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Submitted
August 10, 2020
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September 16, 2020
Published
October 7, 2020
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Abstract

This paper examines whether stock prices for fourteen African countries are affected by transitory or permanent shocks. This study answers whether Africa stock market indices are mean-reverting or random-walk in the presence of multiple structural breaks. To investigate African equity price behavior, we considered one and two endogenously determined structural break tests of Zivot and Andrews (1992) and Lumsdaine and Papell (1997), respectively. Findings/Originality: Our results show that almost all African equity price indices follow the random walk processes except for Senegal and Botswana, which exhibit mean-reversion properties in its equity prices. It implies that investors in African stock markets cannot rely on past information and behavior to predict stock market movements or develop their trading strategies. The result also confirms that the Augmented Dickey-Fuller (ADF) unit root test is not applicable in the presence of structural breaks in African stock markets.

Keywords

African stocks structural breaks mean-reversion random-walk unit root test

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Author Biography

Osarumwense Osabuohien-Irabor, Department of International Economics, School of Economics and Management, Ural Federal University, Yekaterinburg, Sverdlovsk Oblast, Russia.

Research scientist (Laboratory for International and Regional Economics)
How to Cite
Osabuohien-Irabor, O. (2020). Unit root tests in the presence of structural breaks: Evidence from African stock markets. Economic Journal of Emerging Markets, 12(2), 119–137. https://doi.org/10.20885/ejem.vol12.iss2.art1
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References

