Defying the LATE? Identification of local treatment effects when the instrument violates monotonicity

The instrumental variable method relies on a strong "no-defiers" condition, which requires that the instrument affect every subject's treatment decision in the same direction. This paper shows that "no-defiers" can be replaced by a weaker "compliers- defiers" condition, which requires that a subgroup of compliers have the same size and the same distribution of potential outcomes as defiers. This condition is necessary and sufficient for IV to capture causal effects for the remaining part of compliers. In many applications, "compliers-defiers" is a very weak condition. For instance, in Angrist & Evans (1998), 94% of DGPs compatible with the data satisfy "compliers-defiers", while 0% satisfy "no-defiers"

How to understand our willingness-to-pay to fight climate change? A choice experiment approach

We explore the willingness-to-pay (WTP) to fight climate change in a choice experiment. Since tree planting prevents climate change, subjects are offered to choose between receiving a high amount of money or receiving a lower amount of money plus participating to tree planting action. This allows us to get an individual interval of the WTP to prevent climate change. We also set the experiment to control for framing effects: we measure whether subjects WTP is higher not to prevent a tree planting action (negative framing) than to contribute to it (positive framing). Finally, we measure subjects' individual characteristics like altruism and risk aversion with a questionnaire, to understand the determinants of WTP. The results show that the WTP to prevent climate change is high: subjects are ready to give up half their gains to participate to a tree planting action. Women tend to have a higher WTP. We also find that both altruistic and self-interested motives can explain WTP. Surprisingly, their degree of knowledge of climate change related issues do not influence subjects WTP. Finally, when the choice is negatively phrased, WTP increases: subjects are ready to pay more not to make the number of trees planted decrease than to increase it. This suggests that negative eco-labelling might have a greater impact on consumer preferences than positive labels.willingness-to-pay, preferences elicitation, carbon-offset schemes, framing effect, climate change.

Workplace smoking ban effects in an heterogeneous smoking population

Many public policies, and especially health policies, are aimed at modifying individual behavior. This is particularly true of anti smoking policies. However, health behavior is highly heterogeneous, and so are individual responses to public policies such as taxes or restriction on use. We investigate the effect of a workplace smoking ban which took place in France in 2007. By its national aspect, the French reform offers a good case to study the effect of workplace smoking bans. Using original data on patients who consult tobacco cessation services, we show that the ban caused an increase in the demand for such services, and in the number of successful attempts to quit smoking. However, using survey data, we show that the ban had no measurable effect on overall prevalence in the general population. Models of quasi rational smoking behavior may offer an explanation for these two apparently contradictory findings.workplace smoking ban ; tobacco control ; smoking cessation ; impact evaluation

Fuzzy differences in differences

Difference in differences require that 0% of observations are treated in the control group and during period 0 (no "always takers") and 100% in the treatment group in period 1 (no "never takers"). Sometimes, the treatment rate increases more in the treatment than in the control group but there are never or always takers. This paper develops results to identify treatment effects in such settings. They only require one common trend assumption on the outcome of interest Y whereas the standard instrumental variable result also requires common trend on treatment D. I derive bounds for treatment effects which are tight when there are no or few always takers. This can be the case in applications considering the effect of an innovation, where by definition no observations are treated in period 0. I derive other bounds that are tight when the treatment rate does not change much between the two periods in the control group, which can be the case in applications considering the extension of a program to a group previously not eligible. I use my results to measure the efficacy of a new drug for smoking cessation.Difference in Differences ; Heterogeneous Treatment Effect ; Imperfect Compliance ; Partial Identification ; Smoking Cessation

Clustering and External Validity in Randomized Controlled Trials

In the literature studying randomized controlled trials (RCTs), it is often assumed that the potential outcomes of units participating in the experiment are deterministic. This assumption is unlikely to hold, as stochastic shocks may take place during the experiment. In this paper, we consider the case of an RCT with individual-level treatment assignment, and we allow for individual-level and cluster-level (e.g. village-level) shocks to affect the potential outcomes. We show that one can draw inference on two estimands: the ATE conditional on the realizations of the cluster-level shocks, using heteroskedasticity-robust standard errors; the ATE netted out of those shocks, using cluster-robust standard errors. By clustering, researchers can test if the treatment would still have had an effect, had the stochastic shocks that occurred during the experiment been different. Then, the decision to cluster or not depends on the level of external validity one would like to achieve

Two-way Fixed Effects Regressions with Several Treatments

We study regressions with period and group fixed effects and several treatment variables. Under a parallel trends assumption, the coefficient on each treatment identifies the sum of two terms. The first term is a weighted sum of the effect of that treatment in each group and period, with weights that may be negative and sum to one. The second term is a sum of the effects of the other treatments, with weights summing to zero. Accordingly, coefficients in those regressions are not robust to heterogeneous effects, and may be contaminated by the effect of other treatments. We propose alternative estimators.Comment: 25 pages. Compared to the previous version, we have added in particular Corollary 1, Section 4.2 on dynamic effects and an applicatio

Late Again with Defiers

We show that the Wald statistic still identifies a causal effect if instrument monotonicity is replaced by a weaker condition, which states that the potential propensities to be treated with or without the instrument should have the same distribution, conditional on potential outcomes. This holds for instance if the slippages between these potential propensities and the average propensity are independent of potential outcomes. In this framework, the Wald statistic identifies a LATE on a population which comprises both compliers and always takers