Description
The purpose of this paper is to show that economic policy impacts sovereign debt risk in
addition to economic performance
Journal of Financial Economic Policy
Economic freedom and sovereign credit ratings and default risk
Saurav Roychoudhury Robert A. Lawson
Article information:
To cite this document:
Saurav Roychoudhury Robert A. Lawson, (2010),"Economic freedom and sovereign credit ratings and
default risk", J ournal of Financial Economic Policy, Vol. 2 Iss 2 pp. 149 - 162
Permanent link to this document:
http://dx.doi.org/10.1108/17576381011070201
Downloaded on: 24 January 2016, At: 21:39 (PT)
References: this document contains references to 24 other documents.
To copy this document: [email protected]
The fulltext of this document has been downloaded 609 times since 2010*
Users who downloaded this article also downloaded:
David G. Tarr, (2010),"The political, regulatory, and market failures that caused the US financial
crisis: What are the lessons?", J ournal of Financial Economic Policy, Vol. 2 Iss 2 pp. 163-186 http://
dx.doi.org/10.1108/17576381011070210
Sven Blank, J onas Dovern, (2010),"What macroeconomic shocks affect the German banking system?:
Analysis in an integrated micro-macro model", J ournal of Financial Economic Policy, Vol. 2 Iss 2 pp.
126-148 http://dx.doi.org/10.1108/17576381011070193
J ames Barth, J ohn J ahera, (2010),"US enacts sweeping financial reform legislation", J ournal of Financial
Economic Policy, Vol. 2 Iss 3 pp. 192-195 http://dx.doi.org/10.1108/17576381011085412
Access to this document was granted through an Emerald subscription provided by emerald-srm:115632 []
For Authors
If you would like to write for this, or any other Emerald publication, then please use our Emerald for
Authors service information about how to choose which publication to write for and submission guidelines
are available for all. Please visit www.emeraldinsight.com/authors for more information.
About Emerald www.emeraldinsight.com
Emerald is a global publisher linking research and practice to the benefit of society. The company
manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as
providing an extensive range of online products and additional customer resources and services.
Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee
on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive
preservation.
*Related content and download information correct at time of download.
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Economic freedom and sovereign
credit ratings and default risk
Saurav Roychoudhury
School of Management and Leadership, Capital University,
Columbus, Ohio, USA, and
Robert A. Lawson
Department of Finance, College of Business, Auburn University,
Auburn, Alabama, USA
Abstract
Purpose – The purpose of this paper is to show that economic policy impacts sovereign debt risk in
addition to economic performance.
Design/methodology/approach – Regression analysis was employed to determine the factors that
contribute to sovereign bond ratings and bond spreads for a sample of 93 countries from 2000 to 2006.
Findings – After controlling for common factors like per capita gross domestic production, growth,
and political regime, the results suggest that a two unit (or a 2.4 standard deviation) drop in the
economic freedom index represents approximately a 50 percent higher cost of borrowing for a country.
Originality/value – The paper contributes to the empirical literature on sovereign credit risk by
identifying factors found to be the most signi?cant in determining sovereign credit ratings and bond
spreads.
Keywords National economy, Risk analysis, Bonds, Borrowing, Fiscal policy
Paper type Research paper
1. Introduction
With the unfolding sovereign debt crisis in Greece and other European countries as well
as increasing concern about the ability of the US Government to carry its ever-increasing
debt load into the future, it is all the more important to develop an increased
understanding of the root causes of such crises.
The credit ratings of sovereign bonds re?ect anevaluation of a national government’s
willingness and ability to repay its debts. These ratings are given considerable attention
because some of the largest issuers on the international capital markets are
governments, and these assets represent the backbone of the world’s ?nancial
system. As such defaults on sovereign debt can and have real economic consequences.
This paper contributes to the empirical literature on sovereign credit risk by identifying
factors that we ?nd to be the most signi?cant in determining sovereign credit ratings
and bond spreads.
