Predicting binary outcomes based on the pair-copula construction

Kajal Lahiri () and Liu Yang ()
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Kajal Lahiri: University at Albany, SUNY
Liu Yang: Nanjing University

A chapter in Advances in Applied Econometrics, 2024, pp 633-663 from Springer

Abstract: Abstract We develop a new econometric model for the purpose of predicting binary outcomes based on an ensemble of predictors. The method uses the pair-copula construction (PCC) to optimally combine diverse information. As a building block of PCC, the conditional copula is permitted to depend on the conditioning variable in a nonparametric way. This is the major methodological departure from our previous work. We apply this methodology to predict US business cycle peaks 6 months ahead based on the three prominent leading indicators currently used by The Conference Board. In terms of the predictive accuracy as measured by the receiver operating characteristic curve, the proposed scheme is found to do well in comparison with some popular combination models. We have also evaluated the probability forecasts generated from these models using a battery of diagnostic tools, each of which reveals different aspects of skill of the generated forecasts.

Keywords: Pair-copula construction; Local likelihood; Receiver operating characteristic curve; Calibration; Recession (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-48385-1_23

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