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Professor Michael Clements

Professor of Econometrics

PhD Programme Director

Michael Clements



ICMA Centre, Whiteknights Campus

Michael P Clements is Professor of Econometrics at the ICMA Centre, Henley Business School, University of Reading and an Associate member of the Institute for New Economic Thinking at the Oxford Martin School, University of Oxford. He obtained a DPhil in Econometrics from Nuffield College, University of Oxford in 1993, moved to Warwick University Economics Department as a Research Fellow in 1995, and became a full professor in 2007. He moved to Reading in 2013.

Mike’s interests are in the areas of time-series econometrics and forecasting, and he has published widely in academic journals on forecast evaluation, mixed-frequency data modelling, non-linear modelling and business cycle analysis, real-time modelling and forecasting, factor model forecasting, and the analysis of survey expectations.

Mike became a Journal of Applied Econometrics Distinguished Author in 2008.

He served as an editor of the International Journal of Forecasting between 2001 and 2012, and since standing down from this role has served as an associate editor.

He was elected an Honorary Fellow of the International Institute of Forecasters in 2014:

All of Mike’s publications are available at and recent Discussion Papers at

Reference: Clements, M. P. (2020) Are some forecasters' probability assessments of macro variables better than those of others? Econometrics, 8 (2). 16. ISSN 2225-1146 doi:
Reference: Clements, M. (2020) Individual forecaster perceptions of the persistence of shocks to GDP. Journal of Applied Econometrics. ISSN 1099-1255 (In Press)
Reference: Clements, M. (2020) Do survey joiners and leavers differ from regular participants? International Journal of Forecasting. ISSN 0169-2070 (In Press)

Financial Econometrics

Building on the material introduced in Quantitative Methods for Finance, this module covers a number of more advanced techniques that are relevant for financial applications, and in particular for modelling...

Module code: ICM204