The effect of target-firm accounting quality on valuation in acquisitions

Abstract

We examine whether acquisitions are more profitable for acquirers when the firms they target disclose higher-quality accounting information. If accounting information reduces uncertainty in the value of the target firm by facilitating a more precise valuation, we predict that managers of the acquiring firm can bid more effectively and pay less to acquire a target firm that has high-quality accounting information. Using a large sample of acquisitions of public firms from 1990 to 2010, we find evidence consistent with our prediction. Specifically, when target firms have higher-quality accounting information, acquirer returns around the acquisition announcement are higher and target returns are lower—consistent with acquirers capturing a greater portion of acquisition gains by paying less for target firms. These findings, which are robust to a variety of controls and alternative measures of uncertainty and accounting quality, suggest that higher-quality accounting information leads to better bidding decisions in acquisitions.

Appendices

Appendix 1: Variable definitions

ACQ_RET	Three-day market-adjusted stock return of acquiring firm, centered on the date of the acquisition announcement.
TARG_RET	Three-day market-adjusted stock return of target firm, centered on the date of the acquisition announcement.
UNC_RET	Volatility of the target firm’s monthly stock returns over the most recent two fiscal years prior to the acquisition announcement.
UNC_CFO	Volatility of the target firm’s annual cash flows from operations divided by total assets, measured over the 8 years leading up to the acquisition announcement.
UNC_DTV	Primary factor obtained through factor analysis of target’s size, age, volatility, dividends, sign of earnings, intangible assets, R&D spending, and deviations from sample mean of book-to-market ratio, sales growth, and change in external financing.
F_AQ	Firm-level accounting quality (see Appendix 2).
I_AQ	Industry-level accounting quality (see Appendix 2).
ACQ_SIZE	Natural log of the acquirer’s market value, measured 2 days prior to the acquisition announcement.
ACQ_DOTCOM	Indicator, =1 if the acquirer’s name includes “.com.”
REL_SIZE	Ratio of the target’s market value of equity to the acquirer’s market value of equity, each measured 2 days prior to the acquisition announcement.
TARG_GROWTH	Target’s annual revenue, divided by revenue of the prior year.
TARG_DOTCOM	Indicator, =1 if the target’s name includes “.com.”
IND_LIQUID	Sum of acquisition deal prices for each industry divided by the aggregate assets across firms in the same industry, measured on an annual basis.
SAME_IND	Indicator, =1 if the acquirer and target firm have the same two-digit SIC code.
STOCK	Indicator, =1 if at least 90 percent of the acquisition price was paid with equity.
TENDER	Indicator, =1 if the acquisition is a tender offer.
NEGOTIATED	Indicator, =1 if deal is negotiated.
COMPETING	Indicator, =1 if there are additional (i.e., competing) bids for the target.
EARNOUT	Indicator, =1 if deal includes an earnout.
POISONPILL	Indicator, =1 if target has a poison pill.

Appendix 2: Description of accounting quality measures

Models:

$$ ACC_{{{\text{t}} - 1}} = {\text{ a }} + {\text{ b}}_{ 1} \varDelta SALES_{{{\text{t}} - 1}} + {\text{ b}}_{ 2} PPE_{{{\text{t}} - 1}} + {\text{ b}}_{ 3} CF_{{{\text{t}} - 2}} + {\text{ b}}_{ 4} CF_{{{\text{t}} - 1}} + {\text{ b}}_{ 5} CF_{\text{t}} + {\text{ e}} $$

(2)

$$ CF_{\text{t}} = {\text{ a }} + {\text{ b}}_{ 1} CF_{{{\text{t}} - 1}} + {\text{ b}}_{ 2} ACC_{{{\text{t}} - 1}} + {\text{ e}} $$

(3)

• CF = cash from operations

• ACC = accruals = net income before extraordinary items – CF

• SALES = sales revenue

• PPE = gross property, plant, and equipment

2.1 Firm-level measures

Models (2) and (3) are estimated cross-sectionally by industry (two-digit SIC code) and year.

• F_AQ1 = –1 × the standard deviation of a firm’s residuals from model (2) calculated over the eight years leading up to the acquisition

• F_AQ2 = –1 × the standard deviation of a firm’s residuals from model (3) calculated over the eight years leading up to the acquisition

• F_AQ = mean of F_AQ1 and F_AQ2

We require nonmissing data for at least five of the eight years.

2.2 Industry-level measures

Models (2) and (3) are estimated cross-sectionally in the target firm’s industry (two-digit SIC code) in the year such that CF _t is the most recent fiscal year ending prior to the acquisition announcement.

• I_AQ1 = –1 × the standard deviation of an industry’s residuals from model (2)

• I_AQ2 = –1 × the standard deviation of an industry’s residuals from model (3)

• I_AQ = mean of I_AQ1 and I_AQ2