# Exponential Discounting under Partial Efficiency

## TL;DR

This paper introduces a new revealed preference approach to assess deviations from exponential discounting without parametric utility assumptions, using longitudinal scanner data to identify sources of non-exponential discounting behavior.

## Contribution

It develops a non-parametric, heterogeneity-friendly representation of exponential discounting and provides a practical method to detect departures from it.

## Key findings

- Identifies sources of non-exponential discounting in real data
- Offers a flexible, non-parametric testing framework
- Provides insights into discounting behavior heterogeneity

## Abstract

This paper derives a novel representation of the exponential discounting model that allows one to assess departures from the model via a measure of efficiency. The approach uses a revealed preference methodology that does not make any parametric assumption on the utility function and allows for unrestricted heterogeneity. The method is illustrated using longitudinal data from checkout scanners and gives insights into sources of departure from exponential discounting.