act requires
federally funded transit agencies to provide detailed financial and operating
data including capital expenditures, revenues and expenses. These data are generally
considered accurate because the FTA reviews and validates information submitted
by individual transit agencies. Reliability may vary because some transit agencies
cannot obtain accurate information or misinterpret certain data definitions. APTA
conservatively adjusts FTA data to include transit operators that do not report
to the database(private and very small operators and rural operators).
Rail
Data are from Railroad Facts published annually by the Association of American
Railroads (AAR). AAR figures are based on 100-percent reporting by all nine Class
I railroads to the Surface Transportation Board (STB) via Schedule 700 of the
R1 Annual Report. STB defines Class I railroads as having operating revenues at
or above a threshold indexed to a base of $250 million in 1991 and adjusted annually
in concert with changes in the "Railroad Freight Rate Index" published by the
Bureau of Labor Statistics. In 1999, the adjusted threshold for Class I railroads
was $258.5 million. Declassification from Class I status occurs when a railroad
falls below the applicable threshold for three consecutive years. Although Class
I railroads comprise only 2 percent of the number of railroads in the country,
they account for over 71 percent of the industry's mileage operated, 91 percent
of total freight rail revenue, and 88 percent of railroad employment.
Intercity/Amtrak
Average passenger fare data are based on 100 percent of issued tickets, and
thus should be accurate. Created as a publicly-owned for-profit corporation, Amtrak
collects its own financial data and reports this information in its annual report.
Auditing should ensure the accuracy of the operating revenue figures.
Trucking and Courier Services (except air)
The Census Bureau's Transportation Annual Survey (formerly known as the Motor
Freight Transportation and Warehousing Survey) is the source of this information.
The sample survey represents all employer firms with one or more establishments
engaged primarily in providing commercial motor freight transportation or public
warehousing services. It excludes motor carriers that operate as auxiliary establishments
to nontransportation companies, as well as independent owner-operators with no
paid employees. Thus, the data do not represent the total trucking industry.
In 1999, Transportation Annual Survey was merged with the Census Bureau's Service
Annual Survey (SAS) and is the source of data for years 1998 and later. SAS provides
estimates of operating revenue of taxable firms and revenue and expenses of firms
exempt from federal income taxes for selected service industries. Unlike the Transportation
Annual Survey, the SAS is based on the North American Industry Classification
System (NAICS).
As with all sample surveys, two types of errors are possible: sampling and
nonsampling. Nonsampling errors may include response errors and mistakes in coding
or keying data. For additional information about the survey and data reliability,
the reader is referred to the Census Bureau website at www.census.gov.
Water (Domestic)
Eno Transportation Foundation, Inc. is the source of these data. Eno estimates
these figures by multiplying ton-mile figures by estimated revenue per ton-mile.
The U.S. Army Corps of Engineers reports the ton-mile figures in its publication
Waterborne Commerce of the United States, and the revenue per ton-miles figures
are estimated by Eno.
Oil Pipeline
Eno Transportation Foundation, Inc., publishes these data, which are based
on Federal Energy Regulatory Commission (FERC) data and reported by the Oil Pipeline
Research Institute for years 1977 to the present. FERC data originates from required
quarterly reports filed by pipeline companies. Prior to 1977, the data are based
on the former Interstate Commerce Commission data for regulated pipelines, and
estimated to be 16 percent of the total of nonregulated pipelines.
Gas Pipeline
These statistics originate from Gas Facts, published annually by the American
Gas Association (AGA).AGA data are based on gas utilities participation and reporting
to the Uniform Statistical Report and estimates for those companies not reporting
based on recent historical experience. Varying percentages of nonreporters from
year to year introduce minor reliability problems for time-series comparisons.
TABLE 3-19. Employment in For-Hire Transportation and Selected Transportation-Related
Industries
Employment data by industry are from the National Employment, Hours, and Earnings
estimates published by the Bureau of Labor Statistics (BLS), U.S. Department of
Labor. These estimates originate from the Current Employment Statistics (CES)
survey program. The CES is a monthly survey conducted by state employment security
agencies in cooperation with the BLS. The survey provides employment, hours, and
earnings estimates based on payroll records of nonfarm business establishments,
including government.
BLS uses a stratified sample based on a sector's employment size, or the degree
of variability among its establishments, or both. This ensures that BLS captures
a more representative survey from employers with large payrolls. Thus, large establishments
are certain of selection while smaller ones have less of chance.
Data Collection
Data are collected electronically from about two-thirds of the respondents
and by mail or fax from the remainder. The primary type of electronic reporting
is touch-tone phone self-response; others are computer-assisted phone interviews
and phone voice recognition technology. Increasingly, data are collected through
electronic data interchange from a small but growing number of companies that
have a large number of establishments across the country. Mail respondents submit
Form 790 to the BLS each month. It is then edited and returned to the respondent
for use again the following month. All firms with 250 employees or more are asked
to participate in the survey, as well as a sample of smaller firms.
