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Are GDP fluctuations transitory or permanent in African countries? Sequential Panel Selection Method

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  • Chang, Tsangyao
  • Chu, Hsiao-Ping
  • Ranjbar, Omid

Abstract

The purpose of this study is to examine whether GDP shocks are transitory or permanent in African countries. The Sequential Panel Selection Method (SPSM) using Panel KSS test with a Fourier function—which is good enough to control for structural breaks and nonlinearity as well as cross-section dependency and heterogeneity is applied to per capita real GDP data for 52 African countries for the period 1969 to 2011. The SPSM classifies the whole panel into a group of stationary series and a group of non-stationary series that is very suitable to identify how many and which series in the panel are stationary processes. The empirical results from several conventional unit root tests indicate that the per capita real GDP for the countries are non-stationary, however, when the SPSM using the Panel KSS unit root test with a Fourier function is conducted, we find that the per capita real GDP are stationary in 50 out of the 52 African countries. Besides, we indicate that allowing for nonlinearities and structural breaks in the series results in more rejection of the null of unit root hypothesis. Our results thereby point out to the importance of the proper modeling of both structural breaks and nonlinearities in real output levels of developing countries. The findings imply that GDP fluctuations in African countries are overall transitory and they provide important policy implications for African countries.

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  • Chang, Tsangyao & Chu, Hsiao-Ping & Ranjbar, Omid, 2014. "Are GDP fluctuations transitory or permanent in African countries? Sequential Panel Selection Method," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 380-399.
  • Handle: RePEc:eee:reveco:v:29:y:2014:i:c:p:380-399
    DOI: 10.1016/j.iref.2013.07.001
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    2. Wang, Juan & Zhang, Dongxiang & Zhang, Jian, 2015. "Mean reversion in stock prices of seven Asian stock markets: Unit root test and stationary test with Fourier functions," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 157-164.
    3. Furkan Emirmahmutoglu & Rangan Gupta & Stephen M. Miller & Tolga Omay, 2020. "Is real per capita state personal income stationary? New nonlinear, asymmetric panel‐data evidence," Bulletin of Economic Research, Wiley Blackwell, vol. 72(1), pages 50-62, January.
    4. Gil-Alana, Luis A. & Mudida, Robert & Zerbo, Eleazar, 2021. "GDP per capita IN SUB-SAHARAN Africa: A time series approach using long memory," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 175-190.
    5. Gökhan Konat & Fatma Zeren, 2021. "Is Real Gross Domestic Product (GDP) Series Stationary in EU Countries? Evidence from the RALS-CIPS Test," Economics Bulletin, AccessEcon, vol. 41(3), pages 1813-1825.
    6. Lee, Yi-Lung & Ranjbar, Omid & Jahangard, Fateme & Chang, Tsangyao, 2020. "Analyzing slowdown and meltdowns in the African countries: New evidence using Fourier quantile unit root test," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 187-198.
    7. Sakiru Solarin & Emmanuel Anoruo, 2015. "Nonlinearity and the Unit Root Hypothesis for African Per Capita Real GDP," International Economic Journal, Taylor & Francis Journals, vol. 29(4), pages 617-630, December.
    8. Sakiru Adebola Solarin, 2017. "Testing for the Stationarity in Total Factor Productivity: Nonlinearity Evidence from 79 Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(1), pages 141-158, March.

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    More about this item

    Keywords

    Sequential Panel Selection Method; Panel KSS unit root test; Fourier function; Policy implications; African countries;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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