Dr. AHAMUEFULA OGBONNA E.

Email

ae.ogbonna@cear.org.ng; ogbonnaephraim@yahoo.com

Personal Research Links

       Google Scholar;
       ResearchGate;
       RePEc;
       ORCID;
       WOS

Dr. Ahamuefula Ephraim Ogbonna holds a Professional Diploma, a Bachelor’s Degree and a Master’s Degree in Statistics, from the University of Ibadan, and has in the process, garnered the pre-requisite knowledge in the rudiments of Statistics, both theoretical and empirical. He is a Research Fellow at the Centre for Econometrics and Applied Research (CEAR), Ibadan, Nigeria; with over seven (7) years research experience, working with renowned Statisticians and Economists. Under the CEAR platform, which he joined in 2015, he has participated in the macroeconomic modelling of the Nigerian economy that provides evidence-based policy options to the Monetary Policy Committee (MPC) of the Central Bank of Nigeria (CBN), to aid their policy decisions; and also co-facilitated trainings of post-graduate students, academics and professionals in the use of Econometric tools and statistical soft-wares for empirical research analyses. He has also been actively involved in the Project LINK Meeting for the period between 2015 and 2018; reporting Nigeria’s economic outlook annually, having empirically examined and forecasted key macroeconomic fundamentals for the years under review. As a young researcher, his research focuses on empirical application of recent Econometric methodologies. He has interest in programming with diverse software programs, to solve analytical and numeric problems, with demonstrated proficiency in the usage of statistical programming soft-wares. He has several publications in ISI and Scopus indexed journals. As at October 2023, he is ranked in the top 3% (Nigeria) and 8% (Africa), according to RePEC/IDEAS ranking of economists based on his economic related publications.

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Some Selected Journal Articles
  1. Salisu, A.A., Ogbonna, A.E., Gupta, R., Bouri, E. (2025). Forecasting Spot and Futures Price Volatility of Agricultural Commodities: The Role of Climate-Related Migration Uncertainty. Research in International Business and Finance, https://doi.org/10.1016/j.ribaf.2025.103133.
  2. Salisu, A.A., Ogbonna, A.E., & Vo, X.V. (2025). Climate risks and the REITs market. International Journal of Finance & Economics, 30(2), 1632-1648. https://doi.org/10.1002/ijfe.2983
  3. Farag, M., Musa, D.C., Olayinka, H.A., Ogbonna, A.E., Yaya, O.S. and Olubusoye, O.E. (2025). Market Fear Forecastibility: The Role of Policy Uncertainty and Geopolitical Risks. Applied Economics, 1 – 16. https://doi.org/10.1080/00036846.2025.2504192
  4. Salisu, A.A., Ogbonna, A.E., Gupta, R. and Shiba, S. (2025). Energy market uncertainties and gold return volatility: A GARCH-MIDAS approach. Australian Economic Papers, https://doi.org/10.1111/1467-8454.12396
  5. Salisu, A.A., Isah, K.O. and Ogbonna, A.E. (2025). Sectoral Corporate Profits and Long‐Run Stock Return Volatility in the United States: A GARCH‐MIDAS Approach. Journal of Forecasting, 44(2), 623-634. https://doi.org/10.1002/for.3207
  6. Oloko, T.F., Ogbonna, A.E. and Adediran, I.A. (2024). Digital Currencies and Macroeconomic Performance: A Global Perspective. Bulletin of Monetary Economics and Banking (BMEB) 27 (2), 351 – 394. https://doi.org/10.59091/2460-9196.1954