Estimation
Employment estimates are made at what is termed the basic estimating cell level
and aggregated upward to broader levels of industry detail by simple addition.
Basic cells are defined by industry (usually at the 3- or 4-digit SIC level) and
are stratified within industry by geographic region and/or size class in the majority
of cases. Within the wholesale trade, retail trade, and services divisions, most
industries are stratified into three to five size classes (beginning in 1984).
Most national employment estimates are multiplied by bias adjustment factors
to produce the monthly published estimates. Bias adjustment factors are used primarily
to compensate for the inability to capture the entry of new firms on a timely
basis. New firms contribute a substantial amount to employment growth each year,
but there is a lag between the creation of a firm and its inclusion on the sample
frame (i.e., the Unemployment Insurance universe file). It is, therefore, necessary
to use modeling techniques to capture this segment of the population. BLS also
performs seasonal adjustments for certain SIC industries.
Accuracy
BLS does not publish data reliability information along with estimates. Instead,
it provides estimation formula and the necessary parameters so that users can
estimate standard errors. For additional information, see the "Explanatory Notes
and Estimates of Error" in the BLS monthly publication Employment and Earnings.
The CES survey, which began over 50 years ago, predates the introduction of
probability sampling as the internationally recognized standard for sample surveys.
Instead, a quota sample has been used since its inception. Quota samples are at
risk for potentially significant biases, and recently completed BLS research suggests
that, despite the large CES sample size, employment estimates based on that sample
at times diverge substantially from those that a more representative sample would
have been expected to produce. This leads to an over-reliance on bias adjustment
in the estimation procedure. Because bias adjustment is primarily based on past
experience, it is limited in its ability to accurately reflect changing economic
conditions on a timely basis.
Government Employment
The Office of the Secretary provides employment figures for the U.S. Department
of Transportation. State and local highway department employment figures are from
the' State and Local Government Employment and Payroll Estimates, published by
the U.S. Department of Commerce, Bureau of the Census. The data are for the 50
states and the District of Columbia. Employment and payroll data pertain to the
month of October. At present, data are collected for one pay period that includes
October 12 (regardless of the period's length) through the Public Employment Survey
(PES).
Employment refers to all persons gainfully employed by and performing services
for a government. Employees include all persons paid for personal services performed
from all sources of funds, including persons paid from federally funded programs,
paid elected officials, persons in a paid leave status, and persons paid on a
per meeting, annual, semiannual, or quarterly basis. Excluded from employment
statistics are unpaid officials, pensioners, persons whose work is performed on
a fee basis, and contractors and their employees.
The Census Bureau derives full-time equivalent(FTE) employment by summing the
number of full-time employees reported and converting the number of hours worked
by part-time employees to a full-time equivalent amount. Up until 1985 data, the
method used to calculate FTEs was based solely on payroll data. Effective with
1986 data, the annual employment survey started collecting data on the number
of hours worked by part-time employees in order to provide a more accurate representation
of full-time equivalent employment. No October 1985 FTE employment data are available.
Beginning in 1999, the Public Employment Survey (PES) was conducted using a
separate sample of approximately 11,000 government units to improve data accuracy
and survey efficiency. Government units meeting any of the following criteria
are included in the survey: 1) counties with populations greater than 100,000;
2) cities with populations greater than 75,000; 3) townships in New England and
Mid-Atlantic with populations greater than 50,000; 4) special districts with FTEs
greater than 1000; 5) independent school districts with enrollment greater than
10,000; and 6) all dependent and independent schools providing college level education.
In 1999, government units were sampled to obtain a relative standard error of
3 percent or less for FTE and total payroll for each of the states by type of
government groups.
Prior to 1993, the PES used a joint sample of approximately 24,000 units for
both employment and finance. From 1993 to 1998, the sample size was reduced to
around 14,000 units. The standard error for the PES prior to 1999 was designed
to be around 3 percent for major state- or county-level estimates of finance variables
(state-level for 1993-1998 and county-level prior to 1993).Employment estimates
are made using regression, except when the number of noncertainty cases contributing
to the estimate is less than 20, where a simple unbiased estimate is used.
TABLE 3-20. Employment in Transportation Occupations
TABLE 3-22. Median Weekly Earnings of Full-Time Wage and Salary Workers in
Transportation by Detailed Occupation
Employment by detailed transportation occupation data are from the Occupational
Employment Statistics (OES) survey, collected by the Bureau of Labor Statistics
(BLS).The OES is a periodic mail survey of nonfarm establishments that collects
occupational employment data on workers by industry. The OES program surveys approximately
725,000 establishments in 400 detailed industries. The average response rate for
the last three years, according to a BLS official, averaged about 70 percent.
The sample is selected primarily from the list of business establishments reporting
to the state unemployment insurance program. The OES sample initially stratifies
the universe of establishments by three-digit industry code and size- class code.
