Confidence, animal spirits, and the macroeconomy in China: Based on mixed-frequency data models
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DOI: 10.1371/journal.pone.0332909
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- Giannone, Domenico & Reichlin, Lucrezia & Simonelli, Saverio, 2009.
"Nowcasting Euro Area Economic Activity in Real Time: The Role of Confidence Indicators,"
National Institute Economic Review, National Institute of Economic and Social Research, vol. 210, pages 90-97, October.
- Domenico Giannone & Lucrezia Reichlin & Saverio Simonelli, 2009. "Nowcasting Euro Area Economic Activity In Real Time: The Role Of Confidence Indicators," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210(1), pages 90-97, October.
- Domenico Giannone & Lucrezia Reichlin & Saverio Simonelli, 2009. "Nowcasting Euro Area Economic Activity in Real-Time: The Role of Confidence Indicators," CSEF Working Papers 240, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
- Domenico Giannone & Lucrezia Reichlin & Saverio Simonelli, 2009. "Nowcasting Euro Area Economic Activity in Real-Time: The Role of Confidence Indicator," Working Papers ECARES 2009_021, ULB -- Universite Libre de Bruxelles.
- Javier Rojo-Suárez & Ana Belén Alonso-Conde, 2020. "Impact of consumer confidence on the expected returns of the Tokyo Stock Exchange: A comparative analysis of consumption and production-based asset pricing models," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
- Guo, Yumei & He, Shan, 2020. "Does confidence matter for economic growth? An analysis from the perspective of policy effectiveness," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1-19.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004.
"The MIDAS Touch: Mixed Data Sampling Regression Models,"
University of California at Los Angeles, Anderson Graduate School of Management
qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
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