  7. Ogbonna, A.E., Farag, M., Akintande, O.J., Yaya, O.S. and Olubusoye, O.E. (2024). Re-Validating Phillips Curve Hypothesis in Africa and the Role of Oil Price: A Mixed Frequency Approach. Energy 303, 131862. https://doi.org/10.1016/j.energy.2024.131862
  8. Salisu, A.A., Ogbonna, A.E., Gupta, R. and Bouri, E. (2024). Energy-related uncertainty and international stock market volatility. The Quarterly Review of Economics and Finance, 95, 280-293. https://doi.org/10.1016/j.qref.2024.04.005
  9. Yaya, O.S., Olayinka, H.A., Ogbonna, A.E., Al-Faryan, M.A.S., & Vo, X.V. (2024). Dynamic connectedness of economic policy uncertainty in G7 countries and the influence of the USA and UK on non-G7 countries. Economic Change and Restructuring, 57(2), 76. https://doi.org/10.1007/s10644-024-09658-1
  10. Furuoka, F., Gil-Alana, L.A., Yaya, O.S., Aruchunan, E. and Ogbonna, A.E. (2024). A new fractional integration approach based on neural network nonlinearity with an application to testing unemployment hysteresis. Empirical Economics 66, 2471-2499 https://doi.org/10.1007/s00181-023-02540-5
  11. Salisu, A.A., Ogbonna, A.E. and Oloko, T.F. (2023). Pandemics and cryptocoins. IIMB Management Review, 35 (2), 164-175. https://doi.org/10.1016/j.iimb.2023.06.002
  12. Ogbonna, A.E., Adediran, I.A., Oloko, T.F. and Isah, K.O. (2023). Information and Communication Technology (ICT) and youth unemployment in Africa. Quality & Quantity 57 (6), 5055-5077 https://doi.org/10.1007/s11135-022-01600-9
  13. Ayinde, T.O., Olaniran, A.O., Abolade, O.C. and Ogbonna, A.E. (2023). Technology shocks-gold market connection: Is the effect episodic to business cycle behaviour? Resources Policy 84, 103771 https://doi.org/10.1016/j.resourpol.2023.103771
  14. Salisu, A.A., Ogbonna, A.E. and Vo, X.V. (2023). Oil tail risks and the realized variance of consumer prices in advanced economies. Resources Policy 83, 103755 https://doi.org/10.1016/j.resourpol.2023.103755
  15. Adediran, I.A., Isah, K.O., Ogbonna, A.E. and Badmus, S.K. (2023). A global analysis of the macroeconomic effects of climate change. Asian Economics Letters 4(1) https://doi.org/10.46557/001c.39732
  16. Salisu, A.A., Gupta, R. and Ogbonna, A.E. (2023). Tail risks and forecastibility of stock returns of advanced economies: evidence from centuries of data. The European Journal of Finance, 29(4), 466–481. https://doi.org/10.1080/1351847X.2022.2097883
  17. Yaya, O.S., Ogbonna, A.E., Adesina, O.A. Alobaloke, K.A. and Vo, X.V. (2022). Time-variation between metal commodities and oil, and the impact of oil shocks: GARCH-MIDAS and DCC-MIDAS analyses. Resources Policy 79, 103036 https://doi.org/10.1016/j.resourpol.2022.103036
  18. Salisu, A.A., Ogbonna, A.E., Lasisi, L. and Olaniran, A. (2022). Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach. The North American Journal of Economics and Finance, Vol. 62, 101755, ISSN 1062-9408, https://doi.org/10.1016/j.najef.2022.101755
  19. Salisu, A.A., Gupta, R., Ogbonna, A.E. and Wohar, M.E. (2022). Uncertainty and Predictability of Real Housing Returns in the United Kingdom: A Regional Analysis. Journal of Forecasting, 41(7), 1525–1556. https://doi.org/10.1002/for.2878
