Department of Economics and Business Economics

Forecasting dynamically asymmetric fluctuations of the U.S. business cycle.

Research output: Working paper


    Emilio Zanetti Chini, University of Pavia and CREATES, Italy
I provide general frequentist framework to elicit the forecaster’s expected utility based on a Lagrange Multiplier-type test for the null of locality of the scoring rules associated to the probabilistic forecast. These are assumed to be observed transition variables in a nonlinear autoregressive model to ease the statistical inference. A simulation study reveals that the test behaves consistently with the requirements of the theoretical literature. The locality of the scoring rule is fundamental to set dating algorithms to measure and forecast probability of recession in US business cycle. An investigation of Bank of Norway’s forecasts on output growth leads us to conclude that forecasts are often suboptimal with respect to some simplistic benchmark if forecaster’s reward is not properly evaluated.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages41
StatePublished - 9 Jan 2018
SeriesCREATES Research Papers

See relations at Aarhus University Citationformats

ID: 120260077