Pragmatic cancer screening trials mimic real-world scenarios in which patients and doctors are the ultimate arbiters of treatment. Intention-to-screen (ITS) analyses of such trials maintain randomization-based apples-to-apples comparisons, but differential adherence (the failure of subjects...

Both instrumental variable (IV) estimation and mediation analysis are tools for causal inference. However, IV estimation has mostly developed in economics for causal inference from observational data. In contrast, mediation analysis has mostly developed in psychology, as a tool to empirically...

The measurement error problem in linear time series regression, with focus on the impact of error memory, modeled as nite-order MA processes, is considered. Three prototype models, two bivariate and one univariate ARMA, and ways of handling the problem by using instrumental variables (IVs) are...

In this paper, we investigate what can be learned about average counterfactual outcomes when it is assumed that treatment response functions are smooth. The smoothness conditions in this paper amount to assuming that the differences in average counterfactual outcomes are bounded under different...

This paper studies models of processes generating censored outcomes with endogenous explanatory variables and instrumental variable restrictions. Tobit-type left censoring at zero is the primary focus in the exposition. The models studied here are unrestrictive relative to others widely used in...

In this paper I revisit the interpretation of the linear instrumental variables (IV) estimand as a weighted average of conditional local average treatment effects (LATEs). I focus on a practically relevant situation in which additional covariates are required for identification while the...

Estimators that exploit an instrumental variable to correct for misclassification in a binary regressor typically assume that the misclassification rates are invariant across all values of the instrument. We show that this assumption is invalid in routine empirical settings. We derive a new...

This paper puts forward a new instrumental variables (IV) approach for linear panel datamodels with interactive effects in the error term and regressors. The instruments are transformed regressors and so it is not necessary to search for external instruments. The proposed method asymptotically...

Instrumental variables (IV) is an indispensable tool for establishing causal relationships between variables. Recent work has focused on improving bounds for cases when an ideal instrument does not exist. We leverage a principle, "Intransitivity in Correlations," related to an under-utilized...

We propose an instrumental variables (IV) estimator based on nonlinear (in param- eters) moment conditions for estimating linear dynamic panel data models and derive the large sample properties of the estimator. We assume that the only explanatory variable in the model is one lag of the...