John Ozment .... Cook and Cook (1989) reviewed much of the literature on rural .... [c] Literacy rate is in percentage of population 15 years and older who can ...
Assessing Transportation Contributions to the Economic Performance of Developing Countries
John Ozment Oren Harris Chair of Transportation Department of Marketing and Transportation College of Business Administration University of Arkansas Fayetteville, Arkansas 72701 (501) 575-6142 College of Business Administration
Assessing Transportation Contributions to the Economic Performance of Developing Countries
INTRODUCTION Few people would argue with the suggestion that transportation improvements contribute to economic development. Inadequate transportation limits a nation's ability to utilize its natural resources, distribute food and other finished goods, integrate the manufacturing and agricultural sectors, and supply education and medical services. However, there is little actual evidence linking transportation improvements to economic development. It generally is not known whether investments in transportation infrastructure are more productive than investments in other sectors of an economy. Nor is it known whether capital expenditures on one mode of transportation are more productive than those spent on another. When resources are scarce, is it better to develop the rail network, highway network, airports, or what? Transportation planners in developing countries need guidance to aid them in making decisions regarding spending on transportation improvements. Addus (1989) suggests that there is a serious need for improved road transportation service in developing countries, and that improving the efficiency of road transport would have a beneficial impact on industrial and agricultural production and distribution (Addus 1989, p. 429). On the other hand, Carter, Chadda and Schonfeld (1984) suggest that developing countries may actually over invest in transportation improvements. In many cases, this is due to applying solutions to problems in developed countries such as the U.S. to problems in developing countries with little concern for differences in "need, values, resource availability, climate, etc. (Carter, Chadda, and Schonfeld 1984, p. 79)." This comes about in part from using imported consultants and local planners who want modern solutions such as jet aircraft, automated factories, modern highways, etc. If
developing countries follow the pattern of U.S. development, they would invest first in railroads. This would appear to be a logical progression given the natural economies of railroads vis-a-vis trucks and other forms of transportation. However, the developing nations of the World today exist in an environment which is dramatically different from that in which the U.S. and other countries developed. Technological and social differences provide an environment which may require a completely different approach to growth and economic development than that which led to the development of the U.S. and other developed nations of the World today. Industry, agriculture, education, and health all are vital to economic growth, and they all compete with transportation for a share of a nation's limited resources and foreign aid. It is crucial to develop transportation systems which are efficient and make the most of the resources required to develop them, avoiding the consumption of excessive amounts. Officials and planners in developing countries must make decisions regarding the use of limited financial resources. If capital improvements in transportation facilities lead to greater development than when capital is used in other areas, then planners should realize the benefits to be gained by developing the transportation infrastructure. If on the other hand, capital improvements in transportation facilities cannot be linked to economic performance, then scarce resources could, perhaps, be put to better use. Additionally, if certain modes of transportation are related to economic growth more than others, then it would be prudent for officials and planners to develop first those portions of the infrastructure which permit the development of those modes of transportation. In this paper, we examine the relationship between economic growth and transportation in developing countries of Africa. Major differences exist between African countries, but they also have several common problems which suggest the need for study. These include poorly
developed industrial and agricultural sectors, high population growth rates, severe shortages of professional, managerial, technical, and financial resources, and an inefficient transportation system (Carter, Chadda, and Schonfeld 1984). Africa has a large number of developing countries with varied backgrounds and varying levels of infrastructure development. Many of its nations are characterized by sparsely populated rural areas which are virtually inaccessible by motor vehicles. Frequently, pack animals (mules, donkeys, horses, and camels) are a major means of transportation. Thus, leaders of African nations face serious problems with respect to using available resources to foster economic growth and improve the quality of life.