  20. Ogbonna, A.E. and Olubusoye, O.E. (2022). Connectedness of green investments and uncertainties: new evidence from emerging markets. Fulbright Review of Economics and Policy 2 (2), 136-160. https://doi.org/10.1108/FREP-04-2022-0028
  21. Yaya, O.S., Ogbonna, A.E. and Vo, X.V. (2022). Oil shocks and volatility of green investments: GARCH-MIDAS analyses. Resources Policy, Volume 78, 102789. https://doi.org/10.1016/j.resourpol.2022.102789
  22. Salisu, A.A., Gupta, R. and Ogbonna, A.E. (2022). A Moving Average Heterogeneous Autoregressive Model for Forecasting the Realized Volatility of the US Stock Market: Evidence from Over a Century of Data. International Journal of Finance and Economics, 27(1), 384 – 400. https://doi.org/10.1002/ijfe.2158
  23. Yaya, O.S., Ajose, T.S and Ogbonna, A.E. (2021). Modelling the Popularity of Some Selected Nigerian Music Top Stars with Long-Range Dependence. Journal of Science Research, Vol. 20
  24. Oloko, T.F., Ogbonna, A.E., Adedeji, A.A. and Lakhani, N. (2021). Fractional cointegration between gold price and inflation rate: Implication for inflation rate persistence. Resources Policy, 74, 102369. https://doi.org/10.1016/j.resourpol.2021.102369
  25. Salisu, A.A. and Ogbonna, A.E. (2021). The return volatility of crypto currencies during the COVID-19 pandemic: Assessing the news effect. Global Finance Journal, 100641. https://doi.org/10.1016/j.gfj.2021.100641
  26. Awolaja, O.G., Yaya, O.S., Ogbonna, A.E., S.O. Joseph and Vo, X.V. (2021). Unemployment hysteresis in Middle East and North Africa countries: panel SUR-based unit root test with a Fourier function. Middle East Development Journal, 1-17. https://doi.org/10.1080/17938120.2021.1958587
  27. Salisu, A.A., Gupta, R. and Ogbonna, A.E. (2021). Point and density forecasting of macroeconomic and financial uncertainties of the USA. Journal of Forecasting, 40: 700–707. https://doi.org/10.1002/for.2740
  28. Ogbonna, A.E. and Olubusoye, O.E. (2021). Tail Risks and Stock Return Predictability: Evidence From Asia-Pacific. Asian Economics Letters, 2(3), 24417. https://doi.org/10.46557/001c.24417
  29. Olubusoye, O.E., Akintande, O.J., Yaya, O.S., Ogbonna, A.E., and Adenikinju, A.F. (2021). Energy pricing during the COVID-19 pandemic: Predictive information-based uncertainty indexes with machine learning algorithm. Intelligent Systems with Applications, 12, 200050. https://doi.org/10.1016/j.iswa.2021.200050
  30. Oloko, T.F., Ogbonna, A.E., A.A. Adedeji and N. Lakhani (2021). Oil price shocks and inflation rate persistence: A Fractional Cointegration VAR approach. Economic Analysis and Policy, 70, 259-275. https://doi.org/10.1016/j.eap.2021.02.014
  31. Salisu, A.A., Ogbonna, A.E., Oloko, T.F. and Adediran, I.A. (2021). A New Index for Measuring Uncertainty due to the COVID-19 Pandemic. Sustainability, 13(6), 3212. https://doi.org/10.3390/su13063212
  32. Olubusoye, O.E., Ogbonna, A.E., Yaya, O.S. and Umolo, D. (2021). An Information-Based Index of Uncertainty and the predictability of Energy Prices. International Journal of Energy Research, https://doi:10.1002/er.6512
  33. Yaya, O.S., Ogbonna, A.E., Furuoka, F. and Gil-Alana, L.A. (2021). A new unit root analysis for testing hysteresis in unemployment. Oxford Bulletin of Economics and Statistics, https://doi:10.1111/obes.12422
