Data and code for: A Unified Model of Learning to Forecast

Principal Investigator(s): View help for Principal Investigator(s) George W. Evans, University of Oregon; Christopher Giorgio Gibbs, University of Sydney; Bruce McGough, University of Oregon

Version: View help for Version V1

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__pycache__			02/08/2024 06:32:PM
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__init__.py	text/x-python		02/08/2024 01:23:PM
models.py	text/x-python	4.4 KB	02/08/2024 01:23:PM
pages.py	text/x-python	1.8 KB	02/08/2024 01:23:PM
tests.py	text/x-python	249 bytes	02/08/2024 01:23:PM

Project Description

Summary: We propose a model of boundedly rational and heterogeneous expectations that unifies adaptive learning, k-level reasoning, and replicator dynamics. Level-0 forecasts evolve over time via adaptive learning. Agents revise over time their depth of reasoning in response to forecast errors, observed and counterfactual. The unified model makes sharp predictions for when and how fast markets converge in Learning-to-Forecast Experiments, including novel predictions for individual and market behavior in response to announced events.

This repository contains the raw data of the experiment to the test the unified model. It contains experimental data collected in the UNSW Sydney Business School BizLab in 2018 and in the University of Sydney School of Economics Experimental Lab in 2019. Subject played a learning-to-forecast game, where they were paid based on the accuracy of their forecasts. The subjects forecasted the price of a good traded in simple demand and supply dynamic market environment with a production lag. The market featured structural changes to the environment, which were fully known to subjects. How subjects' forecasts incorporated the information about the structural change is the main question of interest.

Scope of Project

Subject Terms: adaptive learning; level-k reasoning; behavioral macroeconomics; forward guidance; experiment

JEL Classification:
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      D84 Expectations; Speculations
      E31 Price Level; Inflation; Deflation
      E32 Business Fluctuations; Cycles
      E52 Monetary Policy
      E71 Macro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on the Macro Economy

Geographic Coverage: Australia

Data Type(s): experimental data

Methodology

Sampling: Laboratory experiment

Collection Mode(s): coded on-site observation

Related Publications

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Published Versions

V1 [2025-03-12]

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