TRANSPORTATION AND ECONOMIC DEVELOPMENT Economic development occurs when the income level and productive output of an area increase (Forkenbrock 1989). The benefits of transportation improvements are related to the reduced costs associated with transportation. That is, if a transportation improvement is provided, the result should be reduced transportation costs to the area (Forkenbrock 1989). Reduced transportation costs, then, should lead to greater productivity and increased economic growth. Typically, transportation has been viewed as an enabling, but insufficient factor leading to economic development (Owen 1964; Meyer, et al. 1971). Historically, transportation's contribution to economic development has been through providing access to markets and raw materials, and by alleviating congestion. These benefits allow an economy to maximize its comparative advantages (Bell and Feitelson 1989, p. 57). Once raw materials and markets are made accessible, attention turns to relieving congestion in these sectors which then facilitates productivity improvements. Most of the research attempting to actually link transportation to economic development has been focused on the U.S. and other developed nations. Even so, the relationship is not well-defined. Bell and Feitelson (1991) examined the implications of structural changes taking
place in the U.S. economy on future demand for transportation services and noted that "research has not yet fully explained the relationship between the level and quality of infrastructure services and private sector economic performance (p. 518)." Aschauer (1989) analyzed the relationship between public capital and total factor productivity in the U.S. from 1949 to 1985. His findings suggest that the decline in U.S. productivity in recent years has been preceded somewhat by a "precipitous decline in additions to the net stock of public nonmilitary structures... such as highways, streets, water systems, and sewers" (pp. 195, 197). Similarly, Munnell (1990) examined U.S. productivity between 1948 and 1987 and found that multifactor productivity which had grown at 2.5 percent between 1948 and 1969 fell to 1.1 percent between 1969 and 1987. She concluded that the drop in labor productivity has been a direct result of the decline in the growth of public infrastructure. Collapses of bridges and highways seem to provide ample evidence that the United States has not been maintaining its public capital, much less undertaking any enhancements (Munnell 1990, p. 20). Lynde and Richmond (1993) analyzed annual time series data for the nonfinancial corporate sector of the U.S. covering the period from 1959 to 1989 and found support for the impact that public sector investment has on productivity. Their study concluded that approximately 40 percent of the decline in labor productivity is due to a decline in the growth of the public capitallabor ratio. While these studies are innovative and important, they do not establish whether infrastructure investment effects economic growth or whether economic growth effects infrastructure investment. Furthermore, they base their conclusions on aggregate public investment and do not differentiate between the types of investment that may yield the greatest return to the private sector, and, thus, give us no evidence of the contribution of transportation infrastructure development. Tatom (1993) addressed the question of whether public investment effects economic growth or whether economic growth effects public investment by analyzing lagged data from both perspectives. He concluded that there is essentially no impact of infrastructure capital on productivity. If anything, reductions in economic growth lead to reductions in infrastructure
capital. In contrast, Otto and Voss (1996, 1998) analyzed quarterly data from 1959 through 1992 for the Australian economy and concluded that public capital does contribute significantly to productivity. Moreover, they found no evidence of causality from private production to public capital stocks. Holtz-Eakin (1994) also studied this question. He analyzed data for the contiguous 48 states which covered 1969 to 1986 and found no relationship between productivity and public sector capital from either the state level or regional level. However, his study, just as those mentioned above (Aschauer 1989; Munnell 1990; Lynde and Richmond 1993; Tatum 1993; Otto and Voss 1996), also used aggregate measures of government capital. He noted the problems of using aggregated data and called for research that would analyze the microeconomic linkage between infrastructure and production so that the most productive types of capital expenditures could be identified (Holtz-Eakin 1994, p. 20). Gramlich (1994) reviewed the literature on infrastructure investment and economic development in an attempt to assess the need for change in policies regarding infrastructure investment in the U.S. He examined literature that focused on Engineering Needs Assessments, Political Voting, Economic Rates of Return, and Econometric Estimates of Productivity Impacts. Finding no clear evidence of the effects of infrastructure capital on productivity, he noted: Not only have previous studies not provided very convincing answers to whether there is or has been an infrastructure shortage, but they may not have even focused on the right question in the first place… [I]t seems more helpful to ask what, if any, policies should be changed (Gramlich 1994, p.1189).
