 Was the recent downturn in US real GDP predictable?Mehmet Balcilar, Rangan Gupta, Anandamayee Majumdar and Stephen Miller Applied Economics, 2015, vol. 47, issue 28, 2985-3007 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-of-sample 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. Date: 2015 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:47:y:2015:i:28:p:2985-3007 Ordering information: This journal article can be ordered from DOI: 10.1080/00036846.2015.1011317 Access Statistics for this article Applied Economics is currently edited by Anita Phillips More articles in Applied Economics from Taylor & Francis Journals |
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