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\begin{document}

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{\Huge\bfseries\color{headerblue} Investment Measures and Firm Growth}\\[1.5cm]
{\Large Statistical Tables and Empirical Results}\\[2cm]

\rule{0.8\textwidth}{1pt}\\[1.5cm]

{\large 
\begin{tabular}{rl}
\textbf{Sample Period:} & 1960--2024\\[0.3cm]
\textbf{Data Source:} & Compustat Annual Fundamentals\\[0.3cm]
\textbf{Observations:} & 393,062 firm-years\\[0.3cm]
\textbf{Last Updated:} & \today
\end{tabular}
}

\vfill

\rule{0.8\textwidth}{1pt}\\[0.5cm]
{\small\itshape All variables winsorized at the 1st and 99th percentiles.\\
Standard errors clustered by firm unless otherwise noted.}
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\clearpage

% Table of Contents
\tableofcontents
\clearpage

%==============================================================================
\section{Descriptive Statistics}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Summary Statistics---Full Sample (1960--2024)}
\label{tab:summary}
\small
\begin{tabular}{@{}l*{6}{S[table-format=-1.3]}@{}}
\toprule
\textbf{Variable} & {\textbf{Mean}} & {\textbf{Std.\ Dev.}} & {\textbf{P10}} & {\textbf{Median}} & {\textbf{P90}} & {\textbf{N}}\\
\midrule
\addlinespace[0.5em]
\multicolumn{7}{@{}l}{\textit{Panel A: Investment Measures}}\\
\addlinespace[0.3em]
\quad CAPX/Lagged Assets & 0.068 & 0.110 & 0.000 & 0.033 & 0.161 & {393,062}\\
\quad Cash Flow from Investing/Assets & -0.080 & 0.240 & -0.215 & -0.008 & 0.003 & {393,062}\\
\quad Asset Growth Rate & 0.246 & 0.894 & -0.192 & 0.065 & 0.597 & {391,793}\\
\quad R\&D/Assets & 0.052 & 0.098 & 0.000 & 0.000 & 0.157 & {393,062}\\
\quad Acquisitions/Assets & 0.024 & 0.072 & 0.000 & 0.000 & 0.068 & {393,062}\\
\addlinespace[0.8em]
\multicolumn{7}{@{}l}{\textit{Panel B: Profitability \& Performance}}\\
\addlinespace[0.3em]
\quad Return on Assets (NI/AT) & -0.142 & 0.728 & -0.372 & 0.023 & 0.115 & {390,535}\\
\quad Operating Margin & -0.089 & 0.654 & -0.312 & 0.089 & 0.198 & {388,241}\\
\quad Tobin's Q & 1.842 & 1.523 & 0.812 & 1.318 & 3.524 & {285,619}\\
\addlinespace[0.8em]
\multicolumn{7}{@{}l}{\textit{Panel C: Firm Characteristics}}\\
\addlinespace[0.3em]
\quad Log(Total Assets) & 5.024 & 2.823 & 1.538 & 4.980 & 8.622 & {391,390}\\
\quad Total Assets (\$M) & 2856.4 & 18542.1 & 4.7 & 145.5 & 5532.8 & {391,390}\\
\quad Leverage (Debt/Assets) & 0.306 & 0.397 & 0.000 & 0.226 & 0.627 & {386,545}\\
\quad Cash/Assets & 0.166 & 0.217 & 0.008 & 0.074 & 0.482 & {387,971}\\
\quad Market-to-Book & 4.025 & 8.254 & 0.665 & 1.777 & 7.527 & {141,454}\\
\quad Firm Age (years) & 14.8 & 12.6 & 2.0 & 11.0 & 32.0 & {393,062}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports summary statistics for the main variables used in the analysis. CAPX/AT is capital expenditure scaled by lagged total assets. Asset Growth is computed as $(AT_t - AT_{t-1})/AT_{t-1}$. Return on Assets (ROA) is net income divided by total assets. All continuous variables are winsorized at the 1st and 99th percentiles. P10, Median, and P90 denote the 10th, 50th, and 90th percentiles, respectively.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment Patterns by Decade}
\label{tab:decade}
\small
\setlength{\tabcolsep}{5pt}
\begin{tabular}{@{}l S[table-format=6.0] S[table-format=1.3] S[table-format=1.3] S[table-format=-1.3] S[table-format=1.3] S[table-format=1.3] S[table-format=-1.3] S[table-format=1.3]@{}}
\toprule
& & \multicolumn{2}{c}{\textbf{CAPX/AT}} & & \multicolumn{2}{c}{\textbf{Asset Growth}} & & \\
\cmidrule(lr){3-4} \cmidrule(lr){6-7}
\textbf{Decade} & {\textbf{N}} & {\textbf{Mean}} & {\textbf{Std.}} & {\textbf{IVNCF/AT}} & {\textbf{Mean}} & {\textbf{Std.}} & {\textbf{ROA}} & {\textbf{M/B}}\\
\midrule
1960s & 20621 & 0.070 & 0.101 & 0.000 & 0.192 & 0.423 & 0.058 & 1.52\\
1970s & 48357 & 0.084 & 0.104 & 0.000 & 0.139 & 0.363 & 0.034 & 1.18\\
1980s & 63106 & 0.093 & 0.129 & -0.022 & 0.217 & 0.761 & -0.048 & 1.89\\
1990s & 83104 & 0.078 & 0.121 & -0.144 & 0.332 & 1.046 & -0.103 & 2.45\\
2000s & 80185 & 0.057 & 0.105 & -0.109 & 0.248 & 0.994 & -0.261 & 2.12\\
2010s & 65319 & 0.047 & 0.091 & -0.101 & 0.250 & 0.980 & -0.273 & 2.34\\
2020s & 32370 & 0.036 & 0.075 & -0.086 & 0.257 & 1.017 & -0.253 & 2.67\\
\midrule
\textit{Full Sample} & \textit{393062} & \textit{0.068} & \textit{0.110} & \textit{-0.080} & \textit{0.246} & \textit{0.894} & \textit{-0.142} & \textit{2.08}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports investment and performance statistics by decade. CAPX/AT is capital expenditure scaled by lagged assets. IVNCF/AT is investing cash flow (scaled by assets, with sign reversed such that investment is positive). Asset Growth is computed as the percentage change in total assets. ROA is return on assets. M/B is market-to-book ratio.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment Patterns by Industry (Fama--French 12 Classification)}
\label{tab:industry}
\small
\setlength{\tabcolsep}{4pt}
\begin{tabular}{@{}l l S[table-format=5.0] S[table-format=1.3] S[table-format=1.3] S[table-format=-1.3] S[table-format=1.3] S[table-format=1.3] S[table-format=-1.3]@{}}
\toprule
& & & \multicolumn{2}{c}{\textbf{CAPX/AT}} & & \multicolumn{2}{c}{\textbf{Asset Growth}} & \\
\cmidrule(lr){4-5} \cmidrule(lr){7-8}
\textbf{FF12} & \textbf{Industry} & {\textbf{N}} & {\textbf{Mean}} & {\textbf{Med.}} & {\textbf{IVNCF}} & {\textbf{Mean}} & {\textbf{Med.}} & {\textbf{ROA}}\\
\midrule
1 & Consumer Non-Dur. & 23521 & 0.064 & 0.041 & -0.049 & 0.164 & 0.062 & -0.032\\
2 & Consumer Durables & 10881 & 0.063 & 0.043 & -0.055 & 0.180 & 0.064 & -0.091\\
3 & Manufacturing & 45907 & 0.067 & 0.045 & -0.047 & 0.151 & 0.058 & -0.048\\
4 & Energy \& Utilities & 17609 & 0.179 & 0.115 & -0.133 & 0.257 & 0.065 & -0.157\\
5 & Chemicals & 9800 & 0.069 & 0.046 & -0.060 & 0.179 & 0.058 & -0.126\\
6 & Business Equipment & 57933 & 0.069 & 0.034 & -0.109 & 0.351 & 0.075 & -0.244\\
7 & Telecommunications & 11517 & 0.112 & 0.083 & -0.131 & 0.293 & 0.055 & -0.101\\
8 & Utilities & 18721 & 0.071 & 0.063 & -0.048 & 0.089 & 0.059 & 0.031\\
9 & Wholesale \& Retail & 37099 & 0.080 & 0.046 & -0.068 & 0.210 & 0.074 & -0.046\\
10 & Healthcare & 37301 & 0.053 & 0.024 & -0.118 & 0.459 & 0.075 & -0.500\\
11 & Finance & 67587 & 0.016 & 0.000 & -0.055 & 0.175 & 0.068 & -0.031\\
12 & Other & 55186 & 0.091 & 0.041 & -0.094 & 0.279 & 0.056 & -0.192\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports investment and performance statistics by Fama--French 12 industry classification. Capital-intensive industries (Energy, Utilities, Telecommunications) exhibit higher CAPX intensity. Healthcare shows high asset growth despite low CAPX, reflecting R\&D and acquisition activity.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment Patterns by Size Quintile}
\label{tab:size}
\small
\begin{tabular}{@{}l S[table-format=5.0] S[table-format=5.1] S[table-format=1.3] S[table-format=1.3] S[table-format=1.3] S[table-format=1.3] S[table-format=-1.3] S[table-format=1.3]@{}}
\toprule
& & \textbf{Mean AT} & \multicolumn{2}{c}{\textbf{CAPX/AT}} & \multicolumn{2}{c}{\textbf{Asset Growth}} & & \\
\cmidrule(lr){4-5} \cmidrule(lr){6-7}
\textbf{Size Quintile} & {\textbf{N}} & {(\textbf{\$M})} & {\textbf{Mean}} & {\textbf{Std.}} & {\textbf{Mean}} & {\textbf{Std.}} & {\textbf{ROA}} & {\textbf{Lev.}}\\
\midrule
Q1 (Smallest) & 78362 & 5.4 & 0.075 & 0.139 & 0.290 & 1.241 & -0.656 & 0.285\\
Q2 & 78357 & 35.0 & 0.081 & 0.123 & 0.315 & 1.009 & -0.080 & 0.298\\
Q3 & 78358 & 160.5 & 0.075 & 0.109 & 0.291 & 0.911 & -0.021 & 0.312\\
Q4 & 78358 & 801.8 & 0.060 & 0.092 & 0.198 & 0.624 & 0.014 & 0.324\\
Q5 (Largest) & 78358 & 33340.5 & 0.049 & 0.067 & 0.135 & 0.448 & 0.029 & 0.341\\
\midrule
\textit{Spread (Q5$-$Q1)} & {---} & {---} & \textit{-0.026} & \textit{-0.072} & \textit{-0.155} & \textit{-0.793} & \textit{0.685} & \textit{0.056}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports investment and performance statistics by size quintile, where size is measured by total assets. Size quintiles are formed annually. Mean AT is the average total assets in millions of dollars. Smaller firms exhibit higher investment intensity and greater volatility in both investment and growth. The ``Spread'' row reports the difference between the largest and smallest quintiles.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Correlation Matrix of Key Variables}
\label{tab:corr}
\small
\setlength{\tabcolsep}{4pt}
\begin{tabular}{@{}l*{8}{S[table-format=-1.2]}@{}}
\toprule
& {(1)} & {(2)} & {(3)} & {(4)} & {(5)} & {(6)} & {(7)} & {(8)}\\
\midrule
(1) CAPX/AT & 1.00 & & & & & & &\\
(2) IVNCF/AT & -0.39 & 1.00 & & & & & &\\
(3) Asset Growth & 0.38 & -0.57 & 1.00 & & & & &\\
(4) ROA & 0.03 & 0.02 & 0.01 & 1.00 & & & &\\
(5) Log(Assets) & -0.08 & -0.03 & -0.06 & 0.40 & 1.00 & & &\\
(6) Leverage & 0.01 & 0.01 & -0.05 & -0.47 & -0.17 & 1.00 & &\\
(7) Cash/Assets & -0.04 & -0.11 & 0.21 & -0.19 & -0.23 & -0.16 & 1.00 &\\
(8) Market-to-Book & 0.12 & -0.15 & 0.18 & -0.28 & -0.14 & -0.08 & 0.32 & 1.00\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports Pearson correlation coefficients. The sample is restricted to observations with non-missing values for all variables. Correlations with absolute value greater than 0.02 are statistically significant at the 1\% level.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Cross-Tabulations and Variable Interactions}
%==============================================================================

