Issues in the Measurement of Transportation Output: The Perspective of the BEA Industry Accounts

Transcription

1 Issues in the Measurement of Transportation Output: The Perspective of the BEA Industry Accounts Robert E. Yuskavage Senior Economist Bureau of Economic Analysis Paper prepared for presentation at the May 4, 2 Brookings Workshop on Transportation Output and Productivity

2 Issues in the Measurement of Transportation Output: The Perspective of the BEA Industry Accounts Overview Economists and policymakers studying the post-995 acceleration in labor productivity growth and other changes that characterize the new economy increasingly use data from BEA s industry accounts, primarily the GDP by Industry and Input-Output accounts. While most studies have focused on macroeconomic developments, attention has turned recently to more disaggregated industry levels where differences in productivity provide insights into forces at work in the aggregate economy, and where a deeper understanding of productivity relationships may be found. 2 For example, several researchers have sought to determine whether the link between investment in information technology (IT) and productivity growth has spread beyond the IT producing industries to the IT using industries, which has important implications for the durability of the productivity growth revival. BEA s industry accounts are well-suited for studying these issues. The primary purpose of this paper is to provide insight and guidance for using the industry accounts data, focusing on transportation as a case study. This paper makes clear that researchers should be aware of both the conceptual and empirical differences in industry output measures, because they can lead to very different measures of productivity growth. While the choice between gross output and value-added depends on many factors, both series should be examined before conclusions are drawn. 3 This paper also discusses improvements in source data and methodology that can help to For recent examples, see Baily and Lawrence (2), Nordhaus (2), and Stiroh (2). 2 This is an extension of the theme expressed by Harberger (998) who used a "yeast vs. mushrooms" analogy to explain that productivity growth real cost reduction in his terms has many sources. Some are broad economy-wide forces that affect all sectors in a uniform fashion in much the same way that yeast causes bread to expand, and some are industry-specific forces that are uneven in their impact, like mushrooms that have the habit of popping up almost overnight in an unpredictable fashion. Harberger states that an understanding of both "yeast and mushroom" processes is necessary for a thorough understanding of productivity growth. 3 This issue is addressed some detail in a forthcoming manual on productivity measurement prepared by the Organization for Economic Cooperation and Development (2). Section 3. of the proposed manual discusses the choice between gross output and value-added as an output measure, including the theoretical and

3 -3- improve the industry accounts and reduce differences in output measures. A paper presented to the BEA Advisory Committee in November 2 (available at this conference) describes these measurement issues and their implications in detail. The first part of this paper is an overview of the size, scope, and structure of the transportation sector in BEA s industry accounts, including trends based on data from the GDP by Industry accounts. The second part presents specific measurement issues raised in the November 2 paper, focusing on their implications for transportation industries and their impact on the measurement of labor productivity in transportation. The third part discusses the major sources of data for measuring transportation output in the industry accounts, and highlights limitations in the existing source data that contribute to the measurement differences. The final part makes recommendations for improvements in source data and describes possible enhancements to BEA s industry accounts that are under consideration. Transportation Trends BEA s GDP by Industry accounts provide time series of gross output, intermediate inputs, and value-added for seven detailed transportation industries defined at the two-digit Standard Industrial Classification (SIC) level. These industries include railroad transportation, local and interurban passenger transit, trucking and warehousing, water transportation, transportation by air, pipelines, except natural gas (hereinafter referred to as pipelines), and transportation services, which includes travel agencies and freight forwarders. In both the GDP by Industry accounts and in the input-output (I-O) accounts, the output of transportation industries consists mostly of forhire and contract services, and excludes "own-account" transportation performed by firms on their own behalf. Transportation industries do not include industries engaged in the production or distribution of transportation equipment, nor in the construction of highways and other transportation-related structures. practical considerations involved for productivity measurement.

