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his paper studies heterogeneity in the reaction to rank feedback. In a laboratory experiment, individuals take part in a series of dynamic real-effort contests with intermediate feedback. To solve the identification problem in estimating the causal effect of rank feedback on subsequent effort provision we implement a random multiplier in the first round of each contest. The realization of this multiplier then serves as a valid instrument for rank feedback. While rank feedback has a robust effect on subsequent effort provision on average, an explicit analysis of between-subject heterogeneity reveals that a substantial fraction of participants in fact react entirely opposite than the aggregated results indicate. We further show that this heterogeneity has consequences for overall outcomes, thereby arguing that heterogeneous sensitivities to rank feedback could have implications for the design of various policies in education and organizations.
Improving financial conditions of individuals requires an understanding of the mechanisms through which bad financial decision-making leads to worse financial outcomes. From a theoretical point of view, a key candidate inducing mistakes in financial decision-making are so called present-biased preferences, which are one of the cornerstones of behavioral economics. According to theory, present-biased households should behave systematically different when it comes to consumption and saving decisions, as they should be more prone to spending too much and saving too little.
In this policy letter we show how high frequency financial transaction data available in digitized form allows to precisely categorize individual financial-decision making to be present-biased or not. Using this categorization, we find that one out of five individuals in our sample exhibits present-bias and that this present-biased behavior is associated with a stronger use of overdrafts. As overdrafts represent a particularly expensive way of short-term borrowing, their systematic use can be interpreted as a measure of suboptimal financial-decision making. Overall, our results indicate that the combination of economic theory and Big Data is able to generate valuable insights with applications for policy makers and businesses alike.