Takeover Vulnerability and Pre-Emptive Earnings Management

Figures & data

Table 1. Descriptive statistics.

	N	Mean	SD	p25	p50	p75
Variables	(1)	(2)	(3)	(4)	(5)	(6)
Panel A: Main variables
Target	24,454	0.049	0.217	0.000	0.000	0.000
Vulnerability	24,454	0.051	0.028	0.028	0.051	0.071
REM	21,928	0.004	0.503	−0.174	0.025	0.236
REMprod	21,928	−0.002	0.226	−0.089	0.000	0.103
REMdisx	24,335	0.001	0.390	−0.112	0.020	0.164
REMcfo	24,333	−0.002	0.339	−0.077	−0.005	0.051
AEM	23,211	−0.003	0.394	−0.054	0.000	0.057
Premium	1115	43.767	38.091	21.210	37.860	58.900
Panel B: Control variables – Firm financial characteristics
Abnormal returns	24,454	0.000	0.003	−0.001	0.000	0.001
Profitability	24,454	0.006	0.284	−0.029	0.070	0.134
Tobin's q	24,454	1.902	1.953	1.000	1.350	2.020
Market to book	24,454	1.601	2.146	0.560	0.987	1.766
Sales growth	24,454	0.266	0.977	−0.036	0.075	0.240
Liquidity	24,454	0.151	0.181	0.030	0.085	0.196
Leverage	24,454	0.189	0.194	0.025	0.151	0.283
Debt issue	20,936	1.011	5.250	−0.251	0.000	0.374
Growth-resource	24,454	0.151	0.358	0.000	0.000	0.000
Disturbance	24,454	0.729	0.445	0.000	1.000	1.000
Firm size	24,454	18.141	2.239	16.615	17.923	19.511
Free cash flow	24,454	−0.035	0.236	−0.057	0.018	0.070
Tangible assets	24,454	0.282	0.254	0.066	0.215	0.431
Firm age	24,454	2.339	1.034	1.609	2.398	3.296
Block holders	24,454	0.223	0.252	0.000	0.130	0.420
Z–Score	20,630	80.121	339.054	3.348	9.099	20.637
Net operating assets	24,264	1.740	6.032	0.255	0.499	1.075
Panel C: Control variables – Corporate governance characteristics
Audit quality	24,454	0.027	0.158	0.000	0.001	0.005
Gender diversity	12,169	0.068	0.102	0.000	0.000	0.143
Board independence	12,169	0.384	0.226	0.250	0.429	0.556
Director experience	12,160	54.498	4.514	51.800	54.667	57.429
Board tenure	12,160	5.813	3.597	3.356	5.000	7.411
Audit committee	12,169	0.962	0.190	1.000	1.000	1.000
Panel D: Control variables – M&A characteristics
Cash payment	1208	0.762	0.426	1.000	1.000	1.000
Crossborder	1208	0.288	0.453	0.000	0.000	1.000
Bid attitude	1208	0.913	0.282	1.000	1.000	1.000
Competing bids	1208	0.099	0.299	0.000	0.000	0.000
Diversifying bids	1208	0.563	0.496	0.000	1.000	1.000
Panel E: Other variables (including instruments)
Merger intensity	17,819	1.092	0.920	0.000	1.099	1.792
Industry rumors	24,454	0.022	0.038	0.000	0.010	0.030
LTIP	13,388	0.073	0.106	0.000	0.000	0.135
Concentration	24,454	0.238	0.198	0.102	0.188	0.301
Sentiment	23,136	0.091	0.160	0.010	0.138	0.209

Note: The table presents the descriptive statistics for key variables used in the study. All continuous variables are winsorised at the 1st and 99th percentile to eliminate outliers. Full variable definitions are available in Appendix A1.

Table 2. Estimating firm vulnerability to future takeovers.

Panel A: Regression coefficients and descriptive statistics
	Logit regression coefficients:			Descriptive statistics of yearly regression
	Pooled sample			coefficients
	Pred.	Margins	P-value	Mean	SD	Min	Max
Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)
Abnormal returns	−	−1.894***	(0.000)	−49.486	73.702	−210.146	145.630
Profitability	−	−0.000	(0.964)	−0.010	0.361	−1.008	0.859
Tobin's q	−	−0.005***	(0.000)	−0.232	0.230	−0.619	0.086
Sales growth	$+/-$	−0.003*	(0.098)	−0.245	0.454	−1.848	0.289
Liquidity	$+/-$	−0.013	(0.210)	−0.188	1.303	−2.673	2.193
Leverage	$+/-$	0.008	(0.357)	−0.087	0.909	−2.201	1.478
Growth-resource	+	−0.000	(0.916)	−0.012	0.415	−1.109	0.607
Disturbance	+	0.003	(0.325)	0.087	0.456	−0.938	0.875
Firm size	+	0.136***	(0.000)	3.642	2.166	−0.426	7.412
Firm size#Firm size	−	−0.004***	(0.000)	−0.094	0.058	−0.197	0.012
Free cash flow	+	0.040***	(0.002)	0.910	1.698	−2.043	5.583
Tangible assets	+	0.008	(0.190)	0.193	0.869	−1.348	2.223
Firm age	−	−0.007***	(0.000)	−0.252	0.324	−1.549	0.035
Block holders	+	0.006	(0.430)	0.016	0.894	−2.474	1.975
Observations		24,802
Firm FE		Yes
Year FE		Yes
${\chi }^2$		460	(0.000)
Pseudo $R^2$		0.057
Panel B: Within sample performance diagnostics: Goodness-of-fit of prediction versus null model
	Prediction	vs	Null
McFadden's $R^2$	6.2%		3.5%
Maximum Likelihood $R^2$	2.4%		1.2%
McKelvery and Zaroina's $R^2$	23.2%		8.9%
Cragg and Uhler's $R^2$	7.4%		4.1%
Efron's $R^2$	2.6%		1.4%
Area under ROC curve	69.9%		50.0%

Note: The table presents the regression results for Equation (1(1) $\mathrm{Takeover}\mathrm{Likelihoo}{d}_{\mathrm{it}}=\frac{1}{1+e^{-Z_{\mathrm{it}-1}}}$(1) ) which estimates each firm's takeover likelihood from a vector of its characteristics. The dependent variable takes a value of one if a firm receives a takeover bid in the next period and a value of zero otherwise. All predictor variables are fully defined in Appendix A1. The marginal effects presented in column 2 are generated from the entire sample (1987–2016). P-values are presented in parentheses. We present descriptive statistics for coefficients generated from yearly regressions in columns 3 to 6. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 3. Vulnerability, actual takeovers and earnings management.