2. Literature review
The sovereign credit ratings are an important determinant for foreign institutional
investment and foreign direct investment. It has been found that the ?ows of capital
fromrich to poor countries are impacted by sovereign default risk (Reinhart and Rogoff,
2004). Sovereign credit ratings have been found to be strongly related to the cost of
government borrowing (Butler and Fauver, 2006). The ratings also affect the credit
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
Sovereign credit
ratings and
default risk
149
Journal of Financial Economic Policy
Vol. 2 No. 2, 2010
pp. 149-162
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381011070201
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
ratings and cost of borrowing of a large number of other borrowers of the same country.
The rating agencies generally do not assign ratings to debt issuers that are higher than
their home country’s sovereign rating; therefore, sovereign ratings in?uence the ratings
given to local municipalities, provincial governments, and ?rms headquartered
within the same country. This directly impacts the ability of ?rms in that country to
access international capital markets (Martell, 2005). The sovereign bond yields tend to
rise as ratings fall, re?ecting the rise in default risk premium (Cantor and Packer, 1996).
Sovereign ratings also affect the required rate of return on the equities as we would
expect the sovereign equity risk premium to be wider than the sovereign bond default
spread since stocks are riskier than bonds (Damodaran, 2010). Consequently, sovereign
bond ratings are found to be strong predictors of a country’s equity market
returns (Erb et al., 1996). For emerging market economies, downgrades in sovereign
rating led to a 2 percent increase in average bond yield spreads and about 1 percent
decrease in average stock returns (Kaminsky and Schmukler, 2002). Foreign
currency rating downgrades are associated with signi?cant negative wealth effects
(Brooks et al., 2004). There is also some evidence of negative spillover effects in the
regional emerging economies when a neighboring emerging economy is downgraded
(Kraeussl, 2003).
In recent years, empirical measures of the quality of institutions and policies have
greatly enhanced the ability of researchers to examine the impact of the institutional
environment on economic performance (IMF, 2005). One such measure is the Economic
Freedom of the World (EFW) index by Gwartney and Lawson (2008). The EFW index
is designed to measure the consistency of a jurisdiction’s institutions and policies with
economic freedom. In order to achieve a high rating, a jurisdiction must provide secure
protection of privately owned property, evenhanded enforcement of contracts, and
a stable monetary environment. It also must keep taxes low, refrain from creating
barriers to both domestic and international trade, and rely more fully on markets rather
than the political process to allocate goods and resources.
The EFW index has been shown to be highly correlated with economic growth
and other measures of economic performance in dozens of studies (Berggren, 2003;
De Haan et al., 2006).
Comparatively few empirical papers have utilized the EFW index in ?nance. In the
area of macro-?nance Gwartney et al. (2006) ?nd that both the quantity and
productivity of investment are greater when economic freedom, measured by the EFW
index, is greater and increasing. Using the EFW index, Lothian (2006) ?nds that “good
policies – pursuit of price stability, fewer direct investments, and sound institutional
structures – are accompanied by higher capital ?ows.” On a more micro-?nance level,
Boubakri et al. (2005) and D’Souza et al. (2005) use certain components of the EFW
index, both ?nding that the stock performance of privatized state-owned enterprises
was better in countries with greater market liberalization.
The EFW index was used to build a stock portfolio by Stocker (2005) who argued
that “the rate of increase in economic freedom is directly related to equity returns and
that an investment strategy based on economic freedom earned attractive investment
returns.” A related study by Roychoudhury and Lawson (2008) found evidence that
?rms located in US states with increasing economic freedom experience higher stock
market returns.