He suggested that there while there was not enough attention given to public investment in
infrastructure prior to 1989, it has probably received too much attention since then, and he
recommended that the federal government should permits states and local governments to
determine their own optimal level of infrastructure investment.
Finn (1993) analyzed annual data for the U.S. covering the period from 1950 to 1989 and
attempted to address prior questions concerning causality and the effects of individual
components of public capital on productivity. She controlled for reverse causation through her
methodology and found highway capital expenditures to provide significant (and very large)
returns to the private sector. Cullison (1993) used a similar data set covering 1953 through 1991
which contained 21 categories of government expenditures, including transportation. He used
Granger-causality tests to control for direction of impact, and found that transportation spending
was not significant. However, his measure of transportation included expenditures for air, rail,
water, and transit as well as for highways.
As noted above, most of the research in this area has been focused on developed nations,
the U.S. in specific, and evidence is conflicting. Little empirical research has been done to
determine the role that transportation should play in aiding economic growth in developing
countries or just how much transportation improvements contribute to economic development.
Cook and Cook (1989) reviewed much of the literature on rural transportation impacts in
developing countries and noted that economic models have shown little explanatory power in
predicting the effects of rural transportation investments. They cite a separate review of rural
road research in India which also reveals a lack of tangible results (p.107). Their conclusion was
that the problem lies in the lack of an explicit model to establish causal linkages and the use of
incomplete databases. Thus, their attention was directed to the development of a comprehensive
and complex model of rural transportation impact. However, the complexity of the model stands
in stark contrast to the availability of data and remains untested.
In many instances, transportation infrastructure improvements are justified on the basis of
intangible benefits. The view held by many officials and planners of developing countries is that
road programs are valued as necessary components in programs to improve human welfare in
rural areas. It was this view that led to the development of the Rural Access Roads Program in
Kenya (Lele 1975). Moreover, development of infrastructure for such purposes seems to
accomplish that objective. Research on rural road transportation in China attempted to link
agricultural production to road improvements. However, rural roads generally did not lead to
increased agricultural output. Instead, they showed significant increases in nonagricultural traffic
and rapid growth in personal mobility (Cook and Cook 1991, p. 109). Levine and Renelt (1992)
examined data across 119 countries to test the effects of a large number of variables suggested
within the literature to affect growth rates. The results were disappointing, and like most of the
variables, government investment in infrastructure was not found to be significant.
Addus (1989) examined road transportation in 15 African countries for 1982-83.
Presented was an overview of facilities which when compared to the U.S. highlighted the
severity of an inadequate road network and a severe shortage of vehicles. However, no linkage
of improvements to economic development was provided. He explored the reasons for the
inadequate road conditions indicating the problems presented by climate, terrain, difficult
roadway engineering, high construction costs, and circuitous routes (p. 430). Additionally, the
problems of political instability were noted. Not only do regional conflicts and civil wars divert
important resources (financial and human) away from road construction, they also have resulted
in the destruction of existing bridges and roads.
Lionjanga and Raman (1989) discussed the development of transportation in Botswana
since the country's independence in 1966. At the time of independence, there were just 12 km of
tarred roads in the entire country. Transportation was not considered to be a prime determinant
of economic growth, but because of Botswana's dispersed population and overwhelming
dependence on neighboring countries for transportation services, it was seen as a prerequisite to
"stable population growth and balanced economic development (p. 211)." Thus, transportation
was included as an element in the National Development Plan which called for 15 to 20 percent
of annual investments to be in the transportation sector. In many years, the commitment
exceeded this level. While transportation development in Botswana has accompanied the
nation's growth since independence, the authors provide no direct evidence of the role that
transportation played in that development.