Panel A: Vulnerability and future (actual) takeovers
		Within 1 Year		Within 3 Years		Within 5 Years
Quintile	Total	Bids	%.	Bids	%.	Count	%
Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)
Q1	4899	107	2.2%	326	6.7%	515	10.5%
Q2	4888	196	4.0%	533	10.9%	768	15.7%
Q3	4896	241	4.9%	670	13.7%	937	19.1%
Q4	4888	307	6.3%	771	15.8%	1079	22.1%
Q5	4883	357	7.3%	855	17.5%	1187	24.3%
Total	24,454	1208	4.9%	3155	12.9%	4486	18.3%
Panel B: Vulnerability and earnings management: Univariate analysis
		Vulnerability quintiles						Median vulnerability
Quintile	All	Q1	Q2	Q3	Q4	Q5	Q5-Q1	Low	High	Diff.
Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Means of earnings management proxies
REM	0.004	−0.046	−0.026	0.013	0.041	0.037	0.083${}^{\ast \ast \ast }$	−0.026	0.035	0.060${}^{\ast \ast \ast }$
REMprod	−0.002	−0.010	−0.012	0.000	0.011	0.002	0.012${}^{\ast \ast }$	−0.009	0.007	0.016${}^{\ast \ast \ast }$
REMdisx	0.001	−0.044	−0.019	0.011	0.024	0.031	0.075${}^{\ast \ast \ast }$	−0.023	0.024	0.047${}^{\ast \ast \ast }$
REMcfo	−0.002	0.049	0.005	−0.008	−0.021	−0.035	−0.084${}^{\ast \ast \ast }$	0.018	−0.022	−0.039${}^{\ast \ast \ast }$
AEM	−0.003	−0.012	−0.001	0.007	0.002	−0.013	−0.001	−0.003	−0.003	−0.000
Medians of earnings management proxies
REM	0.025	0.003	0.007	0.028	0.041	0.047	0.044${}^{\ast \ast \ast }$	0.012	0.041	0.029${}^{\ast \ast \ast }$
REMprod	0.000	0.000	0.000	0.000	0.000	0.002	0.002${}^{\ast }$	0.000	0.001	0.001${}^{\ast }$
REMdisx	0.020	0.006	0.007	0.019	0.029	0.036	0.030${}^{\ast \ast \ast }$	0.011	0.031	0.020${}^{\ast \ast \ast }$
REMcfo	−0.005	0.000	0.000	−0.003	−0.008	−0.020	−0.020${}^{\ast \ast \ast }$	−0.000	−0.013	−0.013${}^{\ast \ast \ast }$
AEM	0.000	0.000	0.000	0.001	0.000	0.000	0.000	0.000	0.000	0.000

Note: Panel A of the table assesses the out-of-sample predictive ability of the proxy for vulnerability. We rank all firms in each year by their vulnerability measure, then split them into 5 equal groups (quintiles). Q1 (Q5) represents the 20% of firms with lowest (highest) vulnerability. We then explore whether firms in each quintile receive takeover bids within the next year (within 1 year), 3 years (within 3 years) and 5 years (within 5 years). ‘Total’ indicates the number of firms in each quintile. ‘Bids’ indicates the number of actual targets in each quintile. ‘%’ (percentage) indicates the proportion of firms in each quintile (‘Total’) that receive ‘Bids’ each year. Panel B of the table presents the means and medians of measures of earnings management (EM) across quintiles of vulnerability. Q5-Q1 presents the difference in mean and median of EM proxies. All variables are fully defined in Appendix A1. For mean differences, statistical significance is based on p-values from difference of means (t) test. For median differences, we use p-values of chi-square (continuity corrected) from a difference of median test. P-values are untabulated for brevity. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistically significant difference at the 1%, 5% and 10% levels, respectively.

Table 4. Vulnerability and earnings management: Real vs accrual.

		Specific REM channels				Trade-offs
	REM	REMprod	REMdisx	REMcfo	AEM	REM
Variables	(1)	(2)	(3)	(4)	(5)	(6)
Vulnerability	1.073***	0.602***	0.521***	−0.385**	−0.091	0.956***
	(0.000)	(0.000)	(0.000)	(0.020)	(0.569)	(0.000)
Vulnerability#AEM						1.597***
						(0.008)
AEM						−0.051
						(0.222)
Profitability	−0.011	−0.075***	0.073***	−0.115***	0.011	0.033
	(0.684)	(0.000)	(0.001)	(0.000)	(0.555)	(0.384)
Firm size	0.018***	0.011***	0.006***	0.005***	−0.005***	0.017***
	(0.000)	(0.000)	(0.000)	(0.003)	(0.007)	(0.000)
Market to book	−0.037***	−0.013***	−0.023***	−0.002	−0.000	−0.032***
	(0.000)	(0.000)	(0.000)	(0.358)	(0.935)	(0.000)
Debt issue	−0.001	−0.000	−0.001*	−0.000	0.000	−0.003***
	(0.211)	(0.961)	(0.081)	(0.924)	(0.990)	(0.002)
Leverage	−0.002	−0.067***	0.055**	−0.005	0.020	0.004
	(0.944)	(0.000)	(0.013)	(0.712)	(0.296)	(0.887)
Free cash flow	0.020	−0.077***	0.131***	−0.216***	0.066**	−0.100**
	(0.662)	(0.000)	(0.000)	(0.000)	(0.017)	(0.020)
Block holders	−0.048**	−0.005	−0.042***	0.019**	−0.029	−0.060***
	(0.025)	(0.600)	(0.007)	(0.047)	(0.210)	(0.003)
Z score	−30.093**	−7.746	−33.053***	12.393**	15.699	−17.113
	(0.016)	(0.200)	(0.000)	(0.014)	(0.194)	(0.151)
Net operating assets	0.003***	0.001***	0.002***	−0.001*	−0.002	0.002***
	(0.000)	(0.000)	(0.001)	(0.092)	(0.550)	(0.003)
Audit quality	0.070*	0.022	0.062*	−0.026	0.007	0.077**
	(0.066)	(0.122)	(0.067)	(0.375)	(0.648)	(0.017)
Constant	−0.343***	−0.181***	−0.151***	−0.063**	0.104***	−0.327***
	(0.000)	(0.000)	(0.000)	(0.042)	(0.003)	(0.000)
Observations	17,076	17,076	17,547	17,498	17,082	17,893
R-squared	0.062	0.049	0.066	0.046	0.011	0.054
Adj.R${}^2$	0.060	0.047	0.064	0.044	0.009	0.051
Industry FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes
F stat	17.03	15.63	14.69	12.48	1.898	14.10
Prob > F	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
Highest VIF	2.070	2.070	2.080	2.080	2.080	2.120

