Phone: +44 20 7882 8826
Office hours: Friday 14:00-16:00
Research keywords: Econometrics and Quantitative Methods
Download CV: Liudas Giraitis [83 KB]
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.
Giraitis, L., Koul, H. and Surgailis, D. (2012). Large Sample Inference for Long memory Processes, pp. 587, Imperial College Press.
Giraitis, L., Kapetanios, G. and Yates, T. (2014). Inference on stochastic time-evolving coefficient models. Journal of Econometrics, 179, 46–65.
Giraitis, L., Kapetanios, G. and Price, S. (2013). Adaptive forecasting in the presence of recent and ongoing structural change. Journal of Econometrics, 177, 153–-170.
Giraitis, L. and 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.