Feltenstein and Ha (1995) studied the relationship between the public infrastructure and
private output in sixty-three sectors in Mexico, aggregated into sixteen groups over the years
1970-1990. The dependent measure was sectoral gross domestic product. Independent measures
included wages, the cost of capital, and the nominal values of the stocks of three types of
infrastructure: electricity, transport, and communications. Public expenditures on infrastructure
in electricity and communications tend to reduce sectoral production costs whereas expenditures
on transportation infrastructure increase those costs. They note that they can offer, “no good
explanation for the counterintuitive results for transport (Feltenstein and Ha 1995, p. 298).”
Canning (1999) studied the productivity of infrastructure in 57 countries for the period
covering 1960 through 1990. His dependent variable was GDP per worker, and independent
variables were human capital per worker, telephones per worker, electric generating capacity per
worker, and transportation routes per worker. The coefficients of electric generating capacity and
transportation infrastructure were not statistically significant; that is, they had the average
productivity level of overall capital. However, telephones were found to have a very large
statistically significant impact on productivity, suggesting that investment in telephones is more
productive that investing in electric generation or in transportation infrastructure. When the
sample was split into higher and lower income countries, results were similar except that
transport appears to be more important to developed countries. While Canning (1999) used
lagged data in some of his analyses, his purpose was to assess direction of causality.
METHODOLOGY If transportation contributes to the economic development of a nation, then we should expect to see improvements in certain indicators of economic activity and well-being following improvements in transportation. This generally is the relationship that researchers in the works referred to above attempted to identify. However, in those analyses transportation infrastructure and economic performance were measured within the same time periods. Researchers have not differentiated between the time that transportation improvements are made and the time that economic activity increases. For this study, we examined the relationship between economic performance and transportation developments from prior periods. To examine the relationship between transportation and economic performance, data from the Central Intelligence Agency's World Factbook were analyzed over a twelve year period from 1981 to 1993. Table 1 provides selected economic variables for the sample of 44 African countries for 1993. South Africa was not included in the sample since it is not considered a developing country. Four other countries were omitted due to insufficient data. Table 2 provides selected measures of transportation infrastructure for the sample of countries during 1993. A multiple regression analysis was performed using 1993 Gross Domestic Product per Capita as the dependent variable. Changes in independent variables of interest were measured
from 1981 to 1987 to see if infrastructure changes in prior periods were related to today's GDP/Capita. The independent variables included 1993 population, and the average annual percentage changes from 1981-1987 of population, kilometers of railroad, kilometers of highway, kilometers of paved highway, the number of usable airports, the number of airports with permanent runways, the number of TV stations, and the literacy rate. Unfortunately, there TABLE 1 Selected Economic Variables for 44 African Countries, 1993 Country[a] ALGERIA ANGOLA BENIN BOTSW ANA BURKINA BURUNDI CAMEROON CENTRAL AFRICA CHAD CONGO COTE D'IVORIE DJIBOUTI EGYPT EQUATORIAL GUINEA ETHIOPIA GABON THE GAMBIA GHANA GUINEA GUINEA-BISSAU KENYA LESOTHO LIBERIA LIBYA MADAGASCAR MALAW I MALI MAURITANIA MOROCCO MOZAMBIQUE NIGER NIGERIA RW ANDA SENEGAL SIERRA LEONE