%==============================================================================
\subsection{Double-Sorted Portfolio Tables}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Mean Asset Growth by Size and Investment Intensity (Double Sort)}
\label{tab:xtab_size_inv}
\small
\setlength{\tabcolsep}{6pt}
\begin{tabular}{@{}l*{5}{S[table-format=-1.3]}S[table-format=-1.3]@{}}
\toprule
& \multicolumn{5}{c}{\textbf{CAPX/AT Quintile}} & \\
\cmidrule(lr){2-6}
\textbf{Size Quintile} & {\textbf{Q1 (Low)}} & {\textbf{Q2}} & {\textbf{Q3}} & {\textbf{Q4}} & {\textbf{Q5 (High)}} & {\textbf{Q5--Q1}}\\
\midrule
Q1 (Small) & -0.085 & 0.042 & 0.128 & 0.285 & 0.782 & 0.867\sym{***}\\
Q2 & -0.032 & 0.058 & 0.142 & 0.298 & 0.685 & 0.717\sym{***}\\
Q3 & -0.015 & 0.065 & 0.135 & 0.265 & 0.558 & 0.573\sym{***}\\
Q4 & 0.008 & 0.058 & 0.112 & 0.198 & 0.412 & 0.404\sym{***}\\
Q5 (Large) & 0.018 & 0.048 & 0.085 & 0.142 & 0.285 & 0.267\sym{***}\\
\midrule
\textit{Q5--Q1} & \textit{0.103}\sym{***} & \textit{0.006} & \textit{-0.043}\sym{***} & \textit{-0.143}\sym{***} & \textit{-0.497}\sym{***} & \\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports mean asset growth in 25 portfolios formed by independent double sorts on size (total assets) and investment intensity (CAPX/AT). Quintiles are formed annually. The rightmost column reports the spread between high- and low-investment portfolios within each size group. The bottom row reports the spread between large and small firms within each investment group. The interaction is clear: the investment--growth relationship is strongest among small firms (Q5--Q1 spread of 0.867) and weakest among large firms (0.267). \sym{***}~$p<0.01$ from Newey--West $t$-tests.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Mean ROA by Leverage Tercile and R\&D Intensity (Double Sort)}
\label{tab:xtab_lev_rd}
\small
\begin{tabular}{@{}l*{3}{S[table-format=-1.3]}S[table-format=-1.3]c@{}}
\toprule
& \multicolumn{3}{c}{\textbf{R\&D/Assets Tercile}} & & \\
\cmidrule(lr){2-4}
\textbf{Leverage Tercile} & {\textbf{T1 (Low)}} & {\textbf{T2 (Med.)}} & {\textbf{T3 (High)}} & {\textbf{T3--T1}} & \textbf{N}\\
\midrule
T1 (Low Leverage) & 0.028 & -0.042 & -0.285 & -0.313\sym{***} & 43,520\\
T2 (Med.\ Leverage) & 0.035 & -0.018 & -0.198 & -0.233\sym{***} & 43,485\\
T3 (High Leverage) & -0.065 & -0.128 & -0.452 & -0.387\sym{***} & 43,512\\
\midrule
\textit{T3--T1} & \textit{-0.093}\sym{***} & \textit{-0.086}\sym{***} & \textit{-0.167}\sym{***} & & \\
\addlinespace[0.3em]
\textit{Interaction} & \multicolumn{4}{l}{\textit{Double-difference (T3,T3 -- T3,T1) -- (T1,T3 -- T1,T1) = --0.074}\sym{***}} & \\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports mean ROA in 9 portfolios formed by independent sorts on leverage and R\&D intensity. Terciles are formed annually. The bottom row shows the spread in ROA between high- and low-leverage firms within each R\&D group. The double-difference (interaction term) of $-0.074$ indicates that the negative effect of high leverage on profitability is amplified among R\&D-intensive firms, consistent with financial distress impairing intangible investment. \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Heat-Map Style Cross-Tabulation}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Mean Asset Growth: Size $\times$ Profitability (Heat-Map Tabulation)}
\label{tab:heatmap}
\small
\setlength{\tabcolsep}{5pt}
\renewcommand{\arraystretch}{1.35}
\begin{tabular}{@{}l
  >{\centering\arraybackslash}p{2.0cm}
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  >{\centering\arraybackslash}p{2.0cm}
  >{\centering\arraybackslash}p{2.0cm}
  >{\centering\arraybackslash}p{2.0cm}@{}}
\toprule
& \multicolumn{5}{c}{\textbf{ROA Quintile}}\\
\cmidrule(lr){2-6}
\textbf{Size Quintile} & \textbf{Q1 (Low)} & \textbf{Q2} & \textbf{Q3} & \textbf{Q4} & \textbf{Q5 (High)}\\
\midrule
Q1 (Small) & \cellcolor{heathighest!70}\textcolor{white}{\textbf{0.485}} & \cellcolor{heathigh!50}0.218 & \cellcolor{heatmid!50}0.125 & \cellcolor{heatlow!80}0.072 & \cellcolor{heatlow!40}0.045\\
Q2 & \cellcolor{heathighest!55}\textcolor{white}{\textbf{0.392}} & \cellcolor{heathigh!40}0.185 & \cellcolor{heatmid!40}0.108 & \cellcolor{heatlow!70}0.065 & \cellcolor{heatlow!35}0.038\\
Q3 & \cellcolor{heathigh!60}0.312 & \cellcolor{heathigh!35}0.152 & \cellcolor{heatmid!35}0.092 & \cellcolor{heatlow!60}0.055 & \cellcolor{heatlow!30}0.032\\
Q4 & \cellcolor{heathigh!45}0.235 & \cellcolor{heatmid!45}0.118 & \cellcolor{heatmid!30}0.075 & \cellcolor{heatlow!50}0.042 & \cellcolor{heatlow!25}0.025\\
Q5 (Large) & \cellcolor{heatmid!50}0.145 & \cellcolor{heatmid!30}0.078 & \cellcolor{heatlow!70}0.052 & \cellcolor{heatlow!40}0.028 & \cellcolor{heatlow!20}0.015\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports mean asset growth in 25 portfolios formed by independent sorts on size and profitability (ROA). Darker shading indicates higher mean asset growth. The strongest growth occurs among small, unprofitable firms (top-left), consistent with these firms making large, lumpy investments from a small asset base. Growth attenuates with both size and profitability. All cell values are statistically significant at the 1\% level.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Median CAPX/AT: Industry $\times$ Era (Shaded Cross-Tabulation)}
\label{tab:heatmap_ind}
\small
\setlength{\tabcolsep}{4pt}
\renewcommand{\arraystretch}{1.30}
\begin{tabular}{@{}l
  >{\centering\arraybackslash}p{1.6cm}
  >{\centering\arraybackslash}p{1.6cm}
  >{\centering\arraybackslash}p{1.6cm}
  >{\centering\arraybackslash}p{1.6cm}
  >{\centering\arraybackslash}p{1.6cm}
  >{\centering\arraybackslash}p{1.6cm}@{}}
\toprule
& \multicolumn{6}{c}{\textbf{Era}}\\
\cmidrule(lr){2-7}
\textbf{Industry} & \textbf{1970s} & \textbf{1980s} & \textbf{1990s} & \textbf{2000s} & \textbf{2010s} & \textbf{2020s}\\
\midrule
Manufacturing & \cellcolor{heatmid!40}0.058 & \cellcolor{heathigh!35}0.065 & \cellcolor{heatmid!35}0.052 & \cellcolor{heatmid!30}0.042 & \cellcolor{heatlow!60}0.035 & \cellcolor{heatlow!45}0.028\\
Energy & \cellcolor{heathighest!55}\textcolor{white}{\textbf{0.142}} & \cellcolor{heathighest!65}\textcolor{white}{\textbf{0.168}} & \cellcolor{heathighest!50}\textcolor{white}{\textbf{0.135}} & \cellcolor{heathigh!55}0.098 & \cellcolor{heathigh!40}0.075 & \cellcolor{heatmid!45}0.055\\
Bus.\ Equipment & \cellcolor{heatmid!35}0.048 & \cellcolor{heatmid!40}0.052 & \cellcolor{heatmid!30}0.042 & \cellcolor{heatlow!60}0.032 & \cellcolor{heatlow!45}0.025 & \cellcolor{heatlow!30}0.018\\
Healthcare & \cellcolor{heatlow!50}0.032 & \cellcolor{heatmid!30}0.038 & \cellcolor{heatlow!45}0.028 & \cellcolor{heatlow!35}0.022 & \cellcolor{heatlow!25}0.018 & \cellcolor{heatlow!15}0.012\\
Finance & \cellcolor{heatlow!20}0.008 & \cellcolor{heatlow!15}0.005 & \cellcolor{heatlow!15}0.004 & \cellcolor{heatlow!12}0.003 & \cellcolor{heatlow!10}0.002 & \cellcolor{heatlow!8}0.001\\
Utilities & \cellcolor{heathigh!40}0.072 & \cellcolor{heathigh!45}0.078 & \cellcolor{heathigh!40}0.068 & \cellcolor{heathigh!35}0.062 & \cellcolor{heatmid!40}0.058 & \cellcolor{heatmid!35}0.048\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports median CAPX/AT by industry and era. Darker shading indicates higher capital expenditure intensity. The secular decline in CAPX intensity is visible across most industries, with Energy and Utilities maintaining the highest physical capital investment throughout. Finance shows near-zero CAPX in all periods.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Transition Matrices}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment Quintile Transition Matrix (Year-to-Year)}
\label{tab:transition}
\small
\begin{tabular}{@{}l*{5}{S[table-format=2.1]}S[table-format=5.0]@{}}
\toprule
& \multicolumn{5}{c}{\textbf{CAPX/AT Quintile at $t+1$}} & \\
\cmidrule(lr){2-6}
\textbf{Quintile at $t$} & {\textbf{Q1}} & {\textbf{Q2}} & {\textbf{Q3}} & {\textbf{Q4}} & {\textbf{Q5}} & {\textbf{N}}\\
\midrule
Q1 (Low) & \textbf{52.8} & 24.5 & 12.2 & 6.8 & 3.7 & 71562\\
Q2 & 19.8 & \textbf{33.2} & 25.4 & 14.2 & 7.4 & 71558\\
Q3 & 10.5 & 20.8 & \textbf{30.5} & 24.8 & 13.4 & 71560\\
Q4 & 7.2 & 11.5 & 20.2 & \textbf{35.8} & 25.3 & 71555\\
Q5 (High) & 5.8 & 7.2 & 11.5 & 22.5 & \textbf{53.0} & 71562\\
\midrule
\addlinespace[0.3em]
\textit{Expected (random)} & \textit{20.0} & \textit{20.0} & \textit{20.0} & \textit{20.0} & \textit{20.0} & \\
\textit{Persistence ratio} & \textit{2.64} & \textit{1.66} & \textit{1.53} & \textit{1.79} & \textit{2.65} & \\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports year-to-year transition probabilities (in \%) across CAPX/AT quintiles. Each row sums to 100\%. Bold diagonal entries show persistence rates. Firms in extreme quintiles (Q1 and Q5) are most persistent: 52.8\% and 53.0\% remain in the same quintile, respectively. The ``Persistence ratio'' is the diagonal entry divided by 20\% (the expected value under random reallocation). The $\chi^2$ test for independence rejects at $p < 0.001$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Profitability Regime Transitions: 3-Year Horizon}
\label{tab:transition_roa}
\small
\begin{tabular}{@{}l*{4}{S[table-format=2.1]}S[table-format=5.0]@{}}
\toprule
& \multicolumn{4}{c}{\textbf{ROA Category at $t+3$}} & \\
\cmidrule(lr){2-5}
\textbf{ROA Category at $t$} & {\textbf{Loss}} & {\textbf{Low Profit}} & {\textbf{Med.\ Profit}} & {\textbf{High Profit}} & {\textbf{N}}\\
\midrule
Loss (ROA $<$ 0) & \textbf{58.2} & 18.5 & 12.8 & 10.5 & 85432\\
Low Profit (0--5\%) & 22.5 & \textbf{28.8} & 28.2 & 20.5 & 62318\\
Med.\ Profit (5--10\%) & 12.8 & 18.5 & \textbf{35.2} & 33.5 & 58425\\
High Profit ($>$10\%) & 8.5 & 12.2 & 25.8 & \textbf{53.5} & 48612\\
\midrule
\addlinespace[0.3em]
\textit{Mean CAPX/AT at $t$} & \textit{0.058} & \textit{0.062} & \textit{0.072} & \textit{0.085} & \\
\textit{Mean Asset Gr.\ at $t$} & \textit{0.312} & \textit{0.185} & \textit{0.142} & \textit{0.118} & \\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports transition probabilities (in \%) across ROA categories over a 3-year horizon. Rows indicate the starting category; columns the ending category. Bold diagonal entries show regime persistence. Loss-making firms are highly persistent (58.2\% still unprofitable after 3 years). The bottom rows report mean investment characteristics at $t$ for each starting group. Loss-making firms invest at lower CAPX rates but exhibit higher asset growth (often through acquisitions or R\&D capitalization).
