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Published in: Empirical Economics 1/2020

07-01-2020

Economic forecasting: editors’ introduction

Authors: Robert M. Kunst, Martin Wagner

Published in: Empirical Economics | Issue 1/2020

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Excerpt

This special issue of Empirical Economics contains, with some exceptions, papers presented at the First Vienna Workshop on Economic Forecasting that took place at the Institute for Advanced Studies in Vienna in February 2018. The 2-day workshop, organized by Robert M. Kunst and Martin Wagner, drew much more attention than originally expected. This reflects the increased—respectively regained—importance of forecasting not only in practical terms but also as a research topic in the underlying scientific disciplines. Much of this growing interest may be also rooted in increased importance of forecasting in fields such as management science, marketing or supply chain management and may well be driven by methodological developments rooted in several disciplines that could be summarized under labels such as big data, machine learning and the like; the workshop itself had a narrower focus on macroeconomic forecasting. Even with the specific focus on macroeconomics, the papers span a wide portfolio of approaches and applications, ranging from statistical theory to data-driven research. As indicated in the beginning, some of the contributions in this special volume are not related to the workshop, as submission of manuscripts was open. …

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Literature
go back to reference Carriero A, Clark TE, Marcellino M (2015) Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility. J R Stat Soc Ser A 178:837–862CrossRef Carriero A, Clark TE, Marcellino M (2015) Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility. J R Stat Soc Ser A 178:837–862CrossRef
go back to reference deJong S, Kiers HAL (1992) Principal covariates regression: part I. Theory. Chemometr Intell Lab 14:155–164CrossRef deJong S, Kiers HAL (1992) Principal covariates regression: part I. Theory. Chemometr Intell Lab 14:155–164CrossRef
go back to reference Foroni C, Marcellino M, Schumacher C (2015) U-MIDAS: MIDAS regressions with unrestricted lag polynomials. J R Stat Soc Ser A 178:57–82CrossRef Foroni C, Marcellino M, Schumacher C (2015) U-MIDAS: MIDAS regressions with unrestricted lag polynomials. J R Stat Soc Ser A 178:57–82CrossRef
go back to reference Ghysels E, Santa-Clara P, Valkanov R (2004) The MIDAS touch: mixed data sampling regression models. CIRANO working papers 2004s-20, CIRANO, Montreal, Canada Ghysels E, Santa-Clara P, Valkanov R (2004) The MIDAS touch: mixed data sampling regression models. CIRANO working papers 2004s-20, CIRANO, Montreal, Canada
go back to reference Ghysels E, Santa-Clara P, Valkanov R (2006a) MIDAS regressions: further results and new directions. Econom Rev 26:53–90CrossRef Ghysels E, Santa-Clara P, Valkanov R (2006a) MIDAS regressions: further results and new directions. Econom Rev 26:53–90CrossRef
go back to reference Ghysels E, Santa-Clara P, Valkanov R (2006b) Predicting volatility: getting the most out of return data sampled at different frequencies. J Econom 131:59–95CrossRef Ghysels E, Santa-Clara P, Valkanov R (2006b) Predicting volatility: getting the most out of return data sampled at different frequencies. J Econom 131:59–95CrossRef
go back to reference Kauppi H, Saikkonen P (2008) Predicting U.S. recessions with dynamic binary response models. Rev Econ Stat 90:777–791CrossRef Kauppi H, Saikkonen P (2008) Predicting U.S. recessions with dynamic binary response models. Rev Econ Stat 90:777–791CrossRef
go back to reference Zhou Z, Xu Z, Wu WB (2010) Long-term prediction intervals of time series. IEEE Trans Inform Theory 56:1436–1446CrossRef Zhou Z, Xu Z, Wu WB (2010) Long-term prediction intervals of time series. IEEE Trans Inform Theory 56:1436–1446CrossRef
Metadata
Title
Economic forecasting: editors’ introduction
Authors
Robert M. Kunst
Martin Wagner
Publication date
07-01-2020
Publisher
Springer Berlin Heidelberg
Published in
Empirical Economics / Issue 1/2020
Print ISSN: 0377-7332
Electronic ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-019-01820-3

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