  34. Yaya, O.S., Otekunrin, O.A. and Ogbonna, A.E. (2021). Life Expectancy in West African countries, Evidence of Convergence and Catching up with the North. Statistics in Transition, 22(1), 75-89. https://doi.org/10.21307/stattrans-2021-004
  35. Yaya, O.S., Ogbonna, A.E., Mudida, R. and Abu, N. (2021). Market Efficiency and Volatility Persistence of Cryptocurrency during Pre- and Post-Crash Periods of Bitcoin: Evidence based on Fractional Integration. International Journal of Finance and Economics, 26, 1318–1335, https://doi.org/10.1002/ijfe.1851
  36. Salisu, A.A., Ogbonna, A.E. and Adediran, I. (2021). Stock-Induced Google Trends and the predictability of Sectoral Stock Returns. Journal of Forecasting, 40: 327-345, https://doi.org/10.1002/for.2722
  37. Yaya, O.S., Vo, X.V., Ogbonna, A.E. and Adewuyi, A. (2020). Modelling Cryptocurrency High-Low Prices using Fractional Cointegrating VAR. International Journal of Finance and Economics, https://doi.org/10.1002/ijfe.2164
  38. L.A. Gil-Alana, R. Mudida, Yaya, O.S., Osuolale, K.A. and Ogbonna, A.E. (2020). Mapping US Presidential terms with S&P500 Index: Time Series Analysis Approach. International Journal of Finance and Economics, 26(2) 1938 – 1954 https://doi.org/10.1002/ijfe.1887
  39. Olofin, S., Oloko, T.F., Isah, K.O. and Ogbonna, A.E. (2020). Crude oil price–shale oil production nexus: a predictability analysis. International Journal of Energy Sector Management, https://doi.org/10.1108/IJESM-05-2019-0004
  40. Salisu, A.A., Ogbonna, A.E. and Adewuyi, A. (2020). Google trends and the predictability of precious metals. Resources Policy 65, https://doi.org/10.1016/j.resourpol.2019.101542
  41. Yaya, O.S., Ogbonna, A.E. and Mudida, R. (2019). Hysteresis of Unemployment rate in Africa: New Findings from Fourier ADF test. Quality and Quantity, 53(4), https://doi:10.1007/s11135-019-00894-6
  42. Yaya, O.S., Ogbonna, A.E. and Atoi, N.V. (2019). Are inflation rates in OECD countries actually stationary during 2011-2018? Evidence based on Fourier Nonlinear Unit root tests with Break. Empirical Economics Review, 9(4), 309 – 325. https://mpra.ub.uni-muenchen.de/93937/1/MPRA_paper_93937.pdf
  43. Yaya, O.S., Ogbonna, A.E. and Olubusoye, O.E. (2019). How Persistent and Dynamic Inter-Dependent are pricing Bitcoin to other Cryptocurrencies Before and After 2017/18 Crash? Physica A, Statistical Mechanics and Applications. https://doi.org/10.1016/j.physa.2019.121732
  44. Yaya, O.S., Akintande, O.J., Ogbonna, A.E. and Hammed, M.A. (2019). CPI inflation in Africa: Fractional persistence, Mean reversion and Nonlinearity. Statistics in Transition new series, 20(3), 119 – 132, https://doi.org/10.21307/stattrans-2019-027
  45. Salisu, A.A. and Ogbonna, A.E. (2019). Another look at the energy-growth nexus: New insights from MIDAS regressions. Energy, https://doi:10.1016/j.energy. 2019.02.138
  46. Yaya, O.S., Luqman, S., Akinlana, D.M., Tumala, M.M., Ogbonna, A.E. (2017): Oil Price-US Dollars Exchange Returns and Volatility Spillovers in OPEC Member Countries: Post Global Crisis Period’s Analysis. African Journal of Applied Statistics, 4(1): 191-208. https://doi:10.16929/ajas/2017.165.208
  47. Yaya, O.S., Akinlana, D.M. and Ogbonna, A.E. (2017). Investigating Structural break-GARCH-based Unit root test in US exchange rates. Journal of Science Research, 16, 80 – 95. https://journals.ui.edu.ng/index.php/jsr/article/view/610/550