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Testing Growth Convergence with Time Series Data— a non-parametric approach

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  • Mikael Linden

Abstract

A non-parametric time series testing is suggested to analyse the convergence of international output per-capita gaps. Non-parametric tests are based on signs and ranks of time series properties of output differences. The methods are applied to logs of USA percapita income differences for 16 OECD countries from 1900-97. In contrast to the results obtained by Bernard & Durlauf (1995) for the period 1900-87, convergence of output gaps was evident for the majority of countries. However, the trends in 1970-97 and 1987-97 are noticeably more complicated than the homogeneous convergence found in the pre-1970 period. The results indicate that widening USA gaps are now more likely to emerge than steady-state or narrowing gaps.

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  • Mikael Linden, 2000. "Testing Growth Convergence with Time Series Data— a non-parametric approach," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(3), pages 361-370.
    • Handle: RePEc:taf:irapec:v:14:y:2000:i:3:p:361-370
    DOI: 10.1080/02692170050084088
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    Cited by:

    1. Domingo Rodríguez Benavides & Ignacio Perrotini Hernández & Miguel Ángel Mendoza González, 2014. "Economic Growth and Convergence in Latin America, 1950-2010," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(2), pages 253-284, July-Dece.
    2. Ozgen Sayginsoy, 2004. "Powerful and Serial Correlation Robust Tests of the Economic Convergence Hypothesis," Discussion Papers 04-07, University at Albany, SUNY, Department of Economics.
    3. Ozgen Sayginsoy, 2005. "Powerful and Serial Correlation Robust Tests of the Economic Convergence Hypothesis," Econometrics 0503014, University Library of Munich, Germany, revised 11 Mar 2005.

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