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Author/Editor:
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Baba, Chikako ; Kisinbay, Turgut
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Publication Date:
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October 01, 2011
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Electronic Access:
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Free Full text
(PDF file size is 1,241KB).
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Disclaimer: This Working Paper should not be reported as representing the views of the IMF.
The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate
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Summary:
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.
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Order a print copy
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Series:
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Working Paper No. 11/235
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Subject(s):
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Business cycles | Economic forecasting | Economic indicators | Economic recession | Forecasting models | United States
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Author's Keyword(s):
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business cycles | leading indicators | forecast encompassing | forecast combination |
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