We investigate identification of causal parameters in case-control and related studies. The odds ratio in the sample is our main estimand of interest and we articulate its relationship with causal parameters under various scenarios. It turns out that the odds ratio is generally a sharp upper...

One of the most powerful critiques of the use of randomised experiments in the social sciences is the possibility that individuals might react to the randomisation itself, thereby rendering the causal inference from the experiment irrelevant for policy purposes. In this paper we set out a...

This paper partially identifies population treatment effects in observational data under sample selection, without the benefit of random treatment assignment. Bounds are provided for both average and quantile population treatment effects, combining assumptions for the selected and the...

Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. Using income tax record data in combination with survey data is a potential approach to address the problem; we consider here the UK's pioneering 'SPI adjustment' method that implements...

Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. Using income tax record data in combination with survey data is a potential approach to address the problem; we consider here the UK's pioneering ‘SPI adjustment' method that implements...

In this paper we describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects such as large employer-employee data sets. This approach is computationally intensive but imposes minimum memory requirements. We also show that the...