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

中文翻译：

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金融创新对货币需求函数的影响：印度的经验验证

传统的货币需求函数经常被批评为持续的过度预测，难以置信的参数估计，高度序列相关的错误和不稳定的货币需求。这项研究认为，其中一些问题可能是由于缺乏将金融创新因素纳入货币需求函数中而出现的。这项研究估计了改革后时期（从1996：Q2到2016：Q3）印度的货币需求。货币需求函数通过Pesaran，Shin和Smith（2001）开发的线性ARDL协整方法进行估计，用于水平关系分析的边界测试方法，Journal of Applied Econometrics，16（3），289–326，之后雇用各种代理人进行金融创新。总之，研究发现变量之间存在稳定的长期关系，例如实际货币余额，以及规模和机会成本变量。简而言之，该研究评估了金融创新变量在货币需求方程中的相对重要性，并发现金融创新在货币需求规格及其稳定性中起着非常重要的作用。JEL分类：E41，E44，E42，E52，O16，O53