Forecasting Deflation Probability in the EA: A Combinatoric Approach - Luca Brugnolini (Central Bank of Malta, 2018)
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.
Keywords: C25; C63; E3; E58; 330