% ============================================================================
\section{Data}
\label{sec:data}
% ============================================================================

\subsection{Source}

The data are a snapshot of active residential listings on Centris, the listing platform of the Qu\'ebec Professional Association of Real Estate Brokers, which aggregates brokered listings for the whole province. The snapshot files are dated 8 January 2026 (Unix timestamps of the extraction) and contain 42,481 listings in four product categories: 18,920 single-family houses, 9,347 condominium units, 4,619 multiplexes (two to six residential units) and 9,595 vacant parcels. Each record carries the asking price, structural attributes, lot and floor dimensions, geographic coordinates, the municipality, the type of parking and a free-text ``amenities nearby'' field completed by the listing broker. The snapshot is not redistributed; the repository documents its structure and the scripts that process it.

Two features of the source condition the analysis. First, the dependent variable is an asking price. Asking prices exceed eventual transaction prices on average and the gap varies with market conditions, with the seller's pricing strategy and with time on market \citep{horowitz1992role, knight2002listing, anglin2003tradeoff, haurin2010list}. The hedonic coefficients estimated on asking prices are therefore implicit prices of the listing schedule; they equal those of the transaction schedule only if the listing premium is, conditionally on the covariates, unrelated to the attributes of interest. Section~\ref{sec:identification} returns to this point. Second, the sample is a stock of listings at one date, not a flow of sales over a period. Properties that sell quickly are under-represented relative to properties that linger, and the listing stock in January is thinner than in spring; both features may differ across segments and price levels.

\subsection{Variables}

Table~\ref{tab:variables} defines the variables. Structural attributes are the number of bedrooms, the number of bathrooms (full bathrooms plus one half for each powder room), the number of storeys, the log of interior floor area in square feet, the log of lot area in square feet, the number of parking spaces and an indicator for a garage; the multiplex specification adds the number of units. Interior area is parsed from the floor-area measurement field (for condominiums, from the interior-size field when available) and lot area from the lot-size field, with conversion of square metres, acres, hectares and arpents to square feet. Location is represented by the log of the straight-line distance to downtown Montreal, computed by a flat-earth approximation from the coordinates and floored at 0.5 km, and by three regional indicators derived from the municipality name: the Montreal metropolitan area (the island, Laval and the North and South Shore suburbs), the Qu\'ebec City area (including L\'evis) and the remaining regions, with Gatineau (including Hull and Aylmer) as the omitted category in every segment.

\input{tables/variables}

The six amenity indicators equal one when the words ``Highway'', ``Hospital'', ``Park'', ``School'', ``Transit'' or ``Golf'' appear in the broker's amenities-nearby field. They are therefore binary, broker-reported and undistanced: they do not say how far the amenity is, how large or of what quality it is, nor whether ``transit'' refers to a metro station, a commuter-rail station or a bus stop. A broker who regards an amenity as relevant to the marketing of a property is more likely to mention it, so the indicators partly measure the broker's judgement about the market positioning of the listing. These limitations are discussed in Section~\ref{sec:limitations}; they argue for reading the estimates as capitalisation differentials associated with the broker's classification rather than with physical proximity.

\subsection{Sample construction}

Listings with a non-positive or missing asking price or without coordinates are dropped. Houses, condominiums and multiplexes require non-missing bedrooms and bathrooms; floor area is required when it is available for at least 30 percent of the segment (houses and condominiums, not multiplexes), and must then exceed 100 sq.\,ft.; lot area is required when it is available for at least 30 percent of the segment (all three) and is winsorised at its 99th percentile; storeys are imputed at the segment median and parking spaces at zero when missing. Vacant parcels require a lot area above 10 sq.\,ft. The log asking price and, where present, the log floor area and log lot area are then trimmed at their 0.5th and 99.5th percentiles. Table~\ref{tab:sample} reports the resulting estimation samples: 6,250 houses, 1,031 condominiums, 3,755 multiplexes and 9,239 parcels, a total of 20,275 listings. The retention rate is lowest for condominiums (11 percent), because interior area is missing for most condominium listings in the snapshot. This selection is not innocuous: a condominium listing that reports its interior area may differ systematically from one that does not, and the condominium estimates should be read as conditional on that reporting.

\input{tables/sample}

\subsection{Descriptive statistics}

Table~\ref{tab:descriptive} reports the prevalence of each amenity indicator and the regional composition of the four samples; the median asking prices are \$579,000 for houses, \$425,000 for condominiums, \$799,000 for multiplexes and \$150,000 for parcels. Amenity mentions are most frequent for condominiums (transit 73 percent, park 81 percent, school 83 percent) and multiplexes, and least frequent for vacant land (transit 8 percent), which reflects the urban location of the former and the peripheral location of the latter. The regional composition differs markedly across segments: 70 percent of the houses, 70 percent of the condominiums, 44 percent of the multiplexes and 89 percent of the parcels lie outside the three metropolitan areas, and the Montreal area accounts for 47 percent of the multiplexes but only 19 percent of the houses. Median asking prices in the Montreal area are higher than elsewhere in every segment (\$868,942 against \$520,000 for houses in the other regions; \$1,049,000 against \$525,000 for multiplexes). The amenity indicators are thus correlated with the regional and distance variables, and their coefficients must be read conditionally on those controls. The preserved log of the estimation run does not record the moments of the structural variables (bedrooms, bathrooms, areas); they are therefore not tabulated here, and Appendix~\ref{app:audit} lists them among the outputs to be restored when the pipeline is re-run.

\input{tables/descriptive}