Financial constraints and share repurchases

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Journal of Financial Economics

Journal of Financial Economics 105 (2012) 311–331

0304-40

doi:10.1

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Choi, K

Frank C

particip

Univers

Yanzhi

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2410-Hn Corr

fax: þ8

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yeanjyh

journal homepage: www.elsevier.com/locate/jfec

Financial constraints and share repurchases$

Sheng-Syan Chen a, Yanzhi Wang b,n

a Department of Finance, College of Management, National Taiwan University, Taipei 10167, Taiwanb Department of Finance, College of Management, Yuan Ze University, Taoyuan 32003, Taiwan

a r t i c l e i n f o

Article history:

Received 10 May 2010

Received in revised form

5 July 2011

Accepted 28 July 2011Available online 8 March 2012

JEL classification:

G32

G34

G35

Keywords:

Share repurchase

Financial constraint

Corporate liquidity

Managerial hubris

5X/$ - see front matter & 2012 Elsevier B.V.

016/j.jfineco.2012.03.003

wish to thank Amy Dittmar (the referee), Ko

im Wai Ho, Chia-Wei Huang, Roger D. Huan

. Jen, Cheng-few Lee, Inmoo Lee, Ji-Chai

ants at National Taiwan University and Na

ity for helpful comments and suggestions. Sh

Wang gratefully acknowledge financial su

rcial Bank and the National Science Council

-155-014), respectively.

esponding author. Tel.: þ886 3 463 8800x26

86 3 463 0377.

ail addresses: [email protected].

@saturn.yzu.edu.tw (Y. Wang).

a b s t r a c t

We examine how the financial constraints of repurchasing firms affect their post-

buyback performance. By every constraint measure we use, a set of constrained firms

repurchase. They display significantly poorer post-buyback abnormal return and

operating performance than unconstrained firms. Financial constraints are more

important in explaining the performance of share buybacks for firms with high actual

repurchase ratios. Constrained firms, especially those with high actual repurchase

ratios, experience a significantly greater increase in post-buyback distress risk than

unconstrained firms. Managerial hubris could explain why constrained firms buy back

shares even if the buybacks do not improve shareholder wealth.

& 2012 Elsevier B.V. All rights reserved.

1. Introduction

Prior research shows the value-enhancing nature ofcorporate share repurchase programs. Vermaelen (1981)and Comment and Jarrell (1991) find positive announce-ment-period abnormal returns associated with sharerepurchases, which they interpret as a signal of undervalua-tion for the repurchasing firms. Ikenberry, Lakonishok, andVermaelen (1995, 2000) find positive long-term abnormal

All rights reserved.

nan Chan, Dosoung

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Lin, and seminar

tional Chiao Tung

eng-Syan Chen and

pport from E.SUN

of Taiwan (NSC98-

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tw (S.-S. Chen),

returns following share repurchases for a period of up to 4years. Other authors since then have provided varyingexplanations for the long-term drift in stock prices. Grullonand Michaely (2004) argue that stock prices impoundchanges in the cost of capital only gradually and that therisk changes associated with repurchases provide an expla-nation for the long-run price trend. Chan, Ikenberry, and Lee(2004) suggest mispricing and, to some degree, the disgor-ging of free cash flows as sources of the long-horizon returndrift. Gong, Louis, and Sun (2008) suggest that deflatingearnings around repurchase announcements is one reasonrepurchasing firms experience post-repurchase abnormalreturns. Peyer and Vermaelen (2009) find strong supportfor the long-term abnormal returns as a correction of anoverreaction to bad news prior to the repurchase.

Even though previous studies suggest that repurchaseprograms enhance firm value, repurchasing firms couldsuffer reduced corporate liquidity following sharerepurchases. Repurchasers spend cash or increase borrow-ing when they buy back shares (Jensen, 1986; Stephensand Weisbach, 1998; Dittmar, 2000; Hovakimian, 2004).

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S.-S. Chen, Y. Wang / Journal of Financial Economics 105 (2012) 311–331312

Reduced cash balances and added financial leverage fol-lowing repurchases lead to a decline in corporate liquidityfor repurchasing firms. If repurchasing firms are finan-cially constrained before a buyback, dampened corporateliquidity resulting from repurchases can be harmful. Asfinancing future investment becomes more difficult, thesefirms could have less competitive ability due to under-investment in the product market (Froot, Scharfstein, andStein, 1993; Chevalier and Scharfstein, 1996; Campello,2003; Almeida, Campello, and Weisbach, 2004). With lesscash, they are constrained in making technologicalimprovements in cash management (Opler, Pinkowitz,Stulz, and Williamson, 1999). They could also be morelikely to suffer financial distress risk (Opler, Pinkowitz,Stulz, and Williamson, 1999; Kaplan and Zingales, 2000;Lamont, Polk, and Saa-Requejo, 2001; Almeida, Campello,and Weisbach, 2004; Whited and Wu, 2006; Denis andSibilkov, 2010). Compared with financially unconstrainedrepurchasers, constrained repurchasers overall areexpected to exhibit poorer post-repurchase performancebecause of a decline in their corporate liquidity.

We examine how the financial constraints of repurch-asing firms affect firm performance following sharerepurchases. We use the KZ index to measure a firm’sfinancial constraint, as suggested by Kaplan and Zingales(1997), Lamont, Polk, and Saa-Requejo (2001), Baker,Stein, and Wurgler (2003), Chen, Goldstein, and Jiang(2007), and Hennessy, Levy, and Whited (2007). The KZindex describes the wedge between the internal andexternal costs of funds. Financially constrained firms, alsoknown as equity-dependent firms, tend to face highercosts for financing their needs externally. While the KZindex is closely associated with corporate liquidity andmeasures the ability of the firm to generate adequateamounts of cash to meet its needs, it might not be the bestmeasure of a firm’s financial constraints. For this reason,we also use three other typical measures of financialconstraint: the cash–cash flow sensitivity of Almeida,Campello, and Weisbach (2004), the investment–cashflow sensitivity of Fazzari, Hubbard, and Petersen(1988), and the WW index of Whited and Wu (2006).

We use a sample of 4,710 share repurchase announce-ments from 1990 through 2007. We show that, whicheverfinancial constraint measure we use, a set of constrainedfirms repurchase shares. These firms display significantdeclines in cash and cash flow and significant increases inleverage after buyback announcements, resulting inreductions in investment. We also show that both initialand long-run stock price reactions to repurchaseannouncements are significantly less favorable for con-strained firms than for unconstrained firms. Depending onthe financial constraint measure, the average three-dayannouncement-period abnormal returns for constrainedfirms range from 0.23% to 0.75%, much lower than theaverage abnormal returns of 0.92% to 1.83% for uncon-strained firms. For up to 4 years following the announce-ments, constrained firms experience average buy-and-hold abnormal returns of �5.96% to �1.40% per year,compared with 1.12–1.52% per year for unconstrainedfirms. Moreover, our regression analyses indicate thatlong-run stock price reactions over the post-repurchase

period are significantly negatively related to a firm’sfinancial constraints. These results, which are robust todifferent measures of financial constraint, hold even afterwe control for other potential explanatory variables. Thefindings suggest that share repurchase programs producepoorer post-buyback stock return performance for firmsthat are financially constrained.

We also examine whether the impact of financialconstraints on the post-repurchase stock performance ofbuyback firms depends on the proportion of repurchasesactually undertaken. Many firms announce repurchaseprograms but do not follow through with them (Ikenberryand Vermaelen, 1996; Stephens and Weisbach, 1998; Lie,2005). If firms actually buy back more shares following arepurchase program announcement, they are more likely toexperience reduced cash balances and increased financialleverage, resulting in poorer corporate liquidity followingrepurchases. Financially constrained firms would beexpected to suffer poorer post-repurchase stock perfor-mance when they actually buy back more shares. Ourresults show significantly less favorable post-buyback stockperformance for constrained firms with a high actual buy-back ratio. Financial constraints are less important inexplaining the long-run stock performance of repurchasingfirms with a low actual buyback ratio. Our evidence alsosuggests that actual repurchases, rather than announce-ments of repurchase programs per se, determine theperformance deterioration for constrained firms.

The financial constraints of repurchasing firms haveimpacts for their post-buyback operating performance.Share buyback programs result in significantly poorerabnormal operating performance for constrained firmsthan for unconstrained firms. Furthermore, our cross-sectional regression analyses indicate that post-buybackoperating performance is inversely related to firms’financial constraints, especially when highly constrainedfirms have high actual buyback ratios. Our findingssuggest that the reduced corporate liquidity resultingfrom share buybacks is harmful to the competitive abilityof constrained firms. This then leads to their pooreroperating performance in the post-buyback period.

Share buybacks have different impacts on financialdistress risk for constrained and unconstrained firms.They reduce cash levels and increase leverage ratios,resulting in greater financial risk (Maxwell andStephens, 2003). Constrained repurchasers are more likelyto be exposed to increased financial risk because of lowercorporate liquidity in the post-buyback period. Using theAltman (1968) Z-score to measure distress risk, we findthat, following a repurchase announcement, constrainedfirms (especially those with high actual buyback ratios)experience a significantly greater increase in distress riskthan unconstrained firms. We also find a significantlyhigher increase in the fraction of firms with a highprobability of default in the post-buyback period forconstrained firms. Our results indicate that constrainedfirms are more likely to suffer risk of financial distressfollowing the repurchase announcement.

Why would a constrained firm buy back shares if therepurchase does not enhance shareholder wealth? Apossible explanation is managerial hubris. In the period

S.-S. Chen, Y. Wang / Journal of Financial Economics 105 (2012) 311–331 313

surrounding repurchases, top managers of constrainedfirms tend to hold more in-the-money unexercised vestedoptions than managers of unconstrained firms. Ourregression analyses show that in-the-money vestedoptions surrounding the repurchase period are signifi-cantly positively related to the financial constraints of afirm, after controlling for other potentially influentialvariables. Failure to exercise in-the-money vested optionscan be interpreted as managerial overconfidence, asMalmendier and Tate (2005, 2008), Ben-David, Graham,and Harvey (2007), and Malmendier, Tate, and Yan (2011)suggest. Our results indicate that managers of constrainedrepurchasers tend to overestimate the future returns oftheir firms and, thus, postpone the exercise of their stockoptions.

We also show a link between managerial overconfi-dence and the long-run post-repurchase stock returnperformance of buyback firms. Our regression analysesshow that post-repurchase stock performance is signifi-cantly inversely related to in-the-money unexercisedvested options for constrained repurchasers. That is,constrained repurchasers with more overconfident man-agers experience poorer post-buyback stock performance.We use the universe of firms and a Tobit model toexamine whether managerial overconfidence explainsconstrained firms’ motives for repurchasing. We find thatactual buyback ratios are significantly positively relatedto in-the-money unexercised vested options for repurcha-sers that are constrained. This finding indicates thatconstrained firms tend to buy back more shares whentheir managers are more overconfident. These resultsprovide further support for a managerial hubris explana-tion of why constrained firms repurchase.

The paper is organized as follows. Section 2 describesour data and methodology. Section 3 examines the rela-tion between financial constraints and the stock returnperformance of buyback firms. Section 4 examines theeffects of financial constraints on post-buyback changesin the operating performance and financial distress risk ofrepurchasing firms. Section 5 provides our managerialhubris explanation of why constrained firms would buyback shares. The final section summarizes our findings.

2 The results do not change when we exclude financial firms

(Standard Industrial Classification code 60). Following Ikenberry,

Lakonishok, and Vermaelen (1995), Chan, Ikenberry, and Lee (2004),

and Peyer and Vermaelen (2009), we report combined results for both

financial firms and nonfinancial firms. Separate results are available

upon request.3 To address any possible problem associated with overlapping data,

we also exclude repeat repurchases in the announcement year, in the 4-

2. Data and methodology

2.1. Sample design

We obtain our sample of common stock repurchasesfrom the Securities Data Company (SDC) US Mergers andAcquisitions database. The sample covers originalannouncement dates between January 1, 1990 andDecember 31, 2007.1 Our procedures require that firmsbe included in the Center for Research in Security Prices(CRSP) and Compustat files. We exclude firms with shareprices lower than $3 to avoid skewing long-run returnestimations (Loughran and Ritter, 1996). American

1 The results (available upon request) are similar if the sample ends

with firms repurchasing in 2004 to avoid the potential effects of the

2008 financial crisis.

