The payout policy of politically connected firms: Tunnelling or reputation?

The payout policy of politically connected firms: Tunnelling or reputation?

North American Journal of Economics and Finance 50 (2019) 101025 Contents lists available at ScienceDirect North American Journal of Economics and F...

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North American Journal of Economics and Finance 50 (2019) 101025

Contents lists available at ScienceDirect

North American Journal of Economics and Finance journal homepage: www.elsevier.com/locate/najef

The payout policy of politically connected firms: Tunnelling or reputation?

T

Félix J. López-Iturriagaa, , Domingo Javier Santana Martínb ⁎

a b

Universidad de Valladolid, School of Business & Economics, 47011 Valladolid, Spain University of Las Palmas de Gran Canaria, School of Business & Economics, 35017 Las Palmas de Gran Canaria, Spain

ARTICLE INFO

ABSTRACT

JEL codes: G34 G3

Using company directors who have a background in politics as a measure of political connections, we analyze the relationship between political ties and dividend policy in a sample of listed Spanish firms. We find political connections to be positively related with cash dividends. This result is consistent with concern regarding the interests of minority shareholders in politically connected firms or with the lower number of financial constraints in these firms. We also find a positive relationship between political connections and share repurchases, a means of shareholder compensation that is gaining popularity, a result that might be related to the valuation of politically connected firms. Our results are robust to alternative empirical specifications such as the propensity score matching procedure, different metrics of payout policy, and different measures of political connections. Interestingly, the recent financial crisis has not changed connected firms’ preference for shareholder compensation with dividends and share repurchases.

Keywords: Political connections Dividends Dominant owners Share repurchases Board of directors

1. Introduction Political connections are common in the corporate sector. Faccio (2006) shows that, on average, politically connected firms account for eight percent of world market capitalization. In the UK, the figure is 39 percent, in Ireland it is 22 percent, and in Belgium 19 percent. Carney and Child (2013) documented a significant increase in the political connections of East Asian firms over the last two decades. As stated by Morck, Wolfenzon, and Yeung (2005), in most developed economies, there are explicit or tacit agreements between political and business agents, leading to the so-called “entrenched economy”. These political connections provide firms with a number of advantages such as access to privileged funds, granting of subsidies, sales of products and services to public authorities, a knowledge of bureaucratic procedures in the industry, tax advantages, less regulatory control, and the ability to network or lobby with current policymakers (Agrawal & Knoeber, 2001; Faccio, 2006; Goldman, Rocholl, & So, 2009; Unsal, 2019). This worldwide existence of corporate political connections runs parallel to the interest shown by investors, analysts, the media and scholars in dividend policies motivated by the growing relevance of dividends in shareholder wealth (Janus Henderson Global Investors, 2018). The picture to emerge from the Global Dividend Index is that firms the world over– not only those in certain nations and regions – are increasingly recognizing the need to provide investors with dividends. In the period 2009–2017, global dividends paid by the 1200 largest firms rose from US dollars 717 billion to 1.252 trillion, i.e., the amount of dividends paid by large firms the world over grew by 75%. In such a context, analysing payout policy in politically connected firms may prove interesting since political ties have often been felt to affect financial decisions, albeit in an unclear direction. Political ties might increase cash dividends given the higher rents, ⁎

Corresponding author. E-mail addresses: [email protected] (F.J. López-Iturriaga), [email protected] (D.J. Santana Martín).

https://doi.org/10.1016/j.najef.2019.101025 Received 27 February 2019; Received in revised form 12 May 2019; Accepted 11 July 2019 Available online 13 July 2019 1062-9408/ © 2019 Elsevier Inc. All rights reserved.

North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

lower risk of bankruptcy, the looser financial constraints and the greater public scrutiny of politically connected firms (Boubakri, Cosset, & Saffar, 2012; Chaney, Faccio, & Parsley, 2010). Nevertheless, politically connected firms might pay lower dividends since they could become isolated from market pressures, such that insiders might use political ties to increase the resources under their discretionary control and to extract personal benefit from external investors (Morck, Stangeland, & Yeung, 2000; Qian, Pan, & Yeung, 2011). Additionally, politically connected firms might manipulate financial statements and become more opaque in order to avoid disclosing political favours, especially when such favours border on the illegal (Ben-Nasr, Boubakri, & Cosset, 2012; Fan & Wong, 2002; Leuz & Oberholzer-Gee, 2006; Riahi-Belkaoui, 2004). Since opacity might lead to stock misevaluation and harm controlling shareholders’ interest and reputation, a link between political connections and share repurchases may arise. However, by increasing public scrutiny of connected firms, political ties might reduce the adverse selection problems and insider incentives to take advantage of misevaluation by repurchasing shares (Brennan & Thakor, 1990; Grinstein & Michaely, 2005; Jeon, Lee, & Moffett, 2011). In sum, the relationship between political connections and payout policy remains unclear, particularly in certain institutional environments that offer weak legal protection for investors, where political ties may affect the interplay between dominant owners and minority shareholders. To address this research question, we use a sample of politically connected and nonconnected Spanish listed firms over the period 2003–2016. Spain offers a paradigmatic setting to evaluate the impact of political connections on payout policy for several reasons. Political connections are quite common in Spanish listed firms. As in the continental European context, the government plays an active role in company performance and financing. Moreover, Spanish firms have a highly concentrated ownership structure with dominant owners playing an active role in the firm (Miguel, Pindado, & Torre, 2004; Ruiz-Mallorquí & Santana-Martín, 2011). In this context in which the board of directors is dominated by internal or external directors related to the controlling shareholders, the capital market is relatively illiquid and has a weak disciplinary role (Acero Fraile & Alcalde Fradejas, 2012; Cuervo García, 2002). Consequently, the relevant agency conflict in the Spanish context might be between minority shareholders and dominant owner (Arosa, Iturralde, & Maseda, 2010; García-Meca & Sánchez-Ballesta, 2011). As regards payout policy, Spanish firms are characterized by a stable cash dividend distribution and an increase in repurchases. In fact, the dividend yield of Spanish listed firms is higher than their European or US counterparts (García Coto & Garrido Domingo, 2019). Among the main regulatory changes in Spanish markets, prominent are the enforcement of the European MiFID (Markets in Financial Instruments Directive) and the issuance of two new codes of good governance (in 2006 and 2015) aimed at strengthening the functioning of financial markets and the defence of investors’ interests. In this context, our hypothesis is that political ties might affect dominant owner incentives to contrive dividend policy. Our results show that political connections increase cash dividend payouts, which might be seen as having a positive effect on shareholder wealth. This result is consistent with the view of politically connected firms coming under greater supervision. This scrutiny might mean closer attention being paid to the interests of minority shareholders, given the relevance of trust, reputation and the long-term stability of shareholdings in politically connected firms. This result is also consistent with the view of politically connected firms being subject to fewer financial constraints. We also find that political connections increase share repurchases. This result can be explained based on the poorer valuation of connected firms due to accounting opacity. In these cases, dominant owners may be interested in correcting and signalling misevaluation through share repurchases. Our study contributes to the literature that explores the effect of political ties on corporate finance by providing evidence concerning the link between political ties and dividend policy in a developed country, Spain, which has a non-planned economic system where ownership concentration is prevalent. To the best of our knowledge, only Su, Fung, Huang, and Shen (2014) and Jebaraj Benjamin, Mat Zain, and Abdul Wahab (2016) have thus far explored the link between corporate payout policy and political connections, in China and Malaysia, respectively. Nevertheless, their results are difficult to extrapolate to continental Europe because in East Asia the principal channels of political connection involve a large and stable stake in company capital. Additionally, political connections in the East Asian context may be explained by government interest in using firms for public-policy objectives (Adhikari, Derashid, & Zhang, 2006; Megginson & Netter, 2001; Wu, Wu, & Rui, 2012). However, in the continental European framework, the presence of politically connected directors on the board is the natural form of political connection. We also contribute to the literature by providing an analysis of dividend policy in a weak legal protection and dominant owner context, where the relationship between corporate governance and dividends is unclear. Some of our findings are consistent with the outcome hypothesis that stipulates a positive effect of effective governance on dividends (Adjaoud & Ben-Amar, 2010; Fairchild, Guney, & Thanatawee, 2014; La Porta, López de Silanes, Shleifer, & Vishny, 2000; Mancinelli & Ozkan, 2006; Shao, Kwok, & Guedhami, 2013). Nevertheless, the substitute hypothesis, which considers that dividends replace other corporate governance mechanisms in mitigating agency conflicts, may explain why insiders use dividends as a commitment to build reputation in the capital market, and may shed some light on our results (John, Knyazeva, & Knyazeva, 2015; Kuo, 2017; Lepetit, Meslier, Strobel, & Wardhana, 2018; Pindado, Requejo, & Torre, 2012; Setia Atmaja, Tanewski, & Skully, 2009). Although not an explicit contribution, we analyse payout policy comprehensively since we not only focus on cash dividends but also take account of share repurchases. This approach is consistent with the increasing importance of repurchases as a form of shareholder compensation worldwide. The rest of this paper is organized as follows. Section 2 presents the theoretical arguments and develops testable hypotheses. Section 3 describes our sample, the data, and the empirical method. Section 4 presents our empirical tests and results. Section 5 concludes.

