spb/wp5_uqo

1<!-- Author: Simon-Pierre Boucher — simon-pierre.boucher@uqo.ca -->2# REVIEW-REPORT — Editorial-board scientific review of UQO WP 5 (2026-10-17)34**Paper:** *Airbnb, Residential Rents, and Housing Market Pressure: A Hedonic and Spatial Econometric Analysis* (v1.0, May 2026, 51 pages → v1.1, October 2026, 59 pages).5**Protocol:** `Recherche-UQO/REVISION-MASTER-PROMPT.md` (8 phases) and `REVISION-PROTOCOLE.md`. Pre-revision state: git tag `pre-revision-20261017`, `docs/main_pre-revision-20261017.pdf`.6**Audit trail of every change:** `docs/CHANGELOG-REVISION.md`.78## 1. Summary verdict910The v1.0 manuscript was a competently executed cross-sectional hedonic study whose headline claim — a stable 0.4 % rent premium per nearby Airbnb listing, "strikingly close" to quasi-experimental magnitudes — did not survive the two checks that a referee in urban economics would ask for first: (i) location fixed effects finer than the city and (ii) standard errors that respect the spatial dependence of a buffer-based exposure variable. Both were feasible with the committed data (postal codes → forward sortation areas; coordinates → Conley HAC) and were run during this review. **With FSA fixed effects the coefficient falls from 0.0039 to 0.0008 and is not distinguishable from zero under Conley or FSA-clustered inference; with city fixed effects the HC1 standard error understates the spatial standard error by a factor of ≈ 3.** The paper has been rewritten around this result: the city-FE estimate is now presented as an upper bound, the association as predominantly between-neighbourhood, and the policy discussion toned down accordingly. Three further defects were corrected: a bimodal, partly total-stay Airbnb price field (which produced the v1.0 "superhost discount"), a collinear regressor reported with a pseudo-inverse coefficient in the Airbnb pricing model, and three misquoted benchmark magnitudes (Duso et al., Koster et al., Garcia-López et al.). The revised paper is honest, better identified in its claims, and better referenced; its publishable contribution is now *methodological-empirical* (what a cross-sectional STR–rent correlation is worth once neighbourhood FE and spatial inference are applied, documented for a new market) rather than a new positive estimate.1112## 2. Section-by-section diagnosis1314| Section | Strengths (v1.0) | Weaknesses / errors found | Action |15|---|---|---|---|16| Abstract | Clear, cautious wording | "approximately 5,000 Airbnb listings" (3,456 analysed; 30.9 % had no price); results stated as if robust; no mention of FE resolution or spatial SEs | Rewritten with correct N and the two-layer result |17| 1 Introduction | Good motivation, P2P framing, explicit endogeneity paragraph | Uncited facts ("over 11 million visitors", "historically low vacancy"); magnitude preview relied on a misread of Duso et al.; contributions overstated ("mutual corroboration") | Facts softened; preview rewritten; contributions reframed |18| 2 Literature | Thematic, 56 refs, mostly verified | 3 defective entries (Garcia-López title; Ke venue/author; Parmeter 2010 non-existent), 1 unverifiable (Agyeman 2020); misquoted magnitudes; no spatial-inference, identification-bounds or endogenous-amenity literature; Calder-Wang, Lee, Conley, Kelejian–Prucha 2007, Cameron–Miller, Bishop et al., Kuminoff–Pope, Oster, Almagro–Domínguez-Iino, Hidalgo et al., Fotheringham–Wong, Cocola-Gant–Gago absent | 12 added, 3 corrected, 1 removed; all 67 Crossref/DOI-verified; identification subsection added |19| 3 Data | Transparent cleaning, Haversine merge formalised | Airbnb price bimodality (26.5 % > $1,000 "per night") not noticed although the summary table showed mean $1,233 vs median $220; exposure distribution (44 % zeros at 500 m) described in one sentence; postal codes available but unused; nested/overlapping buffers not discussed; ML/1e samples (N = 4,370) not explained; scrape date, winter composition, Realtor.ca selection unmentioned | Price caveat + log-scale figure; exposure table; FSA description; buffer-overlap paragraph; limitations rewritten |20| 4 Methodology | Equations for all models | No formal W; SAR coefficient read as marginal effect; Model 2 "θ identified from variation absorbed by FE" is false (collinear); "153 cities" in clusters (252); no FSA FE; no spatial SE; "row-standardisation guarantees non-empty neighbourhoods" wrong (it is the KNN) | Added Eq. for FSA FE, hurdle/log forms, W, reduced form, LeSage–Pace impacts, Conley/cluster formulas; identification rewritten as "measurable" |21| 5 Results | Accurate reading of tables | SAR "attenuation" (0.0034 vs 