HSE Centre for Big Data in Economics and Finance research seminar: “Sparsity Tests for High Dimensional Time Series Regression”, Valentina Corradi (NYU Abu Dhabi)
HSE Centre for Big Data in Economics and Finance invites you to the research seminar on “Sparsity Tests for High Dimensional Time Series Regression” by Valentina Corradi (NYU Abu Dhabi), April 20, 2026, at 12:00 (Moscow time)
HSE Centre for Big Data in Economics and Finance invites you to the regular research seminar on April 20, 2026, at 12:00 (Moscow time) via Zoom.
Speaker: Valentina Corradi (NYU Abu Dhabi)
Topic: “Sparsity Tests for High Dimensional Time Series Regression”
Contact info: vc2718@nyu.edu
The speaker will present a new Hausman-type test for exact sparsity in high-dimensional linear time series models — including settings where the number of predictors may exceed the sample size. The null hypothesis assumes that at most k0 regressors have non-zero coefficients. Under the alternative, the upper bound on sparsity is larger than k0, and the talk will outline how to determine this ultimate upper bound using a sequential testing procedure.
The author establishes the first-order validity of block bootstrap critical values and assesses their finite-sample performance through simulations. The empirical part of the study uncovers evidence of very sparse models across a range of U.S. macroeconomic and financial target variables, even when using a large set of candidate predictors.
The HSE Centre for Big Data in Economics and Finance, established in 2025 at the Faculty of Economic Sciences, conducts fundamental and applied research in big data analysis, develops modern econometric and machine learning methods, and implements educational programs training next-generation specialists. Learn more about the Centre's activities on its official webpage.
To participate, please register on the Centre's seminar page where the Zoom link will be provided upon confirmation.
