up to the technology leader shows more consistency across sectors. It is not so much human
capital that dominates the sectoral growth process but rather the induced effect through
catch-up with the technology leader. The catch-up effect consistently drives the growth
process in almost all sectors. In particular, the states with initially low levels of GDP show
more pronounced catch-up effects. The effect of human capital is indirect, working through
the interaction with the catch-up term to drive the growth process. Geographic and
technological proximity are both relevant for the sectoral productivity growth. However, the
technological effect seems to be more prominent. Further improvement regarding models
and data could help to substantiate our conclusion. As far as models improvement are
concerned, possible consideration for future studies could be: system approach estimation,
panel data set up and higher order models accounting for both technological and sectoral
spillover effects.
References
Anselin, L. and S. Rey 1991. “Properties of Tests for Spatial Dependence in Linear
Regression Models” Geographic Analysis 23:110—131.
Anselin, L. and R. Florax 1995. “Small Sample Properties of Tests for Spatial Dependence in
Regression Models. In New direction in Spatial Econometrics, ed. L Anselin and R
Florax. Berlin: Springer Verlag.
Abreu, M., H.L.F. de Groot and R.J.G.M. Florax 2005. “A Meta-Analysis of β-
Convergence: The Legendary 2%” Journal of Economic Surveys 19: 389—420.
Barro, R.J. and X. Sala-i-Martin 1991. “Convergence across States and Regions.” Brookings
Papers on Economic Activity 1:107—58.
Barro, R. J. and X. Sala-i-Martin 1995. “Economic Growth” McGraw Hill, New York.
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