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Forecasting Inflation with a Simple and Accurate Benchmark: The Case of the US and a Set of Inflation Targeting Countries

Listed author(s):
  • Pablo M. Pincheira

    ()

    (Central Bank of Chile and School of Business, Adolfo Ibánez University, Chile)

  • Carlos A. Medel

    (Central Bank of Chile)

We evaluate the ability of several univariate models to predict inflation in the US and in a number of inflation targeting countries at different forecasting horizons. We focus on forecasts coming from a family of ten seasonal models that we call the Driftless Extended Seasonal ARIMA (DESARIMA) family. Using out-of-sample Root Mean Squared Prediction Errors (RMSPE) we compare the forecasting accuracy of the DESARIMA family with that of traditional univariate time-series benchmarks available in the literature. Our results show that DESARIMA-based forecasts display lower RMSPE at short horizons for every single country, with the exception of one case. We obtain mixed results at longer horizons. In particular, when the family-median forecast is considered, in more than half of the countries our DESARIMA-based forecasts outperform the benchmarks at long horizons. Remarkably, the forecasting accuracy of our DESARIMA family is high in stable-inflation countries, for which the RMSPE is around 100 basis points when a prediction is made 24 and even 36 months ahead.

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Article provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.

Volume (Year): 65 (2015)
Issue (Month): 1 (January)
Pages: 2-29

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Handle: RePEc:fau:fauart:v:65:y:2015:i:1:p:2-29
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  1. Proietti, Tommaso, 2011. "Direct and iterated multistep AR methods for difference stationary processes," International Journal of Forecasting, Elsevier, vol. 27(2), pages 266-280.
  2. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
  3. Clive Granger & Yongil Jeon, 2004. "Forecasting Performance of Information Criteria with Many Macro Series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(10), pages 1227-1240.
  4. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
  5. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
  6. Pablo Pincheira & Roberto Álvarez, 2009. "Evaluation of Short Run Inflation Forecasts and Forecasters in Chile," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(2), pages 159-180, July-Dece.
  7. Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
  8. 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.
  9. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
  10. Pablo Pincheira & Carlos A. Medel, 2012. "Forecasting Inflation with a Simple and Accurate Benchmark: a Cross-Country Analysis," Working Papers Central Bank of Chile 677, Central Bank of Chile.
  11. Pincheira, Pablo, 2013. "A Bunch of Models, a Bunch of Nulls and Inference about Predictive Ability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 26-43, October.
  12. Pablo Pincheira, 2010. "A Real Time Evaluation of the Central Bank of Chile GDP Growth Forecasts," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 37-73, January-J.
  13. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
  14. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
  15. Pablo Pincheira & Carlos Medel, 2012. "Forecasting Inflation With a Random Walk," Working Papers Central Bank of Chile 669, Central Bank of Chile.
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