  1. Abakah, E. J. A., Alagidede, P., Mensah, Lord, & Ohene-Asare, K. (2018). Non-linear approach to random walk test in selected African countries. International Journal of Managerial Finance, 14(3), 362–376. https://doi.org/10.1108/IJMF-10-2017-0235
  2. Anoruo, E., & Gil-Alana, L. A. (2011). Mean reversion and long memory in African stock market prices. Journal of Economics and Finance, 35(3), 296–308. https://doi.org/10.1007/s12197-010-9124-0
  3. Ben-David, D., Lumsdaine, R. L., & Papell, D. H. (2003). Unit roots, postwar slowdowns and long-run growth: Evidence from two structural breaks. Empirical Economics, 28(2), 303–319. https://doi.org/10.1007/s001810200132
  4. Chaudhuri, K., & Wu, Y. (2003). Random walk versus breaking trend in stock prices: Evidence from emerging markets. Journal of Banking & Finance, 27(4), 575–592. https://doi.org/10.1016/S0378-4266(01)00252-7
  5. Chia, R., Jiun, C., & Xin, P. W. (2019). Does mean reversion occur in selected African stock markets? In Proceedings of the International Conference on Economics (pp. 60–66).
  6. Chow, K. V., & Denning, K. C. (1993). A simple multiple variance ratio test. Journal of Econometrics, 58(3), 385–401. https://doi.org/10.1016/0304-4076(93)90051-6
  7. Dewandaru, G., Masih, R., & Masih, A. M. M. (2016). Contagion and interdependence across Asia-Pacific equity markets: An analysis based on multi-horizon discrete and continuous wavelet transformations. International Review of Economics & Finance, 43, 363–377. https://doi.org/10.1016/j.iref.2016.01.002
  8. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 76–66. https://doi.org/10.2307/2286348
  9. Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813–836. https://doi.org/10.2307/2171846
  10. Enders, W., & Lee, J. (2012). A unit root test using a fourier series to approximate smooth breaks*. Oxford Bulletin of Economics and Statistics, 74(4), 574–599. https://doi.org/10.1111/j.1468-0084.2011.00662.x
  11. Fama, E. F., & French, K. R. (1988). Permanent and temporary components of stock prices. Journal of Political Economy, 96(2), 246–273. https://doi.org/10.1086/261535
  12. Glynn, J., & Perera, N. (2007). Unit root tests and structural breaks: A survey with applications. Journal of Quantitative Methods for Economics and Business Administration, 3(1), 63–79.
  13. Graham, M., Peltomäki, J., & Sturludóttir, H. (2015). Do capital controls affect stock market efficiency? Lessons from Iceland. International Review of Financial Analysis, 41, 82–88. https://doi.org/10.1016/j.irfa.2015.05.009
  14. Gyamfi, E. N., Kyei, K. A., & Gill, R. (2016). Stationarity of African stock markets under an ESTAR framework. EuroEconomica, 2(35), 93–101.
  15. Hayashi, N. (2005). Structural changes and unit roots in Japan’s macroeconomic time series: Is real business cycle theory supported? Japan and the World Economy, 17(2), 239–259. https://doi.org/10.1016/j.japwor.2003.12.006
  16. Hiremath, G. S., & Narayan, S. (2016). Testing the adaptive market hypothesis and its determinants for the Indian stock markets. Finance Research Letters, 19, 173–180. https://doi.org/10.1016/j.frl.2016.07.009
  17. Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1–3), 159–178. https://doi.org/10.1016/0304-4076(92)90104-Y
  18. Lawal, A., Somoye, R., & Babajide, A. (2017). Are African stock markets efficient? Evidence from wavelet unit root test for random walk. Economics Bulletin, 37(4), 2665–2679.
  19. Lee, J., & Strazicich, M. (2003). Minimum lagrange multiplier unit root test with two structural breaks. The Review of Economics and Statistics, 85(4), 1082–1089.
  20. Lee, J., & Strazicich, M. (2013). Minimum LM unit root test with one structural break. Economics Bulletin, 33(4), 2483–2492.
  21. Ling, T. Y., Nor, A. H. S. M., Saud, N. A., & Ahmad, Z. (2013). Testing for unit roots and structural breaks: Evidence from selected ASEAN macroeconomic time series. International Journal of Trade, Economics and Finance, 4(4), 230–237. https://doi.org/10.7763/ijtef.2013.v4.292
  22. Magnusson, M., & Wydick, B. (2002). How efficient are Africa’s emerging stock markets? The Journal of Development Studies, 38(4), 141–156. https://doi.org/10.1080/00220380412331322441
  23. Moin, S. (2007). New frontier markets tempt investors. African Review of Business and Technology, 1(1), 1–7.
  24. Morris, Q., Van Vuuren, G., & Styger, P. (2009). Further evidence of long memory in the South African stock market. South African Journal of Economics, 77(1), 81–101. https://doi.org/10.1111/j.1813-6982.2009.01203.x
  25. Narayan, P. K., & Popp, S. (2010). A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37(9), 1425–1438. https://doi.org/10.1080/02664760903039883
  26. Narayan, P., Liu, R., & Westerlund, J. (2016). A GARCH model for testing market efficiency. Journal of International Financial Markets, Institutions and Money, 41(C), 121–138. https://doi.org/10.1016/j.intfin.2015.12.008
  27. Nelson, C. R., & Plosser, C. I. (1982). Trends and random walks in macroeconomic time series. Journal of Monterey Economics, 10, 139–162.
  28. Ng, S., & Perron, P. (1995). Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag. Journal of the American Statistical Association, 90(429), 268–281. https://doi.org/10.1080/01621459.1995.10476510
  29. Ng, S., & Perron, P. (2001). LAG length selection and the construction of unit root tests with good size and power. Econometrica, 69(6), 1519–1554. https://doi.org/10.1111/1468-0262.00256
  30. Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361–1401. https://doi.org/10.2307/1913712
  31. Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.2307/2336182
  32. Poterba, J. M., & Summers, L. H. (1988). Mean reversion in stock prices: Evidence and implications. Journal of Financial Economics, 22(1), 27–59. https://doi.org/10.1016/0304-405X(88)90021-9
  33. Senbet, L., & Otchere, I. (2008). Beyond banking: Developing markets; African stock market Organized by the (African Finance for the 21st Century High-Level Seminar No. 21). Tunisia.
  34. Sensoy, A., & Tabak, B. M. (2015). Time-varying long term memory in the European Union stock markets. Physica A: Statistical Mechanics and Its Applications, 436, 147–158. https://doi.org/10.1016/j.physa.2015.05.034
  35. Smith, G., Jefferis, K., & Ryoo, H.-J. (2002). African stock markets: Multiple variance ratio tests of random walks. Applied Financial Economics, 12(7), 475–484. https://doi.org/10.1080/09603100010009957
  36. Suresh, K. G., & Shylajan, C. S. (2015). Structural Breaks and Unit Roots in Indian Macroeconomic Variables. Theoretical and Applied Economics, 4(605), 145–150.
  37. Tiwari, A. K., & Kyophilavong, P. (2014). New evidence from the random walk hypothesis for BRICS stock indices: a wavelet unit root test approach. Economic Modelling, 43, 38–41. https://doi.org/10.1016/j.econmod.2014.07.005
  38. Trabelsi Mnif, A. (2017). Political uncertainty and behavior of Tunisian stock market cycles: Structural unobserved components time series models. Research in International Business and Finance, 39(A), 206–214. https://doi.org/10.1016/j.ribaf.2016.07.029
  39. Tuyon, J., & Ahmad, Z. (2016). Behavioural finance perspectives on Malaysian stock market efficiency. Borsa Istanbul Review, 16(1), 43–61. https://doi.org/10.1016/j.bir.2016.01.001
  40. Urquhart, A., & McGroarty, F. (2016). Are stock markets really efficient? Evidence of the adaptive market hypothesis. International Review of Financial Analysis, 47, 39–49. https://doi.org/10.1016/j.irfa.2016.06.011
  41. Yamamoto, T. (1996). A simple approach to the statistical inference in linear time series models which may have some unit roots. Hitotsubashi Journal of Economics, 37(2), 87–100.
  42. Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270. https://doi.org/10.2307/1391541
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