Dynamic Connectedness among Business Cycle, Financial Cycle, and Policy Uncertainty Index in India
Keywords:Business cycle, Financial Cycle, Uncertainty, TVP-VAR, India
Purpose: Pervasive impact of uncertainty necessitates relooking at the traditional empirical approaches to gauge the nexus between the real economy and the financial market, especially after the 2008 financial meltdown. The recent pandemic and ongoing geo-political tension across the globe further emphasized the need for augmentation of the existing analytical framework to address the prime importance and influence of uncertainty on the real economy and financial market. This is why, in this paper, we empirically attempted to calculate the connectedness among the business cycle, financial cycle, and economic policy uncertainty in India. The major contribution of this work can be attributed to the TVP VAR model-based empirical investigation of time-varying connectedness among the aforementioned three variables for the Indian economy from January 1997 to May 2022. Unlike erstwhile works, the paper assesses the net transmitter and receiver of shocks in the multivariate framework too.
Design/methodology/approach: To estimate the dynamic connectedness among business cycle, financial cycle, and economic policy uncertainty, this paper integrates Diebold and Yilmaz's (2014) connectedness technique with Antonakakis and Gabauer's (2017) TVP-VAR methodology.
Findings: We found that the business cycle and financial cycle are the primary receivers of shocks whereas policy uncertainty is the primary transmitter of shocks.
Originality/value: To the best of our knowledge, this is the first empirical attempt to use such a technique in the Indian business cycle literature.
Practical implications: The findings of the paper suggest the need to augment the existing policy framework by incorporating the economic uncertainty component. A stable economic environment is congenial to promote investment and garner consumers’ confidence to boost growth in developing nations like India.
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