JFEP
2,2
150
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
3. Data
We utilize the Moody’s long-term foreign currency sovereign bond rating system[1]
which has rating categories ranging from Aaa down to D (for default). A rating of Baa3
and above is regarded as an investment grade rating. Table I lists the number of
observations in each of the categories; note that not all of Moody’s rating categories
are represented in our data set. If the country has bonds denominated in US dollars, the
sovereign bond spreads are estimated by looking at the Moody’s ratings and the
associated default spreads over the ten-year US Treasury bond. For countries which do
not have government bonds denominated in US dollars but are rated by Moody’s, we use
the typical default spread for countries that have the same Moody’s rating. This method
is followed in Damodaran (2010), based on the assumption that countries with the same
sovereign credit rating will have similar default risk. The credit default swaps (CDS)
markets for countries that yield measures of default spreads may be more updated and
precise than bond default spreads data (Damodaran, 2010), but the sovereign CDS
market data is available only fromthe end of 2004. The data on Moody’s credit ratings as
well as the default spread is obtained from Aswath damodaran’s web site at: http://
pages.stern.nyu.edu/,adamodar/
The EFW index published by the Fraser Institute and the Heritage Foundation/Wall
Street Journal’s index of economic freedom are the two most widely used measures of
economic freedom. The methodologies to construct the two indices are actually very
different. We use the EFW index as it is more precise and transparent (Gwartney and
Lawson, 2003) and has been more widely cited in the literature (De Haan et al., 2006).
However, in spite of their methodological differences the country rankings of the
Heritage/Wall Street Journal and EFW indexes are highly correlated (Hanke and
Walters, 1997).
The EFW index measures the degree of economic freedom present in ?ve major
areas:
(1) Size of government: expenditures and taxes, enterprises.
(2) Legal structure and security of property rights.
(3) Access to sound money.
Investment grade Below investment grade
Aaa 116 Ba1 35
Aaa3 1 Ba2 29
Aa1 17 Ba3 15
Aa2 16 B1 32
Aa3 15 B2 30
A1 32 B3 29
A2 55 Caa1 12
A3 24 Caa2 2
Baa1 42 Ca 2
Baa2 31
Baa3 36
Note: Moody’s sovereign ratings are obtained from Aswath Damodaran’s web site at: http://pages.
stern.nyu.edu/,adamodar/ at the Stern School of Business at New York University
Table I.
Moody’s sovereign
ratings (2000-2006)
Sovereign credit
ratings and
default risk
151
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
(4) Freedom to trade internationally.
(5) Regulation of credit, labor, and business.
Within the ?ve major areas, there are 23 components incorporated into the index. Many
of those components are themselves made up of sub-components. Each component and
sub-component is placed on a scale from 0 to ten that re?ects the distribution of the
underlying data. The subcomponent ratings are averaged to determine each component.
In turn, the ?ve area ratings are averaged to derive the summary rating for each country.
On a scale of 0 to ten, a higher EFW score implies better economic freedom. For our
sample, the EFWindex has mean score of 6.84 with a high of 8.68 for Singapore (in 2005)
and a low of 3.99 for Venezuela (in 2003). The scores on the components and
sub-components of the EFW index for each country are provided in the annual EFW
Reports. Appendix 1 lists all the areas, components and sub-components of the EFW
index. This paper uses the chain-linked version of the EFW index which is the most
consistent index when doing times-series or longitudinal studies.
For the control variables, we obtain the real per capita gross domestic production
(GDP) data (based on purchasing power parity) and the growth rate of real per capita
GDP. The polity variable measures the level of democracy and the political regime
stability.
Our ?nal dataset contains information from 2000 to 2006 spanning 93 countries
with 571 useable observations. Descriptive statistics and source information of all the
quantitative variables can be found in Table II. The list of countries included in the
dataset can be found in Appendix 2.
4. Results
A very casual look at the data indicates that the EFW index and sovereign bond
ratings may be linked. For example, both the EFW and Moody’s ratings fell for
Argentina in 2001. The EFW for Argentina fell sharply by about 10 percent from the
2000 level and the Moody’s rating fell from B2 to Ca re?ecting a higher probability of
default. Incidentally, Argentina defaulted on its payment on January 3, 2002. Ukraine,
which is rated very low in the EFW index throughout the period of our analysis,
defaulted on its scheduled repayment of 16 percent Deutsche Mark-denominated bonds
in 2000. The Moody’s rating for Ukraine in 2000 and 2001 was Caa1 which indicated a
high probability of default.
For a graphical representation of the relationship, we divide our sample into four
quartiles based on their EFW levels. We then calculate the mean of the sovereign bond
spread for the two extreme quartiles. Figure 1 shows that there is a large difference in
sovereign bond spreads between the quartile having the lowest EFW rating and the
quartile having the highest EFW rating. The average spread between the extreme
quartiles is 545 basis points in our data period.