Depository Receipts, Real Estate Investment Trusts, andclosed-end funds are also excluded.2 We require samplefirms to have positive intended buyback ratios, size,assets, sales, and book-to-market ratios. The final sampleconsists of 4,710 repurchase announcements.3

2.2. Methodology

2.2.1. Measuring financial constraint

We use the KZ index to measure a firm’s financialconstraint. This index comes from Kaplan and Zingales(1997) in an in-depth study of the financial constraintsfaced by a sample of 49 low-dividend manufacturingfirms. Kaplan and Zingales rank these firms on an ordinalscale, from least to most obviously constrained, and thenrun an ordered logit of this scale on observable firmcharacteristics. Lamont, Polk, and Saa-Requejo (2001),Baker, Stein, and Wurgler (2003), Chen, Goldstein, andJiang (2007), and Hennessy, Levy, and Whited (2007) usethese logit coefficients on data from a broad sample offirms to construct a synthetic KZ index to measurefinancial constraints. A firm with a high KZ index isconsidered more financially constrained as the wedgebetween its internal and external cost of funds increases.The KZ index gives positive weight to Tobin’s Q andleverage, and negative weight to operating cash flow,cash balances, and dividends.

We construct the KZ index for each firm-year as thelinear combination

KZ ¼21:002ðCF=TAÞ239:368ðDIV=TAÞ

21:315ðCA=TAÞþ3:139LEVþ0:283Q , ð1Þ

where CF/TA is cash flow over lagged book assets, DIV/TA iscash dividends over lagged book assets, CA/TA is cashbalances over lagged book assets, LEV is total debt overbook assets, and Q is the ratio of the market-to-book valueof the firm’s assets.4 To reduce the effects of a few extremevalues, we winsorize the components of the KZ index atthe 1st and 99th percentiles before constructing it.

For every year of data, we sort all the firms inCompustat into quintiles according to the value of theirKZ indexes. Firms with the lowest KZ index values areplaced in quintile one, and firms with the highest valuesin quintile five. We then assign our repurchase samplefirms to these groups based on the KZ quintiles for thefiscal year before the repurchasing announcement. Fol-lowing Baker, Stein, and Wurgler (2003) and Chen,Goldstein, and Jiang (2007), we consider repurchasing

year post-buyback period, or in the entire sample period. We obtain

similar results (available upon request).4 The results are similar if we use a lagged property, plant, and

equipment (PPE) deflator or exclude the Q term when computing the KZ

index.

7 No look-ahead bias is present in this restriction (Loughran and

Vijh, 1997). We also test whether our results hold when we include only

firms with no repurchase announcement within the last 5 or the next 5

years. We find similar results, although this procedure of removing


firms in the highest KZ quintile to be financially con-strained and repurchasing firms in other KZ quintiles tobe financially unconstrained.5

To assess the robustness of our results, we use severalalternative measures of financial constraint. First, follow-ing Almeida, Campello, and Weisbach (2004), we measurea firm’s financial constraint by its cash flow sensitivity ofcash. We run a regression using firm-level time seriesdata in the pre-repurchase period:

DCA=TA¼ a0þa1Qþa2CFAD=TAþa3 logTAþu, ð2Þ

where DCA/TA is the change in the firm’s cash to totalassets, CFAD/TA is the ratio of earnings before extraordin-ary items and depreciation (minus dividends) to totalassets, log TA is the natural log of total assets, and u is theerror term. The firm’s cash–cash flow sensitivity is mea-sured by the coefficient a2 of CFAD/TA in regression modelEq. (2), whose value is higher for firms that are morefinancially constrained.6

Second, following Fazzari, Hubbard, and Petersen(1988), Cleary (1999), and Korajczyk and Levy (2003), wemeasure a firm’s financial constraint by its investment–cash flow sensitivity. We run a regression using firm-leveltime series data in the pre-repurchase period:

I=PPE¼ a0þa1Qþa2CF=PPEþu, ð3Þ

where I and PPE are the firm’s capital expenditures andproperty, plant, and equipment, respectively, and u is theerror term. The firm’s investment–cash flow sensitivity ismeasured by the coefficient a2 of CF/PPE in Eq. (3). Firmsthat are more financially constrained have higher valuesof a2.

Finally, we measure a firm’s financial constraint usingthe WW index of Whited and Wu (2006) as follows:

WW ¼20:091ðCF=TAÞ20:062DIVDUMþ0:021ðLTD=TAÞ

20:044logTAþ0:102INDSG20:035SG, ð4Þ

where DIVDUM equals one if the firm pays cash dividendsand zero otherwise; LTD is long-term debt; INDSG is thefirm’s three-digit industry sales growth; and SG is the firm’ssales growth. A firm with a high WW index is consideredmore financially constrained. As before, financially con-strained firms are repurchasing firms in the highest quintileof cash–cash flow sensitivity, investment–cash flow sensi-tivity, or the WW index. Financially unconstrained firms arerepurchasing firms in other quintiles.

2.2.2. Measuring abnormal stock returns

We measure initial stock price responses to announce-ments of share repurchases by the three-day buy-and-hold abnormal return (BHAR) over the period from day�2 through day 0, where day 0 is defined as the initialannouncement date. The 3-day BHAR measures the dif-ference in the 3-day compound return between repurch-asing firms and matching firms. Matching firms must be

5 Our conclusions remain unchanged if we define financially con-

strained repurchasing firms as in the top 15% or 25% of the KZ index.6 We obtain similar results if we augment the regression model

Eq. (2) by including four additional control variables (as in Almeida,

Campello, and Weisbach, 2004): capital expenditures, acquisitions,

changes in noncash net working capital, and changes in short-term debt.

listed on the same stock exchange as the repurchasingfirms. They must not have had a share repurchaseannouncement in the 5 years before the repurchasingfirm’s announcement date.7 They also must be within thesame size decile, book-to-market (B/M) quintile, and KZindex quintile as the repurchasing firm. Matching firmsare identified on the basis of size, B/M, and the KZ index,because these are important factors in explaining cross-sectional stock returns (see Fama and French, 1992, 1993,1996; Lakonishok, Shleifer, and Vishny, 1994; Daniel andTitman, 1997; Lamont, Polk, and Saa-Requejo, 2001).Among all firms meeting the criteria, we then select fivematching firms based on the closest B/M ratio to therepurchasing firm. Lee (1997) and Chan, Ikenberry, andLee (2004) suggest that using five control firms avoidspotentially noisy point estimates (Lyon, Barber, and Tsai,1999). The average compound return of the five matchingfirms over the 3-day announcement period is used as thebenchmark.8

To estimate long-horizon return performance asso-ciated with a share repurchase, we use annual buy-and-hold returns, an approach widely used (see, e.g.,Lakonishok, Shleifer, and Vishny, 1994; Chan, Lakonishok,and Sougiannis, 2001) and found to be attractive in com-parison to other techniques (e.g., Barber and Lyon, 1997;Kothari and Warner, 1997). We calculate the average annualbuy-and-hold returns for both repurchasing firms andmatching firms from the first year (year þ1) following therepurchase announcement to the fourth anniversary, or to afirm’s delisting date or December 2007 if the full sampleperiod is not available. Each year is defined as a uniformblock of 252 trading days, and year þ1 starts on theannouncement date. The long-run abnormal stock perfor-mance of firms that announce repurchase programs ismeasured by the difference between their average annualbuy-and-hold returns and their matching firms’ returns overthe 4-year post-repurchase period.

2.2.3. Measuring operating performance

Following Lie (2005) and Gong, Louis, and Sun (2008),we measure the operating performance of repurchasingfirms over the eight quarters after the repurchaseannouncement quarter (quarter 0). Operating perfor-mance is measured by return on assets (ROA), which isdefined as operating income divided by total book assetsat the beginning of the quarter.9 The abnormal operatingperformance for a given firm is the firm-specific ROAminus the ROA of its matching firm.

overlapping observations could suffer from a look-ahead bias.8 Our conclusion remains unchanged if we identify matching firms

on the basis of size and B/M only, if we use five matched firms based on

the closest KZ index to the repurchasing firm, if we use only one control

firm, or if we use the 2-day (�1, 0) announcement period.9 The results are similar if ROA is defined as operating income

divided by cash-adjusted total assets (i.e., total assets minus cash and

cash equivalents).


We select the matching firms using a matching pro-cedure similar to that in Lie (2005) and Gong, Louis, andSun (2008). For each repurchasing firm, we select all non-repurchasing firms in the same two-digit Standard Indus-trial Classification (SIC) code and in the same KZ quintilethat have operating performance for the announcementquarter within 720% or within 70.01; operating perfor-mance for the four quarters ending with quarter 0 within720% or within 70.01; and pre-announcement market-to-book value of assets within 720% or within 70.1. Ifno firms meet these criteria, we relax the industrycriterion to a one-digit SIC. Finally, if still no firms meetthe criteria, we disregard the SIC code and the KZcriteria.10 From these firms, we select the firm with thelowest sum of absolute performance difference, defined as

9ROAquarter 0,sample firm�ROAquarter 0,matching firm9

þ9ROAfour quarters ending with quarter 0, sample firm

�ROAfour quarters ending with quarter 0,matching firm9

þ9M=Bquarter�1,sample firm�M=Bquarter�1,matching firm9:

ð5Þ

2.2.4. Measuring financial distress risk

We follow other authors and use the Altman (1968)Z-score to measure financial distress risk (e.g., Officer,2007; Purnanandam, 2008). Altman’s Z-score is negativelycorrelated with the probability of financial distress and iscomputed as

Z-score¼ 1:2X1þ1:4X2þ3:3X3þ0:6X4þ0:999X5, ð6Þ

where X1 is working capital divided by book assets; X2 isretained earnings divided by book assets; X3 is earningsbefore interest and taxes divided by book assets; X4 ismarket value of equity divided by total liabilities; and X5

is net sales divided by book assets. To reduce the effects ofa few extreme values, we winsorize Z-scores at the 1stand 99th percentiles. Altman’s model classifies firms withZ-scores lower than 1.81 as failing. We, therefore, define arepurchasing firm to have a high probability of default ifits Z-score is lower than 1.81.

2.3. Sample statistics

Table 1 presents descriptive statistics for the finalsample. Panel A shows that, of the 4,710 repurchaseannouncements, 90.17% are open market sharerepurchases, 4.82% are tender offer repurchases, and5.01% are block (private negotiation), auction, or othertype of repurchase transactions.11 The average percentageof shares intended to be repurchased at the announce-ment of the repurchase program is 7.87%. The averagefirm size at 2007 prices is $4,834 million and the averageB/M is 54.37%. The intended buyback ratio, size, and B/Mof the repurchasing firms fluctuate over time.

Panel B of Table 1 shows the median matching-firmadjusted changes in cash (CA/TA), cash flow (CF/TA), leverage

10 We can find a match within the industry, with a similar KZ

criterion, for about 85% of our sample firms. Only a small proportion

(about 15%) of our sample firms do not have such a match.11 We obtain similar results for the subsample that includes only

open market share repurchases.

(LEV), and investment (INV) for 625 KZ-constrained and4,085 KZ-unconstrained repurchasers between year �1(the year before the repurchase announcement) and yearsþ1, þ2, þ3, and þ4 (the 4 years after the repurchaseannouncement).12 Investment is measured by the sum ofcapital expenditures and research and developmentexpenses scaled by lagged book assets (as in Grullon andMichaely, 2004). The results are similar for the other threefinancial constraint categorizations, so to save space we donot report them here. Panel B shows that constrainedrepurchasers experience significant declines in cash, cashflow, and investment and significant increases in leverageafter repurchase announcements, based on Wilcoxon signed-rank tests. The results indicate that share repurchases byconstrained firms produce post-buyback cash, cash flow, andleverage constraints that result in reduced investment.Unconstrained repurchasers generally experience significantdeclines in cash and significant increases in leverage, but nosignificant changes in cash flow and investment in the post-buyback period.13 Wilcoxon rank-sum tests indicate that themedian changes in CA/TA, CF/TA, LEV, and INV from year �1to year þ4 are significantly different for constrained andunconstrained repurchasers.

