% Auto-generated by scripts/16_robustness.py — do not edit numbers.
\begin{table}[t]\centering\begin{adjustbox}{max width=\textwidth}
\begin{threeparttable}
\caption{Robustness of the market-wide null and the network channel}
\label{tab:robustness}
\small\begin{tabular}{lrrr}
\toprule
Sample / design & $\Delta\Delta$Breadth$_{5}$ & $\Delta\Delta$Breadth$_{30}$ & Network diff$_{5}$ \\
\midrule
Full sample & -1.04 (0.87) & -3.10 (0.99) & 64.02 (1.84) \\
Post-decimalization (2002+) & -1.03 (0.97) & -3.04 (1.25) & 65.81 (1.96) \\
Mid-day events (10:00–15:30) & -1.12 (1.04) & -3.48 (1.07) & 64.75 (2.03) \\
Ex announcement windows & -1.28 (0.96) & -3.50 (1.11) & 63.34 (1.92) \\
Calm years (ex 2008–09, 2020) & -1.35 (0.87) & -3.29 (1.00) & 63.62 (1.95) \\
Crisis years only & 2.69 (5.14) & -0.79 (6.32) & 68.06 (6.34) \\
Source $|z|\ge 8$ & 0.61 (1.23) & -1.66 (1.43) & 49.89 (2.09) \\
Source $|z|\ge 12$ & 1.12 (1.45) & 0.32 (1.78) & 33.94 (2.28) \\
Ex non-common tickers & -1.04 (0.95) & -3.08 (1.06) & 63.99 (1.87) \\
Month-cluster bootstrap & -1.04 (0.92) & --- & 64.02 (3.44) \\
Placebo events, neighbor diff & --- & --- & -2.71 (2.82) \\
\bottomrule\end{tabular}
\begin{tablenotes}[flushleft]\footnotesize
\item Notes: All entries $\times 10^{-4}$, day-block bootstrap SEs in
parentheses (500 reps; final row of the market-wide block uses
month-cluster resampling). $\Delta\Delta$Breadth = abnormal market-wide
breadth (real $-$ placebo, post $-$ pre). Network diff = neighbor $-$
non-neighbor abnormal breadth at $h{=}5$. `Placebo events' row reports
the neighbor differential among placebo events alone (falsification;
expected $\approx 0$).
\end{tablenotes}\end{threeparttable}
\end{adjustbox}\end{table}