| 000 | 00960nam a2200121 4500 | ||
|---|---|---|---|
| 999 |
_c39248 _d39248 |
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| 020 | _a9783030311520 | ||
| 245 |
_aMacroeconomic Forecasting in the Era of Big Data: _bTheory and Practice |
||
| 260 |
_bSpringer Nature _c©2020 |
||
| 300 | _a 719 p. | ||
| 520 | _aThis book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics. About the Author | ||
| 700 |
_aPeter Fuleky _eEditor |
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| 942 |
_2ddc _cBK |
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