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Inflation forecasting in Angola: a fractional approach

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  • Carlos Barros
  • Luis Gil-Alana

Abstract

This paper forecasts inflation in Angola with an ARFIMA (AutoRegressive Fractionally Integrated Moving Average) model. It is found that inflation in Angola is a highly persistent variable with an order of integration constrained between 0 and 1. Moreover, a structural break is found in August, 1996. Using the second sub-sample for forecasting purposes, the results reveal that inflation will remain low, assuming that prudent macroeconomic policies are maintained.

Suggested Citation

  • Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Center of African, Asian and Latin American Studies.
  • Handle: RePEc:cav:cavwpp:wp103
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    References listed on IDEAS

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    1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    2. Lars E O Svensson, 2005. "Monetary Policy with Judgment: Forecast Targeting," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    3. Pedregal, Diego J. & Pérez, Javier J., 2010. "Should quarterly government finance statistics be used for fiscal surveillance in Europe?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 794-807, October.
    4. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    5. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    6. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
    7. David K. Backus & Stanley E. Zin, 1993. "Long-memory inflation uncertainty: evidence from the term structure of interest rates," Proceedings, Federal Reserve Bank of Cleveland, pages 681-708.
    8. Gil-Alana, Luis A., 2011. "Inflation in South Africa. A long memory approach," Economics Letters, Elsevier, vol. 111(3), pages 207-209, June.
    9. Cancelo, José Ramón & Espasa, Antoni & Grafe, Rosmarie, 2008. "Forecasting the electricity load from one day to one week ahead for the Spanish system operator," International Journal of Forecasting, Elsevier, vol. 24(4), pages 588-602.
    10. Luis A. Gil‐alana, 2010. "Inflation In South Africa: A Time‐Series View Across Sectors Using Long‐Range Dependence," South African Journal of Economics, Economic Society of South Africa, vol. 78(4), pages 325-343, December.
    11. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
    12. Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, pages 427-449.
    13. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    14. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    15. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.
    16. Kadima D. Kalonji & Jan Gottschalk & Ken Miyajima, 2008. "Analyzing Determinants of Inflation When There Are Data Limitation; The Case of Sierra Leone," IMF Working Papers 08/271, International Monetary Fund.
    17. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    18. A. Espasa & E. Senra & R. Albacete, 2002. "Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors," The European Journal of Finance, Taylor & Francis Journals, pages 402-421.
    19. Luis A. Gil-Alana, 2008. "Fractional integration and structural breaks at unknown periods of time," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 163-185, January.
    20. Chambers, Marcus J, 1998. "Long Memory and Aggregation in Macroeconomic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1053-1072, November.
    21. Richard T. Baillie & Young Wook Han & Tae-Go Kwon, 2002. "Further Long Memory Properties of Inflationary Shocks," Southern Economic Journal, Southern Economic Association, vol. 68(3), pages 496-510, January.
    22. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    23. Baillie, Richard T & Chung, Ching-Fan & Tieslau, Margie A, 1996. "Analysing Inflation by the Fractionally Integrated ARFIMA-GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 23-40, Jan.-Feb..
    24. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    25. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    26. Gil-Alana, Luis A., 2000. "Mean reversion in the real exchange rates," Economics Letters, Elsevier, vol. 69(3), pages 285-288, December.
    27. Christopher F. Baum & John T. Barkoulas & Mustafa Caglayan, 1999. "Persistence in International Inflation Rates," Southern Economic Journal, Southern Economic Association, vol. 65(4), pages 900-913, April.
    28. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, pages 131-159.
    29. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    30. Luis A. Gil-Alana & S. G. Brian Henry, 2003. "Fractional Integration and the Dynamics of UK Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(2), pages 221-239, May.
    31. Christopher F. Baum & John Barkoulas, 2006. "Long-memory forecasting of US monetary indices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 291-302.
    32. Franses, Philip Hans & Ooms, Marius, 1997. "A periodic long-memory model for quarterly UK inflation," International Journal of Forecasting, Elsevier, vol. 13(1), pages 117-126, March.
    33. Duarte, Claudia & Rua, Antonio, 2007. "Forecasting inflation through a bottom-up approach: How bottom is bottom?," Economic Modelling, Elsevier, vol. 24(6), pages 941-953, November.
    34. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    35. Kallon, Kelfala M, 1994. "An Econometric Analysis of Inflation in Sierra Leone," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 3(2), pages 199-230, October.
    36. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    37. William R. Parke, 1999. "What Is Fractional Integration?," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 632-638, November.
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    Cited by:

    1. Carlos Pestana Barros & Otavio Henrique dos Santos Figueiredo & Peter Fernades Wanke, 2016. "Peasants’ Poverty and Inequality in Angola," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(2), pages 751-761, September.
    2. Carlos P. Barros & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, pages 59-73.

    More about this item

    Keywords

    Angola; inflation; long memory;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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