_300_ ) reduced their body weight based on either intrinsic motivation, extrinsic motivation or a combination of the two. According to the motivation crowding theory, monetary rewards for maintaining the previously achieved body weight should be less effective for members of the control group than for members of the treatment groups of the first intervention. In the latter group, there is simply less intrinsic motivation that can be destroyed by additional extrinsic rewards.

Since the present analysis rests on data generated in the course of a randomized trial, simply comparing means across treatment and control groups in principle yields an unbiased estimate of the causal effect because randomization ensures that the different experimental groups differ only in terms of receiving the treatment. To address the sensitivity of our results with respect to random imbalance of individual characteristics and potential strategic behavior of participants to achieve their target, we rely on multivariate ordinary least squares regressions when considering the percentage change of body weight as the main outcome variable, and linear probability models for the binary indicator of whether the target weight has been achieved as alternative outcome variable. As covariates we include age, gender, month of recruitment for the experiment, and variables that relate to the weigh‐in at the pharmacies. Concerning the latter, we asked the pharmacists to indicate whether the participants’ last food intake was more than half an hour or more than two hours ago, whether they were wearing shoes (and if so whether these were heavy), a pullover, long trousers, and whether they attended the control weigh‐in within the specified time. An additional set of dummy variables captures whether participants attended the control weigh‐in prior to the specified date of measurement, within the right week (reference category), two weeks, three weeks or more than three weeks after this date. Variables that describe the condition at the control weigh‐in allow us to capture possible ways of how participants may influence their measured body weight other than through weight loss. This may be particularly relevant for the analysis of monetary rewards for maintaining a previously achieved target weight since, at the end of the second intervention, members of the treatment groups may behave strategically to achieve their target in order to increase their bonus.<sup>11</sup> Except for the variables related to the weigh‐in, all variables enter the analysis as pre‐ treatment values. Following a standard approach (e.g., Morris, 2006; Spenkuch, 2012), we deal with missing values in covariates by replacing them with zero and including additional dummy variables indicating missing values. Only the gender of the participants is imputed using predictions from a probit regression of the variable on relevant individual characteristics. Imputation is preferred to excluding observations with missing information because the latter

> 11 The same argument applies to the first intervention. Yet, here we focus on the effects after the weight‐ loss rewards have been removed, i.e., members of the treatment groups do not have incentives to behave strategically.

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