ECONOMY OF FOREIGN COUNTRIES УДК JEL: C32, E31, E52, Q02 BENKHELOUF Rachid1, SAHED Abdelkader2 1University Centre of Maghnia , Research ID : http://www.researcherid.com/rid/ OIL PRICES SHOCKS AND INFLATION RATE PERSISTENCE FOR ALGERIA: A FRACTIONAL COINTEGRATION RELATIONSHIP This study aims to analyse the relationship between oil prices and inflation rates in Algeria to determine the extent of inflation persistence in face to oil price shocks from January1998 to March 2023 using the recently developed Fractional Cointegration Model, which allows residuals to be fractionally integrated rather than stationary, with the classical cointegration approach based on I(0) stationarity or I(1) cointegrating relationships. This topic was chosen due to its significance for monetary policymakers, investors, financial analysts and academics in understanding the dynamics of inflation persistence in Algeria and studying the impact of some price shocks on it, such as oil price shocks. Our results also showed that Algeria has a co-integration relationship between oil prices and the inflation rate, with an estimated persistence of 0.883, which is greater than 0.5 and less than 1. This indicates that the impact of oil price shocks is still present for a long time on the inflation rate persistence in Algeria, in other words the inflation rate in Algeria will persistence for a longer period due to the shock of oil prices before eventually fading away, and with the adoption of a monetary policy targeting inflation in Algeria, it will contribute to reducing the inflation rates persistence. Keywords:inflation rate persistence; oil prices shocks; fractional cointegration; Algeria.
1. Tule M.K., Salisu A.A., Ebuh G.U. A test for inflation persistence in Nigeria using fractional integration & fractional cointegration techniques. Econ. Model, 2020, Vol. 87, pp. 225-237. doi.org/10.1016/j.econmod.2019.07.024 2. Amano R. Inflation persistence and monetary policy: A simple result. Econ. Lett., 2007, Vol. 94, No. 1, pp. 26-31. doi.org/10.1016/j.econlet.2006.06.022 3. Coenen G. Inflation persistence and robust monetary policy design. J. Econ. Dyn. Control, 2007, Vol. 31, No. 1, pp. 111-140. doi.org/10.1016/j.jedc.2005.09.012 4. Tetlow R. The monetary policy response to uncertain inflation persistence. Econ.Lett., 2019, Vol. 175, pp. 5-8. doi.org/10.1016/j.econlet.2018.10.034 5. Sbordone A.M. Inflation persistence: Alternative interpretations and policy implications. J. Monet. Econ., 2007, Vol. 54, No. 5, pp. 1311-1339. doi.org/10.1016/j.jmoneco.2007.06.007 6. Bratsiotis G.J., Madsen J., Martin C. Inflation Targeting and Inflation Persistence. Econ. Polit. Stud., 2015, Vol. 3, No. 1, pp. 3-17. doi.org/10.1080/20954816.2015.11673835 7. Gerlach S., Tillmann P. Inflation targeting and inflation persistence in Asia-Pacific'. J. Asian Econ., 2012, Vol. 23, No. 4, pp. 360-373. doi.org/10.1016/j.asieco.2012.03.002 8. Meller B., Nautz D. Inflation persistence in the Euro area before and after the European Monetary Union. Econ. Model., 2012, Vol. 29, No. 4, pp. 1170-1176. doi.org/10.1016/j.econmod.2012.03.016 9. Misati R., Nyamongo E., Mwangi I. Commodity price shocks and inflation in a net oil-importing economy. OPEC Energy Rev., 2013, Vol. 37. pp. 125-148. doi.org/10.1111/opec.12010 10. Lacheheb M., Sirag A. Oil price and inflation in Algeria: A nonlinear ARDL approach. Q. Rev. Econ. Finance, 2019, Vol. 73, pp. 217-222. doi.org/10.1016/j.qref.2018.12.003 11. Raheem I.D., Bello A.K., Agboola Y.H. A new insight into oil price-inflation nexus. Resour. Policy, 2020, Vol. 68, No. 101804. doi.org/10.1016/j.resourpol.2020.101804 .12. Salisu A.A., Isah K.O., Oyewole O.J., Akanni L.O. Modelling oil price-inflation nexus: The role of asymmetries. Energy, 2017, Vol. 125, pp. 