Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models
R Schunck - The Stata Journal, 2013 - journals.sagepub.com
Correlated random-effects (Mundlak, 1978, Econometrica 46: 69–85; Wooldridge, 2010,
Econometric Analysis of Cross Section and Panel Data [MIT Press]) and hybrid models …
Econometric Analysis of Cross Section and Panel Data [MIT Press]) and hybrid models …
Interactions in fixed effects regression models
M Giesselmann… - Sociological Methods & …, 2022 - journals.sagepub.com
An interaction in a fixed effects (FE) regression is usually specified by demeaning the
product term. However, algebraic transformations reveal that this strategy does not yield a …
product term. However, algebraic transformations reveal that this strategy does not yield a …
The effects of birth inputs on birthweight: evidence from quantile estimation on panel data
J Abrevaya, CM Dahl - Journal of Business & Economic Statistics, 2008 - Taylor & Francis
Unobserved heterogeneity among childbearing women makes it difficult to isolate the causal
effects of smoking and prenatal care on birth outcomes (such as birthweight). Whether a …
effects of smoking and prenatal care on birth outcomes (such as birthweight). Whether a …
Estimating conditional average treatment effects
We consider a functional parameter called the conditional average treatment effect (CATE),
designed to capture the heterogeneity of a treatment effect across subpopulations when the …
designed to capture the heterogeneity of a treatment effect across subpopulations when the …
Selection into identification in fixed effects models, with application to Head Start
Many papers use fixed effects (FE) to identify causal impacts. We document that when
treatment status only varies within some FE groups (for example, families, for family fixed …
treatment status only varies within some FE groups (for example, families, for family fixed …
Effect or treatment heterogeneity? Policy evaluation with aggregated and disaggregated treatments
The analysis of causal effects is at the heart of empirical research in economics, political
science, the biomedical sciences, and beyond. To evaluate and design policies …
science, the biomedical sciences, and beyond. To evaluate and design policies …
Nonlinear panel data estimation via quantile regressions
M Arellano, S Bonhomme - 2016 - academic.oup.com
We introduce a class of quantile regression estimators for short panels. Our framework
covers static and dynamic autoregressive models, models with general predetermined …
covers static and dynamic autoregressive models, models with general predetermined …
Identifying distributional characteristics in random coefficients panel data models
M Arellano, S Bonhomme - The Review of Economic Studies, 2012 - academic.oup.com
We study the identification of panel models with linear individual-specific coefficients when T
is fixed. We show identification of the variance of the effects under conditional …
is fixed. We show identification of the variance of the effects under conditional …
Nonparametric estimation of causal heterogeneity under high-dimensional confounding
M Zimmert, M Lechner - arXiv preprint arXiv:1908.08779, 2019 - arxiv.org
This paper considers the practically important case of nonparametrically estimating
heterogeneous average treatment effects that vary with a limited number of discrete and …
heterogeneous average treatment effects that vary with a limited number of discrete and …
Doubly robust uniform confidence band for the conditional average treatment effect function
In this paper, we propose a doubly robust method to estimate the heterogeneity of the
average treatment effect with respect to observed covariates of interest. We consider a …
average treatment effect with respect to observed covariates of interest. We consider a …