This paper uses direct and indirect demands for transportation as a proportion of final demand to assess the relative share of transportation-related demand in Canadian gross domestic product (GDP) from 1971 to 1996. The data are derived from the Canadian input/output tables. Three trends are highlighted over the time period studied: a growing share of transportation-related trade in GDP, a decline in transportation investment, and a decline in the transportation margins associated with the distribution of commodities. Overlying these trends, as a major determinant of transportation as a share of GDP, is the volatility of transport fuel prices. Transportation as a share of GDP has been fairly steady over the time period studied, representing 20.7% of GDP in 1996, with a peak of 21.1% in 1981 corresponding to the peak in fuel prices, and a low of 19.1% during the recession of the early 1990s.
This paper uses the Canadian system of national accounts (CNA) to estimate the proportion of Canadian gross domestic product (GDP) that is transport-related, with transportation final demand as the measure of GDP instead of value added or income. Final demand is used here because it allows for a broader definition of transportation, notably including the use of transportation equipment, fuel, and infrastructure traditionally not considered to be part of the transportation industries, but instead considered private transportation demand by industry and consumers, and public transportation demand by government.
The paper draws on the work of Han and Fang (1998) on the final demand-based methodology used by the U.S. Department of Transportation and expands on that methodology in two principal ways:
1. by broadening the definition of transportation-related demand to include both transportation fuels (e.g., gasoline, diesel oil) and transportation margins,1 as well as transportation equipment, infrastructure, and industries;
2. by including not only direct transportation-related demand but also indirect demand, which is embedded in nontransportation-related final demand. For example, shoes that are consumed as part of final demand require transportation as an intermediate input in their production, thus some part of the final cost of shoes to consumers can be considered as indirect transportation-related final demand.
The data used in this paper are from the CNA input-output (IO) tables, using the industry and commodity classification system based on the Canadian Standard Industrial Classification (SIC) system. The SIC has been replaced by the North American Industry Classification System (NAICS). However, at the time this paper was written, NAICS-coded data were not available for the years assessed (19711996). Statistics Canada's IO division provided all data described in this paper.2
It should be noted that this paper does not develop a satellite account for transportation in the same sense as the U.S. satellite account for transportation described in Fang et al. (2000).3 Transportation satellite accounts typically develop an estimate for a new industry, for example, private trucking, by disaggregating and then reaggregating data derived from other industries. For example, trucking employment, transportation equipment investment, or transportation fuel use contained in other industries, such as the retail or wholesale trade industries, will form the basis for estimating the private trucking industry.
This paper neither disaggregates nor reaggregates data, but uses the existing rows and columns contained in the CNA, while imposing a definition of transportation-related demand that encompasses both existing industries (e.g., transportation industries) and commodities (e.g., transportation equipment, fuel). The same methodology used in this paper could be applied to transportation satellite account IO tables where, for example, private trucking was reconstituted as a separate industry column, thereby increasing the accuracy of the description of transportation within the national economy. A more detailed description of the methodology used here is provided later in this paper.
The paper is structured in three sections: the CNA, methodology, and results. The paper traces the evolution of transportation-related demand from 1971 to 1996, at five-year intervals based on the Canadian census years, where 1996 is the most current IO table available. These time periods were also selected to allow for observations relative to the business cycle, with 1971 and 1976 straddling the 1973 OPEC oil crisis, 1981 and 1991 representing recession years, and 1986 and 1996 representing years of recovery and positive growth.
The CNA, as represented by the IO tables, are structured into the make ( M ), use ( U ), and final demand ( FD ) matrices. The M table is a commodity by industry matrix that indicates which commodities are made by which industry. The U table is a commodity and primary inputs by industry matrix that indicates the amount of commodities and primary inputs used by industry. The FD table is a commodity and primary inputs by FD category matrix that indicates the amount of commodities and primary inputs that form part of FD . FD categories are broadly classified as consumption ( C ), investment ( I ), government spending ( G ), imports ( IM ), and exports ( EX ) where
FD = GDP = C + I + G IM + EX , and
FDD (final domestic demand) = C + I + G .