Table 2 presents the number of constrained repurcha-sers based on our four measures of financial constraint. Inthe sample, there are 625, 862, 970, and 225 constrainedrepurchasers according to the KZ index, cash–cash flowsensitivity, investment–cash flow sensitivity, and the WWindex, respectively. This evidence indicates that, which-ever constraint measure we use, a set of constrained firmsbuy back their own shares. Table 2 also shows the over-laps between the subsamples defined as constrained byeach of the four constraint measures. Of the 625repurchasers considered constrained according to the KZindex, 111, 124, and 114 are also considered constrainedaccording to cash–cash flow sensitivity, investment–cashflow sensitivity, and the WW index, respectively. Also, ofthe 862 constrained repurchasers according to cash–cashflow sensitivity, 214 and 78 are constrained according toinvestment–cash flow sensitivity and the WW index,respectively. Seventy-one repurchasers are classified asconstrained according to both investment–cash flow sen-sitivity and the WW index. These results suggest that,regardless of the cross-classification, a set of firms that isindisputably constrained repurchase.

3. Relation between financial constraints and stockreturn performance of buyback firms

3.1. Univariate analyses

Table 3 reports the initial and long-run stock pricereactions to share repurchase announcements for con-strained and unconstrained firms. Panel A shows a

12 Conclusions remain unchanged when we use mean changes in these

four ratios. The procedure for identifying matching firms is identical to the

matching procedure for abnormal operating performance.13 The results for the whole sample of repurchasers show a similar

pattern, consistent with findings in Grullon and Michaely (2004),

Hovakimian (2004), and Lie (2005).

Table 1Sample statistics.

This table reports descriptive statistics about our sample of share repurchases from 1990 through 2007. In Panel A, the intended buyback ratio is the

initial announced repurchase ratio authorized by the board of directors, size is the market value of common equity converted to 2007 dollars using the

consumer price index, and B/M is the book value of common equity divided by the market value of common equity. Panel B reports the median matching-

firm adjusted changes in cash (CA/TA), cash flow (CF/TA), leverage (LEV), and investment (INV) for 625 KZ-constrained and 4,085 KZ-unconstrained

repurchasers between year –1 (the year before the repurchase announcement) and years þ1, þ2, þ3, and þ4 (the 4 years after the repurchase

announcement). CA/TA is cash balances over lagged book assets, CF/TA is cash flow over lagged book assets, LEV is total debt over book assets, and INV is

sum of capital expenditures and research and development expenses scaled by lagged book assets. The KZ index is defined in Eq. (1). For every year of

data, we sort all the firms in Compustat into quintiles based on the value of their KZ indexes, where quintile one represents the lowest values and quintile

five the highest. We then assign the firms in the repurchase sample to these groups based on the KZ quintiles for the fiscal year before the repurchasing

announcement. Repurchasing firms in the highest KZ quintile are considered financially constrained; repurchasing firms in other KZ quintiles, financially

unconstrained. The procedure for identifying matching firms is identical to the matching procedure for abnormal operating performance described in

Section 2.2.3. Wilcoxon signed-rank tests are used to test the hypotheses that the median changes are equal to zero. Differences in median changes are

assessed using a Wilcoxon rank-sum test. p-values are reported in parentheses. nnn, nn, and n represent 1%, 5%, and 10% significance level, respectively.

Panel A: Summary statistics

Calendar

year

N Average intended buyback ratio

(percent)

Average size (millions of

dollars)

Average B/M

(percent)

Firms by type of share buyback

announced (percent)

Open market

repurchases

Tender

offers

Other

All 4,710 7.87 4,834 54.37 90.17 4.82 5.01

1990 2 4.08 1,074 62.15 100.00 0.00 0.00

1991 2 27.24 13,187 55.86 100.00 0.00 0.00

1992 8 8.58 10,264 39.15 100.00 0.00 0.00

1993 23 5.35 4,344 42.34 100.00 0.00 0.00

1994 285 7.97 2,923 53.43 83.86 7.37 8.77

1995 286 7.90 3,294 55.13 87.06 4.55 8.39

1996 345 7.39 3,174 49.02 89.57 6.09 4.35

1997 360 7.32 3,514 48.62 88.06 4.72 7.22

1998 558 8.19 2,557 56.94 92.47 3.76 3.76

1999 388 8.34 3,550 64.24 89.69 5.15 5.15

2000 361 9.36 4,737 74.26 90.30 6.09 3.60

2001 291 7.57 5,292 61.29 92.10 3.44 4.47

2002 241 7.47 6,956 58.96 92.12 2.90 4.98

2003 219 7.23 7,043 60.64 92.24 4.57 3.20

2004 318 6.38 8,104 45.07 93.40 3.77 2.83

2005 401 7.07 6,197 43.89 89.53 4.49 5.99

2006 390 7.93 6,142 46.26 91.03 5.90 3.08

2007 232 10.20 7,290 44.54 88.36 5.17 6.47

Panel B: Changes in cash, cash flow, leverage, and investment

Category Period Change in CA/TA Change in CF/TA Change in LEV Change in INV

Constrained firms Year �1 to þ1 �0.0050 �0.0031 0.0160 �0.0008

(0.00)nnn (0.03)nn (0.00)nnn (0.02)nn

Year �1 to þ2 �0.0128 �0.0060 0.0198 �0.0096

(0.00)nnn (0.00)nnn (0.00)nnn (0.02)nn

Year �1 to þ3 �0.0195 �0.0180 0.0521 �0.0062

(0.00)nnn (0.00)nnn (0.00)nnn (0.02)nn

Year �1 to þ4 �0.0251 �0.0173 0.0614 �0.0121

(0.00)nnn (0.00)nnn (0.00)nnn (0.04)nn

Unconstrained firms Year �1 to þ1 �0.0013 0.0009 0.0130 0.0031

(0.00)nnn (0.63) (0.45) (0.41)

Year �1 to þ2 �0.0071 �0.0034 0.0121 0.0000

(0.00)nnn (0.22) (0.00)nnn (0.10)

Year �1 to þ3 �0.0043 0.0007 0.0142 0.0040

(0.00)nnn (0.21) (0.00)nnn (0.81)

Year �1 to þ4 �0.0027 0.0023 0.0185 0.0044

(0.00)nnn (0.21) (0.00)nnn (0.96)

Median difference Year �1 to þ4 �0.0224 �0.0196 0.0429 �0.0165

(0.00)nnn (0.00)nnn (0.01)nnn (0.01)nnn


significantly smaller initial stock price reaction to repurch-ase announcements for constrained firms than for uncon-strained firms, regardless of the constraint measure. Forexample, when the KZ index is used, unconstrained

repurchasers have a positive average three-day BHAR of0.92%, which is statistically significant at the 1% level.Constrained repurchasers, however, have an average 3-dayBHAR of only 0.25%, which is statistically insignificantly

Table 2Number of constrained repurchasers by various measures of financial

constraint.

This table shows the number of repurchasing firms that are financially

constrained based on the following four measures: the KZ index, cash–

cash flow sensitivity, investment–cash flow sensitivity, and the WW

index, which are defined in Eqs. (1)–(4). Financially constrained firms

are repurchasing firms in the highest quintile of the KZ index, cash–cash

flow sensitivity, investment–cash flow sensitivity, or the WW index.

Financially unconstrained firms are repurchasing firms in other quin-

tiles. This table also shows the overlaps between the subsamples defined

as constrained by each of the four constraint measures.

Financial

constraint

measure

KZ

index

Cash–cash

flow

sensitivity

Investment–cash

flow sensitivity

WW

index

KZ index 625

Cash–cash flow

sensitivity

111 862

Investment–cash

flow sensitivity

124 214 970

WW index 114 78 71 225


different from zero at the conventional level. The meandifference between the 3-day BHAR for constrained andunconstrained repurchasers is �0.67%. A t-test shows thatthe mean difference is statistically significant at the 5% level.The results are similar when we use cash–cash flowsensitivity, investment–cash flow sensitivity, or the WWindex to measure financial constraint.

Panel B of Table 3 presents the results for annualBHARs over the 4-year period after the repurchaseannouncement date. Long-run stock price reactions toshare repurchase announcements are less favorable forconstrained firms than for unconstrained firms. Whenfinancial constraint categorization is based on the KZindex, unconstrained repurchasers exhibit an averageannual BHAR of 1.44% over the 4-year post-repurchaseperiod, which is statistically significant at the 1% level.Constrained repurchasers, however, experience an aver-age annual BHAR of �2.98%, which is statistically sig-nificant at the 5% level. The mean difference of �4.41%between the annual BHAR for constrained and uncon-strained firms is statistically significant at the 1% level.The results are similar for the other three measures offinancial constraint. The findings in Table 3 suggest thatreduced corporate liquidity resulting from share buybackprograms is harmful to financially constrained repurcha-sers.14 This then leads to their poorer stock performancein the post-buyback period.

We perform several robustness checks of the subsam-ple results. Prior research finds negative post-announce-ment long-run abnormal stock returns for initial publicofferings (IPOs) (Ritter, 1991), seasoned equity offerings

14 We also investigate the dividend payout of constrained firms

when they announce a repurchase. We find that only a very small

proportion of these firms reduce dividends (about 2%). This small

proportion occurs mainly because the majority of these firms (about

71%) do not pay any dividends, suggesting that they are constrained. Our

results indicate that share repurchases by these constrained firms lead

to increases in total payouts, which, in turn, result in a decline in

corporate liquidity.

(SEOs) (Loughran and Ritter, 1995), stock acquisitions(Loughran and Vijh, 1997), or dividend omissions(Michaely, Thaler, and Womack, 1995). We thus excluderepurchasers that have made such announcements duringthe 3-year period before their repurchase announcement.In untabulated results, we continue to find that con-strained repurchasers experience poorer long-run stockprice performance than unconstrained repurchasers, sug-gesting that our findings are not driven by the effects ofIPOs, SEOs, stock acquisitions, or dividend omissions. Wenext exclude negotiated repurchases (identified in theSDC database) from our sample because they could berelated to merger and acquisition (M&A) attempts. Theresults (untabulated) do not change our conclusion, sug-gesting that the poorer long-run stock performance ofconstrained repurchasers is not driven by effects relatedto M&A attempts.15

We also estimate long-horizon return performance usingthe calendar-time portfolio method recommended by Fama(1998) and Lyon, Barber, and Tsai (1999). We use both theFama and French (1993) three-factor model and the Carhart(1997) four-factor model to estimate abnormal returns.Our findings are robust using the calendar-time port-folio approach. The average post-buyback abnormalreturn differences between constrained and unconstrainedrepurchasers range from �0.44% to �0.39% per month(statistically significant at the 5% level), depending on themodel or weighting scheme.

3.2. Cross-sectional regression analyses

Table 4 presents cross-sectional regression analyses ofthe long-run stock price reactions to share repurchaseannouncements. The dependent variable is the annualbuy-and-hold abnormal return over the 4-year periodfollowing the repurchase announcement. We define avariable, financial constraint dummy, that equals one forconstrained repurchasers and zero for unconstrainedrepurchasers, where a firm’s financial constraint is mea-sured by the KZ index. The results are similar for the otherthree measures of financial constraints, so we do notreport them here.

In Model 1, the explanatory variable is the financial

constraint dummy. We control for the potential effects ofindustry-specific and year-specific differences by includ-ing one-digit SIC and year dummies in the regression. Thecoefficient on the financial constraint dummy variable is�0.0351, which is statistically significant at the 1% level.This result indicates that constrained firms experience along-run post-repurchase abnormal stock return of 3.51%per year lower than unconstrained firms after controllingfor industry and year effects.

In Model 2, we regress the long-run stock returnperformance of buyback firms against the financial

constraint dummy and a number of control variablessuggested by Massa, Rehman, and Vermaelen (2007),

15 When we eliminate repurchasers if they were announced as an

M&A target (according to the SDC) during the 3-year period before the

repurchase announcement, our conclusion is unchanged.

Table 3Initial and long-run stock price reactions to share repurchase announcements.

