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1\begin{table}[htbp]2\centering\footnotesize3\caption{Monte Carlo scenarios (60 months, 4 regions × 3 MRCs × 5 municipalities, log-normal municipality sizes)}\label{tab:mc_design}4\begin{threeparttable}56\begin{tabular}{lrrrrrr}7\toprule8Scenario & Drift (\\%/m) & $\tau$ prov/reg/MRC/mun (\\%) & Quality trend (\\%/m) & $\beta\_{fa}$ drift & $t$ d.f. / contamination & Sales scale \\9\midrule10baseline & 0.4 & 1.2/0.6/0.4/0.60 & +0.0 & +0.00 & 4.0 / 1\\% & 1.00 \\11turning point & 0.6 $\to$ -0.8 at m36 & 1.2/0.6/0.4/0.60 & +0.0 & +0.00 & 4.0 / 1\\% & 1.00 \\12flat quality up & 0.0 & 0.6/0.6/0.4/0.60 & +0.4 & +0.00 & 4.0 / 1\\% & 1.00 \\13rising quality down & 0.8 & 1.2/0.6/0.4/0.60 & -0.4 & +0.00 & 4.0 / 1\\% & 1.00 \\14drifting hedonics & 0.4 & 1.2/0.6/0.4/0.60 & +0.0 & +0.15 & 4.0 / 1\\% & 1.00 \\15heavy tails & 0.4 & 1.2/0.6/0.4/0.60 & +0.0 & +0.00 & 2.5 / 4\\% & 1.00 \\16sparse & 0.4 & 1.2/0.6/0.4/0.60 & +0.0 & +0.00 & 4.0 / 1\\% & 0.35 \\17no local dynamics & 0.4 & 1.2/0.1/0.1/0.05 & +0.0 & +0.00 & 4.0 / 1\\% & 1.00 \\18idiosyncratic towns & 0.4 & 1.2/0.2/0.4/2.00 & +0.0 & +0.00 & 4.0 / 1\\% & 1.00 \\19\bottomrule20\end{tabular}21\begin{tablenotes}\footnotesize\item Quality trend = monthly drift of the mean log floor area of sold homes (composition); $\beta_{fa}$ drift = change of the floor-area elasticity over the sample; sales scale multiplies expected monthly sales (baseline median $\approx$ 3.3 per municipality).\end{tablenotes}22\end{threeparttable}23\end{table}24