Public Expenditure and Economic Growth in India: An Empirical Analysis Using Vector Autoregression (VAR) Model

Objective – The objective of this study is to test direction of causality between components of public expenditure and economic growth in India. Methodology/Technique – The paper uses annual data for the period 1980-2015. To measure public expenditure, plan expenditure and non-plan expenditure are used. The econometric methodology employed is Vector Auto regression (VAR) model. Findings – First, the stationary properties of the data were tested using Augmented Dickey-Fuller (ADF) test, Dickey-Fuller (DF) test, and the Phillip-Perron (PP) test and found that variables were non-stationary in level, but stationary in first differences. Then, Johansen- Jueslius cointegration test was employed to test the long-run association among the variables and results suggest an absence of any long-run association between plan expenditure and non-plan expenditure and economic growth in India. The Granger Causality test suggests there is unidirectional causality running from economic growth and non-plan expenditure and plan expenditure and non-plan expenditure and absence of causality public expenditure and economic growth. Novelty – The results of the Forecast Error Variance Decompositions test indicated that innovations in the variables are mostly explained by their own shocks. The impulse responses of the economic growth, plan expenditure and non-plan expenditure with respect to identified shocks are consistent with the results of Variance Decomposition Analysis. Type of Paper: Empirical. JEL Classification: O4, O49, O53. Keywords: Plan Expenditure; Non-plan Expenditure; Economic Growth; Unit Root; Cointegration Test; Granger Causality Test; Forecast Error Variance Decomposition; Impulse Responses. Reference to this paper should be made as follows: Gupta, R; Shastri, S. 2020. Public Expenditure and Economic Growth in India: An Empirical Analysis Using Vector Autoregression (VAR) Model, J. Bus. Econ. Review 5(2) 45– 58 https://doi.org/10.35609/jber.2020.5.2(1)