CAPÍTULO II DIAGNÓSTICO SITUACIONAL DE LA EMPRESA
2.2 MACROAMBIENTE DE LA EMPRESA
2.2.3 ASPECTO ECONÓMICO
2.2.3.9 Impuestos:
25 See, e.g., Tufano (1993), Stoh and Mauer (1996), Johnson (1997), and Park (2000). For instance, Johnson
(1997) finds that debt maturity (measured by the proportion of debt maturing in more than three years) is significantly longer for firms using predominantly public debt than for firms using predominantly bank debt.
26 See, e.g., Gilson and Warner (2000). In our sample, secured bank debt represents 32% of total bank debt
There is rich empirical evidence suggesting that the divergence between ownership and control creates strong incentives for large shareholders to engage in tunneling and other moral hazard activities. Yet little is known about how such incentives and activities induced by dominant shareholders’ excess control rights affect firm financing behavior. The aim of this paper is to enhance our knowledge of these matters by examining the choice of debt source by firms with control-ownership divergences. Compared to public bondholders, banks can serve as more effective monitors in deterring potential self-dealing activities because of their concentrated holdings, strong bargaining power, and superior access to information. As a consequence, firms controlled by large shareholders with excess control rights and hence strong tunneling incentives may prefer public debt financing over bank debt as a way to evade scrutiny and insulate themselves from bank monitoring.
Our paper examines this bank monitoring avoidance hypothesis using a novel, hand- collected data set on corporate ownership, control and debt structures for 9,831 firms in 20 countries from 2001 to 2010. We find strong evidence that the monitoring avoidance incentives induced by the separation of ownership and control exert a significant impact on the choice between bank debt and public debt. Specifically, we find that the divergence between the control rights and cash-flow rights of a borrowing firm’s controlling shareholder decreases its reliance on bank debt financing and increases its reliance on public debt financing significantly. These effects are particularly pronounced for family-controlled firms, informationally opaque firms, and firms with high financial distress risk, and are weakened by the presence of multiple large owners and strong shareholder rights. We also find that the control-ownership divergence of a borrowing firm’s dominant shareholder increases the firm’s debt maturity and decreases its debt collateralization significantly. Collectively, our results identify ownership structure as an important determinant of firm debt structure and shed new light on a channel through which the
control-ownership divergence and the ensuing moral hazard incentives influence firm financial decisions.
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.2 .4 .6 .8 1 0 .1 .2 .3 .4 Austria .2 .4 .6 .8 1 0 .1 .2 .3 .4 Belgium 0 .2 .4 .6 .8 1 0 .1 .2 .3 Finland 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 France 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 Germany 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 Hong Kong 0 .2 .4 .6 .8 1 0 .1 .2 .3 Ireland .2 .4 .6 .8 1 0 .1 .2 .3 .4 .5 Italy 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 .5 Japan 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 South Korea 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 Malaysia 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 .5 Norway .2 .4 .6 .8 1 0 .05 .1 .15 .2 Portugal 0 .2 .4 .6 .8 1 0 .2 .4 .6 Singapore 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 .5 Spain 0 .2 .4 .6 .8 1 0 .1 .2 .3 Sweden 0 .2 .4 .6 .8 1 0 .05 .1 .15 .2 .25 Switzerland 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 .5 Taiwan 0 .2 .4 .6 .8 1 0 .05 .1 .15 .2 .25 Thailand 0 .2 .4 .6 .8 1 0 .1 .2 .3 .4 UK Figure 1
The relation between bank debt and control-ownership wedge across countries
This figure presents country-by-country scatter plots of the control-ownership wedge on the x-axis and the ratio of bank debt to total debt on the y-axis. The solid line in each plot is the fitted bank debt-to- total debt ratio. For each sample firm, the control-ownership wedge and the bank debt-to-total debt ratio plotted are the average value of the firm’s control-ownership wedge and the average value of the firm’s bank debt-to-total debt ratio over the sample period, respectively.
Table 1A
Variable definitions
This table provides definitions for all the variables used in the paper. Variable name Variable definition
Debt structure
Bank debt/Total debt The ratio of bank debt to total debt, calculated as the sum of term loans and revolving credit divided by total debt
Public debt/Total debt The ratio of public debt to total debt, calculated as the sum of senior bonds and notes, subordinated bonds and notes, and commercial papers divided by total debt
Debt maturity The ratio of long-term debt due after three (or five) years to total debt Debt security The ratio of total secured debt to total debt
Ownership structure
Control-ownership wedge The difference between the control rights and cash-flow rights of the largest ultimate owner of the firm
Cash-flow rights The cash-flow rights of the largest ultimate owner of the firm
Family ownership dummy A dummy variable that equals one if the largest ultimate owner of the firm is a family or an individual and zero otherwise
Multiple large owners dummy A dummy variable that equals one if the firm has at least one other owner besides the ultimate largest owner that has 10% or more of the voting rights and zero otherwise
Firm characteristics
Leverage The sum of long-term debt and debt in current liabilities divided by total assets
Tangibility Net property, plant, and equipment divided by total assets
Log assets The natural log of total assets measured in millions of U.S. dollars Profitability EBITDA divided by total assets
Q The sum of market value of equity plus book value of debt divided by total
assets, where market value of equity equals price per share times the total number of shares outstanding, and book value of debt equals total assets minus book value of equity
Distance to default A market-based measure of default risk operationalized in Crosbie and Bohn (2003), calculated as (Va − D)/(Vaσa), where Va is market value of assets, D is
debt in current liabilities plus one half of long-term debt, and σa is one-year
asset volatility. The two unobservable variables, Va and σa, are estimated by
solving the following Merton (1974) pricing model for a one-year time horizon (T=1) using the market value of equity (Ve), one-year equity
volatility (σe), debt (D), and the three-month Treasury-bill rate (r): Ve =
VaN(d1) − e-rDN(d2) and σe = N(d1)σaVa/Ve, where d1 = [ln(Va/D) + r +
0.5σa2 ]/σa and d2 = d1−σa.
