Mental Models of Causal Structure in Economics and Psychology

TL;DR

This paper surveys how economic agents form and learn causal beliefs, connecting economic and cognitive science research, and discusses methodological challenges and applications across various economic fields.

Contribution

It provides an accessible overview of causal modeling in economics, integrating cognitive science insights and reviewing empirical and theoretical developments.

Findings

Individuals reason within fully parameterized causal structures.

People estimate parameters and learn causal structures over time.

Applications span microeconomics, macroeconomics, political economy, and business.

Abstract

A burgeoning literature in economics studies how people form beliefs about the causal structures linking economic variables, and what happens when those beliefs are mistaken. We survey this research and connect it to a rich literature in cognitive science. After providing an accessible introduction to causal Directed Acyclic Graphs, the dominant modeling approach, we review theory and evidence addressing three nested questions: how individuals reason within a fully parameterized causal structure, how they estimate its parameters, and how they learn such structures to begin with. We then discuss methodological challenges and review applications in microeconomics, macroeconomics, political economy, and business.