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North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

2. Theoretical background Recent explanations of dividend policy based on the agency theory have grown at a rapid pace because dividends can reduce the conflict between managers and minority shareholders (Baker, 2009; Jensen, 1986; Pathak & Ranajee, 2019; Smith, Pennathur, & Marciniak, 2017). However, unlike in the Anglo-American context, which is characterised by the extensive presence of wide-ranging ownership and the effective legal protection of minority shareholders, the most prevalent agency conflict in continental European countries is that between dominant owners and minority shareholders, added to which the legal system offers less external investor protection (Djankov, La Porta, Lopez-de-Silanes, & Shleifer, 2008; Faccio & Lang, 2002; La Porta, Lopez-de-Silanes, & Shleifer, 1999; La Porta, López de Silanes, Shleifer, & Vishny, 1998). These institutional differences may have diverse implications on corporate payout policy. Dividend policy may thus involve unclear drivers that are conditional on the ownership concentration context (Goyal & Muckley, 2013; La Porta et al., 2000). On the one hand, in weak shareholder protection countries, dominant owners might have incentives to extract private control benefits by reducing dividends and increasing the funds under their control (Adjaoud & Ben-Amar, 2010; Alzahrani & Lasfer, 2012; Shao et al., 2013). On the other hand, dividend policy, as a convergence mechanism, may make up for the scant legal protection since the personal ties among dominant shareholders can improve a firm’s reputation and alleviate minority shareholder concerns (Farinha, 2003; John et al., 2015; Kuo, 2017; Pindado et al., 2012; Stafsudd, 2009). Consequently, political connections may shed new light, since the advantages they afford can be exploited to favour either all shareholders or a core of controlling owners (Su, Fung, & Yau, 2013). Among the most often cited advantages of the connections between politicians and business, mention can be made of access to privileged funds, granting of subsidies, sales of products and services to public authorities, a know-how of administrative procedures and the connections required to benefit from new regulations or contracts with public administration, and tax advantages (Agrawal & Knoeber, 2001; Fisman, 2001; Tang, Lin, Peng, Du, & Chan, 2016; Zhang, Liu, Xie, & Ye, 2017). Politically connected firms are more leveraged and borrow more money from financial institutions, implying they have softer budget constraints (Bliss & Gul, 2012; Boubakri, Guedhami, Mishra, & Saffar, 2012; Faccio, 2010; Yang, Lu, & Luo, 2014). The smaller number of financial constraints imposed on politically connected firms has repeatedly been confirmed in the literature (Cull, Li, Sun, & Xu, 2015; Chan, Dang, & Yan, 2012). Accordingly, firms with political ties rely less on internal cash flows to fund investment, which might mean more internal funds available for alternative uses such as dividends or share repurchases. This view has been confirmed by Bradford, Chen, and Zhu (2013), who show that politically connected firms received more subsidies. Additionally, Wang (2015) finds that Chinese firms benefit from having politicians by gaining access to external debt financing and more government subsidies. In this line, Faccio, Masulis, and McConnell (2006) show that politically connected firms are far more likely to be bailed out than similar non-connected firms, and Khwaja and Mian (2005) find that connected firms borrow much more from government banks. These circumstances enable politically connected firms to enjoy a lower cost of equity capital than their non-connected peers, as shown by Boubakri, Cosset, et al. (2012), and Duchin and Sosyura (2012). In turn, easier and cheaper external funds are likely to result in less incentives to retain benefits, such that politically connected firms can use internal cash flows to pay more dividends (Chae, Kim, & Lee, 2009). From a complementary perspective, political ties can increase public scrutiny of connected firms. Chaney et al. (2010) show that politically connected firms come under the microscope of analysts and mass media to a greater extent. This stricter supervision can mean more attention being focused on minority shareholder interests, given the relevance of trust, reputation and the long-term stability of dominant owners in a weak legal protection context (Bona-Sánchez, Pérez-Alemán, & Santana-Martín, 2019). Under such circumstances, dividend policy may be a dominant owner mechanism to build reputation. In fact, prior studies show that dominant owners use dividends to alleviate agency conflicts with external investors market (Farinha, 2003; John et al., 2015; Kuo, 2017; Pindado et al., 2012; Setia Atmaja et al., 2009). However, the financial advantages related to political connections may lead to less dependence on capital markets and, to some extent, therefore isolate connected firms from the watchful eye of such markets. Consistent with this fact, Qian et al. (2011) document that controlling shareholder expropriation behaviour through tunnelling or self-dealing is greater in politically connected firms. These results are due to less concern for capital market punishment and more secure bank loan access and public funds. Thus, lower capital market discipline on dominant owners weakens the effectiveness of corporate governance and enables wealth expropriation. Consequently, political ties might be associated with a lower payout level. Jebaraj Benjamin et al. (2016) suggest another factor that can reduce dividends in politically connected firms. When competing for the support of politicians, these firms can choose to offer money or campaign donations in exchange, which reduces funds available to investors. Di Giuli and Kostovetsky (2014) propose another channel through which political affiliation may harm shareholder wealth. They find that firms with politically linked founders, CEOs, and directors spend more on CSR than their counterparts. Interestingly, any benefits to stakeholders from social responsibility come at the direct expense of current shareholders. Political connections may also be related to share repurchases in two ways. Politically connected firms are more opaque and disclose limited information in order to protect themselves from public scrutiny and prevent the leakage of competitive advantages to competitors (Ben-Nasr et al., 2012; Chaney et al., 2010; Riahi-Belkaoui, 2004). Thus, both dominant shareholders and politicians alike might be interested in constraining transparency so as to avoid disclosing political favours, especially when these favours border on the illegal (Leuz & Oberholzer-Gee, 2006). Consequently, such opacity might lead to stock misevaluation and damage the interest and reputation of controlling shareholders. Given their high stake in capital, controlling shareholders could have an incentive to correct misevaluation through share repurchase. Nevertheless, at the same time, by increasing public scrutiny of politically connected firms, political ties might reduce adverse selection problems (Barclay & Smith, 1988; Brennan & Thakor, 1990; Grinstein & Michaely, 3

