Dividend payout policies evidence from Latin America

Finance Research Letters 17 (2016) 197–210

Contents lists available at ScienceDirect

Finance Research Letters
journal homepage: www.elsevier.com/locate/frl

Dividend payout policies: Evidence from Latin America
Julian Benavides a,∗, Luis Berggrun b, Hector Perafan b
a
b

Director of the Accounting and Financial Studies Department, Universidad Icesi Cali Colombia
Department of Accounting and Financial Studies, Universidad Icesi Cali Colombia

a r t i c l e

i n f o

Article history:
Received 12 February 2016
Accepted 7 March 2016
Available online 17 March 2016
JEL classification:
C33
G32
C34
G35
Keywords:
Dividends
Pecking order model

Trade-off model
Lifecycle theory of dividends
Latin America

a b s t r a c t
This paper examines dividend payout policies for firms in six Latin American countries
from 1995 to 2013. As predicted by the pecking order and trade-off models, the dividend
payout is positively linked to profitability and negatively related to past indebtedness and
investment opportunities. We also find that the target dividend payout ratio is positively
related to governance indicators at the country level. In addition, the speed to which firms
adjust their dividends to changes in earnings is lower in high governance countries in the
region. Thus, firms smooth dividends more in countries with higher governance scores. We
do not find evidence supporting the lifecycle theory nor illiquidity effects on dividends
levels.
© 2016 Elsevier Inc. All rights reserved.

1. Introduction
Means to give firm shareholders their money back, have always been (and always will be) a contentious issue. The financial literature has studied the ways, dividends and repurchases, and the motivations behind giving back cash to shareholders.
Floyd et al., (2015), for example, study how payout policies evolve over the last 30 years in the United States, arguing that
signaling and agency costs are extant reasons to explain those policies. Both explanations arise from the two main models
the financial literature has posited to explain capital structure decisions: the pecking order model and the trade-off model.
Although initially conceived to explain capital structure choices, both models also offer predictions on how firms decide to
pay dividends to their shareholders (Fama and French, 2002).
In the pecking order framework, Myers (1984) posits that asymmetric information leads managers to issue risky securities when they are overpriced. As a result, investors demand a premium on new and existing shares, once new issues
are announced. In anticipation managers can forego profitable investments if they require additional risky capital. To avoid
this problem, minimizing asymmetric information costs, managers prefer to finance new projects with retained earnings,
then with low risk debt, risky debt, and as a last option they issue equity. The pecking order model does not explain why
firms pay dividends; however, once dividends are paid, firms with less profitable assets in place, large current and expected
investments, and high leverage find dividends less attractive, given the financing costs attached to the issue of new risky
securities.

∗

Corresponding author. Tel.: +57 25552334.
E-mail addresses: (J. Benavides), (L. Berggrun), (H. Perafan).

/>1544-6123/© 2016 Elsevier Inc. All rights reserved.


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J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

Higher stability of income can also be associated with a lower likelihood of foregoing attractive investments or the need
of issuing risky securities. Thus, to lower the possibility of not taking advantage of investment opportunities when cash flow
is low, firms with volatile income pay less dividends. The following associations, controlling for additional interactions, are
expected: (1) more profitable firms pay more dividends; (2) firms with more leverage and more investment opportunities
pay less dividends; and (3) firms with more volatile income pay less dividends
The other main venue in explaining capital structure decisions is the trade-off model. Under this model firms make
capital structure decisions weighing different and opposing forces. In this setting, firms weigh bankruptcy costs and tax
considerations when determining a target or optimal level of debt. Firms with higher leverage, more volatile income, and
larger expected investment outlays are likely to set a lower leverage level to minimize distress costs. Given the fiscal benefits
of interest payments, one also would expect a more intense use of debt by the most profitable firms.
The pecking order and trade-off models make similar predictions in terms of dividends. Firms set dividends as to minimize potential bankruptcy costs (bearing in mind the differential fiscal treatment of dividends versus interest payments).
Thus, firms with less volatile earnings, lower leverage, and lower expected investment opportunities are more prone to pay
higher dividends. Conversely, firms with unprofitable assets in place are likely to have a low dividend payout ratio.
Under the trade-off model, agency cost considerations can also account for leverage and dividend decisions. Easterbrook
(1984) analyzes the effect of a consistent dividend policy in an environment characterized by agency problems within the
firm. One agency cost firms face is the one related to supervising management1 , a cost which shareholders must assume
since the interests of shareholders and managers are not always aligned. A second agency cost refers to risk aversion by

management (given its human capital investment in the firm) that prompts management to take low risk projects which in
many cases may not be the most beneficial for shareholders.
Dividends can reduce these two agency costs since they can force companies to use financial markets more frequently
and in the process expose the company to a higher degree of monitoring by investors and investment bankers that ends up
reducing monitoring costs initially borne by all investors. Likewise, according to Easterbrook (1984), dividends can serve to
adjust the level of risk taken by management to a point more in line with shareholder’s preference (higher level). In this
sense, paying a dividend increases the debt-to-equity ratio benefiting shareholders and sets free an efficient mechanism2
which results in a reduction in the firm’s agency costs.
Jensen (1986) points out the potential cost of agency that large free cash flow, under managerial control, could pose on
the firm value. Without restrictions in the use of the free cash flow, managers can waste the free cash flow in negative net
present value projects. Larger dividends reduce those agency costs forcing managers to take better decisions before wasting
resources of the firm. Iturriaga and Crisóstomo (2010) confirm the role of dividends in Brazil as a disciplining mechanism to
control managers that may feel inclined to pursue value-destroying projects.
La Porta et al. (20 0 0) discusses two versions of the agency theory of dividends. By and large, agency theory considers
dividends as a mechanism to mitigate conflicts between corporate insiders and outside shareholders.
A first version referred to as the “outcome model” states that dividends are a result of an effective legal protection
system of shareholders. In this sense one would expect a positive relationship between the level of dividends and the level
of investor protection across countries. The latter, since investors in more protected countries can extract more dividends
from companies they invest in.
A second version of the agency theory of dividends (“substitute model”) considers dividends and investor protection as
substitutes. In this version, dividends become an instrument to strengthen the reputation of companies. This reputation is
important since firms may occasionally need to get funding in financial markets. Under this model one would expect an
indirect relationship between dividends payments and the level of investor protection across countries, since it is likely that
companies in low investor protection countries care more about their reputation and as a means to protect it use dividends
more intensely than companies in high investor protection countries.
In addition to pecking order and trade off explanations on how firms pay dividends, DeAngelo
et al. (2006) propose a lifecycle theory of dividends as an alternative to these two often used models. They claim
that young firms tend to be less prone to pay dividends since they are likely to be in a capital infusion phase, and thus
most of its capital is contributed (e.g., by new shareholders), not earned. On the other hand, as firms mature (and most of
its capital is earned not contributed) these older firms are more inclined to pay dividends as they run out of investment

opportunities.
DeAngelo et al. (2006) find supportive empirical evidence of a lifecycle explanation of dividends because they document
a positive and highly significant relationship between the earned over contributed capital ratio (proxied by retained earnings
over total equity, or over total assets) and the propensity to pay dividends, even after controlling for firm size, growth, and
profitability.
Brockman and Unlu (2011) extend the evidence of a lifecycle theory of dividends in an international study of payout
policies. The ratio of retained earnings to equity had a positive influence in the likelihood that a firm pays dividends implying that young firms (usually with a low ratio of retained earnings to contributed capital) tend to pay lower dividends
than older firms. Not only age considerations play a role in explaining dividend policy; Brockman and Unlu document that

1
2

For example, audit costs to avoid manipulation of financial statements and possibly, expropriation by managers.
That increases the probability of using the market for capital with the consequent reduction of monitoring costs of management’s actions.


