spb/wp5_uqo Public

1\begin{tabular}{lccccc}2\toprule3 & \textbf{(R1)} & \textbf{(R2)} & \textbf{(R3)} & \textbf{(R4)} & \textbf{(R5)} \\4Dep.\ var: & \textit{log\_rent} & \textit{log\_rent} & \textit{log\_rent} & \textit{log\_rent} & \textit{log\_rent} \\5\midrule6Airbnb count (500m) & 0.0039*** & 0.0039*** & 0.0032*** &  & 0.0013*** \\7 & (0.0002) & (0.0001) & (0.0003) &  & (0.0003) \\[4pt]8log(1 + Airbnb count 500m) &  &  &  & 0.0484*** &  \\9 &  &  &  & (0.0025) &  \\[4pt]10Airbnb count (500m--1km ring) &  &  &  &  & 0.0018*** \\11 &  &  &  &  & (0.0002) \\[4pt]12Bedrooms & 0.1276*** & 0.1276*** & 0.1271*** & 0.1296*** & 0.1322*** \\13 & (0.0046) & (0.0043) & (0.0076) & (0.0046) & (0.0047) \\[4pt]14Bathrooms & 0.2287*** & 0.2287*** & 0.2103*** & 0.2274*** & 0.2246*** \\15 & (0.0126) & (0.0291) & (0.0202) & (0.0125) & (0.0125) \\[4pt]16Interior size (100 sq ft) &  &  & 0.0044*** &  &  \\17 &  &  & (0.0017) &  &  \\[4pt]18\midrule19Standard errors & HC1 & City cluster & HC1 & HC1 & HC1 \\20Building type \& city FE & Yes & Yes & Yes & Yes & Yes \\21Observations & 7,925 & 7,925 & 3,531 & 7,925 & 7,925 \\22R$^2$ & 0.5697 & 0.5697 & 0.6044 & 0.5726 & 0.5786 \\23\bottomrule24\end{tabular}25\parbox{\textwidth}{\footnotesize Standard errors in parentheses: HC1 except column (R2), which clusters by city. All columns control for bedrooms, bathrooms, building type, and city fixed effects; column (R3) adds interior size (per 100 sq ft) on the subsample reporting it. Column (R5) includes the 500m count and the count in the 500m--1km annulus jointly. $^{***}p<0.01$; $^{**}p<0.05$; $^{*}p<0.10$.}26