Establishments employing 250 employees or more are sampled with certainty. Establishments
employing fewer than 250 employees but more than 4 employees are sampled with
probability proportional to the size class employment within each three-digit
industry. Establishments employing four or fewer employees (i.e., size class 1
establishments) are not sampled. Instead, the employment for these establishments
are accounted for by assigning a larger sampling weight to establishments employing
five to nine employees (i.e., size-class 2 establishments).Within each three-digit
industry/size- class cell, establishments are systematically selected into the
sample through a single random start.
Data Collection
Employers are the source of occupational data. Within establishments, the main
source of occupational data reported by respondents is personnel records. Data
are collected from respondents primarily by mail. Occasionally, visits are made
to large employers and to other respondents who indicate particular difficulty
in completing the questionnaires. Ordinarily, two mailings follow the initial
mailing. After the third mailing, a subsample of the remaining nonrespondents
is drawn and contacted by telephone. The OES survey follows a 3-year cycle. Three
surveys are conducted alternately for manufacturing, nonmanufacturing, and the
balance of nonmanufacturing industries.
Estimation
During the sample selection process, each sampled establishment is assigned
a sampling weight that is equal to the reciprocal of its probability of selection.
For example, if an establishment on the sampling frame had a 1 in 10 chance of
being selected into the sample, then its sampling weight is 10. For establishments
that did not respond to the survey, a nonresponse adjustment factor is calculated
and applied against the sampling weights of the responding establishments within
each state/3-digit industry/size-class cell. Multiplying these adjustment factors
by sampling weights increases the weight of the responding establishments so they
can account for the missing employment data of the nonresponding establishments.
Accuracy
The OES survey uses a subsample replication technique to estimate variances
in occupational employment at the 3-digit industry/size-class level. For additional
information on occupational employment estimates and measurements of sampling
error associated with the estimates, the reader is referred to http://stats.bls.gov/oeshome.htm.
TABLE 3-21. Average Wage and Salary Accruals per Full-Time Equivalent Employee
by Transportation Industry
TABLE 3-23. Total Wage and Salary Accruals by Transportation Industry
The Survey of Current Business (tables 6.3c and 6.6c) published by the U.S.
Department of Commerce, Bureau of Economic Analysis, is the source of transportation
wage and salary data. These estimates are based on BLS tabulations of employee
wages that are covered by State unemployment insurance. As a component of the
income side of National Income and Product Account, wages and salaries comprise
part of the GDP calculation. These data reflect the monetary remuneration of employees
in terms of wage accruals less disbursements. It is defined as the difference
between wages and salaries on a "when-earned" basis, or accrued, and wages and
salaries on a "when-paid," or disbursed basis. This computation was instituted
in 1992 because a significant portion of bonus payments were missed in previous
calculations. Readers should also refer to the earlier discussion of GDP methods
and reliability for more detail.
TABLE 3-24. Labor Productivity Indices for Selected Transportation Industries
The Bureau of Labor Statistic's (BLS) Industry Productivity Measures is the
source of transportation labor productivity data. BLS develops industry productivity
measures based on various data sources.
For rail, BLS uses freight ton-mile and passenger miles that are collected
by the Surface Transportation Board (STB), the Association of American Railroads
(AAR), and Amtrak. BLS also aggregates four different air transportation outputs
to form a single productivity index: domestic passenger-miles, domestic freight
ton-miles, international passenger-miles, and international freight ton-miles.
Air transportation data come from Air Carrier Traffic Statistics and Air Carrier
Financial Statistics, published by the U.S. Department of Transportation, Bureau
of Transportation Statistics. For petroleum pipeline, BLS relies on data from
the Association of Oil Pipelines and derived an output index based on trunkline
barrel-miles. A barrel-mile is one barrel of petroleum moved through one mile
of pipeline.
Estimation
BLS generally calculates labor productivity by dividing an index of output
(in this case, ton-miles) by an index of hours. Output is derived with a weight
adjusted Tornqvist formula that produces an output ratio for one year. BLS then
combines these in a series that produces a chained output index. The hour indexes
are developed from data in BLS's Current Employment Statistics (CES; see discussion
above for table 3-12) and are the results of dividing the annual aggregate hours
for each year by a base-period figure. Readers who need more detail, such as mathematical
specifications or equations, should refer to Kunze and Jablonski (Kunze and Jablonski
1998) or call the Office of Productivity and Technology at BLS.
Accuracy
BLS provides no measures of reliability. However, BLS makes an assumption that
transportation outputs should be measured using the production of passenger-miles
or freight-miles. Another school of thought might assume that many transportation
firms or facilities are actually providing capacity rather than actual use. Thus,
an argument can be made that productivity should be based on capacity rather than
use. In fact, this is how BEA measures transportation output. To evaluate the
BLS assumption, one study compared the two approaches by examining the different
growth rates produced by BLS and BEA and found that in 25 of 35 service industries,
the differences are within one percentage point. For transportation, differences
in growth rates across BLS and BEA estimates were two percentage points or less
(Kunze and Jablonski 1998).