J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

199

agency costs considerations (related to accounting disclosure quality) also shape dividend decisions. In all, they document
a U-shape relationship between dividend payments and disclosure quality. Managers in transparent environments pay high
dividends because they are obliged by their shareholders, while managers in opaque settings pay high dividends to attract
(hesitant) external capital suppliers.
This paper studies dividend payment decisions of firms in six Latin American countries in the 1995–2013 period applying
the Lintner (1956) model, under the framework of Fama and French (2002) tests, that incorporate firm-specific variables in
analyzing the target dividend payout decision. These firm-specific variables (related to profitability, investment opportunities,
volatility, and the earned-contributed capital mix) allow us to examine the dividend predictions of the pecking order and
trade-off models, as well as those of the lifecycle theory of dividends.
Previous research Rajan and Zingales (1995), Demirgüç-Kunt and Maksimovic (1999), Booth et al. (2001), Bancel and

Mittoo (2004), de Jong et al. (2008), and Kirch and Terra (2012) emphasize the need to account for country-specific factors
when examining leverage decisions worldwide.
In a recent study, de Jong et al. (2008) show that country-specific factors (law abidance, shareholder/creditor right protection, market/bank financial system orientation, stock/bond market development and GDP growth rate) are important determinants (both directly and indirectly) of the leverage decisions of a panel of firms from 42 countries. In particular, firms
in countries with more developed bond markets and higher GDP growth show higher leverage.
We contribute to the literature by examining the extent of how both firm- and country-specific factors (mostly related
to corporate governance) shape the dividend decisions of Latin American firms within the framework of the pecking order
and trade off models, and the recent lifecycle theory of dividends.
We find that the dividend payout rate is positively associated to profitability and negatively related to past indebtedness
and investment opportunities, as predicted by the pecking order and trade-off models. Governance indicators at the country level are also positively correlated with the target dividend payout. Mitton (2004) finds similar evidence for a sample
of countries from emerging markets. Furthermore, he finds that country- and firm-level governance indicators are complements rather than substitutes in explaining the positive relationship between governance and dividends. We expand Mitton’s
(2004) evidence and examine the association between governance (at the country level) and the way firms adjust their dividends to shifts in earnings. We find that the speed to which firms adjust their dividends to changes in earnings is lower in
high governance countries in the region. Thus, firms pay less volatile dividends in countries with higher governance scores.
Contrary to what De Angelo et al. (2006) report, we find a negative impact of retained earnings on dividends, older firms in
our sample do not pay higher dividends; we interpret this result as a consequence of the very low use of equity markets of
our firms as a financing mechanism, with managers prioritizing investment flexibility (Blau and Fuller, 2008) or being less
disciplined by market forces (Easterbrook, 1984).
The rest of the paper is organized as follows: Section 2 describes the dataset, while Section 3 discusses our econometric
approach and findings on dividend policy in Latin America. Section 4 reports results from robustness checks. Lastly, Section
5 concludes the paper with a summary of our findings.
2. Data
Our sample includes financial data for public firms in six Latin American countries (Argentina, Brazil, Chile, Colombia,
Mexico and Peru) from 1995 to 2013. We collect firm data from consolidated financial statements and expressed in U.S.
dollars. Our source is Economatica, a database specialized in Latin American exchanges.3 In addition, we gather information
on a rule of law index from the World Bank. The index is built from thirty underlying sources which report perceptions
from survey respondents and experts worldwide (Kaufmann et al., 2010). The scale of the index varies from -2.5 (weak)
to 2.5 (strong) rule of law abidance. We perform cubic spline interpolation when there is missing data for the rule of law
indicator.
To construct our dataset we apply several screens. Utilities and banks are excluded from our sample because their dividend decisions are often influenced by regulation. Only firms with at least five million dollars of average assets enter our
sample. We do not include information on share repurchases due to the lack of data for these transactions in Economatica.4
Repurchases are infrequent in the region given the highly concentrated ownership. Venezuelan firms are not included in our

sample given the low number of reporting firms especially for the years 2010 and 2011. In our estimations we only consider
observations with positive reported dividends. To mitigate the impact of outliers, we censor observations at the 2nd and
98th percentile.
Pt
Our main variable, dividends, is calculated indirectly using two different methods. In the first method: Dt = DPP St . BVP
St . BEt ,
t
where dividends for fiscal year t (Dt ) are calculated multiplying the current dividend yield (dividends per share, DPSt , over
share price, (Pt ) times the price to book (book value per share, BVPSt ) ratio times the book value of common equity (BEt ).
The second method is straightforward:Dt = DPP St .MVEt , we just multiply the dividend yield times the total market capitalizat
tion (MVE or market value of equity). We report our results below using the first method. Nonetheless, our results remain
qualitatively similar using either of the two methods.

3
4

Dividend information in the Emerging Markets Database in Compustat for Latin American countries is almost nonexistent.
We only found repurchases information for the last five years for some of the countries of our sample.


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J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

Given the differences in the balance sheets of firms in the region we make some adjustments to obtain comparable
figures. We compute for Brazil dividends as the sum of reported dividends plus shareholder equity interest. Corporations in
Brazil can remunerate shareholders via interest payments to obtain tax savings (Velez-Pareja and Benavides Franco, 2011).
To estimate retained earnings, we construct a series for each country. We add retained earnings, other reserves type A,
and legal reserves to obtain retained earnings for Argentina. For Chile, we add retained earnings and other reserves type A
and B. while for Peru we add, in addition, unrealized results. Retained earnings in Brazil are the sum of retained earnings

and reserves. In Colombia, we assimilate retained earnings as the addition of net income, total reserves, and accumulated
income. As for Mexican firms, retained earnings are set equal to net income for the year, legal reserves, and reserves created
in previous years.
The top panel of Table 1 includes a brief description of our main variables. In Panel B of Table 1 we observe that Chilean
firms pay the highest dividends as a percentage of assets. Mexican and Brazilian firms are the largest (by assets) possibly
because these firms come from the two biggest economies of the region. Focusing on variables related to investment opportunities ( MAVt , and P P Nt+1 ), we observe, by and large, that Chilean and Peruvian tend to show the highest ratios. As
t

for profitability measures,

Et
St

fluctuates from 12.29% and 21.16%, while

N It
At+1

ranges from 3.88% to 7.41%. In terms of leverage

(using both book or market figures), Brazilian firms appear the more highly indebted while Colombian firms are the less
leveraged in the region. Mexican and Chilean firms show the higher retained earning-to-assets ratio possibly indicating that
these firms are the most mature in the region. In addition, Chile scores strongly in rule of law compliance5 , while Colombia
shows the weakest score.
D
The third panel of Table 1 shows, as expected, a positive and significant correlation (0.534) between dividends At+1 and
net income

N It
.

At+1

MVt
At
( EStt )

The panel also shows a positive correlation between dividends and

likely to be more related to profitability than to investment opportunities. Profitability
correlated. Conversely, investment opportunities comprise in the ratio of

P P Nt+1
At

t+1

suggesting that this variable is
and dividends are also positively

and dividends are negatively correlated al-

though the correlation is not statistically significant, which contrast with those include in the ratio

At+1
At+1

that has a positive

statistically significant correlation with dividends. Leverage is negatively related with dividends. All the previous associations
are very much in line with predictions of the pecking order and trade off models. The lifecycle theory of dividends suggests

a positive association between dividends and retained earnings (or RAEt ); however, this correlation is negative and significant
t
for our sample (−0.37), when discussing the results from Table 2 we will elaborate on this issue. Interestingly, dividend
payments and the rule of law indicator are positively and significantly correlated lending univariate support to the outcome
model of the agency theory of dividends (La Porta et al., 20 0 0).
In Table 1, Panel D we note that our unbalanced panel comprises 666 firms and 3798 firm-year observations. Brazilian
and Chilean firms constitute more than 50% of the sample. The average number of observations per firm is 5.70.
The bottom panel (E) of Table 1 reports the evolution in time of one of our main independent variables. The ratio of net
income to assets appears more stable (measured by the coefficient of variation) in Chile and Peru. Conversely, and Mexican
and Argentinean show the most volatile profits. The last four years have witnessed an increase in profits for all the countries
in the sample, in line with the economic recovery of the region.
3. Econometric approach and results
Lintner (1956) in an influential survey on dividend policy, still being applied to explain firm’s payouts Andres et al.,
(2015), found that firms pay considerable attention to the existing rate of dividend payments when determining the upcoming dividend. Furthermore, changes in dividends were strongly affected by variations in current earnings. Most of the
firms in their sample intended to keep a roughly constant target dividend payout (TP) ratio (with 50% being the most common target). In all, Lintner (1956) posits that firms have a long term target payout ratio that affects target dividends in the
following way:

