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Article type: Research Article
Authors: Viththika, Selvavinayagama | Arulrajah, Jeyapiratheeba Antona | Gnanachandran, Gnanasubramaniamb; *
Affiliations: [a] Department of Economics and Statistics, Faculty of Arts and Culture, Eastern University of Sri Lanka, Vantharumoolai, Sri Lanka | [b] Department of Economics, Bharathidasan University, Tamil Nadu, India
Correspondence: [*] Corresponding author: Gnanasubramaniam Gnanachandran, Department of Economics, Bharathidasan University, Tamil Nadu, India. E-mail: Gnanachandrang@esn.ac.lk.
Abstract: This research explores the impact of budget deficits on inflation in Sri Lanka from 1990 to 2022, examining both long-term and short-term effects. The study uses statistical methods like unit root tests and econometric models, including the Autoregressive Distributed Lag (ARDL) model and the Error Correction Model (ECM), to assess the reliability and stability of these relationships. Inflation is the dependent variable, with budget deficits as the primary independent variable, and money supply, interest rates, and unemployment rates as secondary variables. Findings indicate an inverse relationship between budget deficits and long-term inflation, while money supply and unemployment rates positively affect inflation. In the short term, previous year’s money supply, budget deficit, and unemployment rates are negatively correlated with inflation. However, the previous year’s budget deficit and the current year’s unemployment rate significantly increase short-run inflation. Interest rates do not significantly impact inflation in either the short or long term. This study, through historical data analysis and econometric techniques, aims to clarify these impacts, enhancing understanding of Sri Lanka’s macroeconomic dynamics and aiding policymakers in sustainable economic management.
Keywords: Inflation, interest rate, budget deficit, money supply, unemployment, Autoregressive Distributed Lag (ARDL) model, error correction model (ECM)
DOI: 10.3233/MAS-241931
Journal: Model Assisted Statistics and Applications, vol. 19, no. 3, pp. 239-250, 2024
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