IDEAS home Printed from https://ideas.repec.org/a/bla/sajeco/v90y2022i3p329-348.html
   My bibliography  Save this article

Revisiting the accuracy of inflation forecasts in Nigeria: The oil price–exchange rate–asymmetry perspectives

Author

Listed:
  • Kazeem O. Isah
  • Abdulkader C. Mahomedy
  • Elias A. Udeaja
  • Ojo J. Adelakun
  • Yusuf Yakubu
  • Danmecca Musa

Abstract

Motivated by the distinctive paradoxical nature of the Nigerian economy as the only OPEC oil‐exporting economy that yet depends heavily on the importation of gasoline, we are compelled to re‐examine the accuracy of the oil‐based augmented Philips curve model in the predictability of inflation. Using quarterly data from 1970 to 2020, we investigate whether extending the oil price‐based augmented Phillips curve to include exchange rate improves the accuracy of inflation forecast in Nigeria. We rely on the outcomes of our preliminary analysis to account for the presence of endogeneity, persistence and conditional heteroscedasticity in the predictability of inflation following the Westerlund and Narayan (2015) procedure. We find the extended variant of the oil price‐based Phillips curve model that includes the exchange rate pass‐through as most accurate for improving inflation forecasts in Nigeria. Given the robustness of our results from several models, we conclude that the exchange rate channel through which shocks to the oil price transmit into the economy is essential for enhancing the accuracy of inflation forecasts.

Suggested Citation

  • Kazeem O. Isah & Abdulkader C. Mahomedy & Elias A. Udeaja & Ojo J. Adelakun & Yusuf Yakubu & Danmecca Musa, 2022. "Revisiting the accuracy of inflation forecasts in Nigeria: The oil price–exchange rate–asymmetry perspectives," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 329-348, September.
  • Handle: RePEc:bla:sajeco:v:90:y:2022:i:3:p:329-348
    DOI: 10.1111/saje.12313
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/saje.12313
    Download Restriction: no

