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Tinatin Akhvlediani and Andrzej Cieślik

Abstract

The paper examines the effects of intra- and inter-regional knowledge spillovers on innovative activities in German states using the augmented Griliches-Jaffe knowledge production function. The “Harris market potential” type index is calculated to proxy for inter-regional knowledge transfers of two types: industrial knowledge transfers generated from the business enterprise sector and academic spillovers generated from universities across all German states. The model also includes the concentration of high-tech enterprises, in order to capture the agglomeration effect in the local economy. The estimation results reveal that not only do local private and university research efforts have a positive and significant effect on local innovative activities, but there are also important interregional knowledge spillovers across the German regions.

Open access

Tinatin Akhvlediani and Andrzej Cieślik

Abstract

The paper examines the effects of intra- and inter-regional knowledge spillovers on innovative activities in German states using the augmented Griliches–Jaffe knowledge production function. The “Harris market potential” type index is calculated to proxy for inter-regional knowledge transfers of two types: industrial knowledge transfers generated from the business enterprise sector and academic spillovers generated from universities across all German states. The model also includes the concentration of high-tech enterprises, in order to capture the agglomeration effect in the local economy. The estimation results reveal that not only do local private and university research efforts have a positive and significant effect on local innovative activities, but there are also important inter-regional knowledge spillovers across the German regions.

Open access

Katarzyna Śledziewska and Tinatin Akhvlediani

Abstract

The paper aims to identify the determinants of exports in high-technology sectors (high-tech, HT) of Visegrad countries (the Visegrad four, V4: Poland, the Czech Republic, Slovakia and Hungary) and the core member states of the European Union (EU). Based on the augmented gravity model, we estimate the regressions on panel data of the bilateral export flows of the EU-15 and V4 with the rest of the world in 1999–2011, by employing the Poisson pseudo-maximum-likelihood (PPML) estimator. The comparison of the estimations of overall export flows with the estimates explicitly done for the high-tech sectors allows us to outline the main characteristics of the existing gap in high-tech export performances of the EU-15 and V4. Estimation results find that while for the EU-15, human capital accumulation is statistically significant and export flows increase with similarity in physical capital accumulation of the trade partner; for V4, instead of similarity, the difference in physical capital stock increases exports and human capital accumulation does not yield statistically significant effects.