Nowcasting Economic Activity in Times of COVID-19 : An Approximation from the Google Community Mobility Report
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- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
- Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011.
"A two-step estimator for large approximate dynamic factor models based on Kalman filtering,"
Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2006. "A Two-step estimator for large approximate dynamic factor models based on Kalman filtering," THEMA Working Papers 2006-23, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," PSE-Ecole d'économie de Paris (Postprint) hal-00638009, HAL.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00638009, HAL.
- Catherine Doz & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Post-Print hal-00844811, HAL.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Post-Print hal-00638009, HAL.
- Reichlin, Lucrezia & Doz, Catherine & Giannone, Domenico, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers.
- Jushan Bai & Serena Ng, 2002.
"Determining the Number of Factors in Approximate Factor Models,"
Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012.
"A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models,"
The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
- Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "A quasi maximum likelihood approach for large approximate dynamic factor models," Working Paper Series 674, European Central Bank.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2008. "A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models," Working Papers ECARES 2008_034, ULB -- Universite Libre de Bruxelles.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," Post-Print hal-00638440, HAL.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00638440, HAL.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) hal-00638440, HAL.
- Reichlin, Lucrezia & Doz, Catherine & Giannone, Domenico, 2006. "A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models," CEPR Discussion Papers 5724, C.E.P.R. Discussion Papers.
- Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019.
"Forecasting economic time series using score-driven dynamic models with mixed-data sampling,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
- Paolo Gorgi & Siem Jan (S.J.) Koopman & Mengheng Li, 2018. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," Tinbergen Institute Discussion Papers 18-026/III, Tinbergen Institute.
- Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
- 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.
- Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
- James H. Stock & Mark W. Watson, 1989.
"New Indexes of Coincident and Leading Economic Indicators,"
NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409,
National Bureau of Economic Research, Inc.
- Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Andreou, Elena & Ghysels, Eric & Kourtellos, Andros, 2010.
"Regression models with mixed sampling frequencies,"
Journal of Econometrics, Elsevier, vol. 158(2), pages 246-261, October.
- Elena Andreou, Eric Ghysels & Eric Ghysels & Andros Kourtellos, 2007. "Regression Models with Mixed Sampling Frequencies," University of Cyprus Working Papers in Economics 8-2007, University of Cyprus Department of Economics.
- repec:hal:journl:peer-00844811 is not listed on IDEAS
- Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
- Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 521-536.
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Cited by:
- Steven J. Davis & Dingqian Liu & Xuguang Simon Sheng, 2022.
"Stock Prices and Economic Activity in the Time of Coronavirus,"
IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(1), pages 32-67, March.
- Steven J. Davis & Dingqian Liu & Xuguang Simon Sheng, 2021. "Stock Prices and Economic Activity in the Time of Coronavirus," NBER Working Papers 28320, National Bureau of Economic Research, Inc.
- Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024. "Reinvigorating Gva Nowcasting In The Postpandemic Period: A Case Study For India," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(Spesial I), pages 95-130, Februari.
- Yose Rizal Damuri & Prabaning Tyas & Haryo Aswicahyono & Lionel Priyadi & Stella Kusumawardhani & Ega Kurnia Yazid, 2021. "Tracking the Ups and Downs in Indonesia’s Economic Activity During COVID-19 Using Mobility Index: Evidence from Provinces in Java and Bali," Working Papers DP-2021-18, Economic Research Institute for ASEAN and East Asia (ERIA).
- Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Carlos D. Rojas-Martínez, 2021. "Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches," Borradores de Economia 1168, Banco de la Republica de Colombia.
- Noel Rapa, 2021. "Mitigation measures, prevalence response and public mobility during the COVID-19 emergency," CBM Working Papers WP/03/2021, Central Bank of Malta.
- Joshua Rosenberg & Ilan Strauss & Gilad Isaacs, 2021. "COVID‐19 impact on SADC labour markets: Evidence from high‐frequency data and other sources," African Development Review, African Development Bank, vol. 33(S1), pages 177-193, April.
- Velias, Alina & Georganas, Sotiris & Vandoros, Sotiris, 2022. "COVID-19: Early evening curfews and mobility," Social Science & Medicine, Elsevier, vol. 292(C).
- Chakrabarty, Debajyoti & Bhatia, Bhanu & Jayasinghe, Maneka & Low, David, 2023. "Relative deprivation, inequality and the Covid-19 pandemic," Social Science & Medicine, Elsevier, vol. 324(C).
- Davide Furceri & Siddharth Kothari & Longmei Zhang, 2021. "The effects of COVID‐19 containment measures on the Asia‐Pacific region," Pacific Economic Review, Wiley Blackwell, vol. 26(4), pages 469-497, October.
- Mantas Lukauskas & Vaida Pilinkienė & Jurgita Bruneckienė & Alina Stundžienė & Andrius Grybauskas & Tomas Ruzgas, 2022. "Economic Activity Forecasting Based on the Sentiment Analysis of News," Mathematics, MDPI, vol. 10(19), pages 1-22, September.
- Cseres-Gergely, Zsombor & Kecht, Valentin & Le Blanc, Julia & Onorante, Luca, 2024. "The economic impact of general vs. targeted lockdowns: New insights from Italian municipalities," Economic Modelling, Elsevier, vol. 134(C).
- Emily Schmidt & Paul Dorosh & Rachel Gilbert, 2021. "Impacts of COVID‐19 induced income and rice price shocks on household welfare in Papua New Guinea: Household model estimates," Agricultural Economics, International Association of Agricultural Economists, vol. 52(3), pages 391-406, May.
- Daniel Hopp, 2022. "Performance of long short-term memory artificial neural networks in nowcasting during the COVID-19 crisis," Papers 2203.11872, arXiv.org.
- João Tovar Jalles & Bryn Battersby & Rachel Lee, 2024. "Effectiveness of Fiscal Announcements: Early Evidence from COVID-19," Open Economies Review, Springer, vol. 35(3), pages 623-658, July.
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Keywords
International Trade and Trade Rules; Health Care Services Industry; Pharmaceuticals Industry; ICT Policy and Strategies; ICT Legal and Regulatory Framework; Economic Conditions and Volatility;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ETS-2020-05-25 (Econometric Time Series)
- NEP-HEA-2020-05-25 (Health Economics)
- NEP-ICT-2020-05-25 (Information and Communication Technologies)
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