Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast Combinations

Turgut Kisinbay and Chikako Baba

No 2011/235, IMF Working Papers from International Monetary Fund

Abstract: This study proposes a data-based algorithm to select a subset of indicators from a large data set with a focus on forecasting recessions. The algorithm selects leading indicators of recessions based on the forecast encompassing principle and combines the forecasts. An application to U.S. data shows that forecasts obtained from the algorithm are consistently among the best in a large comparative forecasting exercise at various forecasting horizons. In addition, the selected indicators are reasonable and consistent with the standard leading indicators followed by many observers of business cycles. The suggested algorithm has several advantages, including wide applicability and objective variable selection.

Keywords: WP; business cycle; significance level; formal methods; business cycles; leading indicators; forecast encompassing; forecast combination; leading indicator literature; EAL forecast; housing sector variable; EAL algorithm; forecasting recession; employment variable; Cyclical indicators; Housing; Labor markets; Capacity utilization; Global (search for similar items in EconPapers)
Pages: 30
Date: 2011-10-01
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Citations: View citations in EconPapers (3)

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