EducaciÃ³n y Crecimiento EconÃ³mico Provincial en Argentina
AbstractInvestment in education is an essential element for the economic growth of a country. Theory supports this argument with models that stress the individual and social benefits of education. Although the empirical literature shows ample consensus regarding the existence of positive individual returns to education, its impact on economic growth is, nevertheless, not clear. This paper applies panel data techniques to measure the effects of education on long-run economic growth, to the case of regional growth in Argentina.
There are two major problems when estimating growth regressions: 1) individual effects are correlated with explanatory variables, and 2) simultaneity biases. To avoid these problems, a generalized method of moments (GMM) estimator is used (Arellano and Bond, 1991; Caselli, Esquivel and Lefort, 1996).
Two types of models were tested. Standard and human capital-augmented Solow models, and Barro specifications. The standard Solow model fit poorly in most cases. Likewise, the augmented Solow model presented wrong signs on most coefficients. However, education always showed a positive and significative impact on long-run growth. On the other hand, in a-la-Barro specifications always education present a positive and important impact on growth, using aggregate measures of education achievement levels, although using disaggregate measures of education the results were not so clear. It turns out that, depending on the empiric specification, secondary school and university education have an important effect on growth.Regarding convergence, the empirical evidence is mixed. Under certain specifications, GMM estimation finds strong evidence of convergence at a rather fast speed (around 5% per year), which is twice as fast as estimates using standard techniques for the US and Japan (Barro and Sala-i-Martin, 1995). However, when using more demanding specifications, the data does not support the conditional convergence hypothesis.
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