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UQO Working Paper No. 3 — Hedonic housing price models for the US: parametric, quantile, and machine-learning approaches.

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# UPGRADE_REPORT — Scholarly upgrade of the paper (2026-08-05)

Scope executed: Phase 1 (PAPER_REVIEW.md), Phase 2 (literature expansion, all references verified via OpenAlex), Phase 3 (section rewrites), Phase 4 (this report). No results, data, figures, or tables were changed. Paper version bumped 1.0 → 1.1. Compiled: paper/main.pdf, 61 pages (was 52), 0 errors, 0 undefined references, 69/69 bibliography entries cited.

Parameters chosen for the bracketed placeholders: field = housing / real estate economics (journal-article standard, e.g., Journal of Housing Economics / Real Estate Economics); reference target ≈ 60–65 (final: 69, from 37); length target ≈ +25–35 % prose (achieved: intro ×2.2, literature ×4, discussion ×2.7, conclusion ×2.5 in source lines; total document +9 pages ≈ +17 % because tables and figures are unchanged).


# 1. New references added (32 net: 33 added, 1 removed) — with justification

All entries verified one-by-one against OpenAlex (exact title, authors, venue, volume/pages, DOI). None were added from memory.

# Hedonic foundations & identification (7)

Key Reference Why added
waugh1928quality Waugh (1928), J. Farm Economics Historical origin of hedonic regression
ridker1967determinants Ridker & Henning (1967), REStat First property-value hedonic; anchors capitalization lineage
bartik1987estimation Bartik (1987), JPE Second-stage identification problem
kuminoff2010which Kuminoff, Parmeter & Pope (2010), JEEM Directly supports the FE-granularity exercise (region→state→ZIP3)
kuminoff2013new Kuminoff, Smith & Timmins (2013), JEL Modern survey of what hedonic estimates identify
bishop2020best Bishop et al. (2020), REEP Best-practice benchmark the paper now aligns itself with
hill2013hedonic (existing, re-cited) Was dropped by rewrite; restored in functional-form review

# Spatial econometrics (4)

Key Reference Why added
anselin1988spatial Anselin (1988), Kluwer book Canonical spatial-econometrics reference
dubin1998spatial Dubin (1998), J. Housing Econ. Why house prices are spatially autocorrelated
basu1998analysis Basu & Thibodeau (1998), JREFE Housing-specific residual autocorrelation benchmark for Moran's I
moran1950notes Moran (1950), Biometrika Primary source for the statistic used

# Quantile regression (3)

Key Reference Why added
koenker2001quantile Koenker & Hallock (2001), JEP Accessible methodological grounding
mcmillen2008changes McMillen (2008), JUE Coefficients-vs-characteristics evidence supporting QR relevance
waltl2019variation Waltl (2019), Real Estate Economics Recent comprehensive housing QR (Sydney), closest antecedent

# Listing prices & seller behavior (3)

Key Reference Why added
horowitz1992role Horowitz (1992), J. Applied Econometrics Theory of list price as commitment device
genesove2001loss Genesove & Mayer (2001), QJE Loss aversion → systematic asking-price behavior; grounds the central caveat
han2016role Han & Strange (2016), JUE Directing role of asking price in buyer search

# Capitalization of local public goods (3)

Key Reference Why added
black1999better Black (1999), QJE Boundary-discontinuity school valuation; disciplines the negative school-rating sign
bayer2007unified Bayer, Ferreira & McMillan (2007), JPE Sorting framework; same purpose
pivo2011walkability Pivo & Fisher (2011), Real Estate Economics Walkability premium; grounds Walk Score discussion

# ML in economics & valuation (6)

Key Reference Why added
varian2014big Varian (2014), JEP ML-for-econometrics canon
athey2019machine Athey & Imbens (2019), Annu. Rev. Econ. Canonical ŷ-vs-β̂ framing
breiman2001random Breiman (2001), Machine Learning Random Forest benchmark used in the paper
friedman2001greedy Friedman (2001), Annals of Statistics Gradient boosting primary source
park2015using Park & Bae (2015), ESWA Real ML-housing-prediction reference replacing a fabricated one (see §3)
steurer2021metrics Steurer, Hill & Pfeifer (2021), J. Property Research AVM evaluation-metrics literature; grounds deployment discussion

# Explainability (2)

Key Reference Why added
ribeiro2016should Ribeiro, Singh & Guestrin (2016), KDD Surrogate-explanation instability
rudin2019stop Rudin (2019), Nature MI Post-hoc-explanation caution; strengthens SHAP caveats

# Spatial validation (4)

Key Reference Why added
valavi2019blockcv Valavi et al. (2019), MEE Standard spatial-blocking methodology
ploton2020spatial Ploton et al. (2020), Nature Comms Dramatic random-vs-spatial validation gap, parallel to the paper's core result
wadoux2021spatial Wadoux et al. (2021), Ecological Modelling Dissenting view — spatial CV pessimistic for interpolation (see §4)
pace2020examining Pace & Hayunga (2020), JREFE Trees/forests extract spatial signal from hedonic residuals — closest antecedent to the ablation finding

# Climate risk (2)

Key Reference Why added
bernstein2019disaster Bernstein, Gustafson & Lewis (2019), JFE Sea-level-rise capitalization; supports "missing climate variables" limitation
murfin2020risk Murfin & Spiegel (2020), RFS Counterpoint within climate literature (weaker capitalization)

# 2. Corrections to existing entries (verified against OpenAlex)

  • bourassa2019machinebourassa2010predicting : year was wrong (2019 → 2010), pages 139–159 → 139–160, DOI added.
  • meyer2019importancemeyer2021predicting : year was wrong (2019 → 2021), DOI added.
  • mak2010quantile : confirmed; author initials completed; DOI added.