In the CNA, detailed commodities are more numerous than either industry or final demand classifications, in order to account for industries producing more than one commodity or joint production, thus leading to rectangular matrix forms. Commodities are goods or services while primary commodities represent returns to primary factors (e.g., labor, capital), as well as variables such as indirect taxes. There are four levels of detail for which IO tables are available in the CNA: s, m, l, and w. S corresponds to small (in terms of numbers of rows and columns), m to medium, and w to working (the most detailed level available). L refers to an historical link series, which provides a consistent classification of industries and commodities going back over time to 1961. This paper uses the Canadian SIC-based system used at Statistics Canada for the 1986 to 1997 IO tables, which has now been replaced by the NAICS.4 Table 1 illustrates the dimensions of the two most detailed levels available (l, w) based on the SIC, where the l (or historical link) tables are used in this paper to represent a consistent classification over time, though at some loss of detail.
Figure 1 shows the relationship between the three IO tables and illustrates two common means of calculating GDPby the sum of primary inputs and the sum of final demands. The third common means of calculating GDP is value added, which is done by subtracting the U from the M matrix, leaving a commodity by industry matrix of value added.
In terms of how supply and demand for transportation is represented in the CNA tables, the M matrix indicates the total supply of transportation (where M shows the value and type of commodities produced by each industry, or gross output). The U and FD matrices represent, respectively, the intermediate and final demands for commodities, where U indicates which commodities are used as inputs in production and FD indicates those commodities that are allocated to final demand categories and thus form GDP.
In terms of transport demand, the direct demand for transportation (e.g., automobiles, rail investment) is found in the FD tables, while indirect demand is derived from transportation commodities (e.g., domestic freight) used as inputs in the U matrix. Indirect demand refers to the proportion of transportation commodities embedded in nontransport final demand. For example, shoes consumed as part of final demand require transportation as an intermediate input in their production; thus a proportion of the final cost of shoes to consumers can be considered as indirect transportation-related final demand. The definition of the industries and commodities classified as transportation-related demand in this paper is provided in the following section.
One difficulty, or opportunity, in accounting for transportation in the CNA is commercial transportation, which is attributed to "fictive" industries, notably transportation margins (TMs). Margins are created to account for the difference between factor prices, or price at the factory gate, and final prices, or prices charged to the consumer, with the two main types of margins being transportation and trade margins.5 TMs appear as both columns and rows in the M and U matrices and as a row in the FD matrix, and can be interpreted as the distribution costs imputed to transportation industries. The use of TMs means that transportation industry commodities are allocated between: 1) transportation used in distribution, or transportation costs as a portion of the difference between the factor price and final price, and 2) transportation used in production, or transportation costs as a share of factor prices.
The fictive TMs industry uses solely for-hire commercial freight transportation industry commodities (e.g., trucking, rail) as inputs in the U matrix, while its commodity output is represented as a single row in both the U and FD matrices. This means that components of the TMs (e.g., trucking, rail) cannot be attributed to specific industries, although they can be classified in aggregate through the inputs of the U matrix. Table 2 lists the composition, or inputs, to the TMs industry from 1971 to 1996. The trends show the most growth in trucking as a share of the TMs, going from 41.1% in 1971 to 60.6% in 1996, with the largest growth from 1991 (52.3%) to 1996 (60.6%), possibly reflecting trade trends and the ongoing movement to just-in-time distribution. Over the same period, rail declined from 41.7% to 27.3% and water transport from 11.9% to 3.6% of the TMs.
These pronounced trends are an early indication of this paper's themethe observation that many of the most interesting trends in commercial freight transportation are actually found within the evolution of the TMs. As an indication of the importance of the TMs in this area, in 1996 the rail and truck inputs to the TMs accounted for 81.9% and 62.6%, respectively, of the gross outputs of the two commercial transportation industries, as table 3 illustrates. However, caution must be taken when interpreting the TMs, particularly for smaller freight industries (e.g., air, marine freight) as they are an artificial industry created within the CNA to distinguish between factor and final prices. The TMs also do not include private or in-house freight transportation.
The first step in determining the importance of transportation is the definition of direct transport demand in terms of the commodities (rows) and final demand categories (columns) of the FD matrix. An important point to note is that no disaggregation or reaggregation of the existing l-level rows or columns were used in this paper, as this would represent the development of a satellite account for transportation, a partial example of which is provided in the U.S. national accounts with the satellite account for private truck transport.