0.0038) misread (total impact 0.0040); spatial table uses 15-city FE, not stated; superhost discount interpreted as composition; bedroom/bathroom % slightly off; quantile differences not tested; ML split leakage unaddressed | New §5.2 FSA, §5.3 inference, §5.4 impacts, §5.8 spatial CV; Model 2 restricted sample |22| 6 Robustness | Broad battery | Buffer figure duplicated (same PDF in §5 and §6); "Houses" subsample included townhouses; "153 clusters" | Fixed; accumulation-with-radius interpretation added |23| 7 Discussion | Candid about two disagreements | Magnitude comparison factually wrong (Berlin "7–13 €/month" is 1.3–2.4 % per m² per commercial listing; LA 2 % is 3 %; Barcelona 4.6–7 % conflated prices/rents); regulation description partly outdated; limitations list-like | Rewritten in standardised terms; new between/within subsection; regulation updated with footnoted official source; limitations by type |24| 8 Conclusion | Cautious | Repeated the "5,000", "mutual corroboration" claims | Rewritten |25| Appendices | Haversine, W, QR, ML | Several "available upon request"; correlation matrix generated but not included (raw underscores) | Correlation table included; Conley/impacts/projection documented |2627## 3. Methodology verdicts (master prompt §3)2829- **Specification justified:** yes for the hedonic form; the v1.0 reliance on city FE alone was not justified given available postal codes — now remedied (FSA FE).30- **Estimation assumptions explicit:** now yes (exogeneity failure channels, FE scope, SAR reduced form, Conley kernel).31- **Variables correctly defined:** yes after corrections (entire-home = property-type proxy, stated; composition variables undefined at zero exposure, stated; density = rescaled count).32- **Fixed effects appropriate:** city FE insufficient — the core finding of the review; FSA FE implemented; quantile/spatial models still use coarse city groups (stated as a limitation).33- **Spatial dependence defensible:** W now on projected coordinates (v1.0 used degrees → anisotropic neighbourhoods; effect on estimates marginal: ρ 0.137 → 0.134); impacts reported; SEM λ ≈ 0.54 motivates HAC SEs.34- **Standard errors:** v1.0 HC1 only (plus one city-cluster column that *tightened* SEs — a symptom of a dominant cluster, not a reassurance). Now HC1 / cluster-city / cluster-FSA / Conley 1–10 km; FSA-cluster and Conley agree (0.0007 vs HC1 0.0002).35- **Sample construction transparent:** now yes (attrition, matched-city N = 2,437, restricted N = 1,699, FSA singletons, ML N = 4,370).36- **Robustness addresses genuine threats:** v1.0 battery addressed stability, not identification; the FSA/Conley/spatial-CV analyses address the genuine threats.37- **Coefficient interpretation:** semi-elasticities now given exactly (100(e^β−1)); SAR impacts; log(1+count) elasticity; density rescaling.38- **Statistical vs economic significance:** distinguished ($8 vs $1.6 per listing at the median; 1 SD = 5.5 % vs 1.2 %).39- **Causal claims:** none; "effect/impact" reserved for the spatial-econometric sense.4041## 4. Literature (all entries verified via Crossref `api.crossref.org/works`, DOI resolution, or publisher/working-paper page)4243- **Corrected:** `garcia2020airbnb` (title → "Do short-term rental platforms affect housing markets? Evidence from Airbnb in Barcelona", DOI 10.1016/j.jue.2020.103278); `ke2017sharing` (→ Qing Ke, WebSci '17, pp. 131–139, DOI 10.1145/3091478.3091504; v1.0 gave a non-existent IJHM article); `parmeter2010applied` (non-existent) → `parmeter2007nonparametric` (JAE 22(3), 10.1002/jae.929); DOIs added to barron2021effect (10.1287/mksc.2020.1227), horn2017airbnb, wachsmuth2018airbnb, nieuwland2020regulating, palmquist2005property, rosen1974hedonic, koenker1978regression, zietz2008determinants, gyourko2005superstar, glaeser2005urban, saiz2010geographic, athey2019machine, mullainathan2017machine, tibshirani1996regression, breiman2001random, friedman2001greedy; sheppard2016airbnb given its WP number (2016-03).44- **Removed:** `agyeman2020airbnb` (no such Urban Studies article found in Crossref; only McLaren & Agyeman book chapters).45- **Added (12):** lee2016airbnb (HLPR 10(1) 229–253); calderwang2021distributional (SSRN 3908062, working paper — publication status unresolved, cited as such); conley1999gmm (10.1016/S0304-4076(98)00084-0); kelejian2007hac (10.1016/j.jeconom.2006.09.005); cameron2015practitioner (10.3368/jhr.50.2.317); bishop2020best (10.1093/reep/reaa001); kuminoff2014capitalization (10.1111/iere.12088); oster2019unobservable (10.1080/07350015.2016.1227711); almagro2025location (Econometrica 93(3), 10.3982/ECTA21394); hidalgo2024effect (JRS 