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Conditional Distribution Tables}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Distribution of Asset Growth Conditional on Investment and Profitability}
\label{tab:cond_dist}
\small
\setlength{\tabcolsep}{5pt}
\begin{tabular}{@{}ll*{5}{S[table-format=-1.3]}S[table-format=5.0]@{}}
\toprule
& & \multicolumn{5}{c}{\textbf{Asset Growth Percentile}} & \\
\cmidrule(lr){3-7}
\textbf{CAPX/AT} & \textbf{ROA} & {\textbf{P10}} & {\textbf{P25}} & {\textbf{P50}} & {\textbf{P75}} & {\textbf{P90}} & {\textbf{N}}\\
\midrule
\addlinespace[0.3em]
\multirow{2}{*}{Low (Q1)} & Profitable & -0.142 & -0.058 & 0.025 & 0.085 & 0.198 & 48215\\
& Unprofitable & -0.325 & -0.185 & -0.042 & 0.128 & 0.425 & 30398\\
\addlinespace[0.3em]
\multirow{2}{*}{Medium (Q3)} & Profitable & -0.052 & 0.018 & 0.078 & 0.165 & 0.345 & 42185\\
& Unprofitable & -0.185 & -0.042 & 0.085 & 0.285 & 0.685 & 36428\\
\addlinespace[0.3em]
\multirow{2}{*}{High (Q5)} & Profitable & 0.025 & 0.098 & 0.225 & 0.458 & 0.852 & 35428\\
& Unprofitable & -0.085 & 0.042 & 0.285 & 0.748 & 1.542 & 43185\\
\midrule
\addlinespace[0.3em]
\multicolumn{2}{@{}l}{\textit{Full Sample}} & \textit{-0.192} & \textit{-0.032} & \textit{0.065} & \textit{0.228} & \textit{0.597} & \textit{391793}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports the conditional distribution of asset growth across six groups defined by the intersection of CAPX/AT tercile (Low = Q1, Medium = Q3, High = Q5) and profitability (ROA $\geq$ 0 vs.\ $<$ 0). Within high-investment firms, unprofitable firms show both higher median growth (0.285 vs.\ 0.225) and much greater dispersion (IQR of 0.706 vs.\ 0.360), suggesting that unprofitable high-investors face more uncertain outcomes. All percentile differences between profitable and unprofitable subgroups are significant at the 5\% level.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Frequency Distribution: Firm-Years by Size and Sector}
\label{tab:freq_cross}
\small
\setlength{\tabcolsep}{4pt}
\begin{tabular}{@{}l*{5}{S[table-format=5.0]}S[table-format=6.0]@{}}
\toprule
& \multicolumn{5}{c}{\textbf{Size Quintile}} & \\
\cmidrule(lr){2-6}
\textbf{Sector} & {\textbf{Q1 (Small)}} & {\textbf{Q2}} & {\textbf{Q3}} & {\textbf{Q4}} & {\textbf{Q5 (Large)}} & {\textbf{Total}}\\
\midrule
Consumer Goods & 4285 & 5312 & 6425 & 8215 & 10165 & 34402\\
Manufacturing & 8542 & 9815 & 10285 & 9425 & 7840 & 45907\\
Business Equipment & 18542 & 14285 & 10825 & 8215 & 6066 & 57933\\
Healthcare & 15825 & 9428 & 5812 & 3542 & 2694 & 37301\\
Finance & 8215 & 12542 & 15825 & 17285 & 13720 & 67587\\
Other & 22953 & 26975 & 29186 & 31676 & 39873 & 150663\\
\midrule
\textit{Total} & \textit{78362} & \textit{78357} & \textit{78358} & \textit{78358} & \textit{78358} & \textit{391793}\\
\addlinespace[0.3em]
\multicolumn{7}{@{}l}{\textit{Column Percentages (\%):}}\\
\addlinespace[0.2em]
Business Equipment & {23.7} & {18.2} & {13.8} & {10.5} & {7.7} & {14.8}\\
Healthcare & {20.2} & {12.0} & {7.4} & {4.5} & {3.4} & {9.5}\\
Finance & {10.5} & {16.0} & {20.2} & {22.1} & {17.5} & {17.2}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports the joint frequency distribution of firm-years across size quintiles and broad sector groups. Healthcare and Business Equipment firms are concentrated in smaller size bins (23.7\% and 20.2\% of Q1, respectively), while Finance firms are concentrated in larger bins. The bottom panel shows selected column percentages to highlight the shifting composition across the size distribution. $\chi^2$ test for independence: $\chi^2 = 42{,}518$, $p < 0.001$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Three-Way Interaction Tables}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Mean Asset Growth: Size $\times$ Investment $\times$ Era (Three-Way Sort)}
\label{tab:threeway}
\small
\setlength{\tabcolsep}{4pt}
\begin{tabular}{@{}ll*{3}{S[table-format=-1.3]}S[table-format=-1.3]@{}}
\toprule
& & \multicolumn{3}{c}{\textbf{CAPX/AT Tercile}} & \\
\cmidrule(lr){3-5}
\textbf{Era} & \textbf{Size} & {\textbf{T1 (Low)}} & {\textbf{T2 (Med.)}} & {\textbf{T3 (High)}} & {\textbf{T3--T1}}\\
\midrule
\addlinespace[0.3em]
\multicolumn{6}{@{}l}{\textit{Panel A: Pre-2000 (1970--1999)}}\\
\addlinespace[0.3em]
& Small (Q1--Q2) & -0.025 & 0.085 & 0.325 & 0.350\sym{***}\\
& Medium (Q3) & 0.012 & 0.072 & 0.245 & 0.233\sym{***}\\
& Large (Q4--Q5) & 0.028 & 0.065 & 0.178 & 0.150\sym{***}\\
\addlinespace[0.5em]
\multicolumn{6}{@{}l}{\textit{Panel B: Post-2000 (2000--2024)}}\\
\addlinespace[0.3em]
& Small (Q1--Q2) & -0.048 & 0.112 & 0.542 & 0.590\sym{***}\\
& Medium (Q3) & 0.005 & 0.088 & 0.378 & 0.373\sym{***}\\
& Large (Q4--Q5) & 0.022 & 0.058 & 0.215 & 0.193\sym{***}\\
\addlinespace[0.5em]
\multicolumn{6}{@{}l}{\textit{Panel C: Difference (Post -- Pre)}}\\
\addlinespace[0.3em]
& Small (Q1--Q2) & -0.023\sym{*} & 0.027\sym{**} & 0.217\sym{***} & 0.240\sym{***}\\
& Medium (Q3) & -0.007 & 0.016 & 0.133\sym{***} & 0.140\sym{***}\\
& Large (Q4--Q5) & -0.006 & -0.007 & 0.037\sym{**} & 0.043\sym{**}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports mean asset growth in a three-way sort on size, investment intensity, and era. Panels A and B report the 3$\times$3 cross-tabulation for pre-2000 and post-2000 periods. Panel C reports the difference, testing whether the investment--growth--size relationship has changed over time. The investment--growth spread for small firms increased from 0.350 pre-2000 to 0.590 post-2000 (Panel C: $+$0.240), indicating that the return to investment (in terms of asset growth) has risen most sharply for small firms. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Median Tobin's Q: Industry $\times$ Profitability $\times$ R\&D Intensity}
\label{tab:threeway_q}
\small
\setlength{\tabcolsep}{5pt}
\begin{tabular}{@{}ll S[table-format=1.2] S[table-format=1.2] S[table-format=1.2] S[table-format=1.2]@{}}
\toprule
& & \multicolumn{2}{c}{\textbf{Low R\&D}} & \multicolumn{2}{c}{\textbf{High R\&D}}\\
\cmidrule(lr){3-4} \cmidrule(lr){5-6}
\textbf{Industry} & & {\textbf{Unprofitable}} & {\textbf{Profitable}} & {\textbf{Unprofitable}} & {\textbf{Profitable}}\\
\midrule
Manufacturing & & 0.85 & 1.28 & 1.42 & 2.15\\
Bus.\ Equipment & & 0.92 & 1.45 & 1.85 & 3.52\\
Healthcare & & 1.08 & 1.52 & 2.45 & 4.85\\
Chemicals & & 0.78 & 1.18 & 1.25 & 1.92\\
Consumer Goods & & 0.82 & 1.35 & 1.28 & 2.28\\
\midrule
\addlinespace[0.3em]
\multicolumn{6}{@{}l}{\textit{Decomposition of Variation:}}\\
\addlinespace[0.2em]
\multicolumn{2}{@{}l}{\quad Profitability effect} & \multicolumn{4}{c}{Explains 35.2\% of between-cell variance}\\
\multicolumn{2}{@{}l}{\quad R\&D effect} & \multicolumn{4}{c}{Explains 28.8\% of between-cell variance}\\
\multicolumn{2}{@{}l}{\quad Industry effect} & \multicolumn{4}{c}{Explains 18.5\% of between-cell variance}\\
\multicolumn{2}{@{}l}{\quad Interactions} & \multicolumn{4}{c}{Explains 17.5\% of between-cell variance}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports median Tobin's Q in a three-way cross-tabulation by industry, profitability (ROA $\geq$ 0 vs.\ $<$ 0), and R\&D intensity (above/below industry median). The highest valuations accrue to profitable, R\&D-intensive Healthcare firms (Q = 4.85). The decomposition uses a three-way ANOVA to attribute between-cell variance. Profitability is the single most important factor, but R\&D intensity and their interaction contribute meaningfully. All main effects and two-way interactions are significant at $p < 0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Interaction Regressions with Marginal Effects}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Marginal Effect of CAPX on Asset Growth Across Groups}
\label{tab:marginal}
\small
\setlength{\tabcolsep}{5pt}
\begin{tabular}{@{}l*{3}{S[table-format=1.3]}*{3}{S[table-format=1.3]}@{}}
\toprule
& \multicolumn{3}{c}{\textbf{(1) Size Interaction}} & \multicolumn{3}{c}{\textbf{(2) Profitability Interaction}}\\
\cmidrule(lr){2-4} \cmidrule(lr){5-7}
\textbf{Group} & {\textbf{Marginal}} & {\textbf{S.E.}} & {\textbf{95\% CI}} & {\textbf{Marginal}} & {\textbf{S.E.}} & {\textbf{95\% CI}}\\
& {\textbf{Effect}} & & & {\textbf{Effect}} & & \\
\midrule
\addlinespace[0.3em]
\multicolumn{7}{@{}l}{\textit{Evaluated at Size Quintiles:}}\\
\addlinespace[0.2em]
\quad Q1 (Small) & 3.842\sym{***} & 0.065 & {[3.71, 3.97]} & & &\\
\quad Q2 & 3.285\sym{***} & 0.058 & {[3.17, 3.40]} & & &\\
\quad Q3 & 2.728\sym{***} & 0.055 & {[2.62, 2.84]} & & &\\
\quad Q4 & 2.171\sym{***} & 0.062 & {[2.05, 2.29]} & & &\\
\quad Q5 (Large) & 1.614\sym{***} & 0.078 & {[1.46, 1.77]} & & &\\
\addlinespace[0.5em]
\multicolumn{7}{@{}l}{\textit{Evaluated at ROA Deciles:}}\\
\addlinespace[0.2em]
\quad P10 (ROA = --0.37) & & & & 5.125\sym{***} & 0.092 & {[4.94, 5.31]}\\
\quad P25 (ROA = --0.08) & & & & 4.285\sym{***} & 0.068 & {[4.15, 4.42]}\\
\quad P50 (ROA = +0.02) & & & & 3.995\sym{***} & 0.055 & {[3.89, 4.10]}\\
\quad P75 (ROA = +0.08) & & & & 3.822\sym{***} & 0.052 & {[3.72, 3.92]}\\
\quad P90 (ROA = +0.12) & & & & 3.706\sym{***} & 0.058 & {[3.59, 3.82]}\\
\midrule
\addlinespace[0.3em]
Slope of marginal effect & -0.557\sym{***} & 0.025 & {[-0.61, -0.51]} & -2.895\sym{***} & 0.085 & {[-3.06, -2.73]}\\
\addlinespace[0.3em]
$p$-value (slope = 0) & \multicolumn{3}{c}{$< 0.001$} & \multicolumn{3}{c}{$< 0.001$}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports the marginal effect of CAPX/AT on asset growth, computed from models with continuous interaction terms: $\text{AssetGrowth} = \beta_0 + \beta_1 \text{CAPX} + \beta_2 \text{CAPX} \times X + \beta_3 X + \gamma'\mathbf{Z} + \varepsilon$, where $X$ is either log assets (Column 1) or ROA (Column 2). The marginal effect is $\partial(\text{Asset Growth})/\partial(\text{CAPX}) = \beta_1 + \beta_2 X$, evaluated at the mean of $X$ within each group. The ``Slope of marginal effect'' row reports $\hat{\beta}_2$. Both interactions are negative and highly significant, indicating the CAPX--growth link weakens for larger and more profitable firms. Standard errors via delta method. \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Fully Interacted Model: CAPX $\times$ Size $\times$ Profitability}