This table presents initial and long-run stock price responses to announcements of share repurchases for constrained and unconstrained firms,

according to four measures of financial constraints. The KZ index, cash–cash flow sensitivity, investment–cash flow sensitivity, and the WW index are

defined in Eqs. (1)–(4). Financially constrained firms are repurchasing firms in the highest quintile of the KZ index, cash–cash flow sensitivity,

investment–cash flow sensitivity, or the WW index. Financially unconstrained firms are repurchasing firms in other quintiles. Panel A shows the average

three-day buy-and-hold abnormal return (BHAR). The three-day BHAR measures the difference in the 3-day compound return between repurchasing

firms and matching firms from day –2 through day 0, where day 0 is defined as the initial announcement date. Matching firms are identified according to

the procedure described in Section 2.2.2. Panel B shows the average annual BHAR over the 4-year period following the repurchase announcement. We

calculate the average annual buy-and-hold returns for both repurchasing firms and matching firms from the first year (year þ1) following the repurchase

announcement to the fourth anniversary, or to a firm’s delisting date or December 2007 if the full sample period is not available. Each year is defined as a

uniform block of 252 trading days and year þ1 starts on the announcement date. The long-run abnormal stock performance of firms that announce

repurchase programs is measured by the difference between their average 4-year post-repurchase buy-and-hold returns and their matching firms’

returns. The number of observations varies across measures of financial constraints because of data availability. t-tests are used to test the hypotheses

that the means are equal to zero. Differences in mean are assessed using a t-test. t-statistics are reported in parentheses. nnn, nn, and n represent 1%, 5%,

and 10% significance level, respectively.

Panel A: Initial stock price reactions

Average three-day buy-and-hold raw return Average three-day buy-and-hold

abnormal return

Financial constraint measure N Sample firms Matching firms

KZ Index

Constrained firms 625 0.0001 �0.0024 0.0025

(0.01) (�1.65)n (0.68)

Unconstrained firms 4,085 0.0089 �0.0003 0.0092

(7.36)nnn (�0.53) (7.64)nnn

Mean difference �0.0088 �0.0021 �0.0067

(�2.56)nn (�1.36) (�2.02)nn

Cash–cash flow sensitivity


(1.61) (�0.18) (1.74)n


(8.65)nnn (�0.28) (9.15)nnn

Mean difference �0.0070 �0.0001 �0.0069

(�2.78)nnn (�0.05) (�2.82)nnn

Investment–cash flow sensitivity

Constrained firms 970 0.0032 0.0009 0.0023

(1.65)n (1.01) (1.21)


(7.76)nnn (�2.61)nnn (9.24)nnn

Mean difference �0.0064 0.0025 �0.0089

(�2.83)nnn (2.38)nn (�4.10)nnn

WW index


(1.02) (�0.78) (1.35)

Unconstrained firms 3,672 0.0202 0.0019 0.0183

(20.83)nnn (3.34)nnn (18.11)nnn

Mean difference �0.0149 �0.0041 �0.0107

(�2.70)nnn (�1.32) (�2.44)nn

Panel B: Long-run stock price reactions

Average annual buy-and-hold raw return Average annual buy-and-hold

abnormal return


KZ index

Constrained firms 625 0.0974 0.1271 �0.0298

(7.96)nnn (14.56)nnn (�2.52)nn


(38.21)nnn (47.72)nnn (2.96)nnn

Mean difference �0.0801 �0.0359 �0.0441

(�6.26)nnn (�3.83)nnn (�3.46)nnn

Cash–cash flow sensitivity


(20.19)nnn (25.25)nnn (�1.77)n


(37.47)nnn (47.68)nnn (3.30)nnn

Mean difference �0.0198 0.0095 �0.0293

(�2.64)nnn (0.08) (�2.92)nnn

Investment–cash flow sensitivity


(19.69)nnn (25.20)nnn (�2.01)nn


Table 3 (continued )

Panel B: Long-run stock price reactions

Average annual buy-and-hold raw return Average annual buy-and-hold

abnormal return



(29.23)nnn (38.70)nnn (2.16)nn

Mean difference �0.0326 �0.0054 �0.0272

(�3.58)nnn (�0.74) (�2.91)nnn

WW index


(5.35)nnn (8.91)nnn (�2.55)nn


(35.79)nnn (46.90)nnn (2.21)nn

Mean difference �0.0442 0.0266 �0.0708

(�1.81)n (1.25) (�2.96)nnn

Table 4Cross-sectional regression analyses of long-run stock price reactions to share repurchase announcements.

This table presents cross-sectional regression analyses of the long-run stock price reactions to share repurchase announcements. The dependent

variable is the average annual buy-and-hold abnormal return (BHAR) over the 4-year period following the repurchase announcement, where the measure

of the annual BHAR is described in Table 3. Financial constraint dummy equals one for financially constrained firms and zero for financially unconstrained

firms, where a firm’s financial constraint is measured by the KZ index as defined in Eq. (1). Repurchasing firms in the highest KZ quintile are considered

financially constrained; repurchasing firms in other KZ quintiles, financially unconstrained. Low HHI dummy equals one for repurchasers whose HH index

is below the median in the Compustat population and zero otherwise, where the HH index is the Herfindahl–Hirschman Index, measured by the sum of

the squared fraction of industry sales by all firms in the three-digit Standard Industrial Classification (SIC) industry for the year prior to the repurchase

announcement. Definitions of other variables are in Appendix A. The industry dummies are based on the one-digit SIC code. We also apply the Carhart

(1997) adaptation of the Fama and French (1993) method to calculate long-run abnormal returns associated with share repurchase announcements,

where the regression model is described in Eq. (7). The estimated intercept from this regression captures the average monthly abnormal return over the

four-year period following the repurchase announcement. We compute the t-values with heteroskedasticity-consistent standard errors (White, 1980).

The number of observations varies across regressions because of data availability. nnn, nn, and n represent 1%, 5%, and 10% significance level, respectively.

Dependent variable

Buy-and-hold abnormal return Carhart abnormal return

Independent variable Model 1 Model 2 Model 3 Model 4 Model 1 Model 2 Model 3 Model 4

Intercept 0.0058 0.0968 0.0819 0.1001 �0.0036 0.0071 0.0063 0.0211

(1.30) (0.93) (0.79) (0.97) (�1.48) (0.84) (0.75) (2.50)nn

Financial constraint dummy �0.0351 �0.0353 0.0202 �0.0283 �0.0026 �0.0022 0.0014 �0.0020

(�2.66)nnn (�2.62)nnn (0.88) (�2.15)nn (�2.37)nn (�1.96)nn (0.71) (�1.89)n

Intended buyback ratio 0.2034 0.2042 0.1848 0.0112 0.0112 0.0105

(2.11)nn (2.12)nn (1.93)n (1.45) (1.45) (1.43)

OMSR dummy �0.0237 �0.0234 �0.0217 �0.0030 �0.0030 �0.0024

(�1.63) (�1.61) (�1.50) (�2.53)nn (�2.52)nn (�2.12)nn

Size �0.0012 �0.0008 �0.0014 �0.0006 �0.0006 �0.0011

(�0.40) (�0.26) (�0.48) (�2.78)nnn (�2.66)nnn (�3.66)nnn

B/M �0.0178 �0.0177 �0.0191 0.0014 0.0015 0.0016

(�1.20) (�1.20) (�1.30) (1.21) (1.25) (1.50)

Prior AR �0.0140 �0.0141 �0.0115 �0.0003 �0.0003 �0.0003

(�1.19) (�1.20) (�0.98) (�0.35) (�0.35) (�0.33)

DA �0.2995 �0.2961 �0.3103 �0.0241 �0.0240 �0.0270

(�3.25)nnn (�3.22)nnn (�3.40)nnn (�3.23)nnn (�3.22)nnn (�3.84)nnn

DA missing dummy 0.0010 0.0025 �0.0013 0.0011 0.0012 0.0016

(0.10) (0.26) (�0.14) (1.46) (1.59) (2.23)nn

HH index �0.0394 �0.0400 �0.0375 �0.0030 �0.0030 �0.0041

(�1.63) (�1.66)n (�1.53) (�1.52) (�1.56) (�2.17)nn

Actual buyback dummy 0.0042 0.0139 0.0053 �0.0007 �0.0001 �0.0008

(0.45) (1.40) (0.61) (�0.89) (�0.10) (�1.11)

Financial constraint dummy �0.0831 �0.0052

� actual buyback dummy (�2.97)nnn (�2.27)nn


� low HHI dummy (�2.18)nn (�2.21)nn

Industry dummies Yes Yes Yes Yes Yes Yes Yes Yes

Year dummies Yes Yes Yes Yes Yes Yes Yes Yes

N 4,710 3,250 3,250 3,250 4,432 3,125 3,125 3,125

Adjusted R2 0.0019 0.0151 0.0175 0.0211 0.0371 0.0525 0.0538 0.0661

F-statistic 3.58nn 2.30nnn 2.47nnn 2.69nnn 5.61nnn 5.61nnn 5.60nnn 6.38nnn


17 We thank Kenneth French for making these factors publicly


Gong, Louis, and Sun (2008), and Peyer and Vermaelen(2009). Control variables are defined in Appendix A. Resultsof the Model 2 regression are consistent with all the resultsso far, although there are fewer observations because ofsome missing data. After we control for other potentialinfluences, we find that constrained firms still experienceless favorable long-run post-repurchase stock return perfor-mance than unconstrained firms. The coefficient on thefinancial constraint dummy is �0.0353, which is statisticallysignificant at the 1% level. Model 2 also shows that thecoefficient on the intended buyback ratio variable is signifi-cantly positive and that the coefficient on the DA variable issignificantly negative, as Chan, Ikenberry, and Lee (2004)and Gong, Louis, and Sun (2008) have suggested.

We further examine how the proportion of repurchasesactually undertaken determines the impact of financial con-straints on the post-repurchase stock performance of buy-back firms. If firms actually buy back more shares after arepurchase announcement, their cash balances are morelikely to decline and their financial leverage to increase. Withless corporate liquidity following repurchases, constrainedfirms with higher actual buyback ratios should experiencepoorer post-repurchase performance. Model 3 includes allthe variables in Model 2 plus an interaction term, financial

constraint dummy� actual buyback dummy, where actual

buyback dummy equals one if the actual buyback ratio inthe first four quarters after the repurchase announcement ishigher than the sample median and zero otherwise.16 Theresults now show that the coefficient on the interaction termis �0.0831, which is statistically significant at the 1% level,indicating that constrained firms with high buyback ratiosexperience a post-buyback abnormal return of 8.31% per yearlower than constrained firms with low buyback ratios aftercontrolling for other determining factors. The coefficient onthe financial constraint dummy is 0.0202, but it is statisticallyinsignificant. These findings are consistent with our predic-tion that the post-repurchase stock performance of con-strained firms is more vulnerable for firms with high actualbuyback ratios. Financial constraints are less important inexplaining the long-run stock performance of share buybacksfor firms with a low actual repurchase ratio. Our results alsosuggest that actual repurchases, and not so much announce-ments of the repurchase program per se, determine perfor-mance deterioration for constrained repurchasers.

In Model 4, we replace financial constraint dummy� ac-

tual buyback dummy by financial constraint dummy� low

HHI dummy, where low HHI dummy equals one forrepurchasers whose HH index is below the median inthe Compustat population and zero otherwise. The HH

index is the Herfindahl–Hirschman Index, which is mea-sured by the sum of the squared fraction of industry salesby all firms in the three-digit SIC industry for the yearprior to the repurchase announcement. A lower HH index

indicates greater product market competition. If dam-pened corporate liquidity following share buybacksmakes constrained firms less competitive due to

16 Stephens and Weisbach (1998) show that a substantial portion of

buyback activity occurs in the first year of a repurchase program, so we

focus on the actual buyback in the first four quarters after the

repurchase announcement.

underinvestment in the product market, we expect themto suffer poorer post-repurchase stock performance whenthey face greater market competition. The coefficient onfinancial constraint dummy � low HHI dummy is �0.0572,which is statistically significant at the 5% level. This resultindicates that constrained firms in more competitiveindustries experience a post-repurchase abnormal returnthat is 5.72% per year lower than constrained firms in lesscompetitive industries.