Note: This table presents the coefficient estimates from OLS regressions exploring the relationship between vulnerability to takeovers and earnings management (EM) and the trade-off between real and accrual EM by vulnerable firms. The base model is specified in Equation (2(2) $E{M}_{\mathrm{it}}={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}$(2) ). The model controls for firm characteristics that influence the EM decision, as well as industry and year fixed effects. All independent variables in columns 1 to 5 are lagged by one year. Column 6 explores contemporaneous relationships. All variables are fully defined in Appendix A1. P-values (from robust standard errors) are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 5. Pre-emptive earnings management and future takeovers.

	Full sample		Three-way interaction		Entrenchment
					High	Low
Variables	(1)	(2)	(3)	(4)	(5)	(6)
Vulnerability#REM#Entrenched			−9.959${}^{\ast \ast }$
			(0.027)
Vulnerability#AEM#Entrenched				−1.526
				(0.830)
Vulnerability#REM	0.569		2.368		−7.567${}^{\ast \ast }$	0.778
	(0.597)		(0.492)		(0.012)	(0.816)
Vulnerability#AEM		−0.229		0.904
		(0.830)		(0.897)
Vulnerability#Entrenched			5.267${}^{\ast \ast }$	3.938${}^{\ast }$
			(0.041)	(0.093)
REM#Entrenched			0.482${}^{\ast }$
			(0.093)
AEM#Entrenched				0.031
				(0.938)
Vulnerability	−1.092	−0.067	−1.846	−1.713	2.880	−2.494
	(0.375)	(0.964)	(0.559)	(0.564)	(0.529)	(0.526)
REM	−0.066		−0.186		0.323${}^{\ast }$	−0.103
	(0.355)		(0.404)		(0.094)	(0.627)
AEM		0.057		0.061
		(0.528)		(0.874)
Entrenchment			−0.438${}^{\ast \ast }$	−0.354${}^{\ast \ast }$
			(0.016)	(0.035)
Abnormal returns	−4.834	−1.013	3.577	−5.427	12.994	−8.729
	(0.473)	(0.881)	(0.753)	(0.612)	(0.386)	(0.618)
Profitability	0.032	0.050	0.056	0.077	0.083	0.011
	(0.308)	(0.129)	(0.393)	(0.202)	(0.353)	(0.908)
Tobin's q	−0.026${}^{\ast }$	−0.017	−0.045	−0.045	−0.023	−0.080${}^{\ast \ast }$
	(0.092)	(0.222)	(0.185)	(0.131)	(0.614)	(0.037)
Sales growth	0.011	0.003	0.054${}^{\ast }$	0.019	0.070${}^{\ast \ast }$	0.009
	(0.564)	(0.851)	(0.063)	(0.501)	(0.040)	(0.874)
Liquidity	−0.126	−0.162	−0.002	−0.138	0.022	−0.233
	(0.321)	(0.161)	(0.993)	(0.480)	(0.938)	(0.403)
Leverage	0.065	0.054	−0.010	0.015	−0.426${}^{\ast }$	0.430${}^{\ast }$
	(0.529)	(0.592)	(0.955)	(0.927)	(0.099)	(0.081)
Growth-resource	0.026	0.028	0.048	0.044	0.008	0.067
	(0.544)	(0.506)	(0.509)	(0.517)	(0.937)	(0.503)
Disturbance	0.092${}^{\ast \ast }$	0.094${}^{\ast \ast }$	0.212${}^{\ast \ast \ast }$	0.231${}^{\ast \ast \ast }$	0.203${}^{\ast }$	0.242${}^{\ast \ast }$
	(0.023)	(0.021)	(0.007)	(0.003)	(0.073)	(0.030)
Firm size	1.296${}^{\ast \ast \ast }$	1.083${}^{\ast \ast \ast }$	0.492	0.644	0.660	0.248
	(0.000)	(0.000)	(0.224)	(0.110)	(0.307)	(0.650)
Firm size#Firm size	−0.033${}^{\ast \ast \ast }$	−0.028${}^{\ast \ast \ast }$	−0.012	−0.016	−0.016	−0.007
	(0.000)	(0.000)	(0.241)	(0.124)	(0.343)	(0.624)
Free cash flow	0.209${}^{\ast }$	0.125	0.236	0.129	0.444	0.193
	(0.098)	(0.362)	(0.317)	(0.543)	(0.151)	(0.621)
Tangible assets	0.144${}^{\ast }$	0.089	0.087	0.078	0.120	−0.002
	(0.065)	(0.259)	(0.549)	(0.568)	(0.534)	(0.992)
Firm age	−0.074${}^{\ast \ast \ast }$	−0.068${}^{\ast \ast \ast }$	−0.044	−0.110${}^{\ast \ast \ast }$	−0.096${}^{\ast }$	−0.018
	(0.000)	(0.001)	(0.265)	(0.003)	(0.091)	(0.738)
Block holders	0.021	0.021	0.190	0.111	−0.017	0.428${}^{\ast \ast }$
	(0.815)	(0.803)	(0.163)	(0.384)	(0.923)	(0.040)
Constant	−13.882${}^{\ast \ast \ast }$	−11.932${}^{\ast \ast \ast }$	−7.430${}^{\ast \ast }$	−8.431${}^{\ast \ast }$	−9.299	−5.022
	(0.000)	(0.000)	(0.046)	(0.023)	(0.113)	(0.321)
Observations	19,307	20,477	8731	9726	4494	3880
Industry FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes
${\chi }^2$	332.1	340.8	155.7	195.9	95.85	92.31
Prob (${\chi }^2$)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
Highest VIF	1.350	1.390	1.390	1.430	1.460	1.470
Pseudo R${}^2$	0.053	0.050	0.076	0.078	0.081	0.078

Note: This table presents the probit regression estimates from Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) which explores the takeover deterrent effect of earnings management (EM). Columns 1 and 2 presents coefficient estimates of Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) based on our entire sample. Columns 3 and 4 present coefficient estimates of Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) when interacted with the entrenchment indicator. Columns 5 and 6 presents coefficient estimates of Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) from two sub-samples; high and low entrenchment firms. We define high (low) entrenchment as a sub-sample of firms in which the value of compensation made up of long term incentive plans (LTIP) as a proportion total compensation (averaged across all board members) is less (greater) than the 2-digit SIC code industry-year median value. The model controls for firm characteristics that influence takeover likelihood, as well as industry and year fixed effects. All variables are fully defined in Appendix A1. P-values are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 6. Target earnings management and merger premiums.

