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Highway Infrastructure Investment and Regional Employment Growth: Dynamic Panel Regression Analysis

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  • Piyapong Jiwattanakulpaisarn

    ()

  • Robert Noland

    ()

  • Daniel Graham

    ()

  • John Polak

    ()

Abstract

A number of macro-level studies attempting to establish the statistical link between public investment in highway infrastructure and employment have applied econometric techniques to estimate the effect of highways while controlling for the effects associated with other factors. Unfortunately, direct use of empirical findings from these historic and recent studies, in shaping transport policy and supporting particular investment decisions, has been rather limited by mixed and inconclusive evidence in the literature. Apart from the common differences among these studies in scope and methodology, another possible reason for the contradictory evidence is that much of the previous work has generally suffered from several methodology drawbacks. In many studies, for instance, several important determinants of employment growth are omitted, and the choices of control variables included in the estimated equations generally are not based on theory. Those studies based solely on cross-sectional data also typically do not account for unobserved regional heterogeneity that may explain spatial differences in employment changes. Moreover, the possibility that the causal relationship between transportation investment and economic growth could work in both directions is generally ignored. This paper attempts to shed some light on this controversy by analysing the effect of highway investment on county-level employment in the State of North Carolina, United States. We derive a reduced from model of equilibrium employment that considers the effects of highways and other potential factors on the supply and demand for labour. Given the potential for lagged responses of the labour market to any exogenous shock, we assume a partial adjustment process for actual employment in our empirical model. A panel data set for 100 North Carolina counties from 1985 to 1997 is used in order to control for unobserved county and time specific effects using panel regression techniques. We also address the causality issue by the use of a two-stage least squares procedure with an instrumental variable. Our main results are that the employment effect of highway infrastructure depends critically on model specifications considered, and failure to account for the dynamics of employment adjustment could lead to an upward bias in the estimated effect of highways.

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa06p207.

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Date of creation: Aug 2006
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Handle: RePEc:wiw:wiwrsa:ersa06p207

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References

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  1. Haughwout, Andrew F., 1997. "Central city infrastructure investment and suburban house values," Regional Science and Urban Economics, Elsevier, vol. 27(2), pages 199-215, April.
  2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  3. Douglas R. Dalenberg & Mark D. Partridge & Dan S. Rickman, 1998. "Public Infrastructure: Pork or Jobs Creator?," Public Finance Review, , vol. 26(1), pages 24-52, January.
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  8. Alfredo M. Pereira, 2000. "Is All Public Capital Created Equal?," The Review of Economics and Statistics, MIT Press, vol. 82(3), pages 513-518, August.
  9. Daniel Graham, 2000. "Spatial Variation in Labour Productivity in British Manufacturing," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(3), pages 323-341.
  10. Richard Blundell & Steve Bond, 1999. "GMM estimation with persistent panel data: an application to production functions," IFS Working Papers W99/04, Institute for Fiscal Studies.
  11. McDonald, John F. & Osuji, Clifford I., 1995. "The effect of anticipated transportation improvement on residential land values," Regional Science and Urban Economics, Elsevier, vol. 25(3), pages 261-278, June.
  12. Noland, Robert B., 2001. "Relationships between highway capacity and induced vehicle travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 47-72, January.
  13. Robert Cervero & Mark Hansen, 2002. "Induced Travel Demand and Induced Road Investment: A Simultaneous Equation Analysis," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 36(3), pages 469-490, September.
  14. Aschauer, David Alan, 1989. "Is public expenditure productive?," Journal of Monetary Economics, Elsevier, vol. 23(2), pages 177-200, March.
  15. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  16. Randall W. Eberts & Joe A. Stone, 1992. "Wage and Employment Adjustment in Local Labor Markets," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wea, December.
  17. Bollinger, Christopher R. & Ihlanfeldt, Keith R., 2003. "The intraurban spatial distribution of employment: which government interventions make a difference?," Journal of Urban Economics, Elsevier, vol. 53(3), pages 396-412, May.
  18. Robert Noland & William Cowart, 2000. "Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel," Transportation, Springer, vol. 27(4), pages 363-390, December.
  19. Mark, Stephen T. & McGuire, Therese J. & Papke, Leslie E., 2000. "The Influence of Taxes on Employment and Population Growth: Evidence from the Washington, D.C. Metropolitan Area," National Tax Journal, National Tax Association, vol. 53(n. 1), pages 105-24, March.
  20. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
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