Note(s): This table reports the results of multivariate DID regressions on the number of M&As for the pilot and the control firms over the periods before, during, and after Regulation SHO's pilot program. We categorize all firms into two groups according to agency cost of free cash flow (Agency^FCF). We construct Agency^FCF in two steps. First, we use Tobin's q to measure a firm's growth opportunities. We sort the firms by Tobin's q into quartiles and classify the firms in the top quartile as the high-growth-opportunities firms. For those firms, a high level of free cash flow is not an issue, so we set their Agency^FCF as zero. The firms not in the top quartile are low-growth-opportunities firms. We calculate their Agency^FCF using the scaled free cash flow

$Agencyi,tFCF=INCi,t−TAXi,t−INTEXPi,t−PEDDIVi,t−COMDIVi,tAsseti,t,$

where INC_i,t is operating income before depreciation (Compustat item No. 13); TAX_i,t is total income tax (Compustat item No. 16) minus change in deferred taxes from the previous year to the current year (change in Compustat item No. 35); INTEXP_i,t is gross interest expense on short-and long-term debt (Compustat item No.15); PEDDIV_i,t (Compustat item No. 21) and COMDIV_i,t (Compustat item No. 19) are dividends on preferred shares and common shares, respectively. Using the measures of Agency^FCFat 2003, we group all firms into two subsamples. We define a firm with an Agency^FCF value above the median as a high-Agency^FCF firm and a firm with an Agency^FCF value below the median as a low-Agency^FCF firm

We estimate the multivariate DID panel regression as follows

Ln_(1 + Count_i,t) = α₀ + β₁Pilot_i×During_t + β₂Pilot_i×After_t + β₃Pilot_i + β₄During_t + β₅After_t + β₆X_i,t + ɛ_i,t

In this model, Ln_(1 + Count_i,t) is the natural logarithm of (1 + Count_i,t), while Count_i,t is the total number of value-destroying M&As, including either cross-industry M&As or those with a negative CAR, announced by firm i in a given year t. Pilot_i equals one if firm i belongs to the pilot group and zero otherwise. After_t is a dummy variable that equals one if the year is during the Post period (2007 to 2010). X_i,t is the set of controlling variables including return on assets (ROA), market-to-book ratio (MB_Ratio), leverage (Leverage), size (Ln_MV), sales (Ln_Sales), capital expenditures (CAPEX), R&D expenditures (RDX) and cash and short-term investment (Cash). If we add a firm fixed effect in the panel regression, we omit Pilot_i in that column to avoid multicollinearity. We cluster the standard errors at the firm level. The Chi-square test statistic (χ²) indicates whether the coefficient of Pilot × During differs significantly between the two subsamples. For simplicity, we do not report the coefficients of the control variables. ^***, ^** and ^* denote significance at the 1%, 5% and 10% level, respectively