T Dt+1 = T P ∗ N It

(1)

In Eq. (1), T Dt+1 is target dividend measured in year t + 1, and NIt is the net income that backs the observed dividends.
Adjustment costs produce just a partial movement to the target in year t + 1, thus the change ( ) in dividends is the result
of the difference between the target dividend and the actual dividend times the speed of adjustment (SOA):

Dt+1 = SOA(T Dt+1 − Dt ) + εt+1

(2)

In order to estimate Eq. (2), Lintner (1956) replaced TDt + 1 to obtain an empirical counterpart of his model:

Dt+1 = α1 N It + α2 Dt + εt+1
The speed of adjustment is SOA = −α2 and the target payout is T P =

(3)
α1

SOA

.

5
The rule-of-law indicators remain (not shown) relatively stable or improve throughout the years, except for Argentina which suffered a sudden decline
in the rule of law index in the 20 0 0–20 02 period.


J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

201

Table 1
Selected sample statistics.
Panel A Description of variables
Variable

Definition

D/A
Dt + 1 /At + 1
Ln(A)

A t + 1 /At + 1
NIt /At + 1
MV
MV/A
E/S
PPNt + 1 /At
L/A
L/MV
Dt /At + 1
RE/A
GI

Dividends over assets
Change in dividends over assets
Natural logarithm of assets (in millions of US dollars)
Proportional change of assets
Net income over assets of next fiscal year
Market value = market equity + liabilities (in millions of US dollars)
Market value over assets
Earnings before interest and taxes over sales
Change in net plant and equipment over assets of past fiscal year
Liabilities over assets
Liabilities over market value
Dividends over assets of next fiscal year
Retained earnings over assets
Governance index: rule of law (World Bank governance indicators)

Panel B Mean values of selected variables per country (1995–2013)

Dt + 1 / At + 1 (%)

Dt + 1 / At + 1 (%)
At ($)
At + 1 / At + 1 (%)
NIt / At + 1 (%)
MVt / At
Et /St (%)
PPNt + 1 /At (%)
Lt + 1 /At + 1 (%)
Lt + 1 /MVt + 1 (%)
Dt / At + 1 (%)
REt /At (%)
GIt + 1

Argentina

Brazil

Chile

Colombia

Mexico

Peru

Total

3.48
0.44
$1,571

4.84
6.70
1.22
18.26
1.91
44.94
40.71
3.04
18.51
−0.41

2.70
0.35
$2,004
5.68
5.46
1.21
14.17
2.70
53.94
50.47
2.35
13.17
−0.31

3.56
0.26
$1,258
7.21
5.59

1.36
15.04
4.37
47.91
39.82
3.30
21.22
1.23

2.08
0.06
$1,787
8.46
3.88
0.97
12.29
3.56
34.21
36.51
2.02
12.89
−0.69

2.53
0.16
$3,284
6.08
6.50
1.58
14.36

3.03
46.40
32.53
2.37
27.10
−0.54

3.27
0.34
$640
8.08
7.41
1.37
21.16
4.52
42.09
37.17
2.94
14.92
−0.67

3.04
0.31
$1,682
6.37
5.80
1.28
15.38
3.33
49.52

44.12
2.73
16.78
0.07

Panel C Correlation matrix (1995–2013)
Dt+1 /
At+1
Dt + 1 /At + 1
At
At + 1 /At + 1
NIt /At + 1
MVt /At
Et /St
PPNt + 1 /At
Lt + 1 /At + 1
Lt + 1 /MVt + 1
Dt /At + 1
REt /At
GIt

0.457∗∗∗
−0.038∗∗
−0.050∗∗∗
0.534∗∗∗
0.353∗∗∗
0.277∗∗∗
−0.009
−0.169∗∗∗
−0.417∗∗∗

0.795∗∗∗
0.081
0.107

At

0.002
0.060∗∗∗
0.126
0.107
0.079
0.051∗∗∗
−0.038∗∗
−0.146∗∗∗
−0.176∗∗∗
−0.012
−0.018

At+1 /
At+1

NIt /
At+1

MVt /
At

Et /
St

PPNt+1 / Lt+1 /
At
At+1

Lt+1 /
MVt+1

Dt /
At+1

REt /
At

GIt

0.048∗∗∗
−0.094
0.107
0.138∗∗∗
0.044∗∗∗
0.226∗∗∗
0.049∗∗∗
−0.043∗∗∗
−0.047∗∗∗
−0.075

−0.050∗∗∗
0.173∗∗∗
0.051∗∗∗
0.670∗∗∗

0.056∗∗∗
−0.171∗∗∗
−0.097
0.037∗∗
−0.009

0.392∗∗∗
0.372∗∗∗
0.201∗∗∗
−0.019
0.140∗∗∗
0.102
−0.271∗∗∗
0.097
−0.088
0.052∗∗∗
−0.455∗∗∗ −0.471∗∗∗ −0.234∗∗∗ −0.123
0.634∗∗∗
0.505∗∗∗
0.317∗∗∗
0.252∗∗∗ −0.045∗∗∗ −0.161∗∗∗ −0.362∗∗∗
∗∗∗
∗
0.345
0.125
0.014
0.027
−0.391∗∗∗ −0.370∗∗∗ 0.097
−0.053∗∗∗
0.074

−0.032∗∗
0.033∗∗ −0.014
−0.092
0.131 0.202∗∗∗

Panel D Firms per country (1995–2013)

Argentina
Brazil
Chile
Colombia
Mexico
Peru
Total

Firms

Observations (firm-year)

Average (Obs/Firms)

60
319
141
19
60
67
666

293

1,758
1,099
87
192
369
3,798

4.88
5.51
7.79
4.58
3.20
5.51
5.70

Panel E Average NIt /At + 1 per country and year

Argentina
Brazil
Chile
Colombia
Mexico
Peru
Total

1995

1996

1997

1998

1999

20 0 0

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

7.39%
4.33%
6.23%
2.75%
3.20%
9.07%
5.44%

5.94%
5.01%
5.81%
4.32%
9.40%
7.53%
5.68%

5.75%
5.04%
6.18%
4.87%
7.67%
9.37%
5.99%

6.14%
5.31%
6.31%
4.92%
4.92%

6.64%
5.82%

4.23%
4.25%
5.65%
2.66%
7.28%
7.77%
4.99%

4.74%
6.07%
5.15%
5.26%
6.00%
7.21%
5.77%

8.55%
6.67%
5.21%
5.32%
6.23%
6.42%
6.14%

2.24%
4.06%
4.24%

4.66%
7.92%
5.92%
4.29%

6.44%
5.89%
5.13%
4.62%
9.85%
6.75%
5.72%

7.51%
6.60%
5.87%
2.53%
4.70%
7.43%
6.38%

8.85%
6.13%
6.07%
2.22%
6.84%
6.85%
6.31%

8.43%

4.98%
5.97%
2.18%
7.03%
7.40%
5.95%

7.40%
7.21%
6.36%
2.87%
8.39%
8.14%
7.16%

5.95%
4.41%
4.66%
1.59%
5.03%
7.23%
4.88%

5.62%
4.87%
5.43%
2.19%
6.03%
7.86%
5.53%

8.50%
6.48%
6.46%
5.28%
7.47%
8.23%
6.91%

8.85%
5.47%
4.53%
3.93%
5.82%
7.55%
5.68%

6.15%
4.87%
4.79%
3.19%
4.94%
5.53%
5.01%

(continued on next page)