Beginning with 1997 data, the indices for bus and petroleum pipelines did not
meet BLS publication standards and are considered less reliable than those for
other modes. These industries had between 14,000 and 15,000 employees, far below
the 50,000-employee threshold established for transportation industries by BLS.
However, they both met a basic test of variability of the annual percent changes
in the output per hour measure.
GOVERNMENT REVENUES AND EXPENDITURES
TABLE 3-25a &3-25b. Federal, State, and Local Government Transportation-Related
Revenues and Expenditures, Fiscal Year (Current and constant 1996 dollars)
TABLE 3-26a & 3-26b. Federal Transportation-Related Revenues, Fiscal Years
(Current dollars and constant 1996 dollars)
TABLE 3-27a & 3-27b. Federal Transportation-Related Expenditures by Mode,
Fiscal Year (Current and constant 1996 dollars)
TABLE 3-28. Cash Balances of the Transportation-Related Federal Trust Funds,
Fiscal Year
The main sources for federal-level data are the Budget of the United States
Government and the Appendix to the Budget. These data are the actual
figures as reported for the various transportation-related programs in the appendices
of each year's budget document.1 The figures are consistent from year
to year and follow the definitional structure required by the Office of Management
and Budget (OMB).
1 The federal budget is broken down into 20 functional categories,
of which one is transportation (function 400). Function 400 is not tied to any
one department or agency, but instead aggregates transportation functions wherever
in the federal government they occur. Thus, the transportation function may include
many activities, such as highway construction and safety, airways and airports,
maritime subsidies, U.S. Coast Guard operations, railroads, and mass transit.
It also covers grants-in-aid programs to support state and local activities. A
good summary of the federal budget process can be found in Stanley E. Collender,
The Guide to the Federal Budget, Fiscal Year 1996 (Washington, DC: Urban
Institute Press. 1995).
Primary sources for state and local transportation-related revenues and expenditures
data are censuses and surveys collected by the U.S. Census Bureau. All units of
government are included in the Census of Governments, which is taken at five-year
intervals for years ending in 2 or 7, and these data are full counts, which are
not subject to sampling error.
State and local government data for noncensus years are obtained by annual
surveys, which are subject to sampling error. For U.S. totals of local government
revenues and expenditures in this report, sampling variability is less than 3
percent.
Federal figures in this report correspond to the federal fiscal year, which
begins on October 1, while state and local data are for fiscal years that generally
start in July. While this may create a small error in totals for any given year,
the data are suitable for illustrating trends in public transportation finance.
Programs terminated before 1985 are excluded from the tables. The totals for transportation
revenues and expenditures in this report are the sum of the Census Bureau's state
and local numbers plus the total of the federal numbers.
The source of the chained dollar deflators is The National Income and Product
Account Tables, Bureau of Economic Analysis, table 7.1, "Quantity and Price
Indexes for Gross Domestic Product." All inflation-adjusted data are for the base
year 1996, instead of 1992 as in previous editions of National Transportation
Statistics. Note that deflators used for the federal data differ from those
used for state and local data. Thus, if expenditures are totaled across different
levels of government in chained dollars before and after federal grant transfers,
the totals will not match.
Transportation Revenues
Transportation revenue estimates include transportation-related user charges,
taxes, or fees earmarked for transportation-related expenditures. Estimates include
transit fares from systems owned and operated by state and local governments,
including those systems operated under contract by a private firm under day-to-day
financial oversight by government.
Federal transportation revenues generally consist of trust-fund collections
from user charges, such as fuel taxes, vehicle taxes, registration and licensing
fees, and air passenger ticket taxes. Damage payments made by private parties
are deposited in the funds to reimburse the government for related fund expenditures.
The five transportation-related Federal trust funds are established by law:
- Highway Trust Fund (HTF), which includes both highway and transit accounts;
- Airport and Airway Trust Fund (AATF);
- Harbor Maintenance Trust Fund (HMTF);
- Inland Waterways Trust Fund (IWATF); and
- Oil Spill Liability Trust Fund (OSLTF).
Highway Revenues
The Highway Trust Fund (HTF) was established by the Highway Revenue Act of
1956. Highway Trust Fund revenues are derived from various excise taxes on highways
users (e.g., motor fuel, motor vehicles, tires, and parts and accessories for
trucks and buses) and interest earned on balances. The Transportation Equity Act
for the 21st Century (TEA-21), which was enacted in June 1998, made
important changes to the Federal Highway Trust Fund legislations (FHWA, 1999):
- extension of deposit provisions of almost all highway user taxes through September
30, 2005;
- after September 30, 1998, the HTF can no longer earn interest on balances,
and the balance in the highway account would be transferred to the general fund;
- TEA-21 keys Federal-aid highway funds to receipts of the Highway Account of
the HTF; and
- the Transit Account share of fuel tax rose from 2 cents per gallon to 2.86
cents per gallon.