	All firms		Vulnerability
			Low	High
Variables	(1)	(2)	(3)	(4)
Vulnerability#REM	136.966${}^{\ast \ast }$
	(0.048)
Vulnerability#AEM		123.109
		(0.243)
Vulnerability	29.021	4.684
	(0.547)	(0.919)
REM	−5.992		−6.415	5.852${}^{\ast \ast }$
	(0.278)		(0.195)	(0.025)
AEM		−14.839${}^{\ast \ast \ast }$
		(0.000)
Profitability	0.146	−3.261	1.749	−0.399
	(0.987)	(0.688)	(0.903)	(0.973)
Firm size	−1.917${}^{\ast \ast \ast }$	−1.890${}^{\ast \ast \ast }$	−2.871${}^{\ast \ast \ast }$	0.227
	(0.003)	(0.004)	(0.000)	(0.851)
Market to book	−0.602	−0.629	−0.872	−1.041
	(0.340)	(0.276)	(0.382)	(0.230)
Debt issue	−0.016	−0.090	0.194	−0.030
	(0.932)	(0.593)	(0.646)	(0.887)
Leverage	−1.505	−1.753	−13.868	12.216
	(0.841)	(0.815)	(0.210)	(0.246)
Free cash flow	−16.869	−13.912	−18.890	−24.544
	(0.219)	(0.322)	(0.373)	(0.194)
Block holders	−10.576${}^{\ast }$	−11.036${}^{\ast }$	−22.975${}^{\ast \ast }$	2.149
	(0.086)	(0.069)	(0.029)	(0.809)
Cash payment	8.599${}^{\ast \ast \ast }$	9.785${}^{\ast \ast \ast }$	6.376${}^{\ast }$	9.642${}^{\ast \ast \ast }$
	(0.000)	(0.000)	(0.062)	(0.001)
Cross border	4.753${}^{\ast \ast }$	4.153${}^{\ast }$	6.597${}^{\ast }$	3.117
	(0.043)	(0.085)	(0.063)	(0.360)
Bid attitude	6.568${}^{\ast \ast }$	5.383${}^{\ast }$	6.658	8.023${}^{\ast }$
	(0.039)	(0.082)	(0.104)	(0.070)
Competing bids	19.955${}^{\ast \ast \ast }$	18.973${}^{\ast \ast \ast }$	20.931${}^{\ast \ast \ast }$	18.937${}^{\ast \ast \ast }$
	(0.000)	(0.000)	(0.000)	(0.000)
Diversifying bids	−1.339	−1.307	−2.351	−1.410
	(0.507)	(0.518)	(0.467)	(0.607)
Constant	73.014${}^{\ast \ast \ast }$	73.121${}^{\ast \ast \ast }$	97.792${}^{\ast \ast \ast }$	29.002
	(0.000)	(0.000)	(0.000)	(0.248)
Observations	1291	1349	538	737
Industry FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
F stat	5.177	5.143	3.660	3.656
Prob > F	(0.000)	(0.000)	(0.000)	(0.000)
Highest VIF	2.680	2.620	2.890	3.020
Adj.R${}^2$	0.125	0.112	0.139	0.131

Note: This table presents the coefficient estimates from OLS regressions exploring the relationship between pre-emptive EM and subsequent merger premiums. The model is specified in Equation (4(4) $\begin{array}{rl}\mathrm{Premiu}{m}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(4) ). The model controls for target firm characteristics that influence merger premiums, deal characteristics, as well as industry and year fixed effects. All variables are fully defined in Appendix A1. P-values (from robust standard errors) are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 7. Vulnerability and earnings management; Additional tests.