Since the EFW scores are available in consecutive years from 2000 onwards, our
sample period is from 2000 to 2006. Table II presents the summary of the variables
used in our analysis. The average per capita GDP is $16,621.50 with the lowest per
capita GDP of $1,720 and the highest of $70,762. The average GDP growth rate per
capita is 3.19 percent. The average sovereign bond spread over a ten-year US bond is
about 265 basis points.
JFEP
2,2
152
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Given the discrete and ordinal nature of the dependent variable (Moody’s sovereign
credit ratings), it is important to use an ordered probit estimator. We encode the
alphanumeric ratings into a linear scale assigning a number re?ecting the ordinal
nature of credit ratings[2]. A lower number on the scale re?ects a higher quality credit
rating. The advantage of using an ordered probit model is that it endogenously
determines the statistical break point within the linear scale. The regression
speci?cations are as follows:
Moody’s ratings
it
¼ b
0
þb
1
EFW
i;t21
þb
2
X
i;t
þb
3
CNTRY
i
þb
4
YEAR
t
þu
i;t
ð1Þ
Moody’s ratings
it
¼ b
0
þb
1
A
k;i;t21
þb
2
EFW_A
k;i;t21
þb
3
X
i;t
þb
4
CNTRY
i
þb
5
YEAR
t
þu
i;t
ð2Þ
where Moody’s ratings represent the dependent variable which is ordinal in nature,
EFW
i,t21
denotes the economic freedom level for country i in period t 2 1, A
k,i,t21
is
the EFW rating for area k, where (k ¼ 1, 2, . . . ,5), EFW_A
k,it21
is the EFW overall
rating re-calculated to omit that particular area k, X is a matrix of control variables,
CNTRY represents the matrix of country dummies and YEAR
t
represents the matrix
of year dummies[3]. The EFW variables are all included lagged one period to allow the
bond rating agency time to re?ect any changes in the EFW index and to minimize
endogeneity[4]. The set of control variables includes GDP per capita, growth rate of
Variable Mean SD Min. Max. n
Per capita GDP (in ’000s of ppp$) 16.6215 12.52371 1.72 70.76 571
Growth rate of per capita GDP 3.19% 3.31% 212.52% 28.54% 571
Sovereign bond spreads 2.65% 2.94% 0.00% 13.50% 571
Polity 6.6025 5.334883 29 10 571
EFW overall index 6.8429 0.809133 3.99 8.68 571
Area 1: size of government 6.1557 1.43636 2.41 9.25 571
Area 2: legal structure and property rights 6.1542 1.898765 1.43 9.62 571
Area 3: access to sound money 8.4079 1.416655 2.71 9.84 571
Area 4: freedom to trade internationally 7.2464 0.818831 4.29 9.37 571
Area 5: regulation of credit, labor, and business 6.2500 0.881329 3.95 8.7 571
EFW: all areas except Area 1 6.984623 1.025108 3.8 8.92 571
EFW: all areas except Area 2 7.074764 0.702775 4.59 8.78 571
EFW: all areas except Area 3 6.438581 0.768421 3.84 8.41 571
EFW: all areas except Area 4 6.73648 0.886781 3.7 8.68 571
EFW: all areas except Area 5 6.980158 0.843366 4.04 8.9 571
Notes: The per capita GDP and growth rate data were obtained from the World Bank’s World
Development Indicators web site at: http://.go.worldbank.org/6HAYAHG8H0 The Moody’s credit
ratings and the sovereign bond spreads were obtained from Aswath Damodaran’s web site at: http://
pages.stern.nyu.edu/,adamodar/ The sovereign bond spread is the difference between the ten-year
sovereign bond rate of country and the ten-year bond rate. The political regime characteristics and
transitions or the polity data were obtained from the Polity IV Project data at: www.systemicpeace.org
The Polity data is based on a 21-point scale ranging from 210 (hereditary monarchy) to þ10
(consolidated democracy). The Polity conceptual scheme is unique in that it examines concomitant
qualities of democratic and autocratic authority in governing institutions, rather than discreet and
mutually exclusive forms of governance. The EFW index and the sub-areas are available from the
database maintained by the Fraser Institute, www.freetheworld.com
Table II.