The Excise tax on gasoline is the most important source of the HTF revenues
and has changed five times since 1985. It increased from 9 cents per gallon in
1985 to 9.1 cents per gallon on January 1, 1987; to 14.1 cents per gallon on December
1, 1990; to 18.4 cents per gallon on October 1, 1993; to 18.3 cents per gallon
on January 1, 1996; and to 18.4 cents per gallon on October 1, 1997 (FHWA, 1999).
Money paid into the fund is earmarked primarily for the Federal-aid Highway
program, which is apportioned to states for planning, constructing, and improving
the nation’s highway system, roads, and bridges. Effective April 1983, the Highway
Revenue Act of 1982 created the Mass Transit Account within the HTF.
Some portion of the HTF is dedicated to budget deficit reduction and the Leaking
Underground Storage Tank Trust Fund (LUSTTF). For example, 4.3 cents per gallon
of the federal excise tax on gasoline has been assigned to the general fund since
January 1, 1996, and 0.1 cents per gallon was apportioned to the LUSTTF since
October 1, 1997 (FHWA, 1999). These funds are not considered as transportation-related
in this report.
State and local highway revenues include state and local taxes on motor fuels,
motor vehicle licenses, and motor vehicle operator licenses, along with state
and local charges for regular toll highways and local parking charges. Regular
highway charges (revenues) include reimbursements for street construction and
repairs, fees for curb cuts and special traffic signs, and maintenance assessments
for street lighting, snow removal, and other highway or street services unrelated
to toll facilities. Local governments use special assessments and property taxes
that may be commingled with other local revenue in a general fund to finance local
road and street programs. Consistent with federal revenues, state and local transportation
revenues in this report do not include general funds that may be allocated to
transportation.
Transit Revenues
As mentioned above, the Highway Revenue Act of 1982 created the Mass Transit
Account within the HTF. Effective April 1983, the act provided one cent per gallon
of the federal excise tax on gasoline sales to be set-aside for the Mass Transit
Account to help finance transit capital projects. The rate was increased to 1.5
cents per gallon on December 1, 1990; to 2 cents per gallon on January 1, 1996;
and to 2.86 cents per gallon on October 1, 1997 (FHWA, 1999). Although highway
users pay these taxes, the funds are treated as federal transit revenues.
State and local transit revenues include revenues from operations of public
mass transportation systems (rapid transit, subway, bus, railway, and commuter
rail services), such as fares, charter fees, advertising income, and other operations
revenues. They exclude subsidies from other governments to support either operations
or capital projects.
Air Revenues
The Tax Equity and Fiscal Responsibility Act of 1982, as amended by Omnibus
Budget Reconciliation Acts of 1990 and 1993, the Small Business Job Protection
Act of 1996, and the Taxpayers Relief Act of 1997, provides for the transfer of
receipts received in the U.S. Treasury from the passenger ticket tax and certain
other taxes paid by airport and airway users to the Airport and Airways Trust
Fund (AATF). Effective October 1, 1997, the Taxpayers Relief Act of 1997 extends
aviation excise taxes for 10 years and includes the following major provisions
(FAA, 1999):
- retains existing freight weigh bill, general aviation fuel and gas taxes,
and a 6-dollar departure tax on domestic flights to and from Alaska and Hawaii;
- converts the 10 percent ad valorem tax on domestic passenger tickets to a
combination of ad valorem and flight segment tax over three years beginning October
1, 1997;
- imposes a new 7.5 percent tax on payments to airlines for frequent flyer and
similar awards by banks and credit card companies, merchants, frequent flyer program
partners—other airlines, hotels, or rental car companies and other businesses;
- increases the current 6-dollar international departure tax to 12 dollars per
passenger and adds a 12-dollar international arrival tax;
- lowers tax rates on flights to certain rural airports to 7.5 percent without
a flight segment component; and
- transfers revenues from the 4.3 cents-per-gallon aviation fuel taxes currently
dedicated to reduce the national U.S. deficit from the general fund to the AATF.
Most of this trust fund is used to finance the Federal Aviation Administration’s
(FAA’s) capital programs, namely, Facilities and Equipment; Research, Engineering,
and Development; and Airport Improvement Program. Within certain limits set by
Congress, some of the remaining money is used to cover FAA operation and maintenance
expenses. The portion of the FAA’s operation and Maintenance expenses not paid
from the trust fund revenues are financed by U.S. Treasury general funds.
State and local revenues from air transportation are derived from airport charges.
Beginning in 1992, local governments began collecting passenger facility charges
and spending these revenues (both subject to FAA approval) to finance capital
programs.
The collection of passenger facility charges was authorized by the Aviation
Safety and Capacity Expansion Act of 1990.2
2 Public Law 101-508, 104 Stat. 1388 (November 5, 1990).
Waterway and Marine Revenues
Federal water revenues come from four primary sources: the Harbor Maintenance
Trust Fund (HMTF), the Inland Waterways Trust Fund (IWATF), the Oil Spill Liability
Trust Fund (OSLTF), and tolls and other charges collected by the Panama Canal
Commission.
