Predicting economic contractions and expansions with the aid of professional forecasts

Chew Lian Chua, Sarantis Tsiaplias

Research output: Journal PublicationArticlepeer-review

Abstract

Traditional econometric models of economic contractions typically perform poorly in forecasting exercises. This criticism is also frequently levelled at professional forecast probabilities of contractions. This paper addresses the problem of incorporating the entire distribution of professional forecasts into an econometric model for forecasting contractions and expansions. A new augmented probit approach is proposed, involving the transformation of the distribution of professional forecasts into a 'professional forecast' prior for the economic data underlying the probit model. Since the object of interest is the relationship between the distribution of professional forecasts and the probit model's economic-data dependent parameters, the solution avoids criticisms levelled at the accuracy of professional forecast based point estimates of contractions. An application to US real GDP data shows that the model yields significant forecast improvements relative to alternative approaches.

Original languageEnglish
Pages (from-to)438-451
Number of pages14
JournalInternational Journal of Forecasting
Volume27
Issue number2
DOIs
Publication statusPublished - Apr 2011
Externally publishedYes

Keywords

  • Bayesian analysis
  • Forecast performance
  • Probit model

ASJC Scopus subject areas

  • Business and International Management

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