4 -4- Transportation shares and growth rates.-- In 999, the value added of transportation industries was $33.4 billion, which represented 3.3 percent of nominal GDP, about the same share as in Trucking and warehousing and transportation by air are the two largest industries in the transportation group, together accounting for nearly 7 percent of transportation value added in recent years (see chart ). The composition of transportation has changed very little since 987. The share for railroad transportation declined slightly, while the share for air transportation increased slightly; shares for the smaller industries were stable over the period. From , transportation real value added grew faster than the economy as a whole (4.4 percent vs. 3.2 percent for real GDP), contributing on average. percentage points to real GDP growth, about the same as in the period Air transportation grew the fastest (8.2 percent) while pipelines grew the slowest (-.5 percent). The value-added price index for transportation correspondingly grew slower than the overall GDP price index (. percent vs. 2.5 percent). Only the price index for local and interurban passenger transit increased faster than the GDP price index, while the price indexes for railroad transportation, transportation by air, and pipelines declined. Transportation production process.--the production process can be viewed as a combination of certain intermediate inputs (energy, materials, and purchased services) and valueadded inputs (labor and capital) that produces the industry s gross output. With the exceptions of pipelines and transportation services, these processes are quite similar across transportation industries. Intermediate inputs generally account for nearly 5 percent of gross output, with slightly higher shares for water transportation and significantly smaller shares for pipelines and for transportation services (see chart 2.) The industries with the highest ratios of intermediate inputs to gross output--local passenger transit, trucking, water transportation, and air transportation--are major users of refined petroleum products such as gasoline, diesel fuel, and aviation and jet fuel. 4 Estimates for own-account transportation are provided in transportation satellite accounts developed jointly by BEA and the Bureau of Transportation Statistics. These accounts indicate that the value added from all transportation activities, including own-account transportation, amounted to 4.8 percent of GDP in 996. See Fang, Han, Okubo, and Lawson (2).

5 -5- Transportation is more labor-intensive than all private industries, with compensation of employees accounting for slightly more than 6 percent of value-added, compared to slightly more than 5 percent for all private industries. In most years, labor intensity was highest in local passenger transit and lowest in pipelines, which is among the lowest of all private industries. Output per Employee.--Since 987, real output for transportation has grown faster than real output for all private industries, whether measured on a gross output basis or on a valueadded basis. For the period , real gross output increased at an average annual rate of 4.3 percent, while real value added increased 4.4 percent. For all private industries, the comparable growth rates were 3.7 percent and 3.4 percent, respectively. Above-average output growth raises the question of how labor productivity growth in transportation compares to other industries, and to what extent transportation has contributed to the post-995 acceleration in aggregate labor productivity growth. This issue is addressed below using both value added and gross output as output measures. Real value added per employee.--chart 3 and table a present growth in real value added per employee for each of the detailed transportation industries for For all transportation, real value added per full-time equivalent employee (FTE) increased at an average annual rate of.7 percent, slightly stronger than the.4 percent growth rate for all private industries. Productivity growth was especially strong for railroad transportation, water transportation, and--for the period transportation by air. 5 Value-added labor productivity growth for all private industries accelerated sharply during the late 99's, from. percent for to 2. percent for However, for transportation it remained constant at.7 percent in both periods, thus not contributing to the overall acceleration for private industries. The major contributor to transportation s above-average labor productivity growth for was railroad transportation, which increased 5.9 percent. For , when 5 Starting in 988, combination air and ground couriers were reclassified from trucking and warehousing to transportation by air. This reclassification affects changes in value added, employment, and productivity for these two industries between 987 and 988.

6 transportation productivity growth was below average, trucking and warehousing declined.7 percent. Comparing the two periods, railroad transportation decelerated sharply (4.7 points). -6- Real gross output per employee.--chart 4 and table b present labor productivity growth rates for transportation industries using gross output rather than value added, and a similar yet slightly different story emerges. For all transportation, real gross output per FTE increased at an average annual rate of.6 percent for , the same as for all private industries. Railroad transportation led the increase with a 5. percent growth rate, followed by trucking and warehousing at 3.6 percent. For , however, labor productivity for transportation increased at an average annual rate of.2 percent, much slower than the 2.4 percent rate for all private industries. Because of its size, trucking and warehousing exerted the largest influence on the below-average growth for transportation, increasing just.9 percent. Measured by gross output, labor productivity in transportation decelerated sharply during , declining.7 percentage points from the earlier period. The major contributors to the deceleration for transportation were railroad transportation (-4.4 points) and trucking and warehousing (-4. points). Measurement Issues The differences in productivity growth rates discussed above partly reflect the broader measurement issues for the industry accounts that were raised in the November 2 paper, and specifically how these issues affect the estimates for transportation industries. These measurement issues provide partial explanations for differences between the GDP by Industry accounts and the I-O accounts, the divergent trends in output per employee for transportation industries, and reasons for the limited detail for transportation industries. An understanding of these issues is important when using the industry accounts data for studying structural change and industry trends. GDP by Industry vs. I-O.--One of the first measurement issues that must be addressed

