Does foreign currency-denominated debt affect dividend payout policy? Evidence from Korea

J. of Multi. Fin. Manag. 49 (2019) 20–34

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Does foreign currency-denominated debt affect dividend payout policy? Evidence from Korea Young Mok Choi a , Kunsu Park b,∗ a College of Business Administration, Cheongju University, 298, Daeseong-ro, Cheongwon-gu, Cheongju-si, Chungcheongbuk-do 28497, Republic of Korea b Bang College of Business, KIMEP University, Abay Ave. 2, Almaty 050010, Kazakhstan

a r t i c l e

i n f o

Article history: Received 12 November 2018 Received in revised form 27 January 2019 Accepted 4 February 2019 Available online 6 February 2019 JEL classification: F31 G32 G35

a b s t r a c t This study examines the effect of foreign currency-denominated debt on dividend payouts in the context of risk hedging and debt financing costs. We find that firms with a higher proportion of foreign currency debt are more likely to pay dividends; furthermore, we also find that these firms pay higher dividends. We further find that the positive relation between the proportion of foreign currency debt and dividend payouts is more pronounced in firms with lower credit risk and cash flows than their counterparts. Our results are robust to alternative estimation methods, endogeneity concerns, and alternative proxies for foreign currency debt and dividend payouts. © 2019 Elsevier B.V. All rights reserved.

Keywords: Foreign currency-denominated debt Dividend policy Hedging Debt financing costs

1. Introduction The currency of denomination is identified as one of the most important features in any corporate debt issue (Keloharju and Niskanen, 2001). Foreign currency-denominated debt can be used as an instrument for hedging foreign currency exposures (Goswami and Shrikhande, 2001; Keloharju and Niskanen, 2001; Kedia and Mozumdar, 2003; Bartram et al., 2010; Aabo et al., 2015). In certain situations, such as different tax laws and regimes, debt financing with foreign currency debt is more cost effective than that with domestic currency debt (Shapiro, 1984). The proportion of foreign currency debt has significantly increased in Korean firms over the past decades. For example, the amount of foreign currency debt for our sample firms increased from about 23 trillion KRW in 2001 to about 102 trillion KRW in 2016.1 Moreover, as presented later in this paper, the number of firms that issue foreign currency debt increased from 84 to 356 and 68.4% of sample firms issued foreign currency debt during the corresponding period. In this study, we investigate whether foreign currency-denominated debt is associated with dividend payouts. We reason that firms with a higher proportion of foreign currency debt are expected to have a higher likelihood of paying dividends and pay a higher level of dividends. When firms operating business activities overseas issue foreign currency debt, a natural

∗ Corresponding author. E-mail addresses: [email protected] (Y.M. Choi), [email protected] (K. Park). 1 The amounts of foreign currency debt are expressed in Korean won (KRW), the currency of South Korea. https://doi.org/10.1016/j.mulfin.2019.02.001 1042-444X/© 2019 Elsevier B.V. All rights reserved.

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hedge can partially arise (Géczy et al., 1997; Allayannis and Ofek, 2001; Kedia and Mozumdar, 2003; Nguyen and Faff, 2006; Bartram et al., 2010; Aabo et al., 2015). Many domestic and foreign firms use foreign currency debt for the purpose of lowering debt financing costs (Keloharju and Niskanen, 2001). When firms hedge foreign currency risk with the issuance of foreign currency debt while lowering their costs of capital, they are expected to have higher profitability. As a result, these firms are likely to have a higher dividend capacity. Using a sample of 8278 Korean firm-year observations between 2001 and 2017, we examine the link between foreign currency-denominated debt and dividend payouts. Using a logit model, we find that firms with a higher proportion of foreign currency debt are more likely to pay dividends. Using a Tobit model, we also find that firms with a higher proportion of foreign currency debt pay higher levels of dividends. Our main results are robust to alternative estimation methods, endogeneity concerns, and alternative proxies for foreign currency debt and dividend payouts. We further find that the positive relation between the proportion of foreign currency debt and dividend payouts is more pronounced in firms with lower credit risk and cash flows than their counterparts. This study contributes to the literature in two ways. First, our study contributes to the literature on foreign currencydenominated debt. Prior research on foreign currency debt mainly focuses on its determinants (Allayannis and Ofek, 2001; Géczy et al., 1997; Keloharju and Niskanen, 2001; Allayannis et al., 2003; Kedia and Mozumdar, 2003; Bordo and Meissner, 2006; Nguyen and Faff, 2006; McBrady and Schill, 2007; Clark and Judge, 2008; Brown et al., 2011; Mora et al., 2013). These prior studies examine why a firm issues foreign currency debt from different perspectives, such as hedging purposes against foreign exchange exposures, speculative motives, different tax systems, and legal regimes. We extend this growing literature by investigating the effect of foreign currency debt on corporate financial policy. Second, our study contributes to the literature by providing an additional determinant of dividend payouts. Prior studies document a negative association between leverage ratios and dividend payouts (Jensen et al., 1992; Fenn and Liang, 2001; Fama and French, 2001; Allen and Michaely, 2003; Michaely and Roberts, 2012). However, interestingly, we find that foreign currency debt is positively associated with dividend payouts. Thus, we extend and complement these prior studies by providing new evidence that firms with a higher proportion of foreign currency debt tend to pay more dividends. The remainder of this paper is organized as follows: Section 2 summarizes the prior literature and develops our hypotheses; Section 3 describes details of the sample and defines relevant variables; Section 4 presents the results; Section 5 discusses robustness checks; and Section 6 concludes the study. 2. Prior literature and hypothesis development One of the main concerns of firm managers implementing dividend policy has to do with their financing decisions. As leverage increases, the default risk of firms become high; thus, leverage may be negatively related to the level of dividends (Jensen et al., 1992; Fama and French, 2001; Michaely and Roberts, 2012). In the context of foreign currency risk, as the proportion of foreign currency debt becomes larger, it is likely that firms face a higher risk associated with their debt repayment. If this is the case, to manage such potential risk, firms may have incentives to control cash outflow through their conservative dividend payout policy. However, as firms issue foreign currency debt, an increase in risk associated with the debt may not be large. This is because firms can hedge foreign currency risk using foreign currency debt. For example, using a sample of large U.S. firms, Kedia and Mozumdar (2003) find that firms issue foreign currency debt to hedge their foreign exchange exposures. Kedia and Mozumdar further provide evidence that firms’ decisions to issue foreign currency debt are determined by the size of their foreign operations. A natural hedge can partially occur when firms with foreign operations use foreign currency debt (Géczy et al., 1997; Allayannis and Ofek, 2001; Nguyen and Faff, 2006). Given that firms are exposed to foreign exchange fluctuations, if the firms hedge foreign currency risk by issuing foreign currency debt, they have less incentive to pay a lower level of dividends. Furthermore, firms issue foreign currency debt to reduce their costs of debt financing (Keloharju and Niskanen, 2001). When firms issue foreign currency debt for the purpose of lowering debt financing costs, their foreign currency risk may increase due to the fluctuation in foreign exchange rates and in interest rates of foreign countries. If changes in the values of foreign currency-denominated assets are assumed to be constant, repayment burdens of foreign currency debt will be lessened as foreign exchange rates fall (i.e., the appreciation of domestic currency). In contrast, repayment burdens will be greater as foreign exchange rates rise (i.e., the depreciation of domestic currency). In these situations, firms can hedge their foreign exchange risk by using asset-liability matching, foreign exchange risk insurance, derivatives, and foreign currency debt. Thus, as firms’ foreign currency debt increases, if foreign currency risk can be partially or perfectly hedged while lowering their debt financing costs (Keloharju and Niskanen, 2001), then profitability of the firms will increase. An increase in profitability implies that firms have a higher dividend capacity than before. That is, it is expected that firms with a larger proportion of foreign currency debt will not only be more likely to pay their dividends but also pay a higher level of dividends. Based on the above logic, we propose the first hypothesis as follows (stated in alternative form): H1: Ceteris paribus, firms with a higher proportion of foreign currency debt are more likely to pay their dividends, and pay higher levels of dividends when they do. In addition to our main hypothesis, we further predict that the cross-sectional variation in our main results will depend upon credit risk. Firms with higher credit ratings (or lower credit risk) are less subject to financial constraints (Fazzari et al., 1988; Sufi, 2009) and exhibit a higher level of profitability (Ashbaugh-Skaife et al., 2006). Thus, those firms are likely to have

