A Romerian Contribution to the Empirics of Economic Growth
AbstractMankiw Romer and Weil (1992) made the Solovian set up widely-used to test the determinants of economic growth and the speed of convergence. Subsequently, in almost all convergence studies, an exogenously growing technology is assumed and this component is treated as part of the constant term. In this study, we expand the Mankiw Romer and Weil (1992) set-up through a Solovianized Romer (1990) framework, which allows us to decompose the exogenously growing technological progress. Within this framework, the growth rate of technology depends on the characteristics of the R&D sector, including the share of labor devoted to R&D activities. We estimate the convergence equation derived from Solovianized Romer model for 31 OECD countries for the period 1980-2008 by applying the system GMM approach. The empirical findings of the model supports the conditional convergence hypothesis, but predicts a much lower convergence rate (0.01) than that predicted by the existing empirical growth literature (0.02). The model supports the positive and significant role of R&D on economic growth. Another contribution of the model is the elegant introduction of human capital to the convergence equation.
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Bibliographic InfoPaper provided by Izmir University of Economics in its series Working Papers with number 1201.
Length: 41 pages
Date of creation: Jan 2012
Date of revision:
Convergence; Economic Growth; Exogenous Technological Change;
Find related papers by JEL classification:
- O30 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - General
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
- O50 - Economic Development, Technological Change, and Growth - - Economywide Country Studies - - - General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
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