Professor Dimitris Korobilis

  • Professor of Econometrics (Economics)

telephone: +44 (0)141 330 2000 (ext. 0635)
email: Dimitris.Korobilis@glasgow.ac.uk

Adam Smith Business School, Room 405A, Gilbert Scott Building (West Quadrangle), G12 8QQ, Glasgow

Import to contacts

ORCID iDhttps://orcid.org/0000-0001-9146-3008

Biography

Dimitris Korobilis (PhD Strathclyde, 2010) is Professor of Econometrics at the Adam Smith Business School. Before joining Glasgow he was Professor of Finance at Essex Business School, University of Essex.

He works in the area of applied statistical inference using economic and financial data. Recent research involves the development of machine learning algorithms for high-dimensional inference in macroeconomic models with large datasets; research that has been published in Journal of Econometrics and Journal of Business & Economic Statistics, among other journals. His models have been used extensively by policy-making institutions to monitor financial conditions (International Monetary Fund) and to forecast inflation (European Central Bank). He has been a consultant for major international institutions and government, and he delivers regularly specialized training in central banks on topics related to statistical inference that supports policy decision-making.

Dimitris is the director of the MSc in Data Analytics for Economics and Finance. He is also teaching at, and co-ordinating the annual ASBS Summer School in Empirical Macroeconomics. He is the alternate lead of the macroeconomics research cluster of the Adam Smith Business School. Finally, he is the organizer of the Econometrics Seminar Series.

Personal website

CV

Research interests

Dimitris is the alternate lead of the School's Macroeconomics research cluster.

Areas of expertise:

  • Macroeconometrics; Time-series Analysis; Forecasting
  • Bayesian statistics; Machine Learning; High-dimensional Models; Text Analytics
  • News and Business Cycles; Monetary policy; Macroeconomic Uncertainty

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2008
Number of items: 34.

2024

Korobilis, D. and Schröder, M. (2024) Monitoring multi-country macroeconomic risk: a quantile factor-augmented vector autoregressive (QFAVAR) approach. Journal of Econometrics, (Accepted for Publication)

2023

Koop, G. and Korobilis, D. (2023) Bayesian dynamic variable selection in high dimensions. International Economic Review, 64(3), pp. 1047-1074. (doi: 10.1111/iere.12623)

Korobilis, D. and Montoya-Blandón, S. (2023) Discussion of “multivariate dynamic modeling for Bayesian forecasting of business revenue”. Applied Stochastic Models in Business and Industry, 39(3), pp. 315-317. (doi: 10.1002/asmb.2753)

2022

Korobilis, D. (2022) A new algorithm for structural restrictions in Bayesian vector autoregressions. European Economic Review, 148, 104241. (doi: 10.1016/j.euroecorev.2022.104241)

Baumeister, C., Korobilis, D. and Lee, T. (2022) Energy markets and global economic conditions. Review of Economics and Statistics, 104(4), pp. 828-844. (doi: 10.1162/rest_a_00977)

Korobilis, D. and Shimizu, K. (2022) Bayesian approaches to shrinkage and sparse estimation. Foundations and Trends in Econometrics, 11(4), pp. 230-354. (doi: 10.1561/0800000041)

Gambetti, L., Görtz, C., Korobilis, D. , Tsoukalas, J. D. and Zanetti, F. (2022) The effect of news shocks and monetary policy. In: Dolado, J. J., Gambetti, L. and Matthes, C. (eds.) Essays in Honour of Fabio Canova (Advances in Econometrics, Vol. 44A). Emerald, pp. 139-164. ISBN 9781803826363 (doi: 10.1108/S0731-90532022000044A005)

2021

Korobilis, D. (2021) High-dimensional macroeconomic forecasting using message passing algorithms. Journal of Business and Economic Statistics, 39(2), pp. 493-504. (doi: 10.1080/07350015.2019.1677472)

2020

Korobilis, D. and Pettenuzzo, D. (2020) Machine Learning Econometrics: Bayesian algorithms and methods. In: Hamilton, J. H., Dixit, A., Edwards, S. and Judd, K. (eds.) Oxford Research Encyclopedia of Economics and Finance. Series: Oxford Research Encyclopedias. Oxford University Press. ISBN 9780190625979 (doi: 10.1093/acrefore/9780190625979.013.588)

Beckkmann, J., Koop, G., Korobilis, D. and Schuessler, R. A. (2020) Exchange rate predictability and dynamic Bayesian learning. Journal of Applied Econometrics, 35(4), pp. 410-421. (doi: 10.1002/jae.2761)