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more capacity to pay a higher level of dividends. In contrast, firms with higher credit risk are more likely to face financial constraints and thus manage cash outflows, such as dividend payouts, conservatively. Firms with lower credit risk generally tend to issue more foreign currency debt than their counterparts. Thus, the increase in dividend payouts owed to the use of foreign currency debt is expected to be greater in firms with lower credit risk. This expectation can be expressed as the first subsidiary hypothesis to H1: H1a: The positive relation between the proportion of foreign currency debt and the level of dividends is more pronounced in firms with lower credit risk than in those with higher credit risk. We also predict the cross-sectional variation associated with cash flows regarding the relation between the proportion of foreign currency debt and the level of dividends. Firms with high cash flows may have not only the capacity to pay dividends but also higher agency costs. Jensen (1986) argues that cash flows can lead to an agency problem between managers and shareholders, and this issue suggests that firms can use dividends as a way to address the agency problem. In other words, firms with higher cash flows tend to pay a higher level of dividends. Thus, the increase in dividend payouts due to the use of foreign currency debt is expected to be larger in firms with low cash flows. This expectation can be formulated as the second subsidiary hypothesis to H1: H1b: The positive relation between the proportion of foreign currency debt and the level of dividends is stronger in firms with lower cash flows than in those with higher cash flows. 3. Data and variable definition 3.1. Data and sample selection We collect annual financial data from the Korea Investors Service-Value (KIS-Value) database provided by the National Information and Credit Evaluation (NICE) between 2001 and 2017. We use a sample of non-financial firms listed on the Korea Exchange (KRX). To ensure comparability across firms, we also restrict the sample to firms with fiscal years ending in December. We remove firm-year observations with missing values. We winsorize all continuous variables at the 1% and 99% levels to mitigate the impact of extreme observations. Our final sample is composed of 8278 firm-year observations, representing 662 firms. 3.2. Dependent variables We estimate logit and Tobit regressions to examine whether a firm’s use of foreign currency debt affects the level of dividends as well as the likelihood of paying dividends. In the logit model, we consider a firm’s payment of dividends to reflect its decision on whether or not to pay dividends. Specifically, we assign an indicator variable (Dividend Payer) to one if a firm pays its cash dividends, and zero otherwise. Regarding the Tobit model, we use two proxies for dividend payouts. First, following La Porta et al. (2000), Brockman and Unlu (2009), and Chay and Suh (2009), we use the ratio of cash dividends on common stocks to net sales (Dividend Sales) as a proxy for dividend payouts. For a robustness check, we use an alternative proxy for dividend payouts, Dividend Income. It is measured as the ratio of cash dividends to net income. 3.3. Independent variables We use the proportion of foreign currency debt as a main explanatory variable. We measure the proportion of foreign currency debt in a firm’s capital structure through the following two ways. We measure the first proxy as the ratio of net foreign currency debt to the market value of total assets (Foreign Debt MVTA). We use net foreign currency debt to capture its net effect on dividend payouts, calculated as foreign currency debt minus foreign currency assets. The market value of total assets is measured as the sum of total liabilities and the market value of equity. As a robustness check, we calculate the second proxy as the ratio of net foreign currency debt to total debt (Foreign Debt TD). Based on prior studies (Smith and Watts, 1992; Faccio et al., 2001; Fama and French, 2001; Baker and Wurgler, 2004a, 2004b; Von Eije and Megginson, 2008, Brockman and Unlu, 2009; Chay and Suh, 2009), we control for the following variables. First, we control for firm leverage (Leverage) and predict that firms with high leverage will pay low dividends. Second, we control for foreign ownership (Foreign Own) and controlling shareholder’s ownership (Control Own) as proxies for ownership structure. Shleifer and Vishny (1986) argue that institutional investors with high ownership can mitigate the conflicts of interest between managers and shareholders by frequently monitoring managerial actions. Moreover, majority shareholders with high ownership may maximize a firm’s value rather than exploit its resources for their private benefits. Therefore, we predict that firms with greater majority shareholders’ ownership will pay more dividends. Third, we control for operating cash flow ratios (OCF Sales). As in Jensen (1986), we predict that firms with high cash flows will pay more dividends than those with low cash flows. Fourth, following Chay and Suh (2009), we control for stock return volatility (Stock Volatility) as a proxy for cash flow uncertainty. As in Chay and Suh (2009), we predict that firms with higher cash flow uncertainty will pay a lower level of dividends. Fifth, we control for market-to-book ratio (MTB) and R&D intensity (R&D Intensity) as proxies for a firm’s growth opportunities. Firms with higher growth opportunities pay lower dividends because the firms prefer to use internal financing that is less costly to make investments. In contrast, firms with low growth opportunities maintains a smaller proportion of internal reserves and are likely to pay more dividends since such a firm has less capital