To assess the robustness of the regression results, weapply the Carhart (1997) adaptation of the Fama andFrench (1993) method to calculate long-run abnormalreturns associated with share repurchase announcements.Specifically, we use the calendar-time regression approachsuggested by Fama (1998), Mitchell and Stafford (2000),and Grullon and Michaely (2004). The regression model is

Rit2Rf t ¼ aiþbiðRmt2Rf tÞþsiSMBtþhiHMLtþpiPR1YRtþeit ,

ð7Þ

where Rit is the return on firm i in month t; Rft is the returnon one-month Treasury bills in month t; Rmt is the return ona market index in month t; SMBt is the difference in thereturns of a portfolio of small and big stocks in month t;HMLt is the difference in the returns of a portfolio of highbook-to-market stocks and low book-to-market stocks inmonth t; PR1YRt is the difference in the returns of a portfolioof prior-year high return stocks and prior-year low returnstocks in month t; and eit is the error term for firm i in montht.17 The estimated intercept from this regression captures theaverage monthly abnormal return over the 4-year periodfollowing the repurchase announcement.

The last four columns in Table 4 report cross-sectionalregression analyses of the long-run stock price reactionsto repurchase announcements using this measure ofabnormal returns as the dependent variable. The resultsare similar to those using annual BHARs to measureabnormal returns. Constrained firms earn a post-repurch-ase abnormal return that is 0.22–0.26% lower per month(or 2.64–3.12% lower per year) than unconstrained firms,and constrained firms with high buyback ratios earn0.52% less per month (or 6.24% less per year) thanconstrained firms with low buyback ratios. Our evidenceagain indicates that constrained firms, especially thosewith high actual buyback ratios, experience poorer long-run post-repurchase stock return performance thanunconstrained firms. Table 4 also shows that constrainedfirms experience poorer post-repurchase performancewhen they face greater product market competition. Thepost-repurchase abnormal return is 0.30% lower permonth (or 3.60% lower per year) for constrained firms inmore competitive industries.18

available at his website (http://mba.tuck.dartmouth.edu/pages/faculty/

ken.french/).18 Following Shumway (1997), Shumway and Warther (1999), and

Eberhart, Maxwell, and Siddique (2004), we also correct for a delisting

bias for the firms in our sample that are delisted for performance

reasons. The conclusions remain unchanged.

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/


4. Effects of financial constraints on operatingperformance and financial distress risk

4.1. Post-repurchase operating performance

We examine whether the poorer stock performanceof financially constrained firms is attributable to theirpoorer operating performance following share repurchases.

Table 5Changes in abnormal operating performance following share repurchase annou

This table presents the effects of financial constraints on post-repurchase change

operating performance over the eight quarters following the repurchase announcem

performance is measured by return on assets (ROA), which is defined as operating i

operating performance for a given firm is the firm-specific ROA minus the ROA of i

firm’s financial constraint is measured by the KZ index as defined in Eq. (1). R

repurchasing firms in other KZ quintiles, unconstrained. Wilcoxon signed-rank test

Differences in median changes are assessed using a Wilcoxon rank-sum test. p-val

analyses of the changes in abnormal operating performance. Financial constraint du

HHI dummy equals one for repurchasers whose HH index is below the median in

Herfindahl-Hirschman Index, measured by the sum of the squared fraction of ind

(SIC) industry for the year prior to the repurchase announcement. Definitions of oth

digit SIC code. We include nonlinearity controls by incorporating expected earnin

French, 2000). We compute the t-values with heteroskedasticity-consistent st

regressions because of data availability. nnn, nn, and n represent 1%, 5%, and 10% si

Panel A: Changes in abnormal operating performance

Category N Sample firms

Constrained firms 401 �0.2889

(0.00)nnn

Unconstrained firms 3,056 �0.1469

(0.00)nnn

Median difference �0.1421

(0.04)nn

Panel B: Cross-sectional regression analyses

Independent variable Model 1

Intercept 3.0218

(1.44)

Financial constraint dummy �0.4067

(�2.16)nn (

Intended buyback ratio

OMSR dummy(

Size

DA

DA missing dummy

HH index

Actual buyback dummy

Financial constraint dummy� actual buyback dummy

Financial constraint dummy� low HHI dummy

Industry dummies Yes

Year dummies Yes

Nonlinearity controls Yes

N 3,457

Adjusted R2 0.0397

F-statistic 3.09nnn

Reduced corporate liquidity resulting from repurchasesmakes it harder for constrained firms to finance futureinvestment, leading to underinvestment in the productmarket. Constrained firms could thus be less able tocompete and suffer poorer operating performance follow-ing repurchases.

In Table 5, we examine the median changes in abnormaloperating performance for constrained and unconstrained

ncements.

s in operating performance. Panel A shows the median changes in abnormal

ent quarter (quarter 0) for constrained and unconstrained firms. Operating

ncome divided by total assets at the beginning of the quarter. The abnormal

ts matching firm. See Section 2.2.3 for details on the matching procedure. A

epurchasing firms in the highest KZ quintile are considered constrained;

s are used to test the hypotheses that the median changes are equal to zero.

ues are reported in parentheses. Panel B presents cross-sectional regression

mmy equals one for constrained firms and zero for unconstrained firms. Low

the Compustat population and zero otherwise, where the HH index is the

ustry sales by all firms in the three-digit Standard Industrial Classification

er variables are in Appendix A. The industry dummies are based on the one-

gs, past earnings changes, and their nonlinear ingredients (as in Fama and

andard errors (White, 1980). The number of observations varies across

gnificance level, respectively.

Median change Median change in

in ROA (percent) abnormal ROA

Matching firms (percent)

0.0279 �0.2589

(0.74) (0.04)nn

�0.3510 0.2826

(0.00)nnn (0.00)nnn

0.3789 �0.5415

(0.07)n (0.04)nn

Model 2 Model 3 Model 4

3.0414 2.9576 3.1404

(1.42) (1.37) (1.47)

�0.4128 0.1795 �0.2073

�2.17)nn (0.44) (�1.71)n

0.0058 0.0063 0.0008

(0.96) (1.04) (0.13)

�0.8847 �0.8798 �0.8682

�3.79)nnn (�3.77)nnn (�3.72)nnn

0.0856 0.0902 0.0710

(1.49) (1.59) (1.29)

0.2231 0.2331 0.1710

(0.33) (0.34) (0.30)

�0.0181 �0.0083 �0.0022

(�0.16) (�0.07) (�0.02)

0.0648 0.0520 0.0087

(0.16) (0.13) (0.02)

0.4354 0.5233 0.3601

(5.10)nnn (6.92)nnn (4.14)nnn

�0.8574

(�2.13)nn

�0.4509

(�2.42)nn

Yes Yes Yes

Yes Yes Yes

Yes Yes Yes

2,608 2,608 2,6080.0441 0.0443 0.0470

2.91nnn 2.87nnn 2.92nnn


firms according to the KZ index over the eight quartersfollowing the repurchase announcement quarter (quarter 0).We obtain similar results for the other three measures offinancial constraints. Wilcoxon signed-rank tests are used totest the hypothesis that the median changes are equal tozero. These tests are more powerful than t-tests in detectingabnormal operating performance (Barber and Lyon, 1996;Loughran and Ritter, 1997).

Panel A of Table 5 shows that constrained repurchasershave a median change in abnormal ROA of �0.2589% overthe eight-quarter post-repurchase period (significantlydifferent from zero at the 5% level), compared with0.2826% for unconstrained repurchasers (significantlydifferent from zero at the 1% level).19 The difference inthe median change of abnormal ROA between constrainedand unconstrained firms is �0.5415%, which is statisti-cally significant at the 5% level by a Wilcoxon rank-sumtest. The results indicate that post-buyback operatingperformance is poorer for constrained firms than forunconstrained firms.

Panel B of Table 5 presents cross-sectional regressionanalyses of the changes in abnormal operating perfor-mance over the eight-quarter post-repurchase period,where the number of observations varies across regres-sions because of data availability. In Model 1 the financial

constraint dummy is the explanatory variable. We alsoinclude one-digit SIC and year dummies to control for thepotential effects of industry-specific and year-specificdifferences. As the mean reversion process of profitabilityis highly nonlinear, we also include nonlinearity controlsby incorporating expected earnings, past earningschanges, and their nonlinear ingredients (as in Fama andFrench, 2000; Grullon and Michaely, 2004). In Model 1 thecoefficient on the financial constraint dummy variable isnegative and statistically significant at the 5% level. Thisresult again indicates less favorable post-repurchaseabnormal operating performance for constrained firms.

In Model 2, we regress the changes in post-buybackoperating performance against the financial constraint

dummy and several control variables suggested in theliterature (e.g., Comment and Jarrell, 1991; Grullon andIkenberry, 2000; Lie, 2005; Massa, Rehman, andVermaelen, 2007; Gong, Louis, and Sun, 2008). Aftercontrolling for these other potential explanatory vari-ables, constrained firms still experience less favorablepost-buyback operating performance than unconstrainedfirms. The coefficient on the financial constraint dummy isnegative and statistically significant at the 5% level. Model2 also shows that post-buyback operating performance isless favorable for an open market share repurchaseannouncement or for a repurchasing firm with a lowactual buyback ratio, as previous studies have suggested.

19 For the whole sample, the median changes in ROA are �0.1638%

for the sample firms and �0.2854% for the matching firms, both

statistically significantly different from zero at the 1% level. The median

change in abnormal ROA is 0.2217%, statistically significant at the 1%

level. The results are consistent with the Lie (2005) findings. Both the

sample firms and the matching firms experience poorer post-buyback

operating performance as a result of mean reversion, with the decline

less pronounced for the sample firms.

In Model 3, we add an interaction term, financial

constraint dummy� actual buyback dummy, to examinehow the actual buyback ratio affects the impact offinancial constraints on the post-repurchase operatingperformance of buyback firms. The coefficient on theinteraction term is negative and statistically significantat the 5% level, but the coefficient on the financial

constraint dummy is no longer significant. As constrainedfirms with high actual buyback ratios are likely to sufferreduced corporate liquidity following repurchases, theirpost-repurchase operating performance is more vulner-able to competition. Financial constraints are less impor-tant in explaining operating performance after sharebuyback for firms with low actual repurchase ratios.Again, our results suggest that the actual repurchases,not announcements of a repurchase program per se,appear to determine the deterioration in operating per-formance for constrained firms.

In Model 4, we substitute financial constraint dum-

my� low HHI dummy for financial constraint dummy� ac-

tual buyback dummy. The coefficient on this interactionterm is negative and statistically significant at the 5%level. As dampened corporate liquidity following sharebuybacks makes constrained firms less competitive due tothe difficulty of financing future investment, post-repurchase operating performance is poorer for con-strained firms facing greater product market competition.

4.2. Post-repurchase distress risk

Share buybacks result in lower cash levels and higherleverage ratios, both of which put a firm at greater risk offinancial distress. This increase in the risk of distress isexpected to be higher for financially constrained firms,because they are more likely to have less corporateliquidity subsequent to the repurchases. In Table 6, weexamine the impact of share buybacks on financial dis-tress risk for constrained firms versus unconstrained firmsaccording to the KZ index. The results are similar for otherthree measures of financial constraints.

Subpanel A1 presents the mean Altman (1968) Z-scorein the year before the repurchase announcement (year�1) and over the 4-year period following the announce-ment year (years þ1 to þ4). The mean change in theZ-score from year �1 through year þ4 is significantlynegative at the 1% level for both constrained and uncon-strained firms but constrained firms experience a signifi-cantly greater decline in Z-score following the repurchaseannouncement (�2.69 compared with �0.81). The meandifference between the changes for the two groups is�1.88, which is statistically significant at the 1% level.We also find that the mean Z-scores are similar forconstrained and unconstrained firms in year �1, butconstrained firms have significantly lower mean Z-scoresin years þ1 to þ4. The results in Subpanel A1 indicatethat the risk of financial distress increases significantly forall repurchasing firms after repurchase announcements,but the effect is stronger for constrained firms.