In terms of commodities, all rows associated with transportation equipment (including tires), transportation industries (including pipelines), as well as the TMs were used. Selected commodities were also chosen to represent transportation fuels, transportation construction, and other transportation services, three areas where the level of aggregation at the l level of the CNA leads to somewhat incomplete datasets.
In the case of transportation fuels, diesel and aviation fuel are aggregated with heating oil as one commodity (or row), and thus transport demand for this commodity will be slightly overestimated. However, this commodity is included as part of transport fuels, along with motor gasoline.
In terms of construction, the level of detail does not allow for disaggregating transportation-related expenditures from several commodities, notably construction repair, other engineering construction, and railways and communications. The only row in construction that is unequivocally transportation-related is roads, highways, and airport construction. A similar problem of inadequate detail also occurs with other service commodities, principally repair services and trade margins as well as indirect taxes. The only other services commodity that is unequivocally transportation-related is car and truck rentals.
Thus, in order to develop a more complete picture of transportation-related demand, certain FD categories or columns were also classified as direct transport demand, notably all columns in consumption unequivocally related to transportion demand, as well as equipment and construction investment by transportation industries. Therefore, construction commodities (e.g., railway track) or service commodites (e.g., trade margins, repair services), as well as indirect taxes found in these FD columns will also be classified as direct transport demand. This should limit, but not completely account for, the underestimation of transportion-related demand due to transportation-related expenditures embedded within construction, other services, or indirect tax commodities.
Given this definition, the direct demand for transportation ( FDt ) can be classified as a matrix of c * f proportions where c refers to commodities, f to final demand categories, and all nontransport-related commodities or columns are specified as zeros. Summing FDt by commodities generates the breakdown of direct transportation-related demand presented in this paper.
Indirect demand refers to the demand for transport embedded in the factor price of nontransport-related commodities and FD columns, where transport-related commodities and columns are as defined above. Determining the indirect demand for transportation requires all three matrices, the M , U , and FD .
The first step in calculating the indirect demand is to generate a proportional matrix of U , where all commodity entries are divided by the total gross inputs to generate a c * i (or industry) matrix of proportions, here called the UP matrix. Each individual entry in this matrix indicates the proportion of industry gross inputs accounted for by that commodity.
The second step is multiplying the UP matrix by the transpose of the M matrix ( Mt ) where the transpose is required due to the rectangular format of the CNA.6 Thus
UP * Mt = C
where C is a c * c matrix indicating the commodity values used in the production of other commodities. Converting the C matrix to proportions in a similar manner to the U matrix by dividing the commodity rows by the commodity gross outputs generates the CP matrix, a c * c matrix where each entry indicates the proportion of each commodity used in the production of all other commodities.
In the third step, we return to FD , and in order to avoid double counting, subtract FDt or
FD FDt = FDnt
where FDnt represents a c * f matrix with zero entries and the direct transportation commodities and columns as defined above are located. This step ensures that transportation commodities used in the production of other such commodities (e.g., transportation industries used to produce transportation equipment) are not double counted.
In the fourth step, the FDnt matrix is reduced to a c * 2 matrix, where the two columns represent indirect domestic demand and exports, here called FDID . Indirect domestic demand ( IDD ) is calculated as C + I + G Ip = IDD , where Ip refers to the proportion of imports that are attributed to final demand. This commodity import proportion is calculated as the relative share of final demand by commodity as a proportion of commodity gross output, multiplied by total imports. Thus, IDD is an estimate of the nontransportation-related domestic demand met by domestic producers.
The final step requires:
CP * FDID = ID, where ID (indirect demand) refers to a c * 2 matrix listing the commodity values used in the production of the FDnt commodities. Using the same definition of transport commodities as listed above in FDt allows for the calculation of the indirect share of transport in FDID.
Transportation-related consumption has remained at a fairly steady proportion of total consumption, varying between a high of 16.2% in 1981, at the height of the fuel price spike brought about by the OPEC cartel, to a low of 14.7% in the recession of the early 1990s (table 4). In 1996, the largest component of transport consumption was "other transportation services" associated with equipment sales and use, that is, trade margins and repairs. The "other transportation services" category shows a low of 4.0% in 1981 and a high of 4.4% in 1996.
