The Oxford Handbook of Economic Forecasting
- Clements, Michael P.(University of Warwick)Hendry, David F.(University of Oxford)Registered editor(s):
This Handbook provides up-to-date coverage of both new developments and well-established fields in the sphere of economic forecasting. The chapters are written by world experts in their respective fields, and provide authoritative yet accessible accounts of the key concepts, subject matter and techniques in a number of diverse but related areas. It covers the ways in which the availability of ever more plentiful data and computational power have been used in forecasting, either in terms of the frequency of observations, the number of variables, or the use of multiple data vintages. Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained; the volume provides explanations and critiques of these developments. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models, as well as models for handling data observed at mixed frequencies, high-frequency data, multiple data vintages, and methods for forecasting when there are structural breaks, and how breaks might be forecast. Also covered are areas which are less commonly associated with economic forecasting, such as climate change, health economics, long-horizon growth forecasting, and political elections. Econometric forecasting has important contributions to make in these areas, as well as their developments informing the mainstream. In the early 21st century, climate change and the forecasting of health expenditures and population are topics of pressing importance.
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|This book is provided by Oxford University Press in its series OUP Catalogue with number 9780195398649 and published in 2011.|
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- Martyna Marczak & Tommaso Proietti, 2014.
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- Marczak, Martyna & Proietti, Tommaso, 2014. "Outlier detection in structural time series models: The indicator saturation approach," FZID Discussion Papers 90-2014, University of Hohenheim, Center for Research on Innovation and Services (FZID).
- Martyna Marczak & Tommaso Proietti, 2014. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," CREATES Research Papers 2014-20, School of Economics and Management, University of Aarhus.
- Andrea CARRIERO & Todd E. CLARK & Massimiliano MARCELLINO, 2012.
"Common Drifting Volatility in Large Bayesian VARs,"
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ECO2012/08, European University Institute.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Paper 1206, Federal Reserve Bank of Cleveland.
- Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
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