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A Machine Learning Approach To GDP Nowcasting: An Emerging Market Experience
The growth rate of real Gross Domestic Product (GDP), as measured by the National Statistical Office of India, is an important metric for monetary policy making. Because GDP is released with a significant lag, particularly for the emerging market economies, this article presents various methodologies for nowcasting and forecasting GDP, using both traditional time series and machine learning methods. Further, considering the
importance of forward-looking information, our nowcasting model incorporates financial market data and an economic uncertainty index, in addition to high-frequency traditional macroeconomic indicators. Our findings suggest an improvement in the performance of nowcasting using a hybrid of machine learning and conventional time series methods.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| PSB lt.dasar - Pascasarjana (Majalah) | 1 |
| Penerbit | Jakarta: Bank Indonesia 2023 |
|---|---|
| Edisi | Volume 26, 16th BMEB Call for Papers Special Issue |
| Subjek | Machine Learning Nowcasting Market experience |
| ISBN/ISSN | 2460-9196 |
| Klasifikasi | NONE |
| Deskripsi Fisik | 148 p. |
| Info Detail Spesifik | Bulletin Of Monetary Economics And Banking |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas |