% Author: Simon-Pierre Boucher — contact@spboucher.ai
%
\begin{table}[!htbp]
\centering
\caption{Summary of robustness analyses.}
\label{tab:robustness_summary}
\small
\begin{adjustbox}{max width=\textwidth}
\begin{tabular}{llp{7.5cm}}
\toprule
\textbf{Test} & \textbf{Main Result Stable?} & \textbf{Notes} \\
\midrule
HC3 robust standard errors & Yes & Baseline inference method \\
Breusch-Pagan test & Yes & Heteroskedasticity confirmed (LM $= 768.0$); HC3 justified \\
Variance inflation factors & Yes (block level) & Substantial collinearity (mean VIF 17.2; 16/20 $>$ 10); joint inference unaffected, individual coefficients less precise \\
Bootstrap inference (1{,}000 rep.) & Yes & SE within 9\% of HC3 (15/20 within 5\%); CIs match \\
Trimmed prices (1st/99th pctile) & Yes & No sign reversals; all 16 significant dimensions remain significant \\
Quantile regression ($\tau = .25, .50, .75$) & Yes & Luxury premium increasing in price; discounts attenuate at upper quantiles \\
Lasso / elastic net selection & Yes (block level) & Sparse selection of 4 block representatives; semantic signal survives penalization \\
PCA comparison & Yes & PCA fits better ($\Delta R^2$ +0.070 vs.\ +0.044) but is uninterpretable; reference approach preferred for inference \\
\bottomrule
\end{tabular}
\end{adjustbox}
\end{table}
