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Forecasting Deflation Probability in the EA: A Combinatoric Approach

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  • Luca Brugnolini

    (Central Bank of Malta)

Abstract

This paper assesses and forecasts the probability of deflation in the EA at different horizons using a binomial probit model. The best predictors are selected among more than one-hundred variables adopting a two-step combinatoric approach and exploiting parallel computation in Julia language. The best-selected variables coincide to those standardly included in a small New Keynesian model. Also, the goodness of the models is assessed using three different loss functions: the Mean Absolute Error (MAE), the Root Mean Squared Error (RMSE) and the Area Under the Receiver Operating Characteristics (AUROC). The results are reasonably consistent among the three criteria. Finally, an index averaging the forecasts is computed to assess the probability of being in a deflation state in the next two years. The index shows that having inflation above the 2% level before March 2019 is extremely unlikely.

Suggested Citation

  • Luca Brugnolini, 2018. "Forecasting Deflation Probability in the EA: A Combinatoric Approach," CBM Working Papers WP/01/2018, Central Bank of Malta.
    • Handle: RePEc:mlt:wpaper:0118
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    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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