North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

2005; Jeon et al., 2011). Given the less asymmetric information available on these firms, the market value of the firm is less likely to be under-priced, such that insiders have fewer incentives to repurchase shares. In line with the above arguments, the interactions between political ties and dividend policy is an empirical question. Thus, we test the following hypotheses: H1: The presence of political connections affects dividend policy H1a: The presence of political connections has a positive effect on dividend policy H1b: The presence of political connections has a negative effect on dividend policy 3. Research design 3.1. Sample, variables and models The initial sample comprises 123 non-financial listed Spanish firms between 2003 and 2016. Given the small size of Spanish capital markets, our sample accounts for over 98 percent of the capitalization of non-financial firms and for over 98 percent of market trading. We thus obtain a panel of 1358 firm-year observations, with firms averaging 11.05 observations over the 2003–2016 period. Variables were winsorized at the 1st and 99th percentiles to reduce the impact of potential outliers, except for the dummy variables. Our sample begins in 2003, when a law was passed aimed at enhancing the transparency of financial reporting. This law means Spanish listed firms having to issue an annual corporate governance report in which directors’ political connections are detailed. Research into the relationship between political connections and corporate behaviour must cope with the limited transparency inherent in such links. Our dataset comes from Bona-Sánchez et al. (2019), who follow earlier literature and consider the presence of politicians on the firm’s board of directors as a proxy of political connections (Boubakri, Guedhami, et al., 2012; Chaney et al., 2010; Chen, Li, Su, & Sun, 2011; Duchin & Sosyura, 2012; Faccio, 2006; Goldman et al., 2009). We then define political ties (CONNECTED) as members of the board of directors who have held a past political position at either the European, national, regional, or local level. Payout policy has traditionally been measured through the amount of dividends paid to shareholders. However, over the last few years share repurchases have become a common way of distributing cash among shareholders (Chen, Harper, & Iyer, 2018; Chen, Chen, & Liu, 2019; Eije & Megginson, 2008). We control for this tendency and operationalize dividend policy using several alternative dependent variables. We mainly define dividend policy as the percentage of net profit that firms pay to their shareholders at the end of each year. Given the two basic ways of rewarding shareholders, we use dividends, repurchases and total payout, i.e. dividends plus repurchases, scaled by total assets. There are several reasons to use total assets as the denominator. First, it increases the comparability of our results with earlier literature, most of which uses the same measure. Second, assets are less volatile than other metrics such as net income or market measures. Moreover, net income may be strongly influenced by accounting choices, and the problem of influential observations may arise when earnings approach zero (Fama & French, 2002). We control for some common characteristics of dividend policy recognised by earlier research (Abreu & Gulamhussen, 2013; Fama & French, 2001): size, profitability, financial leverage, firm age, and growth opportunities. As do Jeon et al. (2011) and Faccio (2010), we include the firm’s cash holding and market capitalization. Consistent with previous studies (Gugler & Yurtoglu, 2003; La Porta et al., 2000; Pindado et al., 2012), we include the voting rights in the hands of the ultimate or dominant owner. We also include a set of dummy variables to control for industry (ρi) and year effects (μt). Descriptions of all the variables are provided in the Appendix. 3.2. Method We use the Generalized Method of Moments (GMM) to test our hypotheses (Arellano & Bover, 1995; Blundell & Bond, 1998). The GMM procedure, based on the panel data methodology, allows us to address unobserved constant heterogeneity, potential endogeneity1 concerns, and reverse causality (Pindado, Requejo, & de la Torre, 2014). The general models, where we include εit an error term, can be expressed as follows:

DIVTAit =

1

+

1 CONNECTEDit

AGEit + REPTAit =

1

+

i

1

+

i

+ µt +

2 VOTINGit

3 MK .

SHAREit +

4

SIZEit +

5 CASHit

+

6

ROAit +

7 MTBit

+

8 LEVit

+

+

2 VOTINGit

+

3 MK .

SHAREit +

4

SIZEit +

5 CASHit

+

6

ROAit +

7 MTBit

+

8 LEVit

+

9

(2)

it

9 AGEit

9

(1)

1 CONNECTEDit

LEVit +

+

it

1 CONNECTEDit

AGEit +

DIVREPTAit =

+ µt +

+

+

i

+

2 VOTINGit

+ µt +

+

3 MK .

SHAREit +

4

SIZEit +

5 CASHit

+

6

ROAit +

7 MTBit

+

8

(3)

it

In order to control for differences in characteristics between connected and non-connected firms and to mitigate potential 1 In line with Wooldridge (2010), we broadly define endogeneity bias as any situation where the disturbance term of the structural equation is correlated with one or more independent variables.

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F.J. López-Iturriaga and D.J. Santana Martín

Table 1 Descriptive and univariate analysis. Panel A. Descriptive statistics Connected

Divtaa Reptaa Divreptaa Voting MK.Share Size Cash ROA MTB Lev Age

2003 50.60

2004 51.19

2005 51.69

2006 50.52

2007 51.38

2008 51.38

2009 51.89

2010 54.37

2011 53.00

2012 52.58

2013 51.61

2014 52.75

2015 38.78

Mean

Median

Std. Dev

1stQ

3rdQ

4thQ

2.186 0.800 2.524 31.287 0.100 13.858 0.063 0.050 2.437 0.631 48.759

1.689 0.373 1.706 25.088 0.043 13.632 0.044 0.057 1.716 0.641 43.000

1.762 0.930 2.530 19.450 0.122 1.846 0.061 0.071 2.231 0.193 28.670

0.777 0.089 0.653 14.919 0.009 12.385 0.016 0.021 0.977 0.500 26.000

2.947 1.180 3.416 49.560 0.153 15.110 0.086 0.090 3.000 0.770 70.000

6.175 2.867 9.082 69.753 0.427 17.454 0.224 0.186 8.886 0.973 115.000

2016 39.39

Panel B. Correlation matrix

Repta Divrepta Connected Voting MK.Share Size Cash ROA MTB Lev Age

Divta

Repta

Divrepta

Connected

0.122*** 0.839*** 0.079** −0.008 0.306*** 0.101*** 0.1586*** 0.551*** 0.382*** −0.288*** 0.007