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J. Benavides et al. / Finance Research Letters 17 (2016) 197–210
Table 1
Continued.
Argentina
Brazil
Chile
Colombia
Mexico
Peru
Total

Avg (%)

σ (%)

σ /μ (%)

6.59
5.43
5.56
3.63
6.60
7.38
5.76

1.78
0.94
0.69
1.28
1.73

0.98
0.71

27.04
17.30
12.45
35.39
26.16
13.26
12.26

Note: The table describes the variables we use (Panel A) from Economatica and World Bank Governance Indicators. Panel B
reports average values of our main variables per country, all variables are ratios except Assets (At ) which is measured in millions
of US dollars. Panel C reports correlations among variables, where ∗∗∗, ∗∗ and ∗ denote significance of the pairwise correlation
(Ho: ρ = 0) at the 0.01, 0.05 and 0.10 levels. The next panel (Panel D) shows the number of firms and observations per country.
It
over the sample years per country, the last three columns present the average, the standard deviation and
Panel E reports ANt+1
the coefficient of variation, respectively.

3.1. Target payout and speed of adjustment
Following Fama and French (2002) we examine the target payout and the speed of adjustment taking into account the
effect of the driving variables of dividend decisions according to the pecking order and trade off models as well as the lifeA
cycle theory of dividends. We proxy profitability with ESt and MAVt ; investment opportunities with At+1 and PAPNt . Leverage
L

t

L

is measured using accounting ( At+1 ) or market ( MVt+1 ) figures.
t+1

t+1

t

REt
At

t

t

is our proxy for the earned over contributed capital ratio

which is the main driving variable of dividend decisions according to the lifecycle theory of dividends. We use the natural
logarithm of size as a proxy for volatility (as Fama and French (2002)). Larger firms are more likely to have low volatility
given their more stable cash flows and earnings.
We model how TP and SOA are affected by firm specific variables. Thus we follow Fama and French (2002), who argued
that a more robust approach to test theories about dividends determinants is that firm specific factors affect directly the
magnitude of TP and SOA. We also include country effects in our estimation to assess the effect of unobserved heterogeneity
among countries on dividend policies. Additionally, there is a substantial body of research (see Section 1) that stresses the
need to account for country specific factors in modeling leverage decisions. We expand this approach to dividend decisions
by estimating a panel model with country fixed effects.
Our model derived from Eq. (1) allows TP to vary using firm specific factors:

Dt+1
= a0 + d ci +
At+1

+ εt+1

a1 + a2

MVt
Et
+ a3 + a4
At
St

P P Nt
REt
+ a5 ln (At ) + a6 Levt+1 + a7
At
At

Opposite
Hypotenuse

N It
At+1
(4)

The dummy variables dci account for differential intercepts for each country, allowing the estimation of differential target
payouts.
We initially estimate Eq. (4) using a panel regression with country dummies and clustering errors at the year level. The
relation between dividends and the exogenous variables is modeled in five ways. The first model (a.) includes country dummies, but assumes no interaction between ANIt and the proxies used for profitability, investment opportunities, volatility,
t+1

leverage and the earned/contributed capital (i.e., a2 = a3=…a7 = 0). The second approach (b.) allows for the interaction of

N It
only with our proxies of profitability, investment opportunities, and volatility. The following two specifications (c. and
A
t+1

d.) expand specification b. and include leverage effects in terms of book or market leverage. The last specification (e.) resembles specification d. and includes lifecycle effects. Argentina is use as the omitted country in deriving our country dummies.
At the bottom of Panel A of Table 1 we report the number of firms and yearly observations used under each specification.
Wald tests’ results strongly support the inclusion of country dummies (which are mostly negative). We can decisively
reject the null that the joint value of the country dummies is equal to zero. Moreover, the fit of the model (that never falls
below 0.26) increases slightly as we move from specification a. to specification e.
Our evidence of a positive relationship between MAVt and dividend is similar to that of Fama and French (2002) for a U.S.
t
sample and is in accordance with the signaling hypothesis (Bozos et al., 2011). However, the positive sign of the interaction
N It
MVt
variable A
∗ A is unexpected since under the pecking order and trade-off models firms with high investment prospects
t+1

t

are expected to pay lower dividends. Perhaps this positive sign can be rationalized under the premise that MAVt can also be
t
considered as a proxy the current profitability of firms.
Et
N It
The positive coefficients of the interaction variables related to S and A
concur with the pecking order and trade off
t

t+1

models that assume that the most profitable firms are more prone to pay higher dividends. Under the trade-off model these
higher dividends are explained as a means to counter agency problems prompted by excess cash flows. In the pecking order
model, these higher dividends are explained by the use of more profitable assets that allow firms to maintain a low risk


J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

203

Table 2
Determinants of dividend payout ratio.
Panel A Estimates with country effects
Specification:

a. No interaction

Intercept
NIt / At + 1
d-Brazil
d-Chile
d-Colombia
d- Mexico
d-Peru
NIt /At + 1 ∗ MVt /At
NIt /At + 1 ∗ Et /St
NIt /At + 1 ∗ PPNt + 1 /At
NIt /At + 1 ∗ ln(at )
NIt /At + 1 ∗ Lt + 1 /At + 1

NIt /At + 1 ∗ Lt + 1 /MVt + 1
NIt /At + 1 ∗ REt /At
Wald
Adjusted R2
N
Firms

0.012∗∗∗

0.335∗∗∗
−0.003
0.005∗∗∗
0.0 0 0
−0.008∗∗∗
−0.005∗∗

160.6∗∗∗
0.268
6037
836

b. No leverage

c. Book leverage

0.014∗∗∗

0.014∗∗∗

0.122∗∗

−0.003
0.004∗∗
−0.003∗
−0.009∗∗
−0.006∗∗∗
0.107∗∗∗
0.336∗∗∗
−0.174∗∗
−0.002

0.143∗∗∗
−0.002
0.004∗∗∗
−0.004∗
−0.009∗∗
−0.006∗∗∗
0.108∗∗∗
0.338∗∗∗
−0.182∗∗
−0.002
−0.034

114.4∗∗∗
0.322
4962
770

134.5∗∗∗
0.322
4912

769

d. Market leverage

e. Retained earnings

0.014∗∗∗

0.015∗∗∗
0.394∗∗∗
−0.003
0.004∗∗
−0.006∗∗
−0.010∗∗∗
−0.007∗∗∗
0.063∗∗∗
0.260∗∗∗
−0.208∗∗
0.005

−0.430∗∗∗

−0.588∗∗∗
−0.397∗∗∗
111.0∗∗∗
0.366
4838
767

0.274∗∗∗

−0.002
0.004∗∗
−0.005∗∗
−0.011∗∗∗
−0.006∗∗∗
0.074∗∗∗
0.218∗∗∗
−0.221∗∗∗
0.004

140.0∗∗∗
0.348
4911
770

Panel B Target payout

Argentina
Brazil
Chile
Colombia
Mexico
Peru

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.555
0.509
0.641
0.549
0.407
0.467

0.533
0.484
0.604
0.477
0.380
0.431

0.528
0.484
0.603
0.465
0.376
0.426

0.509
0.478
0.573
0.427
0.314

0.405

0.524
0.477
0.588
0.425
0.341
0.401

Panel C Estimates with governance indicators
Specification:

a. No interaction

Intercept
NIt / At + 1
NIt ∗ GIt
NIt /At + 1 ∗ MVt /At
NIt /At + 1 ∗ Et /St
NIt /At + 1 ∗ PPNt + 1 /At
NIt /At + 1 ∗ ln(at )
NIt /At + 1 ∗ Lt + 1 /At + 1
NIt /At + 1 ∗ Lt + 1 /MVt + 1
NIt /At + 1 ∗ REt /At
Adjusted R2
N
Firms