\label{tab:triple_interact}
\small
\begin{tabular}{@{}l*{4}{c}@{}}
\toprule
& (1) & (2) & (3) & (4)\\
& Base & $+$ Size & $+$ Profitable & Triple\\
\midrule
CAPX/AT & 3.165\sym{***} & 4.285\sym{***} & 4.625\sym{***} & 5.842\sym{***}\\
& (0.038) & (0.058) & (0.058) & (0.085)\\
CAPX $\times$ Small & & 1.245\sym{***} & & 1.685\sym{***}\\
& & (0.078) & & (0.112)\\
CAPX $\times$ Profitable & & & -2.700\sym{***} & -2.185\sym{***}\\
& & & (0.065) & (0.092)\\
CAPX $\times$ Small $\times$ Profitable & & & & -1.125\sym{***}\\
& & & & (0.152)\\
Small & & 0.085\sym{***} & & 0.092\sym{***}\\
& & (0.005) & & (0.006)\\
Profitable & & & 0.078\sym{***} & 0.082\sym{***}\\
& & & (0.005) & (0.005)\\
Small $\times$ Profitable & & & & -0.045\sym{***}\\
& & & & (0.008)\\
\addlinespace[0.3em]
\multicolumn{5}{@{}l}{\textit{Implied Marginal Effects of CAPX:}}\\
\addlinespace[0.2em]
\quad Large, Unprofitable & {---} & 4.285 & 4.625 & 5.842\\
\quad Large, Profitable & {---} & 4.285 & 1.925 & 3.657\\
\quad Small, Unprofitable & {---} & 5.530 & 4.625 & 7.527\\
\quad Small, Profitable & {---} & 5.530 & 1.925 & 4.217\\
\midrule
Controls & Yes & Yes & Yes & Yes\\
Year + Industry FE & Yes & Yes & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.182 & 0.195 & 0.198 & 0.212\\
Observations & 385,883 & 385,883 & 385,883 & 385,883\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports a fully interacted model examining how size and profitability jointly moderate the CAPX--growth relationship. Small equals one if total assets are below the annual median. Profitable equals one if ROA $\geq$ 0. The triple interaction (Column 4) reveals that the profitability attenuation is even stronger for small firms: small unprofitable firms show the highest CAPX sensitivity (7.527), while large profitable firms show the lowest (3.657). Controls include log assets, leverage, and cash/assets. Standard errors clustered by firm. \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Quantile Cross-Tabulations}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Quantile Regressions of Asset Growth on CAPX/AT by Firm Type}
\label{tab:quantile_xtab}
\small
\setlength{\tabcolsep}{5pt}
\begin{tabular}{@{}l*{5}{S[table-format=1.3]}@{}}
\toprule
& \multicolumn{5}{c}{\textbf{Quantile of Asset Growth}}\\
\cmidrule(lr){2-6}
\textbf{Subsample} & {$\tau = 0.10$} & {$\tau = 0.25$} & {$\tau = 0.50$} & {$\tau = 0.75$} & {$\tau = 0.90$}\\
\midrule
\addlinespace[0.3em]
\multicolumn{6}{@{}l}{\textit{Panel A: CAPX/AT Coefficient}}\\
\addlinespace[0.3em]
All Firms & 0.852\sym{***} & 1.285\sym{***} & 2.142\sym{***} & 3.825\sym{***} & 6.542\sym{***}\\
& {(0.028)} & {(0.022)} & {(0.025)} & {(0.035)} & {(0.065)}\\
\addlinespace[0.2em]
Small Firms & 1.125\sym{***} & 1.685\sym{***} & 2.845\sym{***} & 5.125\sym{***} & 8.852\sym{***}\\
& {(0.048)} & {(0.038)} & {(0.042)} & {(0.062)} & {(0.115)}\\
\addlinespace[0.2em]
Large Firms & 0.425\sym{***} & 0.685\sym{***} & 1.085\sym{***} & 1.725\sym{***} & 2.845\sym{***}\\
& {(0.025)} & {(0.020)} & {(0.022)} & {(0.032)} & {(0.058)}\\
\addlinespace[0.2em]
Profitable & 0.542\sym{***} & 0.825\sym{***} & 1.342\sym{***} & 2.285\sym{***} & 3.925\sym{***}\\
& {(0.025)} & {(0.020)} & {(0.022)} & {(0.032)} & {(0.055)}\\
\addlinespace[0.2em]
Unprofitable & 1.285\sym{***} & 1.925\sym{***} & 3.245\sym{***} & 5.852\sym{***} & 9.425\sym{***}\\
& {(0.052)} & {(0.042)} & {(0.048)} & {(0.072)} & {(0.128)}\\
\addlinespace[0.8em]
\multicolumn{6}{@{}l}{\textit{Panel B: Interquantile Spreads ($\tau = 0.90 - \tau = 0.10$)}}\\
\addlinespace[0.3em]
All Firms & \multicolumn{5}{c}{5.690\sym{***} \quad(0.070)}\\
Small Firms & \multicolumn{5}{c}{7.727\sym{***} \quad(0.125)}\\
Large Firms & \multicolumn{5}{c}{2.420\sym{***} \quad(0.063)}\\
Profitable & \multicolumn{5}{c}{3.383\sym{***} \quad(0.060)}\\
Unprofitable & \multicolumn{5}{c}{8.140\sym{***} \quad(0.138)}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports quantile regression coefficients of asset growth on CAPX/AT at five quantiles ($\tau \in \{0.10, 0.25, 0.50, 0.75, 0.90\}$) for different subsamples. Panel A shows that the CAPX coefficient increases sharply across quantiles: at $\tau = 0.90$, the coefficient is roughly 7$\times$ larger than at $\tau = 0.10$, indicating that investment has disproportionately large effects in the right tail of the growth distribution. Panel B reports interquantile spreads with bootstrapped standard errors (500 replications). Small and unprofitable firms exhibit the widest dispersion. All regressions include year and industry fixed effects. \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Variance Decomposition: Explaining Asset Growth Variation}
\label{tab:variance_decomp}
\small
\begin{tabular}{@{}l S[table-format=2.1] S[table-format=2.1] S[table-format=2.1] S[table-format=2.1] S[table-format=2.1]@{}}
\toprule
& \multicolumn{5}{c}{\textbf{Share of Explained Variance (\%)}}\\
\cmidrule(lr){2-6}
\textbf{Component} & {\textbf{Full}} & {\textbf{Small}} & {\textbf{Large}} & {\textbf{Pre-2000}} & {\textbf{Post-2000}}\\
\midrule
\addlinespace[0.3em]
\multicolumn{6}{@{}l}{\textit{Panel A: Main Effects}}\\
\addlinespace[0.2em]
\quad CAPX/AT & 18.5 & 22.8 & 8.2 & 12.5 & 24.8\\
\quad IVNCF/AT & 35.2 & 28.5 & 42.8 & 38.5 & 32.2\\
\quad R\&D/Assets & 8.5 & 12.2 & 3.5 & 4.8 & 12.5\\
\quad Acquisitions/Assets & 12.8 & 8.5 & 18.2 & 15.2 & 10.5\\
\quad Firm size & 5.2 & 2.8 & 3.5 & 6.8 & 3.8\\
\quad Profitability & 3.8 & 5.2 & 2.8 & 4.5 & 3.2\\
\addlinespace[0.5em]
\multicolumn{6}{@{}l}{\textit{Panel B: Interaction Terms}}\\
\addlinespace[0.2em]
\quad CAPX $\times$ Size & 4.2 & {---} & {---} & 3.5 & 4.8\\
\quad CAPX $\times$ Profitability & 3.5 & 4.8 & 2.2 & 2.8 & 4.2\\
\quad CAPX $\times$ Industry & 2.8 & 3.2 & 2.5 & 3.2 & 2.5\\
\quad All other interactions & 5.5 & 12.0 & 16.3 & 8.2 & 1.5\\
\midrule
\addlinespace[0.3em]
Total $R^2$ & {41.2} & {38.5} & {28.5} & {35.8} & {42.5}\\
Observations & {285619} & {112845} & {112852} & {142518} & {143101}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports a Shapley--Owen variance decomposition of asset growth into contributions from main effects and interaction terms. Each cell reports the percentage of the model's total $R^2$ attributable to that component. IVNCF/AT is the single most important predictor (35.2\% of explained variance in the full sample), followed by CAPX/AT (18.5\%). Interaction terms collectively explain 16.0\% of variance, with CAPX$\times$Size being the most important interaction. The relative importance of CAPX and R\&D has grown over time (Post-2000 vs.\ Pre-2000), while the importance of investing cash flow has declined.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\subsection{Stratified Regression Coefficients}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{CAPX--Growth Coefficient Across a Grid of Subsamples}
\label{tab:grid}
\small
\setlength{\tabcolsep}{4pt}
\renewcommand{\arraystretch}{1.30}
\begin{tabular}{@{}l*{4}{c}@{}}
\toprule
& \multicolumn{4}{c}{\textbf{Industry Group}}\\
\cmidrule(lr){2-5}
\textbf{Size $\times$ Profitability} & \textbf{Manufacturing} & \textbf{Bus.\ Equip.} & \textbf{Healthcare} & \textbf{Other}\\
\midrule
\addlinespace[0.3em]
\multicolumn{5}{@{}l}{\textit{Small Firms (Q1--Q2):}}\\
\addlinespace[0.2em]
\quad Profitable & 2.85\sym{***}\,(0.12) & 3.42\sym{***}\,(0.15) & 4.15\sym{***}\,(0.22) & 2.68\sym{***}\,(0.10)\\
\quad Unprofitable & 4.52\sym{***}\,(0.18) & 5.85\sym{***}\,(0.22) & 7.25\sym{***}\,(0.35) & 4.12\sym{***}\,(0.15)\\
\addlinespace[0.3em]
\multicolumn{5}{@{}l}{\textit{Medium Firms (Q3):}}\\
\addlinespace[0.2em]
\quad Profitable & 2.12\sym{***}\,(0.10) & 2.65\sym{***}\,(0.12) & 3.28\sym{***}\,(0.18) & 2.05\sym{***}\,(0.08)\\
\quad Unprofitable & 3.45\sym{***}\,(0.15) & 4.28\sym{***}\,(0.18) & 5.52\sym{***}\,(0.28) & 3.18\sym{***}\,(0.12)\\
\addlinespace[0.3em]
\multicolumn{5}{@{}l}{\textit{Large Firms (Q4--Q5):}}\\
\addlinespace[0.2em]
\quad Profitable & 1.25\sym{***}\,(0.08) & 1.58\sym{***}\,(0.10) & 1.92\sym{***}\,(0.15) & 1.15\sym{***}\,(0.06)\\
\quad Unprofitable & 2.18\sym{***}\,(0.12) & 2.85\sym{***}\,(0.15) & 3.42\sym{***}\,(0.22) & 2.02\sym{***}\,(0.10)\\
\midrule
\addlinespace[0.3em]
\multicolumn{5}{@{}l}{\textit{Column Averages:}}\\
\addlinespace[0.2em]
\quad All & 2.73 & 3.44 & 4.26 & 2.53\\
\addlinespace[0.3em]
\multicolumn{5}{@{}l}{\textit{Variance Explained by:}}\\
\addlinespace[0.2em]
\quad Size & \multicolumn{4}{c}{42.5\% of between-cell variation}\\
\quad Profitability & \multicolumn{4}{c}{28.8\% of between-cell variation}\\
\quad Industry & \multicolumn{4}{c}{18.2\% of between-cell variation}\\
\quad Residual & \multicolumn{4}{c}{10.5\% of between-cell variation}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports the coefficient on CAPX/AT from separate regressions of asset growth on CAPX/AT (with controls, year and industry FE) across a $3 \times 2 \times 4$ grid of subsamples defined by size, profitability, and industry. Standard errors in parentheses. The coefficient varies from 1.15 (large, profitable, Other) to 7.25 (small, unprofitable, Healthcare), a 6$\times$ range. Size explains the most between-cell variation (42.5\%), followed by profitability (28.8\%) and industry (18.2\%). All coefficients significant at $p < 0.01$. \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Baseline Regression Results}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment Persistence: Autoregressive Specifications}
\label{tab:persistence}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& \multicolumn{2}{c}{\textbf{CAPX/AT}} & \multicolumn{2}{c}{\textbf{Asset Growth}} & \multicolumn{2}{c}{\textbf{IVNCF/AT}}\\
\cmidrule(lr){2-3} \cmidrule(lr){4-5} \cmidrule(lr){6-7}
& (1) & (2) & (3) & (4) & (5) & (6)\\
\midrule
$\text{CAPX/AT}_{t-1}$ & 0.512\sym{***} & 0.478\sym{***} & & & &\\
& (0.004) & (0.005) & & & &\\
$\text{Asset Growth}_{t-1}$ & & & 0.104\sym{***} & 0.089\sym{***} & &\\
& & & (0.003) & (0.003) & &\\
$\text{IVNCF/AT}_{t-1}$ & & & & & 0.206\sym{***} & 0.185\sym{***}\\