Area in Square Kilometers 2381740 1246700 110620 585370 273800 25650 469440 622980 1259200 341500 318000 21980 995450 28050 1119683 257670 10000 230020 245860 28000 569250 30350 96320 1759540 581540 94080 1220000 1030400 446300 784090 1266700 910770 24950 192000 71620
Population[b] 27.256 9.545 5.167 1.326 9.853 5.985 12.756 3.074 5.351 2.389 13.808 0.402 59.586 0.399 53.278 1.123 0.930 16.699 6.237 1.072 27.372 1.896 2.875 4.873 13.006 9.832 8.869 2.125 27.955 16.342 8.33 95.060 8.139 8.463 4.511
Literacy Rate[c] 57 42 23 72 18 50 54 27 30 57 54 48 48 50 62 61 27 60 24 36 69 59 40 64 80 22 32 34 50 33 28 51 50 38 21
GDP[d] 42000 5100 2000 3600 3300 1230 11500 1300 1100 2500 10000 358 41200 144 6600 4600 292 6600 3000 210 8300 620 988 26100 2500 1900 2300 1100 28100 1750 2300 35000 2350 5400 1400
GDP per Capita[d] 1570 950 410
Inflation Rate 55.0 1000.0 3.4
2450 350 205 1040 440 215 1070 800 1030 730 380 130 4200 325 410 410 210 320 340 400 5800 200 200 265 555 1060 115 290 300 290 780 330
16.5 -1.0 9.0 3.0 -3.0 2.5 -0.6 1.0 7.7 21.0 1.4 7.8 0.7 12.0 10.0 19.6 55.0 30.0 17.9 12.0 7.0 20.0 21.0 1.4 6.2 6.0 50.0 1.3 60.0 6.0 2.0 5.0
Unemployment Rate 35.0 NA NA 25.0 NA NA 25.0 30.0 NA NA 14.0 30.0 20.0 NA NA NA NA 10.0 NA NA NA 55.0 43.0 NA NA NA NA 20.0 19.0 50.0 NA 28.0 NA NA NA
SUDAN 2376000 28.730 27 5200 184 150.0 30.0 SW AZILAND 17200 0.907 55 700 800 13.0 NA TANZANIA 886040 27.286 46 7200 260 22.0 NA TOGO 54390 4.105 43 1500 400 0.5 2.0 TUNISIA 155360 8.571 65 13600 1650 6.0 15.7 UGANDA 199710 19.344 48 6000 300 41.5 NA ZAIRE 2267600 41.346 72 9200 235 40.0 NA ZAMBIA 740720 8.926 73 4700 550 170.0 NA ZIM BABW E 386670 10.838 67 6200 545 45.0 35.0 [a] South Africa was not included because it is the only African nation which is considered to be developed. Four additional nations were omitted due to insufficient data. These were Eriteria, Nambia, Somolia and W estern Sahara. [b] Population in Millions. [c] Literacy rate is in percentage of population 15 years and older who can read and write. [d] GDP is in millions of equivalent U.S. dollars. GDP/Capita is in equivalent U.S. dollars. Source: Directorate of Intelligence (1994), The W orld Factbook, (Washington, D.C.: Central Intelligence Agency, various editions).
TABLE 2 Transportation Infrastructure: African Countries, 1993 Airports Number of with Kilometers Usable Permanent of Inland Kilometers Airports Runways W aterway of Pipeline 124 53 0 9858 173 32 1295 179 5 1 0 0
Kilometers of Railroad 4060 3189 578
Kilometers of Highway 90031 73828 5050
Kilometers of Paved Highway 58868 8577 920
712 620 0 1003 0 0 797 660 97
11514 16500 5900 65000 22000 31322 11960 46600 2900
1600 1300 400 2682 458 32 560 3600 280
87 38 4 51 51 55 41 37 11
8 2 1 11 3 5 5 7 2
0 0 NA 2090 800 2000 1120 980 0
0 0 0 0 0 0 25 0 0
EGYPT 5110 EQUATORIAL GUINEA 0 ETHIOPIA 781
51925 2760 39150
17900 331 2776
82 3 82
66 2 9
3500 0 0
2227 0 0
Country ALGERIA ANGOLA BENIN BOTSW ANA BURKINA BURUNDI CAM EROON CENTRAL AFRICA CHAD CONGO COTE D'IVORIE DJIBOUTI
GABON THE GAM BIA GHANA GUINEA GUINEA-BISSAU KENYA LESOTHO LIBERIA LIBYA MADAGASCAR MALAW I MALI MAURITANIA MOROCCO MOZAMBIQUE NIGER NIGERIA RW ANDA SENEGAL SIERRA LEONE SUDAN
649 0 953 1045 0 2040 2.6 480 0 1020 789 642 690 1893 3288 0 3505 0 1034 84 5516
7500 3083 32250 30100 3218 64590 7215 10087 19300 40000 13135 15700 7525 59198 26498 39970 107990 4885 14007 7400 20703
