Measuring Time Inconsistency by Using Bank Account Data

Project Start:10/2016
Status:Completed
Researchers:Andrej Gill, Florian Hett
Category: Financial Intermediation, Experiment Center
Funded by:LOEWE

Present biased preferences are one of the cornerstones of behavioral economics. An important potential consequence of such preferences is that they induce time-inconsistent behavior in intertemporal decision problems. Arguably, one of the most important domains of intertemporal decision making is choosing the structure and financing of consumption patterns. This includes the timing of purchasing particular goods as well as the decision whether, how much, and in which form to save and invest money. From a theoretical perspective, individuals with present biased preferences should behave systematically different in these areas than individuals with “standard” intertemporal preferences that feature exponential discounting. This raises the question about the prevalence and severity of time-inconsistent behavior in this area.

 

Collaborating in this project with a fintech start-up based in Berlin, we can access detailed financial account data from individual households. The data set is transaction-based, e.g. it lists every transaction that takes place on an individual’s bank account. This allows identifying individuals whose consumption, financing, and savings behavior can be classified as present biased by looking for systematic differences in transaction patterns within a consumption period, e.g. a month. In particular, present bias corresponds to excessive shares of consumption spending in direct response to the reception of income within a short period. Identifying this kind of response to income flows explicitly requires transaction data detailed by area of consumption. Our project relies on exactly such data, therefore, allowing to assess the role of present bias in explaining deviations from optimal intertemporal consumption, financing, and savings behavior.

Related Policy Publications

AuthorTitlePublished
Andrej Gill,
Florian Hett,
Johannes Tischer
Measuring Time Inconsistency Using Financial Transaction Data
White Paper No. 55
2018
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