The impact of transport infrastructure investment on regional employment: an empirical investigation

Imperial Users onl

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

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.

Causal linkages between highways and sector-level employment

While transport infrastructure investments have usually been viewed to have long-term impacts on employment, what is perhaps not immediately clear is the direction of causality. This paper has sought to disentangle the causal relationship between highway infrastructure and employment, using panel data for the 48 contiguous US states from 1984 to 1997. Of particular emphasis in this analysis is the sectoral differences in the causal and spatial effects of highway capacity expansions for employment growth in alternative sectors of the economy. The results indicate that lane-mile additions of own-state major highways could increase state employment growth in the services sector while reducing growth in manufacturing. However, the causal relationship is also found to work the other way around. That is, both the rapid growth in services employment and the slowdown in manufacturing jobs temporally lead to increases in roadway capacity of non-interstate major roads. Our analysis also shows that highway infrastructure could produce both positive and negative employment spillovers across states. We find that improvements in non-interstate major roads outside the state border are beneficial to the manufacturing sector which generally serves regional and national markets. For the services sector, however, employment gains from interstate highways in the same state may come at the expense of other states as there is clear evidence of negative employment spillovers from interstate lane-mile additions.Highway infrastructure Employment Dynamic panel models Granger causality Spatial spillovers