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Convergence, Endogenous Growth, and Productivity Disturbances

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Leung, Charles K
Quah, Danny

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Abstract

Kelly (1992) has recently shown that evidence on convergence cannot be taken as evidence against endogenous growth in general. This study uses a well-known class of stochastic growth models to show other difficulties with traditional empirical studies of convergence. Key parameters typically cannot be estimated consistently in cross-section regressions. When the parameters are assumed known, implications for convergence are unavailable except under restrictive and economically unmotivated assumptions. Those same assumptions that relate key parameters to cross-country convergence render cross-section regressions impossible to estimate consistently.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 1383.

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Date of creation: Apr 1996
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Handle: RePEc:cpr:ceprdp:1383

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Related research
Keywords: Cross-country Dependence Cross-country Regression Increasing Returns Stochastic Growth Time-series Regression

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Find related papers by JEL classification:
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
O41 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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