0.547*** 0.085*** −0.076** 0.146*** 0.073** 0.030 0.107*** 0.1642*** −0.029 0.014

0.066** −0.004 0.305*** 0.078** 0.166*** 0.481*** 0.411*** −0.246*** −0.004

−0.030 0.270*** 0.401*** 0.112*** 0.082*** 0.055** 0.071** 0.102***

Voting

MK.Share

−0.044 0.064** 0.107*** 0.020 0.083*** 0.071** −0.060**

0.625*** 0.130*** 0.308*** 0.249*** 0.031 0.179***

Size

0.029 0.158*** 0.001 0.284*** 0.233***

Cash

0.148*** 0.219*** 0.017 −0.055

ROA

0.306*** −0.326*** 0.024

MTB

0.072** −0.036

Lev

VIF

0.168*** Mean VIF

1.22 1.05 2.02 2.31 1.09 1.43 1.32 1.43 1.09 1.44

Panel C. Connected firms versus non-connected firms Connected firms (N = 680)

Divta Repta Divrepta Voting MK.Share Size Cash ROA MTB Lev Age

Non-connected firms (N = 678)

Mean

Median

Std. Dev

Mean

Median

Std. Dev

T-test

Wilcoxon Test

1.456 0.477 2.110 30.698 0.133 14.598 0.070 0.056 2.562 0.645 3.729

0.872 0.011 1.380 24.818 0.089 14.677 0.052 0.061 1.835 0.661 3.806

1.764 0.825 2.383 19.177 0.130 1.812 0.064 0.068 2.223 0.184 0.732

1.180 0.344 1.782 31.869 0.067 13.116 0.056 0.045 2.314 0.617 3.588

0.361 0.000 0.678 25.358 0.021 12.981 0.036 0.050 1.563 0.606 3.688

1.738 0.720 2.530 19.777 0.102 1.561 0.058 0.072 2.237 0.201 0.780

2.927*** 3.171*** 2.459*** −1.106 10.363*** 16.146*** 4.150*** 3.050*** 2.050** 2.640*** 3.440***

4.685*** 2.934*** 4.910*** −1.135 11.754*** 14.628*** 4.299*** 3.006*** 3.386*** 2.840*** 3.569***

*,**,***

: Statistically significant at 1, 5 and 10 percent, respectively. aPercentages calculated on firms with dividends and repurchases.

selection bias, we run a matching procedure (Boubakri, Guedhami, et al., 2012; Faccio et al., 2006). For each politically connected firm, we choose a matching non-connected firm in our sample. The candidate firm must meet two conditions. First, it must be from the same industry and year as the connected firm, Second, it must be the optimal match based on the nearest neighbour procedure employing a propensity score matching technique (Heckman, Ichimura, & Todd, 1998; Heckman, Ichimura, & Todd, 1997; Rosenbaum & Rubin, 1983). We use cross-listing, firms’ market-to-book ratio, leverage, size and age to calculate the propensity score. Using this procedure, we find a control sample of non-connected firms that show no observable differences relative to connected firms. Consequently, each pair of matched firms is essentially similar to each other except for the political tie. We thus obtain a matched sample of 782 firm-year observations equally distributed by year and industry between connected and non-connected firms.

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F.J. López-Iturriaga and D.J. Santana Martín

4. Results 4.1. Descriptive analysis Table 1 (Panel A) reports the percentage of Spanish companies with former politicians on their boards. The table shows that around half of the listed companies have at least one director who held a political position between 2003 and 2014. However, the presence of connected firms fell to around 40% in 2015–2016. This decline may be a result of the end of the two-party system, with the emergence of new political parties in Spanish politics. In this new situation, firms face greater difficulty when choosing which politicians might bring more advantages to the firm. In any case, these data highlight the important role played by political connections in this context of weak legal protection. These figures are significantly higher than those provided by Faccio (2006), for a number of reasons. First, our measure of political connections differs because, rather than focusing on large shareholders who are at the same time ministers or members of parliament, we identify directors who have been politicians at the local, regional, national or European level.2 Faccio (2006) focused on presidents, vice-presidents, CEOs and secretaries who had been former politicians. Our measure of political connections is broader since, consistent with Bona-Sánchez, Pérez-Alemán, and Santana-Martín (2014) and Guerra Pérez, Bona Sánchez, and Santana Martín (2015), we consider all directors. Moreover, Faccio (2006) drew on information from 2001, when the level of transparency in the Spanish market was limited. Spanish listed firms are now required to provide more details concerning the composition of the board and their directors’ background, such that we are better placed to identify political connections. Panel B of Table 1 reports the correlations among the variables and suggests that multicollinearity does not affect subsequent regressions. However, we conduct a formal test to ensure that multicollinearity is not present in our regressions. In particular, we analyse the Variance Inflation Factor (VIF) for each independent variable included in the estimated model.3 Panel C of Table 1 reports the tests of the mean and median differences between connected and non-connected firms. The means comparisons show that connected and non-connected firms differ in terms of dividend policy, with higher values for politically connected firms. Both types of companies evidence no significant difference in terms of voting rights of the dominant owner. Nevertheless, the tests show that politically connected firms have greater means and median market capitalization, size, cash holding, profitability, growth opportunities, leverage and age. Table 2 provides a comparison of payout policy between the matched samples. As shown, connected firms display larger payout ratios than non-connected firms (both for cash dividends and repurchases) even though matched firms are virtually identical in terms of the other observable variables. This result suggests that the above differences are not due to observable differences in firm characteristics but are related to political ties. 4.2. Baseline results Table 3 presents the baseline results of the effect of political connections on payout policy, both for full sample (Models 1–3) and for the matched sample (Models 4–6). In particular, estimates show a positive and statistically significant effect of political connections on payout ratios. These results are consistent with H1a, which posits that political connections are positively associated with payout policy. Therefore, political ties increase the incentives for cash dividends since political connections provide access to financial resources and decrease bankruptcy risk. In addition, politically connected firms are more closely followed by analysts and mass media, increasing the concern on the minority shareholders’ rights. Results also show that political connections positively affect share repurchases and the addition of repurchases and dividends (Models 2, 3, 5, and 6). This set of results can be explained based on the poorer valuation of these firms, such that managers and dominant owners may have an incentive to draw attention to market misevaluation by repurchasing shares. As for the control variables, the results in Table 3 show a positive effect of the dominant owner’s voting rights on payout policy. This result supports the use of dividends to alleviate expropriation concerns of minority shareholders by dominant owners (Pindado et al., 2012). Market share positively affects dividend policy as shown by Denis and Osobov (2008) and Fatemi and Bildik (2012) in the international arena. In contrast, the firm’s financial leverage and growth opportunities are negatively and significantly related to payout. This latter finding is consistent with the view that dividends act as corporate control mechanisms and compete with capital expenditures in the allocation of company funds (Brav, Graham, Harvey, & Michaely, 2005). Our results also suggest that return on assets, size, cash holding and the age of the firm have a positive impact on dividend policy (Denis & Osobov, 2008; Ferris, Jayaraman, & Sabherwal, 2009). These results are also consistent with the signalling and life-cycle theory of dividends (Khanal & Mishra, 2017; Tao, Nan, & Li, 2016). Table 3 also reports a set of specification tests. According to the m2 test, no second-order serial correlation in the error exists, and the Hansen test of over identifying restrictions supports the validity of the instrumental variables. According to the Z1 test, our independent variables are significant explanatory factors of dividend policy. The significance of the Z2 and Z3 tests corroborates the need to control for time and industry fixed effects.

