Was the recent downturn in US real GDP predictable?
Loading...
Date
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.