Fiscal Policy, Inflation Volatility, and Macroeconomic Instability in Nigeria: A GARCH-Family Modelling Approach with Asymmetric Effects and Structural Break Analysis

This paper investigates the dynamic relationship between fiscal policy instruments and inflation volatility in Nigeria over the period 1990Q1–2024Q2, deploying a sophisticated econometric framework that integrates Generalised Autoregressive Conditional Heteroskedasticity (GARCH) modelling — including GARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1) specifications — with Autoregressive Distributed Lag (ARDL) bounds testing and structural break analysis. The core innovation of this study lies in explicitly modelling inflation uncertainty as a time-varying, heteroskedastic process driven by fiscal policy shocks, rather than treating volatility as a nuisance parameter. Using quarterly data on government expenditure (GEXP), total government revenue (GR), fiscal deficit (FD), and the consumer price index (CPI), we find that: (i) inflation in Nigeria exhibits significant ARCH effects and conditional volatility clustering, confirming the validity of GARCH-family models; (ii) government expenditure shocks significantly increase both the level and conditional variance of inflation, with asymmetric leverage effects confirmed by the EGARCH specification — negative fiscal shocks (expenditure contractions) generate disproportionately larger volatility responses than positive shocks of equal magnitude; (iii) fiscal deficit persistently feeds inflation uncertainty, with the GJR-GARCH estimates revealing that deficit shocks above a threshold trigger regime shifts in inflation volatility; (iv) three significant structural breaks are identified — 1999 (democratic transition), 2009 (post-financial crisis fiscal stimulus), and 2020 (COVID-19 emergency spending) — each associated with discrete upward jumps in the GARCH volatility process; and (v) ARDL bounds testing confirms a long-run cointegrating relationship between fiscal variables and inflation, with government expenditure contributing a long-run coefficient of 0.347 and fiscal deficit contributing 0.218 to CPI growth. The findings carry profound implications for fiscal-monetary policy coordination, inflation targeting frameworks, and the design of fiscal rules in oil-dependent economies.

GARCH; EGARCH; GJR-GARCH; Inflation Volatility

1. Adefeso, H. A., & Mobolaji, H. I. (2010). The fiscal-monetary policy and economic growth in Nigeria: Further empirical evidence. Pakistan Journal of Social Sciences, 7(2), 137–142. [Google Scholar] [Crossref]

2. Adediran, I., & Aladejana, S. (2020). Fiscal policy and inflation in Nigeria: Disaggregated expenditure analysis. Journal of African Business, 21(3), 345–361. [Google Scholar] [Crossref]

3. Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1–22. [Google Scholar] [Crossref]

4. Baillie, R. T., Chung, C.-F., & Tieslau, M. A. (1996). Analysing inflation by the fractionally integrated ARFIMA–GARCH model. Journal of Applied Econometrics, 11(1), 23–40. [Google Scholar] [Crossref]

5. Barro, R. J. (1979). On the determination of public debt. Journal of Political Economy, 87(5), 940–971. [Google Scholar] [Crossref]

6. Blanchard, O. (2017). Macroeconomics (7th ed.). Pearson Education. [Google Scholar] [Crossref]

7. Bollerslev, T. (1986). Generalised autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. [Google Scholar] [Crossref]

8. Central Bank of Nigeria (CBN). (2022). Statistical Bulletin (Vol. 33). CBN Publications. [Google Scholar] [Crossref]

9. Chenery, H. B. (1975). The structuralist approach to development policy. American Economic Review, 65(2), 310–316. [Google Scholar] [Crossref]

10. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. [Google Scholar] [Crossref]

11. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. [Google Scholar] [Crossref]

12. Ezeabasili, V. N. (2012). Fiscal deficits and inflation in Nigeria: An analysis of causal relationships. International Journal of Business and Social Science, 3(19), 220–227. [Google Scholar] [Crossref]

13. Fountas, S. (2001). The relationship between inflation and inflation uncertainty in the UK: 1885–1998. Economics Letters, 74(1), 77–83. [Google Scholar] [Crossref]

14. Friedman, M. (1968). The role of monetary policy. American Economic Review, 58(1), 1–17. [Google Scholar] [Crossref]

15. Friedman, M. (1977). Nobel lecture: Inflation and unemployment. Journal of Political Economy, 85(3), 451–472. [Google Scholar] [Crossref]

16. Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48(5), 1779–1801. [Google Scholar] [Crossref]

17. Grier, K. B., & Perry, M. J. (1998). On inflation and inflation uncertainty in the G7 countries. Journal of International Money and Finance, 17(4), 671–689. [Google Scholar] [Crossref]

18. Keynes, J. M. (1936). The general theory of employment, interest, and money. Palgrave Macmillan. [Google Scholar] [Crossref]

19. Lamoureux, C. G., & Lastrapes, W. D. (1990). Persistence in variance, structural change, and the GARCH model. Journal of Business and Economic Statistics, 8(2), 225–234. [Google Scholar] [Crossref]

20. Lipsey, R. G., & Chrystal, K. A. (2015). Economics (13th ed.). Oxford University Press. [Google Scholar] [Crossref]

21. Musgrave, R. A., & Musgrave, P. B. (1989). Public finance in theory and practice (5th ed.). McGraw-Hill. [Google Scholar] [Crossref]

22. National Bureau of Statistics (NBS). (2024). Consumer Price Index Report — March 2024. Abuja: NBS. [Google Scholar] [Crossref]

23. Ndou, E., & Mokoena, T. (2019). Fiscal consolidation, inflation and fiscal volatility: A South African GARCH analysis. South African Journal of Economics, 87(2), 194–214. [Google Scholar] [Crossref]

24. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. [Google Scholar] [Crossref]

25. Ogunmuyiwa, M. S., & Ekone, F. (2010). Money supply and economic growth nexus in Nigeria. Journal of Social Science, 22(3), 199–204. [Google Scholar] [Crossref]

26. Omitogun, O., & Ayinla, T. A. (2007). Fiscal policy and Nigerian economic growth. Journal of Research in National Development, 5(2), 1–12. [Google Scholar] [Crossref]

27. Onwioduokit, E. A. (2012). Fiscal policy and macroeconomic management in Nigeria. CBN Economic and Financial Review, 50(1), 45–68. [Google Scholar] [Crossref]

28. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. [Google Scholar] [Crossref]

29. Sims, C. A. (1994). A simple model for study of the determination of the price level and the interaction of monetary and fiscal policy. Economic Theory, 4(3), 381–399. [Google Scholar] [Crossref]

30. Woodford, M. (2001). Fiscal requirements for price stability. Journal of Money, Credit and Banking, 33(3), 669–728. [Google Scholar] [Crossref]

31. World Bank. (2022). World Development Indicators. Washington, DC: World Bank. [Google Scholar] [Crossref]

• Impact of Foreign Direct Investment in India
• Issues Involved in Digitalisation Special Reference to Indian Tourism Growth
• Relationship Marketing and Customer Loyalty in the Fast-Moving Consumer Goods (FMCG) Industry in Nairobi County
• Financial Literacy or Financial Inclusion? Which is Which, What is What—To Achieve Uganda’s 10-Fold Economic Growth By 2040
• Harnessing Natural Gas for Economic Transformation: Overcoming the Regulatory and Infrastructural Bottlenecks in Nigeria