560 431 6084 1145 2698 7000 572 603 10800 4694 2364 1670 1685 27740 4593 3170 30019 460 3777 1150 2000
56 1 9 15 15 208 28 41 124 103 41 27 29 65 131 26 63 7 19 7 56
10 1 5 4 4 18 3 2 56 30 5 8 9 26 25 9 34 3 10 4 10
1600 400 1293 1295 NA NA 0 0 0 0 NA 1815 800 0 3750 300 8575 NA 897 800 5310
284 0 0 0 0 483 0 0 6773 0 0 0 0 1094 565 0 5542 0 0 0 815
SW AZILAND TANZANIA TOGO TUNISIA UGANDA ZAIRE ZAMBIA
297 3555 570 2115 1300 5254 1266
2853 81900 6462 17700 26200 146500 36370
510 3600 1762 9100 1970 2800 6500
21 92 9 26 23 235 104
1 12 2 13 5 25 13
0 NA 50 0 NA 15000 2250
0 982 0 1625 0 390 1724
ZIMBABW E
2745
85237
15800
403
22
0
Source: Directorate of Intelligence (1994), The World Factbook, (Washington, D.C.: Central Intelligence Agency, various editions).
212
was not sufficient data available to include other variables which may have added to the overall explanation of GDP/Capita. As noted above, industry, agriculture, education, and health all are vital to economic growth. However, insufficient data restricted our ability to adequately analyze these measures. The number of TV stations and the literacy rate were used as surrogates for industrial development and education and were included to help specify a more complete model. As can be seen from Table 1, very little data on unemployment was available. Similarly, data on industrial development and agriculture was too limited to include appropriate variables. Limited data from previous years for water ways, ports, and pipelines also hampered the analysis. Moreover, as can be seen from Table 2, many countries have so little of this type of infrastructure that these variables were not included, and the impacts of these modes were not analyzed. Some analyses were performed with variables adjusted for land area; kilometers of highway per square kilometer, for example. However, none of these analyses yielded more productive results than those reported below.
RESULTS Table 3 provides the results of the regression analysis. The results are exceptionally good considering the limited specification of the model. The overall fit of the model is quite good (RSquared = 52%; F = 4.035, significant at 0.001). Population, changes in population, changes in the number of TV stations, and changes in the literacy rate were not significant. The change in kilometers of rail line was highly significant (p = 0.004). The total kilometers of highways was not significant, but the kilometers of paved highways was (p = 0.066). Similarly, the number of usable airports was not significant, but the
number of airports with permanent runways was highly significant (p = 0.023). Of these significant variables, all three were positively related to GDP/Capita. TABLE 3 Regression of 1993 GDP/Capita on Transportation Variables
Variable[a] Pop 93 Pop 81-87 RR 81-87 Hwy 81-87 Pav 81-87 Air 81-87 Run 81-87 TV 81-87 Lit 81-87 Dependent: GDP/Cap 93
Mean 14.226 22.297 9.697 31.024 10.153 -6.728 10.147 45.278 164.185 761.23
Standard Deviation 18.418 11.120 41.467 79.910 17.464 19.439 37.307 147.067 241.078
Standardized Regression Coefficient -3.290 -13.681 11.496 -.756 15.156 9.999 9.875 .759 .417
Regression Coefficient -.057 .674 -.144 .451 -.057 .250 .184 .348 .105 .095
P-Value .376 .004 .691 .066 .309 .023 .505 .494
1058.197
R-Squared = 51.6%; F-Value = 4.03; P Value = .001 [a] The variables used include 1993 population (Pop 93), and the average annual percentage changes from 1981-1987 in: population (Pop 81-87), kilometers of railroad (RR 81-87), total kilometers of highway (Hwy 81-87), total kilometers of paved highway (Pav 81-87), the number of usable airports (Air 81-87), number of airports with permanent runways (Run 81-87), the number of TV stations (TV 81-87), the literacy rate (Lit 81-87).
