arXiv subjects

Christiern Rose

Publications and source records attributed to Christiern Rose.

5 recordsLinked to original sources

arXiv2022

Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments

We propose and implement an approach to inference in linear instrumental variables models which is simultaneously robust and computationally tractable. Inference is based on self-normalization of sample moment conditions, and allows for (but does not require) many (relative to the sample size), weak, potentially invalid or potentially endogenous instruments, as well as for many regressors and conditional heteroskedasticity. Our coverage results are uniform and can deliver a small sample guarantee. We develop a new computational approach based on semidefinite programming, which we show can equally be applied to rapidly invert existing tests (e.g,. AR, LM, CLR, etc.).

econ.EM↗

arXiv2022

Incorporating Financial Hardship in Measuring the Mental Health Impact of Housing Stress

Housing expenditure tends to be sticky and costly to adjust, and makes up a large proportion of household expenditure. Additionally, the loss of housing can have catastrophic consequences. These specific features of housing expenditure imply that housing stress could cause negative mental health impacts. This research investigates the effects of housing stress on mental health, contributing to the literature by nesting housing stress within a measure of financial hardship, thus improving robustness to omitted variables and creating a natural comparison group for matching. Fixed effects (FE) regressions and a difference-in-differences (DID) methodology are estimated utilising data from the Household Income and Labour Dynamics in Australia (HILDA) Survey. The results show that renters who are in housing stress have a significant decline in self-reported mental health, with those in prior financial hardship being more severely affected. In contrast, there is little to no evidence of housing stress impacting on owners with a mortgage. The results also suggest that the mental health impact of housing stress is more important than some, but not all, aspects of financial hardship.

econ.GN↗

arXiv2022

Identification of Peer Effects with Miss-specified Peer Groups: Missing Data and Group Uncertainty

We consider identification of peer effects under peer group miss-specification. Two leading cases are missing data and peer group uncertainty. Missing data can take the form of some individuals being entirely absent from the data. The researcher need not have any information on missing individuals and need not even know that they are missing. We show that peer effects are nevertheless identifiable under mild restrictions on the probabilities of observing individuals, and propose a GMM estimator to estimate the peer effects. In practice this means that the researcher need only have access to an individual level sample with group identifiers. Group uncertainty arises when the relevant peer group for the outcome under study is unknown. We show that peer effects are nevertheless identifiable if the candidate groups are nested within one another and propose a non-linear least squares estimator. We conduct a Monte-Carlo experiment to demonstrate our identification results and the performance of the proposed estimators, and apply our method to study peer effects in the career decisions of junior lawyers.

econ.EM↗

arXiv2021

Identification of Peer Effects using Panel Data

We provide new identification results for panel data models with peer effects operating through unobserved individual heterogeneity. The results apply for general network structures governing peer interactions and allow for correlated effects. Identification hinges on a conditional mean restriction requiring exogenous mobility of individuals between groups over time. We apply our method to surgeon-hospital-year data to study take-up of keyhole surgery for cancer, finding a positive effect of the average individual heterogeneity of other surgeons practicing in the same hospital

econ.EM↗

arXiv2021

High-dimensional instrumental variables regression and confidence sets

This article considers inference in linear instrumental variables models with many regressors, all of which could be endogenous. We propose the STIV estimator. Identification robust confidence sets are derived by solving linear programs. We present results on rates of convergence, variable selection, confidence sets which adapt to the sparsity, and analyze confidence bands for vectors of linear functions using bias correction. We also provide solutions to some instruments being endogenous. The application is to the EASI demand system.

math.ST↗