\begin{table}[htbp]\centering
\caption{Descriptive lead--lag associations between a banner's weekly log price change and rivals' changes (Model C)}\label{tab:spillovers}
\small
\begin{adjustbox}{max width=\textwidth}
\begin{tabular}{lrrrrrrr}
\toprule
Rival set & N & $k=0$ & $k=1$ & $k=2$ & $k=3$ & lead 1 & lead 2 \\
\midrule
All rivals & 22\,213 & 0.037 (0.018) & 0.037 (0.012) & 0.015 (0.013) & 0.043 (0.015) & 0.009 (0.012) & 0.013 (0.015) \\
Same-company rivals & 21\,192 & 0.028 (0.018) & 0.042 (0.012) & 0.011 (0.013) & 0.034 (0.015) & 0.013 (0.012) & 0.015 (0.014) \\
Other-company rivals & 1\,784 & 0.081 (0.066) & -0.001 (0.048) & -0.057 (0.029) & 0.047 (0.060) & -0.108 (0.048) & -0.064 (0.049) \\
\bottomrule
\end{tabular}
\end{adjustbox}
\begin{minipage}{\textwidth}\footnotesize\vspace{2pt}
Dependent variable: $\Delta\log p$ of banner $r$ for product $i$ in week $w$; regressors: mean $\Delta\log p$ of the other banners in the match group at $w-k$ (lags) and $w+k$ (leads, placebo). Banner and week fixed effects; s.e. clustered by match group. Contemporaneous terms absorb common shocks and are not causal; a non-zero lead coefficient indicates timing noise or anticipation and is reported as a failed placebo.
\end{minipage}
\end{table}