The second largest category of consumption in 1996 was transportation equipment (at factor price), varying from a high of 4.5% in 1986, in the growth period following the recession of the early 1980s, to a low of 3.7% in the recession of the early 1990s. Automobiles constitute the largest segment of transportation equipment, although a slight decrease in consumption from 3.1% in 1971 to 2.5% in 1996 is seen. However, increases in the truck category, from 0.2% in 1971 to 0.9% in 1996, compensate for the decrease in the automobile category.
Indirect taxes (e.g., sales tax, excise tax) were the third largest component, accounting for 2.8% of consumption in both 1991 and 1996. This represents an increasing trend from a low of 2.1% of consumption in 1981, with the share of indirect taxes also lower in the 1970s relative to the 1990s.
Transportation industries, or commercial transportation, show a steady level of consumption at approximately 2% in all years. Within commercial transportation, two slight trends are evident, an increasing share of air transportation, from 0.7% in 1971 to 1.1% in 1996, and a declining trend for surface passenger transportation, from 0.8% in 1971 to 0.5% in 1996. The TMs show a more pronounced decline, from 1.0% of consumption in 1971 to 0.5% in 1996, possibly associated with trucking deregulation and price competition, and the corresponding increased trend toward truck freight use in the TMs.
The most volatile of transportation commodities are transportation fuels, swinging from a high of 3.0% of consumption in 1981 to a low of 1.2% in 1996, after beginning at 1.5% in 1971. Although accounting for a relatively low share of consumption, the influence of fuel price swings is evident, with the 1981 fuel price peak generating the most atypical year of all years assessed.
Investment can be classified into three separate categories to distinguish between transportation industries, other industries, and government. Note that all investment undertaken by transportation industries is classified as transportation-related, but only investment in commodities that are transportation-specific is counted for government and business.
The components of investment by transportation industries experienced a major swing from 1971 to 1996, with an increasing share of transportation equipment29.0% in 1971 to 59.5% in 1996and a declining share of transportation construction63.3% in 1971 to 32.9% in 1996 (table 5). This reflects the reduced level of construction investment in railways as they consolidated their construction capital stock, which is consistent with their declining market share in freight transportation. It also reflects a surge in investment in other equipment, particularly between 1991 and 1996, possibly reflecting a more recent swing from investment in transportation equipment to information and communications technology. As of 1996, "other equipment" was the largest component in the transportation equipment category, ahead of aircraft and other complete equipment (e.g., trailers and semi-trailers). As expected, annual investment is rather volatile, particularly aircraft investment; nevertheless, we can see a slight upward trend for aircraft and trucks and a slight downward trend for railroad equipment.
Transportation investment by other businesses accounted for 7.2% of total investment in 1996, with a low of 5.0% in 1991 and a high of 7.5% in 1986 (table 6). This investment is almost exclusively in transportation equipment where a pronounced business cycle trend is evident, with lower investment in recessions and higher investment in recoveries. As of 1996, transportation equipment accounted for 6.8% of total investment, up from a low of 4.4% in the recession year of 1991. The largest share of business investment was in automobiles (4.4% in 1996) and trucks (1.5% in 1996), with a slight increase in automobiles and a slight decline in trucks, possibly reflecting increased outsourcing from private to commercial transportation.
Government investment is primarily road-related construction, with total transportation investment accounting for 25.9% of government investment in 1996with a low of 23.8% in 1991 and a high of 32.2% in 1971 (table 7). Government transportation investment exhibits a declining trend, with road investment declining from 29.3% of government investment in 1971 to a low of 21.3% in 1991, followed by a slight upturn to 23.4% in 1996.
Summing the three categories of transportation investment generates the result that the highest level of transportation-related investment as a proportion of total investment was in 1971 (16.4%table 8). A contradictory business cycle movement can be observed, with investment by transportation industries becoming the largest component of transport investment in recessions (1981, 1991) while other business forms the largest component in recoveries (1986, 1996). The share of government exhibits a steady decline, from the largest share in 1971 (6.2%) to 3.4% of total investment in 1996.
