The 26 reference contexts in paper Christopher F. Baum, Atreya Chakraborty, Boyan Liu (2008) “The Impact of Macroeconomic Uncertainty on Firms' Changes in Financial Leverage” / RePEc:boc:bocoec:688

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    Corresponding author: Christopher F Baum, Department of Economics, Boston College, Chestnut Hill, MA 02467 USA, Tel: 617–552–3673, fax 617–552–2308, e-mail: baum@bc.edu. 1 Keywords: macroeconomic uncertainty, corporate governance, leverage, JEL: D81, G32, G34 2 1 Introduction There is a large literature, starting with
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    Jensen & Meckling(1976),
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    discussing how agency conflicts affect a firm’s capital structure decisions.Evidence from early work generally indicates that entrenched managers prefer lowerleverage (Berger, Ofek & Yermack (1997), Garvey & Hanka (1999)).
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    : 617–552–3673, fax 617–552–2308, e-mail: baum@bc.edu. 1 Keywords: macroeconomic uncertainty, corporate governance, leverage, JEL: D81, G32, G34 2 1 Introduction There is a large literature, starting with Jensen & Meckling(1976), discussing how agency conflicts affect a firm’s capital structure decisions.Evidence from early work generally indicates that entrenched managers prefer lowerleverage
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    (Berger, Ofek & Yermack (1997), Garvey & Hanka (1999)).
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    In recent years, widely available use of indices to measure shareholder rights (for example, the Gindex of Gompers, Ishii & Metrick (2003)) has produced new results that do not agree with these empirical findings.
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    There is a large literature, starting with Jensen & Meckling(1976), discussing how agency conflicts affect a firm’s capital structure decisions.Evidence from early work generally indicates that entrenched managers prefer lowerleverage (Berger, Ofek & Yermack (1997), Garvey & Hanka (1999)). In recent years, widely available use of indices to measure shareholder rights (for example, the Gindex of
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    Gompers, Ishii & Metrick (2003))
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    has produced new results that do not agree with these empirical findings. Jiraporn & Gleason (2007) argue that since leverage alleviates agency problems, firms with larger agency problems should adopt higher debt ratios.
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    In recent years, widely available use of indices to measure shareholder rights (for example, the Gindex of Gompers, Ishii & Metrick (2003)) has produced new results that do not agree with these empirical findings.
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    Jiraporn & Gleason (2007)
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    argue that since leverage alleviates agency problems, firms with larger agency problems should adopt higher debt ratios. They find that debt ratios are inversely related to measures for better corporate governance for a large sample of non-regulated firms between 1993-2002.
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    Jiraporn & Gleason (2007) argue that since leverage alleviates agency problems, firms with larger agency problems should adopt higher debt ratios. They find that debt ratios are inversely related to measures for better corporate governance for a large sample of non-regulated firms between 1993-2002.
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    John& Litov (2008)
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    also find, over a similar period, that manufacturing firms with weaker shareholder rights use more debt financing and have higher leverage between 1993-2004.1They assume that better-governed firms are easier to monitor: it is easier for the market to distinguish between managers’ bad luck versus bad judgment.
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    that poorly governed firms will be associated with more conservative investments and higher use of debt relative to their better-governed counterparts.2 The focus of this paper is to highlight the impact of macroeconomic uncertainty on the relationship between corporate governance and changes in firms’ financial leverage. It is reasonable to assume that economy-wide risks that are exogenous 1
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    Wald & Long (2007)
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    also find a firms that incorporate themselves with states with stronger anti-takeover provisions (i.e., weaker shareholder rights) have a higher debt-to-market ratio. They attribute this to the decrease in firm value associated with anti-takeover amendments. 2A theoretical framework for why entrenched managers may prefer safer investments is developed in John, Litov & Yeung (2008). 3 to the operat
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    that are exogenous 1Wald & Long (2007) also find a firms that incorporate themselves with states with stronger anti-takeover provisions (i.e., weaker shareholder rights) have a higher debt-to-market ratio. They attribute this to the decrease in firm value associated with anti-takeover amendments. 2A theoretical framework for why entrenched managers may prefer safer investments is developed in
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    John, Litov & Yeung (2008).
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    3 to the operation of the firm and difficult to hedge against may play an important role in any financing decision. There is strong evidence thatfirms time their debt issuance based on macroeconomic conditions (Korajczyk & Levy (2003)).
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    in firm value associated with anti-takeover amendments. 2A theoretical framework for why entrenched managers may prefer safer investments is developed in John, Litov & Yeung (2008). 3 to the operation of the firm and difficult to hedge against may play an important role in any financing decision. There is strong evidence thatfirms time their debt issuance based on macroeconomic conditions
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    (Korajczyk & Levy (2003)).
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    However, prior research has not considered how the governance-leverage relationship may be affected by macroeconomic risks. This is the primary contribution of our paper. We first investigate if corporate governance affects firms’ financing decisions.
