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Predictable non-linearities in U.S. inflation

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  • Binner, Jane M.
  • Elger, C. Thomas
  • Nilsson, Birger
  • Tepper, Jonathan A.

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  • Binner, Jane M. & Elger, C. Thomas & Nilsson, Birger & Tepper, Jonathan A., 2006. "Predictable non-linearities in U.S. inflation," Economics Letters, Elsevier, vol. 93(3), pages 323-328, December.
    • Handle: RePEc:eee:ecolet:v:93:y:2006:i:3:p:323-328
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    References listed on IDEAS

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    1. Nakamura, Emi, 2005. "Inflation forecasting using a neural network," Economics Letters, Elsevier, vol. 86(3), pages 373-378, March.
    2. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    3. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
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    Cited by:

    1. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Sciendo, vol. 9(2), pages 18-34, July.
    2. Elger, Thomas & Jones, Barry E. & Nilsson, Birger, 2006. "Forecasting with Monetary Aggregates: Recent Evidence for the United States," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 428-446.
    3. Macias, Paweł & Stelmasiak, Damian & Szafranek, Karol, 2023. "Nowcasting food inflation with a massive amount of online prices," International Journal of Forecasting, Elsevier, vol. 39(2), pages 809-826.
    4. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    5. Zhang, Lingxiang, 2013. "Modeling China's inflation dynamics: An MRSTAR approach," Economic Modelling, Elsevier, vol. 31(C), pages 440-446.
    6. Emrah Çevik & Erdal Atukeren & Turhan Korkmaz, 2013. "Nonlinearity and nonstationarity in international art market prices: evidence from Markov-switching ADF unit root tests," Empirical Economics, Springer, vol. 45(2), pages 675-695, October.
    7. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    8. Tea Šestanović & Josip Arnerić, 2021. "Can Recurrent Neural Networks Predict Inflation in Euro Zone as Good as Professional Forecasters?," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
    9. Marcos Álvarez-Díaz & Rangan Gupta, 2015. "Forecasting the US CPI: Does Nonlinearity Matter?," Working Papers 201512, University of Pretoria, Department of Economics.
    10. Antonio N. Bojanic, 2021. "A Markov-Switching Model of Inflation in Bolivia," Economies, MDPI, vol. 9(1), pages 1-18, March.
    11. Binner, J.M. & Tino, P. & Tepper, J. & Anderson, R. & Jones, B. & Kendall, G., 2010. "Does money matter in inflation forecasting?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4793-4808.
    12. Tea Šestanović & Josip Arnerić, 2021. "Neural network structure identification in inflation forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 62-79, January.

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