97-106. doi.org/10.1016/j.energy.2017.02.128 13. Valcarcel V.J., Wohar M.E. Changes in the oil price-inflation pass-through. J. Econ. Bus., 2013, Vol. 68, pp. 24-42. doi.org/10.1016/j.jeconbus.2013.03.001 14. Antonakakis N., Cunado J., Gil-Alana L.A., Gupta R. Is inflation persistence different in reality? Econ. Lett., 2016, Vol. 148, pp. 55-58. doi.org/10.1016/j.econlet.2016.09.003 15. Johansen Sø. A representation theory for a class of vector autoregressive models for fractional processes. Econom. Theory, 2008, Vol. 24, No. 3, pp. 651-676. doi.org/10.1017/S0266466608080274 16. Johansen S., Nielsen M. Ø. Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model. Econometrica, 2012, Vol. 80, No. 6, pp. 2667-2732. doi.org/10.3982/ECTA9299 17. Johansen S. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. 1st ed. Oxford University Press. Oxford, 1995. doi.org/10.1093/0198774508.001.0001 18. Gil-Alana L.A., Yaya O.S., Awe O.O. Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach. Resour. Policy, 2017, Vol. 53, pp. 117-124. doi.org/10.1016/j.resourpol.2017.06.006 19. L. A. Gil-Alana and H. Carcel, 'A fractional cointegration var analysis of exchange rate dynamics'. North Am. J. Econ. Finance, 2020, Vol. 51, P. 100848. doi.org/10.1016/j.najef.2018.09.006 20. Granville B., Zeng N. Time variation in inflation persistence: New evidence from modelling US inflation. Econ. Model., 2019, Vol. 81, pp. 30-39. doi.org/10.1016/j.econmod.2018.12.004 21. Bilici B., Çekin S. E. Inflation persistence in Turkey: A TVP-estimation approach. Q. Rev. Econ. Finance, 2020, Vol. 78, pp. 64-69. doi.org/10.1016/j.qref.2020.04.002 22. Gil-Alana L.A., Gupta R. Persistence and cycles in historical oil price data. Energy Econ., 2014, Vol. 45, pp. 511-516. doi.org/10.1016/j.eneco.2014.08.018 23. Chen J., Zhu X., Li H.The pass-through effects of oil price shocks on China's inflation: A time-varying analysis. Energy Econ., 2020, Vol. 86, No. 104695. doi.org/10.1016/j.eneco.2020.104695 24. Choi S., Furceri D., Loungani P., Mishra S., Poplawski-Ribeiro M. Oil prices and inflation dynamics: Evidence from advanced and developing economies. J. Int. Money Finance, 2018, Vol. 82, pp. 71-96. doi.org/10.1016/j.jimonfin.2017.12.004 25. Lahiani A. Exploring the inflationary effect of oil price in the US: A quantile regression approach over 1876-2014. Int. J. Energy Sect. Manag., 2019, 2019, Vol. 13, No. 1, pp. 60-76. doi.org/10.1108/IJESM-05-2018-0002 26. Batini N., Nelson E. The Lag from Monetary Policy Actions to Inflation: Friedman Revisited. Int. Finance, 2001, Vol. 4, No. 3, pp. 381-400. doi.org/10.1111/1468-2362.00079 27. Roache S.K., Inflation Persistence in Brazil: A Cross Country Comparison. IMF Working Paper, 2014, No. 14/55. URL: ssrn.com/abstract=2431229 doi.org/10.5089/9781475585230.001 28. Fuhrer J., Moore G. Inflation Persistence. Q. J. Econ., 1995, Vol. 110, No. 1, pp. 127-159. doi.org/10.2307/2118513 29. Oil Prices and Inflation Dynamics: Evidence from Advanced and Developing Economies. IMF Working Papers, 2017, Iss. 196. URL: www.elibrary.imf.org/view/journals/001/2017/196/001.2017.issue-196-en.xml (accessed: Jun 06, 2023). 30. Ross M.L. The Political Economy of the Resource Curse. World Polit., 1999, Vol. 51, No. 2, pp. 297-322. URL: www.jstor.org/stable/25054077 doi.org/10.1017/S0043887100008200 31. Bernanke B.S., Gertler M., Watson M., Sims C.A., Friedman B.M. Systematic Monetary Policy and the Effects of Oil Price Shocks. Brook. Pap. Econ. Act., 1997, No. 1, p. 91. doi.org/10.2307/2534702 32. Oloko T.F., Ogbonna A.E., Adedeji A.A., Lakhani N. Fractional cointegration between gold price and inflation rate: Implication for inflation rate persistence. Resour. Policy, 2021, Vol. 74, No. 102369. doi.org/10.1016/j.resourpol.2021.102369 33. Oloko T.F., Ogbonna A.E., Adedeji A.A., Lakhani N. Oil price shocks and inflation rate persistence: A Fractional Cointegration VAR approach. Econ. Anal. Policy, 2021, Vol. 70, pp. 259-275. doi.org/10.1016/j.eap.2021.02.014 34. Geronikolaou G., Spyromitros E., Tsintzos P. Progressive taxation and human capital as determinants of inflation persistence. Econ. Model., 2020, Vol. 88, pp. 82-97. doi.org/10.1016/j.econmod.2019.09.011 35. Wu J.