Data and Code for: Do Credit Conditions Move House Prices?

Principal Investigator(s):  View help for Principal Investigator(s) Daniel Greenwald, New York University; Adam Guren, Boston University

Version:  View help for Version V1

Name File Type Size Last Modified
  AggregateData 08/10/2025 04:17:PM
  Codebooks 08/10/2025 04:20:PM
  Empirical 08/10/2025 04:23:PM
  Microdata 08/10/2025 04:28:PM
  Model 08/10/2025 04:36:PM
  PaperFiguresTables 08/10/2025 04:42:PM
  Tools 08/10/2025 04:39:PM
LICENSE.txt text/plain 19.7 KB 08/10/2025 12:41:PM
ReadMe.pdf application/pdf 202.7 KB 08/11/2025 12:52:PM
requirements.txt text/plain 373 bytes 08/10/2025 08:25:AM

Project Citation: 

Greenwald, Daniel, and Guren, Adam. Data and Code for: Do Credit Conditions Move House Prices? Nashville, TN: American Economic Association [publisher], 2025. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-09-26. https://doi.org/10.3886/E225841V1

Project Description

Summary:  View help for Summary Abstract: Did credit drive the 2000s housing cycle? The existing literature's findings range from credit having no effect to credit explaining most of the cycle. We show that these disparate results hinge on the extent to which landlords absorb credit-driven demand, which depends on the degree of housing market segmentation. We develop a model that nests cases between the extremes of no segmentation and perfect segmentation typically considered, estimate an elasticity that pins down the degree of segmentation, and use it to calibrate our model. We find that credit standards played an important role, explaining 32% to 53% of the boom.
Funding Sources:  View help for Funding Sources National Science Foundation (SES-1623801)

Scope of Project

Subject Terms:  View help for Subject Terms house prices; mortgages; homeownership; credit; rental markets
JEL Classification:  View help for JEL Classification
      E44 Financial Markets and the Macroeconomy
      G51 Household Finance: Household Saving, Borrowing, Debt, and Wealth
      R31 Housing Supply and Markets
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 1995 – 2017
Collection Date(s):  View help for Collection Date(s) 2018 – 2025
Universe:  View help for Universe Core-Based Statistical Areas in the United States
Data Type(s):  View help for Data Type(s) aggregate data; program source code

Methodology

Data Source:  View help for Data Source CBRE Economic Advisors, 2018
CoreLogic, 2018
"Credit Induced Boom and Bust." Marco Di Maggo and Amir Kermani, 2017
"Credit Supply and Housing Speculation." Atif Mian and Amir Sufi, 2022
SmartyStreets, 2020, 2021
Federal Housing Finance Agency, 2018, 2023
Federal Reserve Board of Governors, 2021, 2023
"The Geographic Determinants of Housing Supply." Albert Saiz, 2010
Infutor, 2019
IPUMS National Historical Geographic Information System, 2022
U.S. Bureau of Economic Analysis, 2022
U.S. Census Bureau, 2017 - 2023
U.S. Department of Housing and Urban Development, 2020
Zillow, 2021

Unit(s) of Observation:  View help for Unit(s) of Observation US Core-Based Statistical Area
Geographic Unit:  View help for Geographic Unit US Core-Based Statistical Area

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Published Versions

V1 [2025-09-26]

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