    File URL: https://libkey.io/10.1111/saje.12313?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ciner, Cetin, 2011. "Commodity prices and inflation: Testing in the frequency domain," Research in International Business and Finance, Elsevier, vol. 25(3), pages 229-237, September.
    2. van Amano, Robert A & Norden, Simon, 1998. "Exchange Rates and Oil Prices," Review of International Economics, Wiley Blackwell, vol. 6(4), pages 683-694, November.
    3. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    4. Reboredo, Juan C., 2012. "Modelling oil price and exchange rate co-movements," Journal of Policy Modeling, Elsevier, vol. 34(3), pages 419-440.
    5. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    6. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2015. "The nexus between oil price and Russia's real exchange rate: Better paths via unconditional vs conditional analysis," Energy Economics, Elsevier, vol. 51(C), pages 54-66.
    7. Moses Tule & Afees Salisu & Charles Chiemeke, 2020. "Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 191-229, March.
    8. Browne, Frank & Cronin, David, 2010. "Commodity prices, money and inflation," Journal of Economics and Business, Elsevier, vol. 62(4), pages 331-345, July.
    9. Park, Jungwook & Ratti, Ronald A., 2008. "Oil price shocks and stock markets in the U.S. and 13 European countries," Energy Economics, Elsevier, vol. 30(5), pages 2587-2608, September.
    10. Atems, Bebonchu & Kapper, Devin & Lam, Eddery, 2015. "Do exchange rates respond asymmetrically to shocks in the crude oil market?," Energy Economics, Elsevier, vol. 49(C), pages 227-238.
    11. Ahmad, A.H. & Moran Hernandez, Ricardo, 2013. "Asymmetric adjustment between oil prices and exchange rates: Empirical evidence from major oil producers and consumers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 306-317.
    12. Agnès Bénassy‐Quéré & Maylis Coupet & Thierry Mayer, 2007. "Institutional Determinants of Foreign Direct Investment," The World Economy, Wiley Blackwell, vol. 30(5), pages 764-782, May.
    13. Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(1), pages 1-30, February.
    14. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    15. Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
    16. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    17. Chen, Yu-chin & Turnovsky, Stephen J. & Zivot, Eric, 2014. "Forecasting inflation using commodity price aggregates," Journal of Econometrics, Elsevier, vol. 183(1), pages 117-134.
    18. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    19. Maurizio Michael Habib & Sascha Bützer & Livio Stracca, 2016. "Global Exchange Rate Configurations: Do Oil Shocks Matter?," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(3), pages 443-470, August.
    20. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    21. Stephen G. Cecchetti & Rita S. Chu & Charles Steindel, 2000. "The unreliability of inflation indicators," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 6(Apr).
    22. Le, Thai-Ha & Chang, Youngho, 2011. "Dynamic relationships between the price of oil, gold and financial variables in Japan: a bounds testing approach," MPRA Paper 33030, University Library of Munich, Germany.
    23. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    24. Turhan, M. Ibrahim & Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "A comparative analysis of the dynamic relationship between oil prices and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 397-414.
    25. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    26. Golub, Stephen S, 1983. "Oil Prices and Exchange Rates," Economic Journal, Royal Economic Society, vol. 93(371), pages 576-593, September.
    27. A. Nazif Çatik & A. Özlem Önder, 2011. "Inflationary Effects of Oil Prices in Turkey: A Regime-Switching Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(5), pages 125-140, September.
    28. Narayan, Paresh Kumar & Gupta, Rangan, 2015. "Has oil price predicted stock returns for over a century?," Energy Economics, Elsevier, vol. 48(C), pages 18-23.
    29. Kapur, Muneesh, 2013. "Revisiting the Phillips curve for India and inflation forecasting," Journal of Asian Economics, Elsevier, vol. 25(C), pages 17-27.
    30. Frankel, Jeffrey A., 2014. "Effects of speculation and interest rates in a “carry trade” model of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 88-112.
    31. Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "The hidden predictive power of cryptocurrencies and QE: Evidence from US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    32. Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
    33. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    34. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    35. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    36. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    37. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    38. Aloui, Riadh & Ben Aïssa, Mohamed Safouane & Nguyen, Duc Khuong, 2013. "Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 719-738.
    39. Paul Krugman, 1983. "Oil Shocks and Exchange Rate Dynamics," NBER Chapters, in: Exchange Rates and International Macroeconomics, pages 259-284, National Bureau of Economic Research, Inc.
    40. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    41. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    42. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    43. Jiang, Jiaqi & Gu, Rongbao, 2016. "Asymmetrical long-run dependence between oil price and US dollar exchange rate—Based on structural oil shocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 75-89.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Moses Tule & Afees Salisu & Charles Chiemeke, 2020. "Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 191-229, March.
    2. Afees A. Salisu & Raymond Swaray & Hadiza Sa'id, 2021. "Improving forecasting accuracy of the Phillips curve in OECD countries: The role of commodity prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2946-2975, April.
    3. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    4. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    5. Moses Tule & Afees A. Salisu & Charles Chimeke, 2018. "You are what you eat: The role of oil price in Nigeria inflation forecast," Working Papers 040, Centre for Econometric and Allied Research, University of Ibadan.
    6. Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
    7. Afees A. Salisu & Juncal Cunado & Kazeem Isah & Rangan Gupta, 2020. "Oil Price and Exchange Rate Behaviour of the BRICS for Over a Century," Working Papers 202064, University of Pretoria, Department of Economics.
    8. Afees A. Salisu & Kazeem O. Isah & Idris Ademuyiwa, 2017. "Testing for asymmetries in the predictive model for oil price-inflation nexus," Economics Bulletin, AccessEcon, vol. 37(3), pages 1797-1804.
    9. Afees A. Salisu & Raymond Swaray & Idris Adediran, 2018. "Improving the predictability of commodity prices in US inflation: The role of coffee price," Working Papers 041, Centre for Econometric and Allied Research, University of Ibadan.
    10. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
    11. Xu, Yang & Han, Liyan & Wan, Li & Yin, Libo, 2019. "Dynamic link between oil prices and exchange rates: A non-linear approach," Energy Economics, Elsevier, vol. 84(C).
    12. Fasanya, Ismail O. & Awodimila, Crystal P., 2020. "Are commodity prices good predictors of inflation? The African perspective," Resources Policy, Elsevier, vol. 69(C).
    13. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
    14. Salisu, Afees A. & Swaray, Raymond & Oloko, Tirimisiyu F., 2019. "Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables," Economic Modelling, Elsevier, vol. 76(C), pages 153-171.
    15. Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "The hidden predictive power of cryptocurrencies and QE: Evidence from US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    16. Changyu Liu & Muhammad Abubakr Naeem & Mobeen Ur Rehman & Saqib Farid & Syed Jawad Hussain Shahzad, 2020. "Oil as Hedge, Safe-Haven, and Diversifier for Conventional Currencies," Energies, MDPI, vol. 13(17), pages 1-19, August.
    17. Beckmann, Joscha & Czudaj, Robert L. & Arora, Vipin, 2020. "The relationship between oil prices and exchange rates: Revisiting theory and evidence," Energy Economics, Elsevier, vol. 88(C).
    18. Bing‐Yue Liu & Qiang Ji & Duc Khuong Nguyen & Ying Fan, 2021. "Dynamic dependence and extreme risk comovement: The case of oil prices and exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2612-2636, April.
    19. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2019. "Structural instability and predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    20. Salisu, Afees A. & Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "Testing the predictability of commodity prices in stock returns of G7 countries: Evidence from a new approach," Resources Policy, Elsevier, vol. 64(C).

    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E53 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Deposit Insurance
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:sajeco:v:90:y:2022:i:3:p:329-348. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.