7 -7- when using data from the industry accounts is the difference between the annual GDP by Industry estimates and the periodic benchmark and annual I-O accounts. Differences in source data and methodology often result in large differences in levels and growth rates. Fortunately for transportation industry analysts, these differences are not as large for transportation as for some other sectors, which partly reflects the nature of the source data for the larger transportation industries. However, an investigation into these differences offers insights into the important roles played by differences in source data and methodology. Tables 2a-2c compare estimates for 992 from the revised GDP by Industry accounts with the 992 benchmark I-O accounts for gross output, intermediate inputs, and value added. With the exception of water transportation, differences in gross output for 992 were very small. 6 This is not surprising since the GDP by Industry gross output estimates are "benchmarked" or controlled to the I-O levels. All else equal, GDP by Industry estimates are generally slightly larger than the corresponding I-O estimates because the GDP estimates include own-account construction and own-account software production in the originating industry, whereas these activities are included in the construction and software industries in the I-O accounts. GDP by Industry estimates can also differ from I-O estimates due to revised estimates for commodity taxes, which include Federal excise taxes and State and local sales taxes. Table 2b presents differences in intermediate inputs for transportation industries. In the GDP by Industry accounts, intermediate inputs are obtained as the difference between independent estimates of gross output and value-added, whereas in the I-O accounts intermediate inputs are obtained from a combination of source data for industry purchases and indirect techniques, and value added is the residual. (Differences for intermediate inputs are not directly addressed.) A comparison of value-added estimates from the GDP by Industry accounts and the I-O accounts (table 2c) reveals a negligible difference of $. billion for all transportation 6 The relatively large difference for water transportation was due to a correction based on new data that was incorporated in the revised GDP by Industry estimates but that was not available in time for incorporation in the benchmark I-O accounts.

8 industries, but relatively large and offsetting differences for individual industries. These -8- differences highlight important features of the respective methodologies. In the GDP by Industry accounts, value-added is constructed directly from the NIPA s by summing each industry s labor and property income, including indirect business taxes. Labor income, which includes wages and salaries and supplements, is derived largely from Bureau of Labor Statistics (BLS) data; property income is derived largely from Internal Revenue Service (IRS) data reported on business tax returns. Since the major components of property income are reported to IRS on a company basis, these estimates are converted by BEA to an establishment basis. In contrast, value-added in the I-O accounts is obtained indirectly as the difference between estimates of gross output and intermediate inputs. Gross output estimates are largely based on data from the quinquennial economic census, but data for intermediate inputs are quite limited. Compensation estimates in the I-O accounts are based largely on economic census data for payroll and fringe benefits, and the estimates for other value added are derived as a residual. Transportation services shows a large difference for value added ($4.2 billion) despite nearly identical estimates for gross output. This difference is largely due to differences in the estimates of property income, which account for $3.2 billion of the difference. Put another way, even if the estimates of compensation and IBT in the I-O accounts exactly matched the GDP by Industry estimates, the latter would still exceed I-O value added estimate by $3.2 billion, or.3 percent of gross output. Thus, either the I-O estimates of intermediate inputs are too low, the GDP by Industry estimates of property income are too high, or some combination of both applies. However, this difference cannot be resolved without more consistent source data for both sets of accounts. Trucking and warehousing and transportation by air provide examples of how differences in source data classification can lead to large differences in value-added estimates. In 996, BLS reclassified certain combination ground and air carriers from the trucking industry (SIC 42) to the air transportation industry (SIC 45). These carriers were presumably classified in the same