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that is needed to invest among earnings generated from business operations. Thus, we predict a negative relation between growth opportunities and the level of dividends. Sixth, we control for firm size (Firm Size). As in Brockman and Unlu (2009), we predict that large firms will tend to pay more dividends than small firms. Seventh, following DeAngelo et al. (2006), we control for the ratio of retained earnings to total equity (Retained Equity) as a proxy for a firm’s financial life-cycle. According to the life-cycle theory of dividends (Mueller, 1972; Fama and French, 2001; Grullon et al., 2002; DeAngelo et al., 2006), immature firms with higher investment opportunities pays a lower level of dividends, while mature firms with lower investment opportunities pays a higher level of dividends. Thus, we predict a positive coefficient on Retained Equity. Eighth, we control for stock turnover ratios (Stock Turnover) as a proxy for stock liquidity. Miller and Modigliani (1961) argue that corporate dividend policy is irrelevant to firm value since investors can create homemade dividends through trading stocks under the assumption of perfect markets. However, in the real business world, there are frictions in the financial market, such as transaction costs. Investors who hold stocks with less liquidity are likely to pay more transaction costs and, as a result, may prefer cash flows through dividends over stock trading. Thus, if investors’ preferences affect corporate dividend policy, firms with low liquidity may be more likely to pay higher levels of dividends than those with high liquidity (Banerjee et al., 2007). Thus, we predict that firms with high stock turnover ratios will pay a lower level of dividends. Ninth, we control for dividend premium (Dividend Premium) as a proxy for catering incentives. The catering theory of dividends proposed by Baker and Wurgler (2004a, 2004b) suggests that firms determine their dividend policies based on the demand for dividends. When the values of dividend-paying firms are highly evaluated compared to those of non-dividend paying firms in capital markets, it is considered indicative of a higher demand for dividends. Firms will adjust their dividend policy in reaction to investors’ demands. Baker and Wurgler (2004a) document that firms with a higher dividend premium are more likely to initiate its dividends. Thus, we predict that dividend premiums are positively related to the levels of dividends. Finally, we control for year and industry fixed effects. All variables are defined in Appendix A. 4. Results 4.1. Descriptive statistics and the Pearson correlation coefficients Table 1 presents descriptive statistics for our sample and the correlation coefficients among variables used in our analysis. Table 1, Panel A describes the historical trend in foreign currency-denominated debt from 2001 to 2017. The amount of foreign currency debt has tripled from about 23 trillion KRW in 2001 to about 70 trillion KRW in 2017. This trend shows that, for our sample firms, the use of foreign currency debt has dramatically increased for the same period. The percentage of sample firms that use foreign currency debt is approximately 68.4% (=5661/8278), indicating that many Korean firms issue foreign currency debt. Panel B in Table 1 shows the descriptive statistics of the full sample. The mean (median) value of Dividend Payer is about 72.5% and 100%, respectively. These values indicate that most of our sample firms pay dividends. The mean (median) value of Dividend Sales is about 2.0% (0.6%). The mean (median) value of Foreign Debt MVTA is 0.3% (0.0%) and its 75th percentile is about 1.7%. The mean (median) value of Foreign Debt TD is −2.5% (0.0%) and its 75th percentile is approximately 4.1%. In addition, control variables used in the analysis are evenly distributed between the top and bottom 5% and are centered at the mean. These distributions indicate that there is no possibility of sample selection biases. Panel C in Table 1 presents the Pearson correlation coefficients among variables. Dividend Payer is positively and significantly correlated with Foreign Debt MVTA and Foreign Debt TD. This evidence suggests that firms with a higher proportion of foreign currency debt are more likely to pay dividends. The correlations between Dividend Sales and Foreign Debt MVTA, and between Dividend Sales and Foreign Debt TD are positive but insignificant. These insignificant correlations may be due to an omitted variable bias. As expected, the correlation between Dividend Payer and Dividend Sales is positive and significant. We also observe that Leverage is negatively and significantly correlated with Dividend Payer and Dividend Sales. 4.2. The proportion of foreign currency debt and the likelihood of paying dividends Using a logit model, we examine the relation between the proportion of foreign currency debt and the likelihood of paying dividends. To do this, we specify the logit regression model as follows: Prob(Divident Payer i, t = 1)

= F(ˇ0 + ˇ1 Foreign Debt MVTAi,t + ˇ2 Leveragei,t +ˇ3 Foreign Owni,t + ˇ4 Control Owni,t + ˇ5 OCF Salesi,t +ˇ6 Stock Volatilityi,t + ˇ7 MTBi,t + ˇ8 R&D Intensityi,t

(1)

+ˇ9 Firm Size i, t + ˇ10 Retained Equityi,t +ˇ11 Stock Turnover i,t + ˇ12 Dividend Premiumi,t ), where we use an indictor variable, Dividend Payer, as a dependent variable. The subscript i and t refer to a firm i during the fiscal year t. Our main explanatory variable of interest is the proportion of foreign currency debt (Foreign Debt MVTA). As

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Table 1 Descriptive statistics and correlation coefficients. Panel A: distribution of foreign-currency denominated debt by year Year

Number of firms issuing foreign currency debt

Amounts of foreign currency debt (in one hundred million KRW)

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Total

230,736 319,873 586,514 396,153 502,244 554,510 569,878 974,596 987,447 942,808 1,612,090 1,257,359 1,003,208 835,635 862,813 1,015,249 698,581

Number of firm-year observations

84 154 305 313 342 364 392 404 403 395 367 372 330 350 370 356 360 5661

101 201 382 408 457 479 508 511 520 546 566 572 580 597 624 637 589 8278

Panel B: descriptive statistics Variable

N

Mean

Dividend Payer Dividend Sales Foreign Debt MVTA Foreign Debt TD Leverage Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Cost Debt

8278 8278 8278 8278 8278 8278 8278 8278 8278 8278 8278 8278 8278 8278 8278 7390

0.725 0.020 0.003 −0.025 0.448 0.111 0.431 0.070 46.968 1.105 0.010 26.703 0.399 0.012 −0.087 4.843

Std. Dev. 0.446 0.051 0.104 0.257 0.234 0.143 0.168 0.142 19.131 0.641 0.021 1.600 0.649 0.021 0.340 3.626

25th

Median

75th

0.000 0.000 −0.017 −0.051 0.252 0.010 0.312 0.011 33.632 0.745 0.000 25.555 0.260 0.002 −0.261 2.814

1.000 0.006 0.000 0.000 0.446 0.047 0.429 0.059 43.318 0.931 0.001 26.368 0.522 0.005 −0.060 4.117

1.000 0.015 0.017 0.041 0.637 0.162 0.541 0.114 56.593 1.210 0.010 27.604 0.740 0.012 0.206 5.647

Panel C: Pearson correlation coefficients Variable

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(1) Dividend Payer (2) Dividend Sales (3) Foreign Debt MVTA (4) Foreign Debt TD (5) Leverage (6) Foreign Own (7) Control Own (8) OCF Sales (9) Stock Volatility (10) MTB (11) R&D Intensity (12) Firm Size (13) Retained Equity (14) Stock Turnover (15) Dividend Premium

1.000 0.234 0.039 0.036 −0.216 0.230 0.090 0.235 −0.315 −0.054 −0.024 0.159 0.482 −0.285 −0.045

1.000 −0.017 −0.023 −0.348 0.112 0.114 0.480 −0.129 0.112 −0.003 0.082 0.109 −0.105 0.048

