IDEAS home Printed from https://ideas.repec.org/r/bin/bpeajo/v51y2020i2020-01p167-229.html
   My bibliography  Save this item

When Is Growth at Risk?

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
  2. Xu, Qifa & Xu, Mengnan & Jiang, Cuixia & Fu, Weizhong, 2023. "Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China," Economic Systems, Elsevier, vol. 47(4).
  3. Dimitris Korobilis & Maximilian Schroder, 2023. "Monitoring multicountry macroeconomic risk," Papers 2305.09563, arXiv.org.
  4. Wenbo Jia & Hao Jiang & Yiqing Lyv & Stavros Sindakis, 2025. "Uncertainty’s Effect on China’s Knowledge-Based Economy: Transformation Beyond Trade," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 4684-4725, March.
  5. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
  6. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
  7. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
  8. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
  9. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
  10. Zheng, Tingguo & Gong, Lu & Ye, Shiqi, 2023. "Global energy market connectedness and inflation at risk," Energy Economics, Elsevier, vol. 126(C).
  11. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
  12. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.
  13. Ana Beatriz Galvão & Michael Owyang, 2022. "Forecasting low‐frequency macroeconomic events with high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1314-1333, November.
  14. Huang, Yu-Fan & Liao, Wenting & Wang, Taining, 2024. "Does US financial uncertainty spill over through the (asymmetric) international credit channel? The role of market expectations," Journal of International Money and Finance, Elsevier, vol. 148(C).
  15. Hongqi Chen & Ji Hyung Lee, 2024. "Predictive Quantile Regression with High-Dimensional Predictors: The Variable Screening Approach," Papers 2410.15097, arXiv.org.
  16. Suarez, Javier, 2021. "Growth-at-risk and macroprudential policy design JEL Classification: G01, G20, G28," ESRB Occasional Paper Series 19, European Systemic Risk Board.
  17. Yao, Shouyu & Liu, Zezhong & Wang, Chunfeng & Palma, Alessia & Goodell, John W., 2024. "Is macroeconomic tail risk contagious to stock idiosyncratic risk?," Finance Research Letters, Elsevier, vol. 63(C).
  18. Yannick Hoga & Christian Schulz, 2025. "Self-Normalized Inference in (Quantile, Expected Shortfall) Regressions for Time Series," Papers 2502.10065, arXiv.org.
  19. Hie Joo Ahn & Lam Nguyen, 2025. "Who's at Risk? Effects of Inflation on Unemployment Risk," Papers 2505.05757, arXiv.org.
  20. Liu, Han & Wang, Lijun & Zhuo, Xingxuan, 2025. "Unveiling the shadows: The effects of financial conditions on the tail risks of China's macroeconomic activities," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 1-14.
  21. Tobias Adrian & Hongqi Chen & Max-Sebastian Dov`i & Ji Hyung Lee, 2025. "Machine-learning Growth at Risk," Papers 2506.00572, arXiv.org.
  22. Michael T. Kiley, 2024. "Growth at risk from climate change," Economic Inquiry, Western Economic Association International, vol. 62(3), pages 1134-1151, July.
  23. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Vulnerable funding in the global economy," Journal of Banking & Finance, Elsevier, vol. 169(C).
  24. Forni, Mario & Gambetti, Luca & Maffei-Faccioli, Nicolò & Sala, Luca, 2024. "The effects of monetary policy on macroeconomic risk," European Economic Review, Elsevier, vol. 167(C).
  25. Moffo, Ahmadou Mustapha Fonton, 2024. "A machine learning approach in stress testing US bank holding companies," International Review of Financial Analysis, Elsevier, vol. 95(PC).
  26. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024. "Reprint of: Out-of-sample tests for conditional quantile coverage: An application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 244(2).
  27. Sui, Jianli & Lv, Wenqiang & Gao, Xiang & Koedijk, Kees G., 2024. "China’s GDP-at-Risk: Real-Time Monitoring, Risk Tracing, and Macroeconomic Policy Effects," Journal of International Money and Finance, Elsevier, vol. 147(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.