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World economic convergence: Does the estimation methodology matter?

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  • Desli, E.
  • Gkoulgkoutsika, A.

Abstract

An extant empirical literature produces evidence on economic convergence using methods that assume an underlying deterministic trend. Competing approaches that assume a stochastic trend, however, produce only limited evidence of economic convergence. In this paper we address this puzzling feature of the literature by providing a comprehensive analysis of economic convergence using three methodologies that cover all possible underlying assumptions: deterministic, stochastic, and combination trends. We also develop a method for an overall Stochastic Convergence Rate Index, that combines the outcomes of alternative stochastic tests and provides a single measure of the intensity of stochastic convergence. We consider 135 economies over the period 1980–2017. We find that economic convergence occurs at a global level through the formation of convergence clubs, and economic convergence emerges as a deterministic rather than a stochastic process. Tests that ignore deterministic trends tend to understate the evidence for convergence.

Suggested Citation

  • Desli, E. & Gkoulgkoutsika, A., 2020. "World economic convergence: Does the estimation methodology matter?," Economic Modelling, Elsevier, vol. 91(C), pages 138-147.
  • Handle: RePEc:eee:ecmode:v:91:y:2020:i:c:p:138-147
    DOI: 10.1016/j.econmod.2020.05.027
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    More about this item

    Keywords

    Economic growth; Economic convergence; Beta-convergence; Stochastic convergence; log(t) convergence;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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