Provided in Table 3 also are standardized coefficients of the independent variables. Standardized coefficients provide a means of comparing data with large differences in values and different bases such as kilometers of road vs the number of airports. Examining these standardized coefficients reveals that changes in railroad facilities yields the greatest GDP/Capita. Next is the number of airports with permanent runways, and finally, although certainly not small, is the contribution made by increases in paved highways. The order of these
variables together with the fact that regular highways and regular airports were not significant suggests that larger investments in infrastructure may bring higher yields with respect to improved economic performance. This is particularly important since there is a tendency to invest in minimum levels of facilities such as unpaved roads to merely gain access to certain areas to link various areas of an economy.
CONCLUSIONS, LIMITATIONS, AND FUTURE RESEARCH While there is little doubt that transportation improvements contribute to economic growth, there is little empirical evidence to support that premise. Transportation planners in developing countries need guidance to aid them in making decisions regarding spending on transportation improvements to assure the efficient utilization of scarce resources. However, there is a lack of research which clearly identifies how transportation contributes to the economic growth of developing countries. Part of the problem may have been the failure to measure the impact of changes in the transportation infrastructure in periods prior to the period in which economic performance is measured. This paper examined the relationship between economic growth and transportation in 44 developing countries of Africa. Gross Domestic Product per Capita was regressed on a series of variables which reflected changes in transportation from previous years. The significance of the rail network, paved highways, and airports with permanent runways in explaining current GDP/Capita suggests that transportation is of vital importance to developing nations. The present research, however, is limited by a lack of adequate data which would perhaps permit a more robust analysis. The model which was tested should be specified more
completely. No doubt this would increase the overall R-Square and give planners a better understanding of how transportation fits into an overall planning process together with measures of industrial development, agriculture, health, and education. Use of the literacy rate and the number of TV stations provides surrogates for some of these variables, but their lack of significance suggests that better measures should be used. Just as it is difficult to believe that transportation would not contribute to economic growth, so it is difficult to accept that education and industrial development are not extremely important determinants of economic growth and performance. Additionally, a more complete analysis of economic activity should be examined in light of transportation improvements from prior periods. While GDP/Capita is a widely accepted measure of economic performance, other measures such as unemployment, growth in GDP/Capita, industrial growth rates, etc., should be examined. Finally, future research should focus on determining a more exact time horizon in which to measure the results of transportation improvements. This study looked at changes over a 12 year period, with an arbitrary division taking place at 6 years. Measuring changes from 1981 to 1987 may not accurately reflect the cumulative benefits of transportation investments. What is the appropriate time horizon in which such investments fully mature and yield the maximum benefits to the society they serve? In today's global economy, it is not surprising that high quality infrastructure improvements are more important to economic development than traditional, more economical facilities such as paved roads vs regular roads and airports with permanent runways vs regular airports. Today, few countries are developing in the isolation of a self-contained economy. Not only are countries trading with their neighbors, but they participate in the economic growth of
developed nations as their cheap labor and other resources are exploited by modern industry and a growing global economy. To the extent that developed nations do business with developing nations, it is only to be expected that we would see the need for advanced transportation facilities and systems to meet the needs not of the developing nation, but of the "exploiter."
