Econometrics

The Econometrics programme research focuses on areas such as long memory time series, nonparametric and semiparametric methods, Edgeworth approximations, adaptive learning, diffusions, bootstrap, simulation methods, sample selection, identification, spatial econometrics, estimation of auction models, data linkage, limited dependent variable models and dynamic panel data.

The programme runs a seminar series and a joint workshop with the Department of Statistics at the LSE.

Featured

Understanding the average effect of microcredit

Rachael Meager explains why microcredit trials show only moderate variation in effects across different settings, suggesting that the average effects of these loans are small. Read more...

Order Selection and Inference with Long Memory Dependent Data

In empirical studies methods to select the order of a model are often invoked. The methods are based on the minimization of a criterion function. Abhimanyu Gupta and Javier Hidalgo propose an alternative way to compute the criterion by using the decomposition of the variance of the innovation errors in terms of its frequency components. Read more...

Reweighted nonparametric likelihood inference for linear functionals

This paper by Karun Adusumilli, Taisuke Otsu and Chen Qiuis, is concerned with inference on finite dimensional parameters in semiparametric moment condition models, where the moment functionals are linear with respect to unknown nuisance functions. Read more...

People

Javier Hidalgo

Javier Hidalgo is Tooke Professor of Economic Science and Statistics at the London School of Economics and joint director of the Econometrics programme hosted by STICERD. He has served as Co-Editor of Econometrica and the Journal of Econometrics and Econometric Theory. He is a Fellow of the British Academy, Fellow of the Institute of Mathematical Statistics, and Fellow of the Econometric Society.

Related

Events

STICERD Econometrics Seminars

Events

Joint Econometrics and Statistics Workshop

Papers

Econometrics Papers Series