News

Event

Double Machine Learning for Static Panel Models with Instrumental variables: Method and Applications

Panel data applications often use instrumental variables (IV) to address endogeneity, but when instrument validity requires conditioning on high-dimensional covariates, flexible adjustment for confounding is essential and standard estimators like two-stage least squares (2SLS) break down. This paper proposes a novel Double Machine Learning (DML) estimator for static panel data...

Presented by: Annalivia Polselli

Venue: 2N2.4.16

News

4th UKMOD Fest – online event, Monday 20 October 2025

A gathering of developers, users and friends of UKMOD, our free tax-benefit microsimulation model for the UK and its constituent nations, to share experiences and ideas related to the model and its applications

Event

Are men’s preferences for couple equity misperceived? Evidence from six countries

Gender gaps in labor supply and household responsibilities persist. Using representative survey data from 24,000 respondents across six countries, this paper explores the actual and perceived preferences of men for couple equity. We document that in all six countries, the majority of men state they prefer an equitable division of...

Presented by: Teodora Boneva (University of Bonn)

Venue: Online: https://essex-university.zoom.us/j/96225051152

Event

Foodbank Use and Wellbeing: Evidence from a Nationally Representative Survey Data in the UK

Quantitative research on foodbanks is usually based on selected samples of the customers of a major foodbank chain. We make two contributions to the existing literature, using the three most recent consecutive cross-sections of the UK’s nationally representative Family Resources Survey. First, we model foodbank use as a function of...

Presented by: Tanisha Mittal (Lancaster University)

Venue: 2N2.4.16

Podcast

Studying for a PhD at ISER

Dr Cara Booker talks about opportunities for PhD study at ISER – the subjects you can research, how we use data and the career paths for our Post Docs.