Economics Applied econometrics
Our research involves the development and use of a range of statistical methods to explore both microeconomic and macroeconomic problems. This include the development of new measures of the modern economy, development of econometric techniques (with a particular specialism in Bayesian econometrics), and work to develop approaches to producing more timely indicators of the macroeconomy through ‘nowcasting’.
Huber, F. Koop, G. Onorante, L., Pfarrhofer, M. & Schreiner, J. (2020). Nowcasting in a pandemic using non-parametric mixed frequency VARs. Journal of Econometrics.
Cross, J. L., Hou, C., & Poon, A. (2020). Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity. International Journal of Forecasting.
Huber, F., Koop, G., & Onorante, L. (2020). Inducing sparsity and shrinkage in time-varying parameter models. Journal of Business & Economic Statistics.
Koop, G., McIntyre, S., & Mitchell, J. (2020). UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting. Journal of the Royal Statistical Society: Series A.
Koop, G., Korobilis, D., & Pettenuzzo, D. (2019). Bayesian compressed vector autoregressions. Journal of Econometrics.
Chan, J. C., Eisenstat, E., & Koop, G. (2016). Large Bayesian VARMAs. Journal of Econometrics.
“Regional Nowcasting in the UK”, Office for National Statistics, Economic Statistics Centre of Excellence,
(Gary Koop, Stuart McIntyre, and James Mitchell (Warwick)).
- Gary Koop
- Stuart McIntyre
- Aubrey Poon