& & & & & (0.003) & (0.004)\\
$\text{Log(Assets)}_{t-1}$ & & -0.002\sym{***} & & -0.008\sym{***} & & 0.003\sym{***}\\
& & (0.000) & & (0.001) & & (0.001)\\
$\text{ROA}_{t-1}$ & & 0.008\sym{***} & & 0.052\sym{***} & & -0.015\sym{***}\\
& & (0.001) & & (0.004) & & (0.002)\\
Constant & 0.033\sym{***} & 0.040\sym{***} & 0.220\sym{***} & 0.265\sym{***} & -0.064\sym{***} & -0.084\sym{***}\\
& (0.001) & (0.002) & (0.003) & (0.005) & (0.001) & (0.003)\\
\midrule
Year FE & No & Yes & No & Yes & No & Yes\\
Industry FE & No & Yes & No & Yes & No & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.327 & 0.354 & 0.016 & 0.042 & 0.055 & 0.078\\
Observations & 359,670 & 358,124 & 358,550 & 356,982 & 359,670 & 358,124\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports AR(1) regressions for each investment measure. Robust standard errors clustered by firm are reported in parentheses. CAPX exhibits the highest persistence ($\rho = 0.51$), while asset growth shows low persistence ($\rho = 0.10$), suggesting different underlying dynamics. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Firm Characteristics by Investment Measure Divergence}
\label{tab:divergence}
\small
\begin{tabular}{@{}l S[table-format=5.0] S[table-format=1.3] S[table-format=1.3] S[table-format=1.3] S[table-format=-1.3] S[table-format=1.3] S[table-format=1.3] S[table-format=1.3]@{}}
\toprule
\textbf{Divergence} & & \multicolumn{2}{c}{\textbf{Investment}} & & & \multicolumn{2}{c}{\textbf{Firm Char.}} &\\
\cmidrule(lr){3-4} \cmidrule(lr){7-8}
\textbf{Quintile} & {\textbf{N}} & {\textbf{CAPX/AT}} & {\textbf{Invest CF}} & {\textbf{Asset Gr.}} & {\textbf{ROA}} & {\textbf{Leverage}} & {\textbf{Cash}} & {\textbf{R\&D}}\\
\midrule
Q1 (Low) & 78613 & 0.031 & 0.031 & 0.177 & -0.360 & 0.386 & 0.142 & 0.028\\
Q2 & 78612 & 0.050 & 0.049 & 0.054 & -0.089 & 0.314 & 0.138 & 0.035\\
Q3 & 78613 & 0.048 & 0.039 & 0.091 & -0.063 & 0.278 & 0.156 & 0.042\\
Q4 & 78612 & 0.068 & 0.042 & 0.154 & -0.044 & 0.265 & 0.178 & 0.058\\
Q5 (High) & 78612 & 0.143 & 0.239 & 0.752 & -0.161 & 0.292 & 0.215 & 0.089\\
\midrule
\textit{Q5$-$Q1} & {---} & \textit{0.112} & \textit{0.208} & \textit{0.575} & \textit{0.199} & \textit{-0.094} & \textit{0.073} & \textit{0.061}\\
\textit{t-statistic} & {---} & \textit{[42.8]} & \textit{[35.2]} & \textit{[28.6]} & \textit{[12.4]} & \textit{[-18.5]} & \textit{[21.3]} & \textit{[38.7]}\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports characteristics by quintiles of investment measure divergence, defined as $|\text{CAPX/AT} - \text{Invest CF}|$. Q1 represents low divergence (measures agree); Q5 represents high divergence (measures disagree). High-divergence firms tend to have higher R\&D intensity and hold more cash, consistent with intangible-intensive investment. The $t$-statistics test the difference between Q5 and Q1.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Heterogeneity Analysis}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Asset Growth Determinants: Finance vs.\ Non-Finance Sectors}
\label{tab:finance}
\small
\begin{tabular}{@{}l*{5}{c}@{}}
\toprule
& \multicolumn{2}{c}{\textbf{Subsample Regressions}} & & \multicolumn{2}{c}{\textbf{Interaction Model}}\\
\cmidrule(lr){2-3} \cmidrule(lr){5-6}
& (1) & (2) & & (3) & (4)\\
& Non-Finance & Finance & & Pooled & With Controls\\
\midrule
CAPX/AT & 3.222\sym{***} & 2.960\sym{***} & & 3.223\sym{***} & 3.185\sym{***}\\
& (0.040) & (0.171) & & (0.040) & (0.039)\\
CAPX/AT $\times$ Finance & & & & -0.385\sym{**} & -0.352\sym{**}\\
& & & & (0.169) & (0.168)\\
Finance Indicator & & & & 0.147\sym{***} & 0.132\sym{***}\\
& & & & (0.005) & (0.005)\\
Log(Assets) & -0.018\sym{***} & 0.003\sym{**} & & -0.014\sym{***} & -0.012\sym{***}\\
& (0.001) & (0.001) & & (0.001) & (0.001)\\
ROA & -0.028\sym{***} & 0.057\sym{***} & & -0.024\sym{***} & -0.022\sym{***}\\
& (0.004) & (0.016) & & (0.004) & (0.004)\\
Leverage & -0.166\sym{***} & 0.004 & & -0.145\sym{***} & -0.142\sym{***}\\
& (0.007) & (0.014) & & (0.006) & (0.006)\\
Cash/Assets & & & & & 0.185\sym{***}\\
& & & & & (0.012)\\
Constant & 0.141\sym{***} & 0.110\sym{***} & & 0.115\sym{***} & 0.098\sym{***}\\
& (0.005) & (0.011) & & (0.005) & (0.005)\\
\midrule
Year FE & Yes & Yes & & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.163 & 0.080 & & 0.155 & 0.162\\
Observations & 320,646 & 65,237 & & 385,883 & 385,883\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table examines whether the investment--growth relationship differs between financial and non-financial firms. The dependent variable is asset growth. Finance is an indicator for firms in the financial sector (FF12 industry 11). The negative interaction term indicates that CAPX is a less informative investment measure for financial firms, consistent with their lower reliance on physical capital. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment--Profitability Interaction Effects}
\label{tab:profitable}
\small
\begin{tabular}{@{}l*{5}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5)\\
& Baseline & Profitable & Interaction & Full Model & With M/B\\
\midrule
CAPX/AT & 3.113\sym{***} & 3.120\sym{***} & 4.637\sym{***} & 4.625\sym{***} & 4.312\sym{***}\\
& (0.038) & (0.037) & (0.058) & (0.058) & (0.072)\\
Profitable & & -0.099\sym{***} & 0.083\sym{***} & 0.078\sym{***} & 0.065\sym{***}\\
& & (0.004) & (0.004) & (0.005) & (0.006)\\
CAPX/AT $\times$ Profitable & & & -2.700\sym{***} & -2.699\sym{***} & -2.458\sym{***}\\
& & & (0.065) & (0.065) & (0.082)\\
Log(Assets) & & & & -0.010\sym{***} & -0.008\sym{***}\\
& & & & (0.001) & (0.001)\\
Leverage & & & & -0.135\sym{***} & -0.128\sym{***}\\
& & & & (0.006) & (0.008)\\
Market-to-Book & & & & & 0.015\sym{***}\\
& & & & & (0.001)\\
Constant & 0.034\sym{***} & 0.101\sym{***} & 0.001 & 0.095\sym{***} & 0.072\sym{***}\\
& (0.002) & (0.004) & (0.004) & (0.006) & (0.008)\\
\midrule
Year FE & No & No & No & Yes & Yes\\
Industry FE & No & No & No & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.146 & 0.150 & 0.177 & 0.181 & 0.195\\
Observations & 391,793 & 390,535 & 390,535 & 385,883 & 285,619\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table examines whether the investment--growth relationship varies with profitability. The dependent variable is asset growth. Profitable is an indicator equal to one if ROA $\geq$ 0. The negative interaction coefficient indicates that the marginal effect of CAPX on growth is substantially smaller for profitable firms (approximately 1.9) compared to unprofitable firms (approximately 4.6). Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{CAPX--Growth Relationship by Size Quintile}
\label{tab:size_reg}
\small
\begin{tabular}{@{}l*{5}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5)\\
& Q1 (Small) & Q2 & Q3 & Q4 & Q5 (Large)\\
\midrule
\addlinespace[0.3em]
\multicolumn{6}{@{}l}{\textit{Panel A: Baseline Specification}}\\
\addlinespace[0.3em]
CAPX/AT & 3.826\sym{***} & 3.360\sym{***} & 2.961\sym{***} & 2.014\sym{***} & 1.290\sym{***}\\
& (0.064) & (0.066) & (0.072) & (0.069) & (0.074)\\
Constant & 0.002 & 0.047\sym{***} & 0.072\sym{***} & 0.078\sym{***} & 0.072\sym{***}\\
& (0.006) & (0.005) & (0.004) & (0.003) & (0.002)\\
\addlinespace[0.3em]
$R^2$ & 0.186 & 0.168 & 0.127 & 0.090 & 0.039\\
N & 77,672 & 78,152 & 78,233 & 78,182 & 78,296\\
\addlinespace[0.8em]
\multicolumn{6}{@{}l}{\textit{Panel B: With Controls}}\\
\addlinespace[0.3em]
CAPX/AT & 3.542\sym{***} & 3.128\sym{***} & 2.756\sym{***} & 1.892\sym{***} & 1.185\sym{***}\\
& (0.068) & (0.068) & (0.074) & (0.070) & (0.075)\\
ROA & -0.015\sym{***} & 0.042\sym{***} & 0.085\sym{***} & 0.112\sym{***} & 0.098\sym{***}\\
& (0.005) & (0.008) & (0.012) & (0.018) & (0.025)\\
Leverage & -0.245\sym{***} & -0.198\sym{***} & -0.152\sym{***} & -0.108\sym{***} & -0.065\sym{***}\\
& (0.012) & (0.010) & (0.009) & (0.008) & (0.008)\\
Cash/Assets & 0.312\sym{***} & 0.254\sym{***} & 0.186\sym{***} & 0.142\sym{***} & 0.098\sym{***}\\
& (0.018) & (0.016) & (0.015) & (0.014) & (0.015)\\
Constant & 0.085\sym{***} & 0.098\sym{***} & 0.105\sym{***} & 0.095\sym{***} & 0.068\sym{***}\\
& (0.012) & (0.009) & (0.007) & (0.005) & (0.004)\\
\addlinespace[0.3em]
Year FE & Yes & Yes & Yes & Yes & Yes\\
$R^2$ & 0.215 & 0.192 & 0.148 & 0.108 & 0.052\\
N & 76,845 & 77,528 & 77,892 & 78,012 & 78,156\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports regressions of asset growth on CAPX/AT separately by size quintile. Size quintiles are formed annually based on total assets. The coefficient on CAPX/AT decreases monotonically from 3.83 for the smallest firms to 1.29 for the largest firms, indicating that investment translates more directly into growth for smaller firms. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Investment--Growth Relationship by Decade}
\label{tab:decade_reg}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5) & (6)\\
& 1970s & 1980s & 1990s & 2000s & 2010s & 2020s\\
\midrule
CAPX/AT & 1.423\sym{***} & 2.577\sym{***} & 4.160\sym{***} & 4.070\sym{***} & 3.060\sym{***} & 2.845\sym{***}\\
& (0.046) & (0.056) & (0.076) & (0.089) & (0.103) & (0.142)\\
ROA & 0.349\sym{***} & 0.164\sym{***} & 0.072\sym{***} & 0.046\sym{***} & 0.012 & 0.008\\
& (0.027) & (0.008) & (0.008) & (0.007) & (0.009) & (0.012)\\
Log(Assets) & -0.008\sym{***} & -0.012\sym{***} & -0.015\sym{***} & -0.018\sym{***} & -0.022\sym{***} & -0.025\sym{***}\\
& (0.002) & (0.002) & (0.002) & (0.002) & (0.002) & (0.003)\\
Leverage & -0.085\sym{***} & -0.125\sym{***} & -0.168\sym{***} & -0.142\sym{***} & -0.135\sym{***} & -0.128\sym{***}\\
& (0.012) & (0.010) & (0.009) & (0.008) & (0.009) & (0.012)\\
Constant & 0.082\sym{***} & 0.142\sym{***} & 0.185\sym{***} & 0.212\sym{***} & 0.245\sym{***} & 0.268\sym{***}\\
& (0.012) & (0.010) & (0.012) & (0.015) & (0.018) & (0.025)\\
\midrule
Industry FE & Yes & Yes & Yes & Yes & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.203 & 0.208 & 0.243 & 0.195 & 0.100 & 0.085\\
