U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000
By
Dr. T.R. Lakshmanan, Director, Bureau of Transportation Statistics
U.S. Department of Transportation
July 1996
| Study | Country/Sample | Type of Estimation | Sector or Output Measure | Public Infrastructure Type |
Public Infrastructure Elasticity |
Private Inputs Type |
Private Inputs Elasticity |
Notes |
|---|---|---|---|---|---|---|---|---|
| Mera 1973, '75 | Japan 8 regions 1954-1963 (time series/cross section) | production function, Cobb-Douglas | primary secondary tertiary | transportation and communication; 3 other categories | 0.35** for transport and communications in secondary; 0.39-0.42 in tertiary; transp. and comm. Not used in primary | capital labor | K: 0.15-0.33 L: 0.55-0.85, according to sector | |
| Elhance and Lakshmanan 1988 | India national 1950-79 (time series) and 6 states 1970-71 (cross section) | cost function, translog, with endogenous private adjustment to publicly supplied infrastructure | manufacturing value added | economic infrastructure (roads, rail, electric capacity); social infrastructure (hospital beds, etc.) | economic infrastr. cost elasticities; at state level, -0.04 to -0.47; at national level -0.01 to -0.03 | capital labor energy materials | adjustment period of about 5 years | |
| Johansson 1992 Johansson and Karlsson 1994 | Sweden 280 and 284 munic. 1980-88 (time series/cross section) | production function, Cobb-Douglas | aggregate income, industry-level income | highway capital public transit capital road accessibility | highway 0.12-0.18; public transp. 0.18-0.20; road accessibility 0.20-0.27 | capital labor | K: 0.47-0.50 | adjustment periods of 14-26 years, depending on industry |
| Seitz 1993 | Germany 1970-89 (time series/cross section) | cost function, translog, industry fixed effectime series | real output, 31 industries | road mileage road capital | negative and significant | capital labor | roads complementary to private capital, substitute for labor; these effects small | |
| Seitz 1994 | Germany 1970-89 (time series/cross section) | cost function, translog, industry fixed effectime series | real output, 31 industries | public capital "core" public capital | on demand for K: 0.36 on demand for L: -0.13 to -0.15 | capital labor | rental elasticity of K demand, -0.04; wage elasticity of L demand, -0.09 | |
| Conrad and Seitz 1994 | Germany, 1961-89 (time series/cross section) | cost function, translog | gross output, 3 sectors: manufacturing, construction., trade and transportation | public capital | negative and significant | capital labor material | estimated shadow price of public infrastructure approx. half of user cost of private capital; decrease in pub infrastr. Partially responsible for observed productivity decline | |
| Lynde and Richmond 1992 | United Kingdom aggregate, 1958-89 (time series) | cost function, translog | manufacturing | public capital | significant cost reduction effect | capital labor | public capital complemntary to private capital; aggregate constant returns to scale with public capital | |
| Lynde and Richmond 1993 | United Kingdom aggregate 1966: 1-1990; 2 (time series) | cost function translog (cointegrated) | manufacturing value added | public capital | significant cost reduction effect | capital labor materials | public capital contributes 17% of manufacturing productivity growth | |
| Anderson, Anderstig and Harsman 1990 | Sweden 70 commuting regions, 1970 and 1980 (cross section) | production function, variable returns to scale | aggregate income | main roads railroads airport capacity accessibility | roads significant in 1980; rail significant in 1970; airports significant only when interacted with R&D | capital labor | K: 0.25 L: 0.28; 0.57- 0.75 combined with knowledge capital | |
| Prud'homme | France, 22 regions, 1981-88 growth (cross section), 1988 (cross section) | production function, Cobb-Douglas | aggregate income/L | public capital | significant only when measured per unit of L times land area | capital/labor | K/L:0.20-0.26 |
| Study | Country/Sample | Type of Estimation | Sector or Output Measure | Public Infrastructure Type |
Public Infrastructure Elasticity |
Private Inputs Type |
Private Inputs Elasticity |
Notes |
|---|---|---|---|---|---|---|---|---|
| Ratner 1983 | U.S. aggregate, 1949-73 (time series) | production function, Cobb-Douglas | private business sector output | public capital: non-military, gov't owned equipment and structures | 0.05 - 0.06 | labor/capital, capital adjusted for capacity utilization | L: 0.71-0.72 K: 0.22 | |
| Costa, Ellson and Martin 1987 | U.S. 48 states, 1972 (cross section) | production function, translog | all sectors manufacturing non-agriculture | state and local public capital | 0.20 for all sectors, .19 for manufacturing, 0.21 - 0.26 for non-agr | capital labor | K: -0.06 - 0.11 L: 0.77 - 1.02 | public capital complementary to labor |
| Keeler and Ying 1988 | U.S. 9 regions, 1950-73 (time series/cross section) | cost function, translog | truckingindustry | federal-aidhighway capitalstock | cost elasticity -0.07 | capital, labor fuel, other materials and services | ||