1.000 0.872 0.198 0.015 0.054 0.008 −0.009 −0.036 −0.069 0.146 −0.014 −0.042 −0.012

1.000 0.234 −0.005 0.069 0.005 −0.006 −0.052 −0.080 0.144 −0.019 −0.051 −0.012

1.000 −0.239 −0.035 −0.269 0.099 −0.492 −0.180 −0.043 −0.202 0.053 0.042

1.000 −0.149 0.202 −0.202 0.232 0.061 0.489 0.205 −0.190 −0.040

1.000 0.066 1.000 −0.142 −0.214 1.000 −0.118 0.104 0.136 1.000 −0.113 0.022 0.024 0.226 1.000 −0.079 0.208 −0.206 0.322 0.085 1.000 0.125 0.241 −0.383 −0.082 0.001 0.170 1.000 −0.252 −0.172 0.588 0.071 0.013 −0.234 −0.298 1.000 −0.005 0.038 −0.032 −0.032 0.015 0.045 0.037 0.017

(15)

1.000

This table presents descriptive statistics for our sample and the correlation coefficients among variables. Panel A shows historical trend in foreign currencydenominated debt from 2001 to 2017. Panel B reports descriptive statistics of full sample. Panel C presents the Pearson correlation coefficients among main variables. Correlations in bold denote significance at the 1% level (two-tailed test). All variables are defined in Appendix A.

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Table 2 The effect of the proportion of foreign currency debt on the likelihood of paying dividends. Independent variables

Dependent variable: Dividend Payer (1)

Intercept Foreign Debt MVTA Leverage

2.977 (9.67) 1.623 (2.97) −2.602 (−9.09)

(2) *** *** ***

3.061 (4.17) 1.640 (3.05) −2.998 (−9.29)

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Year fixed effects Industry fixed effects Number of observations Pseudo R2

Yes No 8278 0.062

Yes Yes 8278 0.136

*** *** ***

(3)

(4)

−1.985 (−1.44) 1.387 (2.35) −2.578 (−6.78) 0.965 (1.35) 0.707 (1.68) 1.255 (3.13) −0.014 (−4.87) −0.524 (−3.33) −6.171 (−2.04) 0.167 (2.98) 4.145 (16.92) −5.048 (−1.92) 2.578 (6.39) Yes No 8278 0.394

−3.469 (−2.01) 1.763 (3.10) −2.553 (−5.80) 1.021 (1.28) 0.735 (1.76) 0.888 (2.14) −0.014 (−4.65) −0.525 (−3.16) −10.223 (−3.33) 0.191 (2.87) 4.207 (16.22) −4.169 (−1.68) 2.580 (5.92) Yes Yes 8278 0.418

** ***

* *** *** *** ** *** *** * ***

** *** ***

* ** *** *** *** *** *** * ***

This table shows the results of analyzing the relation between the proportion of foreign currency debt and the likelihood of paying dividends. To do this, we estimate the pooled fixed-effect logit model with a binary dependent variable, Dividend Payer. The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The Z-statistics are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

a robustness, we also use an additional proxy variable, Foreign Debt TD, for foreign currency debt. We control for year and industry fixed effects in Eq. (1). All variables are defined in Appendix A. Table 2 shows the results of the pooled fixed-effect logit regression. In columns (1) and (2), we estimate the likelihood of paying dividends as a function of Foreign Debt MVTA and Leverage. We include year fixed effects in column (1), while we include year and industry fixed effects in column (2). We find a positive and significant coefficient on Foreign Debt MVTA in the columns, indicating that the likelihood of paying dividends increases with the proportion of foreign currency debt. In columns (3) and (4), we include several control variables that affect the likelihood of paying dividends. We add year fixed effects in column (3) and year and industry fixed effects in column (4). The coefficient on Foreign Debt MVTA is positive and significant in the columns. In contrast, we find a negative and significant relation between Leverage and Dividend Payer across all four columns, suggesting that firms with high leverage are less likely to pay dividends. Taken together, these findings support our first hypothesis (H1) that firms with a higher proportion of foreign currency debt are more likely to pay dividends. The coefficients on control variables are consistent in columns (3) and (4). Specifically, the coefficient on Leverage is negative and significant across the columns. The coefficient on Foreign Own is positive but insignificant, while the coefficient on Control Own is positive and significant. We find a positive and significant coefficient on OCF Sales, indicating that firms with high operating cash flows are more likely to pay dividends. We find a negative and significant coefficient on Stock Volatility. The coefficients on MTB and R&D Intensity are negative and significant, suggesting that firms with higher growth opportunities have a lower likelihood of paying dividends. As expected, we find that the coefficients on Firm Size and Retained Earnings are positive and significant. The coefficient on Stock Turnover is negative but insignificant. Finally, consistent with our expectations, the coefficient on Dividend Premium is positive and significant. 4.3. The proportion of foreign currency debt and the level of dividends We investigate the relation between the proportion of foreign currency debt and the levels of dividends. To do this, we use Dividend Sales as a proxy for the levels of dividends. The dependent variable, Dividend Sales, has a number of observations at zero, i.e., the variable is censored at zero. Thus, some of the desirable properties of the ordinary least squares (OLS) estimators

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Table 3 The effect of the proportion of foreign currency debt on the levels of dividends. Independent variables

Dependent variable: Dividend Sales (1)

Intercept

(2)

0.065 (9.52) 0.050 (4.92) −0.117 (−9.65)

Foreign Debt MVTA Leverage

***

0.046 (4.76) 0.044 (4.56) −0.103 (−10.89)

*** ***

*** *** ***

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Year fixed effects Industry fixed effects Number of observations Number of left-censored obs. Number of uncensored obs.

Yes No 8278 2275 6003

Yes Yes 8278 2275 6003

(3)

(4)

−0.026 (−0.87) 0.026 (3.34) −0.083 (−7.26) −0.008 (−0.71) 0.028 (3.12) 0.191 (9.32) −0.000 (−2.48) −0.009 (−2.39) −0.185 (−2.66) 0.002 (1.60) 0.029 (6.53) −0.141 (−2.42) 0.023 (4.20) Yes No 8278 2275 6003

−0.014 (−0.49) 0.039 (4.74) −0.073 (−7.95) −0.011 (−1.07) 0.030 (3.81) 0.156 (8.67) −0.000 (−3.35) −0.006 (−1.73) −0.232 (−3.57) 0.001 (0.65) 0.028 (7.01) −0.034 (−0.69) 0.015 (2.92) Yes Yes 8278 2275 6003

*** ***

*** *** ** ** ***

*** ** ***

*** ***

*** *** *** * ***

***

***

This table shows the results of analyzing the relation between the proportion of foreign currency debt and the levels of paying dividends. To do this, we estimate the pooled fixed-effect Tobit regressions with a dependent variable, Dividend Sales. The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The t-statistics are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

may no longer hold; for example, it leads to inconsistent estimates of the parameters (Kennedy, 2003). To address these problems, we follow Brockman and Unlu (2009) and use a Tobit regression model, also called a censored normal regression model, on censored data including many zeros. To test our first hypothesis, the Tobit regression model is given by Dividend Salesi,t

