The purpose of this study is to investigate the stability of money demand function in emerging countries using the annual data over the period 1987 – 2018. The panel data was analyzed applying both static and dynamic panel models. With the static panel analysis, the random effect method is found to be an appropriate model to determine the factors that affect money demand in emerging countries. The findings of random effect method reveal real income affect money demand positively while exchange rate and real interest rate influence money demand negatively. For dynamic panel analysis, the Hausman test confirms that Pooled Mean Group (PMG) is an appropriate model for the determination of money demand function in emerging countries. The findings of dynamic panel approach show that real income has positive impact on broad money demand while exchange rate, real interest rate and inflation negatively influence broad money demand in the long-run. The dynamic panel approach confirms that inflation has a significant impact on money demand in addition to the variables found to significantly influence money demand with the random effect method of static panel approach. This implies that dynamic panel model better estimates the determinants of money demand function as compared to static panel model. The stability analysis of each country confirms stable money demand function in China, India, Indonesia, South Africa and Turkey. Whereas, the CUSUM test reflects the structural break in Brazil while the CUSUMSQ test confirms the stability of money demand function. The error correction model reveals any deviation from the equilibrium is corrected each year in the selected emerging countries. Therefore, the monetary policy makers can incorporate the outcome of this study as additional input for the implementation of effective monetary policy in the selected countries of emerging economies.
Keywords: ARDL model, BRICS, Dynamic panel model, Money demand, Pooled Mean Group, Random effect method