Descriptive statistics
Sovereign credit
ratings and
default risk
153
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
per capita GDP, and the Polity IV democratic/autocratic measure. Though the
explanatory and control variables may seem to be closely related we do not ?nd any
problems due to multicollinearity and our coef?cient estimates were quite precise[5].
The results are presented in Table III. Column (1) reports the ordered probit
regression results for equation (1). The variables behave as expected. The lagged EFW
index, the per capita GDP, and the growth rate of GDP all have negative coef?cients
which indicate that an increase in the respective variable is associated with a better bond
rating. The polity variable was negative as expected but insigni?cant throughout.
Columns (2)-(6) in Table III showthe results of equation (2) isolating the impact of each of
the ?ve EFWindex areas. In no case do we ?nd the individual area to be signi?cant, but
the overall index, omitting the respective area, was signi?cant and negative as expected
in four of ?ve cases. In Column (4) we ?nd that neither the Area 3 (sound money) rating
nor the corresponding overall index is signi?cant. However, Column (7) estimates the
impact of just component 3C (current in?ation). The component 3C takes on a higher
value if in?ation is lower. The coef?cient is negative and signi?cant as expected
indicating the better (i.e. lower) in?ation corresponds with better bond ratings. Because
interpreting ordered probit coef?cients is comparatively dif?cult and because the
ensuing results for sovereign bond spreads are qualitatively similar, we will reserve any
discussion of the quantitative magnitude of the results for that model.
Next, we look at the EFW index and its ?ve areas as related to the sovereign bond
spread over US ten-year Treasury bonds. There are many countries, e.g. most
organisation for economic co-operation and development countries, where the sovereign
bond spread vs US Treasuries is zero, and thus tobit is appropriate as it allows for the
censored nature of the dependent variable. The regression equations we estimate are:
Country spread
i;t
¼ b
0
þb
1
EFW
i;t21
þb
2
X
i;t
þb
3
CNTRY
i
þb
4
YEAR
t
þj
i;t
ð3Þ
Figure 1.
Difference in bond spread
between countries with
high EFW index and low
EFW index
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
P
e
r
c
e
n
t
a
g
e
2000 2001 2002 2003 2004 2005 2006
Sovereign bond spread (high EFW)
Sovereign bond spread (low EFW)
Notes: The countries are sorted into four quartiles based on their
EFW levels. The “high EFW” is the quartile with the highest EFW
scores and “low EFW” is the quartile with the lowest EFW scores.
The sovereign bond spreads are the average bond spreads in the
two respective quartiles. The data sovereign bond spreads were
obtained from Aswath Damodaran’s web site at: http://pages.stern.
nyu.edu/~adamodar/
JFEP
2,2
154
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
D
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
¼
M
o
o
d
y
’
s
s
o
v
e
r
e
i
g
n
c
r
e
d
i
t
r
a
t
i
n
g
s
(
1
)
(
2
)
(
3
)
(
4
)
(
5
)
(
6
)
(
7
)
E
F
W
o
v
e
r
a
l
l
i
n
d
e
x
(
t
2
1
)
2
0
.
8
9
6
6
*
*
*
(
0
.
3
3
9
8
)
P
e
r
c
a
p
i
t
a
G
D
P
(
i
n
’
0
0
0
s
o
f
$
)
2
0
.
4
1
6
0
*
*
*
(
0
.
0
8
0
5
)
2
0
.
4
0
6
4
*
*
*
(
0
.
0
8
1
4
)
2
0
.
4
0
0
4
*
*
*
(
0
.
0
8
1
4
)
2
0
.
4
1
0
1
*
*
*
(
0
.
0
8
1
1
)
2
0
.
4
0
6
7
*
*
*
(
0
.
0
8
1
1
)
2
0
.
4
0
8
1
*
*
*
(
0
.
0
8
1
3
)
2
0
.
4
0
3
9
*
*
*
(
0
.
