\begin{tabular}{lccc}
\toprule
 & \textbf{OLS} & \textbf{SAR (GM\_Lag)} & \textbf{SEM (GM\_Error)} \\
Dep.\ var: & \multicolumn{3}{c}{\textit{log\_rent}} \\
\midrule
const & 7.1114*** & 6.0767*** & 7.0905*** \\
 & (0.0211) & (0.1514) & (0.0328) \\[4pt]
airbnb\_count\_500m & 0.0038*** & 0.0034*** & 0.0038*** \\
 & (0.0002) & (0.0002) & (0.0004) \\[4pt]
bedrooms & 0.1194*** & 0.1220*** & 0.1546*** \\
 & (0.0045) & (0.0032) & (0.0030) \\[4pt]
bathrooms & 0.2432*** & 0.2285*** & 0.1795*** \\
 & (0.0123) & (0.0063) & (0.0057) \\[4pt]
bt\_House & 0.1342*** & 0.1188*** & 0.1299*** \\
 & (0.0131) & (0.0101) & (0.0097) \\[4pt]
bt\_Row / Townhouse & 0.1782*** & 0.1604*** & 0.1447*** \\
 & (0.0359) & (0.0313) & (0.0296) \\[4pt]
W\_log\_rent &  & 0.1367*** &  \\
 &  & (0.0199) &  \\[4pt]
$\lambda$ (spatial error) &  &  & 0.5393 \\
\midrule
Observations & 7925 & 7925 & 7925 \\
R$^2$ / pseudo-R$^2$ & 0.5081 & 0.5503 & 0.4972 \\
\bottomrule
\end{tabular}
\parbox{\textwidth}{\footnotesize Standard errors in parentheses. SAR estimated via GM\_Lag; SEM via GM\_Error. $^{***}p<0.01$; $^{**}p<0.05$; $^{*}p<0.10$. City FE included but not shown.}