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    Our empirical findings are presented in Section 4 and Section 5 offers concluding remarks. 4 2 Leverage, macroeconomic uncertainty, and corporate governance Many researchers have considered the importance of firm-specific characteristics as a determinant of firms’ choice of financial leverage
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    (Titman & Wessels (1988), Havakimian, Opler & Titman (2001)).
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    Recently, increasing scrutiny has been focused on agency cost related explanations for firms’ capitalstructure decisions. These studies have generally used different measures of shareholders’ rights to proxy for the quality of corporate governance.
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    There is an equally large literature that documents how capital structure choice varies over time. Some of these studies make a strong case that the macroeconomic environment within which firms operate could be an equally important determinant of their financing decision
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    (Choe, Masulis & Nanda (1993), Gertler & Gilchrist (1994)). Bernanke & Gertler (1995)
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    also provide a very extensive discussion of the impact of monetary policy on the cost of borrowing. The purpose of this paper is not to test the adequacy of any of these models that try to explain a firm’s capital structure.
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    section of the paper, we discuss relevant aspects of these two strands of literature and motivate our study in which they both are intertwined. 2.1 The effects of corporate governance on leverage Agency costs are not observable, but it may be possible to evaluate the quality of corporate governance in a hedonic sense by considering a numberof firm characteristics. This is the approach taken by
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    Gompers et al. (2003)
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    in formingtheirGindexmeasure 5 of the quality of governance. TheGindexis a broad index of antitakeover provisions that influence the likelihood that managers will be able to insulate themselves from the risk of takeover.
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    The Gindexis then measured on a scale of 0 to 24, with higher values indicating greater power in the hands of managers and higher agency costs. There is a wide body of literature that documents the impact of these indices on various corporate decisions. For example,
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    Gompers et al.(2003) and Core, Guay & Rusticus (2006)
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    document that firms with a large number of antitakeover provisions have lower operating performance compared to those with a small number of provisions. In a similar spirit Masulis, Wang & Xie (2007) find that theGIndexis related to stockholder reaction to merger announcements, with highGIndexfirms suffering larger losses on the announcement of a takeover attempt.
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    For example, Gompers et al.(2003) and Core, Guay & Rusticus (2006) document that firms with a large number of antitakeover provisions have lower operating performance compared to those with a small number of provisions. In a similar spirit
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    Masulis, Wang & Xie (2007)
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    find that theGIndexis related to stockholder reaction to merger announcements, with highGIndexfirms suffering larger losses on the announcement of a takeover attempt. These results indicateGindexcan be considered a reasonable measure of the quality of corporate governance, with low values signifying strong shareholders? rights and high values indicative of agency costs.
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    A good measure of agency costs is important to any empirical work on capital structure as theory suggests the conflicts of interest between firms’ stakeholders may play an important role in any financing decision. While earlier work indicates that entrenched managers may seek to avoid debt, evidence also exists that entrenched managers may use higher leverage to thwart expected takeovers
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    (Zwiebel (1996)).
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    Recently the use of governance indices to measure agency costs Jiraporn & Gleason (2007), Wald & Long (2007) and John & Litov (2008)) has furthered interest on the relation between entrenchment and leverage.
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    While earlier work indicates that entrenched managers may seek to avoid debt, evidence also exists that entrenched managers may use higher leverage to thwart expected takeovers (Zwiebel (1996)). Recently the use of governance indices to measure agency costs
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    Jiraporn & Gleason (2007), Wald & Long (2007) and John & Litov (2008))
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    has furthered interest on the relation between entrenchment and leverage. While findingsdiffer among these studies, all of them report an inverse association between measures of better governance and leverage.
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    Our main contribution is to incorporate in this line of reasoning another important determinant of leverage: macroeconomic uncertainty.We highlight the impact 6 of macroeconomic uncertainty on the governance-leverage relationship. There are hints in other research that this interaction might be significant. For example,
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    John & Litov (2008)
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    find that firms with weaker governance enjoy lower bond yields when issuing debt and earn higher credit ratings, allowing thesefirms to issue more debt. Macroeconomic uncertainty should play an important role infirms’ ability to access the capital market.
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    We develop this intuition in the next section. 2.2 The effects of macroeconomic uncertainty on leverage Macroeconomic uncertainty affects both the level of firms’ capital investment and how it is financed.
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    Leahy & Whited (1996)
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    provide a good reviewof the former, reporting that uncertainty reduces investment in their sample but noting that the theoretical prediction on this question is ambiguous and empirical evidence on this issue remains inconclusive.
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    Leahy & Whited (1996) provide a good reviewof the former, reporting that uncertainty reduces investment in their sample but noting that the theoretical prediction on this question is ambiguous and empirical evidence on this issue remains inconclusive.
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    Korajczyk & Levy (2003)
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    point out an important factor that might explain often-contradictory results on this issue. They find that that financially constrained firms react differently to uncertainty than unconstrained firms.
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    Weakly governed firms should choose less risky projects and and make greater use of debt finance given the lower expected risk of bankruptcy. However, macroeconomic uncertainty also affects a firm’s ability to borrow, and weakly governed firms with high leverage 7 will be more likely to be credit constrained
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    (Bernanke & Gertler (1995)).