Subpanel A2 shows the fraction of repurchasing firmswith a high probability of default (Altman Z-score under1.81). The proportion of firms with a high probability of

Table 6Changes in financial distress risk following share repurchase announcements.

This table presents the effects of financial constraints on post-repurchase changes in distress risk. Subpanel A1 reports the average Altman (1968)

Z-score for constrained and unconstrained firms in the year before the repurchase announcement (year �1) and over the 4-year period following the

repurchase announcement year (years þ1 to þ4). Altman’s Z-score is defined in Eq. (6). A firm’s financial constraint is measured by the KZ index as

defined in Eq. (1). Repurchasing firms in the highest KZ quintile are considered constrained; repurchasing firms in other KZ quintiles, unconstrained.

Subpanel A2 shows the proportion of repurchasing firms with a Z-score under 1.81 in years �1 to þ4. Subpanel A3 reports the average matching-firm

adjusted Z-score in years �1 to þ4. The matching procedure for abnormal Z-scores, measured by the difference between the repurchasing and matching

firms’ Z-scores, is identical to the matching procedure for abnormal stock returns described in Section 2.2.2. In Subpanels A1 and A3, t-tests are used to

test the hypotheses that the mean changes are equal to zero. Differences in mean are assessed using a t-test. t-statistics are reported in parentheses. In

Subpanel A2, we use Fisher’s exact test to test the significance of differences in proportions. p-values are reported in parentheses. Panel B presents cross-

sectional regression analyses of the changes in abnormal Z-scores from year �1 through year þ4. Financial constraint dummy equals one for constrained

firms and zero for unconstrained firms. Definitions of other variables are in Appendix A. The industry dummies are based on the one-digit Standard

Industrial Classification (SIC) code. We compute the t-values with heteroskedasticity-consistent standard errors (White, 1980). The number of

observations varies because of data availability. nnn, nn, and n represent 1%, 5%, and 10% significance level, respectively.

Panel A: Changes in financial distress risk

Category Year �1 Year þ1 Year þ2 Year þ3 Year þ4 Change from year �1 to þ4

Subpanel A1: Z-score

Constrained firmsN 460 369 282 209 141

Mean 6.13 5.06 4.90 4.16 3.44 �2.69 (�4.98)nnn

Unconstrained firms

N 3,707 3,411 2,720 2,069 1,654

Mean 6.40 5.82 5.72 5.63 5.59 �0.81 (�4.99)nnn

Mean difference �0.27 �0.76 �0.82 �1.47 �2.15 �1.88

(�1.15) (�2.19)nn (�3.84)nnn (�5.96)nnn (�4.14)nnn (�2.77)nnn

Subpanel A2: Proportion of firms with Z-scores below 1.81


Percent 25.43 29.00 30.50 34.45 38.30 12.87 (0.00)nnn

Unconstrained firms

N 3,707 3,411 2,720 2,069 1,654

Percent 7.66 9.21 10.74 11.60 11.49 3.83 (0.00)nnn

Percent difference17.77 19.79 19.76 22.85 26.81 9.04

(0.00)nnn (0.00)nnn (0.00)nnn (0.00)nnn (0.00)nnn (0.00)nnn

Subpanel A3: Abnormal Z-score


Mean 1.14 0.60 0.89 0.36 �0.56 �1.70 (�2.07)nn

Unconstrained firms

N 3,476 3,201 2,557 1,954 1,557

Mean 0.64 0.51 0.69 0.62 0.69 0.05 (0.31)

Mean difference 0.50 0.09 0.20 �0.26 �1.25 �1.75

(1.06) (1.07) (1.13) (�2.39)nn (�1.98)nn (�3.00)nnn

Panel B: Cross-sectional regression analyses of changes in abnormal Z-score

Independent variable Model 1 Model 2 Model 3

Intercept 1.9541 1.4745 1.4614

(0.49) (0.33) (0.32)

Financial constraint dummy �2.1462 �2.2073 �0.5786

(�2.44)nn (�2.51)nn (�0.50)

Intended buyback ratio 0.0073 0.0047

(0.22) (0.14)

OMSR dummy 0.3465 0.2833

(0.42) (0.34)

Size 0.1950 0.1987

(1.57) (1.60)

DA �0.1479 �0.1679

(�0.10) (�0.11)

DA missing dummy �0.2145 �0.2124

(�0.41) (�0.41)

HH index �2.4785 �2.5508

(�2.23)nn (�2.29)nn

Actual buyback dummy 0.3548 0.6195

(0.78) (1.31)


� actual buyback dummy (�2.19)nn


Table 6 (continued )

Panel B: Cross-sectional regression analyses of changes in abnormal Z-score


Industry dummies Yes Yes Yes

Year dummies Yes Yes Yes

N 1,684 1,616 1,616

Adjusted R2 0.0018 0.0027 0.0051

F-statistic 2.26nnn 1.77nn 2.15nnn


default increases significantly for both groups from year�1 through year þ4 (from 25.43% to 38.30% for con-strained firms and from 7.66% to 11.49% for uncon-strained firms), using Fisher’s exact tests. The increase ismuch greater for constrained firms (12.87%) than forunconstrained firms (3.83%); the difference 9.04% isstatistically significant at the 1% level. Again, financiallyconstrained repurchasers are more likely to be at risk offinancial distress following a repurchase announcement.

In Subpanel A3, we use matching-firm adjustedZ-scores to control for differences in the probability offinancial distress across firm size, book-to-market ratios,and financial constraints. We identify matching firmsusing size, B/M, and the KZ index, because these areimportant factors that explain cross-sectional variationin corporate distress risk and equity risk premium (seeChan and Chen, 1991; Fama and French, 1993, 1995,1996; Griffin and Lemmon, 2002; Whited and Wu,2006). The matching procedure for abnormal Z-scores,measured by the difference between repurchasing andmatching firms’ Z-scores, is identical to the matchingprocedure for abnormal stock returns. The results forconstrained firms in Subpanel A3 are consistent with theresults in Subpanel A1. Constrained firms experience asignificant increase over matching firms in financial dis-tress risk from year �1 to year þ4. The increase indistress risk is significantly greater for constrained firmsthan for unconstrained firms. The mean differencebetween the changes in the abnormal Z-score from year�1 to year þ4 for the two groups is �1.75, which isstatistically significant at the 1% level. We also find nosignificant difference in the mean abnormal Z-scorebetween constrained and unconstrained firms in year�1, but constrained firms have significantly lower meanabnormal Z-scores in years þ3 and þ4.

Panel B of Table 6 presents cross-sectional regressionanalyses of the changes in financial distress risk, wherethe dependent variable is the change in the abnormalZ-score from year �1 through year þ4. In Model 1, theexplanatory variable is the financial constraint dummy. Wealso control for the potential effects of industry-specificand year-specific differences by including industry andyear dummies. The coefficient on the financial constraint

dummy variable is negative and statistically significant atthe 5% level. The results again indicate that constrainedfirms exhibit greater increases in financial distress riskassociated with share buybacks than unconstrained firms.

In Model 2, we add the same control factors as inTable 5. After controlling for these potentially influentialvariables, the increase in financial distress risk followingthe repurchase announcement remains significantlygreater for constrained firms. The coefficient on thefinancial constraint dummy is significantly negative at the5% level. Model 2 also shows a significantly negativecoefficient on the HH index, a result consistent withMassa, Rehman, and Vermaelen (2007). Share buybacksare more likely to be chosen as a strategic reaction toother firms’ repurchase decisions when industry concen-tration increases, so the increase in financial distress riskfollowing the buyback tends to occur for repurchasers inmore concentrated industries.

In Model 3, we include all the variables in Model 2along with the interaction term, financial constraint dum-

my� actual buyback dummy. The coefficient on the inter-action term is significantly negative at the 5% level, butthe coefficient on the financial constraint dummy is notsignificant. The results suggest that constrained firmswith high actual buyback ratios are more likely to sufferlow corporate liquidity and hence higher financial distressrisk following the repurchase. Financial constraints areless important in explaining the change in financialdistress risk associated with share repurchases for firmswith a low actual buyback ratio.

5. Why do financially constrained firms buy back shares?

Repurchasing reduces corporate liquidity and producesmore financial constraints. In the post-buyback period,constrained firms experience poorer stock price and oper-ating performance and higher default risk than uncon-strained firms. Why then does a constrained firm buy backits own shares when the buyback does not enhanceshareholder wealth? A possible explanation is managerialhubris (or managerial overconfidence). We report ourevidence using the financial constraint categorizationprovided by the KZ index. Findings are similar if we usethe other three financial constraint categorizations.

5.1. Managerial hubris and financial constraints of

repurchasing firms

Malmendier and Tate (2005, 2008) note that risk-aversemanagers would reduce their exposure to company-specificrisk by exercising in-the-money executive stock options

Table 7Institutional ownership, financial analyst coverage, and in-the-money

vested stock options held by top executives surrounding share repurch-

ase announcements.

This table presents the average institutional ownership, financial

analyst coverage, and in-the-money vested stock options held by top

executives of constrained and unconstrained firms for two years before

and one year after the repurchase announcement (years �2 to þ1).

Institutional ownership is measured by the percentage of equity own-

ership held by institutional investors, as provided by Thomson Financial.

Analyst coverage is measured by the number of financial analysts

following the firm as reported by Institutional Brokers’ Estimate System

(I/B/E/S), where firms not covered by I/B/E/S are assumed to have zero

analyst coverage. Vested options are defined as unexercised exercisable

options. To standardize the option holdings, we scale them by total

shares outstanding. We winsorize institutional ownership, analyst

coverage, and the option holdings at the 1st and 99th percentiles to

reduce the effects of a few extreme values. Compensation information

for the top five executives of the firms comes from Standard & Poor’s

ExecuComp database. For data availability reasons, we start the analysis

on in-the-money vested stock options in 1992. A firm’s financial

constraint is measured by the KZ index as defined in Eq. (1). Repurchas-

ing firms in the highest KZ quintile are considered constrained;

repurchasing firms in other KZ quintiles, unconstrained. Differences in

mean are assessed using a t-test. t-statistics are reported in parentheses.

The number of observations varies because of data availability. nnn, nn,

and n represent 1%, 5%, and 10% significance level, respectively.

Category Year �2 Year �1 Year þ1

Panel A: Institutional ownership

Constrained firms

N 562 613 619

Mean 42.98% 43.80% 33.46%

Unconstrained firms

N 3,824 4,041 4,056

Mean 45.55% 47.84% 40.57%

Mean difference �2.57% �4.04% �7.10%

(�1.86)n (�3.04)nnn (�5.07)nnn

Panel B: Analyst coverage

Constrained firms

N 598 628 483

Mean 5.50 6.45 6.95

Unconstrained firms

N 4,006 4,082 3,672

Mean 6.59 7.15 7.35

Mean difference �1.09 �0.70 �0.40

(�6.06)nnn (�3.93)nnn (�2.24)nn

Panel C: In-the-money vested stock options

Constrained firms

N 303 319 288

Mean 0.77% 0.74% 0.71%

Unconstrained firms

N 2,202 2,320 2,325

Mean 0.56% 0.58% 0.56%

Mean difference 0.21% 0.16% 0.15%

(3.20)nnn (2.85)nnn (2.97)nnn


before the options expire. If managers are overconfidentabout the future returns of their firms, they are more likelyto delay their exercise of in-the-money vested options.Ben-David, Graham, and Harvey (2007) suggest that over-confident managers tend to repurchase shares when theyoverestimate their firm’s future returns and think themarket undervalues their equity. Therefore, if top managersof financially constrained firms are more likely to be over-confident about future returns, we would expect them tohold more in-the-money unexercised vested options thanmanagers of financially unconstrained firms around theannouncement of share repurchases, even though therepurchases are not beneficial to shareholder wealth.

Managers of financially constrained firms are moreprone to be overconfident about their firm’s future returnsand buy back shares for at least two reasons. First, over-confident managers who believe the equity of their firmsis undervalued (although this is usually not true) woulduse more internal funds and debt financing and less netequity issuance. This suggests that firms with overconfi-dent managers tend to have lower dividend payouts,higher leverage, and lower net equity issuance. Ben-David,Graham, and Harvey (2007) and Malmendier, Tate, and Yan(2011) provide supporting evidence for this relation.Because lower dividend payouts and higher leverage areassociated with a higher degree of financial constraint,and share repurchases reduce net equity issuance, firmswith overconfident managers are likely to be financiallyconstrained and engage in share repurchases.

