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Empirics for Economic Growth and Convergence

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Quah, Danny

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Abstract

The convergence hypothesis has generated a huge empirical literature: this paper critically reviews some of the earlier key findings, clarifies their implications, and relates them to more recent results. Particular attention is devoted to interpreting convergence empirics. The main findings are: (1) The much-heralded uniform 2% rate of convergence could arise for reasons unrelated to the dynamics of economic growth. (2) Usual empirical analyses - cross-section (conditional) convergence regressions, time-series modelling, panel data analysis - can be misleading for understanding convergence; a model of polarization in economic growth clarifies those difficulties. (3) The data, more revealingly modelled, show persistence and immobility across countries: some evidence supports Baumol's idea of `convergence clubs'; some evidence shows the poor getting poorer, and the rich richer, with the middle class vanishing. (4) Convergence, unambiguous up to sampling error, is observed across US states.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 1140.

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Date of creation: Mar 1995
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Handle: RePEc:cpr:ceprdp:1140

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Related research
Keywords: Evolving Distributions; Galton's Fallacy; Polarization; Regional Dynamics; Stochastic Kernal; Unit Root;

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Find related papers by JEL classification:
C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
O41 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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