0
8
1
0
)
G
r
o
w
t
h
r
a
t
e
p
e
r
c
a
p
i
t
a
G
D
P
2
7
.
2
3
1
6
*
*
(
3
.
2
0
2
6
)
2
6
.
8
8
9
0
*
*
(
3
.
2
0
5
0
)
2
7
.
2
2
7
4
*
*
(
3
.
2
4
3
4
)
2
7
.
8
9
3
6
*
*
(
3
.
3
0
5
8
)
2
6
.
8
6
2
3
*
*
(
3
.
2
3
4
9
)
2
6
.
7
1
2
3
*
*
(
3
.
2
0
7
6
)
2
8
.
6
6
5
0
*
*
*
(
3
.
3
5
3
5
)
P
o
l
i
t
y
2
0
.
0
1
1
3
(
0
.
0
7
9
4
)
2
0
.
0
1
2
7
(
0
.
0
7
9
5
)
2
0
.
0
1
4
9
(
0
.
0
7
9
5
)
2
0
.
0
1
2
7
(
0
.
0
7
9
5
)
2
0
.
0
1
6
5
(
0
.
0
8
0
3
)
2
0
.
0
0
9
1
(
0
.
0
8
1
7
)
2
0
.
0
0
3
6
(
0
.
0
7
9
5
)
A
r
e
a
1
:
s
i
z
e
o
f
g
o
v
e
r
n
m
e
n
t
(
t
2
1
)
0
.
0
6
9
8
(
0
.
2
2
8
0
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
1
(
t
2
1
)
2
0
.
9
6
7
4
*
*
(
0
.
3
9
1
1
)
A
r
e
a
2
:
l
e
g
a
l
s
t
r
u
c
t
u
r
e
a
n
d
p
r
o
p
e
r
t
y
r
i
g
h
t
s
(
t
2
1
)
0
.
2
3
4
3
(
0
.
2
3
2
6
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
2
(
t
2
1
)
2
0
.
9
5
6
5
*
*
*
(
0
.
3
6
7
3
)
A
r
e
a
3
:
a
c
c
e
s
s
t
o
s
o
u
n
d
m
o
n
e
y
(
t
2
1
)
2
0
.
2
8
2
7
(
0
.
1
9
3
3
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
3
(
t
2
1
)
2
0
.
3
0
8
6
(
0
.
5
3
0
8
)
2
0
.
1
9
4
3
(
0
.
5
3
8
7
)
A
r
e
a
4
:
f
r
e
e
d
o
m
t
o
t
r
a
d
e
i
n
t
e
r
n
a
t
i
o
n
a
l
l
y
(
t
2
1
)
0
.
0
8
8
9
(
0
.
2
7
2
4
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
4
(
t
2
1
)
2
0
.
9
1
2
6
*
*
(
0
.
3
8
0
6
)
A
r
e
a
5
:
r
e
g
u
l
a
t
i
o
n
o
f
c
r
e
d
i
t
,
l
a
b
o
r
,
a
n
d
b
u
s
i
n
e
s
s
(
t
2
1
)
0
.
0
3
6
4
(
0
.
2
5
6
4
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
5
(
t
2
1
)
2
0
.
8
5
7
2
*
*
(
0
.
3
9
9
4
)
A
r
e
a
3
C
(
t
2
1
)
2
0
.
2
9
0
1
*
*
*
(
0
.
1
0
9
5
)
A
r
e
a
3
(
t
2
1
)
w
i
t
h
o
u
t
3
C
(
t
2
1
)
2
0
.
1
2
7
2
(
0
.
1
4
9
7
)
P
s
e
u
d
o
R
2
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
O
b
s
e
r
v
a
t
i
o
n
s
4
8
9
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
;
s
t
a
n
d
a
r
d
e
r
r
o
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
;
a
l
l
v
a
r
i
a
b
l
e
s
a
r
e
d
e
?
n
e
d
i
n
T
a
b
l
e
I
I
;
h
i
g
h
e
r
v
a
l
u
e
s
i
n
A
r
e
a
3
C
i
m
p
l
i
e
s
l
o
w
e
r
i
n
?
a
t
i
o
n
Table III.