Transportation commodities account for a large share of Canadian exports, 30.0% as of 1996, with a low of 26.0% in the fuel-price-generated recession of 1981 and a high of 34.8% in the recovery year of 1986 (table 9). The main component of exports is transportation equipment, accounting for 23.3% of exports in 1996, with a high of 27.2% in 1986 and a low of 17.4% in 1981. In all years, the main components of transportation equipment exports are automobiles, motor vehicle parts, and trucks.
The second largest component of exports are the TMs, accounting for 2.8% of final export prices in 1996, down from 5.1% in 1971, with a steady decline in all years. Again, this steady decline correlates with an increasing share of trucking in the TMs, and a reorientation and concentration of trade with the United States. Commercial transportation (transportation industries) exhibits a steadier share of exports, also accounting for 2.8% in 1996, with a high of 3.0% in 1991 and a low of 1.4% in 1976. The upward trend in commercial transportation is generated by increasing exports of air, truck, and pipeline services.
Transportation commodities account for a slightly smaller share of Canadian imports, 25.9% as of 1996, with a low of 24.7% in the recession of 1981 and a high of 32.6% in the recovery year of 1986 (table 10). As it is for exports, the main component of imports is transportation equipment, accounting for 22.9% of imports in 1996, with a high of 29.6% in 1986 and a low of 21.7% in 1981. In all years, the main components of transportation equipment imports are motor vehicle parts and automobiles, reflecting Canada's role in transportation equipment manufacturing.
The second largest share of transportation imports is commercial transportation (transportation industries), accounting for 2.2% of imports in 1996, with a high of 2.4% in 1991 and low of 1.0% in 1971. The increasing share of commercial transportation relative to the 1970s derives primarily from greater imports of air and trucking services. There are no TMs in imports, as import factor prices are calculated from the border rather than from the factory gate.
Indirect transportation demand refers to demand for transportation commodities, which is embedded in the price of the nontransportation commodities that make up part of final demand. For example, some portion of the price of shoes is accounted for by the transportation commodities used in the domestic production and distribution of shoes. Indirect demand can be divided into two categories, indirect domestic demand ( IDD ) and exports.
Government spending on transportation, as opposed to investment, is contained within IDD . In the CNA, government is treated as an industry that primarily produces services. Thus, government services commodities are listed primarily as a single entry in FD , under the column government spending. In order to produce services, the government uses inputs such as transportation commodities (table 11). Detailed government inputs are listed in the U , not the FD matrix, and thus transportation commodities used to produce government services will appear in IDD and not direct FD .
Indirect transportation-related domestic demand ( ITDD ) accounted for 2.6% of domestic demand ( DD ) in 1996, the lowest level of all years assessed, with a high of 3.6% in 1981, again reflecting the price spike in fuels (table 12). As of 1996, transportation industries represented the largest component of ITDD at 1.0% of DD , with a surprisingly even trend over time that extends through all categories of commercial transportation. The two largest components of commercial transportation were air and surface passenger transportation, with surface passenger transportation consisting mainly of taxicab use by businesses and ambulance and school bus transport as part of government services. As with direct demand, the most interesting trends related to commercial transportation are found in the TMs, which accounted for 0.4% of DD in 1996, a steady decline from 0.9 % in 1971.
As of 1996, the second largest component of ITDD was transportation equipment, primarily motor vehicle parts, at 0.6% of ITDD , with again a relatively constant trend over time. Fuel was the most volatile component of ITDD , accounting for 0.4% in 1996 and 1971, with a high of 1.1% in 1981.
In terms of exports, TMs represent the largest share of indirect transportation demand, accounting for 0.8% of exports in 1996, a steady decline from 1.2% in 1971 (table 13). Commercial transportation accounts for 0.5%, a slight decline from 0.7% in 1971, with pipeline transportation as the leading component. Transportation equipment, again primarily motor vehicle parts, accounts for 0.3% of indirect demand from exports, with a relatively steady trend. Indirect demand for fuel exports is volatile, ranging from a high of 0.9% in 1981 to a low of 0.3% in 1996.
The previous sections have provided a detailed assessment of the share of direct and indirect transportation as a proportion of the relevant components of final demand. This section aggregates the commodities presented earlier to generate estimates of transportation as a share of GDP and domestic demand. The detailed descriptions of the different components of transportation are aggregated to transportation equipment, fuel, construction, industries, margins, other transportation services (trade margins, repairs, automobile rental services), and indirect taxes.