The Harbor Maintenance Trust Fund was established in accordance with the Harbor
Maintenance Revenue Act of 1986. Revenues for this fund are derived from receipts
of a 0.125 percent ad valorem user fee imposed on commercial users of specified
U.S. ports, Saint Lawrence Seaway tolls. On March 31, 1998, per a U.S. Supreme
Court ruling, the tax on exports was terminated (OMB, 2000). This fund is used
to finance up to 100 percent of the U.S. Army Corps of Engineers’ harbor operation
and maintenance (O&M) costs, including O&M costs associated with Great
Lakes navigational projects, and the fund fully finances the operation and maintenance
of the Saint Lawrence Seaway Development Corp.
The Inland Waterways Trust Fund was established by the Inland Waterways Revenue
Act of 1978 and amended by the Water Resources Development Act of 1986. The trust
fund has been in effect since fiscal year 1981. The sources for the fund are taxes
imposed on fuel for vessels engaged in commercial waterway transportation and
investment interest. From this tax of 24.3 cents per gallon, 4.3 cents goes for
deficit reduction, and a statutory maximum of 20 cents (raised to that level from
the previous maximum of 19 cents at the beginning of 1995) goes to the Trust Fund.
The funds are earmarked for financing one-half of the construction and rehabilitation
costs of specified inland waterway projects.
The Oil Spill Liability Trust Fund was established by the Omnibus Budget Reconciliation
Act of 1989. Revenues for this fund are raised through tax collection of 5 cents
on each barrel of oil produced domestically or imported (OMB, 1999). The resources
from this fund are used to finance oil pollution prevention and cleanup activities
by various federal agencies. For the U.S. Coast Guard, the fund finances oil spill
recovery and payment of claims. Beginning in 1997, the fund also finances the
annual disbursement to the Prince William Sound Oil Spill Recovery Institute.
The Panama Canal Commission was established by the Panama Canal Act of 1979
to manage, operate, and maintain the Panama Canal under the Panama Canal Treaty
of 1977. The treaty period ended on December 31, 1999, when the Republic of Panama
assumed full responsibility for the canal. During the treaty period, the commission
collected tolls and other revenues, which were deposited in the U.S. Treasury
in an account known as the Panama Canal Revolving Fund. Money from this fund was
used to finance canal operations and capital programs, which were reviewed annually
by Congress. The revenues reported under this category for FY 2000 are for the
first quarter (October 1999 – December 1999) of Panama Canal operations.
State and local water revenues are derived from canal tolls, rents from leases,
concession rents, and other charges for use of commercial or industrial water
transport and port terminal facilities and related services. Fees and rents related
to water facilities provided for recreational purposes, such as marina and public
docks, and toll ferries are not included.
Rail Revenues
There are no governmental transportation revenues for rail (Rail generates
fuel taxes that are designated for deficit reduction and, thus, are not considered
transportation revenues in these tables).
Pipeline Revenues
The Pipeline Safety Program is funded by user fees assessed on a per-mile basis.
The assessments are made on each pipeline operator regulated by the Office of
Pipeline Safety (OPS) of the Research and Special Programs Administration (RSPA)
in the U.S. Department of Transportation. There are no state and local revenues
for pipeline.
General Support Revenues
General support revenues come from the Emergency Preparedness Fund, which is
generated from fees paid by registered shippers of hazardous materials. RSPA administers
and distributes the revenues to states, territories, and tribes through the Hazardous
Materials Emergency Preparedness (HMEP) grant program, which is authorized by
Federal Hazardous Materials Transportation Law.
Transportation Expenditures
Expenditures, rather than obligations, are used in these tables because they
represent the final, actual costs to the government, by year, for capital goods
and operating services required by transportation programs. Obligations suggest
government commitment to future transportation expenditures, but do not indicate
when the funds will actually be disbursed or even if the amounts obligated will
be spent.
It is important to recognize that in some accounts in the Budget of the
United States Government, expenditures for a particular year understate total
government disbursements. This is because certain offsetting collections of fees
and assessments from the public are not treated as government revenues, but deducted
from disbursements to determine expenditures. These collections are those mandated,
by statute, to directly fund agency expenditures rather than be transferred to
the U.S. Treasury. For this reason, expenditures do not necessarily indicate how
much the federal government actually spends on transportation each year.
Highway Expenditures
Federal Highway Administration (FHWA) expenditures include funds for Federal
Aid Highways (financed from the HTF) and the Interstate Substitution and Railroad
Crossing Demonstration (financed from the general fund). The National Highway
Traffic Safety Administration (NHTSA) expenditures include: operations, research,
and highway traffic safety grants. Federal highway expenditures also include road
construction activities managed by the Department of the Interior's National Park
Service, Bureau of Indian Affairs, Bureau of Reclamation, and Bureau of Land Management;
the Department of Agriculture's Forest Service; the Department of Housing and
Urban Development; and other federal agencies.
