Empirical Economics

, Volume 46, Issue 1, pp 127–144

Predicting U.S. recessions through a combination of probability forecasts

Article

DOI: 10.1007/s00181-012-0671-4

Cite this article as:
De Luca, G. & Carfora, A. Empir Econ (2014) 46: 127. doi:10.1007/s00181-012-0671-4

Abstract

Recently De Luca and Carfora (Statistica e Applicazioni 8:123–134, 2010) have proposed a novel model for binary time series, the Binomial Heterogenous Autoregressive (BHAR) model, successfully applied for the analysis of the quarterly binary time series of U.S. recessions. In this work we want to measure the efficacy of the out-of-sample forecasts of the BHAR model compared to the probit models by Kauppi and Saikkonen (Rev Econ Stat 90:777–791, 2008). Given the substantial indifference of the predictive accuracy between the BHAR and the probit models, a combination of forecasts using the method proposed by Bates and Granger (Oper Res Q 20:451–468, 1969) for probability forecasts is analyzed. We show how the forecasts obtained by the combination between the BHAR model and each of the probit models are superior compared to the forecasts obtained by each single model.

Keywords

Binary response modelRecession forecasting Forecasts combinationDiebold–Mariano test

Jel Classifications:

E32E37C53

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Statistics and Mathematics for Economic ResearchUniversity of Naples ParthenopeNaplesItaly