Liudas GiraitisProfessorEmail: firstname.lastname@example.orgTelephone: +44 20 7882 8826Room Number: GC403Office Hours: Friday 2-4pmProfilePublicationsProfileResearch keywords: Econometrics and Quantitative Methods. Download CV: Liudas Giraitis [PDF 83KB] Liudas Giraitis is a Professor of Econometrics at Queen Mary University of London. He has completed extensive research on long memory and integrated I(d) models summarized in recent monograph “Large Sample Inference for Long memory Processes”. He has done substantial work on ARCH models, semiparametric inference, and is interested in development of comprehensive asymptotic theory for sums and quadratic forms of dependent variables and their statistical and econometric applications. In ongoing work, he is exploring time varying random coefficient models, their properties and estimation methods, forecasting under ongoing change approaches and heteroscadasticity and mean-variance constancy testing procedures. His research bridges the fields of econometrics, statistics and probability theory, with a substantial emphasis on time series analysis. He has published numerous articles in the leading statistical and econometric journals. Liudas has received his PhD in from Vilnius University. He has gained his research experience working at Heidelberg and Boston Universities and London School of Economics.ResearchPublications Giraitis L., Koul H., Surgailis D. (2012) "Large Sample Inference for Long memory Processes", Imperial College Press pp. 587. Giraitis L., Kapetanios G., Yates, T. (2014) "Inference on stochastic time-evolving coefficient models", Journal of Econometrics, 179, 46–65. Giraitis L., Kapetanios G., Price, S. (2013) "Adaptive forecasting in the presence of recent and ongoing structural change", Journal of Econometrics, 177, 153-170. Giraitis L., Phillips P.C.B. (2012) "Mean and autocovariance function estimation near the boundary of stationarity", Journal of Econometrics, 169, 166-178. Abadir K., Distaso W., Giraitis L. (2011) "An I(d) model with trend and cycles", Journal of Econometrics, 163, 186-199.