Understanding the impact of travel on wellbeing: evidence for Great Britain during the pandemic
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- MAMATZAKIS, emmanuel & MAMATZAKIS, E, 2022. "Understanding the impact of travel on wellbeing: evidence for Great Britain during the pandemic," MPRA Paper 112974, University Library of Munich, Germany.
References listed on IDEAS
- Marta Bańbura, 2008.
"Large Bayesian VARs,"
2008 Meeting Papers
334, Society for Economic Dynamics.
- Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta, 2008. "Large Bayesian VARs," Working Paper Series 966, European Central Bank.
- Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
- Kock, Florian & Nørfelt, Astrid & Josiassen, Alexander & Assaf, A. George & Tsionas, Mike G., 2020. "Understanding the COVID-19 tourist psyche: The Evolutionary Tourism Paradigm," Annals of Tourism Research, Elsevier, vol. 85(C).
- Helmut Lütkepohl, 2005. "New Introduction to Multiple Time Series Analysis," Springer Books, Springer, number 978-3-540-27752-1, March.
- Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).
- Liu, Anyu & Kim, Yoo Ri & O'Connell, John Frankie, 2021. "COVID-19 and the aviation industry: The interrelationship between the spread of the COVID-19 pandemic and the frequency of flights on the EU market," Annals of Tourism Research, Elsevier, vol. 91(C).
- Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2020. "How did COVID-19 impact air transportation? A first peek through the lens of complex networks," Journal of Air Transport Management, Elsevier, vol. 89(C).
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006.
"Predicting volatility: getting the most out of return data sampled at different frequencies,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
- Dieppe, Alistair & van Roye, Björn & Legrand, Romain, 2016. "The BEAR toolbox," Working Paper Series 1934, European Central Bank.
- 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.
- Kadiyala, K Rao & Karlsson, Sune, 1997.
"Numerical Methods for Estimation and Inference in Bayesian VAR-Models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
- Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," SSE/EFI Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
- Karlsson, Sune, 2013.
"Forecasting with Bayesian Vector Autoregression,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897,
Elsevier.
- Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
- Anna Zabai, 2020. "How are household finances holding up against the Covid-19 shock?," BIS Bulletins 22, Bank for International Settlements.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
- Ghysels, Eric & Wright, Jonathan H., 2009.
"Forecasting Professional Forecasters,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
- Eric Ghysels & Jonathan H. Wright, 2006. "Forecasting professional forecasters," Finance and Economics Discussion Series 2006-10, Board of Governors of the Federal Reserve System (U.S.).
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- Lixiong Yang, 2022. "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, vol. 62(2), pages 533-551, February.
- Michael P. Clements & Ana Beatriz Galvão, 2007.
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- I0 - Health, Education, and Welfare - - General
- M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General
- Z0 - Other Special Topics - - General
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