# 3. ⚠ Fabricated reference found and removed

chen2020housing — “Chen, Hu & Lin (2020), Housing price prediction using machine learning: A systematic review, Expert Systems with Applications, 145:113142” — does not exist. No such work in OpenAlex; neither candidate DOI resolves; no ESWA article with that article number matches. This is precisely the citation-hallucination pattern the verification pass was designed to catch. Replaced in the text by real literature (park2015using for ML housing prediction; bishop2020best/rosen1974hedonic for the SHAP-is-not-WTP claim).

# 4. Sections expanded and how

Section Before → After (source lines) Changes
Introduction 31 → ~140 Broader stakes (AVMs, assessment, underwriting); three-tensions framing; leakage contribution moved to center; four enumerated contributions tied to literature strands; practitioner/researcher implications; full roadmap
Literature 37 → ~240 Rebuilt as a 10-theme structured review (origins/identification, functional form, spatial, QR, listing prices (new), capitalization (new), ML/AVM, XAI, spatial validation incl. dissent (new), research gap) with per-strand gap statements
Data +2 paragraphs Listing-price caveat now grounded (Horowitz; Genesove-Mayer; Han-Strange); neighborhood variables tied to capitalization literature
Methodology +5 citation edits QR, boosting (Friedman), RF (Breiman), HC (White + MacKinnon-White), Moran (1950); new paragraph motivating dual validation incl. Wadoux dissent
Results +2 targeted notes School-rating and Walk Score counterintuitive signs now confronted with Black/Bayer and Pivo-Fisher (no numbers touched)
Discussion 44 → ~180 Each message now interprets against published magnitudes; agreements (Sirmans meta-analysis; Zietz/Mak/Waltl QR patterns; Ploton-style validation collapse; Campbell foreclosure discount) and divergences (school-rating sign vs. boundary designs) stated explicitly; Wadoux scope condition; synthesis subsection
Limitations +4 citation-grounded items Listing wedge, spatial models, validation-design duality, climate omission
Conclusion 19 → ~85 Literature-anchored summary; explicit methodological recommendation (report both validations); non-overselling final framing

# 5. Claims flagged for your verification

  1. Black (1999) magnitude — ✅ verified post-hoc against the QJE abstract: “parents pay 2.5% more for a 5% increase in test scores, about half the naive hedonic estimate.” Text corrected from “approximately 2%” to 2.5%.
  2. Campbell, Giglio & Pathak (2011) magnitude — ✅ verified against the AER abstract: average foreclosure discount of 27% on Massachusetts transactions. Text unchanged (accurate).
  3. “Neighborhood scores carry market-specific meaning” conjecture — ✅ now partially grounded: Duncan et al. (2011, IJERPH 8(11), 4160–4179, DOI 10.3390/ijerph8114160; verified via PubMed/MDPI) validate Walk Score across four US metropolitan areas and find its correspondence with walkability constructs varies by metro. Cited in the discussion; the mechanism remains flagged as “plausible rather than established” since we do not test it.
  4. Positioning sentence — ✅ validated by the author (2026-08-05): “To our knowledge, this framing has not previously been brought to bear on national-scale hedonic housing models” is kept as written.
  5. Waltl citation year — ✅ decided (author, 2026-08-05): cite as 2019, the print issue of Real Estate Economics 47(3), 723–756. (OpenAlex records the online-first year 2016.)

# 6. Literature potentially in tension with the paper's findings

  • Wadoux et al. (2021) argue spatial cross-validation is pessimistically biased when the estimand is map accuracy over a sampled region. Rather than ignoring it, the paper now engages it in three places (literature, methodology, limitations) and confines its own claims to the extrapolation setting. This is the most important "contradicting" reference; the engagement strengthens the argument but review it.
  • Murfin & Spiegel (2020) find limited sea-level-rise capitalization, in tension with Bernstein et al. (2019); both are cited to avoid one-sided support for the "climate variables matter" limitation.
  • Bayer, Ferreira & McMillan (2007) imply naive cross-sectional school coefficients confound neighbor characteristics — this supports the paper's caution but contradicts any residual temptation to interpret the school coefficient; the text now explicitly disclaims that interpretation.

# 7. Build status & typographic fixes

latexmk clean build: 60 pages, 0 errors, 0 undefined references/citations, 0 overfull vboxes, 70/70 entries cited, hyperlinks resolving. Version 1.1; title-page date frozen to August 5, 2026 for submission.

Two pre-existing typographic defects were found and fixed during the final QA pass: the main OLS table (Table 5) and the appendix full-OLS landscape table were taller than the page and were being clipped at the bottom (Panel F, fit statistics, and table notes were cut off in the rendered PDF). Table 5 is now split across two pages via \ContinuedFloat; the appendix table was compacted (scriptsize, tighter row spacing). No values were changed.