% Generated by code/make_tables.py from results/runs/table6\_cohort.csv, table6\_cohort\_regression.json. Do not edit by hand.
\begin{table}[H]
\centering\scriptsize
\setlength{\tabcolsep}{3pt}
\caption{Projects per issuer by index-membership cohort: the apparent S\&P~500 effect is a run and volume effect}\label{tab:cohort}
\begin{threeparttable}
\begin{adjustbox}{max width=\textwidth}
\begin{tabular}{lrrrrrrr}
\toprule
\multicolumn{8}{l}{\itshape Panel A: projects per issuer by cohort and by run of the mentions counted} \\
Cohort & Issuers & \multicolumn{1}{c}{\makecell{Projects\\(all mentions)}} & \multicolumn{1}{c}{\makecell{Per\\issuer}} & \multicolumn{1}{c}{\makecell{Projects\\(October mentions)}} & \multicolumn{1}{c}{\makecell{Per\\issuer}} & \multicolumn{1}{c}{\makecell{Ledger rows\\per issuer}} & \multicolumn{1}{c}{\makecell{October rows\\per issuer}} \\
\midrule
S\&P~500 $\cap$ Russell proxy & 491 & 27{,}382 & 55.8 & 11{,}738 & 25.1 & 552.4 & 242.7 \\
Russell proxy only & 1{,}992 & 93{,}333 & 46.9 & 93{,}333 & 46.9 & 423.8 & 423.8 \\
S\&P~500 only & 9 & 384 & 42.7 & 118 & 13.1 & 521.0 & 201.4 \\
\midrule
\multicolumn{8}{l}{\itshape Panel B: issuer-level OLS of projects on the S\&P~500 cohort dummy (HC1 standard errors in parentheses)} \\
Dependent variable & \multicolumn{2}{c}{S\&P~500 dummy} & \multicolumn{2}{c}{log(1 + ledger rows)} & $N$ & $R^2$ & \\
\midrule
Projects, all mentions & 8.84 & (1.62) & -- &  & 2{,}499 & 0.012 & \\
Projects, October mentions only & -22.98 & (1.20) & -- &  & 2{,}499 & 0.083 & \\
Projects, all mentions, volume control & -0.28 & (1.52) & 22.09 & (0.73) & 2{,}499 & 0.274 & \\
Projects, October mentions, volume control & -10.59 & (1.09) & 17.54 & (0.51) & 2{,}499 & 0.323 & \\
\bottomrule
\end{tabular}
\end{adjustbox}
\begin{tablenotes}\footnotesize
\item Panel A counts projects per issuer with all mentions and with only the mentions produced by the October run (a project is ``October'' when at least one of its mentions carries an October timestamp); S\&P~500 issuers were additionally extracted in the June run, whose 10-K items came from a different segmenter (Section~\ref{sec:architecture}). Panel B reports the coefficient on the S\&P~500 dummy from issuer-level OLS with heteroskedasticity-robust (HC1) standard errors; the sign flips from $+8.8$ to $-23.0$ projects per issuer when the run is held fixed and vanishes once the number of ledgered rows is controlled for. Economic magnitude: one log point of ledgered rows is associated with 22.1 additional projects. No causal reading is intended: the regressions describe the composition of the database, not disclosure behaviour.
\end{tablenotes}
\end{threeparttable}
\end{table}