Trust and Time Preference: Measuring a Causal Effect in a Random-Assignment Experiment

TL;DR

This paper explores the potential causal link between trust and patience (time preference) through a neuroscience-inspired model and an experimental Trust Game, but finds no significant effect of trust on time preference.

Contribution

It introduces a novel experimental design to manipulate trust levels and models the trust-time preference relationship via Bayesian inference and neuroscience mechanisms.

Findings

No significant effect of trust on time preference was observed.

Proposed an experimental method to manipulate trust levels.

Model links trust, neuroscience, and Bayesian inference in economic decision-making.

Abstract

Large amounts of evidence suggest that trust levels in a country are an important determinant of its macroeconomic growth. In this paper, we investigate one channel through which trust might support economic performance: through the levels of patience, also known as time preference in the economics literature. Following Gabaix and Laibson (2017), we first argue that time preference can be modelled as optimal Bayesian inference based on noisy signals about the future, so that it is affected by the perceived certainty of future outcomes. Drawing on neuroscience literature, we argue that the mechanism linking trust and patience could be facilitated by the neurotransmitter oxytocin. On the one hand, it is a neural correlate of trusting behavior. On the other, it has an impact on the brain's encoding of prediction error, and could therefore increase the perceived certainty of a neural representation of a future event. The relationship between trust and time preference is tested experimentally using the Trust Game. While the paper does not find a significant effect of trust on time preference or the levels of certainty, it proposes an experimental design that can successfully manipulate people's short-term levels of trust for experimental purposes.