9 -9- (original) industries in 992 by both Census and BLS, because initial comparisons for 992 did not reveal significant differences in either value-added or compensation of employees between the GDP by Industry and the I-O accounts. However, during the comprehensive NIPA and GDP by Industry revisions that were released in October 999 and June 2, the BLS reclassification was carried back to 988 for both wages and salaries and for employment, but was not made for the I- O accounts. Thus, despite nearly identical gross output estimates, the value-added and intermediate inputs estimates for these two industries differ by large and nearly offsetting amounts. Real GPO vs. Real Gross Output.--In the preceding part, trends in labor productivity growth for transportation were compared using both real value-added and real gross output. Since the same labor input measure (FTE) is used for both calculations, the difference is entirely attributable to the real output measures. While the two output measures tell similar stories, some relatively large differences demonstrate the importance of looking at both measures and understanding why they might differ. For example, since 995 labor productivity growth in transportation based on value added has been noticeably faster than growth based on gross output (.7 percent vs..2 percent), with considerable variation among individual industries. For the entire period , labor productivity growth estimates for transportation were larger based on value-added (2. percent) than on gross output (.4 percent). Since this difference prevailed in the two subperiods of and , the deceleration in labor productivity growth was about the same according to both output measures. While some of the individual industry differences were quite large, these were found generally in small industries such as pipelines, water transportation, and local passenger transit. The only large industry with large differences in output per employee over the entire period is transportation by air (4.2 percent based on gross output and percent based on value added). 7 This period is used rather than because of the impact on value-added of the change in classification for trucking and for air transportation back to 988.

10 -- Air Transportation.--Over the period , real gross output in air transportation increased at an average annual rate of 4. percent, whereas real value added increased 7.8 percent. In general, large differences in real growth rates between gross output and value added are attributable either to changes in the nominal ratio of intermediate inputs to gross output (nominal I-O ratio) or to changes in the difference between gross output prices and intermediate inputs prices. Gross output prices have in fact increased more slowly over the period than intermediate inputs prices (.7 percent vs..7 percent), which by itself would tend to raise the growth of real gross output relative to real intermediate inputs, implying faster growth in real value added than in real gross output. However, the more important factor for air transportation appears to be a continuing decline in the nominal I-O ratio, which is important because it provides weights for gross output and for intermediate inputs in the double-deflation formula. This ratio has declined each year since 99, falling from a level of nearly 5 percent in 988 to nearly 33 percent in 999, a substantial decline of about 7 percentage points. The rising share of value-added in gross output is attributable to both labor and property income, which increased on average 6.5 percent and 9.6 percent, respectively, compared to an increase of 4.8 percent in nominal gross output. The growth in property income has been fueled by an average annual increase of 8.2 percent in corporate profits before tax, with large losses before 994 converted to large gains after 994. Corporate profits before tax are essentially the same either on a company basis or an establishment basis, so the company-establishment conversion has very little effect on the valueadded estimates for this industry. These results raise the question about what is driving the increase in corporate profits for air transportation, given that labor costs are growing faster than gross output. Clearly intermediate inputs are growing very slowly, which may reflect operational efficiencies by airlines that result in lower fuel costs and other reductions in non-labor operating costs. Some insight into this issue can be obtained by looking at changes in the I-O accounts between 992 and 997. These accounts show that intermediate inputs declined from 55 percent of gross output in 992 to

11 -- 52 percent in 997, primarily due to below-average growth in two major categories of inputs: Refined petroleum products (which includes aviation and jet fuel) and port expenditures abroad. Major inputs whose growth kept the I-O ratio from declining even faster included aircraft parts and repair and freight forwarding services. Industry Detail.--Many users of the industry accounts are interested in more industry detail to better understand contributions to economic growth, output per employee, and other issues related to structural change. While the GDP by Industry accounts provide detail for most two-digit SIC industries, some frustration has arisen because much of the structural change appears to be taking place in specific three-digit and four-digit industries for which annual valueadded estimates are not available. While integrated, consistent estimates of gross output, intermediate inputs, and value-added are available only for the seven two-digit SIC industries in transportation, more detailed nominal and real gross output estimates are available starting in 987 for 9 categories of transportation. For the air transportation industry, for example, detailed gross output estimates are available for air passenger service; air freight, mail and express service; and other air transportation services, such as airports, flying fields, and airport terminal services. While the additional gross output detail for transportation does not exactly match the more detailed SIC industries, employment for close approximations to these categories can be obtained from BLS to construct estimates of real gross output per employee. Methodology is the primary reason for the limited industry detail in the GDP by Industry accounts. Because nominal value-added cannot be reliably estimated below the two-digit level from the available NIPA data, nominal intermediate inputs which are derived as a residual are likewise constrained to this level of industry detail. This constraint in turn limits the industry detail for real value-added by industry. Source Data This section briefly discusses the major sources of data for measuring transportation

