README.markdown

In johnmyleswhite/BehavioralEconomics: Statistical models for behavioral economics

Introduction

The BehavioralEconomics package is a collection of statistical methods that will be useful to researchers in behavioral economics, particularly if they are modeling intertemporal choice data.

Current Models

At present, the package implements six models for intertemporal choice: Exponential discounting Hyperbolic discounting Quasi-hyperbolic discounting Generalized hyperbolic discounting Kable-Glimcher "as soon as possible" discounting Benhabib fixed cost discounting These are fit using JAGS through the rjags package. Priors are used that as considered "weakly informative".

Intertemporal Choice Models

Every intertemporal choice model assumes that your data is in the form of a data frame with five columns: X1: The monetary value of the first option T1: The time when the first option would be received X2: The monetary value of the second option T2: The time when the second option would be received * C: Binary variable indicating whether the second option (X2, T2) was chosen.

Future Work

In the future, there will be: Models of Decision-Making under Uncertainty * EU Theory * Prospect Theory Maximum Likelihood estimation Alternative priors for Bayesian estimation Simulation tools * Generic helper functions

johnmyleswhite/BehavioralEconomics documentation built on May 19, 2019, 5:17 p.m.