2 In accordance with Spanish law, a politician may not hold a political position and be a member of a company’s board of directors at the same time. 3 The highest VIF for our models is well below five. Multicollinearity is not, therefore, a problem in our sample (Studenmund, 1997).

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North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

Table 2 Propensity score matching estimators. Connected (mean)

Non-connected (mean)

t-test

Divat Repat Divrepat Voting MK.Share Size Cash ROA MTB Lev Age

1.441 0.474 2.170 30.726 0.764 13.781 0.069 0.052 2.766 0.622 45.537

1.047 0.369 1.644 30.987 0.639 13.499 0.062 0.049 2.699 0.610 44.841

3.151*** 1.824* 2.910*** −1.16 1.62 1.33 0.98 1.47 1.61 0.86 0.33

No. of observations

391

391

*,**,***

Statistically significant at 1, 5 and 10 percent, respectively. The propensity score is estimated within an industry-year category using available firm-level observable variables.

Table 3 Political connections and payout policy. Full sample

Matched sample

Divat (1)

Repat (2)

Divrepat (3)

Divat (4)

Repat (5)

Divrepat (6)

Connected Voting MK.Share Size Cash ROA MTB Lev Age Industry Year Intercept

0.300*** (3.15) 0.005*** (2.62) 2.926*** (3.43) 0.164*** (4.82) 1.644* (1.66) 7.450*** (10.49) −0.040*** (−3.42) −2.094*** (−7.78) −0.005 (−1.35) Yes Yes −0.375 (−0.76)

0.099** (2.41) 0.003*** (2.77) 0.889* (1.88) 0.004 (0.12) −0.031 (−0.50) 1.009*** (3.15) 0.001 (0.21) −0.624*** (−3.92) 0.005*** (2.65) Yes Yes 0.740* (1.93)

0.662*** (3.67) 0.010* (1.74) 3.166* (1.71) 0.031 (0.34) 2.776** (2.39) 8.170*** (7.47) −0.169*** (−5.11) −4.841*** (−9.46) 0.006 (0.10) Yes Yes 4.627*** (4.31)

0.269** (1.98) 0.008** (2.08) 5.281*** (3.50) 0.064 (0.78) 1.008 (0.70) 2.700*** (3.97) −0.053** (−2.30) −1.115*** (−3.10) 0.028 (0.90) Yes Yes 1.212 (1.00)

0.451*** (4.16) 0.004* (1.66) 1.774*** (2.76) 0.060 (1.56) 1.284*** (3.27) 1.594*** (3.36) 0.007 (0.73) −1.234*** (−5.54) 0.111* (1.94) Yes Yes −1.178 (−1.26)

0.875*** (3.40) 0.019** (2.28) 5.259* (1.86) 0.123 (0.60) 0.300 (0.19) 2.050 (1.26) −0.090** (−2.05) −2.414*** (−3.88) 0.355* (1.85) Yes Yes −0.854 (−0.29)

m2 Z1 Z2 Z3 Hansen test No. of observations

−1.14 50.89*** 5.13*** 17.83*** 89.35 (145) 1358

−1.20 14.57*** 9.97*** 42.48*** 91.12 (168) 1358

−1.12 21.99*** 2.45** 24.15*** 75.11 (203) 1358

−1.38 15.18*** 7.39*** 10.97*** 40.16 (150) 782

−1.04 13.86*** 13.06*** 22.27*** 43.89 (109) 782

−1.07 8.59*** 5.65*** 42.14*** 53.32 (150) 782

Hansen, test of over-identifying restrictions, under the null hypothesis that all instruments are uncorrelated with the disturbance process. m2, statistic test for lack of second-order serial correlation in the first-difference residual. z1, Wald test of the joint significance of the reported coefficients. z2, Wald test of the joint significance of time dummies. z3, Wald test of the joint significance of industry dummies. *,**,***: Statistically significant at 1, 5 and 10 percent, respectively. In parentheses, t-statistics based on robust standard errors

4.3. Sensitivity and additional analyses In this section, we run several additional analyses to check the robustness of our results. Although the GMM and the matching procedure moderate concerns about the possible endogeneity of political ties, we approach this issue using the instrumental variable method. We also examine whether the recent financial crisis has altered the role of political connections. Finally, we use alternative metrics of payout policy and political ties. As explained before, the GMM and the propensity score matching procedure mitigate but do not completely eliminate the endogeneity issue. We therefore use the instrumental variable approach. Specifically, we use economic uncertainty as an instrument for political ties since the level of economic uncertainty is likely to affect the incentives to establish political connections (Wellman, 2017). In turn, the first-stage regression is a binary model (specifically, a probit model) that predicts political ties using UNCERTAINTY. This variable is obtained from the Economic Policy Uncertainty Index constructed by Baker, Bloom, and Davis (2016)4. In the second step, the fitted values of political ties derived from the first stage are included in the second-stage OLS regression. Table 4 shows the results for both the full sample and the matched sample. The first-stage (Models 7 and 11) suggests that economic policy uncertainty is a good predictor of political connections and increases the likelihood of such ties, as reported by Wellman (2017). The 4

Available at: http://www.policyuncertainty.com. 7

8

1358

0.232 438.20***

−0.004** (−2.24) 0.360 (0.67) 0.262*** (6.11) 2.903*** (4.13) −0.865 (−1.32) −0.053** (−2.46) −0.486* (−1.88) 0.031 (0.57) 0.347*** (2.71) Yes Yes −66.317*** (−2.88)

84.8 1358

***

6.75 1358

***

0.07

Yes Yes 0.015 (0.50)

Yes Yes 3.713*** (4.21) 0.404

1.367** (2.33) −0.001 (−0.92) 1.632 (1.57) 0.006 (0.28) 2.374*** (2.71) 0.156 (0.43) −0.067*** (−4.12) −0.371** (−2.45) 0.001* (1.64)

1.002*** (3.61) 0.003 (1.33) 1.555*** (3.63) 0.296*** (3.09) 1.991* (1.95) 9.848*** (14.98) −0.179*** (−8.96) −1.193*** (−4.20) −0.004 (−0.33)

68.89 1358

0.355 ***

Yes Yes 4.871*** (3.75)