Z-score Altman’s (1968) Z-score, calculated as (1.2×working capital + 1.4×retained earnings + 3.3×EBIT + 0.999×sales)/total assets + 0.6×(market value of equity/book value of debt)
Table 1A
Variable definitions (Continued)
Variable name Variable definition
Stock index inclusion dummy A dummy variable that equals one if the firm is included in a major national stock index and zero otherwise
Number of analysts The total number of stock analysts following the firm
Volatility of accruals An empirical measure of accrual quality (Dechow and Dichev, 2002; McNichols, 2002), defined as the standard deviation of the firm-level residuals from a pooled OLS regression of the change in working capital on past, present, and future operating cash flows, the change in sales, and the level of property, plant, and equipment (all variables scaled by total assets) Propping potential The total value of the assets of all firms that are positioned below the
borrowing firm in the ownership chain, divided by the borrowing firm’s total assets (upper bound measure); or a weighted sum of the asset values of all firms lower down in the ownership chain divided by the borrowing firm’s total assets, with the weight for each firm beneath the borrowing firm defined as the ultimate controlling shareholder’s control rights in that firm (conservative measure)
Other
Anti-self-dealing An index compiled by Djankov et al. (2008) with the help of Lex Mundi law firms that measures legal protection of minority shareholders against self- dealing, with higher values indicating stronger protection
Anti-director An index compiled by La Porta et al. (1998) and Djankov et al. (2008) aggregating shareholder rights concerning voting and minority protection. The index ranges from 0 to 6, with higher values indicating stronger protection of minority shareholders against insider expropriation.
Table 1B
Summary statistics
This table reports the mean, standard deviation (STD), and number of observations (N) for all the variables used in the paper. Definitions of all the variables are provided in Table 1A.
Variable names Mean STD N
Debt structure
Bank debt/Total debt 0.714 0.361 43,502
Public debt/Total debt 0.148 0.271 43,502
Debt maturity (due after 3 years) 0.382 0.313 42,961 Debt maturity (due after 5 years) 0.223 0.267 42,961
Debt security 0.336 0.399 42,961
Ownership structure
Control-ownership wedge 0.042 0.077 43,502
Cash-flow rights 0.214 0.218 43,502
Family ownership dummy 0.278 0.448 43,502
Multiple large owner dummy 0.298 0.457 43,502
Firm characteristics Leverage 0.239 0.182 43,502 Tangibility 0.401 0.241 43,502 Log assets 5.221 1.940 43,502 Profitability 0.077 0.119 43,502 Q 1.233 0.764 43,502 Distance to default 2.355 3.011 43,502 Z-score 2.637 2.347 43,273
Stock index inclusion dummy 0.076 0.265 43,502
Number of analysts 5.240 9.007 43,502
Volatility of accruals 0.133 0.121 41,169
Propping potential (upper bound) 0.533 0.815 43,502
Propping potential (conservative) 0.073 0.161 43,502
Other
Anti-director 3.927 0.820 43,502
Table 2
The effect of control-ownership wedge on the choice of debt source
This table presents regression results on the effect of the control-ownership wedge on the choice of debt source. The dependent variable is the ratio of bank debt to total debt. We estimate ordinary least squares (OLS) regressions in Columns 1 and 2 and a Tobit regression in Column 3 (marginal effects reported). The control-ownership wedge is defined as the difference between the control rights and cash- flow rights of the largest ultimate owner of the firm. Definitions of all the other variables are reported in Table 1A. Robust standard errors clustered by firm are reported in parentheses. Significance at the 10%, 5%, and 1% level is indicated by *, **, and ***, respectively.