Second, managers of firms with limited financialresources or with less external equity financing tend tobe overconfident. Firms without ample resources arelikely to have fewer human and financial resources avail-able to devote to scanning and processing environmentalinformation. Managers of such firms thus might acceptnegative net present value projects and make investmentmistakes. Managers of firms without active externalfinancing have weaker outside monitoring. Inactive exter-nal financing usually yields smaller institutional holdingsand less analyst coverage. Given that institutional hold-ings and analyst coverage are regarded as effective gov-ernance mechanisms in monitoring and discipliningmanagers (Cremers and Nair, 2005; Yu, 2008; Biddle,Hilary, and Verdi, 2009), managers of firms without activeexternal financing are more likely to invest in poorprojects. Therefore, managers of financially constrainedfirms, which usually have fewer financial resources andlack outside monitoring, tend to be overconfident.20

We first examine whether constrained repurchasersare subject to less external monitoring than uncon-strained repurchasers. Panels A and B of Table 7 showaverage institutional ownership and financial analystcoverage of firms in the two years preceding and theone year following buyback announcements (years �2to þ1). Institutional ownership is measured by thepercentage of equity held by institutional investors, as

20 Forbes (2005) provides evidence that managers of small firms,

which typically have limited resources and high degrees of financial

constraints (Almeida, Campello, and Weisbach, 2004), are likely to be

overconfident.

provided by Thomson Financial. Analyst coverage ismeasured by the number of financial analysts followingthe firm as reported by Institutional Brokers’ EstimateSystem (I/B/E/S), where firms not covered by I/B/E/S areassumed to have zero analyst coverage (as in Biddle, Hilary,and Verdi, 2009; Chang, Dasgupta, and Hilary, 2009).21 Wewinsorize institutional ownership and analyst coverage at

21 Conclusions remain unchanged if only sample firms covered by I/

B/E/S are examined.

Table 8Cross-sectional regression analyses of in-the-money vested options.

This table presents cross-sectional regression analyses of in-the-

money vested stock options held by top executives of repurchasing

firms, where vested options are defined as unexercised exercisable

options. To standardize the option holdings, we scale them by total

shares outstanding. We winsorize the option holdings at the 1st and

99th percentiles to reduce the effects of a few extreme values. The

dependent variable is the average in-the-money vested options for two

years before and one year after the repurchase announcement. Financial

constraint dummy equals one for constrained firms and zero for uncon-

strained firms, where a firm’s financial constraint is measured by the KZ

index as defined in Eq. (1). Repurchasing firms in the highest KZ quintile

are considered constrained; repurchasing firms in other KZ quintiles,

unconstrained. Definitions of other variables are in Appendix A. The

industry dummies are based on the one-digit Standard Industrial

Classification code. We compute the t-values with heteroskedasticity-

consistent standard errors (White, 1980). nnn, nn, and n represent 1%, 5%,



Intercept 0.0059 0.0225 0.0292

(9.86)nnn (17.99)nnn (21.81)nnn

Financial constraint dummy 0.0011 0.0012 0.0008

(3.26)nnn (3.69)nnn (2.67)nnn

Intended buyback ratio �0.00002 0.00001

(�1.15) (0.91)

OMSR dummy 0.0005 0.0005

(1.26) (1.22)

Size �0.0012 �0.0015

(�16.37)nnn (�20.09)nnn

DA �0.0006 �0.0004

(�0.73) (�0.49)

DA missing dummy 0.0001 0.0004

(0.56) (1.61)

HH index �0.0022 �0.0021

(�4.34)nnn (�4.16)nnn

Actual buyback dummy 0.00002 0.00001

(0.10) (0.07)

B/M �0.0042

(�12.13)nnn

Prior AR �0.00001

(�0.06)

Industry dummies Yes Yes Yes


N 2,728 2,728 2,728

Adjusted R2 0.0696 0.2014 0.1584

F-statistic 9.38nnn 21.54nnn 17.31nnn


the 1st and 99th percentiles to reduce the effects of a fewextreme values. Constrained repurchasers are found to havesignificantly lower institutional ownership and analystcoverage than unconstrained repurchasers in years �2 toþ1, based on t-tests. Thus, constrained repurchasersare subject to weaker external monitoring than uncon-strained repurchasers, resulting in greater managerialoverconfidence.

We next examine whether managers of constrainedfirms hold more in-the-money unexercised vested optionsthan managers of unconstrained firms in the years aroundthe announcement of share repurchases. Panel C ofTable 7 presents the average in-the-money vested optionsheld by top executives in years �2 to þ1. Vested optionsare defined as unexercised exercisable options. To stan-dardize the option holdings, we scale them by total sharesoutstanding. We winsorize the option holdings at the 1stand 99th percentiles to reduce the effects of a fewextreme values. Compensation information for the topfive executives of the firms comes from Standard & Poor’sExecuComp database. For data availability reasons, westart the analysis in 1992.

Panel C shows that the average holdings in year �2 toyear þ1 are 0.77%, 0.74%, and 0.71% for constrained firms,compared with only 0.56%, 0.58%, and 0.56% for uncon-strained firms, respectively. The differences in the averagevested option holdings between the two groups are statis-tically significant at the 1% level. Constrained firm managershold a significantly higher average proportion of in-the-money vested options in both the two years preceding andthe one year following the repurchase announcement. Theseresults imply that share repurchases by constrained firms,regardless of their negative impact on shareholder wealth,are at least partially affected by managerial overconfidence.

Table 8 presents cross-sectional regression analyses ofin-the-money vested options for the repurchasing firms.The dependent variable is the average in-the-moneyvested options for two years before and one year afterthe repurchase announcement.22 Model 1 includes thefinancial constraint dummy as the explanatory variable andindustry and year dummies to control for the potentialeffects of industry-specific and year-specific differences.The coefficient on the financial constraint dummy variableis 0.0011, which is statistically significant at the 1% level,indicating that the average proportion of in-the-moneyvested options held by managers is 0.11% higher forconstrained firms than for unconstrained firms in theyears around the repurchase announcement. Model 2adds the same control variables as in Tables 5 and 6.The coefficient on the financial constraint dummy variableis 0.0012 and still statistically significant at the 1% levelafter we control for potentially influential variables. InModel 3, we also control for B/M and prior AR, which couldaffect stock return performance associated with repurch-ase announcements. The result for the financial constraint

dummy variable is similar (the coefficient is 0.0008 and

22 We take the average of nonmissing in-the-money vested options

over the three-year period. The results are similar if the dependent

variable is in-the-money vested options for the year preceding the

announcement.

statistically significant at the 1% level). The overall find-ings in Table 8 are again consistent with our managerialhubris explanation. The coefficients on size, HH index, andB/M are significantly negative. Managerial overconfidenceis more likely to occur for small or high-growth firms orfor firms in intense product market competition, consis-tent with Forbes (2005) and Galasso and Simcoe (2011).

5.2. Linking managerial overconfidence to post-repurchase

returns and firms’ motives for repurchasing

We examine whether firms with more overconfidentmanagers experience poorer post-buyback returns whenthey are financially constrained. Model 1 of Table 9reports regressions of long-run stock return performanceover the four-year period following the repurchaseannouncement, measured by buy-and-hold or Carhartabnormal returns. The explanatory variables are financial

Table 9Cross-sectional regression analyses of long-run stock price reactions to share repurchase announcements: managerial overconfidence explanation.

This table examines whether firms with more overconfident managers experience poorer post-buyback returns when they are financially constrained.

The dependent variable is buy-and-hold or Carhart abnormal returns over the post-repurchase period as measured in Table 4. Financial constraint dummy

equals one for constrained firms and zero for unconstrained firms, where a firm’s financial constraint is measured by the KZ index as defined in Eq. (1). In-

the-money options are the three-year average in-the-money vested stock options for two years before and one year after the repurchase announcement.

Institutional ownership is the average percentage of equity ownership held by institutional investors, and analyst coverage is the average number of

financial analysts following the firm as reported by Institutional Brokers’ Estimate System (I/B/E/S) for two years before and one year after the repurchase

announcement, where firms not covered by I/B/E/S are assumed to have zero analyst coverage. In-the-money options missing dummy equals one if in-the-

money options are not available and zero otherwise. Definitions of other variables are in Appendix A. We compute the t-values with heteroskedasticity-

consistent standard errors (White, 1980). The number of observations varies across regressions because of data availability. nnn, nn, and n represent 1%, 5%,


Buy-and-hold abnormal return Carhart abnormal return

Independent variable Model 1 Model 2 Model 3 Model 1 Model 2 Model 3

Intercept 0.1279 0.0239 0.0237 0.0133 0.0018 0.0104

(1.36) (0.27) (0.25) (1.40) (0.20) (1.14)

Financial constraint dummy �0.0117 �0.0561 �0.0585 �0.0006 �0.0077 �0.0061

(�0.90) (�3.27)nnn (�3.67)nnn (�0.45) (�2.99)nnn (�3.80)nnn

In-the-money options 1.5981 0.0425

(1.79)n (0.49)


� in-the-money options (�2.05)nn (�2.21)nn

Institutional ownership �0.0203 �0.0019

(�0.66) (�0.84)

Financial constraint dummy 0.1217 0.0143

� institutional ownership (1.96)nn (2.49)nn

Analyst coverage 0.0003 0.0001

(0.31) (0.70)

Financial constraint dummy 0.0036 0.0004

� analyst coverage (2.04)nn (2.22)nn

In-the-money options missing dummy �0.0380 �0.0032

(�3.28)nnn (�2.75)nnn

Intended buyback ratio 0.0231 0.0843 0.0455 0.0088 0.0119 0.0031

(0.28) (1.04) (0.58) (1.10) (1.40) (0.41)

OMSR dummy �0.0171 �0.0093 �0.0113 �0.0032 �0.0028 �0.0028

(�1.32) (�0.74) (�0.88) (�2.63)nnn (�2.17)nn (�2.26)nn

Size �0.0060 0.0005 0.0010 �0.0011 �0.0003 �0.0011

(�1.85)n (0.20) (0.25) (�3.47)nnn (�0.99) (�2.90)nnn

B/M 0.0066 �0.0018 0.0048 0.0007 0.0016 �0.00004

(0.50) (�0.14) (0.31) (0.54) (1.20) (�0.02)

Prior AR �0.0050 �0.0017 �0.0034 0.0001 0.0002 0.00001

(�0.49) (�0.17) (�0.30) (0.12) (0.16) (0.01)

DA �0.2216 �0.1949 �0.3329 �0.0222 �0.0178 �0.0286

(�2.72)nnn (�2.42)nn (�3.25)nnn (�3.30)nnn (�2.47)nn (�2.72)nnn

DA missing dummy 0.0011 �0.0047 �0.0041 0.0008 0.0003 0.0009

(0.13) (�0.57) (�0.49) (1.04) (0.32) (1.17)

HH index �0.0500 �0.0476 �0.0677 �0.0026 �0.0020 �0.0034

(�2.28)nn (�2.20)nn (�2.67)nnn (�1.25) (�0.91) (�1.82)n

Industry dummies Yes Yes Yes Yes Yes Yes

Year dummies Yes Yes Yes Yes Yes Yes

N 4,265 4,226 4,265 4,265 4,226 4,265

Adjusted R2 0.0163 0.0112 0.0127 0.0404 0.028 0.0385

F-statistic 2.77nnn 2.26nnn 2.39nnn 4.28nnn 2.99nnn 5.10nnn


constraint dummy, in-the-money options, financial con-

straint dummy� in-the-money options, in-the-money

options missing dummy, and other factors that could affectlong-run stock performance. In-the-money options are theaverage in-the-money vested stock options for two yearsbefore and one year after the repurchase announcement.In-the-money options missing dummy equals one if in-the-

money options are not available and zero otherwise.23

23 Conclusions remain unchanged if only sample firms with in-the-

money options available are included in the cross-sectional regressions.

