Balcilar, MehmetGupta, RanganMajumdar, AnandamayeeMiller, Stephen M.2016-04-182015-10Mehmet 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:10.1080/00036846.2015.1011317.0003-6846 (print)1466-4283 (online)10.1080/00036846.2015.1011317http://hdl.handle.net/2263/52036This 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.en© 2015 Taylor and Francis. This is an electronic version of an article published in Applied Economics, vol. 47, no. 28, pp. 2985-3007, 2015. doi : 10.1080/00036846.2015.1011317. Applied Economics is available online at : http://www.tandfonline.comloi/raec20.ForecastingLinear and nonlinear modelsTime series and structural modelsGreat recessionPostprint Article