Forecasting gross domestic product growth with large unbalanced data sets: the mixed frequency three‐pass regression filter
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DOI: 10.1111/rssa.12363
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Cited by:
- Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023.
"Forecasting real activity using cross-sectoral stock market information,"
Journal of International Money and Finance, Elsevier, vol. 131(C).
- Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie Chinn, 2023. "Forecasting real activity using cross-sectoral stock market information," Post-Print hal-04459605, HAL.
- Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
- Nicolas Chatelais & Menzie Chinn & Arthur Stalla-Bourdillon, 2022.
"Macroeconomic Forecasting Using Filtered Signals from a Stock Market Cross Section,"
Working papers
903, Banque de France.
- Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie D. Chinn, 2022. "Macroeconomic Forecasting using Filtered Signals from a Stock Market Cross Section," NBER Working Papers 30305, National Bureau of Economic Research, Inc.
- Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
- Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
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