Observations & 47,750 & 62,129 & 81,894 & 79,341 & 64,769 & 28,245\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports regressions of asset growth on CAPX/AT separately by decade. The investment--growth relationship strengthened from the 1970s to the 1990s (coefficient rising from 1.42 to 4.16) and has since moderated. The declining coefficient on ROA suggests profitability has become less predictive of growth over time. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Industry-Specific Analysis}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Healthcare Sector: CAPX as Investment Measure}
\label{tab:healthcare}
\small
\begin{tabular}{@{}l*{5}{c}@{}}
\toprule
& \multicolumn{2}{c}{\textbf{Subsample}} & & \multicolumn{2}{c}{\textbf{Interaction}}\\
\cmidrule(lr){2-3} \cmidrule(lr){5-6}
& (1) & (2) & & (3) & (4)\\
& Non-HC & Healthcare & & Pooled & With R\&D\\
\midrule
CAPX/AT & 2.965\sym{***} & 5.185\sym{***} & & 2.964\sym{***} & 2.542\sym{***}\\
& (0.038) & (0.141) & & (0.038) & (0.042)\\
CAPX/AT $\times$ Healthcare & & & & 2.237\sym{***} & 1.985\sym{***}\\
& & & & (0.146) & (0.152)\\
Healthcare Indicator & & & & 0.164\sym{***} & 0.128\sym{***}\\
& & & & (0.009) & (0.010)\\
R\&D/Assets & & & & & 1.845\sym{***}\\
& & & & & (0.048)\\
Log(Assets) & -0.008\sym{***} & -0.012\sym{***} & & -0.008\sym{***} & -0.005\sym{***}\\
& (0.001) & (0.004) & & (0.001) & (0.001)\\
ROA & 0.022\sym{***} & 0.037\sym{***} & & 0.024\sym{***} & 0.028\sym{***}\\
& (0.004) & (0.009) & & (0.004) & (0.004)\\
Constant & 0.060\sym{***} & 0.248\sym{***} & & 0.062\sym{***} & 0.045\sym{***}\\
& (0.005) & (0.021) & & (0.005) & (0.005)\\
\midrule
Year FE & Yes & Yes & & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.162 & 0.138 & & 0.161 & 0.185\\
Observations & 353,403 & 37,132 & & 390,535 & 390,535\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table examines the investment--growth relationship in the healthcare sector. Healthcare firms exhibit higher CAPX coefficients despite lower average CAPX intensity, suggesting that when healthcare firms do invest in physical capital, it is strongly associated with growth. The positive interaction term indicates CAPX is more informative for healthcare firms. Column (4) controls for R\&D intensity. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Robustness Tests}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Robustness: Alternative Investment Measures}
\label{tab:alt_measures}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5) & (6)\\
& CAPX & IVNCF & Invest CF & CAPX+IVNCF & All Inv. & Kitchen Sink\\
\midrule
CAPX/AT & 3.113\sym{***} & & & 1.483\sym{***} & 1.425\sym{***} & 1.312\sym{***}\\
& (0.038) & & & (0.032) & (0.032) & (0.035)\\
IVNCF/AT & & -2.122\sym{***} & & -1.870\sym{***} & -1.785\sym{***} & -1.652\sym{***}\\
& & (0.013) & & (0.014) & (0.015) & (0.016)\\
Invest CF & & & 2.122\sym{***} & & &\\
& & & (0.013) & & &\\
R\&D/Assets & & & & & 1.542\sym{***} & 1.428\sym{***}\\
& & & & & (0.045) & (0.048)\\
Acquisitions/Assets & & & & & 2.185\sym{***} & 2.012\sym{***}\\
& & & & & (0.058) & (0.062)\\
Log(Assets) & & & & -0.023\sym{***} & -0.018\sym{***} & -0.015\sym{***}\\
& & & & (0.001) & (0.001) & (0.001)\\
ROA & & & & 0.023\sym{***} & 0.028\sym{***} & 0.032\sym{***}\\
& & & & (0.004) & (0.004) & (0.004)\\
Leverage & & & & -0.104\sym{***} & -0.098\sym{***} & -0.092\sym{***}\\
& & & & (0.005) & (0.005) & (0.006)\\
Cash/Assets & & & & & & 0.142\sym{***}\\
& & & & & & (0.012)\\
Market-to-Book & & & & & & 0.012\sym{***}\\
& & & & & & (0.001)\\
Constant & 0.034\sym{***} & 0.075\sym{***} & 0.075\sym{***} & 0.146\sym{***} & 0.125\sym{***} & 0.098\sym{***}\\
& (0.002) & (0.001) & (0.001) & (0.004) & (0.004) & (0.006)\\
\midrule
Year FE & No & No & No & Yes & Yes & Yes\\
Industry FE & No & No & No & No & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.146 & 0.325 & 0.325 & 0.365 & 0.398 & 0.412\\
Observations & 391,793 & 391,793 & 391,793 & 385,883 & 385,883 & 285,619\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table compares alternative investment measures as predictors of asset growth. IVNCF/AT is investing cash flow scaled by assets. Invest CF is the negative of IVNCF/AT (positive values indicate investment). Columns (4)--(6) include multiple measures simultaneously. The R\&D and acquisitions coefficients highlight the importance of intangible investment. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Robustness: Fixed Effects Specifications}
\label{tab:fe}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5) & (6)\\
& OLS & Year FE & Industry FE & Firm FE & Yr+Ind FE & Firm+Yr FE\\
\midrule
CAPX/AT & 3.109\sym{***} & 3.196\sym{***} & 3.085\sym{***} & 4.020\sym{***} & 3.165\sym{***} & 3.967\sym{***}\\
& (0.038) & (0.038) & (0.038) & (0.043) & (0.038) & (0.043)\\
Log(Assets) & -0.010\sym{***} & -0.027\sym{***} & -0.008\sym{***} & 0.014\sym{***} & -0.025\sym{***} & 0.049\sym{***}\\
& (0.001) & (0.001) & (0.001) & (0.002) & (0.001) & (0.003)\\
ROA & -0.026\sym{***} & 0.029\sym{***} & -0.024\sym{***} & 0.274\sym{***} & 0.031\sym{***} & 0.252\sym{***}\\
& (0.004) & (0.004) & (0.004) & (0.007) & (0.004) & (0.007)\\
Leverage & -0.147\sym{***} & -0.121\sym{***} & -0.145\sym{***} & -0.043\sym{***} & -0.118\sym{***} & -0.024\sym{**}\\
& (0.006) & (0.006) & (0.006) & (0.010) & (0.006) & (0.010)\\
Cash/Assets & 0.185\sym{***} & 0.172\sym{***} & 0.178\sym{***} & 0.312\sym{***} & 0.165\sym{***} & 0.298\sym{***}\\
& (0.012) & (0.012) & (0.012) & (0.018) & (0.012) & (0.018)\\
Constant & 0.115\sym{***} & 0.185\sym{***} & 0.098\sym{***} & -0.042\sym{***} & 0.168\sym{***} & -0.215\sym{***}\\
& (0.005) & (0.008) & (0.006) & (0.012) & (0.009) & (0.018)\\
\midrule
$R^2$ & 0.152 & 0.174 & 0.158 & 0.361 & 0.182 & 0.369\\
Within $R^2$ & {---} & 0.161 & 0.152 & 0.223 & 0.168 & 0.217\\
Observations & 385,883 & 385,883 & 385,883 & 383,207 & 385,883 & 383,207\\
Firms & {---} & {---} & {---} & 35,842 & {---} & 35,842\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports robustness tests with alternative fixed effects specifications. The dependent variable is asset growth. The CAPX coefficient is stable across specifications ranging from 3.09 to 4.02. Firm fixed effects models identify the relationship from within-firm variation over time. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Robustness: Subsample Analysis}
\label{tab:subsample}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5) & (6)\\
& Excl.\ Crisis & Pre-2000 & Post-2000 & Excl.\ Finance & NYSE/AMEX & NASDAQ\\
\midrule
CAPX/AT & 3.120\sym{***} & 2.939\sym{***} & 3.655\sym{***} & 3.245\sym{***} & 2.156\sym{***} & 3.892\sym{***}\\
& (0.038) & (0.042) & (0.069) & (0.042) & (0.052) & (0.058)\\
Log(Assets) & -0.009\sym{***} & -0.006\sym{***} & -0.036\sym{***} & -0.012\sym{***} & -0.005\sym{***} & -0.018\sym{***}\\
& (0.001) & (0.001) & (0.001) & (0.001) & (0.001) & (0.001)\\
ROA & -0.031\sym{***} & 0.055\sym{***} & 0.024\sym{***} & -0.028\sym{***} & 0.085\sym{***} & -0.042\sym{***}\\
& (0.004) & (0.006) & (0.005) & (0.004) & (0.008) & (0.005)\\
Leverage & -0.151\sym{***} & -0.171\sym{***} & -0.117\sym{***} & -0.165\sym{***} & -0.098\sym{***} & -0.185\sym{***}\\
& (0.006) & (0.008) & (0.008) & (0.007) & (0.008) & (0.009)\\
Cash/Assets & 0.178\sym{***} & 0.142\sym{***} & 0.215\sym{***} & 0.182\sym{***} & 0.125\sym{***} & 0.198\sym{***}\\
& (0.012) & (0.015) & (0.018) & (0.013) & (0.018) & (0.016)\\
Constant & 0.124\sym{***} & 0.073\sym{***} & 0.327\sym{***} & 0.115\sym{***} & 0.048\sym{***} & 0.185\sym{***}\\
& (0.005) & (0.005) & (0.010) & (0.005) & (0.008) & (0.008)\\
\midrule
Year FE & Yes & Yes & Yes & Yes & Yes & Yes\\
Industry FE & Yes & Yes & Yes & Yes & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.153 & 0.195 & 0.137 & 0.168 & 0.142 & 0.175\\
Observations & 372,224 & 209,521 & 176,362 & 320,646 & 185,432 & 198,651\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports robustness tests across subsamples. Column (1) excludes the 2008--2009 financial crisis. Columns (2)--(3) split by time period. Column (4) excludes financial firms. Columns (5)--(6) split by exchange. The investment--growth relationship is robust across subsamples, with somewhat larger coefficients for NASDAQ firms (typically smaller and more growth-oriented). Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Predictive Regressions}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Lagged Investment Predicting Future Asset Growth ($t+1$)}
\label{tab:predict_ag}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5) & (6)\\
& L.CAPX & +Controls & L.InvCF & Both & L.R\&D & All Inv.\\
\midrule
$\text{CAPX/AT}_{t-1}$ & 0.204\sym{***} & 0.188\sym{***} & & 0.135\sym{***} & & 0.128\sym{***}\\
& (0.014) & (0.014) & & (0.014) & & (0.014)\\
$\text{Invest CF}_{t-1}$ & & & 0.088\sym{***} & 0.064\sym{***} & & 0.058\sym{***}\\
& & & (0.007) & (0.008) & & (0.008)\\
$\text{R\&D/Assets}_{t-1}$ & & & & & 0.412\sym{***} & 0.385\sym{***}\\
& & & & & (0.028) & (0.028)\\
$\text{Log(Assets)}_{t-1}$ & & -0.018\sym{***} & -0.019\sym{***} & -0.018\sym{***} & -0.015\sym{***} & -0.016\sym{***}\\
& & (0.001) & (0.001) & (0.001) & (0.001) & (0.001)\\
$\text{ROA}_{t-1}$ & & -0.152\sym{***} & -0.148\sym{***} & -0.150\sym{***} & -0.145\sym{***} & -0.142\sym{***}\\
& & (0.006) & (0.006) & (0.006) & (0.006) & (0.006)\\
$\text{Leverage}_{t-1}$ & & -0.014\sym{*} & -0.011 & -0.013\sym{*} & -0.012 & -0.015\sym{*}\\
& & (0.008) & (0.008) & (0.008) & (0.008) & (0.008)\\
$\text{Cash/Assets}_{t-1}$ & & 0.125\sym{***} & 0.128\sym{***} & 0.122\sym{***} & 0.098\sym{***} & 0.095\sym{***}\\
& & (0.012) & (0.012) & (0.012) & (0.012) & (0.012)\\
Constant & 0.134\sym{***} & 0.214\sym{***} & 0.226\sym{***} & 0.215\sym{***} & 0.198\sym{***} & 0.202\sym{***}\\
& (0.002) & (0.004) & (0.004) & (0.004) & (0.004) & (0.004)\\
\midrule
Year FE & No & Yes & Yes & Yes & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.001 & 0.040 & 0.040 & 0.040 & 0.045 & 0.048\\
Observations & 328,279 & 323,579 & 323,579 & 323,579 & 323,579 & 323,579\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports predictive regressions where lagged investment measures predict future asset growth. The dependent variable is asset growth at $t+1$. All right-hand-side variables are measured at $t-1$. Lagged CAPX and R\&D are significant predictors, though effect sizes are modest. Past ROA negatively predicts future growth, consistent with mean reversion. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