= ˇ0 + ˇ1 Foreign Debt MVTAi,t + ˇ2 Levergei,t + ˇ3 Foreign Owni,t +ˇ4 Control Owni,t + ˇ5 OCF Salesi,t + ˇ6 Stock Volatilityi,t +ˇ7 MTBi,t + ˇ8 R&D Intensityi,t + ˇ9 Firm Sizei,t + ˇ10 Retained Equityi,t

(2)

+ˇ11 Stock Turnover i,t + ˇ12 Dividend Premiumi,t



+

 Dividend Salesi,t =

i,t

Year Dummy +

∗ Dividend Salesi,t 0



i,t

Industry Dummy + εi,t

∗ >0 ifDividend Salesi,t otherwise,

where Dividend Sales presents a dependent variable, measured as cash dividends divided by net sales. As in the previous section, Foreign Debt MVTA is our main explanatory variable of interest. All variables are defined in Appendix A. Table 3 presents the results of the pooled fixed-effect Tobit regression. The results reported in all columns (1) through (4) show that the coefficient on Foreign Debt MVTA is positive and significant. The results confirm the previous findings reported in Table 2. These findings are consistent with our first hypothesis (H1) that firms with a higher proportion of foreign currency debt pay higher levels of dividends. Consistent with our prediction, the coefficient on Leverage is negative and significant across all four columns, indicating that firms with higher leverage pay a lower level of dividends. Furthermore, we find a consistent sign of coefficients on each control variable in columns (3) and (4). Specifically, the coefficient on Foreign Own is negative but insignificant, while the coefficient on Control Own is positive and significant. We find a positive and significant coefficient on OCF Sales, consistent with our expectation that firms with high operating cash flows pay more dividends. The coefficient on Stock Volatility is negative and significant, indicating that firms with high cash

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27

flow uncertainty pay less dividends as in Chay and Suh (2009). We find negative and significant coefficients on MTB and R&D Intensity, consistent with firms with higher growth opportunities pay less dividends. We find no relation between Firm Size and Dividend Sales. The coefficients on Retained Equity are positive and significant, consistent with our prediction. We find a negative and significant coefficient on Stock Turnover in column (3). Finally, we find a positive and significant coefficient on Dividend Premium, consistent with the catering theory of dividends. 4.4. The proportion of foreign currency debt and the cost of debt We investigate the relation between the proportion of foreign currency debt and the cost of debt. To support our logical argument associated with the first hypothesis, we estimate the following regression models: Cost Debt i,t

= ˇ0 + ˇ1 Foreign Debt MVTAi,t + ˇ2 Leveragei,t + ˇ3 Foreign Owni,t +ˇ4 Control Owni,t + ˇ5 OCF Salesi,t + ˇ6 Stock Volatilityi,t +ˇ7 MTBi,t + ˇ8 R&D Intensityi,t + ˇ9 Firm Sizei,t



+

i,t

Year Dummy +



i,t

(3)

Industry Dummy + εi,t .

where we use Cost Debt as a dependent variable. Following prior literature (Pittman and Fortin, 2004; Francis et al., 2005; Gray et al., 2009; Jung et al., 2018), we measured Cost Debt as a firm’s interest expenses in year t divided by its average interest-bearing debt in year t and t − 1. Our explanatory variable of interest is Foreign Debt MVTA. Based on prior studies (Fama and French, 1992; Brockman and Unlu, 2009; Li et al., 2014), we choose the control variables as presented in Eq. (3). All variables are defined in Appendix A. Table 4 shows the results of the pooled OLS regression. In Panel A, we estimate the contemporaneous effect of foreign currency debt on the cost of debt. The coefficient on Foreign Debt MVTA is negative and significant in all four columns (1) through (4), indicating that firms with a higher proportion of foreign currency debt have a lower cost of debt. We find a negative and significant coefficient on Leverage, consistent with our expectation. In columns (3) and (4), we find no relation between Foreign Own and Cost Debt. The coefficients on Control Own, OCF Sales, and Firm Size are negative and significant, while the coefficients on Stock Volatility and MTB are positive and significant. In Panel B of Table 4, we repeat the analysis using the lagged independent variables to mitigate an endogeneity problem. Consistent with our expectation, we find a negative and significant coefficient on the lagged foreign currency debt (L Foreign Debt MVTA) across all four columns (1) and (4). This finding confirms the previous result based on the contemporaneous variable. The coefficient on the lagged leverage (L Leverage) is positive and significant in all columns. The sign of coefficients on control variables are consistent with those reported in Panel A. Taken together, our findings support the first hypothesis by providing evidence that foreign currency debt is negatively related to the cost of debt. That is, firms with a higher proportion of foreign currency debt have lower costs of debt. The reduction in costs of debt with the use of foreign currency debt is linked to an increase in profitability; accordingly, a firms’ dividend capacity becomes larger. 4.5. Factors affecting the link between the proportion of foreign currency debt and the level of dividends We investigate the relation between the proportion of foreign currency debt and the level of dividends with a focus on the cross-sectional variation related to credit risk. To capture cross-sectional variations associated with credit risk, we include an interaction term between the proportion of foreign currency debt and a dummy variable for the credit risk, Foreign Debt MVTA*Credit Risk Dummy, in Eq. (2). For Credit Risk Dummy, we assign the value of one if a firm’s Altman’s (1968) Z-scores exceed 2.99, and zero otherwise. Firms with Z-scores greater than 2.99 are considered as financially healthy. We expect that the coefficient on the interaction term is positively related to the level of dividends. Column (1) in Table 5 reports the results of Tobit regressions using an interaction term, Foreign Debt MVTA*Credit Risk Dummy as a main explanatory variable. The coefficient on Foreign Debt MVTA is positive and significant, consistent with the findings reported in Table 3. As expected, we find that the coefficient on Foreign Debt MVTA*Credit Risk Dummy is positive and significant, supporting our first subsidiary hypothesis (H1a). We further find a negative and significant coefficient on Leverage. We also test the cross-sectional variation associated with cash flows on the relation between the proportion of foreign currency debt and the level of dividends. To capture cross-sectional variations related to free cash flows, we include an interaction term between the proportion of foreign currency debt and a dummy variable for operating cash flows, Foreign Debt MVTA*Cash Flow Dummy, in Eq. (2). For Cash Flow Dummy, we assign the value of one if a firm’s operating cash flow ratio (measured as the ratio of operating cash flows to total assets) is negative, and zero otherwise. We expect that the coefficient on the interaction term is positively associated with the level of dividends. Column (2) in Table 5 shows the results of Tobit regressions using an interaction term, Foreign Debt MVTA*Cash Flow Dummy. Consistent with our results reported in Table 3, we find that the coefficient on