12 -2- output in BEA s industry accounts, with separate discussions for benchmark estimates and annual estimates. Limitations of these source data are also discussed. Sources for the annual nominal estimates of value-added from the GDP by Industry accounts were discussed earlier and are not repeated here. Sources for indirect business tax and nontax liability, which include Federal excise taxes and State and local sales and excise taxes, are based largely on data from the U. S. Treasury Department for Federal taxes and on data from individual states for the other taxes. Benchmark Estimates.--The primary source for benchmark nominal gross output estimates is the quinquennial economic census conducted by the Bureau of the Census (Census). Only large "certificated" air carriers and railroads are not covered in the economic census. Data for these industries are obtained from the Department of Transportation s Bureau of Transportation Statistics (BTS) for large air carriers and from the Association of American Railroads (AAR) for rail transportation. The value of commodity shipments by mode of transportation for 997 and earlier years was provided by the Commodity Flow Survey (CFS) funded by BTS. These data are needed to prepare estimates of the purchasers s value of commodities consumed in both intermediate and final uses. Outside of trucking and warehousing, very little comprehensive, consistent data are available for estimating the intermediate inputs consumed by transportation industries. Annual Estimates.-- The key source data for preparing nominal and real annual estimates of industry gross output are current-dollar revenues for use as extrapolators and price indexes for deflation. Annual surveys conducted by the Census provide revenue extrapolators for trucking and warehousing and for the travel agencies portion of transportation services. For railroads and for air transportation, the major data sources are the same as those used for the benchmark gross output estimates (AAR and BTS). For all other transportation industries, sources include trade associations, consulting firms, and BLS wages and salaries (W&S) as a proxy extrapolator. While about 85 percent of the gross output for transportation industries is based on industry-specific receipts data, parts of local passenger transportation, water transportation, and transportation services rely on BLS W&S.

13 -3- For real gross output estimates, the producer price index (PPI) from BLS is now used for all industries for which it is available, including railroads, trucking, water transportation, and parts of transportation services. The BLS consumer price index (CPI) is used for taxicabs, although this estimate is obtained directly from the NIPA s. For most of air transportation, implicit price deflators are constructed based on detailed receipts data and quantity indicators such as ton-miles and passenger-miles. This method is also used for parts of local passenger transportation and for oil pipelines. However, BLS W&S per employee data are also used as a proxy for the gross output price index at detailed levels in the absence of actual price indexes or quantity indexes. This proxy measure is used for school buses, other air transportation, and other transportation services. Prior to the availability of the expanded PPI s for transportation in the early 99's, BLS W&S per employee was also used for parts of water transportation and transportation services. Future Prospects The U.S. economy is undergoing significant structural change that economists and policymakers need to study from an industry perspective. BEA s industry accounts are wellsuited to studying these issues, but yield measures due to differences in source data and methodology. BEA has ideas for improving these accounts to increase consistency and timeliness, but resource constraints and source data limitations require that priorities be established. The impending conversion of BEA s industry estimates to the new North American Industry Classification System (NAICS) offers opportunities to explore these topics in a thorough manner from the ground up, but it also presents challenges with regard to maintaining time-series consistency. International guidelines recommend full integration of the industry, income, and expenditure estimates in a consistent conceptual framework such as the I-O accounts. This approach is followed by many nations and it yields integrated, consistent industry estimates, but often at the expense of timeliness and accuracy due to the lack of high-quality, timely source data.

14 -4- Benchmarking of these industry accounts to comprehensive economic census data is limited or nonexistent, and the estimates rely heavily on judgement and mechanical procedures. The U.S., on the other hand, relies on the income and expenditure approaches for the national income and product accounts (NIPA s) because these approaches allow maximum use of timely, high-quality economic indicators from BLS and Census. Decoupling industry estimates from the NIPA s and tying them more closely to the I-O accounts would be costly because of the loss of consistency with these important economic indicators. Producing integrated industry accounts requires BEA to reconcile differences between GDP by Industry and value-added from the I-O accounts, which are conceptually equivalent. GDP by Industry is based primarily on BLS data for labor income and on IRS data for property income, whereas I-O is based primarily on Census data. Differences in the industry classifications among these major data sources lead to inconsistencies. In addition, I-O value added is a residual that is critically dependent on good data for purchased goods and services by industry, which are limited. The GDP by Industry estimates of property income assume that corporate profits and other company-based income components can be allocated to the establishment level by industry. BEA is also investigating ways to speed-up the availability of both the GDP by Industry accounts and the annual I-O accounts. One of the major obstacles to accelerating release of the industry estimates is the limited availability of source data for gross output by industry early in the year for the prior calendar year, especially for nonmanufacturing industries. Nominal gross output data are especially limited for transportation early in the year. For example, in March gross output source data are available only for rail passenger service, air transportation, and parts of local passenger transportation. BEA is considering a multi-stage approach for improving the industry accounts that includes providing more timely estimates in the short run while working towards more consistent and better integrated industry accounts in the long run. Acceleration and integration of the industry accounts both require improved source data, not just for transportation but for all

