The Impact of Financial Innovation on the Money Demand Function: An Empirical Verification in India

Traditional money demand functions are often criticized for persistent over-prediction, implausible parameter estimates, highly serially correlated errors and unstable money demand. This study argues that some of these problems may have emerged for the lack of factoring financial innovation into the money demand function. This study estimates money demand for India during the post-reform period, from 1996:Q2 to 2016:Q3. The money demand function is estimated with the linear ARDL approach to cointegration developed by Pesaran, Shin, & Smith (2001), Bounds testing approaches to the analysis of level relationships, Journal of Applied Econometrics, 16(3), 289–326, after employing various proxies for financial innovation. In conclusion, the study finds that there is a stable long-run relationship among variables, such as real money balances, and the scale and opportunity cost variables. In a nutshell, the study assesses the relative importance of financial innovation variables in the money demand equation, and finds that financial innovation plays a very significant role in the money demand specification and its stability. JEL Classification: E41, E44, E42, E52, O16, O53