1.171*** (2.59) 0.003 (1.06) 3.214*** (5.09) 0.376*** (2.65) 1.740 (1.16) 10.934*** (11.27) −0.298*** (−10.09) −1.750*** (−4.18) −0.009 (−0.48)

782

0.139 151.49***

−0.010*** (−3.87) 0.023 (0.30) 0.372*** (6.39) 3.178*** (3.45) 0.091 (0.12) −0.103*** (−3.71) −0.240 (−0.75) 0.005 (0.10) 0.330** (1.96) Yes Yes −63.970** (−2.10)

28.64 782

***

0.414

Yes Yes 3.366*** (2.99)

1.818** (1.97) 0.006 (1.52) 2.461*** (3.23) 0.307** (2.41) 0.577 (0.43) 9.718*** (12.67) −0.080** (−2.14) −1.232*** (−3.83) 0.063 (0.89)

Divat (12)

4.34 782

***

0.120

Yes Yes 3.802*** (3.25)

1.258*** (3.21) 0.009** (2.31) 2.075*** (2.07) 0.465*** (3.44) 3.213*** (2.68) 0.121 (0.28) −0.089** (−2.31) 0.038 (0.20) 0.097** (2.42)

Repat (13)

22.32*** 782

0.353

*,**,***

Yes Yes −0.169 (−0.14)

1.060*** (2.90) 0.027*** (2.72) 7.645* (1.73) 0.191** (2.21) 4.682 (1.47) 8.392*** (6.55) −3.945*** (−3.77) −3.945*** (−4.69) 0.089 (0.79)

Divrepat (14)

Models 7 and 11 predict Connected by using Uncertainty as an instrument with controls and fixed effects. Models 8, 9, 10, 12, 13 and 14 of payout policy on the fitted values of Connected. Statistically significant at 1, 5 and 10 percent, respectively. In parentheses each coefficient is the robust t-statistics clustered at the country-year level.

Adj. R2 Likelihood ratio χ2 F test No. of observations

Connected Voting MK.Share Size Cash ROA MTB Lev Age Uncertainty Industry Year Intercept

Divrepat (10)

1st stage (11)

Repat (9)

1st stage (7)

Divat (8)

Matched sample

Full sample

Table 4 Political ties and payout policy. Instrumental variable approach.

:

F.J. López-Iturriaga and D.J. Santana Martín

North American Journal of Economics and Finance 50 (2019) 101025

North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

Table 5 Politically connected firms, payout policy and financial crisis. Before financial crisis: 2003–2007

After financial crisis: 2008–2016

Divat (15)

Repat (16)

Divrepat (17)

Divat (18)

Repat (19)

Divrepat (20)

Connected Voting MK.Share Size Cash ROA MTB Lev Age Industry Year Intercept

0.488** (2.49) 0.024*** (4.51) 4.439*** (3.14) 0.238** (2.36) 1.801* (1.97) 0.593 (0.87) −0.003 (−0.20) −0.506 (−1.00) 0.003 (0.70) Yes Yes 3.284** (2.49)

0.341*** (4.63) 0.007*** (2.76) 2.541*** (3.63) 0.109 (1.55) 1.852*** (3.27) 0.943** (2.17) −0.0291* (−1.73) −0.532* (−1.74) −0.007 (−0.23) Yes Yes 2.371*** (3.06)

0.996*** (4.83) 0.050*** (7.11) 12.435*** (7.41) 0.324*** (2.05) 10.177*** (6.32) 1.918 (1.19) −0.047 (−1.21) −4.185*** (−6.61) 0.016** (2.19) Yes Yes 5.696*** (3.08)

0.192*** (2.79) 0.005*** (2.70) 4.244*** (5.58) 0.023 (0.52) 0.681 (0.78) 6.168*** (11.53) −0.028* (−1.79) −2.423*** (−11.76) 0.003 (1.10) Yes Yes 2.048*** (4.65)

0.117*** (3.45) 0.001 (1.40) 1.944*** (6.60) 0.023 (1.55) 1.521*** (2.81) 1.060*** (5.67) 0.002 (0.47) −0.380*** (−4.47) 0.002** (2.10) Yes Yes 0.815*** (4.87)

0.378** (2.52) 0.011** (2.58) 5.613*** (3.79) 0.058 (0.68) 2.906*** (2.99) 8.852*** (9.03) −0.136*** (−5.19) −4.206*** (−9.95) 0.012** (2.27) Yes Yes 3.979*** (4.41)

m2 Z1 Z2 Z3 Hansen test No. of observations

−0.25 6.17*** 9.22*** 3.43*** 50.27 (55) 677

−0.42 10.62*** 24.47*** 34.11*** 69.51 (69) 677

−1.30 32.49*** 13.04*** 38.24*** 69.89 (69) 677

−1.11 98.02*** 7.38*** 32.36*** 87.02 (190) 681

−1.21 41.07*** 42.41*** 30.40*** 88.43 (169) 681

−1.47 27.75*** 4.99*** 55.40*** 84.65 (190) 681

Hansen, test of over-identifying restrictions, under the null hypothesis that all instruments are uncorrelated with the disturbance process. m2, statistic test for lack of second-order serial correlation in the first-difference residual. z1, Wald test of the joint significance of the reported coefficients. z2, Wald test of the joint significance of time dummies. z3, Wald test of the joint significance of industry dummies. *,**,***: Statistically significant at 1, 5 and 10 percent, respectively. In parentheses, t-statistics based on robust standard errors.

estimates for models 8, 9, 10, 12, 13 and 14 support the previous results and show a positive and statistically significant relation between political connections and company payout. One emerging issue in recent research into payout policy is concern regarding the impact of macroeconomic conditions. The recent financial crisis has resulted in a regulatory shift that has placed dividends under close scrutiny, especially in financial firms (Abreu & Gulamhussen, 2013; Su et al., 2014). van Essen, Engelen, and Carney (2013) find empirical support for the idea that good governance prescriptions designed to ensure managerial oversight may not hold firm in a financial crisis. Similarly, Guerra Pérez et al. (2015) find a relation between the recent financial crisis and the influence of corporate control mechanisms. To address this issue, we split our time framework into two periods depending on when the financial crisis occurred in Spain: before the crisis (2003–2007) and during the crisis (2008–2016). The results for each scenario are reported in Table 5 (Models 15–20) and are fully consistent with previous results, thus providing further support for the notion that political connections positively affect payout policy. This effect holds true irrespective of the time period, such that the role of political connections is not affected by macroeconomic conditions (i.e., the financial crisis). We also check whether the results are sensitive to the measures of payout policy, political ties, and the agency risk of dominant shareholder. In Table 6, we report additional estimates when payout ratios are scaled by EBIT (Models 21–23), when we use a more restrictive definition of political connections -which only considers directors who held a high-level political position at the European or national level in the past- (Models 24–26), when we consider the percentage of politicians in the board of directors (Models 27–29), and when we use the deviation of voting-to-cash flow rights as a measure of the agency risk of dominant owner (Models 30–32). Results are basically unaffected and substantiate the impact of political connections on cash dividends and share repurchases. Finally, we check the consistency of our results with some additional analyses. Thus, we run some models to test whether the agency risk of dominant owner might play a role in the relation between political ties and payout policy. To do this, we interact the Connected variable with the Voting variable (Models 33–35, Table 7). Results show that political ties exacerbate the positive effect of voting rights in the hands of dominant owners. Furthermore, in Models 36–38 (Table 7), we test whether financial constraints affect the relation between political ties and payout policy. Our metric of financial constraints is based on firms’ liquidity as explained in the Appendix. As expected, the dummy of financial constraints has a negative relationship with dividend payout. Interestingly, the interaction between political connections and financial constraints is positive and significant. In turn, our results lend support to the idea that political connections loosen financial constraints, making it less necessary to stockpile liquidity and thus increasing dividend payout. 5. Conclusions Previous research on dividend policy has shown that dividend payout is heavily affected by agency conflicts, the institutional environment, and relations among shareholders. In the present paper, we focus on the effect of political connections, a company feature widely used in many countries. The impact of political ties poses a number of challenges, especially in contexts such as Spain, which offers little protection for minority shareholder rights and evidences a widespread presence of large dominant owners. 9