State and local governments' highway expenditures reported by the Census Bureau
are generally slightly lower than those reported in FHWA's Highway Statistics
because the FHWA includes some highway expenditure data, such as law enforcement
activities and patrols, and policing of streets and highways not included in the
Census data. Box 3-1 outlines
the major differences in Census Bureau and FHWA calculation of state and local
highway transportation financial statistics.
Transit Expenditures
Federal expenditures include grants to states and local agencies for the construction,
acquisition, and improvement of mass transportation facilities and equipment and
for the payment of operating expenses. Several other items are also included:
Federal Railroad Administration (FRA) commuter rail subsidies related to the transition
of Conrail to the private sector; research and administrative expenses of the
Federal Transit Administration (FTA); and Federal interest payment contribution
to the Washington Metropolitan Area Transportation Authority (WMATA).
Air Expenditures
Federal expenditures reported here consist of all FAA expenditures, such as
those associated with constructing, operating, and maintaining the national air
traffic system; administration of the airport grant program; safety regulation;
and research and development. NASA expenses related to air transportation are
also included.
State and local expenditures for air include the operation and maintenance
of airport facilities, as administered by local airport and port authorities quasigovernment
agencies with responsibilities for promoting safe navigation and operations for
air modes.
Waterway and Marine Expenditures
Federal expenditures comprise those parts of the U.S. Coast Guard's expenses
that are transportation-related, such as aids to navigation, marine safety, and
marine environmental protection. All expenses of the U.S. Maritime Administration
are included, such as subsidies for construction and operation of vessels by U.S.-flag
operators, research and development, and training of ship officers. Also included
are those expenses of the U.S. Army Corps of Engineers for construction and operations
and maintenance of channels, harbors, locks and dams; protection of navigation;
the salaries and expenses of the Federal Maritime Commission; and the expenses
of the Panama Canal Commission. Expenditures of the Panama Canal Commission for
FY 2000 include outlays for the first quarter of operations, including severance
pay and accumulated leave. FY 2001 expenses are for the settlement of remaining
accident and contract claims against the Commission.
State and local governments incur water transportation expenditures by operating
and maintaining water terminal facilities within ports and harbors.
Rail Expenditures
Federal rail transportation expenditures include:
- expenses for rail safety enforcement;
- inspection and program administration;
- railroad research and development;
- financial assistance to states for planning, acquisition, rail facility construction,
and track rehabilitation with respect to low volume freight lines;
- grants to Amtrak, including funds to upgrade the high-speed line between Boston,
Massachusetts, and Washington, DC, owned by Amtrak (the Northeast Corridor Improvement
Program); annual appropriations to cover operating losses; and funds to invest
in new equipment and facilities;
- the purchase of redeemable preference shares for track rehabilitation and
line acquisition; and
- loan guarantee defaults for railroad rehabilitation and improvement and Conrail
labor protection.3
3 Funds in the Conrail Labor Protection Program were provided for benefits
to Conrail employees deprived of employment because of work force reductions and
other actions. This program no longer exists since Conrail has been returned to
the private sector. In 1988, the unobligated balances available from this program
were transferred to the USCG, and in 1990 they were returned to the U.S. Treasury.
The local rail freight assistance program, a program of FRA grants to state
governments, has had a 70:30 percent federal-state funding share since 1982.
Pipeline Expenditures
The Office of Pipeline Safety (OPS) reimburses state agencies up to 50 percent
of their costs to carry out state pipeline safety programs. Federal expenditures
are for the enforcement programs, research and development, and grants for state
pipeline safety programs.
General Support Expenditures
General fund expenditures include all of the expenses of the following agencies:
Office of Inspector General, National Transportation Safety Board, all expenses
of the Research and Special Programs Administration, (except pipeline expenditures)
and the Office of the Secretary of Transportation (except for payments to Air
Carriers and the Commission on Aircraft Safety).
Limitations of the Source Data Sets
The database covers civilian transportation-related activities of government
agencies including those of the U.S. Army Corps of Engineers and U.S. Coast Guard.
As mention earlier, federal government data are compiled for the federal fiscal
year, which begins on October 1, while state and local data are for fiscal years
that generally start in July except for
four states with other starting dates (Alabama and Michigan in October, New
York in April, and Texas in September). While this may create a small error in
totals for any given year, the data are suitable for illustrating trends in public
transportation finance.
Readers should note that state and local governments data for census years
are full counts and not subject to sampling errors, whereas the data for noncensus
years are estimated from annual surveys of the Bureau of the Census, which are
subject to sampling variability of less than three percent. The Census Bureau’s
database also does not include detailed modal information on interest earnings
and bond issue proceeds on the revenue side nor bond retirement and interest payments
on the expenditure side
Revenues
Transportation-related revenues like local government property taxes on vehicles,
equipment, and streets, and state income taxes to support rail and intercity bus
services are not covered because they are not shown in the source materials used
to compile the database. In addition, taxes collected from users of the transportation
system that go into the general fund are not included. For example, rail generates
fuel taxes that are designated for deficit reduction and hence are not considered
as transportation revenues. The portion of the Highway Trust Fund (HTF) that goes
to the general fund is not considered as transportation revenues.
