Indeewara PereraPhoto of Indeewara Perera

Lecturer in Economics

9 Mappin Street
S1 4DT, UK

Tel: (+44) (0)114 222 5573



Indeewara Perera is a lecturer of Econometrics in the Department of Economics. Prior to joining the University of Sheffield Indeewara was a Research Fellow of Statistics in the Department of Econometrics and Business Statistics at Monash University, Australia. He has previously held academic positions in the Department of Statistics and Probability at the Michigan State University, as a visiting research associate, and at the University of Colombo, as an assistant lecturer in the Department of Mathematics. His academic qualifications include a Bachelor of Science (Honours) Degree in Mathematics from the University of Colombo, and a PhD in Mathematical Statistics from Monash University, Australia.

Dr Perera has received several awards, including two prizes for mathematics and physics and four gold medals in mathematics (for academic performance) from the University of Colombo, and an Early-Career Development Fellowship from Monash University. He has also been a recipient of the Faculty of Business and Economics Dean's Postgraduate Research Excellence Award from Monash University.


Current teaching responsibilities:

Research Summary

Indeewara’s research interests include model fitting, estimation, inference and forecasting in non-linear time series models, with special emphasis on statistical analysis of financial data. The concepts and tools used for weak convergence of stochastic processes in metric spaces, bootstrap methods, and goodness-of-fit tests play important roles in most of his research.

He has produced several papers in leading journals in the areas of econometric theory, mathematical statistics, and time series analysis. Four of his papers have been published in journals ranked A* by the 2013 Australian Business Deans Council (ABDC) Journal Quality List.

PhD Student Supervision

Indeewara is interested in supervising PhD students working in Econometrics (Theoretical or Applied) and Statistics. Specifically, he is interested in the following areas:

  • Developing new methods for model fitting, estimation, inference and forecasting in non-linear Econometric/Time-Series models, including ARCH/GARCH type models, Multiplicative Error models, and Panel Data models.

  • Bootstrap and resampling methods in Econometrics and Statistics; in particular, he is interested on nonstandard and massive data setups.