0.004 (0.56)

Voting

10

0.036*** (3.57) 0.169 (0.94)

0.020 (0.23)

−0.013*** (−3.31) −0.395*** (−7.02) 0.004*** (9.50) Yes Yes 0.071 (0.54)

−1.05 19.08*** 36.20*** 27.05*** 69.99 (122) 1038

Size

Cash

ROA

MTB

Industry Year Intercept

m2 Z1 Z2 Z3 Hansen test # observat.

−1.53 21.53*** 19.62*** 23.88*** 74.71 (180) 1038

0.450*** (3.65) 0.313*** (3.81) −0.019*** (−5.86) −0.100** (−2.26) 0.002*** (5.09) Yes Yes 0.243*** (2.62) −1.03 23.22*** 5.43*** 28.94*** 84.95 (177) 1038

−0.030*** (−5.49) −0.586*** (−6.15) 0.001*** (2.97) Yes Yes 0.144 (0.63)

0.898*** (3.66) 0.389* (1.98)

0.031 (1.52)

0.5000* (1.82)

0.100*** (3.04) 0.003 (0.38)

Divrepebita (23)

−1.29 51.20*** 10.30*** 13.93*** 83.01 (168) 1358

Yes Yes 2.095*** (3.59)

2.940*** (3.09) 5.640*** (5.88) −0.032** (−2.28) −2.130*** (−7.30) 0.003 (0.70)

2.780*** (3.27) 0.018 (0.37)

0.007*** (3.40) 0.188** (2.00)

Divat (24)

−1.54 12.58*** 11.87*** 31.12*** 70.09 (224) 1358

−0.015** (−2.06) −0.835*** (−4.10) 0.007*** (3.04) Yes Yes 0.974*** (2.65)

0.119 (0.29)

1.515** (2.49)

1.423*** (3.95) 0.033 (1.01)

0.007*** (3.48) 0.099** (2.04)

Repat (25)

−1.50 28.78*** 1.76* 29.73*** 76.65 (203) 1358

3.666*** (3.57) 8.700*** (6.57) −0.139*** (−4.07) −3.706*** (−6.84) 0.017*** (2.85) Yes Yes 2.781** (2.29)

0.183* (1.77)

3.852** (2.03)

0.609*** (2.96)

0.011* (1.78)

Divrepat (26)

−1.16 44.01*** 8.95*** 15.32*** 65.83 (68) 1358

−3.062*** (−10.43) 0.015*** (3.47) Yes Yes 3.807*** (6.69)

2.707*** (3.52) 0.215*** (4.41) 2.398*** (2.71) 5.442*** (7.33) 0.029 (1.36)

0.018*** (3.32)

0.008*** (3.76)

Divat (27)

−1.02 44.78*** 25.49*** 36.92*** 82.44 (144) 1358

−0.014** (−2.22) −0.568*** (−5.18) 0.005*** (2.86) Yes Yes 0.398 (1.21)

1.02*** (4.01)

0.751 (1.56)

1.450*** (3.21) 0.006 (0.21)

0.005** (2.40)

0.002* (1.66)

Repat (28)

−1.52 54.44*** 5.23*** 38.17*** 78.55 (174) 1358

Yes Yes 1.824* (1.73)

9.734*** (9.81) −0.153*** (−3.76) −4.229*** (−6.58) 0.017** (2.40)

0.216*** (2.65) 1.093 (0.81)

1.732 (1.00)

0.044*** (5.50)

0.015** (2.47)

Divrepat (29)

−1.54 31.23*** 31.28*** 32.20*** 76.97 (192) 1358

Yes Yes 1.392** (2.18)

7.568*** (10.83) −0.069*** (−4.74) −1.453*** (−3.89) 0.006 (0.14)

0.519 (0.51)

0.015 (0.31)

0.021*** (3.10) 2.340** (2.13)

0.286*** (2.76)

Divat (30)

−1.48 24.84*** 9.01*** 43.15*** 98.07 (133) 1358

0.088*** (3.95) 1.723*** (5.89) 0.703*** (3.93) −0.022*** (−3.73) −0.113 (−1.30) 0.007*** (4.96) Yes Yes 0.516* (1.98)

0.401 (1.23)

0.005** (2.24)

0.139*** (2.65)

Repat (31)

−1.14 30.07*** 19.04*** 24.92*** 86.23 (135) 1358

Yes Yes 0.122 (0.12)

−0.153*** (−7.58) −1.02*** (−3.04) 0.013*** (3.05)

1.63*** (3.21)

2.03** (2.02)

0.186** (2.25)

2.495*** (2.88)

0.033*** (4.61)

0.271* (1.68)

Divrepat (32)

Hansen, test of over-identifying restrictions, under the null hypothesis that all instruments are uncorrelated with the disturbance process. m2, statistic test for lack of second-order serial correlation in the first-difference residual. z1, Wald test of the joint significance of the reported coefficients. z2, Wald test of the joint significance of time dummies. z3, Wald test of the joint significance of industry dummies. a We have eliminated observations with negative Ebit. *,**,***: Statistically significant at 1, 5 and 10 percent, respectively. In parentheses, t-statistics based on robust standard errors.

Age

Lev

0.083 (0.75)

MK.Share

Voting_CF

Politicians

0.381*** (3.67) 0.004 (0.59)

0.099*** (3.46) 0.001*** (2.81)

0.049** (2.23)

Connected

High_ Connected

Repebita (22)

Divebita (21)

Table 6 Political connections and payout policy. Sensitivity analysis.