28

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Table 4 The effect of the proportion of foreign currency debt on the cost of debt. Panel A: contemporaneous model Independent variables

Dependent variable: Cost Debt (1)

Intercept Foreign Debt MVTA Leverage

7.471 (13.87) −3.306 (−4.96) 0.830 (1.98)

(2) *** *** **

5.779 (8.23) −2.512 (−3.84) 1.002 (2.51)

(3) ***

Yes Yes 7390 0.140

11.952 (6.98) −2.409 (−3.69) 1.384 (2.92) 0.846 (1.09) −1.755 (−3.53) −1.918 (−3.33) 0.019 (4.89) 0.618 (3.05) 1.333 (0.36) −0.226 (−3.70) Yes No 7390 0.116

(2)

(3)

*** **

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Year fixed effects Industry fixed effects Number of observations Adjusted R2

Yes No 7390 0.071

(4) *** *** ***

*** *** *** ***

***

11.606 (6.43) −1.774 (−2.84) 1.117 (2.40) −0.014 (−0.02) −1.638 (−3.82) −1.791 (−3.52) 0.016 (4.12) 0.462 (2.20) 6.280 (1.73) −0.249 (−3.88) Yes Yes 7390 0.173

*** *** **

*** *** *** ** * ***

Panel B: lagged model Independent variables

Dependent variable: Cost Debt (1)

Intercept L Foreign Debt MVTA L Leverage

5.878 (13.18) −3.573 (−5.75) 0.791 (1.73)

*** *** *

4.058 (6.44) −2.755 (−4.38) 1.006 (2.28)

L Foreign Own L Control Own L OCF Sales L Stock Volatility L MTB L R&D Intensity L Firm Size Year fixed effects Industry fixed effects Number of observations Adjusted R2

Yes No 6595 0.064

Yes Yes 6595 0.138

*** *** **

9.922 (6.12) −2.716 (−4.56) 1.505 (2.98) 1.032 (1.34) −1.778 (−3.40) −1.804 (−2.85) 0.020 (5.37) 0.679 (3.04) 3.756 (0.93) −0.219 (−3.57) Yes No 6595 0.110

(4) *** *** ***

*** *** *** ***

***

9.333 (5.26) −2.092 (−3.55) 1.228 (2.49) 0.129 (0.18) −1.616 (−3.72) −1.760 (−3.08) 0.017 (4.55) 0.515 (2.18) 8.656 (2.24) −0.236 (−3.58) Yes Yes 6595 0.173

*** *** **

*** *** *** ** ** ***

This table shows the results of analyzing the relation between the proportion of foreign currency debt and the cost of debt. To do this, we estimate the pooled OLS regression with a dependent variable, Cost Debt, measured as a firm’s interest expenses in year t divided by its average interest-bearing debt in year t and t − 1. In Panel A, we estimate the contemporaneous effect of foreign currency debt on the cost of debt. In Panel B, we repeat the analysis using the lagged independent variables to mitigate an endogeneity problem. L is used as a prefix to denote lagged variables. The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The t-statistics are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

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Table 5 The effect of credit risk and cash flows on the relation between the proportion of foreign currency debt and levels of dividends. Independent variables

Dependent variable: Dividend Sales (1)

Intercept Foreign Debt MVTA Foreign Debt MVTA*Credit Risk Dummy Z Score

−0.085 (−3.59) 0.021 (2.80) 0.053 (2.72) 0.006 (7.49)

*** ***

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Year/Industry fixed effects Number of observations Number of left-censored Obs. Number of Uncensored Obs.

−0.027 (−3.07) −0.015 (−1.87) 0.028 (3.93) 0.128 (7.57) −0.000 (−2.87) −0.017 (−5.04) −0.142 (−2.29) 0.003 (2.75) 0.024 (6.15) −0.006 (−0.14) 0.013 (2.45) Yes 8278 2275 6003

(3)

−0.014 (−0.50) 0.033 (4.06)

−0.084 (−3.59) 0.014 (2.04) 0.057 (2.90) 0.006 (7.49) 0.031 (2.36) −0.027 (−3.07) −0.015 (−1.86) 0.028 (3.92) 0.128 (7.56) −0.000 (−2.87) −0.017 (−5.04) −0.142 (−2.30) 0.003 (2.74) 0.024 (6.16) −0.008 (−0.17) 0.013 (2.47) Yes 8278 2275 6003

***

*** ***

Foreign Debt MVTA*Cash Flow Dummy Leverage

(2)

*** * *** *** *** *** ** *** ***

**

0.030 (1.98) −0.073 (−7.93) −0.011 (−1.07) 0.030 (3.81) 0.157 (8.67) −0.000 (−3.35) −0.006 (−1.73) −0.232 (−3.58) 0.001 (0.65) 0.028 (7.01) −0.036 (−0.72) 0.015 (2.94) Yes 8278 2275 6003

** ***

*** *** *** * ***

***

***

*** ** *** *** ** *** * *** *** *** *** ** *** ***

**

This table reports the results of the pooled fixed-effect Tobit regressions using Dividend Sales as a dependent variable. To capture cross-sectional variations associated with credit risk, we include an interaction term between the proportion of foreign currency debt and a dummy variable for the credit risk, Foreign Debt MVTA*Credit Risk Dummy, in Eq. (2). To capture cross-sectional variations related to cash flows, we include an interaction term between the proportion of foreign currency debt and a dummy variable for cash flows, Foreign Debt MVTA*Cash Flow Dummy, in Eq. (2). The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The t-statistics are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

Foreign Debt MVTA is positive and significant. The coefficient on Foreign Debt MVTA*Cash Flow Dummy is positive and significant, supporting our second subsidiary hypothesis (H1b). Furthermore, the coefficient on Leverage is negative and significant. In column (3), we repeat our analysis including two interaction terms, Foreign Debt MVTA*Credit Risk Dummy and Foreign Debt MVTA*Cash Flow Dummy. Our results are qualitatively similar to those reported in columns (1) and (2), supporting our first and second subsidiary hypotheses.2 We further find that coefficients on control variables are fairly consistent across columns (1) through (3).

5. Robustness checks 5.1. Alternative estimation method and endogeneity concerns We perform additional robustness checks to identify whether our main results are robust to a different estimation method and endogeneity issues. To do this, we repeat the analysis using firm fixed-effect Tobit models and two-stage Tobit regressions with an endogenous regressor.

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Table 6 Alternative estimation methods and endogeneity concerns. Panel A: firm fixed-effect tobit model Independent variables

Dependent variable: Dividend Sales (1)

Intercept

(2)

0.057 (8.73) 0.035 (2.55) −0.103 (−7.43)

Foreign Debt MVTA Leverage

***

0.128 (1.36) 0.043 (3.28) −0.083 (−6.31) −0.018 (−1.19) 0.054 (4.11) 0.123 (7.29) −0.000 (−1.89) −0.001 (−0.19) −0.002 (−0.02) −0.005 (−1.24) 0.033 (6.43) −0.071 (−1.49) 0.018 (2.89) Yes Yes 8278 2275 6003

** ***

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Year fixed effects Firm fixed effects Number of observations Number of left-censored obs. Number of uncensored obs.

