Seeing in the Dark : A Machine-Learning Approach to Nowcasting in Lebanon /
Macroeconomic analysis in Lebanon presents a distinct challenge. For example, long delays in the publication of GDP data mean that our analysis often relies on proxy variables, and resembles an extended version of the 'nowcasting' challenge familiar to many central banks. Addressing this p...
| Main Author: | Tiffin, Andrew |
|---|---|
| Format: | Journal |
| Language: | English |
| Published: |
Washington, D.C. :
International Monetary Fund,
2016.
|
| Series: | IMF Working Papers; Working Paper ;
No. 2016/056 |
| Subjects: | |
| Online Access: | Full text available on IMF |
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