0.011∗∗∗

b. No leverage
0.012∗∗∗

0.342∗∗∗
0.110∗∗∗

0.012∗∗∗

0.104∗∗
0.112∗∗∗
0.095∗∗∗
0.354∗∗∗
−0.175∗∗
0.002

0.285
6037
836

c. Book leverage

0.343
4962
770

d. Market leverage

e. Retained earnings

0.012∗∗∗

0.013∗∗∗
0.368∗∗∗
0.116∗∗∗
0.053∗∗∗
0.297∗∗∗
−0.204∗∗
0.009∗∗

−0.369∗∗∗

−0.551∗∗∗
−0.449∗∗∗
0.385
4838
767

0.126∗∗∗
0.115∗∗∗
0.095∗∗∗
0.369∗∗∗
−0.186∗∗
0.0 0 0
−0.012

0.241∗∗∗
0.104∗∗∗
0.066∗∗∗
0.253∗∗∗
−0.220∗∗∗

0.006

0.343
4912
769

0.363
4911
770

Note: The data is from public Latin-American firms in six countries and it covers seventeen years (1995–2013). The dependent
t+1
variable is DAt+1
, dividends for fiscal year t + 1 divided by assets in year t + 1. Panel A reports the results of panel regressions;
all regressions include country dummies; dci . is the dummy for country i. Specification a. does not include an interaction
It
It
. The next specification, includes interaction terms with ANt+1
for MAVt t , EStt , PPANt t+1 , and ln (At ). Specifications c.
term with ANt+1
vt+1
N It
t+1
with LeAvt+1
and Le
At+1
MVt+1
N It
REt
.

Panel
B
presents
the
and
At+1
At
a2 Mn MAVt t + a3 Mn EStt + a4 Mn PAPt Nt +

and d., expand specification b. interacting
d. with an interaction term of
estimated as

a0 +d ci
NI
Mn ( A t )

+ a1 +

(

)

( )

(

)

respectively. The last specification augments specification

implied target payout per country. The target payout is
a5 Mn(ln(At ) ) + a6 Mn(Levt+1 ) + a7 Mn( RAEtt ), where Mn(.) is

t+1

the sample mean of a variable, and Levt+1 is either book leverage or market leverage in t + 1. Panel C shows regression results
It
replacing country dummies with a governance indicator variable, interacted with ANt+1
. We estimate coefficients’ significance
based on standard errors clustering by time. R2 is the adjusted R2 , and N is the number of observations of each model. ∗∗∗,
∗∗, and ∗ denote significance at the 0.01, 0.05, and 0.10 levels. Wald test proves the null hypothesis that the joint value of the
country dummies is equal to zero.

debt capacity to finance investment. Furthermore, higher profits, ceteris paribus, reduce the financing (or funds flow) deficit
(Shyam-Sunder and Myers, 1999) allowing firms to pay higher dividends.
The change in net plant and equipment carries the expected negative sign in line with predictions of the pecking order
and trade off models. In addition, the slopes for our leverage proxies show an expected and significant negative sign. In the
pecking order model where firms balance current and future financing costs this negative relation is natural since if more
levered firms pay a higher fraction of their earnings in dividends this would increase the probability of using higher cost


204

J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

financing. 6 In the trade-off model dividends and leverage are considered as substitutes to mitigate agency problems. Thus
it is sensible for more indebted firms to control their dividends payments.
ln (At ), our risk proxy, shows a positive slope in our most complete specifications (d. and e.). This result does support the
pecking order and trade- off models that hypothesize that firms with more volatile cash flow tend to be less levered as well
as more conservative in their dividend policies. Nonetheless, the coefficient for our risk proxy is not statistically significant.

The coefficient on the earned to contributed capital variable is negative. The indirect relationship between dividends and
the earned-contributed capital mix does not support the lifecycle theory of dividends which predicts a positive relationship.
Possibly, older firms in the region abstain from paying more generous dividends since they do not recur to equity markets for regular financing needs, as their counterparts in more developed markets do, being less disciplined by the market
(Easterbrook, 1984) and prioritizing investment flexibility (Blau and Fuller, 2008) over shareholders satisfaction. Given the
high ownership concentration of the listed firms in our sample (Benavides, 2005), is not surprising the reluctance to use
equity markets for financing needs, as controlling shareholders seek to maintain their grip on the firm.
In Panel B of Table 2, the implied target payout is calculated for each country in the sample using the same five specifications of the top panel of Table 2. The target payout is calculated as:

TP =

( a0 + d ci )

+ a3 M n

Et
St

+ a5 Mn ln (At ) + a6 Mn(Levt+1 ) + a7 Mn

REt
At

Mn

N It
At+1

+ a1 + a2 M n

MVt

At

+ a4 M n

P P Nt+1
At
(5)

Focusing on the last two columns of Panel B we see that target payouts fluctuate widely from 0.314 to 0.588. In the
last column, Chile shows the highest payout, followed by Argentina, Brazil, Colombia, Peru, and Mexico. Interestingly, Chile
which according to Panel B of Table 1 has the highest rule of law indicator, also presents the most generous target payout.
On the other hand, firms in Peru that face an environment of weak rule of law abidance, showed one of the lowest target
payouts. In fact, the correlation between the country orderings by target payout and by rule of law compliance (Chile, Brazil,
Argentina, Mexico, Peru, and Colombia) is strong (higher than 0.6).
The positive association between the target payout and rule of law abidance gives support to the “outcome model”
of the agency theory of dividends. Our results for Latin America mirror those of La Porta et al. (20 0 0) who in a cross
sectional analysis of more than 40 0 0 firms in 33 countries for 1994 found evidence favoring the “outcome model”. La Porta
et al. (20 0 0) document higher dividend payout rates in countries with better investor protection (generally Anglo-Saxon
or “common law” countries in contrast to civil law countries that often have lower levels of investor protection). Likewise,
Bebczuk (2007) finds that improvements in governance at the firm level (e.g., in transparency and disclosure) are usually
accompanied by a higher dividend payout rate in Argentina.
In the bottom panel of Table 2 we examine the positive association between TP and the rule of law variable in more
detail. Here we use the same model specifications as those of Panel A of Table 2 but with two modifications. We exclude
the country dummies and we expand the model with a new interaction ( ANIt and GIt+1 ) to capture the effect of rule of law
t+1

compliance at the country level and TP.
Panel C of Table 2 shows that the magnitude, sign, and significance of our variables to proxy profitability, investment
opportunities, risk, and lifecycle effects resemble those of the second panel of Table 2. Importantly, our regression results
show that the coefficient of the interaction of the rule of law variable (and ANIt ) is positive and highly significant. This

t+1

finding gives further credence to the idea that investors in better investor protection countries are more likely to benefit
from higher dividends.

3.2. Variations in investments and dividends
This section examines how firms alter their dividends to accommodate variations in their investment outlays. Based on
A
the Lintner (1956) model, and including the variable A t+1 to account for contemporaneous investment one could estimate
t+1

the following dynamic model:

Dt+1
N It
Dt
At+1
= a0 + α1
+ b1
+ c1
+ εt+1
At+1
At+1
At+1
At+1

(6)

Nonetheless, Fama and French (2002) argue that the model of Eq. (6) is misspecified since TP and SOA are likely to vary
across firms. Thus, Eq. (6) is modified to take into account both firm characteristics as well as country effects which likely

affect dividend policy. The resulting model follows:

6

Firms would then have to use either debt at a higher interest rate or equity financing.