	Performance (ROCE)		Suspect firms		The impact of merger intensity
Dependent variable	REM		REM		REM	AEM	REM	AEM
Sub-sample	Low ROCE (Q1)	High ROCE (Q5)	Suspects	Non-suspects	All	All	All	All
Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Vulnerability	1.507${}^{\ast \ast \ast }$	1.177${}^{\ast \ast \ast }$	1.282${}^{\ast \ast \ast }$	1.112${}^{\ast \ast \ast }$			0.039	−0.199
	(0.007)	(0.004)	(0.006)	(0.000)			(0.879)	(0.306)
Merger intensity					0.016${}^{\ast \ast }$	−0.003	−0.048${}^{\ast \ast \ast }$	−0.014${}^{\ast \ast }$
					(0.012)	(0.333)	(0.002)	(0.037)
Vulnerability # Merger intensity							1.128${}^{\ast \ast \ast }$	0.176${}^{\ast \ast }$
							(0.000)	(0.047)
Profitability	0.102${}^{\ast \ast }$	−0.086	0.069	−0.027	−0.012	0.002	−0.033	0.005
	(0.045)	(0.260)	(0.509)	(0.352)	(0.709)	(0.947)	(0.319)	(0.822)
Firm size	0.005	0.020${}^{\ast \ast \ast }$	0.023${}^{\ast \ast \ast }$	0.019${}^{\ast \ast \ast }$	0.022${}^{\ast \ast \ast }$	−0.007${}^{\ast \ast \ast }$	0.022${}^{\ast \ast \ast }$	−0.007${}^{\ast \ast \ast }$
	(0.351)	(0.000)	(0.000)	(0.000)	(0.000)	(0.006)	(0.000)	(0.007)
Market to book	−0.041${}^{\ast \ast \ast }$	−0.024${}^{\ast \ast \ast }$	−0.017${}^{\ast }$	−0.040${}^{\ast \ast \ast }$	−0.040${}^{\ast \ast \ast }$	0.000	−0.040${}^{\ast \ast \ast }$	−0.000
	(0.000)	(0.000)	(0.052)	(0.000)	(0.000)	(0.889)	(0.000)	(0.942)
Debt issue	0.000	−0.003	0.000	−0.001	−0.000	0.000	−0.001	0.000
	(0.983)	(0.176)	(0.977)	(0.147)	(0.840)	(0.929)	(0.486)	(0.885)
Leverage	−0.004	−0.069	0.075	−0.015	0.004	0.027	−0.022	0.027
	(0.963)	(0.297)	(0.318)	(0.629)	(0.907)	(0.267)	(0.547)	(0.281)
Free cash flow	0.009	−0.023	0.005	0.019	0.060	0.081${}^{\ast \ast }$	0.025	0.081${}^{\ast \ast }$
	(0.899)	(0.817)	(0.963)	(0.702)	(0.272)	(0.013)	(0.652)	(0.018)
Block holders	0.110	−0.095${}^{\ast }$	−0.006	−0.054${}^{\ast \ast }$	−0.038	−0.034	−0.045	−0.042
	(0.108)	(0.076)	(0.928)	(0.019)	(0.182)	(0.295)	(0.113)	(0.195)
Z score	−12.962	−32.433	−8.217	−33.244${}^{\ast \ast }$	−43.803${}^{\ast \ast \ast }$	19.795	−48.154${}^{\ast \ast \ast }$	21.126
	(0.669)	(0.181)	(0.813)	(0.013)	(0.004)	(0.215)	(0.002)	(0.199)
Net operating assets	0.003${}^{\ast \ast }$	−0.001	0.004	0.003${}^{\ast \ast \ast }$	0.004${}^{\ast \ast \ast }$	−0.002	0.004${}^{\ast \ast \ast }$	−0.003
	(0.015)	(0.688)	(0.170)	(0.000)	(0.000)	(0.518)	(0.000)	(0.513)
Audit quality	0.118${}^{\ast }$	−0.062	0.122${}^{\ast \ast }$	0.046	0.081${}^{\ast }$	0.014	0.095${}^{\ast \ast }$	0.007
	(0.059)	(0.637)	(0.031)	(0.332)	(0.081)	(0.505)	(0.047)	(0.749)
Constant	−0.138	−0.427${}^{\ast \ast \ast }$	−0.405${}^{\ast \ast \ast }$	−0.374${}^{\ast \ast \ast }$	−0.319${}^{\ast \ast \ast }$	0.032	−0.393${}^{\ast \ast \ast }$	0.172${}^{\ast \ast \ast }$
	(0.200)	(0.000)	(0.000)	(0.000)	(0.000)	(0.563)	(0.000)	(0.001)
Observations	2,625	3,567	2,760	14,316	12,693	12,679	12,227	12,213
R-squared	0.119	0.060	0.048	0.069	0.069	0.016	0.080	0.019
Industry FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
F-stat	5.357	4.895	2.975	16.58	14.37	1.948	15.94	1.864

Note: This table presents the coefficient estimates from OLS regressions exploring the relationship between vulnerability to takeovers and earnings management (EM) across different sub-samples. The table also explores the impact of merger intensity on EM and the vulnerability–EM nexus. The base model is specified in Equation (2(2) $E{M}_{\mathrm{it}}={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}$(2) ). The model controls for firm characteristics that influence the EM decision, as well as industry and year fixed effects. All independent variables are lagged by one year. All variables are fully defined in Appendix A1. P-values (from robust standard errors) are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 8. Vulnerability and earnings management: Two-stage least squares.

	First stage	Second stage
	Vulnerability	REM	AEM
Variables	(1)	(2)	(3)
Industry rumors	0.027${}^{\ast \ast \ast }$
	(0.000)
Peer vulnerability	0.441${}^{\ast \ast \ast }$
	(0.000)
Vulnerability		1.599${}^{\ast \ast }$	−0.281
		(0.011)	(0.277)
Profitability	0.018${}^{\ast \ast \ast }$	−0.026	0.018
	(0.000)	(0.406)	(0.378)
Firm size	−0.001${}^{\ast \ast \ast }$	0.019${}^{\ast \ast \ast }$	−0.006${}^{\ast \ast \ast }$
	(0.000)	(0.000)	(0.005)
Market to book	−0.001${}^{\ast \ast \ast }$	−0.036${}^{\ast \ast \ast }$	−0.000
	(0.000)	(0.000)	(0.847)
Debt issue	0.000${}^{\ast \ast \ast }$	−0.001	0.000
	(0.000)	(0.128)	(0.663)
Leverage	0.010${}^{\ast \ast \ast }$	−0.006	0.022
	(0.000)	(0.842)	(0.282)
Free cash flow	0.025${}^{\ast \ast \ast }$	0.007	0.075${}^{\ast \ast \ast }$
	(0.000)	(0.881)	(0.008)
Block holders	−0.001	−0.046${}^{\ast \ast }$	−0.030
	(0.129)	(0.033)	(0.199)
Z–Score	−0.346	−28.353${}^{\ast \ast }$	16.651
	(0.516)	(0.029)	(0.189)
Net operating assets	0.000${}^{\ast \ast \ast }$	0.003${}^{\ast \ast \ast }$	−0.002
	(0.000)	(0.000)	(0.558)
Audit quality	−0.015${}^{\ast \ast \ast }$	0.079${}^{\ast \ast }$	0.006
	(0.000)	(0.049)	(0.726)
Constant	0.030${}^{\ast \ast \ast }$	−0.384${}^{\ast \ast \ast }$	0.125${}^{\ast \ast \ast }$
	(0.000)	(0.000)	(0.009)
Observations	18,704	16,094	16,095
Industry FE	Yes	Yes	Yes
Year FE	Yes	Yes	Yes
Adj. R${}^2$	0.296	0.063	0.012
F stat	186.74
Prob > F	(0.000)
F test of excluded instruments		266.28	266.86
p-value		0.000	0.000
Under identification test
Kleibergen-Paap rk LM stat		408.895	408.457
${\chi }^2$ p-value		0.000	0.000
Weak identification test
Cragg-Donald Wald F stat		302.630	303.607
Kleibergen-Paap rk Wald F stat		266.281	266.862
Over identification test
Hansen J statistic		1.476	0.091
${\chi }^2$ p-value		0.224	0.763

Note: The table presents results from two-stage least squares (2SLS) regression analysis testing H1. The first stage of the 2SLS estimation is presented in column 1 while the second stage is presented in columns 2–3. The independent variables in the second stage regressions are lagged by 1 period. All predictor variables are fully defined in Appendix A1. P-values are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 9. Pre-emptive earnings management and future takeovers: Propensity Score Matching.