64(3), 10.1111/jors.12685); fotheringham1991modifiable (10.1068/a231025); cocola2021airbnb (10.1177/0308518X19869012).46- **Facts re-verified against abstracts:** Horn & Merante (1 SD → 0.4 %, confirmed); Koster et al. published abstract (listings −50 %, prices −3 %, rents −3 %; WP version said 2 %); Duso et al. published abstract (0.23–0.37 units displaced, rent/m² +1.3–2.4 % per commercial listing); Garcia-López et al. (rents +1.9 %, transaction +4.6 %, posted +3.7 %; top decile rents +7 %); Combs et al. (17,000–43,000 entire homes; v1.0 "31,000" replaced by the published range).47- Count: 56 → **67** references, all cited, 0 BibTeX warnings.4849## 5. Results — inconsistencies found and resolved50511. Abstract/intro/conclusion "≈ 5,000 Airbnb listings" vs 3,456 analysed. 2. Model 2 column (2c) reported a coefficient (0.0307) on a regressor perfectly collinear with city FE. 3. Spatial table OLS column (15-city FE, β 0.0038) compared to Model 1c (252-city FE, 0.0039) as if the same specification. 4. "153 clusters" (actual 252). 5. "Houses" subsample included 48 townhouses (0.0067 → 0.0059 after exact match). 6. SAR coefficient read as attenuated marginal effect (total impact 0.0040). 7. Bedroom/bathroom percentages (11–13/23–30 → 12–14/26–30 exact). 8. Garcia-López "4.6–7 % prices in high-activity areas" conflated two outcomes. 9. Duso "7–13 € per month per listing" — not in the published paper. 10. Koster "2 %" → 3 %. 11. ML sample N = 4,370 (not 7,925) unstated. 12. Figure duplicated.5253## 6. Reanalyses executed (all from versioned scripts; see CHANGELOG §3 for timings)5455FSA fixed effects (6 specifications); HC1 / cluster-city / cluster-FSA / Conley (1, 2, 5, 10 km) SEs for the city-FE and FSA-FE estimates; SAR/SEM on projected-coordinate KNN weights with White-robust SAR SEs; LeSage–Pace impacts with simulated SEs; Model 2 without the collinear regressor and on the ≤ $1,000 subsample; random vs FSA-blocked 5-fold CV for the five ML models; exact-match building-type subsamples; exposure summary table; log-scale price histogram; correlation table.5657## 7. Analyses recommended, not executed5859- **Quantile regressions with FSA fixed effects** — 289 groups require penalised fixed-effects QR (Koenker 2004); not implemented, incidental-parameter concerns.60- **SAR/SEM with FSA fixed effects** — spreg GM estimators with ~290 dummies and instrument proliferation; feasible but outside the 30-minute budget for careful implementation.61- **Formal test of equality of quantile coefficients** (bootstrap); **wild cluster bootstrap** by city (Montreal dominance makes it the appropriate complement to Conley).62- **Oster (2019) bounds** — coefficient movements reported qualitatively (0.0020 → 0.0048 → 0.0039 → 0.0008); the formal δ is ill-suited because observables move the coefficient away from zero while FE move it toward zero.63- **Alternative neighbourhood units** (census tracts / dissemination areas) — would require a geocoding step with external boundary files (not downloaded per protocol).64- **Panel / event-study designs** around Quebec's registration regime and Montreal's 2025 seasonal rule — require repeated scrapes.65- **Host-resolved data**, room type, contract rents — data not available.6667## 8. Remaining limitations6869Single cross-section; asking rents from the agent-listed segment; winter scrape; bimodal price field; no room type / host ID; FSAs are delivery zones, not submarkets; spatial and quantile models use coarse city groups; Montreal = 59 % of the sample.7071## 9. Maturity for publication7273- **Target journals:** *Journal of Housing Economics*, *Regional Science and Urban Economics*, *Journal of Real Estate Research*, *Canadian Journal of Economics* (Canadian evidence), *Urban Studies*. Not JUE/REE at this stage (no causal identification).74- **Risks of rejection:** (i) "a null result after FE" without a causal design — mitigate by framing as the first Canadian listing-level evidence plus a methodological demonstration that cross-sectional STR–rent correlations are mostly between-neighbourhood (the paper now does this); (ii) data quality of the scraped Airbnb file (price field, no room type) — now disclosed, but a referee may ask for a re-scrape with room type and nightly price; (iii) representativeness of Realtor.ca asking rents; (iv) absence of FE in quantile/spatial models.75- **Verdict:** publishable as a careful descriptive-cum-methodological working paper after one more data pass (re-scrape with room type/host ID); the v1.1 text is internally consistent, all numbers are regenerated by the pipeline, and the claims are commensurate with the design.76