J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

Dt+1
= a0 +
At+1

a1 + a2

+ b1 + b2
+ c1

MVt
Et
+ a3 + a4
At
St

MVt
Et
+ b3 + b4
At
St

P P Nt
REt
+ a5 ln (At ) + a6 Levt+1 + a7
At
At

205

N It
At+1

P P Nt
REt
Dt
+ b5 ln (At ) + b6 Levt+1 + b7
+ d ci
At
At
At+1

At+1
+ εt+1
At+1

(7)

Eq. (7) implies a speed of adjustment specific for each country, equal to (where Mn stands for mean):

SOA = − b1 + b2 .Mn

MVt
At

+ b3 .Mn

Et
St

+ b5 .Mn(ln (At ) ) + b6 .Mn (Levt+1 ) + b7 .Mn
The country dummy is interacted with

Dt
At+1

P P Nt
At

+ b4 .Mn
REt
At

+ d ci

(8)

because the SOA is likely to be affected by country characteristics (Adaoglu

(20 0 0) and Andres et al. (2009)). Given that TP is defined as the ratio of the coefficients accompanying

N It

At+1

evaluated at

the mean values of the independent variables over SOA, then TP is also modified by the country dummies. Instead of a
panel regression, each year we estimate cross sectional regressions and average the estimates through the years (Fama and
MacBeth, 1973).
In Panel A of Table 3 we estimate the model of Eq. (7) using a pooled panel regression and clustering errors by year.
Table 3 shows our results for Eq. (7), the reported coefficients are the result of the interaction terms evaluated at the mean
values of the independent variables that account for firm characteristics. We employ five different specifications similar
to those described in Section 3.1 for Table 2. Specification 1 is the simplest and does not consider interactions for firm
characteristics, just for the country dummies. Specification 2 expands specification 1 and includes interactions except with
leverage. In the following two specifications, we additionally include an interaction term for leverage, the first one using
book leverage and the second one market leverage. Specification 5 (or the full model of Eq. (7)) repeats specification 4 plus
an additional interaction term for retained earnings.
The positive and significant coefficient of ANIt supports the idea that dividend changes are influenced by firms’ profits.
t+1

The coefficients to gauge how dividends change after investments outlays is negative and fluctuates from −0.003 to −0.006.
The finding of a negative coefficient supports the idea that firms cut back on dividends when investment requirements
grow. Nonetheless, and similar to previous studies for the U.S. Myers (1984), Shyam-Sunder and Myers (1999) and Fama and
French (2002), the magnitude of the coefficient is economically small since the change in dividends absorbs roughly just
0.6% of the change in assets. Furthermore, in the top panel of Table 3 we can see that the interacted country dummies are
mostly negative but only significant for Mexico.
In Panel B of Table 3 we report the speed of adjustment of dividends to changes in net income controlling for past
dividends and concurrent investment needs. SOA (focusing on the last column of the table) fluctuates from 0.34 to 0.72.
Interestingly, our speed of adjustment estimates for Latin American tend to surpass those reported (that range from 0.28 to
0.33) for the U.S. by Fama and French (2002).
In a related paper, Chemmanur et al. (2010) compare dividend policies in the U.S. and Hong Kong. Firms in Hong Kong
appear to have more flexible dividend policies since they smooth dividends to a lower extent (i.e., they have a higher SOA)

than in the U.S., perhaps as ownership is more closely aligned (alleviating manager-shareholders conflicts). In addition, Hong
Kong managers seem less concerned with the informational content of dividend changes (e.g., reflected in abnormal returns
around dividend increases and cuts) and consequently are inclined to alter dividends more swiftly than U.S. managers. Both
factors that favor a higher speed of adjustment in Hong Kong (i.e., a close alignment between managers and shareholders
and a disregard of market signals related to dividend increases or omissions) are likely to apply as well in Latin America.
We hypothesize that these factors play a role in understanding our finding of a higher SOA in the region.
Another possible explanation for our finding of a more volatile dividend policy in Latin America than in the U.S. may be
related to the more prevalent use of private debt in Latin America versus public debt (which is likely to be more pervasive
in the U.S.). Aivazian et al. (2006) find that firms in the U.S. that rely on private debt are more prone to follow a purely
residual dividend policy as opposed to firms with rated (public) debt. Companies that depend on public debt tend to smooth
dividends (as in Lintner (1956) perhaps to ameliorate signaling and agency problems brought about by their reliance in bond
financing which is a funding source more susceptible to informational asymmetries than bank financing. Thus, the fact that
firms in Latin America are likely to rely on private debt allows them to carry a more flexible (and volatile) dividend policy
in which market signals play a lesser role in determining the rate of change in dividends.
Furthermore, we find in Panel B of Table 3 that firms in countries with low scores on rule of law obedience (Colombia,
Mexico, and Peru) are more likely to have higher speed adjustments than firms located in countries with higher relative
scores on rule of law compliance (Argentina, Brazil, and Chile).
In the literature there is some support for the negative relation between how firms alter their dividends after changes in
profits and the environment in which a firm operates. For example, Andres et al. (2009) claim that dividend volatility is less
of a concern for firms in emerging markets (when compared to firms in developed markets). Further, Adaoglu (20 0 0) finds


206

J. Benavides et al. / Finance Research Letters 17 (2016) 197–210
Table 3
Lintner model with dynamic adjustment according to Eqs. (5) and (6).
Panel A Estimates with country effects
Specification:

a. No interaction

Intercept
NIt / At + 1
At + 1 / At + 1
Dt /At + 1
Dt /At + 1 ∗ d-Brazil
Dt /At + 1 ∗ d-Chile
Dt /At + 1 ∗ d-Colombia
Dt /At + 1 ∗ d- Mexico
Dt /At + 1 ∗ d-Peru
R2
N
Firms

b. No leverage

c. Book leverage

0.003∗∗∗

0.001
0.113∗∗∗
−0.003
−0.234∗∗∗
−0.006
0.088
−0.015
−0.051
0.029

0.163
5,227
798

d. Market leverage

0.004∗∗∗

0.113∗∗∗
−0.006∗∗
−0.339∗∗∗
0.037
0.049
−0.065
−0.164
−0.035
0.251
4,625
762

0.004∗∗∗

0.106∗∗∗
−0.005∗∗
−0.334∗∗∗
0.041
0.045
−0.094
−0.206
−0.063

0.263
4,579
760

e. Retained earnings
0.004∗∗∗
0.121∗∗∗
−0.005∗∗
−0.385∗∗∗
0.020
0.042
−0.077
−0.334∗∗
−0.092
0.292
4,500
752

0.105∗∗∗
−0.005∗∗
−0.382∗∗∗
0.049
0.040
−0.073
−0.240∗
−0.043
0.270
4,566
756

Panel B Speed of adjustment

Argentina
Brazil
Chile
Colombia
Mexico
Peru

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.23
0.24
0.15
0.25
0.28
0.20

0.34
0.30
0.29
0.40

0.50
0.37

0.33
0.29
0.29
0.43
0.54
0.40

0.38
0.33
0.34
0.46
0.62
0.42

0.38
0.37
0.34
0.46
0.72
0.48

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.48
0.47
0.78
0.45
0.40
0.55

0.33
0.37
0.39
0.28
0.22
0.30

0.32
0.36
0.37
0.25
0.20
0.27

0.27
0.31
0.31
0.23
0.17

0.25

0.31
0.33
0.35
0.26
0.17
0.25

Panel C Target payout

Argentina
Brazil
Chile
Colombia
Mexico
Peru

Panel D Governance indicators
Specification:

a. No interaction

Intercept
NIt / At + 1
At + 1 / At + 1
Dt /At + 1
Dt /At + 1 ∗ GIt
R2
N

Firms

b. No leverage
0.003∗∗∗

0.0 0 0
0.111∗∗∗
−0.001
−0.194∗∗∗
0.048∗∗
0.125
5,227
798

0.111∗∗∗
−0.004∗
−0.308∗∗∗
0.026
0.221
4,625
762

c. Book leverage
0.003∗∗∗

0.108∗∗∗
−0.004∗
−0.313∗∗∗
0.032∗
0.233

4,579
760

d. Market leverage
0.004∗∗∗

e. Retained earnings
0.004∗∗∗
0.124∗∗∗
−0.004∗
−0.377∗∗∗
0.049∗∗∗
0.260
4,500
752