15 -5- industries. For transportation, BEA needs improved data on transportation commodity flows by mode; annual receipts for water transportation, transportation services, and local passenger transit; and timely prior-year indicators for freight rail, trucking, water transportation, and transportation services. BEA also needs comprehensive, consistent estimates of intermediate purchases by all industries, and more consistent estimates of labor costs by industry. These source data improvements will depend heavily on initiatives taken by BTS, BLS, and Census. While BEA can envision changes in methodology that would move it closer to meeting these goals for the industry accounts, recent remarks by Federal Reserve Board Chairman Alan Greenspan in the context of measuring the changing economy are instructive. He noted that "...the experience of the last 4 years underscores a fundamental dilemma of business economics. Should we endeavor to continue to refine our techniques of deriving maximum information from an existing body of data? Or should we find ways to augment our data library to gain better insight into how our economy is functioning? Obviously, we should do both, but I suspect greater payoffs will come from more data than from more technique." 8 BEA agrees with that view. 8 Greenspan (2).

16 -6- References Baily, Martin N. and Robert Z. Lawrence. 2. "Do We Have A New E-conomy?" Paper presented at the January 2 meetings of the American Economic Association. Findings from this paper appeared in the Economic Report of the President January 2. Fang, Bingsong, Xiaoli Han, Sumiye Okubo, and Ann M. Lawson. 2. "U.S. Transportation Satellite Accounts for 996." Survey of Current Business 8 (May 2): Greenspan, Alan. 2. "The Challenge of Measuring and Modeling a Dynamic Economy." Remarks at the National Association of Business Economics Washington Economic Policy Conference. Washington, DC, March 27, 2. Harberger, Arnold C "A Vision of the Growth Process." American Economic Review 88 (March 998): -32. Nordhaus, William D. 2. "Productivity Growth and the New Economy." Yale University Cowles Foundation Discussion Paper. Organization for Economic Cooperation and Development. 2. "OECD Productivity Manual: A Guide to the Measurement of Industry-Level and Aggregate Productivity Growth." Draft revision 3. released for comment January 2. Stiroh, Kevin J. 2. "Information Technology and the U.S. Productivity Revival: What Do the Industry Data Say?" Paper presented at the National Bureau of Economic Research March 2 Productivity Program.

17 -7- Chart -Transportation Industry Shares Rail 6 Local 6 Truck Share (%) 4 2 Share (%) 4 2 Share (%) Water 6 Air 6 Pipe Share (%) 4 2 Share (%) 4 2 Share (%) Services Share (%) 4 2

18 -8- Chart 2--Nominal Input-Output Ratio Rail Local Truck Ratio (%) 5 Ratio (%) 5 Ratio (%) Water Air Pipe Ratio (%) 5 Ratio (%) 5 Ratio (%) Services Ratio (%)

19 -9- Chart 3.--Real Value Added per FTE , 996=..4 Rail.4 Local.4 Truck Water.4 Air.4 Pipe Services.2.8.4

20 -2- Chart 4.--Real Gross Output per FTE , 996=..4 Rail.4 Local.4 Truck Water.4 Air.4 Pipe Services.2.8.4

21 -2- Table a-- Real Value Added per FTE (Average annual growth rate) Accel. in Private industries Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Table b-- Real Gross Output per FTE (Average annual growth rate) Accel. in Private industries Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Table c-- Difference in Labor Productivity Measures: Gross Output less Value Added (Difference in growth rates) Accel. in Private industries Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services

22 -22- Table 2a.-- Gross Output, 992 GDP by Input- GDP Diff. as % (Dollar amounts in billions) Industry Output Less I-O of I-O Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Table 2b.-- Intermediate Inputs, 992 GDP by Input- GDP Diff. as % (Dollar amounts in billions) Industry Output Less I-O of I-O Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Table 2c.-- Value Added, 992 GDP by Input- GDP Diff. as % (Dollar amounts in billions) Industry Output Less I-O of I-O Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services