					Entrenchment
	Full sample		Three-way interaction		High	Low
Variables	(1)	(2)	(3)	(4)	(5)	(6)
Vulnerability#REM#Entrenched			−51.223${}^{\ast \ast \ast }$
			(0.002)
Vulnerability#AEM#Entrenched				−79.854
				(0.248)
Vulnerability#REM	0.833		8.976		−80.917${}^{\ast \ast \ast }$	5.849
	(0.878)		(0.464)		(0.000)	(0.558)
Vulnerability#AEM		−34.440${}^{\ast \ast }$		45.735
		(0.034)		(0.405)
Vulnerability#Entrenched			−7.277	−7.896
			(0.558)	(0.532)
REM#Entrenched			2.912${}^{\ast \ast \ast }$
			(0.006)
AEM#Entrenched				3.483
				(0.407)
Vulnerability	8.591${}^{\ast }$	9.080${}^{\ast }$	20.624${}^{\ast }$	23.800${}^{\ast \ast }$	−14.490	36.436${}^{\ast \ast }$
	(0.068)	(0.074)	(0.063)	(0.042)	(0.310)	(0.046)
REM	−0.224		−0.459		5.010${}^{\ast \ast \ast }$	−0.229
	(0.611)		(0.584)		(0.000)	(0.724)
AEM		2.714${}^{\ast \ast }$		−0.506
		(0.024)		(0.893)
Entrenched			0.593	0.671
			(0.568)	(0.516)
Abnormal returns	−33.133	−22.461	−5.672	20.435	23.365	−79.450
	(0.374)	(0.543)	(0.910)	(0.648)	(0.762)	(0.315)
Profitability	−0.203${}^{\ast }$	−0.201${}^{\ast }$	−0.162	−0.164	−0.158	−0.185
	(0.096)	(0.093)	(0.261)	(0.213)	(0.333)	(0.701)
Tobin's q	−0.322${}^{\ast \ast \ast }$	−0.331${}^{\ast \ast \ast }$	−0.325${}^{\ast }$	−0.263${}^{\ast }$	−0.567${}^{\ast \ast }$	−0.261
	(0.004)	(0.003)	(0.063)	(0.063)	(0.049)	(0.312)
Sales growth	0.054	0.049	−0.515	−0.544${}^{\ast }$	−1.588${}^{\ast \ast \ast }$	−0.001
	(0.591)	(0.619)	(0.129)	(0.090)	(0.000)	(0.995)
Liquidity	0.688	0.790${}^{\ast }$	0.893${}^{\ast }$	1.023${}^{\ast \ast }$	−0.165	2.117${}^{\ast \ast }$
	(0.139)	(0.093)	(0.063)	(0.042)	(0.852)	(0.039)
Leverage	0.216	0.195	0.669	0.405	0.924	1.771${}^{\ast }$
	(0.656)	(0.681)	(0.354)	(0.520)	(0.459)	(0.080)
Growth-resource	0.057	0.053	−0.205	−0.250	0.534	−0.813${}^{\ast }$
	(0.798)	(0.816)	(0.505)	(0.403)	(0.240)	(0.070)
Disturbance	1.260	1.140	−0.609	−1.387	4.153${}^{\ast \ast }$	−2.990
	(0.332)	(0.394)	(0.659)	(0.268)	(0.036)	(0.248)
Firm size	−0.029	−0.026	0.020	0.039	−0.100${}^{\ast \ast }$	0.077
	(0.385)	(0.449)	(0.578)	(0.219)	(0.049)	(0.244)
Firm size#Firm size	2.261${}^{\ast \ast \ast }$	2.327${}^{\ast \ast \ast }$	2.486${}^{\ast \ast }$	2.352${}^{\ast \ast }$	9.065${}^{\ast \ast \ast }$	−1.470
	(0.006)	(0.006)	(0.042)	(0.029)	(0.000)	(0.209)
Free cash flow	0.119	0.190	−1.024	−0.769	−0.101	−4.194${}^{\ast \ast \ast }$
	(0.729)	(0.585)	(0.101)	(0.214)	(0.905)	(0.000)
Tangible assets	−0.027	−0.039	−0.095	−0.104	−0.519${}^{\ast \ast }$	0.348${}^{\ast \ast }$
	(0.799)	(0.713)	(0.540)	(0.497)	(0.038)	(0.032)
Firm age	−0.025	−0.052	0.095	0.055	−1.658${}^{\ast \ast \ast }$	1.047
	(0.932)	(0.861)	(0.870)	(0.923)	(0.010)	(0.332)
Block holders	−15.675	−14.467	1.624	8.937	−42.243${}^{\ast \ast }$	23.780
	(0.202)	(0.251)	(0.904)	(0.457)	(0.028)	(0.329)
Constant	−15.675	−14.467	1.624	8.937	−42.243${}^{\ast \ast }$	23.780
	(0.202)	(0.251)	(0.904)	(0.457)	(0.028)	(0.329)
Observations	1552	1517	637	630	340	297
${\chi }^2$	48.10	52.19	37.58	72.15	50.59	37.12
Prob (${\chi }^2$)	(0.000)	(0.000)	(0.010)	(0.000)	(0.000)	(0.002)
Pseudo R${}^2$	0.110	0.116	0.157	0.144	0.361	0.264

Note: This table presents the probit regression estimates from Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) which explores the takeover deterrent effect of earnings management (EM) using a propensity score matched sample. Columns 1–2 presents coefficient estimates of Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) based on our entire sample. Columns 3–4 present coefficient estimates of Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) when interacted with the entrenchment indicator. Columns 5–6 presents coefficient estimates of Equation (3(3) $\begin{array}{rl}\mathrm{Prob}(\mathrm{Target}=1{)}_{\mathrm{it}}& ={\text{β}}_0+{\text{β}}_1\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\ast E{M}_{\mathrm{it}-1}+{\text{β}}_2\mathrm{Vulnerabilit}{y}_{\mathrm{it}-1}\\ & +{\text{β}}_{3}E{M}_{\mathrm{it}-1}+\sum {\text{β}}_k\mathrm{Control}{s}_{\mathrm{it}-1}+v_j+v_t+{ϵ}_{\mathrm{it}}\end{array}$(3) ) from two sub-samples; high and low entrenchment firms. We define high (low) entrenchment as a sub-sample of firms in which the value of compensation made up of long term incentive plans (LTIP) as a proportion total compensation (averaged across all board members) is less (greater) than the 2-digit SIC code industry-year median value. The model controls for firm characteristics that influence takeover likelihood, as well as industry and year fixed effects. All variables are fully defined in Appendix A1. P-values are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table 10. Pre-emptive earnings management and premiums: Heckman's two-stage regressions.

