The TFP model block of the GMR-Hungary impact assessment model

Abstract

The present paper introduces the TFP (Total factor productivity) block of the GMR-Hungary impact model. The TFP blocks have an essential role in the functioning of GMR-models since they examine the productivity effects of the key variables of the knowledge-based economic policy (R\&D expenditures, embeddedness in scientific networks, entrepreneurial attitudes, human resources). These productivity effects are going to be included in the other blocks of the GMR-model to estimate the expected regional and national economic effects of the key variables. The TFP block contains two equations that are simultaneously estimated by regression analysis. On the one hand, it includes an equation that estimates how new patents come into existence. On the other hand, an equation that describes the evolution of productivity in the model.

As the first step, we determined the regional Solow-residuals of a Cobb-Douglas production function, which will serve the dependent variable of the second equation. After Solow-residuals were calculated, each variable became available to carry out the regression
analysis. Both equations include interaction terms, which control for regional heterogeneity. After the estimation, certain coefficients of the equations came through a calibration process. The purpose of the calibration is twofold. Firstly, it ensures a better goodness-of-fit of the model to the observed data. Secondly, the calibration assures an additional factor that helps to analyze the differences in the effectiveness among regions.
Applying the TFP model to assess the effectiveness of the variables to be of interest, many conclusions can be drawn. On the one hand, the effect of an increase in the variables that support R&D activities (R&D expenditures, embeddedness in scientific networks) seems to be the most effective in the capital and those regions where the leading universities of Hungary are located.
On the other hand, the effect of an increase in the variables that reflects the development of entrepreneurship and human resources seems to be the most effective in the capital and those regions that are typically regarded as industrial regions.