Testing for the Effectiveness of Inflation Targeting in India: A Factor Augmented Vector Autoregression (FAVAR) Approach

Jithin, P; Suresh, Babu M

doi:10.2478/jcbtp-2020-0042

Abstract

Employing Factor Augmented Vector Autoregression (FAVAR) model where factors are obtained using the principal component analysis (PCA) and the parameters of the model are estimated using Vector Autoregression framework, we analyse how changes in monetary policy variables impact inflation, output, money supply, and the financial sector in India. Our results for the period 2001:04 to 2016:03 show that the benchmark FAVAR model showed more reliable results than baseline VAR model. Benchmark FAVAR model shows the existence of weak ‘liquidity puzzle’ in India. The impulse responses from the FAVAR approach reveal that monetary policy is more efficient in explaining the variations in inflation rather than stimulating output indicating its effectiveness in attaining the objective of price stability.

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Testing for the Effectiveness of Inflation Targeting in India: A Factor Augmented Vector Autoregression (FAVAR) Approach

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