The group is interested in theoretical and methodological developments in econometrics and statistics, with particular emphasis on applications in macroeconomics and finance. The research interests of the group include estimation, inference and testing in non-linear models, fractional integration, semi-parametric and non-parametric methods, real time monitoring, explosive processes and forecasting. The group organises an annual workshop in econometrics, and aims to build research networks and partnerships both in the UK and internationally.
Research group leader
Workshop on contributions in theoretical and applied time series econometrics:
The Sheffield Time Series Econometrics Research Group will host their second annual workshop in May 2023 on “Contributions in theoretical and applied time series econometrics”, sponsored by the Royal Economic Society. The workshop will bring together leading researchers, from the UK and internationally, with expertise in a diverse set of research topics within the field of time series econometrics. Registration for the event is free and open to all. For more details visit this page.
Advances in Econometrics Workshop:
The Sheffield Time Series Econometrics Research Group held its inaugural Advances in Econometrics Workshop on 24 May 2022, sponsored by the Royal Economic Society. The workshop promoted recent advances in econometrics and their applications in finance and economics. The event included six presentations on a diverse set of research topics within the field, with the keynote speech given by Professor Frank Windmeijer (University of Oxford).
Indeewara Perera. and Silvapulle, M. J. (2022). Bootstrap specification tests for dynamic conditional distribution models. The Journal of Econometrics (in press), 1-22.
Chisiridis, K., Kostas Mouratidis and Panagiotidis, T. (2021). The North-South Divide, the Euro and the World. Journal of International Money and Finance 121. https://doi.org/10.1016/j.jimonfin.2021.102516
Indeewara Perera and Silvapulle, M. J. (2021). Bootstrap based probability forecasting in multiplicative error models. The Journal of Econometrics 221, 1-24.
Kanchana Nadarajah, Martin, G. M. and Poskitt, D. S. (2021). Optimal Bias-correction in the Log periodogram Estimation of the Fractional Parameter: A Jackknife Approach. Journal of Statistical Planning and Inference 211, 41-79.
Koul, H. L. and Indeewara Perera. (2021). A minimum distance lack-of-t test in a Markovian multiplicative error model. Journal of Statistical Theory and Practice 15, 1-22.
Montagnoli, A., Kostas Mouratidis and Whyte, K. (2021). Assessing the cyclical behaviour of bank capital buffers in a finance-augmented macro-economy. Journal of International Money and Finance 110. https://doi.org/10.1016/j.jimonfin.2020.102256
Harvey, D.I., Leybourne, S.J. and Emily Whitehouse (2020). Date-stamping multiple bubble regimes. Journal of Empirical Finance 58, 226-246.
Martin, G. M., Kanchana Nadarajah and Poskitt, D. S. (2020). Issues in the Estimation of Mis-specified Models of Fractionally Integrated Processes. The Journal of Econometrics 215(2), 559-573.
Emily Whitehouse (2019). Explosive asset price bubble detection with unknown bubble length and initial condition. Oxford Bulletin of Economics and Statistics 81, 20-41.
Harris, D., Martin, G., Indeewara Perera, and Poskitt, D. (2019). Construction and Visualization of Confidence Sets for Frequentist Distributional Forecasts. The Journal of Computational and Graphical Statistics 28, 92-104.
Harvey, D.I., Leybourne, S.J. and Emily Whitehouse (2018). Testing for a unit root against ESTAR stationarity. Studies in Nonlinear Dynamics and Econometrics 22(1).
Harvey, D.I., Leybourne, S.J. and Emily Whitehouse (2017). Forecast evaluation tests and negative long-run variance estimates in small samples. International Journal of Forecasting 33, 833-847.
Indeewara Perera and Koul, H. L. (2017). Fitting a two phase threshold multiplicative error model. The Journal of Econometrics 197, 348-367.
Indeewara Perera and Silvapulle, M. J. (2017). Specification tests for multiplicative error models. Econometric Theory 33, 413-438.
Indeewara Perera, Hidalgo, J., and Silvapulle, M. (2016). A Goodness-of-Fit Test for a Class of Autoregressive Conditional Duration Models. Econometric Reviews 35(6), 1111-1141.
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