GROWTH WITH TECHNICAL CHANGE AND HUMAN CAPITAL: TRANSITION DYNAMICS VERSUS STEADY STATE PREDICTIONS

Fidel Perez and Chris Papageorgiou ()
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Fidel Perez: Universidad Pblica de Navarra

No 213, Computing in Economics and Finance 2000 from Society for Computational Economics

Abstract: This paper studies the steady-state and transitional dynamics predictions of an R&D-based growth model and evaluates their performance in explaining income disparities across countries. We find that even though steady-state conditions do slightly better at predicting schooling enrollment and investment rates, transitional dynamics predictions better fit the cross-country output per worker data. These results suggest that the traditional view of a world in which nations move along their distinct balanced-growth paths is as likely as the one in which countries move along adjustment paths toward a common (very long-run) steady state. In addition, the model provides a reduced form empirical specification that incorporates capital input and R&D-effort measures. Therefore, we can compare the performance of the standard neoclassical growth model to that of an R&D-based growth model with human capital and imperfect competition, like ours. This stands in contrast to the prevalent view that reduced form regressions cannot discriminate between neoclassical and R&D-based growth frameworks.

Date: 2000-07-05
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Working Paper: Growth with Technical Change and Human Capital: Transition Dynamics Versus Steady State Predictions (1999)
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