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Convergence, endogenous growth, and productivity disturbances

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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 arc 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.
Original languageEnglish
Pages (from-to)535-547
JournalJournal of Monetary Economics
Volume38
Issue number3
DOIs
Publication statusPublished - Dec 1996
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Research Keywords

  • Cross-country dependence
  • Cross-country regression
  • Increasing returns
  • Stochastic growth
  • Time-series regression

Policy Impact

  • Cited in Policy Documents

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