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    Once one considers both the incentive to borrow and the ability to borrow, the question of how financing decisions are affected by heightened macroeconomic risk becomes largely an empirical issue. However, we expect the ability to borrow to play a large role in our model.
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    relative to firms with stronger governance. 3 Modelling firms’ choice of leverage A challenge to any study considering the effects of uncertainty on firms’ behavior is the construction of an appropriate proxy for uncertainty. The next subsection describes our strategy in generating a proxy for macroeconomic uncertainty. 3.1 Identifying macroeconomic uncertainty In our investigation, as in
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    Driver, Temple & Urga (2005) and Byrne & Davis (2002),
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    we use a GARCH model to proxy for macroeconomic uncertainty.We believe that this approach is more appropriate compared to alternativessuch as proxies obtained from moving standard deviations of the macroeconomic series (e.g.
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    investigation, as in Driver, Temple & Urga (2005) and Byrne & Davis (2002), we use a GARCH model to proxy for macroeconomic uncertainty.We believe that this approach is more appropriate compared to alternativessuch as proxies obtained from moving standard deviations of the macroeconomic series (e.g., Ghosal & Loungani (2000)) or survey-based measures based on the dispersion of forecasts (e.g.,
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    Graham & Harvey (2001), Schmukler, Mehrez & Kaufmann (1999)).
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    We define a volatility measureφi,tderived from changes in the index of leading indicators (LI) as a proxy for the macro-level uncertainty that firms face intheir financial and production decisions. We build a generalizedARCH(GARCH(1,2)) model for ∆LIwhere the mean equation is an autoregression over 1979m3–2006m12, as reported in Table 1.
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    The conditional variance derived from thisGARCHmodel is 8 averaged to the annual frequency and then employed in the analysis as our measure of macroeconomic uncertainty. 3.2 Econometric specification We test the hypotheses that both corporate governance and macroeconomic uncertainty have important effects on nonfinancial firms’ variations in leverage by extending the econometric model of
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    Baum, Stephan & Talavera (2008).
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    That paper focused on the level of short-term leverage, rather than themeasure that we consider in this work. In our specification, we explain a measure of thenet change in leverage, following Berger et al. (1997), defined as ∆Li,t= ∆Di,t−∆Ei,t Ai,t (1) whereDi,tis book debt,Ei,tis book equity andAi,tis total assets at the end of the current fiscal year.
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    that both corporate governance and macroeconomic uncertainty have important effects on nonfinancial firms’ variations in leverage by extending the econometric model of Baum, Stephan & Talavera (2008). That paper focused on the level of short-term leverage, rather than themeasure that we consider in this work. In our specification, we explain a measure of thenet change in leverage, following
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    Berger et al. (1997),
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    defined as ∆Li,t= ∆Di,t−∆Ei,t Ai,t (1) whereDi,tis book debt,Ei,tis book equity andAi,tis total assets at the end of the current fiscal year. The resulting empirical specification, employing a dynamicpanel data model, is: ∆Li,t=β0+β1∆Li,t−1+β2Cit+β3Sit+β4Iit+1+β5Iit+β6Gindexi,t+ (2) β7LIt−1+ +β8φt−1+β9Gindexi,t×φi,t−1+fi+τt+eit Ci,t, cash holdings,Si,t, net sales andIi,tis capital investment, eac
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    In order to measure the quality of corporate governance, we use theIRRCdatabase which provides annual data on anti-takeover provisions forthe years 1990, 1993, 1995, 1998, 2000, 2002, and 2004 on anti-takeover provisions. Following
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    Gompers et al. (2003),
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    we use data from IRRC, filling in the missing years, toconstruct an annual governance index (Gindex) and an entrenchment index (Eindex) (Bebchuk, Cohen & Ferrell (2004)) as measures of the quality of corporate governance.
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    In order to measure the quality of corporate governance, we use theIRRCdatabase which provides annual data on anti-takeover provisions forthe years 1990, 1993, 1995, 1998, 2000, 2002, and 2004 on anti-takeover provisions. Following Gompers et al. (2003), we use data from IRRC, filling in the missing years, toconstruct an annual governance index (Gindex) and an entrenchment index (Eindex)
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    (Bebchuk, Cohen & Ferrell (2004))
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    as measures of the quality of corporate governance. After merging theCOMPUSTATandIRRCsamples and dropping firm-years with missing data, we obtain about 1,125 firms’ annual characteristics. Descriptive statistics for the variables entering the model are presented in Table 1. 10 4 Empirical findings Estimates of optimal corporate behavior often suffer from endogeneity problems, and the use of instr
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    We estimate our econometric models using the system dynamic panel data (DPD) estimator. System DPD combines equations in differences of the variables with equations in levels of the variables. In this “system GMM” approach (see
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    Blundell & Bond (1998)),
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    lagged levels are used as instruments for differenced equations and lagged differences are used as instruments for level equations. The models are estimated using a first difference transformation to remove the individual firm effect.
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