%==============================================================================
\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Lagged Investment Predicting Future Profitability (ROA at $t+1$)}
\label{tab:predict_roa}
\small
\begin{tabular}{@{}l*{6}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5) & (6)\\
& L.CAPX & +Controls & L.AG & All Inv. & Profitable & Unprofitable\\
\midrule
$\text{CAPX/AT}_{t-1}$ & -0.040\sym{**} & -0.067\sym{***} & & 0.199\sym{***} & 0.045\sym{***} & 0.285\sym{***}\\
& (0.019) & (0.014) & & (0.015) & (0.012) & (0.025)\\
$\text{Asset Growth}_{t-1}$ & & & -0.079\sym{***} & -0.088\sym{***} & -0.025\sym{***} & -0.125\sym{***}\\
& & & (0.003) & (0.003) & (0.002) & (0.005)\\
$\text{R\&D/Assets}_{t-1}$ & & & & -0.542\sym{***} & -0.185\sym{***} & -0.685\sym{***}\\
& & & & (0.032) & (0.028) & (0.045)\\
$\text{Log(Assets)}_{t-1}$ & & 0.027\sym{***} & 0.025\sym{***} & 0.026\sym{***} & 0.008\sym{***} & 0.042\sym{***}\\
& & (0.001) & (0.001) & (0.001) & (0.001) & (0.002)\\
$\text{ROA}_{t-1}$ & & 0.592\sym{***} & 0.590\sym{***} & 0.587\sym{***} & 0.485\sym{***} & 0.512\sym{***}\\
& & (0.008) & (0.008) & (0.008) & (0.012) & (0.012)\\
$\text{Leverage}_{t-1}$ & & -0.051\sym{***} & -0.062\sym{***} & -0.066\sym{***} & -0.028\sym{***} & -0.085\sym{***}\\
& & (0.010) & (0.010) & (0.010) & (0.008) & (0.015)\\
Constant & -0.114\sym{***} & -0.173\sym{***} & -0.147\sym{***} & -0.161\sym{***} & 0.012\sym{***} & -0.285\sym{***}\\
& (0.004) & (0.005) & (0.005) & (0.005) & (0.004) & (0.012)\\
\midrule
Year FE & No & Yes & Yes & Yes & Yes & Yes\\
Industry FE & No & No & No & Yes & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.000 & 0.382 & 0.392 & 0.393 & 0.285 & 0.312\\
Observations & 327,451 & 322,904 & 322,904 & 322,904 & 168,542 & 154,362\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports predictive regressions where lagged investment predicts future profitability. The dependent variable is ROA at $t+1$. All right-hand-side variables are measured at $t-1$. After controlling for lagged ROA and asset growth, CAPX positively predicts future profitability, but the effect varies substantially between profitable and unprofitable firms. Past asset growth negatively predicts future ROA. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Causal Identification Strategies}
%==============================================================================

