Was the recent downturn in US real GDP predictable?

Loading...
Thumbnail Image

Authors

Balcilar, Mehmet
Gupta, Rangan
Majumdar, Anandamayee
Miller, Stephen M.

Journal Title

Journal ISSN

Volume Title

Publisher

Routledge

Abstract

This article uses a small set of variables – real GDP, the inflation rate and the short-term interest rate – and a rich set of models – atheoretical (time series) and theoretical (structural), linear and nonlinear, as well as classical and Bayesian models – to consider whether we could have predicted the recent downturn of the US real GDP. Comparing the performance of the models to the benchmark random-walk model by root mean-square errors, the two structural (theoretical) models, especially the nonlinear model, perform well on average across all forecast horizons in our ex post, out-ofsample forecasts, although at specific forecast horizons certain nonlinear atheoretical models perform the best. The nonlinear theoretical model also dominates in our ex ante, out-of-sample forecast of the Great Recession, suggesting that developing forward-looking, microfounded, nonlinear, dynamic stochastic general equilibrium models of the economy may prove crucial in forecasting turning points.

Description

Keywords

Forecasting, Linear and nonlinear models, Time series and structural models, Great recession

Sustainable Development Goals

Citation

Mehmet Balcilar, Rangan Gupta, Anandamayee Majumdar & Stephen M.Miller (2015) Was the recent downturn in US real GDP predictable?, Applied Economics, 47:28,2985-3007, DOI:10.1080/00036846.2015.1011317.