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Previous empirical studies of job creation schemes in Germany have shown that the average effects for the participating individuals are negative. However, we find that this is not true for all strata of the population. Identifying individual characteristics that are responsible for the effect heterogeneity and using this information for a better allocation of individuals therefore bears some scope for improving programme efficiency. We present several stratification strategies and discuss the occurring effect heterogeneity. Our findings show that job creation schemes do neither harm nor improve the labour market chances for most of the groups. Exceptions are long-term unemployed men in West and long-term unemployed women in East and West Germany who benefit from participation in terms of higher employment rates. JEL: C13 , J68 , H43
Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Appleās introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.