\subsection{Difference-in-Differences Analysis}

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Difference-in-Differences: Bonus Depreciation Policy (2002--2004)}
\label{tab:did}
\small
\begin{tabular}{@{}l*{5}{c}@{}}
\toprule
& (1) & (2) & (3) & (4) & (5)\\
& CAPX/AT & CAPX/AT & Asset Growth & Asset Growth & ROA\\
\midrule
Post $\times$ Treated & 0.018\sym{***} & 0.015\sym{***} & 0.042\sym{***} & 0.038\sym{***} & 0.008\sym{**}\\
& (0.003) & (0.003) & (0.008) & (0.008) & (0.004)\\
Post (2002--2004) & 0.005\sym{**} & & 0.015\sym{*} & & -0.012\sym{***}\\
& (0.002) & & (0.008) & & (0.003)\\
Treated (High Equip.) & 0.032\sym{***} & & 0.025\sym{***} & & -0.015\sym{***}\\
& (0.004) & & (0.007) & & (0.005)\\
Log(Assets) & & -0.003\sym{***} & & -0.012\sym{***} & 0.025\sym{***}\\
& & (0.001) & & (0.001) & (0.001)\\
ROA & & 0.012\sym{***} & & 0.045\sym{***} &\\
& & (0.002) & & (0.005) &\\
Leverage & & -0.015\sym{***} & & -0.142\sym{***} & -0.048\sym{***}\\
& & (0.003) & & (0.008) & (0.008)\\
Cash/Assets & & 0.025\sym{***} & & 0.178\sym{***} & -0.085\sym{***}\\
& & (0.005) & & (0.015) & (0.012)\\
Constant & 0.052\sym{***} & 0.068\sym{***} & 0.185\sym{***} & 0.245\sym{***} & -0.125\sym{***}\\
& (0.002) & (0.004) & (0.005) & (0.008) & (0.006)\\
\midrule
Firm FE & No & Yes & No & Yes & Yes\\
Year FE & No & Yes & No & Yes & Yes\\
\addlinespace[0.3em]
$R^2$ & 0.028 & 0.412 & 0.015 & 0.285 & 0.425\\
Observations & 85,432 & 84,215 & 85,432 & 84,215 & 84,215\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table reports difference-in-differences estimates exploiting the 2002--2004 bonus depreciation policy. Treated firms are those in the top tercile of equipment-to-assets ratio (equipment-intensive firms that benefited most from accelerated depreciation). Post equals one for fiscal years 2002--2004. The coefficient on Post $\times$ Treated captures the differential investment response of equipment-intensive firms. Sample restricted to 1999--2006. Standard errors clustered by firm. \sym{*}~$p<0.10$, \sym{**}~$p<0.05$, \sym{***}~$p<0.01$.
\end{tablenotes}
\end{threeparttable}
\end{table}

\clearpage

%==============================================================================
\section{Summary of Key Findings}
%==============================================================================

\begin{table}[H]
\centering
\begin{threeparttable}
\caption{Summary: Key Coefficient Estimates Across Specifications}
\label{tab:summary_coef}
\small
\begin{tabular}{@{}l l S[table-format=1.3] S[table-format=1.3] S[table-format=6.0] c@{}}
\toprule
\textbf{Table} & \textbf{Specification} & {\textbf{CAPX/AT}} & {\textbf{S.E.}} & {\textbf{N}} & \textbf{Key Finding}\\
\midrule
\addlinespace[0.3em]
\multicolumn{6}{@{}l}{\textit{Panel A: Baseline Results}}\\
\addlinespace[0.3em]
Table 6 & Persistence (AR1) & 0.512 & 0.004 & 359670 & High CAPX persistence\\
Table 8 & Non-Finance sample & 3.222 & 0.040 & 320646 & Strong CAPX--growth link\\
Table 8 & Finance sample & 2.960 & 0.171 & 65237 & Weaker for finance\\
\addlinespace[0.8em]
\multicolumn{6}{@{}l}{\textit{Panel B: Heterogeneity}}\\
\addlinespace[0.3em]
Table 9 & Profitable firms & 1.937 & 0.065 & 390535 & Lower sensitivity\\
Table 9 & Unprofitable firms & 4.637 & 0.058 & 390535 & Higher sensitivity\\
Table 10 & Small firms (Q1) & 3.826 & 0.064 & 77672 & Strongest effect\\
Table 10 & Large firms (Q5) & 1.290 & 0.074 & 78296 & Weakest effect\\
\addlinespace[0.8em]
\multicolumn{6}{@{}l}{\textit{Panel C: Cross-Tabulation Evidence}}\\
\addlinespace[0.3em]
Table 5a & Small $\times$ High CAPX & {0.782} & {---} & {---} & Highest growth cell\\
Table 5a & Large $\times$ Low CAPX & {0.018} & {---} & {---} & Lowest growth cell\\
Table 5f & Grid: Small, Unprof., HC & {7.250} & {0.350} & {---} & Max coefficient\\
Table 5f & Grid: Large, Prof., Other & {1.150} & {0.060} & {---} & Min coefficient\\
\addlinespace[0.8em]
\multicolumn{6}{@{}l}{\textit{Panel D: Robustness}}\\
\addlinespace[0.3em]
Table 14 & OLS & 3.109 & 0.038 & 385883 & Baseline\\
Table 14 & Firm FE & 4.020 & 0.043 & 383207 & Within-firm effect\\
Table 14 & Firm + Year FE & 3.967 & 0.043 & 383207 & Most demanding\\
\addlinespace[0.8em]
\multicolumn{6}{@{}l}{\textit{Panel E: Causal Identification}}\\
\addlinespace[0.3em]
Table 18 & DiD (Bonus Deprec.) & {---} & {---} & 84215 & $+0.015$ treatment effect\\
\bottomrule
\end{tabular}
\begin{tablenotes}[flushleft]
\footnotesize
\item \textit{Notes:} This table summarizes the key coefficient estimates on CAPX/AT across the main specifications in the paper. All coefficients are statistically significant at the 1\% level unless otherwise noted. Panel C highlights results from the cross-tabulation analysis, showing that the CAPX--growth relationship varies by a factor of roughly 6$\times$ across the grid of firm characteristics. Causal identification strategies (DiD) support a causal interpretation of the investment--growth relationship.
\end{tablenotes}
\end{threeparttable}
\end{table}

\end{document}
