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A dynamic panel data (DPD) model is estimated to assess the contribution of the average schooling years, the education expenditure and the inventive coefficient—as an approximation for innovation—to the increased productivity of the Mexican states. The potential difficulties of endogeneity and serial correlation are controlled by adopting system General Method of Moments (GMM) procedures. The findings are compatible with the theory. The importance of the lags is confirmed and the positive and significant impacts on productivity tend to vary according to the income level and the geographical location of the regions. Innovation is an important contributor to northern, central and richer states’ productivity, but education expenditure is important for the poorer states and scholarly attainment stands out in the southern states. The analysis emerging from the model concludes that these regional differences should be seen as a potential opportunity for designing customized policies capable of increasing the productivity and not as a weakness.

Contribution of Education and Innovation to Productivity among Mexican Regions: A Dynamic Panel Data Analysis