Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model
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- Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
- Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2023.
"Forecasting regional GDPs: a comparison with spatial dynamic panel data models,"
Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(4), pages 530-551, October.
- Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2021. "Forecasting Regional GDPs: a Comparison with Spatial Dynamic Panel Data Models," FBK-IRVAPP Working Papers 2021-02, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
- Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023.
"Nowcasting in a pandemic using non-parametric mixed frequency VARs,"
Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
- Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.
- Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," JRC Working Papers in Economics and Finance 2021-01, Joint Research Centre, European Commission.
- Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Working Paper Series 2510, European Central Bank.
- João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020.
"Nowcasting East German GDP growth: a MIDAS approach,"
Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
- Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
- Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023.
"High-dimensional conditionally Gaussian state space models with missing data,"
Journal of Econometrics, Elsevier, vol. 236(1).
- Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
- Lehmann Robert & Wohlrabe Klaus, 2015.
"Forecasting GDP at the Regional Level with Many Predictors,"
German Economic Review, De Gruyter, vol. 16(2), pages 226-254, May.
- Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, May.
- Robert Lehmann & Klaus Wohlrabe, 2012. "Forecasting GDP at the Regional Level with Many Predictors," CESifo Working Paper Series 3956, CESifo.
- Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting GDP at the regional level with many predictors," ERSA conference papers ersa13p15, European Regional Science Association.
- Lehmann, Robert & Wohlrabe, Klaus, 2013. "Forecasting GDP at the regional level with many predictors," Discussion Papers in Economics 17104, University of Munich, Department of Economics.
- Carlos M. Carvalho & Nicholas G. Polson & James G. Scott, 2010. "The horseshoe estimator for sparse signals," Biometrika, Biometrika Trust, vol. 97(2), pages 465-480.
- Frank Schorfheide & Dongho Song, 2015.
"Real-Time Forecasting With a Mixed-Frequency VAR,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
- Frank Schorfheide & Dongho Song, 2012. "Real-time forecasting with a mixed-frequency VAR," Working Papers 701, Federal Reserve Bank of Minneapolis.
- Frank Schorfheide & Dongho Song, 2013. "Real-Time Forecasting with a Mixed-Frequency VAR," NBER Working Papers 19712, National Bureau of Economic Research, Inc.
- Robert Lehmann & Ida Wikman, 2022.
"Quarterly GDP Estimates for the German States,"
ifo Working Paper Series
370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
- Robert Lehmann & Ida Wikman, 2023. "Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics," CESifo Working Paper Series 10280, CESifo.
- Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020.
"Computationally efficient inference in large Bayesian mixed frequency VARs,"
Economics Letters, Elsevier, vol. 191(C).
- Deborah Gefang & Gary Koop & Aubrey Poon, "undated". "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Discussion Papers in Economics 20/02, Division of Economics, School of Business, University of Leicester.
- Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
- Henzel Steffen R. & Lehmann Robert & Wohlrabe Klaus, 2015.
"Nowcasting Regional GDP: The Case of the Free State of Saxony,"
Review of Economics, De Gruyter, vol. 66(1), pages 71-98, April.
- Steffen Henzel & Robert Lehmann & Klaus Wohlrabe, 2015. "Nowcasting Regional GDP: The Case of the Free State of Saxony," CESifo Working Paper Series 5336, CESifo.
- Henzel, Steffen & Lehmann, Robert & Wohlrabe, Klaus, 2015. "Nowcasting Regional GDP: The Case of the Free State of Saxony," MPRA Paper 63714, University Library of Munich, Germany.
- Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
- Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
- Gary Koop & Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon & Ping Wu, 2023.
"Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting,"
Working Papers
23-09, Federal Reserve Bank of Cleveland.
- Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon & Ping Wu, 2023. "Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting," Working Papers 2311, University of Strathclyde Business School, Department of Economics.
- Lucie Plzáková & Egon Smeral, 2022. "Impact of the COVID-19 crisis on European tourism," Tourism Economics, , vol. 28(1), pages 91-109, February.
- Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, February.
- Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
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This paper has been announced in the following NEP Reports:- NEP-ECM-2024-02-26 (Econometrics)
- NEP-EEC-2024-02-26 (European Economics)
- NEP-EUR-2024-02-26 (Microeconomic European Issues)
- NEP-GEO-2024-02-26 (Economic Geography)
- NEP-URE-2024-02-26 (Urban and Real Estate Economics)
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