Yes Yes 8278 2275 6003

*** ***

*** *** *

***

***

Panel B: second-stage tobit regressions with an endogenous regressor Independent variables

Dependent variable: Dividend Sales (1)

Intercept Pred Foreign Debt MVTA Leverage Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium

0.070 (10.59) 0.228 (5.35) −0.132 (−27.74)

(2) *** *** ***

0.051 (5.26) 0.150 (3.13) −0.110 (−24.31)

*** *** ***

(3)

(4)

0.019 (0.99) 0.151 (4.10) −0.094 (−19.29) −0.005 (−0.89) 0.022 (4.69) 0.189 (37.74) −0.000 (−2.63) −0.010 (−7.74) −0.159 (−4.82) 0.001 (0.78) 0.029 (13.72) −0.153 (−3.25) 0.015 (2.03)

0.023 (1.08) 0.136 (3.54) −0.081 (−17.15) −0.011 (−2.24) 0.025 (5.98) 0.157 (33.49) −0.000 (−4.47) −0.006 (−4.78) −0.245 (−7.33) −0.000 (−0.60) 0.028 (14.07) −0.047 (−1.10) 0.010 (1.48)

*** ***

*** *** *** *** ***

*** *** **

*** *** ** *** *** *** *** ***

***

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31

Table 6 (Continued) Panel B: second-stage tobit regressions with an endogenous regressor Independent variables

Dependent variable: Dividend Sales (1)

Year fixed effects Industry fixed effects Number of observations Number of left-censored obs. Number of uncensored obs. Wald Test of Exogeneity

Yes No 8278 2275 6003 19.65***

(2) Yes Yes

Yes No 8278 2275 6003 5.18**

(3)

(4)

8278 2275 6003 12.52***

8278 2275 6003 6.73***

Yes Yes

This table shows the results of a sensitivity analysis to alternative estimation specifications and endogeneity issues. To do this, we use a dependent variable, Dividend Sales. Panel A shows the results of firm fixed-effects Tobit models. Panel B reports the results of the second-stage Tobit regressions with an endogenous regressor. The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The t-statistics (Z-statistics) are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

Panel A in Table 6 reports the results of the firm fixed-effects Tobit regression model. We use robust standard errors clustered at the firm level. We also control for year and firm fixed effects. Consistent with our results reported in Table 3, the coefficient on Foreign Debt MVTA is positive and significant in all columns (1) and (2). These findings support our main hypothesis of a positive relation between the proportion of foreign currency debt and the level of dividends. Furthermore, we find a negative and significant coefficient on Leverage. In column (2), the coefficients on Control Own and OCF Sales are positive and significant, while the coefficient on Stock Volatility is negative and significant. We find no relation between MTB, R&D Intensity, Firm Size, and Stock Turnover and the Dividend Sales. The coefficients on Retained Equity and Dividend Premium are positive and significant. Next, we consider a potential endogeneity problem due to the joint determination of foreign currency debt and dividend decisions. For example, using a sample of Finnish firms, Keloharju and Niskanen (2001) examine the determinants of a firm’s use of foreign currency debt. They show that dividend yield, measured as dividend per share divided by year-end stock price, can be one of the factors that affect the likelihood of using foreign currency debt. Thus, an endogeneity bias may arise when foreign currency debt and dividend payouts are jointly determined. As a result, the estimated coefficients from Tobit regressions may be biased and inconsistent. To address potential endogeneity issues, we re-test our main hypothesis using two-stage regressions with an endogenous regressor (i.e., foreign currency debt). The estimation procedures are for the two-stage regressions are as follows. In the first-stage regression, we regress Foreign Debt MVTA as a dependent variable, on instrumental and control variables, and then obtain the predicted values of Foreign Debt MVTA.3 In the second-stage regression, using a Tobit model, we regress Dividend Sales as a dependent variable, on explanatory variables, including the predicted value of Foreign Debt MVTA estimated in the first stage. Based on Keloharju and Niskanen (2001), we use the following instrumental variable: Export to Net Sales, measured as exports divided by net sales. In the analysis, we include year and industry dummies. Panel B in Table 6 shows the results of second-stage Tobit regressions. We find that the coefficient on the predicted values of Foreign Debt MVTA (Pred Foreign Debt MVTA) is positive and significant across all columns (1) through (4). We find a negative and significant coefficient on Leverage in the columns. We find no relation between Foreign Own and Dividend Sales. Moreover, the coefficients on Control Own are positive and significant across all columns. OCF Sales and Retained Equity are positively related to Dividend Sales, while Stock Volatility, MTB, and R&D Intensity are negatively related to Dividend Sales. Overall, our main results are robust to an alternative estimation method and endogeneity issues.

5.2. Alternative measure of foreign currency debt We repeat our analysis using an alternative measure of foreign currency debt, defined as the ratio of foreign currency debt to total debt (Foreign Debt TD). Table 7 shows the results of Tobit regressions using Foreign Debt TD as a main explanatory variable. We find a positive and significant coefficient on Foreign Debt TD across all columns (1) through (4). The coefficient on Leverage is negative and significant. Regarding control variables, the results are qualitatively similar to our findings based on Foreign Debt MVTA. Taken together, using an alternative measure of foreign currency debt (Foreign Debt TD) in Eqs. (1) and (2) does not change our results with Foreign Debt MVTA.

2 We also repeat the analysis using an alternative estimation specification as well as proxies for foreign currency debt and the level of dividends. Our untabulated results are qualitatively similar to those reported in Table 5. 3 We perform a Wald test of exogeneity to identify whether or not the estimation using instrumental variables is appropriate. The null hypothesis is that the proportion of foreign currency debt is exogenous (i.e., there is no endogeneity problem). At the bottom of Panel B, we present the results from a Wald test of exogeneity and find that the null hypothesis is rejected. Thus, we employ two-stage Tobit regressions to address the endogeneity problem.

