Predicting Recessions : A New Approach for Identifying Leading Indicators and Forecast Combinations /
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...
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | 雜誌 |
| 語言: | English |
| 出版: |
Washington, D.C. :
International Monetary Fund,
2011.
|
| 叢編: | IMF Working Papers; Working Paper ;
No. 2011/235 |
| 在線閱讀: | Full text available on IMF |
| 總結: | 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. |
|---|---|
| Item Description: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| 實物描述: | 1 online resource (30 pages) |
| 格式: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| 訪問: | Electronic access restricted to authorized BRAC University faculty, staff and students |