On the Effects of the BRICS on World Economic Growth

Bosupeng, Mpho (2017): On the Effects of the BRICS on World Economic Growth. Published in: Journal of Statistics Applications & Probability , Vol. 2, No. 6 (2017): pp. 429-439.

Abstract

The purpose of this empirical study is to examine the potential effects of the BRICS on other economies’ economic growth over the period 1960-2013. This investigation deploys the Saikkonen and Lu ̈tkepohl cointegration methodology to validate long run relations between Brazil and China’s economic growth and other nation’s output growth. The study further uses the Toda and Yamamoto approach to Granger causality to examine long run causal links between the BRICS economic growth. The results show that all countries exhibit long run relations with China and Brazil’s economic growth. In addition, the results prove that Brazil’s economic growth is induced by South Africa, China and India’s economic growth.

• Item Type: MPRA Paper
• Language: English
• Keywords: economic growth; BRICS; developing economies; economic integration.
• Subjects: F - International Economics > F0 - General > F02 - International Economic Order and Integration

References

Amador, J. (2012). ‘Energy content in manufacturing exports: A cross country analysis’. Energy Economics, Vol. 34, pp. 1074:1081.

Chang, Chun-Ping, Na Berdiev, A. and Lee, Chien-Chiang (2013). ‘Energy exports, globalization and economic growth: The case of South Caucasus’. Economic Modelling, Vol. 33, pp. 383-346.

Sharma, K. (2003). ‘Factors determining India’s export performance’. Journal of Asian Economics, Vol. 14, pp. 435-446.

Tekin, R. B. (2012). ‘Economic growth, exports and foreign direct investment in least developed countries: a panel Granger causality analysis’. Economic Modelling, 29: 868-878.

Asemota, O. M., and Bala, D. A. (2011). ‘A Kalman Filter approach to Fisher effect: Evidence from Nigeria’. CBN Journal of Applied Statistics, Vol. 2, No. 1, pp. 71-91.

Caporale, G. M., and Pittis, N. (1999). ‘Efficient estimation of cointegrating vectors and testing for causality in vector autoregressions’. Journal of Economic Issues, Vol. 13, pp. 3-35.

Chang, Chun-Ping., Berdiev, A. N., and Lee, Chien-Chiang. (2013) ‘Energy exports, globalization and economic growth: The case of South Caucasus’. Economic Modelling, Vol. 33, pp.383-346.

Dickey, D. A., and Fuller, W. A. (1979). ‘Distribution of the estimators for autoregressive time series with a unit root’. Journal of the American Statistical Association, Vol. 74, No. 366, pp. 427-431.

Elliott, G. (1998). ‘On the robustness of cointegration methods when regressors almost have a unit root’. Econometrica, Vol. 66, No.1, pp. 149-158. doi:10.2307/2998544.

Engle, R. F., and Granger, C. W. (1987). ‘Cointegration and error correction: representation, estimation, and testing’. Econometrica, Vol. 55, No. 2, pp. 251-276. doi:10.2307/1913236.

Granger, C. J. (1981). ‘Some properties of time series data and their use in econometric model specification’. Journal of Econometrics, Vol. 55, pp. 251-276. doi:10.1016/0304-4076(81)90079-8.

Granger, C. W. J. and Engle, R. F. (1985). ‘Dynamic model specification with equilibrium constraints’. University of California, San Diego.

Granger, C. W. J., and Weiss, A. A. (1983). ‘Time series analysis of error correction models’. In Karlim, S; Amemiya, T., and Goodman, L. A. Studies in Economic Time Series and Multivariate Statistics, (Academic Press: New York). doi:10.1016/b978-0-12-398750-1.50018-8.

Granger, C. W. J. (1969). ‘Investigating causal relations by econometric models: cross spectral methods’. Econometrica, Vol. 37, No. 3, pp. 424- 438. doi:10.2307/1912791. http://www.theglobaleconomy.com/ (Retrieved 11 January 2016).

Hovarth, W., and Watson, M. (1995). ‘Testing for cointegration when some of the cointegrating vectors are prespecified’. Econometric Theory, Vol. 11, No.5, pp. 984-1014. doi:10.1017/s0266466600009944.