0.106∗∗∗
−0.004∗
−0.355∗∗∗
0.025
0.242
4,566
756

Note: The data is from public Latin-American firms in six countries and it covers seventeen years (1995–2013). The dependent
t+1
, the change in dividends for fiscal year t + 1 versus year t divided by assets in year t + 1. Panel A reports
variable is ADt+1
the results of pooled panel regressions; all specifications include country dummies interacting with
for country i. The slope on

N It
At+1

is the average across years of a1 + a2 Mn( MAVt t ) + a3 Mn( EStt ) + a4 Mn(

Dt+1
,;
At+1
P P Nt
At

dci is the dummy

) + a5 Mn(ln(At ) ) +

a6 Mn(Levt+1 ) + a7 Mn( RAEtt ), where Mn(.) is the sample mean of a variable, ai are the regression coefficients from Eq. (6)
and Levt+1 is either book leverage or market leverage in t + 1. Meanwhile, the slope on
b1 + b2 Mn(

MVt
At

) + b3 Mn( ) + b4 Mn(
Et
St

P P Nt
At

) + b5 Mn(ln(At ) ) + b6 Mn(Levt+1 ) + b7 Mn(

REt
At

Dt
At+1

is the average across years of

) where bi are the regression coefficients

from Eq. (6). Panel B presents the speed of adjustment per country, which is the negative of the sum of the slope on
the dci . The implied target payout in Panel C is the slope on

N It
At+1

Dt
At+1

and

divided by the speed of adjustment. Panel D shows regression

results replacing country dummies with a governance indicator variable, interacted with

Dt
At+1

. We estimate coefficients’ signifi-

cance based on standard errors clustering by time. R2 is the adjusted R2 , and N is the number of observations of each model.
∗∗∗, ∗∗, and ∗ denote significance at the 0.01, 0.05, and 0.10 levels.

that firms in Turkey follow a pure residual policy (i.e., he reports a SOA of 1.0) before and after a change in regulation
that took place in 1995 that exempted firms from paying a minimum mandatory dividend. Even though the regulation shift
should have prompted firms listed on the Istanbul Stock Exchange to adopt more flexible dividend policies these firms stuck
to an unstable dividend policy. Consequently, smoothing (omitting) dividends appears less (more) prevalent in emerging
markets which often score poorly on rule of law compliance.
In all, we find that firms in the region adjust dividends, more swiftly than their U.S. counterparts, to positive and negative
shocks in earnings. A higher alignment between management and shareholders in an environment of high concentration of


J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

207

ownership as well as a lower concern by Latin American managers of the impact of dividend policy changes on firm value
could explain our results. In addition, we expand the international evidence on the positive relationship between SOA and
the extent of rule of law compliance, in line with previous studies.
Target payouts reported in Panel C of Table 3 are roughly consistent (but somewhat smaller) than those reported in Panel
B of Table 2. Yet again, firms in countries with higher rule of law scores reward their investors with richer dividends.
The bottom panel of Table 3 reports an alternative model of Eq. (7). The country dummies are replaced by the rule of
law index. Confirming our previous findings the coefficient of the governance index is positive (indeed, in 13 out of 18 years
the coefficient is positive) and significant, implying that countries with a higher governance score tend to have a lower SOA.
4. Robustness checks
In this section we discuss several robustness tests. The main focus of the tests is to examine whether changes in the
estimation period or in our regression specifications have any impact on our conclusions.
Using similar specifications to those in Table 3, Table 4 reports our estimates of the speed of adjustment, the target

payout, and the impact of rule of law compliance on dividend payments for two sub-periods. The first period extends from
1995 to 2003, and the second covers from 2004 to 2013. We examine the stability of our coefficients or estimates of interest
before and after the crisis in Argentina that was triggered by an abrupt devaluation of the Argentinean peso on December
of 2001.
In the first four panels of Table 4 we observe several interesting patterns. In the second period all countries raised the
target payout with respect to the first except for Argentina (possibly as a consequence of the negative effects of the crisis on
Argentinean firms’ profitability). For example, under specification e. Colombian firms increased the target payout from 0.24
to 0.45 (for an 88% increase). Similar to our findings in Table 3, we document a positive relationship between the standing
of a country in terms of the level of law enforcement and the target payout. For example, in 2002–2013, firms in Chile,
Brazil, and Argentina showed a higher target payout that firms located in countries with lower rule of law scores (Colombia,
Peru, and Mexico).
Focusing on the speed of adjustment across sub-periods, we document a general decrease in SOA for all countries except
Argentina. It seems that most firms in the region pursued a less volatile dividend policy on the second half of the sample. On
the other hand, Argentinean firms pursued a slightly more erratic dividend policy after the crisis. Furthermore, this higher
dividend volatility coincided with a significant drop in 2002 in Argentina’s score on rule of law abidance (the score remained
significantly lower, with respect to pre-crisis levels, until the end of the sample). Our findings for Argentina reinforce the
idea of a negative relationship between the level of law compliance and the velocity in which firms alter their dividends as
a response to shocks in profits.
In Panel E and Panel F of Table 4 we replace again the countries dummies for the rule of law indicator. In our analysis
we will focus on the coefficient on ADt ∗ GIt+1 . In the first period the coefficient is positive, however, in none of the specit+1

fications, the coefficient is statistically significant. During the second period (2002–2013) the coefficients on rule of law are
positive and higher than those for the first period. Importantly, the coefficient on the interaction variable to account for rule
of law effect is significant. In all, the effect of rule of law on dividend policy (and in particular on the speed of adjustment)
appears to show more strongly in the second half of our sample.
We conduct additional robustness checks not reported in tables. We include industry dummies in Eq. (7) (Table 2) with
similar qualitative results. Furthermore, we proxy country governance in Table 3 with a voice and accountability (VA) indicator instead of a rule of law index. VA tries to capture the degree of freedom of expression within a country. In short,
our main findings of a positive (negative) effect of country governance on the target payout (speed of adjustment) remain
unaltered.
In a world with frictions (e.g., frictions related to trading costs and microstructure effects) dividends are possibly a less

costly option for shareholders (than selling their stocks) to obtain cash from their investments in the firm. Banerjee et al.
(2007) find support for the notion of a substitution role of liquidity and dividends since that less liquid firms are more
likely to pay dividends than more liquid firms. In this untabulated robustness check, we examine whether a firm’s liquidity
affects its dividend decisions. To this end, we use Amihud’s (2002) illiquidity measure (the yearly average of the ratio of the
absolute daily return over daily dollar volume) to proxy for liquidity effects. When included in Tables 2 and 3, we observe no
statistically significant effect of illiquidity on the target payout and the speed of adjustment (the magnitude and significance
of the remaining variables continues to be qualitatively similar). Perhaps dividend policies of Latin American firms are more
reactive to shocks in aggregate or overall liquidity rather than to changes in the liquidity of the firm’s shares. Examining
this last assertion, nevertheless, is beyond the scope of this paper.
5. Concluding remarks
We contribute to the literature by analyzing dividend payment decisions of firms in six Latin American countries from
1995 to 2013. Based upon the classic Lintner model (1956), and examining the predictions of three guiding theories (pecking
order model, trade-off model and the lifecycle theory of dividends), our analysis highlights the importance of including both
firm and country specific factors when analyzing how firms adjust their dividends after changes in earnings.


