Impact of Institutional Factors on the Long-run Behaviour of Money Velocity in India

Nandini Sud
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Abstract

The objective of the study is to examine the impact of institutional changes in the financial sector on the long-run behaviour of broad money velocity in India. For this purpose, annual time series data from 1970–1971 to 2019–2020 has been used. To avoid the problem of multicollinearity, three institutional factors (urbanisation ratio, ratio of total deposits to currency and DCPS) have been combined to form an institutional factor index using PCA. The unit root results indicate that variables are a mix of I(0) & I(1), therefore, ARDL-ECM methodology is applied. Results indicate that money velocity exhibits a structural break in 2008, conforming to the global economic crises. To examine the impact of institutional factors a benchmark model (BM) containing per capita GDP and rate of interest has been estimated along with an institutional factors model (IFM) which also contains institutional factors index. The results show that there is no co-integration in BM, whereas co-integration was established in IFM. The error-correction term and institutional factors index were highly significant for IFM, confirming the long-run relationship. The explanatory power (adjusted R2) for IFM was considerably higher than BM, indicating that the addition of institutional variables significantly improves the money velocity model for India. JEL Codes: C32, E41, E52
制度因素对印度货币流通速度长期行为的影响
本研究的目的是考察金融部门的制度变化对印度广义货币流通速度的长期行为的影响。为此,使用了1970-1971年至2019-2020年的年度时间序列数据。为避免多重共线性问题,本文利用主成分分析法将三个制度因素(城镇化率、存款与货币的比率和居民存款准备金率)结合起来形成制度因素指数。单位根结果表明变量是I(0)和I(1)的混合,因此采用ARDL-ECM方法。结果表明,2008年货币流通速度出现结构性断裂,与全球经济危机相适应。为了检验制度因素的影响,我们估计了包含人均GDP和利率的基准模型(BM)以及包含制度因素指数的制度因素模型(IFM)。结果表明,BM中不存在协整,而IFM中存在协整。误差修正期和制度因素指数对IFM具有显著性,证实了两者之间的长期关系。IFM的解释能力(调整后的R2)显著高于BM,表明制度变量的加入显著改善了印度的货币速度模型。JEL代码:C32, E41, E52
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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