Real Earnings Management, Liquidity Risk and REITs SEO Dynamics

Abstract

We analyze how REITs managers use real earnin gs management to address issues of liquidity risk and increased cost of capital they face during seasoned equity offerings. We show that REITs managers engage in real earnings management instead of accrual earnings management to attract more uninformed trading in order to provide the liquidity service at a lower cost during seasoned equity offerings. We find REITs with higher liquidity risk are more likely to manipulate earnings prior to equity offerings and uninformed trading is higher following real earnings management. Firms set the offer price at a smaller discount after engaging in real earnings management and stock returns decline in the long run. The findings are consistent with real option and liquidity risk explanations for equity offerings.

Appendices

Appendix 1 Rhodes-Kropf et al. (2005) (RKRV) methodology

Rhodes-Kropf et al. (2005) (RKRV) methodology estimates the firm value v by estimating both industry level accounting multiples and long run firm accounting multiples using the following equation.

$$ {m}_{it}-{b}_{it}={m}_{it}-v\left({\theta}_{it};{\alpha}_{jt}\right)+v\left({\theta}_{it};{\alpha}_{jt}\right)-v\left({\theta}_{it};{\alpha}_j\right)+v\left({\theta}_{it};{\alpha}_j\right)-{b}_{it} $$

(13)

The first component m _it  − v(θ _it ; α _jt ) measures the difference between market value and fundamental value estimated using firm-specific accounting data and the contemporaneous industry accounting multiples. This component is the mispricing proxy we use in this paper. The third component v(θ _it ; α _j ) − b _it captures the growth opportunities.

To empirically separate mispricing component, RKRV (2005) adopt three different models to estimate firm value. We adopt RKRV’s 3rd model to estimate the market value as follows¹²:

$$ {m}_{it}={\alpha}_{0 jt}+{\alpha}_{1 jt}{b}_{it}+{\alpha}_{2 jt}\ln {(NI)}_{it}^{+}+{\alpha}_{3 jt}{I}_{\left(<0\right)}\ln {(NI)}_{it}^{+}+{\alpha}_{4 jt}{LEV}_{it}+{\varepsilon}_{it} $$

(14)

Where m is market value of equity, b is a book value of equity, $\ln {(NI)}_{it}^{+}$ is the natural logarithm of positive net income, I is an indicator function for negative net income observations, and LEV is leverage ratio.

To calculate the REITs industry wide accounting multiples, we run cross-sectional regressions for the REITs industry to obtain the estimated REITs industry accounting multiples ${\widehat{\alpha}}_{jt}$ for each year t.

Hence, the estimated firm value is obtained in the following equation.

$$ v\left({b}_{it},{NI}_{it},{LEV}_{it};{\widehat{\alpha}}_{0 jt},{\widehat{\alpha}}_{1 jt},{\widehat{\alpha}}_{2 jt},{\widehat{\alpha}}_{3 jt}\right)={\widehat{\alpha}}_{0 jt}+{\widehat{\alpha}}_{1 jt}{b}_{it}+{\widehat{\alpha}}_{2 jt}{I}_{\left(<0\right)}\ln {(NI)}_{it}^{+}+{\widehat{\alpha}}_{3 jt}{LEV}_{it} $$

(15)

If investors overestimate the future cash flows or underestimate risks, market-to-value will capture the mispricing component of the market-to-book ratio. The difference between market value m _it prior to SEO issuance and the estimated firm value $v\left({b}_{it},{NI}_{it},{LEV}_{it};{\widehat{\alpha}}_{0 jt},{\widehat{\alpha}}_{1 jt},{\widehat{\alpha}}_{2 jt},{\widehat{\alpha}}_{3 jt}\right)$ is our proxy for stock mispricing.