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J. Benavides et al. / Finance Research Letters 17 (2016) 197–210
Table 4
Robustness checks.
Panel A Speed of Adjustment (1995–2003)

Argentina
Brazil
Chile
Colombia
Mexico
Peru

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.20
0.39
0.24
0.35
0.33
0.18

0.30
0.45
0.41
0.39
0.52
0.42

0.29
0.45
0.41
0.42
0.65
0.47

0.33
0.48
0.46
0.47
0.71
0.49

0.32
0.51
0.45
0.51
0.79
0.58

Panel B Speed of adjustment (2004–2013)

Argentina
Brazil
Chile
Colombia
Mexico
Peru

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.32
0.10
0.08
0.05
0.27
0.25

0.39
0.15
0.17
0.19
0.48
0.35

0.42
0.14
0.18
0.16
0.48
0.36

0.44
0.18
0.23
0.30
0.55

0.36

0.45
0.20
0.23
0.26
0.52
0.38

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.44
0.23
0.37
0.25
0.27
0.48

0.35
0.23
0.26
0.27

0.20
0.25

0.36
0.23
0.25
0.25
0.16
0.22

0.31
0.21
0.22
0.21
0.14
0.21

0.38
0.24
0.27
0.24
0.15
0.21

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

0.40
1.31
1.52
2.79
0.48
0.52

0.29
0.77
0.66
0.60
0.24
0.32

0.28
0.86
0.64
0.72
0.24
0.32

0.24
0.60
0.47
0.35
0.19

0.30

0.26
0.58
0.52
0.45
0.22
0.31

Panel C Target payout (1995–2003)

Argentina
Brazil
Chile
Colombia
Mexico
Peru

Panel D Target payout (2004–2013)

Argentina
Brazil
Chile
Colombia
Mexico
Peru

Panel E Estimates with governance indicators (1995–2003)
Specification:

a. No interaction

b. No leverage

c. Book leverage

d. Market leverage

e. Retained earnings

Intercept
NIt / At + 1
At + 1 / At + 1
Dt /At + 1
Dt /At + 1 ∗ GIt
R2
N
Firms

0.001∗∗
0.085∗∗∗
0.001
−0.280∗∗∗
0.037
0.168
2,155
567

0.003∗∗∗
0.094∗∗

−0.001
−0.384∗∗∗
−0.003
0.249
1,829
499

0.003∗∗∗
0.094∗∗∗
−0.001
−0.406∗∗∗
0.007
0.267
1,806
496

0.004∗∗∗
0.094∗∗
−0.002
−0.446∗∗∗
0.0 0 0
0.284
1,805
494

0.003∗∗∗
0.113∗
−0.001
−0.462∗∗∗
0.033

0.308
1,797
493

c. Book leverage

d. Market leverage

e. Retained earnings

Panel F Estimates with governance indicators (2002–2013)
Specification:
Intercept
NIt / At + 1
At + 1 / At + 1
Dt /At + 1
Dt /At + 1 ∗ GIt
R2
N
Firms

a. No interaction
0.0 0 0
0.123∗∗∗
0.0 0 0
−0.135∗∗∗
0.057∗∗
0.094
2,819
588

b. No leverage
0.003∗∗

0.112∗∗∗
−0.005
−0.218∗∗∗
0.057∗
0.167
2,587
570

0.003∗∗

0.118∗∗∗
−0.006
−0.220∗∗∗
0.054∗
0.179
2,564
565

0.004∗∗∗

0.003∗∗
0.123∗∗∗
−0.004
−0.271∗∗∗
0.070∗∗
0.207

2,502
558

0.108∗∗∗
−0.004
−0.249∗∗∗
0.054∗
0.191
2,556
566

Note: The data is from public Latin-American firms in six countries and it covers seventeen years (1995–2013). The depent+1
„ the change in dividends for fiscal year t + 1 versus year t divided by assets in year t + 1. We split the
dent variable is ADt+1
dataset in two periods: period a. goes from 1995 to 2003 and period b. goes from 2004 to 2013. Panel A to Panel D present
t
. Panel A and Panel
SOA and TP from pooled panel regressions of Eq. (6) that include country dummies interacted with ADt+1
B present the speed of adjustment per country, which is the negative of the sum of the slope on

Dt
At+1

and the dci , for pe-

riods a. and b. respectively. The implied target payout in Panel C (period a.) and Panel D (period b.) is the slope on
vided by the speed of adjustment. The slope on

N It
At+1

is the average across years of a1 + a2 Mn( MAVt t ) + a3 Mn( EStt ) + a4 Mn(

N It
At+1
P P Nt
At

di-

)+

a5 Mn(ln(At ) ) + a6 Mn(Levt+1 ) + a7 Mn( RAEtt ), where Mn(.) is the sample mean of a variable, ai are the regression coefficients from
Eq. (6) and Levt+1 is either book leverage or market leverage in t + 1. Meanwhile, the slope on

Dt
At+1

is the average across years

of b1 + b2 Mn( MAVt t ) + b3 Mn( EStt ) + b4 Mn( PAPt Nt ) + b5 Mn(ln(At ) ) + b6 Mn(Levt+1 ) + b7 Mn( RAEtt ), where bi are the regression coefficients from Eq. (6). Panel D and Panel E shows regression results replacing country dummies with a governance indicator
t
for periods a. and b. respectively. We estimate coefficients’ significance based on standard errors
variable, interacted with ADt+1
clustering by time. R2 is the adjusted R2 , and N is the number of observations of each model. ∗∗∗, ∗∗, and ∗ denote significance
at the 0.01, 0.05, and 0.10 levels.


J. Benavides et al. / Finance Research Letters 17 (2016) 197–210

209

We find broad support for the common empirical predictions of the pecking order and trade-off models. More profitable
firms tend to pay a higher relative (e.g., with respect to assets) dividend while more indebted firms or firms with higher
investment needs are more likely to pay lower dividends. We do not find a significant effect of volatility (proxied by firm
size) on the dividend payout ratio. Contrary to predictions of the lifecycle theory of dividends, the effect of the earned
to contributed capital in the dividend payout is negative. We hypothesize that for the listed firms in the region paying
a generous dividend is not in their agenda since they have not yet exhausted their investment opportunities, their high
ownership concentration and, consequently, the very low frequency of new financing through the equity markets.
Furthermore, we find differential target payouts and speeds of adjustments per country. Importantly, we find that firms
in countries with a higher rule of law compliance are more likely to pay a higher rate of dividends. This positive association
between the target payout and rule of law abidance supports the “outcome model” of the agency theory of dividends (La
Porta et al., 20 0 0). It appears that investors in more relatively law abiding countries (Argentina, Brazil, and Chile) are able
to extract higher dividends than those investors in countries where the rule of law is weaker (Colombia, Mexico, and Peru).
In terms of the speed of adjustment we document an indirect relationship between SOA and rule of law indices. In all, it
appears that firms in low rule of law countries are more prone to conduct a more erratic dividend policy than firms in high
rule of law countries. We thus extend previous evidence (Adaoglu (20 0 0) and Andres et al. (2009)) that suggests a close
link between how quickly firm adjust their dividends to changes in earnings, and country characteristics in which a firm is
located.
A series of robustness checks gives further credence to our results. We split the sample in two periods to isolate the
effect of the Argentinian crisis (in the end of 2001). It seems that the effect of rule of law on the dividend payout is
stronger and more significant in the second part of our sample. Nonetheless, our positive (negative) relationship between
the rule of law country scores and the target payout (speed of adjustment) holds both for the pre- and post-crisis periods.
Different variations in how we proxy for rule of law and the use of alternative estimation techniques directed us to the
same conclusions.
We leave for future research the effect on dividend policy of the ownership concentration and firm type (whether the
firm is owned by a family, it is a widely held corporation, or a state owned firm). Related research has studied the effect of
ownership concentration on dividends in a country level (Lefort and Walker, 2005). Nonetheless, research in cross country
differences and the effect of ownership type in dividend policies is scant and can shed light on how finance and governance
theories interact for emerging markets.

Repurchases are becoming popular among U.S. managers as a way to distribute excess cash (Brav et al., 2005; Brawn
and Sevic, 2015). Examining whether dividend payments and repurchases are concurrent or not (Fama and French, 2001),
and repurchase determinants in Latin America is also in our agenda to gain a more comprehensive understanding of payout
policy.
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