IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/118357.html
   My bibliography  Save this paper

Do African economies grow similarly?

Author

Listed:
  • Franses, Ph.H.B.F.

Abstract

This paper examines economic growth in 52 African countries for 1961-2016 and seeks to find if there is common growth. As all African countries have their particular features, concerning climate, harvest, industry, size, politics, and infrastructure, and more, it seems best to rely on a non-parametric method. Dynamic Time Warping is such a convenient method, also as it allows leads and lags across countries to vary over time, and as it can easily be incorporated into a clustering technique. Five clusters are found, two of which concern Equatorial Guinea and Botswana, and the three other clusters have common growth rates of about 0, 2 and 4 over more than five decades.

Suggested Citation

  • Franses, Ph.H.B.F., 2019. "Do African economies grow similarly?," Econometric Institute Research Papers EI2019-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:118357
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/118357/EI2019-26.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Franses, Ph.H.B.F. & Wiemann, T., 2018. "Intertemporal Similarity of Economic Time Series," Econometric Institute Research Papers EI2018-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Wang, Gang-Jin & Xie, Chi & Han, Feng & Sun, Bo, 2012. "Similarity measure and topology evolution of foreign exchange markets using dynamic time warping method: Evidence from minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4136-4146.
    3. Sullivan, Mary Kay & Miller, Alex, 1996. "Segmenting the informal venture capital market: Economic, hedonistic, and altruistic investors," Journal of Business Research, Elsevier, vol. 36(1), pages 25-35, May.
    4. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
    5. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    6. Fruhwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2008. "Model-Based Clustering of Multiple Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 78-89, January.
    7. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-380, October.
    8. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-395, October.
    9. Franses, Ph.H.B.F. & S. Vasilev (Simeon), 2019. "Real GDP growth in Africa, 1963-2016," Econometric Institute Research Papers EI2019-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Franses, Ph.H.B.F. & Wiemann, T., 2018. "Intertemporal Similarity of Economic Time Series," Econometric Institute Research Papers EI2018-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Philip Hans Franses & Thomas Wiemann, 2020. "Intertemporal Similarity of Economic Time Series: An Application of Dynamic Time Warping," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 59-75, June.
    3. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    4. Matteo Lanzafame, 2010. "The nature of regional unemployment in Italy," Empirical Economics, Springer, vol. 39(3), pages 877-895, December.
    5. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014. "Forecasting with factor-augmented error correction models," International Journal of Forecasting, Elsevier, vol. 30(3), pages 589-612.
    6. Marco Centoni & Gianluca Cubadda, 2011. "Modelling comovements of economic time series: a selective survey," Statistica, Department of Statistics, University of Bologna, vol. 71(2), pages 267-294.
    7. Alain Hecq & Ivan Ricardo & Ines Wilms, 2024. "Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach," Papers 2407.07973, arXiv.org.
    8. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014. "Forecasting with factor-augmented error correction models," International Journal of Forecasting, Elsevier, vol. 30(3), pages 589-612.
    9. Neville Francis & Michael T. Owyang & Ozge Savascin, 2017. "An endogenously clustered factor approach to international business cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1261-1276, November.
    10. Ibrahim A. Onour, 2012. "Crude oil price and stock markets in major oil-exporting countries: evidence of decoupling feature," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 5(1), pages 1-10.
    11. Apostolos Serletis & Ricardo Rangel-Ruiz, 2007. "Testing for Common Features in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 14, pages 172-187, World Scientific Publishing Co. Pte. Ltd..
    12. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
    13. Osmani Teixeira de Carvalho de Guillén & Carlos Hamilton Vasconcelos Araújo, 2005. "O Mecanismo De Transmissão Da Taxa De Câmbio Para Índices De Preços: Uma Análise Vecm Para O Brasil," Anais do XXXIII Encontro Nacional de Economia [Proceedings of the 33rd Brazilian Economics Meeting] 034, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    14. Jinghui Chen & Masahito Kobayashi & Michael McAleer, 2017. "Testing for volatility co-movement in bivariate stochastic volatility models," Documentos de Trabajo del ICAE 2017-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    15. Lafuente, Juan A. & Novales, Alfonso, 2003. "Optimal hedging under departures from the cost-of-carry valuation: Evidence from the Spanish stock index futures market," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1053-1078, June.
    16. Gaia Garino & Lucio Sarno, 2004. "Speculative Bubbles in U.K. House Prices: Some New Evidence," Southern Economic Journal, John Wiley & Sons, vol. 70(4), pages 777-795, April.
    17. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
    18. Chen, Xiaoshan & Mills, Terence C., 2009. "Evaluating growth cycle synchronisation in the EU," Economic Modelling, Elsevier, vol. 26(2), pages 342-351, March.
    19. Demetrescu, Matei & Salish, Nazarii, 2024. "(Structural) VAR models with ignored changes in mean and volatility," International Journal of Forecasting, Elsevier, vol. 40(2), pages 840-854.
    20. Sharon Kozicki & Peter A. Tinsley, "undated". "Moving Endpoints in Macrofinance," Computing in Economics and Finance 1996 _058, Society for Computational Economics.

    More about this item

    Keywords

    Economic growth; Africa; Non-parametric method; Dynamic Time Warping; Clusters;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • N17 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Africa; Oceania

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ems:eureir:118357. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.