(1) (2) (3)
OLS OLS Tobit
Control-ownership wedge -2.187 -2.104 -2.164 (0.447)*** (0.681)*** (1.015)** Cash-flow rights 0.051 0.042 0.044 (0.043) (0.040) (0.047) Leverage -0.061 -0.087 (0.025)** (0.037)** Tangibility -0.055 -0.072 (0.037) (0.047) Log assets -0.034 -0.033 (0.015)** (0.014)** Profitability -0.002 -0.004 (0.001)** (0.002)* Q -0.037 -0.042 (0.017)** (0.017)** Distance to default -0.024 -0.022 (0.010)** (0.009)**
Industry effects Yes Yes Yes
Country × Time effects Yes Yes Yes
Number of observations 43,502 43,502 43,502
Number of firms 9,831 9,831 9,831
Adjusted R2 0.094 0.129
Table 3
Financial distress risk and the effect of the control-ownership wedge on debt choice
This table presents regression results on the effect of firm financial distress risk on the relation between the control-ownership wedge and debt choice. The dependent variable is the ratio of bank debt to total debt. The control-ownership wedge is defined as the difference between the control rights and cash-flow rights of the largest ultimate owner of the firm. Z-score (Altman, 1968) is an accounting-based measure that captures the financial health of a company. Distance to default (Crosbie and Bohn, 2003) is a market-based measure that estimates the likelihood that the market value of a firm’s assets will stay above its debt default threshold. Detailed definitions of all the variables are reported in Table 1A. Robust standard errors clustered by firm are reported in parentheses. Significance at the 10%, 5%, and 1% level is indicated by *, **, and ***, respectively.
(1) (2) Control-ownership wedge -2.487 -2.527 (0.843)*** (0.809)*** Z-score -5.817 (2.367)** Z-score × Wedge 0.264 (0.105)** Distance to default -0.038 (0.015)**
Distance to default × Wedge 0.211
(0.090)** Cash-flow rights 0.014 0.012 (0.017) (0.014) Leverage -0.088 -0.047 (0.035)** (0.021)** Tangibility -0.051 -0.069 (0.025)** (0.038)* Log assets -0.042 -0.031 (0.017)** (0.014)** Profitability -0.003 -0.004 (0.002)* (0.002)** Q -0.049 -0.033 (0.023)** (0.016)**
Industry effects Yes Yes
Country × Time effects Yes Yes
Number of observations 43,273 43,502
Number of firms 9,783 9,831
Table 4
Information opacity and the effect of the control-ownership wedge on debt choice
This table presents regression results on the effect of firm information opacity on the relation between the control-ownership wedge and debt choice. The dependent variable is the ratio of bank debt to total debt. The control-ownership wedge is defined as the difference between the control rights and cash-flow rights of the largest ultimate owner of the firm. Stock index inclusion is a dummy variable that equals one if the firm is included in a major national stock index and zero otherwise. Number of analysts is the total number of stock analysts following the firm. Volatility of accruals is an empirical measure of accrual quality (Dechow and Dichev, 2002; McNichols, 2002). Detailed definitions of all the variables are reported in Table 1A. Robust standard errors clustered by firm are reported in parentheses. Significance at the 10%, 5%, and 1% level is indicated by *, **, and ***, respectively.
(1) (2) (3) (4) Control-ownership wedge -2.724 -2.185 -2.194 -1.875 (0.538)*** (0.762)*** (0.905)** (0.636)***
Log assets -0.044 -0.038 -0.041 -0.037
(0.017)** (0.016)** (0.018)** (0.016)** Log assets × Wedge 0.116
(0.053)**
Stock index inclusion -0.179 (0.078)** Stock index inclusion × Wedge 0.887
(0.270)***
Number of analysts -0.015
(0.006)** Number of analysts × Wedge 0.062
(0.028)**
Volatility of accruals 0.479
(0.201)**
Volatility of accruals × Wedge -1.581
(0.710)** Cash-flow rights 0.062 0.060 0.025 0.033 (0.072) (0.075) (0.024) (0.039) Leverage -0.049 -0.033 -0.032 -0.053 (0.021)** (0.014)** (0.014)** (0.022)** Tangibility -0.060 -0.066 -0.031 -0.021 (0.027)** (0.031)** (0.023) (0.016) Profitability -0.002 -0.001 -0.001 -0.001 (0.001)** (0.001) (0.001)* (0.001) Q -0.010 -0.018 -0.020 -0.024 (0.005)** (0.008)** (0.009)** (0.011)** Distance to default -0.020 -0.014 -0.018 -0.012 (0.009)** (0.006)** (0.008)** (0.005)**
Industry effects Yes Yes Yes Yes
Country × Time effects Yes Yes Yes Yes
Number of observations 43,502 43,502 43,502 41,169
Number of firms 9,831 9,831 9,831 8,760
Table 5
Family ownership and the effect of the control-ownership wedge on debt choice
This table presents regression results on the effect of family ownership on the relation between the control-ownership wedge and debt choice. The dependent variable is the ratio of bank debt to total debt. The control-ownership wedge is defined as the difference between the control rights and cash-flow rights of the largest ultimate owner of the firm. Family ownership is a dummy variable that equals one if the largest ultimate owner of the firm is a family or an individual and zero otherwise. Definitions of all the other variables are reported in Table 1A. Robust standard errors clustered by firm are reported in parentheses. Significance at the 10%, 5%, and 1% level is indicated by *, **, and ***, respectively.
Control-ownership wedge -1.604 (0.560)***
Family ownership 0.012
(0.010) Family ownership × Wedge -1.382
(0.393)*** Cash-flow rights 0.051