2 resultados para Directed technical change
em University of Connecticut - USA
Resumo:
We examine the effects of technology on productivity growth by disaggregating total output into sectoral components, exploring the roles of investment and technology on productivity growth for countries in different income groups. We find that for low-income countries, investment is the most important determinant of productivity growth. While investment plays an important role in determining productivity growth in middle-income countries, additional effects resulting from technological change also emerge. Investment ceases to have a significant effect on productivity growth in high-income countries.
Resumo:
In this paper we introduce technical efficiency via the intercept that evolve over time as a AR(1) process in a stochastic frontier (SF) framework in a panel data framework. Following are the distinguishing features of the model. First, the model is dynamic in nature. Second, it can separate technical inefficiency from fixed firm-specific effects which are not part of inefficiency. Third, the model allows one to estimate technical change separate from change in technical efficiency. We propose the ML method to estimate the parameters of the model. Finally, we derive expressions to calculate/predict technical inefficiency (efficiency).