Panel A: Heckman's first-stage selection model
	Target		Target
	(REM equation)		(AEM equation)
	Coeff.	p-value	Coeff.	p-value
Variables	(1)	(2)	(3)	(4)
Concentration	−0.354${}^{\ast \ast \ast }$	(0.000)	−0.369${}^{\ast \ast \ast }$	(0.000)
Sentiment	0.387${}^{\ast \ast \ast }$	(0.000)	0.380${}^{\ast \ast \ast }$	(0.000)
Merger intensity	0.010${}^{\ast \ast \ast }$	(0.005)	0.011${}^{\ast \ast \ast }$	(0.004)
Profitability	0.319${}^{\ast \ast \ast }$	(0.002)	0.272${}^{\ast \ast \ast }$	(0.006)
Market to book	−0.043${}^{\ast \ast \ast }$	(0.000)	−0.043${}^{\ast \ast \ast }$	(0.000)
Firm size	0.046${}^{\ast \ast \ast }$	(0.000)	0.048${}^{\ast \ast \ast }$	(0.000)
Free cash flow	0.392${}^{\ast \ast \ast }$	(0.005)	0.390${}^{\ast \ast \ast }$	(0.005)
Constant	−2.593${}^{\ast \ast \ast }$	(0.000)	−2.611${}^{\ast \ast \ast }$	(0.000)
Observations	24,917		24,921
${\chi }^2$	202.7		191.4
p	(0.000)		(0.000)
Likelihood-ratio test of excluded instruments
LR ${\chi }^2$	53.42	(0.000)	55.48	(0.000)
Panel B: Heckman's second-stage regression model
	Premium		Premium
	(REM equation)		(AEM equation)
	Coeff.	p-value	Coeff.	p-value
Variables	(1)	(2)	(3)	(4)
Inverse Mills Ratio	29.055	(0.174)	21.773	(0.291)
Vulnerability	11.076	(0.842)	10.742	(0.848)
Vulnerability#REM	163.298${}^{\ast }$	(0.068)
Vulnerability#AEM			109.448	(0.632)
REM	−8.345	(0.203)
AEM			−10.433	(0.579)
Profitability	9.118	(0.438)	5.644	(0.621)
Firm size	−2.233${}^{\ast }$	(0.054)	−2.458${}^{\ast \ast }$	(0.034)
Market to book	−3.640${}^{\ast \ast \ast }$	(0.004)	−3.248${}^{\ast \ast \ast }$	(0.010)
Debt issue	0.147	(0.537)	0.081	(0.733)
Leverage	1.879	(0.813)	2.107	(0.794)
Free cash flow	−5.981	(0.689)	−3.590	(0.810)
Block holders	−13.057${}^{\ast }$	(0.080)	−11.152	(0.138)
Cash payment	5.239${}^{\ast }$	(0.076)	6.297${}^{\ast \ast }$	(0.037)
Cross border	5.940${}^{\ast \ast }$	(0.035)	6.521${}^{\ast \ast }$	(0.022)
Bid attitude	5.708	(0.166)	5.168	(0.221)
Competing bids	24.716${}^{\ast \ast \ast }$	(0.000)	25.152${}^{\ast \ast \ast }$	(0.000)
Diversifying bids	0.789	(0.750)	1.971	(0.434)
Constant	15.076	(0.822)	33.301	(0.611)
Observations	24,917		24,921
Industry FE	Yes		Yes
Year FE	Yes		Yes
Selected cases	897		901
Wald ${\chi }^2$	202.7	(0.000)	191.4	(0.000)
Highest VIF	2.420		2.290
VIF of Inverse Mills Ratio	2.420		2.290

Note: The table presents results from Heckman's two-stage regression analysis testing H3. The first stage results are presented in panel A while the second stage results are presented in panel B. The independent variables in panel B are lagged by 1 period. All predictor variables are fully defined in Appendix A1. P-values are presented in parentheses. ${}^{\ast \ast \ast }$, ${}^{\ast \ast }$ and ${}^{\ast }$ indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Table A1. Variable descriptions.