The share of transportation in GDP has been relatively stable over the time periods selected, accounting for 20.7% of GDP in 1996 and 1971, with a high of 21.1% associated with the fuel price peak of 1981, and low of 19.1% in the restructuring recession of 1991 (table 14).
Several broad trends can be discerned, the most important of which is the increasing trade related to transportation. In 1996, transportation-related exports were the largest single component of transport demand at 14.2% of GDP, going from a low of 7.6% of GDP in 1971. Particularly strong growth occurred from 1991 (10.0%) to 1996, and from 1981 (8.8%) to 1986 (12.3%), indicating a business cycle trend. Imports also grew, but at a slower pace, from 6.3% in 1971 to 10.3% in 1996, which indicates an increasing trade surplus. While the transportation equipment category dominates trade, transportation industries also show an increasing level of trade, with exports accounting for 1.3% of GDP in 1996, having moved steadily up from a low of 0.4% in 1971, with comparable figures for imports being 0.9% and 0.2%. The direct export associated TMs have maintained a fairly steady level over time, accounting for 1.3% of GDP in 1996, as have the indirect exports TMs (0.4% in 1996). This indicates that the decreases in TMs as a share of exports over time, as indicated in earlier sections on exports and indirect exports, are compensated by the increasing volume of exports.
All of these trade-related trends are consistent with the growth in importance of trade in the Canadian economy, particularly that associated with the advent of the North American Free Trade Agreement. Table 15 presents exports and imports as a share of GDP for 1971 to 1996, showing exports growing from 26.9% of GDP in 1971 to 47.3% in 1996, with particularly high growth from 1991 to 1996.
A second major trend is the decline in transportation-related investment as a share of GDP, down from 4.6% of GDP in 1971 and 1981 to a low of 3.0% in 1996 (see table 14). This is due to a decline in transportation construction as a share of GDP, going from 2.6% of GDP in 1971 to 1.0% in 1996. This results from the ongoing consolidation of railway construction capital stock and a lower level of government investment in roads as a share of GDP, possibly indicating a mature transportation infrastructure. This relative decline may also be associated with increased investment in information and communications technology (ICT), as investment flows from mature industries, such as transportation, to new and growing industries such as ICT. Alternatively, the decline in transportation investment may point to an infrastructure investment deficit, particularly for road infrastructure, where the government may not have been investing sufficiently to meet the increased demand for road infrastructure, as indicated by the growth in consumption and investment in road transportation equipment as well as trucking.
A third major trend is the decline in the TMs associated with domestic demand, both direct and indirect. In consumption, TMs show a steady decline from 0.7% of GDP in 1971 to 0.3% in 1996, while for indirect domestic demand the TMs declined from 0.9% to 0.4% (table 14). This correlates with the increasing share of trucking in the TMs, as discussed above. A possible explanation for this trend is the growth in the efficiency of the freight transportation industries, possibly stemming from deregulation, as well as the advent of more efficient supply chain management practices, such as just-in-time production and distribution. Table 16 shows the relative change in freight rail and trucking prices, gross output (or revenues), and total factor productivity relative to the economy from 1981 to 1996. However, these price, output, and productivity figures cannot explain the relative growth in trucking compared to rail, as rail has exhibited both higher productivity gains and larger declines in prices.
Together these three trends explain the relative stability of transportation as a share of GDP, with the increasing trends in trade, particularly the surplus in equipment, compensating for the decreasing trends in investment and the TMs. A look at table 14 again shows that because trade is excluded from domestic demand, transportation as a share of domestic demand is much lower (14.7% in 1996) than it is as a share of GDP (20.7%), with a similar pattern of volatility (e.g., a low of 14.4% in 1991 and a high of 16.3% in 1981). A possible declining trend can also be observed with the two transportation shares recorded in the 1990s (1991, 14.4%; 1996, 14.7%) representing the lowest shares of domestic demand of all years. This may reflect competition from new consumer durables, such as personal computers.