REFERENCES Aschauer, David Alan (1989), "Is Public Expenditure Productive?" Journal of Monetary Economics, Vol. 23, pp. 177-200. Addus, Abdussalam A. (1989), "Road Transportation in Africa," Transportation Quarterly, Vol. XLIII, no. 3 (July), pp. 421-450. Bell, Michael and Eran Feitelson (1989), "Bottlenecks and Flexibility: Key Concepts for Identifying Economic Development Impacts of Transportation Services," Transportation Research Record, No. 1274, pp. 53-59. Bell, Michael E. and Eran Feitelson (1991), "U.S. Economic Restructuring and Demand for Transportation Services," Transportation Quarterly, Vol. XLV, no. 4 (October), pp. 517-538. Canning, David (1999), “Infrastructure’s Contribution to Aggregate Output,” World Bank Development Research Group, Ref. no. 680-89 (November). Canning, David (1998), “A Database of World Stocks of Infrastructure, 1950-1995,” The
World Bank Economic Review, Vol. 12, no. 3 (September), 529-547. Carter, Everett C., Himmat S. Chadda, and Paul M. Schonfeld (1984), "A Comparison of Transportation Planning in Developed and Developing Countries," Transportation Quarterly, Vol. XXXVII, no. 1 (January), pp. 69-85. Cook, Peter D. and Cynthia C. Cook (1989), "Methodological Review of Analyses of Rural Transportation Impacts in Developing Countries," Transportation Research Record, No. 1274, pp. 171-178. Cullison, William E. (1993), “Public Investment and Economic Growth,” Economic Quarterly Review, Vol. 79, no. 4 (Fall), pp. 19-52. Directorate of Intelligence (1994), The World Factbook, (Washington, D.C.: Central Intelligence Agency, various editions).
Feltenstein, Andrew and Jiming Ha, “The Role of Infrastructure in Mexican Economic Reform,”
The World Bank Economic Review, Volume 9, Number 2, May 1995. Finn, Mary (1993), “Is All Government Capital Productive,” Economic Quarterly Review, Vol. 79, no. 4 (Fall), pp. 53-80. Forkenbrock, David J. (1989), "Putting Transportation and Economic Development into Perspective," Transportation Research Record, No. 1274, pp. 3-11. Gramlich, Edward M. (1994), “Infrastructure Investment: A Review Essay,” Journal of Economic Literature, Vol. XXXII, no. 3 (September), pp. 1176-1196. Holderman, Karen, “Improved Marketing Research Programs Help U.S. Exporters Find Opportunities Abroad,” Business America, October 1996, pp. 7-9. Holtz-Eakin, Douglas (1994), “Public Sector Capital and the Productivity Puzzle,” The Review of Economics and Statistics, Vol. LXXVI, no. 1 (February), pp. 12-21. Johnson, Jay L., “Why American Retailers are Going Global,” Discount Merchandiser, September, 1995, pp. 37-39. Kraft, G., J.R. Meyer, and J.P. Valette (1971), The Role of Transportation in Regional Economic Development, (Lexington, MA: Lexington Books, Inc.). Lele, U. (1975) The Design of Rural Development: Lessons from Africa, (Baltimore, MD: Johns Hopkins University Press). Lionjanga, A.V. and V. Raman (1989), "Transportation and Economic Development in Botswana: A Case Study," Transportation Research Record, No. 1274, pp. 211-219. Lynde, Catherine and J. Richmond (1993), “Public Capital and Total Factor Productivity,” International Economic Review, Vol. 34, no. 2 (May), pp. 401-414. Munnell, Alicia H. (1990), "Why Has Productivity Growth Declined? Productivity and Public Investment," New England Economic Review, (January/February), pp.3-22. Otto, Glenn D. and Grahm Voss (1996) “Public Capital and Private Production,” Southern Economic Journal, Vol. 62, no. 3 (January), pp. 723-738. Otto, Glenn D. and Grahm Voss (1998) “Is Public Capital Provision Proficient?” Journal of Monetary Economics, Vol. 42, no. 1, pp. 47-66. Owen, Wilfred (1964), Strategy for Mobility, (Washington, D.C.: The Brookings Institution). Brookings Institution).
