Detecting and Predicting Economic Accelerations, Recessions, and Normal Growth Periods in Real‐Time. (19th May 2016)

• Record Type: Journal Article
• Authors: Proaño, Christian R.
• Is Part Of: Journal of forecasting. Volume 36:Number 1(2017)
• Page Start: 26
• Page End: 42
• Publication Date: 2016-05-19
• Subjects: business cycle forecasting -- ordered probit models -- dynamic probit models -- real‐time econometrics; Forecasting -- Periodicals; Forecasting -- Mathematical models -- Periodicals; 003.2
• DOI: 10.1002/for.2412
• Languages: English
• ISSNs: 0277-6693

Abstract

Abstract : The dichotomous characterization of the business cycle in recessions and expansions has been central in the literature over the last 50 years. However, there are various reasons to question the adequacy of this dichotomous, recession/expansion approach for our understanding of the business cycle dynamics, as well as for the prediction of future business cycle developments. In this context, the contribution of this paper to the literature is twofold. First, since a positive rate of growth at the level of economic activity can be considered as the normal scenario in modern economies due to both population and technological growth, it proposes a new non‐parametric algorithm for the detection and dating of economic acceleration periods, trend or normal growth periods, and economic recessions. Second, it uses an ordered probit framework for the estimation and forecasting of these three business cycle phases, applying an automatized model selection approach using monthly macroeconomic and financial data on the German economy. The empirical results show that this approach has superior out‐of‐sample properties under real‐time conditions compared to alternative probit models specified individually for the prediction of recessions and/or economic accelerations. Copyright © 2016 John Wiley & Sons, Ltd.