In this paper, we investigate what can be learned about average counterfactual outcomes as well as average treatment effects when it is assumed that treatment response functions are smooth. We obtain a set of new partial identification results for both the average treatment response and the...

It is customary to assume that an indicator of a latent variable is driven by the latent variable and some random noise. In contrast, a background indicator is also systematically influenced by variables outside the structural model of interest. Background indicators deserve attention because in...

Swamy et al. (2015) argue that valid instruments cannot exist when a structural model is misspecified. This note shows that this is not true in general. In simple examples valid instruments can exist and can help to estimate parameters of interest.

Marketing applications offer many difficult and unique challenges in causal inference. In particular, targeted marketing activities, the arch-typical example of is search ads, can be difficult to evaluate using purely observational data. I review causal methods proposed in the recent...

We propose a new algorithm for estimating treatment effects in contexts where the exogenous variation comes from aggregate time-series shocks. Our estimator combines data-driven unit-level weights with a time-series model. We use the unit weights to control for unobserved aggregate confounders...

Bootstrap procedures based on instrumental variable (IV) estimates or t-statistics are generally invalid when the instruments are weak. The bootstrap may even fail when applied to identification-robust test statistics. For subvector inference based on the Anderson-Rubin (AR) statistic, Wang and...

This paper studies estimation and specification testing in threshold regression with endogeneity. Three key results differ from those in regular models. First, both the threshold point and the threshold effect parameters are shown to be identified without the need for instrumentation. Second, in...

The performance in finite samples is examined of inference obtained by variants of the Arellano-Bond and the Blundell-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross-sectional heteroskedasticity. By simulation the effects are...

We propose a procedure for testing simple hypotheses on a subset of the structural parameters in linear instrumental variables models. Our test is valid uniformly over a large class of distributions allowing for identification failure and heteroskedasticity. The large-sample distribution of our...