Economic impact of Government spending on GDP Growth rate: a case study of Pakistan’s economy

Abstract

The present study aimed at assessing Total Expenditure (TE_t), Current Expenditure (CE_t), and Development Expenditure (DE_t) over GDP (LGDP_t) Growth Rate of Pakistan for time period 1994-95 to 2020-21, wherein Results of Augmented Dickey Fuller Test towards GDP  revealed stationary at level I(0) order of integration and respective variables (TE_t, CE_t, DE_t) were stationary at 1^st difference I(1). Findings of Autoregressive Distributed revealed that lag values of Total Expenditure (TE_t), Current Expenditure (CE_t), and Development Expenditure (DE_t) impacted significant influence on GDP Growth Rate of Pakistan. Results of Bound Test indicated long run relationships among variables. A negative and statistically significant value of error correction term (-0.892305) indicated that the variables will adjust positively towards their long-run equilibrium. Since Centered VIF values of all re-tested variables (TE_t, CE_t, DE_t) were found less than 10 revealed no severe presence of multicollinearity in the model. Heteroskedasticity test revealed presence of homoskedasticity (no heteroskedasticity) in the model. F-Statistics value of LM Test indicated no serial correlation/ no autocorrelation in the model. F-Statistics value in case of Normality test revealed that sample data drawn from normally distributed population. Granger Causality Test revealed uni-directional causal relationship between Development Expenditure and GDP (P<0.10), bi-directional between Total Expenditure and Current Expenditure (P<0.10) indicating long-term relationship in the co-integration test, while no causality exists among rest of other combinations in the model. Since negative as well as positive responses existed, so shock to GDP noticed symmetric impact of Total Expenditure, Current Expenditure and Development Expenditure in Pakistan in short as well as in long run. Wald test confirmed the set of independent variables (TE_t, CE_t, DE_t) were significant for a model