Public infrastructure capital, scale economies and returns to variety

dependent variable is the logarithm of the number of manufacturing establishments, and the
independent variable is the logarithm of the public infrastructure capital stock. The latter is again
introduced as three forms (total, productive, and social) in each of the four spatial levels of reference.
Again, the regressions have included a constant term, a time trend, and a set of (N-1) dummy
variables capturing the regional or sectoral specific effects (not reported on here due to space
limitations). Thus, the working equation becomes:

n_u = G_it +1 + u_it                                                                     (42)
(notation as in previous equations)

The results of tables 12 to 15 show that there is no direct impact of public capital on the
number of establishments, as the public capital coefficients are statistically insignificant in all these
regressions. This is true for all spatial levels. However, as Holtz-Eakin and Lovely have argued, there
is the danger that such a regression “fails to control for the resources available to the manufacturing
sector” (1996, p. 120).

Table 12 Infrastructure effects on the equilibrium number of firms (regression based infrastructure and
time): Regional panel for total manufacturing, 1982-1991

*** Statistically significant at 1% level, ** Statistically significant at 5% level, * Statistically significant at 10% level

Table 13 Infrastructure effects on the equilibrium number of firms (regression based infrastructure and

time): Greece panel for sectors, 1982-1991

*** Statistically significant at 1% level, ** Statistically significant at 5% level, * Statistically significant at 10% level

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