Joint Econometrics and Statistics Workshop

Many of our seminars and public events this year will continue as in person or as hybrid (online and in person) events. Please check our website listings and Twitter feed @STICERD_LSE for updates.

Unless otherwise specified, in-person seminars are open to the public.

Those unable to join the seminars in-person are welcome to participate via zoom if the event is hybrid.

Econometrics and Statistics seminars are held on Fridays in term time at 12:00-13:00, ONLINE, unless specified otherwise.

Seminar organisers: Dr Tatiana Komarova and Dr Yunxiao Chen.

For further information please contact Lubala Chibwe, either by email: l.chibwe@lse.ac.uk.

Please use this link to subscribe or unsubscribe to the Econometrics and Statistics seminars mailing list (stats).

Wednesday 01 June 2022 14:00 - 15:00

Quadratic Prediction Methodology and Calibration of Prediction Intervals Based on Subsampling

We consider nonlinear prediction of a stationary time series using quadratic functions of the past data. We derive explicit formulae for the best quadratic predictor and its MSPE. We also give conditions under which the...Read more...

Soumen Lahiri (Washington University in St Louis)

This event is both online and in person

Leverhulme Library, COL 6.15, 6th Floor, Columbia House, LSE, 69 Aldwych, London WC2B 4RR

Friday 20 May 2022 12:00 - 13:00

CANCELLED

Julius Vainora (Cambridge University)

ONLINE

Friday 25 March 2022 12:00 - 13:00

Flexible Covariate Adjustments in Regression Discontinuity Designs

Empirical regression discontinuity (RD) studies often use covariates to increase the precision of their estimates. In this paper, we propose a novel class of estimators that use such covariate information more efficientl...Read more...

Claudia Noack (Oxford University)

ONLINE

Friday 18 February 2022 12:00 - 13:00

Matching for causal effects via multimarginal optimal transport

Please register to attend: https://lse.zoom.us/j/81404118660...Read more...

Florian Gunsilius (Michigan)

ONLINE

Friday 11 February 2022 12:00 - 13:00

Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders

Please register to attend: https://lse.zoom.us/j/82688220867...Read more...

Yuhao Wang (Tsinghua University)

ONLINE

Friday 07 May 2021 12:00 - 13:00

Learning Financial Network with Misspecification via Double Regularized GMM

Financial network analysis has gained significant attention recently. The identification, estimation and inference issues are intrinsically important in understanding the underlying network structure. We try to uncover t...Read more...

Weining Wang, joint with Victor Chernozhukov and Chen Huang

ONLINE

Friday 19 March 2021 12:00 - 13:00

The time-varying evolution of inflation risks

This paper develops Bayesian inference for time series quantile regressions with time-varying parameters (TVPs). We transform the TVP quantile regression into an equivalent high-dimensional quantile regression model and ...Read more...

Dimitris Korobilis (University of Glasgow)

ONLINE

Friday 05 March 2021 12:00 - 13:00

Censored Quantile Regression with Time Varying Covariates

We propose a class of quantile regression models for right censored failure time data with time varying covariates that requires only standard conditional independence. Using a quantile based transformation, a system of ...Read more...

Tony Sit (Chinese University of Hong Kong)

ONLINE

Friday 03 April 2020 12:00 - 13:00

TBC

David Kaplan (University of Wisconsin Madison)

ONLINE

Friday 06 March 2020 12:00 - 13:00

Optimal estimation of functionals of high-dimensional mean and covariance matrix

Motivated by portfolio allocation and linear discriminant analysis, we consider estimating a functional involving both the mean vector and covariance matrix. We study the minimax estimation of the functional in the high-...Read more...

Haolei Weng (Michigan State University)

ONLINE

Friday 21 February 2020 12:00 - 13:00

Bayesian Indirect Inference and the ABC of GMM

Approximate Bayesian Computation (ABC) is a Bayesian technique for estimation of parametric models where the likelihood is not available on closed form. We extend ABC in two directions: First, we demonstrate how one easi...Read more...

Dennis Kristensen (UCL)

ONLINE

Friday 07 February 2020 12:00 - 13:00

Asymptotically normal estimation in random graphs and random structures

Consider a large random structure -- a stochastic process on the line, a random graph, a random field on the grid -- and a function that depends only on a small part of the structure. Now use a family of transformations ...Read more...

Peter Orbanz (UCL)

ONLINE

Friday 13 December 2019 12:00 - 13:00