F.J. López-Iturriaga and D.J. Santana Martín

North American Journal of Economics and Finance 50 (2019) 101025

North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

Table 7 Political connections and payout policy. Further analysis. Divat (33)

Repat (34)

Divrepat (35)

Divat (36)

Repat (37)

Divrepat (38)

Connected Voting Connected × Voting Fin_Constraint Connected × Fin_Constraint MK.Share Size Cash ROA MTB Lev Age Industry Year Intercept

0.156** (2.43) 0.008*** (4.25) 0.002* (1.80)

0.078*** (4.42) 0.002** (2.22) 0.002*** (3.13)

0.234** (2.37) 0.005** (2.30) 0.011*** (5.25)

0.425*** (7.15)

0.204*** (3.51)

0.343* (1.84)

2.536*** (3.52) 0.047 (0.87) 0.0843 (0.80) 2.395*** (5.41) 0.003 (1.25) −0.681*** (−3.37) 0.003** (2.11) Yes Yes 1.347** (2.09)

0.836** (2.44) 0.032* (1.65) 0.442* (1.73) 0.946*** (5.16) −0.011** (−2.32) −0.125* (−1.90) 0.002* (1.67) Yes Yes 0.242 (1.16)

6.61** (7.33) 0.094 (1.21) 1.06 (0.72) 1.57*** (2.79) −0.112*** (−3.21) −1.12*** (−4.46) 0.003 (0.11) Yes Yes 3.28*** (4.09)

−0.486** (−2.20) 0.763** (2.19) 1.229*** (8.12) 0.944*** (7.69)

−0.272*** (−3.05) 0.396*** (3.45) 1.175*** (2.88) 0.036 (1.22)

−0.622*** (−3.42) 1.238*** (4.33) 7.562*** (8.78) 0.363*** (5.94)

6.653*** (4.47) −0.058** (−2.27) −2.844*** (−5.60) 0.008*** (3.70) Yes Yes 1.21*** (9.28)

0.0630 (1.55) −0.021*** (−2.95) −0.269* (−1.94) 0.010*** (4.05) Yes Yes 0.511 (1.40)

8.047*** (8.03) −0.091*** (−3.12) −3.132*** (−8.90) 0.003** (2.20) Yes Yes 1.539*** (8.27)

m2 Z1 Z2 Z3 Hansen test No. of observations

−1.06 32.31*** 14.66*** 52.12*** 93.32 (154) 1358

−1.49 9.54*** 18.92*** 47.85*** 84.74 (146) 1358

−1.06 52.78*** 21.69*** 42.64*** 94.67 (154) 158

−0.12 32.62*** 18.13*** 26.52*** 80.62 (125) 1358

−1.38 7.37*** 21.39*** 34.60*** 75.53 (123) 1358

−1.31 50.92*** 25.86*** 25.88*** 84.57 (108) 1358

Hansen, test of over-identifying restrictions, under the null hypothesis that all instruments are uncorrelated with the disturbance process. m2, statistic test for lack of second-order serial correlation in the first-difference residual. z1, Wald test of the joint significance of the reported coefficients. z2, Wald test of the joint significance of time dummies. z3, Wald test of the joint significance of industry dummies. *,**,***: Statistically significant at 1, 5 and 10 percent, respectively. In parentheses, t-statistics based on robust standard errors.

Our results show that in a context in which ownership concentration is prevalent and where the board of directors plays an influential role in the governance of firms, directors’ political ties have a positive impact on payout policy. We find that political connections increase cash dividends and share repurchases. The cash dividend results are consistent with the view that politically connected firms are subject to fewer financial constraints and come under greater scrutiny from analysts and mass media. This greater supervision may mean more attention being focused on the interests of minority shareholders, given the relevance of trust and reputation in dominant owner contexts. The positive relation between the presence of former politicians on the board and share repurchases may be explained by connected firms being more opaque in accounting terms. This opacity might translate into stock misevaluation and damage the interest and reputation of controlling shareholders. Consequently, controlling shareholders in politically connected firms have an incentive to draw attention to market misevaluation by repurchasing shares. These results are robust to alternative empirical specifications such as the propensity score matching procedure, different payout policy metrics, and different time periods. Results also hold when we focus on high level politicians, i.e., those holding national and international political posts or on the percentage of politicians in the board of directors. Results are in line with Su et al. (2014) for China, where the institutional environment differs from the continental European context. Whereas political ties in East Asia mainly exist to promote public-policy actions, such as supporting strategic industries or certain ethnic groups, our findings show that in an institutional setting where political connections mainly exist for corporate reasons, political connections also positively affect dividend policy. Our results have important implications for academia, investors and regulators alike. Although it focuses on Spain, our research may be applied to similar institutional contexts, such as those prevalent in many continental European countries. Regulators should be aware that these political connections might become a relevant corporate governance mechanism. Our results may prove useful for investors and financial analysts, since they highlight the importance of considering within-firm factors, such as directors’ political ties, when analysing dividend policy. Our research stresses the role of reputation and capital market scrutiny. From said viewpoint, one implication to emerge from our research is that active oversight by financial analysts can prove particularly valuable in politically connected firms. Likewise, the managers of these firms must be aware of the special circumstances under which their corporate payout decisions are interpreted. We note that our research design is subject to limitations related to the difficulty involved in measuring political connections. To build our sample of politically connected firms, we take advantage of regulatory requirements in Spain, since firms must publish directors’ curriculum vitae in their annual corporate governance reports. Although we use a state-of-the-art measure of political connections, we acknowledge that close relationships with political elites which do not involve the presence of a former politician on the board, have not been considered in our empirical analysis. Another interesting issue to address in the future is to explore whether capital markets react differently to the dividend announcements of politically connected firms relative to non-connected ones.

11

North American Journal of Economics and Finance 50 (2019) 101025

F.J. López-Iturriaga and D.J. Santana Martín

Acknowledgments The authors are grateful to Carolina Bona and Philip Jaggs for suggestions and comments on previous versions of the paper. All the remaining errors are the authors’ sole responsibility. This work was supported by the Ministry of Economy and Competitiveness [Grant Numbers ECO2017-84864-P and ECO201784132-R]. Appendix Variable descriptions Variable

Description

Divta Repta Divrepta Divebit Repebit Divrepebit Connected

Dividends scaled by total assets. Repurchases scaled by total assets. Dividend plus repurchases scaled by total assets. Dividends scaled by EBIT. Repurchases scaled by EBIT. Dividend plus repurchases scaled by EBIT. Dummy variable that equals one if at least one member of the board of directors has held a political position at a European, national, regional or local level in the past, and zero otherwise. Dummy variable that equals one if at least one member of the board of directors has held a political position at the European or national level in the past, and zero otherwise. Ratio of former politicians serving as directors over the total number of directors. Voting rights in the hands of ultimate or dominant owner. The difference between the dominant owner’s voting and cash flow rights. Firm’s market capitalization over the total market capitalization of all firms in the same industry The logarithm of total assets. The total amount of cash and cash equivalents divided by total assets. Dummy variable that equals one if the firm’s cash is higher than the annual sectorial median, and zero otherwise. Operating income before interest and taxes divided by total assets. The market value of equity divided by the book value of the shareholder. The relation between a firm’s total debt and total assets. The number of years since the firm began its activity. Based upon the Economic Policy Uncertainty Index constructed by Baker et al. (2016). Available at: http://www.policyuncertainty.com/

High_Connected Politicians Voting Voting_CF MK.Share Size Cash Fin_Constraint ROA MTB Lev Age Uncertainty

Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.najef.2019.101025.

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