-W., Wu J.-L. Does a flexible exchange rate regime increase inflation persistence? J. Int. Money Finance, 2018, Vol. 86, pp. 244-263. doi.org/10.1016/j.jimonfin.2018.05.002 36. Canarella G., Miller S.M. Inflation persistence and structural breaks. J. Econ. Stud., 2016, Vol. 43, No. 6, pp. 980-1005. doi.org/10.1108/JES-10-2015-0190 37. Kilian L., Park C. The impact of oil price shocks on the US stock market. Int. Econ. Rev., 2009, Vol. 50, No. 4, pp. 1267-1287 doi.org/10.1111/j.1468-2354.2009.00568.x 38. Mishkin F.S., Schmidt-Hebbel K. Does Inflation Targeting Make a Difference? NBER Working Paper, 2007, No. w12876. URL: ssrn.com/abstract=961141 doi.org/10.3386/w12876 39. Charaia V., Papava V. On the Inflation and its Modifications in the Era of Global Pandemic: The Case of Some ADB Countries. J. Asian Finance Econ. Bus., 2022, Vol. 9, No. 8, pp. 0007-0017. URL: ssrn.com/abstract=4207659 40. Solarin Sakiru Adebola, Gil-Alana L.A., Madigu G. Gold prices and the cryptocurrencies: Evidence of convergence and cointegration. Phys. Stat. Mech. Its Appl., 2019, Vol. 523, pp. 1227-1236. doi.org/10.1016/j.physa.2019.04.123 41. Aye G.C., Carcel H., Gil-Alana L.A., Gupta R. Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016. Resour. Policy, 2017, Vol. 54, pp. 53-57. doi.org/10.1016/j.resourpol.2017.09.001 42. Nielsen M.Ø., Shibaev S.S. Forecasting daily political opinion polls using the fractionally cointegrated vector auto‐regressive model. J. R. Stat. Soc. Ser. A Stat. Soc., 2018, Vol. 181, No. 1, pp. 3-33. doi.org/10.1111/rssa.12251 43. Yaya O.S., Ogbonna A., Atoi N.V. Are inflation rates in OECD countries actually stationary during 2011-2018? Evidence based on Fourier Nonlinear Unit root tests with Break. MPRA Paper, 2019, No. 93937. URL: econpapers.repec.org/paper/pramprapa/93937.htm 44. Granger C.W. Some properties of time series data and their use in econometric model specification. J. Econom., 1981, Vol. 16, No. 1, pp. 121-130. doi.org/10.1016/0304-4076(81)90079-8 45. Granger C.W.J. Long memory relationships and the aggregation of dynamic models. J. Econom., 1980, Vol. 14, No. 2, pp. 227-238. doi.org/10.1016/0304-4076(80)90092-5 46. Granger C.W., Joyeux R. An introduction to long‐memory time series models and fractional differencing. J. Time Ser. Anal., 1980, Vol. 1, No. 1, pp. 15-29. doi.org/10.1111/j.1467-9892.1980.tb00297.x 47. Hosking J.R.M. Fractional Differencing. Biometrika, 1981, Vol. 68, No. 1, pp. 165-176. doi.org/10.1093/biomet/68.1.165 48. Adenstedt R.K. On large-sample estimation for the mean of a stationary random sequence. Ann. Stat., 1974, Vol. 2, No. 6, pp. 1095-1107. doi.org/10.1214/aos/1176342867 49. Gil-Alana L., Carcel-Villanova H. A fractional cointegration var analysis of exchange rate dynamics. North Am. J. Econ. Finance, 2018, Vol. 51. doi.org/10.1016/j.najef.2018.09.006 50. Engle R.F., Granger C.W.J. Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 1987, Vol. 55, No. 2, pp. 251-276. doi.org/10.2307/1913236 51. Robinson P.M. Multiple local whittle estimation in stationary systems. Ann. Stat., 2008, Vol. 36, No. 5, pp. 2508-2530. doi.org/10.1214/07-AOS545 52. MacKinnon J.G., Nielsen M.Ø. Numerical distribution function of fractional unit root and cointegration tests: fractional cointegration tests. J. Appl. Econom., 2014, Vol. 29, No. 1, pp. 161-171. doi.org/10.1002/jae.2295 |