Variables (Abbrev.)	Construction (Worldscope codes)
Panel A: Main variables
Target $=1$	Dummy variable which takes a value of one if a firm is the subject of a takeover bid and a value of zero otherwise.
Vulnerability	Takeover likelihood as at the start of the period. Derived from Equation (1(1) $\mathrm{Takeover}\mathrm{Likelihoo}{d}_{\mathrm{it}}=\frac{1}{1+e^{-Z_{\mathrm{it}-1}}}$(1) ).
High (Low) vulnerability	Indicator variable capturing whether a firm's level of vulnerability in each year is greater than (i.e., high) or less than (i.e., low) the median vulnerability (defined above).
Abnormal production (REMprod)	Following prior studies (Cohen et al., 2008; Roychowdhury, 2006; Zang, 2012), we model total production costs as a function of sales (WC01001), change in sales and the lagged change in sales and capture the abnormal portion of production costs (REMprod) as the residual from the (2-digit SIC code) industry-year cross-sectional regressions. (A1) $\frac{\mathrm{PRO}{D}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}={\text{β}}_0+{\text{β}}_1\frac{1}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_2\frac{\mathrm{Sale}{s}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_3\frac{\mathrm{\Delta }\mathrm{Sale}{s}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_4\frac{\mathrm{\Delta }\mathrm{Sale}{s}_{\mathrm{it}-1}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{ϵ}_{\mathrm{it}}$(A1)
Abnormal discretionary expenses (REMdisx)	Following prior studies (Cohen et al., 2008; Roychowdhury, 2006; Zang, 2012), we model total discretionary expenses (the sum of R&D expenditures (WC01201) and selling, general and administrative (SG&A) expenditures (WC01101)) costs) as a function of sales (WC01001). REMdisx is the residual from the (2-digit SIC code) industry-year cross-sectional regressions, multiplied by negative one. (A2) $\frac{\mathrm{DIS}{X}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}={\text{β}}_0+{\text{β}}_1\frac{1}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_2\frac{\mathrm{Sale}{s}_{\mathrm{it}-1}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{ϵ}_{\mathrm{it}}$(A2)
Abnormal cash flow from operations (REMcfo)	Following Roychowdhury (2006), we model normal CFO (WC04860) as a function of sales (WC01001) and change in sales. REMcfo is the residual from the (2-digit SIC code) industry-year cross-sectional regressions, multiplied by negative one. (A3) $\frac{\mathrm{CF}{O}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}={\text{β}}_0+{\text{β}}_1\frac{1}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_2\frac{\mathrm{Sale}{s}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_3\frac{\mathrm{\Delta }\mathrm{Sale}{s}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{ϵ}_{\mathrm{it}}$(A3)
Real earnings management (REM)	The sum of Abnormal production (REMprod) and Abnormal discretionary expenses (REMdisx).
Accrual earnings management (AEM)	We use the modified-Jones model (Dechow et al., 1995) to estimate discretionary accruals. Total accruals (Accruals) is modeled as a function of property, plant and equipment (PPE, WC02051) and the difference between change in sales (WC01001) and change in receivables (WC02051). AEM is the residual from the (2-digit SIC code) industry-year cross-sectional regressions. (A4) $\frac{\mathrm{Accrual}{s}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}={\text{β}}_0+{\text{β}}_1\frac{1}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_2\frac{\mathrm{\Delta }\mathrm{Sale}{s}_{\mathrm{it}}-\mathrm{\Delta }\mathrm{Receivable}{s}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{\text{β}}_3\frac{\mathrm{PP}{E}_{\mathrm{it}}}{\mathrm{Asset}{s}_{\mathrm{it}-1}}+{ϵ}_{\mathrm{it}}$(A4)
Premium	Difference between offer price and target stock price (4 weeks before the announcement) as a ratio of target stock price.
Panel B: Control variables – Firm financial characteristics
Abnormal returns	Abnormal returns of the last year computed using the OLS market model. Alpha and beta estimates are first computed from the previous year by regressing stock returns on market returns. Estimates of alpha and beta are then used to compute abnormal return in the current year.
Profitability	Return on assets computed as ratio of earnings before interest and tax (WC18191) total assets (WC02999).
Tobin's Q	Market value of assets (MVA) to replacement cost of assets (RCA), where MVA is the sum of book value of debt (BVD) and market value of equity (MVE). BVD is total assets (WC02999) minus shareholder equity (WC03995). MVE is number of shares outstanding (NOSH) multiplied by share price in pounds (UP/100). RCA is proxied by the book value of total assets (WC02999).
Market to book value	Market value of equity (MVE) divided by book value of equity (WC02999-WC03255).
Sales growth	Change in total revenues (WC01001) as a ratio of previous year's total revenues (WC01001).
Liquidity	Cash and short-term investments (WC02001) to total assets (WC02999).
Leverage	Total debt (WC03255) to total assets (WC02999).
Debt issue	Percentage change in total debt (WC03255).
Growth-resource dummy	Dummy that takes a value of one if a firm has high growth and low resources or vice versa, and a value of zero otherwise. (see, Danbolt et al., 2016; Palepu, 1986).
Industry disturbance dummy	Dummy is one if any merger is completed within a firm's two-digit SIC industry in the year before the bid, and a value of zero otherwise.
Firm size	Natural log of total assets (WC02999).
Free cash flow	Ratio of net cash flow from operating activities (WC04860) minus capital expenditures (WC04601) scaled by total assets (WC02999).
Tangible assets	Ratio of property, plant and equipment (WC02501) to total assets (WC02999).
Firm age	Number of years since date of incorporation (WC18273).
Block holder	Proportion of shares held by strategic shareholder (NOSHST) – i.e., shareholders with at least 5% shareholding.
Z–Score	Taffler Z–Score estimated using the following equation. (A5) $Z_{\mathrm{it}}=3.20+12.18\ast {\mathit{\text{X}}}_1+2.50\ast {\mathit{\text{X}}}_2-10.68\ast {\mathit{\text{X}}}_3+0.029\ast {\mathit{\text{X}}}_4$(A5) where $X_1$ is the ratio of profit before tax (PBT) to current liabilities (CL), $X_2$ is the ratio of current assets to total liabilities, $X_3$ is the ratio of CL to total assets, $X_4$ is the ratio of quick assets minus CL to daily operating expenses (DOE). DOE is computed as sales minus PBT minus depreciation divided by 365.
Net operating assets	Shareholders' equity less cash and marketable securities plus total debt, deflated by total sales.
Panel C: Control variables – Corporate Governance characteristics
Audit quality	The ratio of audit fee to total assets.
Board size	The total number of directors on the board.
CEO duality	A dummy variable which takes a value of one if the chief executive officer (CEO) is also the board chairman, and a value of zero otherwise.
Gender diversity	The proportion of female board members within the board.
Board independence	The proportion of independent directors within the board.
Director experience	The average age of board members.
Board tenure	The average length of time each board member has been on the board.
Audit committee	An indicator variable for the presence or not of an audit committee.
Panel D: Control variables – M&A characteristics
Cash payment	A dummy variable that takes a value of one, when a target receives an all-cash merger offer.
Crossborder	A dummy variable which takes a value of one if an acquirer is a foreign firm i.e., not listed on the London Stock Exchange, and a value of zero otherwise.
Bid attitude	A dummy variable which takes a value of one if the deal is characterized as a hostile deal, and a value of zero otherwise.
Competing bids	A dummy variable which takes a value of one if multiple firms were bidding for the same target within the same period, and a value of zero otherwise.
Diversifying bids	A dummy variable which takes a value of one if the acquirer and target are from different industries, and a value of zero otherwise.
Panel E: Other variables (including instruments)
Concentration (industry)	Herfindahl-Hirschman Index (HHI); sum of squared market shares (computed from revenues) of firms in each 2-digit SIC code industry in each year.
Sentiment (market)	Change in the FTSE-All share index over the last 12-months.
Merger intensity	Natural log of number of M&A bids announced within a firm's 2-digit SIC code industry in the previous year.
Industry rumors	The number of merger rumors within a firm's 2-digit SIC code industry in the previous year scaled by 100.
Peer vulnerability	The mean vulnerability of peer firms (excluding the focal firms) within each 2-digit SIC code industry-year.
Entrenchment	An indicator variable identifying firms in which the ratio of the value of long term incentive plans (LTIP) to total managerial compensation for the period, averaged over all board members, is less than the 2-digit SIC code industry-year median value.

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