Appendix 2 Variable Definition

Variable name	Definition	Data Sources
Panel A: Variables of interests
Abnormal Trading Prior to SEO(AV)	Abnormal trading volume prior to SEO using the standard event study method.	CRSP
SEO discounting	The (negative of) percentage difference between the offer price and the closing price on the prior trading day	COMPUSTAT
SEO Offering at the market price	Equals to 1, if the firm sets the offer price at the market price.	SDC
Panel B: Real earnings management
ABCFO	The actual CFO minus the normal level of CFO, which is estimated as a linear function of sales in the last period and change in revenue in the last period.	COMPUSTAT
ABEXP	The actual property operating expenses minus the normal level of property operating expenses, which is estimated as a linear function of contemporaneous revenue.	COMPUSTAT
ABDISP	Gain/Loss from the Sale of Property, Plant and Equipment and Investments minus the Gain/Loss, which is estimated as a linear function of market capitalization, fixed asset sales and capital expenditure.	COMPUSTAT
Panel C: Control variables
Mkt_beta	The market beta estimated from the liquidity-augmented CAPM model.	CRSP
Liq_beta	The liquidity beta estimated from the liquidity-augmented CAPM model, in which the liquidity factor is developed by Pástor and Stambaugh (2003).	CRSP
Liquidity	The Amihud illiquidity measure	CRSP
Cash	Cash and short-term investment over total assets	COMPUSTAT
Size	The nature logarithm of firm’s market capitalization	COMPUSTAT
logMB	The logarithm of firms’ market value divided by its book value in the most recent quarter	COMPUSTAT
Growth	percentage change of total assets from last period	COMPUSTAT
ROA	Net income over total assets	COMPUSTAT
SeqREIT	The current SEO sequence regarding the REIT itself to account for the clustering and frequency of SEO	SNL
Uranking	The underwriter reputation	SDC
InfoAs	The abnormal return around earning announcement releases as a proxy for information asymmetry	CRSP, COMPUSTAT
Sentiment	Investors’ sentiment index constructed from University of Michigan’s Consumer Sentiment Index, using the methodology described in Lemmon and Portniaguina (2006)	University of Michigan
Accrual	Aggregate accruals estimated by modified Jones Model (1991)	COMPUSTAT

Appendix 3 Determinants of real earnings management for REITs during non SEO years

This table presents the result of determinants of real earnings management for REITs during non SEO years. Dependent variables are measures for real earnings management ABCFO, ABEXP and ABDISP, respectively. The variables of interest are Liq_beta. The independent variables are Mkt_beta, Cash, Size, LogMB, Growth, ROA, InfoAs, and Sentiment as defined in Appendix 1. Coefficients for the variables of interest are presented, and T-statistics are included in parentheses.*, ** and *** represent the 10%, 5% and 1% significance levels, respectively.

	Abnormal CFO(ABCFO)		Abnormal Operating Expense(ABEXP)		Abnormal Asset Disposition(ABDISP)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Liq_beta		−0.315**		0.238***		−0.055*
		(−2.06)		(2.75)		(−1.68)
Mkt_beta	−0.008	−0.077	0.207***	0.249***	0.003	−0.006
	(−0.17)	(−1.50)	(8.28)	(8.52)	(0.36)	(−0.55)
Cash	−1.307**	−1.275**	1.445***	1.371***	0.491***	0.508***
	(−2.17)	(−2.12)	(4.53)	(4.29)	(4.03)	(4.16)
Size	−0.045**	−0.045**	−0.065***	−0.063***	−0.043***	−0.043***
	(−2.51)	(−2.50)	(−6.80)	(−6.59)	(−11.66)	(−11.76)
LogMB	−0.122**	−0.117*	0.015	0.018	0.032**	0.031**
	(−1.97)	(−1.90)	(0.47)	(0.55)	(2.53)	(2.48)
Growth	0.291***	0.292***	−0.098***	−0.097***	−0.008	−0.008
	(10.00)	(10.07)	(−6.36)	(−6.25)	(−1.35)	(−1.42)
ROA	−0.025	−0.023	−0.112***	−0.111***	−0.007**	−0.007**
	(−1.56)	(−1.50)	(−13.45)	(−13.35)	(−2.12)	(−2.18)
InfoAs	0.493	0.375	−0.381*	−0.302	0.234***	0.216***
	(1.24)	(0.94)	(−1.81)	(−1.42)	(2.90)	(2.65)
Sentiment	0.002	0.002	−0.004***	−0.004**	0.002***	0.002***
	(0.81)	(0.81)	(−2.59)	(−2.57)	(3.92)	(3.91)
Constant	Yes	Yes	Yes	Yes	Yes	Yes
Time effect	Yes	Yes	Yes	Yes	Yes	Yes
Property Type	Yes	Yes	Yes	Yes	Yes	Yes
No. of Obs	4442	4442	4442	4442	4442	4442
Adjusted R 2	0.047	0.047	0.197	0.198	0.044	0.044
F Stat	13.90	13.91	64.94	61.84	13.00	12.44

Table 10 Descriptive statistics for REITs firms conducting SEOs during 2000–2011