FISCAL DISCIPLINE AND ECONOMIC GROWTH: AN EMPIRICAL INVESTIGATION OF OPTIMAL THRESHOLD FOR FISCAL DEFICIT IN NIGERIA
Vitus Onyebuchim Onyemailu
, Godwin Mfon Ekpo PhD , Effiwatt Bassey Iwatt PhD
Auto-Regressive Distributed Lag (ARDL), Economic Growth, Fiscal Discipline, Fiscal Deficit, Threshold Auto-Regressive (TAR) model and Keynesian Theory
This study examines the connection between fiscal discipline and economic growth in Nigeria, focusing on identifying the ideal fiscal deficit threshold between 1981 and 2025. A set of macroeconomic variables including GDP growth, CPI inflation, primary balance, gross fixed capital formation as a ratio of GDP, labour force participation rate, exchange rate and financial deepening were used in the study with various econometric technique deployed for empirical analysis. Augmented Dickey fuller and Phillips-Perron Unit root tests revealed that all variables were stationary at first difference while the Auto-Regressive Distributed Lag (ARDL) bounds test was used to investigate the short-run and long-run relationship between the variables of interest, Threshold Auto-Regressive model was utilized to locate the optimal fiscal deficit threshold that stimulates economic growth in Nigeria. The study found a positive long-term relationship between fiscal deficit and economic growth, and determined that a 2% fiscal deficit threshold optimally promotes growth. Although the short-term impact is negligible, the overall conclusion emphasizes the potential of fiscal deficit to drive economic growth. The study recommended that policymakers should aim to keep deficits within the 2% threshold to support economic expansion.
"FISCAL DISCIPLINE AND ECONOMIC GROWTH: AN EMPIRICAL INVESTIGATION OF OPTIMAL THRESHOLD FOR FISCAL DEFICIT IN NIGERIA", JNRID - JOURNAL OF NOVEL RESEARCH AND INNOVATIVE DEVELOPMENT (www.JNRID.org), ISSN:2984-8687, Vol.3, Issue 10, page no.a147-a174, October-2025, Available :https://tijer.org/JNRID/papers/JNRID2510019.pdf
Volume 3
Issue 10,
October-2025
Pages : a147-a174
Paper Reg. ID: JNRID_701757
Published Paper Id: JNRID2510019
Downloads: 000306
Research Area: Science and Technology
Country: -, -, India
DOI: https://doi.org/10.56975/jnrid.v3i10.701757
ISSN: 2984-8687 | IMPACT FACTOR: 9.57 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: JNRID (IJ Publication) Janvi Wave
