We propose and examine a panel data model for isolating the effect of a treatment, taken once at baseline, from outcomes observed over subsequent time periods. In the model, the treatment intake and outcomes are assumed to be correlated, due to unobserved or unmeasured confounders. Intake is partly determined by a set of instrumental variables and the confounding on unobservables is modeled in a flexible way, varying both by time and treatment state. Covariate effects are assumed to be subject-specific and potentially correlated with other covariates. Estimation and inference is by Bayesian methods that are implemented by tuned Markov chain Monte Carlo methods. Because our analysis is based on the framework developed by Chib [2004. Analysis...
International audienceFor static panel data models that include endogenous time-invariant variables ...
Standard statistical analyses of randomized controlled trials with partially missing outcome data of...
In this thesis estimators for "fixed-effects" panel data sample selection models are discussed, most...
This paper proposes a new approach to identifying and estimating the time-varying average treatment ...
This paper considers identification of treatment effects when the outcome variables and covari-ates ...
We present Bayesian models for finding the longitudinal causal effects of a ran-domized two-arm trai...
We consider two approaches for isolating the effect of a treatment on an outcome of interest in sett...
This thesis explores a Bayesian approach for four types of panel data models with interactive fixed ...
When working with panel data, many researchers wish to estimate the direct effects of time-varying f...
Many applied settings in empirical economics require estimation of a large number of individual effe...
Much research in the social and health sciences aims to understand the causal relationship between a...
We show that two commonly employed estimation procedures to deal with correlated unobserved heteroge...
Identification and estimation of treatment effects is an important issue in many application fields,...
The method of instrumental variable (IV) analysis has been widely used in economics, epidemiology, a...
This paper proposes a new approach to estimate the time-varying average treatment effect using panel...
International audienceFor static panel data models that include endogenous time-invariant variables ...
Standard statistical analyses of randomized controlled trials with partially missing outcome data of...
In this thesis estimators for "fixed-effects" panel data sample selection models are discussed, most...
This paper proposes a new approach to identifying and estimating the time-varying average treatment ...
This paper considers identification of treatment effects when the outcome variables and covari-ates ...
We present Bayesian models for finding the longitudinal causal effects of a ran-domized two-arm trai...
We consider two approaches for isolating the effect of a treatment on an outcome of interest in sett...
This thesis explores a Bayesian approach for four types of panel data models with interactive fixed ...
When working with panel data, many researchers wish to estimate the direct effects of time-varying f...
Many applied settings in empirical economics require estimation of a large number of individual effe...
Much research in the social and health sciences aims to understand the causal relationship between a...
We show that two commonly employed estimation procedures to deal with correlated unobserved heteroge...
Identification and estimation of treatment effects is an important issue in many application fields,...
The method of instrumental variable (IV) analysis has been widely used in economics, epidemiology, a...
This paper proposes a new approach to estimate the time-varying average treatment effect using panel...
International audienceFor static panel data models that include endogenous time-invariant variables ...
Standard statistical analyses of randomized controlled trials with partially missing outcome data of...
In this thesis estimators for "fixed-effects" panel data sample selection models are discussed, most...