Expenditures
It is important to recognize that in some accounts in the Budget of the
United States Government, expenditures for a particular year understate total
government disbursements. This is because certain offsetting collections of fees
and assessments from the public are not treated as government revenues, but deducted
from disbursements to determine expenditures. These collections are those mandated,
by statute, to be applied directly to finance agency expenditures rather than
being transferred to the Treasury.
In addition, the Census Bureau’s highway expenditures data do not include highway
law enforcement expenditures, which form a part of the state and local highway
expenditures published in the Highway Statistics. To maintain consistency
between the different modes regarding the types of expenditures included, these
additional data from the Highway Statistics report have not been used.
Data Adjustments
Revisions and corrections to previously published data have been made in most
cases. The base year for chained dollar estimates for current data sets is 1996,
while the earlier version was presented in chained 1992 dollars. Moreover, the
following adjustments have been incorporated.
Revenues
Transportation-related revenues of the Aquatic Resources Fund have been added
to water transportation revenues. In this case, only the excise tax charged on
motor boat fuels for the Boat Safety Program is assumed to be transportation-related.
The preceding data series did not account for revenues of Pollution Fund, Off-Shore
Oil Pollution Fund, and Deep Water Port Liability Fund prior to FY 1990. The current
data sets includes revenues for these funds prior to FY 1990.
Expenditures
Not all expenditures for the U.S. Coast Guard (USCG), as reported by the Office
of Management and Budget, are considered transportation-related. A new approach
has been used to arrive at more accurate USCG transportation-related expenditures.
Similar to the previous approach, the current approach includes all expenditures
for Environmental Compliance and Restoration, Alteration of Bridges, and Oil Spill
Recovery. Part of the expenditures for Operations, Acquisition, Construction and
Improvement, Research & Development, and Test and Evaluation are considered
as transportation. Within these program areas, only Aids to Navigation, Marine
Safety, and Marine Environmental Protection activities are included in the earlier
data sets. In the current version, more activities like Search and Rescue and
Ice Operations have been included. In addition, Boat Safety Program expenditures
have also been included.
Trust fund share of pipeline safety was added to the Research and Special Programs
Administration expenditures since FY 1994. This item was not covered in the previously
published data.
Federal Grants
Federal grants to state and local governments for the Boat Safety Program have
been included. These were not included in the previously reported data.
Data for federal transit grants are obtained from the Office of Management
and Budget public budget database. In the previous data series, they were estimated
by deducting direct federal transit expenditures grants from the total federal
transit expenditures.
REFERENCES
Corrado, C., C. Gilbert, et al. (1997). "Industrial production and capacity
utilization: historical revision and recent developments." Federal Reserve Bulletin
83(2): 67.
Korn, E.L. and B.I. Graubard.1991."A Note on the Large Sample Properties of
Linearization, Jackknife and Balanced Repeated Replication Methods for Stratified
Samples." The Annals of Statistics 19 (4):2275-2279.
Krewski, D. and J.N. K. Rao.1981."Inference from Stratified Samples: Properties
of Linearization, Jackknife and Balanced Repeated Replication Methods." The Annals
of Statistics 9(5):1010-1019.
Kunze, K. and M. Jablonski (1998). Productivity in service-producing industries.
Brookings Workshop on New Service-Sector Data, Washington, DC.
Landerfeld, J. S. and R. P. Parker (1997). "BEA's chain indexes, time series,
and measures of long-term economic growth." Survey of Current Business 77(5):
58.
Moulton, B.R. and Seskin, E.P. (1999)."A preview of the 1999 comprehensive
revision of the National Income and Product Accounts:statistical changes."Survey
of Current Business 79 (October 1999): 6-17.
Parker, R. P. and J. E. Triplett (1996). "Chain-type measures of real output
and prices in the U.S. national income and product accounts: an update." Business
Economics 31(4): 37.
Ritter, J.A. (2000)."Feeding the national accounts." Federal Reserve Bank of
St. Louis Review. March/April:11-20
SCB (1991). "Gross Domestic Product as a measure of U.S. Production." Survey
of Current Business.
Seskin, E. P. and R. P. Parker (1998). "A guide to the NIPA's." Survey of Current
Business 78(3):26.
U.S. Department of Labor, Bureau of Labor Statistics.1997.Measurement Issues
in the Consumer Price Index.Referenced at http://stats.bls.gov/cpigm697.htm
on May 13, 1999.
Valliant, R.1993. "Poststratification and Conditional Vairance Estimation."Journal
of the American Statistical Association 88 (421):89-96.
Young, A. H. (1993). "Reliability and accuracy of the quarterly estimates of
GDP." Survey of Current Business 73(10): 29.
Young, A. H. and H. S. Tice (1985). "An introduction to national economic accounting."
Survey of Current Business 65: 59.
Yuskavage, R. E. (1996). "Improved estimates of gross product by industry,
1959-94." Survey of Current Business 76(8): 133.
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