Overlying these three trends as the major determinant of transportation as a share of GDP is the volatility of fuel as a share of GDP, which can be particularly associated with the market strategies of the OPEC oil cartel. The peak in fuel shares in 1981 (e.g., 2.0% of GDP in consumption and 1.0% in indirect domestic demand), correlates with the peaks in transportation share of GDP and domestic demand (1981 was the most atypical of all years surveyed), along with the restructuring recession of 1991. The trend in fuel shares has followed a triangular pattern over the years assessed, with low and similar fuel shares of GDP in 1971 and 1996, and a peak in 1981; the total transportation share of GDP in 1971 and 1996 was also similar and shows a peak in 1981.
One of the advantages of using a commodity-based classification of transportation demand, as defined in the IO tables, is that it allows for different levels of macroeconomic analysis. Table 17 illustrates an aggregation of the demand for transportation by the different types of commodities, divided in a standard manner into goods, services, and indirect taxes. As can be noted, transportation is fairly evenly split between transportation goods and services, with a slight predominance of transportation goods over services up until 1986 and then again in 1996, corresponding to the growth in equipment exports. The largest transportation commodity is equipment, accounting for a high of 35.1% of total transportation demand in 1996, with a low corresponding to the 1981 fuel price peak (21.5%). The second largest category (other transportation services) is also primarily associated with equipment, notably trade margins and equipment repairs in transportation consumption. Three of the trends discussed above are also highlighted in looking at the demand for transportation by commodity class: the impact and volatility of fuel prices, the declining share of transportation construction, and the steadily declining share of the TMs.
This paper has used the IO tables maintained in the CNA to assess the share of transportation-related demand, both direct and indirect, in Canadian GDP from 1971 to 1996. The industry and commodity classification used in this paper is from the standard industrial classification system that was specific to the Canadian national accounts. This classification system has now been replaced by the NAICS, which will be common to the Canadian, U.S., and Mexican national accounts. NAICS should allow for future work involving a similar methodology to compare trends in the relative share of transportation in the national economies of Canada, Mexico, and the United States. Another future development related to IO data that would enable a refining of these estimates, while using a similar methodology, is the integration of one or more transport satellite accounts, such as private trucking, within the IO tables.
Han, X. and B. Fang. 1998. Measuring Transportation in the U.S. Economy. Journal of Transportation and Statistics 1(1).
Fang, B., X. Han, A. Lawson, and S. Okubo. 2000. U.S. Transportation Satellite Accounts for 1996. Survey of Current Business, May.
Statistics Canada. 1989. A User's Guide to the System of National Accounts.
The author would like to thank the two anonymous referees for their helpful comments, as well as Dr. Xiaoli Han.
Author's address: Jeff Harris, Senior Advisor, Economic Analysis, Place de Ville, Tower C, Ottawa, Ontario, Canada, K1A 0N5. Email: firstname.lastname@example.org.
KEYWORDS: transportation, economic analysis, national accounts, GDP, consumption, investment, imports, exports, direct and indirect demand, domestic demand.
1 Transportation margins (TMs) are a concept unique to the CNA and represent an estimate of the transportation costs incurred in the distribution of commodities. They form, along with trade margins and indirect taxes, the principal difference between commodities at factor prices and final prices as the sum of final demand categories in the CNA. In order to fully account for transportation in the CNA, the margins must either be included separately in transportation demand or disaggregated and merged with other appropriate transportation commodities (e.g., freight trucking) as a form of satellite account. Because this paper is not developing a satellite account, the TMs were included as a separate commodity.
2 A small amount of suppression for confidentiality of certain entries in the IO tables was undertaken by Statistics Canada prior to providing the tables, typically accounting for 1%2% of the total values contained in the tables. Estimates of the suppressed data were generated based on comparisons of the provided actual row and column total values, and comparisons of the values in different years with unsuppressed data.
3 It can be noted that the development of a similar satellite account for private trucking in Canada is proceeding, and when completed, can be used with the same methodology described in this paper to develop a more precise estimate of the share of transport demand in GDP.
6 The transpose is required given the rectangular matrix forms of the CNA in order to ensure that the conformability condition for matrix multiplication applies, specifically that the column dimension of the lead matrix ( UP ) is equal in number to the row dimension of the lag matrix (Mt). An alternate, if more cumbersome, procedure would be to initially merge the various commodity rows to industry dimensions, thus generating a square set of U and M matrices.