Python 64.6%
TeX 23.3%
HTML 11.6%
Makefile 0.5%
1% ==========================================================================2\section{Variable Definitions}3\label{sec:app_variables}4% ==========================================================================56Table~\ref{tab:app_variables} defines every variable used in the paper7and indicates whether it comes from a structured field of the scrape or8is parsed from the card title.910\begin{table}[!htbp]11\centering12\caption{Variable Definitions}13\label{tab:app_variables}14\begin{threeparttable}15\small16\begin{tabular}{p{4.1cm}p{8.3cm}l}17\toprule18Variable & Definition & Source \\19\midrule20\multicolumn{3}{l}{\textit{Dependent variable}} \\21$\ln p$ & Natural log of the displayed price (CAD), winsorised at the 1st/99th percentiles of the priced sample & field \\22\midrule23\multicolumn{3}{l}{\textit{Structural}} \\24$\ln$ bedrooms & Log of the bedroom count; studios recoded to one & field, title \\25$\ln(1+\text{bathrooms})$ & Log of one plus the bathroom count; zeros repaired from the title; half bath $= 0.5$ & field, title \\26$\ln$ guests & Log of the guest capacity (minimum one) & field \\27Shared bathroom & 1 if the title reads ``shared bath'' & title \\28Studio & 1 if the title reads ``Studio'' & title \\29Title category & Six classes of the 44 host-chosen labels (reference: Rental unit) & title \\30\midrule31\multicolumn{3}{l}{\textit{Presentation}} \\32$\ln(1+\text{amenities})$ & Log of one plus the number of amenities listed & field \\33$\ln(1+\text{photos})$ & Log of one plus the number of photos & field \\34Pets allowed & 1 if pets are allowed & field \\35\midrule36\multicolumn{3}{l}{\textit{Host and reputation}} \\37Superhost & 1 if the host holds the Superhost badge & field \\38Guest Favourite & 1 if the listing holds the Guest Favourite badge & field \\39$\ln(1+\text{reviews})$ & Log of one plus the number of reviews & field \\40Rated & 1 if a star rating is displayed (0 for ``New'' and unrated cards) & title \\41Rating $-$ 4.8 & Displayed rating minus 4.8, set to zero for unrated listings & title \\42\midrule43\multicolumn{3}{l}{\textit{Location}} \\44$\ln(1+\text{km to centre})$ & Log of one plus the great-circle distance (km) to the nearest of 22 reference municipalities & coordinates \\45$\ln(1+\text{listings within 1 km})$ & Log of one plus the number of other priced listings within 1~km & coordinates \\46Montreal & 1 if the municipality is Montreal & field \\47City / cell fixed effects & Indicator for the municipality (if $\geq 15$ listings) or for one of 25 $k$-means cells of the remaining listings & field, coordinates \\48\midrule49\multicolumn{3}{l}{\textit{Regime classification}} \\50$\hat p_i$ & Posterior probability of the stay-price regime from Equation~\eqref{eq:mixture} & estimated \\51\bottomrule52\end{tabular}53\begin{tablenotes}54\footnotesize55\item \textit{Notes:} ``Field'' denotes a structured field of the56scrape; ``title'' denotes a value parsed from the listing-card title.57The scraper's price category, rating category and composite quality58score are not used.59\end{tablenotes}60\end{threeparttable}61\end{table}6263% ==========================================================================64\section{Additional Results}65\label{sec:app_results}66% ==========================================================================6768Table~\ref{tab:app_stay_logit} reports a logistic regression of the69mixture classification on listing characteristics, estimated on the full70priced sample, which describes the profile of listings whose displayed71price is a stay price. Table~\ref{tab:app_vif} reports variance inflation72factors for the M4 regressors.7374\begin{table}[!htbp]75\centering76\caption{Which Listings Display a Stay Price? Logistic Regression of the Regime Classification}77\label{tab:app_stay_logit}78\begin{threeparttable}79\small80\input{../results/tables/rev_stay_logit.tex}81\begin{tablenotes}82\footnotesize83\item \textit{Notes:} Dependent variable: 1 if the listing is classified84in the stay regime ($\hat p_i \geq 0.5$). Robust (HC1) standard errors.85Average marginal effects are averaged over the sample. Reference title86category: Rental unit. ***, ** and * denote significance at the 1, 5 and8710\% levels.88\end{tablenotes}89\end{threeparttable}90\end{table}9192\begin{table}[!htbp]93\centering94\caption{Variance Inflation Factors, Specification M4}95\label{tab:app_vif}96\begin{threeparttable}97\small98\input{../results/tables/rev_vif.tex}99\begin{tablenotes}100\footnotesize101\item \textit{Notes:} Variance inflation factors computed on the M4102design matrix (analysis sample, $N = 2{,}480$). Values below 5 indicate103that collinearity among the capacity variables does not compromise the104precision of the estimates.105\end{tablenotes}106\end{threeparttable}107\end{table}108