Convergence in Sub-Saharan Africa : a nonstationary panel data approach

Given the development of time series econometrics and nonstationary data analysis, St. Aubyn (Empirical Economics, 24, 23-44, 1999) demonstrates a new paradigm for testing income convergence, or better defined, income stability, namely testing the stationarity of pair-wise income differentials. In this paper, a panel data set of Sub-Saharan African countries is constructed and panel cointegration and unit root tests are used to investigate the convergence properties of incomes and standards of living within Africa. Overall, little evidence is found to substantiate claims of convergence across Africa, although in some cases, smaller convergence clubs within Africa may be found. In addition the use of nonstationary panel data techniques is proposed for the testing and establishing of coherent convergence clubs

The impact of misdiagnosing a structural break on standard unit root tests : Monte Carlo results for small sample size and power

As discussed by Perron (1989), a common problem when testing for unit roots is the presence of a structural break that has not been accounted for in the testing procedure. In such cases, unit root tests are biased to non-rejection of the null hypothesis of non-stationarity. These results have been discussed using asymptotic theory and large samples in papers by Leybourne and Newbold (2000), Montanes and Reyes (1998) and Lee, Huang, and Shin (1997). In this paper we investigate the impact of ignoring structural breaks on sample sizes of more interest to empirical economists and show the results on power and size for both tests of the null of non-stationarity (ADF and Phillips-Perron) and the null of stationarity (KPSS). We are also able to give some guidelines on break placement which can cause the rapid flipping of rejection probabilities as discussed in Leybourne and Newbold (2000). Finally, we provide examples from time series data in South Africa to show the danger of misdiagnosis and the resulting misspecifications that can occur

On the long-run interdependence of stock markets : a tale of correlations, auto- regressions and decompositions

It seems as if national stock markets within certain groups of countries, for example within Europe and Asia, are interdependent. But to what extent are stock markets between these groups interdependent? Is it still possible to diversify among these groups, or have globalization tied world markets together to such an extent that diversification is no longer feasible? In this study we use time series techniques to analyze the interdependence among four of the most important groups of economies, namely Europe, Latin America, Asia and the US. This will show whether it is still possible to diversify between the stock markets of these groups of economies, since stock markets within these groups seem to be interdependent to such an extent that diversification within these groups is no longer possible. On a methodological level, we compare the results of the OLS-VAR with an FM-VAR model, which is a more robust estimation procedure in the presence of non-stationary or cointegrated series

Convergence in Sub-Saharan Africa: a nonstationary panel data approach

Given the development of time series econometrics and nonstationary data analysis, St. Aubyn (Empirical Economics, 24, 23–44, 1999) demonstrates a new paradigm for testing income convergence, or better defined, income stability, namely testing the stationarity of pair-wise income differentials. In this paper, a panel data set of Sub-Saharan African countries is constructed and panel cointegration and unit root tests are used to investigate the convergence properties of incomes and standards of living within Africa. Overall, little evidence is found to substantiate claims of convergence across Africa, although in some cases, smaller convergence clubs within Africa may be found. In addition the use of nonstationary panel data techniques is proposed for the testing and establishing of coherent convergence clubs.