2019

Koop, G. and Korobilis, D. (2019) Forecasting with high-dimensional panel VARs. Oxford Bulletin of Economics and Statistics, 81(5), pp. 937-959. (doi: 10.1111/obes.12303)

Byrne, J. P., Cao, S. and Korobilis, D. (2019) Decomposing global yield curve co-movement. Journal of Banking and Finance, 106, pp. 500-513. (doi: 10.1016/j.jbankfin.2019.07.018)

Korobilis, D. and Pettenuzzo, D. (2019) Adaptive hierarchical priors for high-dimensional vector autoregressions. Journal of Econometrics, 212(1), pp. 241-271. (doi: 10.1016/j.jeconom.2019.04.029)

Koop, G., Korobilis, D. and Pettenuzzo, D. (2019) Bayesian compressed vector autoregressions. Journal of Econometrics, 210(1), pp. 135-154. (doi: 10.1016/j.jeconom.2018.11.009)

2018

Byrne, J. P., Korobilis, D. and Ribeiro, P. J. (2018) On the sources of uncertainty in exchange rate predictability. International Economic Review, 59(1), pp. 329-357. (doi: 10.1111/iere.12271)

2017

Byrne, J. P., Cao, S. and Korobilis, D. (2017) Forecasting the term structure of government bond yields in unstable environments. Journal of Empirical Finance, 44, pp. 209-225. (doi: 10.1016/j.jempfin.2017.09.004)

Korobilis, D. (2017) Quantile regression forecasts of inflation under model uncertainty. International Journal of Forecasting, 33(1), pp. 11-20. (doi: 10.1016/j.ijforecast.2016.07.005)

2016

Korobilis, D. (2016) Prior selection for panel vector autoregressions. Computational Statistics and Data Analysis, 101, pp. 110-120. (doi: 10.1016/j.csda.2016.02.011)

Byrne, J., Korobilis, D. and Ribeiro, P. J. (2016) Exchange rate predictability in a changing world. Journal of International Money and Finance, 62, pp. 1-24. (doi: 10.1016/j.jimonfin.2015.12.001)

Koop, G. and Korobilis, D. (2016) Model uncertainty in panel vector autoregressive models. European Economic Review, 81, pp. 115-131. (doi: 10.1016/j.euroecorev.2015.09.006)

2015

Bauwens, L., Koop, G., Korobilis, D. and Rombouts, J. V.K. (2015) The contribution of structural break models to forecasting macroeconomic series. Journal of Applied Econometrics, 30(4), pp. 596-620. (doi: 10.1002/jae.2387)

2014

Koop, G. and Korobilis, D. (2014) A new index of financial conditions. European Economic Review, 71, pp. 101-116. (doi: 10.1016/j.euroecorev.2014.07.002)

Belmonte, M. A. G., Koop, G. and Korobilis, D. (2014) Hierarchical shrinkage in time-varying parameter models. Journal of Forecasting, 33(1), pp. 80-94. (doi: 10.1002/for.2276)

2013

Korobilis, D. (2013) Assessing the transmission of monetary policy using time-varying parameter dynamic factor models. Oxford Bulletin of Economics and Statistics, 75(2), pp. 157-179. (doi: 10.1111/j.1468-0084.2011.00687.x)

Korobilis, D. (2013) Bayesian forecasting with highly correlated predictors. Economics Letters, 18(1), pp. 148-150. (doi: 10.1016/j.econlet.2012.10.003)

Bauwens, L. and Korobilis, D. (2013) Bayesian methods. In: Hashimzade, N. and Thornton, M.A. (eds.) Handbook of Empirical Methods in Macroeconomics. Edward Elgar Publishing: Cheltenham, pp. 363-380. ISBN 9780857931016

Koop, G. and Korobilis, D. (2013) Large Time-Varying Parameter VARs. Journal of Econometrics, 177(2), pp. 185-198. (doi: 10.1016/j.jeconom.2013.04.007)

Korobilis, D. (2013) Hierarchical shrinkage priors for dynamic regressions with many predictors. International Journal of Forecasting, 29(1), (doi: 10.1016/j.ijforecast.2012.05.006)

2012

Koop, G. and Korobilis, D. (2012) Forecasting inflation using dynamic model averaging. International Economic Review, 53(3), pp. 867-886. (doi: 10.1111/j.1468-2354.2012.00704.x)

Korobilis, D. and Gilmartin, M. (2012) On regional unemployment: an empirical examination of the determinants of geographical differentials in the UK. Scottish Journal of Political Economy, 59(2), pp. 179-195. (doi: 10.1111/j.1467-9485.2011.00575.x)

