Capital Flows, Monetary Policy and Economic Growth in the Southern African Customs Union (SACU)

Abstract

This study explored the nexus between capital flows, monetary policy, and economic growth in the Southern African Customs Union over the period 1990–2019. Specifically, it examined the trend and pattern of the respective components of capital flows, gross domestic product per capita, and monetary policy measures, as well as other macroeconomic variables such as the globalization index, real exchange rate, monetary credit to the private sector, and gross capital formation growth rate. It also examined the dynamic interaction between capital flows, monetary policies, and economic growth in the union. Efforts were made to ascertain the threshold level of capital flows and monetary policies in relation to economic growth. Moreover, the direction of causality was analyzed through the examination of the responses of the macroeconomic variables to shocks as well as the design of a macroeconomic framework. The study employed annual secondary data for the empirical analysis. The data on GDP per capita, FPI, FDI, Inward Remittances, Official Aid and Development Assistance, monetary credit to the private sector, broad money growth, and gross capital formation growth rate were sourced from the World Development Indicators (WDI). Moreover, the data sets on the globalization index were obtained from the KOF Globalization Index, the real exchange rate from Bruegel data, and the inflation rate (proxied by the consumer price index) from UNCTADSTAT. The central bank policy rates of South Africa (proxied by repo rates) were obtained from the SARB, while those of Lesotho, Namibia, Eswatini, and Botswana, as well as the United States of America (World Interest Rates), were sourced from the IMF. The panel study utilized descriptive and other econometric techniques. These include graphs, the Pooled Mean Group, the Common Correlated Effects, the Fixed Effect Panel Threshold, Feasible Generalized Least Squares, Panel corrected least squares, the Panel Granger Causality test, and Panel Structural Vector Autoregression of Pedroni (2013).