# 🏇 Half a Million Prices, Twenty Models **UQO Working Paper No. 11** — *A Systematic Assessment of Hedonic Specifications and Estimation Methods for the Quebec Housing Market, 2021–2026* [-b31b1b?logo=latex&logoColor=white)](paper/main.pdf) [](requirements.txt) [](data/raw/README.md) [](src/wp11/models.py) [](scripts/) [](https://uqo.ca) [](mailto:contact@spboucher.ai) [](mailto:contact@spboucher.ai) > **TL;DR** — A controlled horse race of **20 hedonic models** on 514,212 Quebec sales > with assessor-grade structural attributes: 6 functional forms × time-FE ladder × > spatial-FE ladder × 6 estimation methods, all scored on the **same price-level > scoreboard** (Duan smearing / Box–Cox inversion) under **two holdouts** (random 80/20 > and forward-in-time). Functional form is second-order (±2 pp of MdAPE); spatial > controls are first-order (~10 pp) but overfit at ~1 km granularity; **gradient > boosting wins under random validation** (MdAPE ≈ 14.4% vs 16.5% for the best linear > model) — but under the forward-in-time split *every* model degrades and the ML > advantage **reverses** (splines 19.1% vs boosting 21.2%, identical R²_ln): random > cross-validation is the wrong experiment for valuation models. Implied price indices > and implicit-price profiles agree across forms far more than the accuracy gap suggests. --- ## 🎯 The four design axes | Axis | Models | Question | |---|---|---| | **A. Functional form** | linear, semi-log, log-log, Box–Cox (λ̂ by profile likelihood), quadratics, cubic splines | does curvature matter? | | **B. Time effects** | none / year / quarter / month FE | how fine must the time dummies be? | | **C. Spatial controls** | none / municipality / ~5.5 km grid / ~1.1 km grid FE | how fine can location FE get before overfitting? | | **D. Estimation method** | OLS, ridge (CV), random forest, gradient boosting (± coordinates), spatial k-NN comparables | what do the machines actually buy? | Every model: same sales, same attributes (floor area, lot, age, storeys, units, class, physical link), metrics on price levels (MdAPE, MAPE, RMSE_ln, R²_ln), municipality-clustered design, and **two splits** — random 80/20 and train < 2025 / test 2025–26 with carry-forward time effects. ## 🗂 Repository layout ``` wp11_uqo/ ├── data/raw/ # snapshot (NOT in git — see data/raw/README.md) ├── src/wp11/ # config, sample, models (the harness), plotstyle ├── scripts/ │ ├── 01_build_sample.py # 745,119 → 514,212 sales │ ├── 02_horserace.py # 20 models × 2 splits + Box–Cox profile │ ├── 03_extensions.py # indices, implicit-price profiles, learning curves, segments │ ├── 04_make_figures.py # 9 journal-calibre figures │ └── 05_make_tables.py # 7 LaTeX tables ├── results/{reproduced,tables}/ ├── figures/ └── paper/ # main.tex + sections/ + references.bib → main.pdf ``` ## 🚀 Quick start ```bash cd wp11_uqo python3 -m pip install -r requirements.txt # place the parquet snapshot in data/raw/ (not distributed), then: for s in scripts/0*.py; do python3 "$s"; done cd paper && make ``` Runtime ≈ 10 minutes on an Apple-silicon laptop (the boosting and forest fits dominate); peak RAM ≈ 8 GB. ## 📝 Citation ```bibtex @techreport{boucher2026horserace, author = {Boucher, Simon-Pierre}, title = {Half a Million Prices, Twenty Models: A Systematic Assessment of Hedonic Specifications and Estimation Methods for the Quebec Housing Market}, institution = {Universit\'e du Qu\'ebec en Outaouais, D\'epartement des sciences administratives}, type = {Working Paper}, number = {11}, year = {2026}, month = {August} } ``` ## 👤 Author & contact **Simon-Pierre Boucher** — Département des sciences administratives, Université du Québec en Outaouais (UQO), Gatineau, QC. 📧 [contact@spboucher.ai](mailto:contact@spboucher.ai)