2011

Koop, G. and Korobilis, D. (2011) UK macroeconomic forecasting with many predictors: which models forecast best and when do they do so? Economic Modelling, 28(5), pp. 2307-2318. (doi: 10.1016/j.econmod.2011.04.008)

Korobilis, D. (2011) VAR forecasting using Bayesian variable selection. Journal of Applied Econometrics, 28(2), pp. 204-230. (doi: 10.1002/jae.1271)

2010

Koop, G. and Korobilis, D. (2010) Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics, 3(4), pp. 267-358. (doi: 10.1561/0800000013)

2008

Korobilis, D. (2008) Forecasting in vector autoregressions with many predictors. Advances in Econometrics(23), pp. 403-431. (doi: 10.1016/S0731-9053(08)23012-4)

This list was generated on Fri Apr 19 15:48:56 2024 BST.
Jump to: Articles | Book Sections
Number of items: 34.

Articles

Korobilis, D. and Schröder, M. (2024) Monitoring multi-country macroeconomic risk: a quantile factor-augmented vector autoregressive (QFAVAR) approach. Journal of Econometrics, (Accepted for Publication)

Koop, G. and Korobilis, D. (2023) Bayesian dynamic variable selection in high dimensions. International Economic Review, 64(3), pp. 1047-1074. (doi: 10.1111/iere.12623)

Korobilis, D. and Montoya-Blandón, S. (2023) Discussion of “multivariate dynamic modeling for Bayesian forecasting of business revenue”. Applied Stochastic Models in Business and Industry, 39(3), pp. 315-317. (doi: 10.1002/asmb.2753)

Korobilis, D. (2022) A new algorithm for structural restrictions in Bayesian vector autoregressions. European Economic Review, 148, 104241. (doi: 10.1016/j.euroecorev.2022.104241)

Baumeister, C., Korobilis, D. and Lee, T. (2022) Energy markets and global economic conditions. Review of Economics and Statistics, 104(4), pp. 828-844. (doi: 10.1162/rest_a_00977)

Korobilis, D. and Shimizu, K. (2022) Bayesian approaches to shrinkage and sparse estimation. Foundations and Trends in Econometrics, 11(4), pp. 230-354. (doi: 10.1561/0800000041)

Korobilis, D. (2021) High-dimensional macroeconomic forecasting using message passing algorithms. Journal of Business and Economic Statistics, 39(2), pp. 493-504. (doi: 10.1080/07350015.2019.1677472)

Beckkmann, J., Koop, G., Korobilis, D. and Schuessler, R. A. (2020) Exchange rate predictability and dynamic Bayesian learning. Journal of Applied Econometrics, 35(4), pp. 410-421. (doi: 10.1002/jae.2761)

Koop, G. and Korobilis, D. (2019) Forecasting with high-dimensional panel VARs. Oxford Bulletin of Economics and Statistics, 81(5), pp. 937-959. (doi: 10.1111/obes.12303)

Byrne, J. P., Cao, S. and Korobilis, D. (2019) Decomposing global yield curve co-movement. Journal of Banking and Finance, 106, pp. 500-513. (doi: 10.1016/j.jbankfin.2019.07.018)

Korobilis, D. and Pettenuzzo, D. (2019) Adaptive hierarchical priors for high-dimensional vector autoregressions. Journal of Econometrics, 212(1), pp. 241-271. (doi: 10.1016/j.jeconom.2019.04.029)

Koop, G., Korobilis, D. and Pettenuzzo, D. (2019) Bayesian compressed vector autoregressions. Journal of Econometrics, 210(1), pp. 135-154. (doi: 10.1016/j.jeconom.2018.11.009)

Byrne, J. P., Korobilis, D. and Ribeiro, P. J. (2018) On the sources of uncertainty in exchange rate predictability. International Economic Review, 59(1), pp. 329-357. (doi: 10.1111/iere.12271)

Byrne, J. P., Cao, S. and Korobilis, D. (2017) Forecasting the term structure of government bond yields in unstable environments. Journal of Empirical Finance, 44, pp. 209-225. (doi: 10.1016/j.jempfin.2017.09.004)

Korobilis, D. (2017) Quantile regression forecasts of inflation under model uncertainty. International Journal of Forecasting, 33(1), pp. 11-20. (doi: 10.1016/j.ijforecast.2016.07.005)

Korobilis, D. (2016) Prior selection for panel vector autoregressions. Computational Statistics and Data Analysis, 101, pp. 110-120. (doi: 10.1016/j.csda.2016.02.011)

Byrne, J., Korobilis, D. and Ribeiro, P. J. (2016) Exchange rate predictability in a changing world. Journal of International Money and Finance, 62, pp. 1-24. (doi: 10.1016/j.jimonfin.2015.12.001)

