Subtopic Deep Dive
Housing Supply Elasticity
Research Guide
What is Housing Supply Elasticity?
Housing supply elasticity measures the responsiveness of new housing construction to changes in housing prices in a given market.
Empirical studies estimate metropolitan housing supply elasticities using regulatory indexes, construction costs, and land availability data. Glaeser, Gyourko, and Saks (2005) show low elasticities in high-regulation areas limit urban growth. Over 10 key papers since 2005 quantify supply constraints' role in price increases.
Why It Matters
Inelastic housing supply amplifies price volatility and reduces affordability in productive cities. Hsieh and Moretti (2019) estimate spatial misallocation from supply restrictions in New York and San Francisco cuts US GDP by 2.4-9.5%. Glaeser, Gyourko, and Saks (2005) link low elasticities to higher rents without city expansion. Quigley and Raphael (2005) demonstrate California's land-use regulations doubled housing costs relative to construction expenses.
Key Research Challenges
Measuring True Elasticity
Estimating supply elasticity requires isolating demand shocks from regulatory changes. Glaeser, Gyourko, and Saks (2005) use metropolitan permit data but note endogeneity issues. Long time-series data are scarce for precise identification.
Quantifying Regulation Impact
Regulatory indexes vary in coverage and subjectivity across studies. Quigley and Raphael (2005) analyze California rules but highlight inconsistent enforcement measurement. Cross-city comparisons face data gaps on zoning strictness.
Modeling Spatial Misallocation
Supply constraints cause labor misallocation across cities with productivity gaps. Hsieh and Moretti (2019) model aggregate GDP losses but assume uniform worker mobility. Glaeser and Berry (2005) note human capital divergence complicates estimates.
Essential Papers
The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment
Raj Chetty, Nathaniel Hendren, Lawrence F. Katz · 2016 · American Economic Review · 2.2K citations
The Moving to Opportunity (MTO) experiment offered randomly selected families housing vouchers to move from high-poverty housing projects to lower-poverty neighborhoods. We analyze MTO's impacts on...
The divergence of human capital levels across cities
Christopher R. Berry, Edward L. Glaeser · 2005 · Papers of the Regional Science Association · 651 citations
Housing Constraints and Spatial Misallocation
Chang‐Tai Hsieh, Enrico Moretti · 2019 · American Economic Journal Macroeconomics · 621 citations
We quantify the amount of spatial misallocation of labor across US cities and its aggregate costs. Misallocation arises because high productivity cities like New York and the San Francisco Bay Area...
Credit Supply and the Price of Housing
Giovanni Favara, Jean Imbs · 2015 · American Economic Review · 593 citations
An exogenous expansion in mortgage credit has significant effects on house prices. This finding is established using US branching deregulations between 1994 and 2005 as instruments for credit. Cred...
Sustainable Solutions for Green Financing and Investment in Renewable Energy Projects
Farhad Taghizadeh–Hesary, Naoyuki Yoshino · 2020 · Energies · 510 citations
The lack of long-term financing, the low rate of return, the existence of various risks, and the lack of capacity of market players are major challenges for the development of green energy projects...
Household Saving Behavior: The Role of Financial Literacy, Information, and Financial Education Programs
Annamaria Lusardi · 2008 · 480 citations
Individuals are increasingly in charge of their own financial security after retirement.But how well-equipped are individuals to make saving decisions; do they possess adequate financial literacy, ...
Urban growth and housing supply
Edward L. Glaeser, Joseph Gyourko, Raven E. Saks · 2005 · Journal of Economic Geography · 469 citations
Cities are physical structures, but the modern literature on urban economic development rarely acknowledges that fact. The elasticity of housing supply helps determine the extent to which increases...
Reading Guide
Foundational Papers
Start with Glaeser, Gyourko, Saks (2005) for core elasticity framework and metro estimates. Follow with Quigley and Raphael (2005) for California regulation evidence.
Recent Advances
Hsieh and Moretti (2019) for macroeconomic misallocation costs. Glaeser et al. (2017) on China supply booms as comparator.
Core Methods
Panel regressions of permits on prices (Glaeser 2005). Regulation indexes from surveys (Quigley 2005). Spatial equilibrium models (Hsieh 2019).
How PapersFlow Helps You Research Housing Supply Elasticity
Discover & Search
Research Agent uses searchPapers('housing supply elasticity Glaeser') to find Glaeser, Gyourko, and Saks (2005, 469 citations), then citationGraph reveals forward citations like Hsieh and Moretti (2019). exaSearch on 'metropolitan supply elasticity estimates' surfaces 50+ empirical papers. findSimilarPapers on Quigley and Raphael (2005) identifies California regulation studies.
Analyze & Verify
Analysis Agent runs readPaperContent on Glaeser, Gyourko, and Saks (2005) to extract elasticity regressions, then verifyResponse with CoVe checks claims against raw data. runPythonAnalysis replicates their supply elasticity models using NumPy/pandas on permit-price datasets. GRADE grading scores evidence strength for regulatory impact claims.
Synthesize & Write
Synthesis Agent detects gaps in elasticity estimates across US metros, flags contradictions between Glaeser et al. (2005) and Hsieh-Moretti (2019) on GDP losses. Writing Agent uses latexEditText to draft equations, latexSyncCitations for 20-paper bibliography, latexCompile for camera-ready review. exportMermaid visualizes supply-demand elasticity diagrams.
Use Cases
"Replicate Glaeser Gyourko Saks 2005 elasticity regression on new metro data"
Research Agent → searchPapers → Analysis Agent → runPythonAnalysis (pandas regression on permits/prices) → matplotlib plot of elasticities.
"Write LaTeX review of housing supply elasticity literature"
Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (Glaeser 2005 et al.) → latexCompile → PDF output.
"Find code for estimating housing supply elasticities from papers"
Research Agent → paperExtractUrls (Hsieh Moretti 2019) → paperFindGithubRepo → githubRepoInspect → runPythonAnalysis on shared elasticity scripts.
Automated Workflows
Deep Research workflow scans 50+ papers on 'housing supply elasticity', chains searchPapers → citationGraph → structured report with elasticity meta-analysis. DeepScan applies 7-step verification to Quigley-Raphael (2005) claims, using CoVe checkpoints on regulation-price links. Theorizer generates hypotheses on future elasticities from Glaeser et al. trends.
Frequently Asked Questions
What is housing supply elasticity?
Housing supply elasticity is the percentage change in housing stock divided by percentage change in price. Glaeser, Gyourko, and Saks (2005) estimate values below 1.0 in most US metros.
What methods estimate supply elasticity?
Methods include regression of building permits on lagged prices controlling for costs. Glaeser et al. (2005) use panel data; Hsieh and Moretti (2019) instrument with regulation indexes.
What are key papers on this topic?
Foundational: Glaeser, Gyourko, Saks (2005, 469 cites); Quigley, Raphael (2005, 424 cites). Recent: Hsieh, Moretti (2019, 621 cites).
What are open problems in supply elasticity research?
Challenges include dynamic effects of regulations and climate adaptation impacts. No consensus on national average elasticity post-2019.
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Part of the Housing Market and Economics Research Guide