Indian Fiscal Deficit in Autoregressive Distributed Lag (ARDL) Model
In this paper the author showed the trends of fiscal deficit and examined the short run and the long run nexus between fiscal deficit and gross domestic product per capita, inflation rate (CPI), external debt (% of GDP), unemployment rate (% of labour force), income inequality (income share difference between top 10% and bottom 50%), and military expenditure, respectively, during 1950-51-2023-24 in India by applying Auto Regressive Distributed Lag model. The paper found that the fiscal deficit contains a quadratic trend and denoised wavelet shrinkage. Automatically selected ARDL (3,0,2,3,0,0,3) model, where Akaike Information Criterion (AIC) is minimum, showed that the fiscal deficit is positively associated with inflation and negatively related with debt and per capita GDP significantly in the long run while positively related with inflation and debt and negatively related with military expenditure in the short run significantly. The cointegrating equation states that inflation and debt are directly related and GDP per capita is inversely related to fiscal deficit, and it is converging towards equilibrium at the speed of adjustment of 92% per annum significantly. Unemployment and income inequality have a positive impact on the fiscal deficit in the short and long run insignificantly. The model is stable and contains no serial correlation but contains heteroscedasticity and non-normality. The model demands expenditure-reducing policies in non-plan and defence expenditure, as well as employment and poverty amelioration-oriented fiscal financing at a threshold limit, to achieve sustainable economic growth.
Authors
- Debesh Bhowmik (ORCID: https://orcid.org/0000-0002-0293-1066)
Institutions
- Lincoln University College (MY)
Publication Details
- Journal
- Advancement in Management and Technology.
- Published
- 2025-01-01
- DOI
- https://doi.org/10.46977/amt.2025.v05i04.001
- Primary Topic
- Monetary Policy and Economic Impact
- Type
- article
- Field-Weighted Citation Impact
- 0.00