All corrections
1
Claim
hyperbolic discounting is necessary for inducing preference reversals in an agent
Correction

Hyperbolic discounting is not necessary for preference reversals. Economists generally treat dynamic inconsistency as arising from non-exponential discounting more broadly, and there are published models of dynamic preference reversal with non-hyperbolic discount functions.

Full reasoning

This overstates the role of hyperbolic discounting.

A standard review of the literature explains that in Strotz's framework, a non-exponential discount function induces dynamic inconsistency; hyperbolic discounting is just one important example, not a necessary condition. In other words, preference reversals are linked to non-exponential discounting in general, not uniquely to hyperbolic discounting.

There is also direct counterevidence to the claim of necessity: Chen, Fu, Wedge, and Zou (2019) explicitly present a "non-hyperbolic discount function that explains dynamic preference reversal." If a non-hyperbolic discount function can generate dynamic preference reversal, then hyperbolic discounting cannot be necessary for inducing preference reversals.

So the sentence should be weakened to something like: hyperbolic discounting is a common or influential model of preference reversal, but it is not required for preference reversals to occur.

2 sources
  • Measuring Time Preferences

    In Strotz’s framework, a non-exponential discount function induces preferences to be dynamically inconsistent ... Figure 2 plots the exponential discount function, along with two common alternatives: continuous-time hyperbolic discounting ... and discrete-time quasi-hyperbolic discounting.

  • Non-hyperbolic discounting and dynamic preference reversal

    In this paper, we present a time-varying and non-stationary but non-hyperbolic discount function that explains dynamic preference reversal. ... Hence, it is premature to interpret the existence of dynamic preference reversal behavior as definitive evidence of hyperbolic discounting.

Model: OPENAI_GPT_5 Prompt: v1.16.0