The Costs of Housing Regulation: Evidence From Generative Regulatory Measurement

103 Pages Posted: 29 Nov 2023

See all articles by Alexander Bartik

Alexander Bartik

University of Illinois at Urbana-Champaign - Department of Economics

Arpit Gupta

NYU Stern School of Business

Daniel Milo

New York University

Date Written: September 14, 2024

Abstract

We present a novel method called "generative regulatory measurement'' that uses Large Language Models (LLMs) to interpret statutes and administrative documents. We demonstrate its effectiveness in analyzing municipal zoning codes, achieving 96% accuracy in binary classification tasks and a 0.92 correlation in predicting minimum lot sizes. Applying this method to U.S. zoning regulations, we establish five facts about American zoning: (1) Housing production disproportionately happens in unincorporated areas without municipal zoning codes. (2) Density in the form of multifamily apartments and small lot single family homes is broadly limited. (3) Zoning follows a monocentric pattern with regional variations, with suburban regulations particularly strict in the Northeast. (4) Housing regulations can be clustered into two main principal components, the first of which corresponds to housing complexity and can be interpreted as extracting value in high demand environments. (5) The second principal component associates with exclusionary zoning.

Keywords: housing regulation, zoning codes, large language models, natural language processing, artificial intelligence, municipal ordinances, retrieval augmented generation

JEL Classification: R52, R58, K11, O38, R31, C81

Suggested Citation

Bartik, Alexander and Gupta, Arpit and Milo, Daniel, The Costs of Housing Regulation: Evidence From Generative Regulatory Measurement (September 14, 2024). Available at SSRN: https://ssrn.com/abstract=4627587 or http://dx.doi.org/10.2139/ssrn.4627587

Alexander Bartik

University of Illinois at Urbana-Champaign - Department of Economics ( email )

410 David Kinley Hall
1407 W. Gregory
Urbana, IL 61801
United States

Arpit Gupta (Contact Author)

NYU Stern School of Business ( email )

Suite 9-160
New York, NY
United States

HOME PAGE: http://arpitgupta.info

Daniel Milo

New York University ( email )

New York
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
2,690
Abstract Views
7,441
Rank
10,591
PlumX Metrics