| Deno 1988 | U.S. 36 metropolitan areas, 1970-78 (time series/cross section) | profit function, translog | manufacturing | highways and bridges; water; sewer | output supply elasticity of highway / bridge 0.31-0.57; 0.06 (not sig.) in declining regions | capital labor | highway capital complementary to private capital in growing regions; complementary to labor in full sample | |
| Duffy-Deno and Eberts 1991 | U.S. 28 metropolitan areas, 1980-84 (time series/cross section) | simultaneous equations: personal income and public investment | per capita personal income | public capital | personal income elasticity of public capital 0.08 | capital labor energy | ||
| Aschauer 1989 | U.S. aggregate, 1949-85 (time series) | production function, Cobb-Douglas | GNP/private capital | non-military public capital and core public capital | non-military 0.39 core 0.24 | labor/ private capital | 0.38 | |
| Munnell 1990 | U.S. aggregate, 1948-87 (time series) | production function, Cobb-Douglas | GNP | core public capital | 0.31 - 0.39 | capital labor | K: 0.56 L: 0.11 | |
| Aschauer 1990 | U.S. 48 states (cross section) | determinants of average annual growth rate | state per capita income | average total highway mileage, 1960-85; disaggregated into rural and urban mileage | total: 0.22-0.37 rural: 0.24-0.40 urban: 0.10-0.17 | higher pavement quality contributes to growth; vehicles/highway mile as congestion measure retards growth | ||
| Eisner 1991 | U.S., 48 states, 1970-86 (time series, cross section, and time series/cross section) | production function Cobb-Douglas and translog | GSP | public capital; highway capital, water and sewer, other | public capital insignificant, highway 0.05-0.07 in time series; public capital 0.16, highway 0.06 in cross section | capital labor | K: 0.29 L: 0.77 | uses data from Munnell 1990; estimates of first differences sensitive to scale constraints |
| Tatom 1991 | U.S. aggregate 1950-88 (time series) | production function, translog, 1st differences | private busines ssector output | public capital | 0.03, not significant | capital labor energy | L/K: 0.69 E(price): -0.06 | energy price variable derived from 1st order condition on energy use |
| Garcia-Mila and Mcguire | U.S. 48 states, 1969-83 (time series/cross section) | production function, Cobb-Douglas | GSP | highway capital | 0.04 | capital structures, capital equipment labor | total K: 0.47 L: 0.36-0.45 | |
| McGuire 1992 | U.S. 48 states, 1969-83 (time series/cross section) | production function, Cobb-Douglas (state fixed effects); translog | GSP | highway capital | C-D (fixed eff.): not significant translog: 0.24 | capitallabor | K: 0.23-0.46 L: 0.70-75 | return to scale of 1.2- 1.3 in state fixed effects model; CRS in random effects model |
| Pinnoi 1992 | U.S. 48 states, 1970-86 (time series/cross section) | production function, Cobb-Douglas | GSP | highway capital | 0.06 - 0.08 | capital labor | K: 0.30 L: 0.70 | first-differencing to correct measurement errors in public capital yielded insignificant highway output elasticities |
| Jones, Miaow, Lee and Rickert 1993 | U.S. 48 states, 1983-89 (time series/cross section) | production function, Cobb-Douglas, 5- eqn system | GSP/L | lane mileage, vehicle miles traveled, separate urban and rural, different groups of highway classes | VMT: 0.16-0.23 LM, total: 0.09-0.14 urban VMT, LM: positive rural VMT,LM: negative | capital/labor | K/L: 0.36-0.38 | endogenous congestion and VMT |
| Moomaw and Williams 1991 | U.S. 48 states, 1954-76 (time series/cross section) | multifactor productivity | manufacturing | highway density | significant positive effect | use regional dummies with state data | ||
| Hulten and Schwab 1991 | U.S. 9 regions, 1951-76 (time series) | Multifactor productivity | manufacturing | none | capital labor | no observed role for public infrastructure in different interregional growth rates | ||
| Hulten and Schwab 1991 | U.S. 9 regions, 1951-86 (time series) | multifactor productivity | manufacturing | public capital | not significant | capital labor materials | model predicts significant coef.ficient on K if public capital operates through production function.; but K coef.ficient is significant and public capital coefficient is insignificant; interpretations unclear | |
| Carlino and Mills 1987 | U.S. approx. 3000 counties, 1970-80 growth (cross section) | determinants of county employment and population growth, simultaneous equation estimation | total employment, manufacturing employment, population | interstate highway density | over decade: 0.06 total employment; 0.06 manufacturing employment.; 0.03 population | |||
| Mills and Carlino 1989 | U.S. approx. 3000 counties, 1970-80 growth (cross section) | determinants of county employment and population growth, simultaneous equation estimation | total employment, manufacturing employment, population | interstate highway density | over decade: 0.54 total employment.: 0.17 population |
Note- all reported coefficients are statistically significant unless explicitly noted otherwise
Source: Dr. T.R. Lakshmanan, Director, Bureau of Transportation Statistics, USDOT