In Model 1 the coefficient on the interaction term offinancial constraint dummy� in-the-money options is nega-tive and statistically significant at the 5% level. The resultshold for both buy-and-hold and Carhart abnormal returns.Our evidence suggests that constrained repurchasers withmore overconfident managers experience less favorablelong-run post-repurchase stock return performance.Model 1 also shows that the coefficient on the financial

constraint dummy is not significant. This finding indicatesthat financial constraints are less important in explainingthe long-run stock performance of share buybacks forfirms that are less likely to have overconfident managers.


We substitute institutional ownership in Model 2 andanalyst coverage in Model 3 for in-the-money options.

Institutional ownership is the average percentage of equityheld by institutional investors, and analyst coverage is theaverage number of financial analysts following the firmfor two years before and one year after the repurchaseannouncement. If managers of constrained firms with lessoutside monitoring tend to be overconfident, we expectpoorer post-buyback returns for constrained repurchaserswith lower institutional ownership or less analyst coverage.Models 2 and 3 show that, for both buy-and-hold andCarhart abnormal returns, the coefficients on financial

constraint dummy� institutional ownership and financial

constraint dummy� analyst coverage are significantly posi-tive. These results provide further support for the man-agerial hubris explanation.24

We next examine whether managerial overconfidenceexplains constrained firms’ motives for repurchasing,using the universe of firms listed on Compustat for eachsample year and a Tobit model. Our analysis followsStephens and Weisbach (1998) and Dittmar (2000). InTable 10, the dependent variable is the actual buybackratio, which equals the dollar volume of repurchasesdivided by the prior year-end market value of equity.The dollar volume of stock repurchases is based on fundsreported on the cash flow statement used to redeem stockafter adjusting for concurrent changes in preferred stock.Independent variables are financial constraint dummy,in-the-money options, financial constraint dummy� in-the-

money options, and several control variables (defined inAppendix A). In-the-money options are the average in-the-money vested stock options for 3 years prior to therepurchase.

Model 1 in Table 10 shows that the coefficient on theinteraction term of financial constraint dummy� in-the-

money options is significantly positive at the 5% level. Thatis, constrained firms tend to buy back more shares whenthey have more overconfident managers. In Models 2 and3 of Table 10, we replace in-the-money options by institu-

tional ownership and analyst coverage, respectively. Ifmanagers of constrained firms with weaker outside mon-itoring tend to be overconfident, we expect them to buyback more shares. The coefficients on financial constraint

dummy� institutional ownership and financial constraint

dummy� analyst coverage are both significantly negative.The results in Table 10 provide additional support for amanagerial hubris explanation of why constrained firmsbuy back shares.25

24 We obtain similar results in Table 9 if we use in-the-money

vested options, institutional ownership, and analyst coverage for the

year preceding the repurchase announcement.25 The results in Table 10 are similar if we use in-the-money vested

options, institutional ownership, and analyst coverage for the year prior

to the repurchase. We also include financial constraint dummy�prior

MAR (or alternatively financial constraint dummy�B/M) and financial

constraint dummy� excess cash in Table 10, where excess cash is the

firm’s excess cash holdings, calculated as in Harford, Mansi, and

Maxwell (2008). We find that the coefficient on financial constraint

dummy� prior MAR (financial constraint dummy�B/M) is significantly

negative (positive) at the 10% level and the coefficient on financial

constraint dummy� excess cash is insignificant. Because repurchasers

5.3. Other possible explanations

One might argue that agency problems could explainthe buyback decisions of financially constrained firms.Fenn and Liang (2001), Kahle (2002), and Chan, Ikenberry,Lee, and Wang (2010) suggest that managers couldrepurchase shares for their private benefit. Adding totheir vested options might tempt managers to boost stockprice via stock repurchase. Managers of constrained firmscould hold more vested options and, hence, have more ofan incentive to boost stock price to increase their ownpersonal wealth through share buybacks, even if buybacksare not value-enhancing. We examine this conjecture byinvestigating the vested options, both in-the-money andout-of-the-money, held by top executives of the repurch-asing firms for the two years before and one year after therepurchase announcement. We find that the averageoption holdings as a percentage of total shares are 1.89%in year �2, 1.87% in year �1, and 1.83% in year þ1 forconstrained firms, compared with 1.44%, 1.50%, and 1.60%for unconstrained firms, respectively. The differencesbetween the two groups are statistically significant atthe 5% level or better. We know from earlier results(Table 3) that constrained firms experience insignificantlyor marginally significantly positive short-horizon andsignificantly negative long-horizon abnormal returnsaround repurchase announcements. This evidence wouldindicate that managers of constrained firms are unsuc-cessful in reaping private benefits via buying back shares.As ex post outcomes should affect ex ante incentives, itseems unlikely that this agency argument can explainthese managers’ decision to undertake repurchases.

Another possible explanation for financially con-strained firms to repurchase stock is that these firms areundervalued and that the benefits of undervaluation out-weigh the costs of constraint. Table 3 has shown signifi-cantly negative post-buyback abnormal stock returns forconstrained firms. The evidence of the long-run stockreturns, therefore, does not support this alternativeexplanation.

6. Summary

We thoroughly examine how the financial constraintsof repurchasing firms affect firm performance followingthe buyback announcement. Share repurchase programsresult in a decline in corporate liquidity for repurchasingfirms. For constrained firms, reduced corporate liquiditycan be harmful to shareholder wealth. These firms facemore difficulty financing future investment, a diminishedlikelihood of making technological improvements in cashmanagement, and higher risk of financial distress. Wewould expect constrained firms to exhibit poorer post-repurchase performance than unconstrained firms.

(footnote continued)

with lower prior MAR (higher B/M) tend to be undervalued (Ikenberry,

Lakonishok, and Vermaelen, 1995; Stephens and Weisbach, 1998), our

results suggest that the undervaluation hypothesis is more important

and the excess cash hypothesis is less important for the constrained

firms.

Table 10Tobit regression analyses of actual share repurchases.

This table presents Tobit regression analyses of the actual buyback ratio using the universe of firms listed on Compustat for each sample year. The

dependent variable is the dollar volume of repurchases divided by the prior year-end market value of equity. The dollar volume of stock repurchases is

based on funds reported on the cash flow statement used to redeem stock after adjusting for concurrent changes in preferred stock. Financial constraint

dummy equals one for constrained firms and zero for unconstrained firms, where a firm’s financial constraint is measured by the KZ index as defined in

Eq. (1). In-the-money options are the average in-the-money vested stock options for three years prior to the repurchase. Institutional ownership is the

average percentage of equity ownership held by institutional investors, and analyst coverage is the average number of financial analysts following the

firm as reported by Institutional Brokers’ Estimate System (I/B/E/S) for 3 years prior to the repurchase, where firms not covered by I/B/E/S are assumed to

have zero analyst coverage. In-the-money options missing dummy equals one if in-the-money options are not available and zero otherwise. Definitions of

other variables are in Appendix A. p-values are in parentheses. The number of observations varies across regressions because of data availability. nnn, nn,

and n represent 1%, 5%, and 10% significance level, respectively.


Intercept �26.8764 �25.3971 �30.3116

(0.000)nnn (0.000)nnn (0.000)nnn

Financial constraint dummy �2.2774 �1.1901 �2.2946

(0.000)nnn (0.031)nn (0.000)nnn

In-the-money options 44.5523

(0.031)nn

Financial constraint dummy 108.0408

� in-the-money options (0.020)nn

Institutional ownership 9.6957

(0.000)nnn


� institutional ownership (0.029)nn

Analyst coverage 0.1330

(0.000)nnn


� analyst coverage (0.017)nn

In-the-money options missing dummy �2.1137

(0.000)nnn

Size 1.3907 0.9082 1.2521

(0.000)nnn (0.000)nnn (0.000)nnn

Q �1.3447 �1.1939 �1.3124

(0.000)nnn (0.000)nnn (0.000)nnn

Prior MAR 0.0992 0.1019 0.0837

(0.449) (0.492) (0.501)

DA �0.3157 �0.3586 �0.3678

(0.350) (0.353) (0.235)

DA missing dummy �0.1364 �0.0461 �0.7541

(0.573) (0.867) (0.001)nnn

HH index �0.2873 �0.9001 3.7737

(0.591) (0.131) (0.000)nnn

CF/TA 10.6330 13.4373 14.4573

(0.000)nnn (0.000)nnn (0.000)nnn

DIV/TA 66.8667 69.2540 45.2065

(0.000)nnn (0.000)nnn (0.000)nnn

Takeover dummy �0.3616 �0.2620 �0.1842

(0.232) (0.429) (0.527)

Debt-to-equity ratio 0.0003 0.0003 0.0003

(0.261) (0.272) (0.206)


N 55,277 44,320 55,277

Log-likelihood �110,380.0 �92,959.7 �112,789.0


By a number of financial constraint measures, a set ofconstrained firms do repurchase stock. Share buybacks byconstrained firms lead to post-repurchase cash, cash flow,and leverage constraints, resulting in reduced investment.We find that constrained firms experience significantlypoorer abnormal stock return and operating performancethan unconstrained firms in the post-repurchase period.Post-repurchase performance is more unfavorable for con-strained firms with high actual buyback ratios. Constrainedfirms also experience a significantly greater increase in post-repurchase distress risk than unconstrained firms, especiallywhen they have high actual buyback ratios.

One possible reason a constrained firm buys backshares, even if the repurchase does not enhance share-holder wealth, is managerial hubris. We show that topmanagers of constrained firms tend to hold more in-the-money unexercised vested options than managers ofunconstrained firms. Managers of constrained firms likelytend to overestimate their firms’ future returns andpostpone their exercise of stock options. We also showthat post-repurchase stock performance is significantlynegatively related to in-the-money unexercised vestedoptions for constrained firms. The results indicate thatconstrained firms with more overconfident managers

Table A1Definitions of control variables used in regression analyses.

Variable Definition

Panel A: Ordinary least squares regressionsIntended buyback ratio Initial announced repurchase ratio authorized by the board of directors

OMSR dummy One if the repurchase announcement is an open market share repurchase announcement and

zero otherwise

Size Logarithm of market value of common equity for the month preceding the announcement

B/M Book value of common equity divided by market value of common equity for the fiscal year

preceding the announcement

Prior AR A 252-day buy-and-hold abnormal return prior to the repurchase announcement

DA Abnormal accruals for the year preceding the announcement, calculated as in Gong, Louis, and

Sun (2008), where the components of DA are winsorized at the 1st and 99th percentiles before

construction

DA missing dummy One if DA is not available and zero otherwise

HH index Herfindahl-Hirschman Index, which is the sum of the squared fraction of industry sales by all

firms in the three-digit Standard Industrial Classification industry for the year prior to the

announcement

Actual buyback dummy One if the actual buyback ratio in the first four quarters after the repurchase announcement is

higher than the sample median and zero otherwise

Panel B: Tobit regressionsSize Logarithm of market value of common equity for the year prior to the repurchase

Q Ratio of the market-to-book value of the firm’s assets for the year prior to the repurchase, where

the market value of assets equals book value of assets minus book value of common equity plus

market value of common equity

Prior MAR Value-weighted, market adjusted buy-and-hold stock return in the year prior to the repurchase

DA Abnormal accruals for the year prior to the repurchase

DA missing dummy One if DA is not available and zero otherwise

HH index Herfindahl–Hirschman Index for the year prior to the repurchase

CF/TA Cash flow over lagged book assets for the year prior to the repurchase

DIV/TA Cash dividends over lagged book assets for the year prior to the repurchase

Takeover dummy One if the firm has been announced as an acquisition target during the three-year period prior

to the repurchase and zero otherwise

Debt-to-equity ratio Book value of total debt divided by book value of common equity for the year prior to the

repurchase


experience more unfavorable post-repurchase stockperformance. We further show that actual buyback ratiosare significantly positively related to in-the-money unex-ercised vested options when repurchasing firms are con-strained. This evidence suggests that constrained firmstend to buy back more shares when their managers aremore overconfident. Thus, considerable support exists fora managerial hubris explanation for share repurchasesthat are not shareholder value-enhancing.

Appendix A

See Table A1.

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Financial constraints and share repurchases