Johansen, S. (1991a). ‘Estimation and hypothesis testing of cointegration vectors in Gaussian Vector Autoregressive models’. Econometrica, Vol. 59, No. 6, pp. 1551-1580. doi:10.2307/2938278.

Johansen, S. (1988b). ‘Statistical analysis of cointegration vectors’. Journal of Economic Dynamics and Control, Vol. 12, pp. 231-254. doi:10.1016/0165-1889(88)90041-3.

Johansen, S., and Juselius, K. (1990). ‘Maximum likelihood estimation and inference on cointegration with applications to the demand for money’. Oxford Bulletin of Economics and Statistics, Vol. 52, No. 2, pp. 169-210. doi:10.1111/j.1468-0084.1990.mp52002003.x.

Mavrotas, G., and Kelly, R. (2001). ‘Old wine in new bottle: testing causality between savings and growth’. The Manchester School Supplement, pp. 97-105.

Park, J. Y. (1992a). ‘Canonical cointegration regression’. Econometrica, Vol. 60, pp.119-144.

Park, J. Y. (1990b). ‘Testing for unit roots and cointegration by variable addition’. Advances in Econometrics, Vol. 8, pp. 107-133.

Phillips, P. C. B and Durlauf, S. N. (1986). ‘Multiple time series regression with integrated processes’. Review of Economic Studies, Vol. 53, pp. 473-495. doi:10.2307/2297602.

Phillips, P. C. B., and Hansen, B. E (1990). ‘Statistical inference in instrumental variable with I(1) processes’. Review of Economic Studies, Vol. 57, pp. 99-125. doi:10.2307/2297545.

Phillips, P. C. B., and Ouilaris, S. (1986). ‘Testing for cointegration’. Cowles Foundation Discussion Paper, No. 809.

Phillips, P. C. B., and Park, J. Y. (1986). ‘Asymptotic equivalence of OLS and GLS in regression with integrated regressors’. Cowles Foundation Discussion Paper, No. 802.

Phillips, P. C. B., and Perron, P. (1988). ‘Testing for a unit root in time series regression’. Biometrika, Vol. 75, No. 2, pp. 335-346. doi:10.2307/2336182.

Rambaldi, A. N. (1997). ‘Mutliple time series models and testing for causality and exogeneity: a review’. Working Papers in Econometrics and Applied Statistics, No. 96. Department of Econometrics, University of New England.

Rambaldi, A. N., and Doran, H. E. (1996). ‘Testing for Granger non-causality in cointegrated systems made easy’. Working Papers in Econometrics and Applied Statistics, No.88. Department of Econometrics, University of New England.

Saikkonen, P. (1992). ‘Estimation and testing of cointegrated systems by an autoregressive approximation’. Econometric Theory, Vol. 8 No. 1, pp. 1-27. doi:10.1017/s0266466600010720.

Saikkonen, P., and Lu ̈tkepohl, H. (2000). ‘Testing for the cointegrating rank of a VAR process with an intercept’. Economic Theory, Vol. 16, pp. 373-406.

Stock, J. H. (1987). ‘Asymptotic properties of least squares estimates of cointegration vectors’. Econometrica, Vol. 55, No. 5, pp. 1035-1056. doi:10.2307/1911260.

Stock, J. H., and Watson, M. W (1987). ‘Testing for common trends’. Working Paper in Econometrics (Hoover Institution, Stanford, CA).

Toda., H. Y., and Yamamoto, T. (1995). ‘Statistical inference in vector autoregressions with possibly integrated processes’. Journal of Econometrics, Vol. 66, pp. 225-250.

Wolde-Rufael, Y. (2005). ‘Energy demand and economic growth: the African experience’. Journal of Policy Modeling, Vol. 27, pp. 891-903. doi:10.1016/j.jpolmod.2005.06.003.

Zapata, H, O., and Rambaldi, A. N. (1997). ‘Monte Carlo evidence on cointegration and causation’. Oxford Bulletin of Economics and Statistics, Vol. 59, pp. 285-298.