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Table 7 Alternative proxy for foreign currency debt. Independent variables

Dependent variables: Dividend Payer

Dividend Sales

(1) Intercept Foreign Debt TD Leverage

Yes Yes 8278

−3.406 (−1.96) 0.687 (2.95) −2.587 (−5.84) 1.043 (1.31) 0.735 (1.76) 0.863 (2.08) −0.014 (−4.67) −0.524 (−3.12) −10.102 (−3.28) 0.193 (2.89) 4.191 (16.18) −4.101 (−1.65) 2.603 (5.99) Yes Yes 8278

0.136

0.418

3.192 (4.27) 0.717 (3.27) −3.073 (−9.49)

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Year fixed effects Industry fixed effects Number of observations Number of left-censored obs. Number of uncensored obs. Pseudo R2

(2) *** *** ***

(3) ** *** ***

0.049 (4.87) 0.018 (4.04) −0.104 (−10.88)

* ** *** *** *** *** *** * *** Yes Yes 8278 2275 6003

(4) *** *** ***

−0.012 (−0.44) 0.014 (3.84) −0.074 (−8.01) −0.010 (−1.01) 0.030 (3.84) 0.156 (8.65) −0.000 (−3.40) −0.006 (−1.73) −0.233 (−3.58) 0.001 (0.67) 0.028 (6.96) −0.034 (−0.68) 0.016 (3.05) Yes Yes 8278 2275 6003

*** ***

*** *** *** * ***

***

***

This table shows the results of the pooled fixed-effect Tobit regressions using the alternative proxy for foreign currency debt, Foreign Debt TD. The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The t-statistics (Z-statistics) are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

5.3. Alternative proxy for the level of dividends As a further robustness check, we repeat the analysis using an alternative proxy for the level of dividends. The proxy is measured as cash dividends on common stocks divided by net income (Dividend Income). Table 8 shows the results of Tobit regressions using Dividend Income as a dependent variable. In all columns (1) through (4), we find that the coefficient on Foreign Debt MVTA is positive and significant. This finding is consistent with the results of regressions using Dividend Sales, confirming that our main results are robust. Furthermore, the coefficient on Leverage is negative and significant as found in Table 3. Our untabulated results show that the results are robust to an alternative estimation specification and endogeneity problems. 6. Conclusions In this study, we investigate the effect of foreign currency-denominated debt on dividend payout policy. To do so, we estimate the pooled fixed-effect logit and Tobit regressions to test our first hypothesis that the proportion of foreign currency debt is positively related to the likelihood of paying dividends and the level of dividends. Consistent with the first hypothesis, we find positive and significant relations between the proportion of foreign currency debt and the likelihood of paying dividends as well as between the proportion of foreign currency debt and the level of dividends. We further find that the positive relation between the proportion of foreign currency debt and the level of dividends is stronger in firms with lower credit risk and cash flows, consistent with our first and second subsidiary hypotheses. In addition, our main findings are robust to an alternative estimation specification, endogeneity issues, and alternative proxies for foreign currency debt and the level of dividends. Our study provides meaningful implications for a firm’s dividend and financing policies. Specifically, given that leverage ratios are comparable across firms, firms can hedge risks due to fluctuations in foreign currency exchange rates by issuing foreign currency debt. Several studies further find that firms can reduce debt financing costs through the use of foreign

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Table 8 Alternative proxy for levels of dividends. Independent variables

Dependent variable: Dividend Income

Intercept

0.380 (8.17) 0.215 (2.48) −0.418 (−8.78)

(1)

Foreign Debt MVTA Leverage

(2) *** ** ***

0.300 (2.76) 0.243 (2.88) −0.412 (−8.42)

Foreign Own Control Own OCF Sales Stock Volatility MTB R&D Intensity Firm Size Retained Equity Stock Turnover Dividend Premium Year fixed effects Industry fixed effects Number of observations Number of left-censored obs. Number of uncensored obs.

Yes No 8278 2670 5608

Yes Yes 8278 2670 5608

(3) *** *** ***

0.364 (1.95) 0.143 (1.87) −0.230 (−4.37) 0.025 (0.31) 0.140 (2.50) 0.242 (4.24) −0.003 (−6.99) −0.003 (−0.17) −0.878 (−2.34) −0.005 (−0.72) 0.357 (12.02) −0.540 (−1.07) 0.259 (4.66) Yes No 8278 2670 5608

(4) * * ***

** *** ***

**

***

***

0.259 (1.19) 0.249 (3.15) −0.218 (−4.00) 0.007 (0.09) 0.133 (2.47) 0.164 (3.01) −0.003 (−6.97) 0.001 (0.05) −1.450 (−3.53) −0.007 (−0.84) 0.359 (11.94) −0.372 (−0.76) 0.237 (4.37) Yes Yes 8278 2670 5608

*** ***

** *** ***

***

***

***

This table shows the results of the pooled fixed-effect Tobit regressions using the alternative measure of levels of dividends. We use Dividend Income as a dependent variable. The sample period is from 2001 to 2017. We use robust standard errors clustered at the firm level. The t-statistics are in parentheses. ***, **, and * denote the statistical significance at the 1%, 5%, and 10% levels, respectively (two-tailed test). All variables are defined in Appendix A.

currency debt (Keloharju and Niskanen, 2001). For firms issuing foreign currency debt, the effect of reduction in debt financing costs is likely to outweigh the hedging costs associated with the debt, thereby likely increasing their profitability. Accordingly, for these firms, the use of foreign currency debt is likely to provide firms with more dividend capacity. Thus, our study sheds light on the role of foreign currency debt in the determination of dividend payouts. Appendix A. Variable definitions Variable

Definition

Dividend Payer Dividend Sales Foreign Debt MVTA

An indicator variable that equals one if a firm pays cash dividends, and zero otherwise. Cash dividends on common stocks divided by net sales. Net foreign currency debt divided by the market value of total assets. Net foreign currency debt is calculated as foreign currency debt minus foreign currency assets. The market value of total assets is measured as the sum of total liabilities and market value of equity. Net foreign currency debt divided by total debt. Net foreign currency debt is calculated as foreign currency debt minus foreign currency assets. The ratio of total non-current liabilities to market value of total assets. The sum of common and restricted stock owned by foreign investors, divided by total shares outstanding. The sum of common and restricted stock owned by controlling shareholders, divided by total shares outstanding. The operating income before depreciation minus capital expenditure, divided by net sales. Standard deviation of daily stock price returns multiplied by the square root of the number of trading days in a year. Retained earnings divided by total equity. The ratio of the sum of the market value of equity and the book value of total liabilities to book value of total assets. R&D expenditures divided by net sales. The natural logarithm of the market value of total assets, where the market value of total assets is the sum of the book value of total liabilities and the market value of common equity. Total value of shares traded for the fiscal year divided by average annual market capitalization. The difference in the logarithm of average market-to-book ratios between dividend-paying and non-dividend-paying firms. A firm’s interest expenses in year t divided by its average interest-bearing debt in year t and t − 1.

Foreign Debt TD Leverage Foreign Own Control Own OCF Sales Stock Volatility Retained Equity MTB R&D Intensity Firm Size Stock Turnover Dividend Premium Cost Debt

34 Export to Net Sales Dividend Income Credit Risk Dummy Cash Flow Dummy

Y.M. Choi and K. Park / J. of Multi. Fin. Manag. 49 (2019) 20–34 Exports divided by net sales. Cash dividends on common stocks divided by net income. An indicator variable set to one if a firm’s Altman’s (1968) Z-scores exceed 2.99 and zero otherwise. An indicator variable set to one if a firm’s cash flow ratio (measured as the ratio of operating cash flows to total assets) is negative and zero otherwise.

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