Koop, G. and Korobilis, D. (2016) Model uncertainty in panel vector autoregressive models. European Economic Review, 81, pp. 115-131. (doi: 10.1016/j.euroecorev.2015.09.006)

Bauwens, L., Koop, G., Korobilis, D. and Rombouts, J. V.K. (2015) The contribution of structural break models to forecasting macroeconomic series. Journal of Applied Econometrics, 30(4), pp. 596-620. (doi: 10.1002/jae.2387)

Koop, G. and Korobilis, D. (2014) A new index of financial conditions. European Economic Review, 71, pp. 101-116. (doi: 10.1016/j.euroecorev.2014.07.002)

Belmonte, M. A. G., Koop, G. and Korobilis, D. (2014) Hierarchical shrinkage in time-varying parameter models. Journal of Forecasting, 33(1), pp. 80-94. (doi: 10.1002/for.2276)

Korobilis, D. (2013) Assessing the transmission of monetary policy using time-varying parameter dynamic factor models. Oxford Bulletin of Economics and Statistics, 75(2), pp. 157-179. (doi: 10.1111/j.1468-0084.2011.00687.x)

Korobilis, D. (2013) Bayesian forecasting with highly correlated predictors. Economics Letters, 18(1), pp. 148-150. (doi: 10.1016/j.econlet.2012.10.003)

Koop, G. and Korobilis, D. (2013) Large Time-Varying Parameter VARs. Journal of Econometrics, 177(2), pp. 185-198. (doi: 10.1016/j.jeconom.2013.04.007)

Korobilis, D. (2013) Hierarchical shrinkage priors for dynamic regressions with many predictors. International Journal of Forecasting, 29(1), (doi: 10.1016/j.ijforecast.2012.05.006)

Koop, G. and Korobilis, D. (2012) Forecasting inflation using dynamic model averaging. International Economic Review, 53(3), pp. 867-886. (doi: 10.1111/j.1468-2354.2012.00704.x)

Korobilis, D. and Gilmartin, M. (2012) On regional unemployment: an empirical examination of the determinants of geographical differentials in the UK. Scottish Journal of Political Economy, 59(2), pp. 179-195. (doi: 10.1111/j.1467-9485.2011.00575.x)

Koop, G. and Korobilis, D. (2011) UK macroeconomic forecasting with many predictors: which models forecast best and when do they do so? Economic Modelling, 28(5), pp. 2307-2318. (doi: 10.1016/j.econmod.2011.04.008)

Korobilis, D. (2011) VAR forecasting using Bayesian variable selection. Journal of Applied Econometrics, 28(2), pp. 204-230. (doi: 10.1002/jae.1271)

Koop, G. and Korobilis, D. (2010) Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics, 3(4), pp. 267-358. (doi: 10.1561/0800000013)

Korobilis, D. (2008) Forecasting in vector autoregressions with many predictors. Advances in Econometrics(23), pp. 403-431. (doi: 10.1016/S0731-9053(08)23012-4)

Book Sections

Gambetti, L., Görtz, C., Korobilis, D. , Tsoukalas, J. D. and Zanetti, F. (2022) The effect of news shocks and monetary policy. In: Dolado, J. J., Gambetti, L. and Matthes, C. (eds.) Essays in Honour of Fabio Canova (Advances in Econometrics, Vol. 44A). Emerald, pp. 139-164. ISBN 9781803826363 (doi: 10.1108/S0731-90532022000044A005)

Korobilis, D. and Pettenuzzo, D. (2020) Machine Learning Econometrics: Bayesian algorithms and methods. In: Hamilton, J. H., Dixit, A., Edwards, S. and Judd, K. (eds.) Oxford Research Encyclopedia of Economics and Finance. Series: Oxford Research Encyclopedias. Oxford University Press. ISBN 9780190625979 (doi: 10.1093/acrefore/9780190625979.013.588)

Bauwens, L. and Korobilis, D. (2013) Bayesian methods. In: Hashimzade, N. and Thornton, M.A. (eds.) Handbook of Empirical Methods in Macroeconomics. Edward Elgar Publishing: Cheltenham, pp. 363-380. ISBN 9780857931016

This list was generated on Fri Apr 19 15:48:56 2024 BST.

Supervision

Teaching

 

ECON5079 Econometrics

ECON5129 Statistical Machine Learning

ECON5119 Applied Time Series and Forecasting

ECON5120 Bayesian Data Analysis

Additional information

 

IDEAS page
 

SSRN page
 

Scholar page

GitHub page

ORCID page

ResearchGate page

Profile photo of Professor Dimitris Korobilis, Professor of Econometrics