Ordered probit analysis:
determinants of Moody’s
Sovereign Credit ratings
Sovereign credit
ratings and
default risk
155
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Country spread
i;t
¼ b
0
þb
1
A
k;i;t21
þb
2
EFW
A
k;i;t21
þb
3
X
i;t
þb
4
CNTRY
i
þb
5
YEAR
t
þj
i;t
ð4Þ
By following McDonald and Mof?tt (1980) we truncate the tobit regression at zero:
Sovereign bond spread
*
i;t
¼
Country spread
i;t
if Country spread
i;t
. 0
0 if Country spread
i;t
# 0
(
It is assumed that the error term, j , Nð0; s
2
I Þ and sovereign bond spread
*
i;t
is the
latent variable used in tobit estimation. We use the same set of seven equations as we did
in previous analysis replacing the sovereign bond rating dependent variable with the
sovereign default spread. The results are presented in Table IV.
The results are qualitatively similar in both Tables III and IV[6]. Column (1) reports
the basic regression results with the EFW overall index as the independent variable in
addition to the controls. The negative sign on the coef?cient indicates that the bond
default spread is lower as economic freedom is higher. The next columns, (3)-(6),
highlight the independent effect of the ?ve areas of the EFW index. Column (7) isolates
the impact of Component 3C (current in?ation) within Area 3 of the EFW index. As
before, we ?nd the individual areas to be insigni?cant in all speci?cations. The overall
index however is negative and signi?cant in each case as is the 3C variable.
The magnitude of the EFW index coef?cient was similar in all the regressions. In
Column (1), the coef?cient of 20.0126 indicates that a two unit difference in the EFW
rating (about 2.4 standard deviations or the difference between the market-oriented the
USA and Pakistan or between reforming China and autarkic Myanmar) corresponds to
a lower sovereign bond spread against US Treasuries of about 250 basis points. Given
that the average interest rate on the ten-year US Treasury bond was about 5 percent in
our dataset, this represents approximately a 50 percent higher cost of borrowing for a
two unit difference in the EFW rating.
5. Conclusion
The credit risk of sovereign debt is an important consideration in ?nancial markets
and has important real economic consequences in a number of areas. This paper ?nds
that countries with higher values on the EFW index, enjoy lower sovereign bond
default risk as measured by Moody’s credit ratings and by sovereign bond spreads
over ten-year US Treasury bonds.
Many of the relationships illustrated in the regressions above re?ect the impact
of economic freedom perhaps as it works through other variables such as increasing
economic growth, and political stability. We have controlled for a few commonly used
economic and political variables and we cannot claim that the controls are exhaustive.
However, the results presented appear to be robust to numerous alternate speci?cations.
No one area of the EFW index appears to stand out, with the possible exception of
Component 3C which re?ects current in?ation. This is consistent the argument made
by Lawson (2006) that economic freedom is a bundle that is dif?cult to disaggregate
either statistically or conceptually.
JFEP
2,2
156
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
D
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
¼
S
o
v
e
r
e
i
g
n
b
o
n
d
s
p
r
e
a
d
s
(
1
)
(
2
)
(
3
)
(
4
)
(
5
)
(
6
)
(
7
)
E
F
W
o
v
e
r
a
l
l
i
n
d
e
x
(
t
2
1
)
2
0
.
0
1
2
6
*
*
*
(
0
.
0
0
3
1
)
P
e
r
c
a
p
i
t
a
G
D
P
(
i
n
’
0
0
0
s
o
f
$
)
2
0
.
0
0
1
1
(
0
.
0
0
0
7
)
2
0
.
0
0
1
2
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
(
0
.
0
0
0
7
)
G
r
o
w
t
h
r
a
t
e
p
e
r
c
a
p
i
t
a
G
D
P
2
0
.
1
0
2
4
*
*
*
(
0
.
0
2
8
6
)
2
0
.
1
0
2
0
*
*
*
(
0
.
0
2
8
6
)
2
0
.
0
9
9
5
*
*
*
(
0
.
0
2
8
9
)
2
0
.
1
0
5
4
*
*
*
(
0
.
0
2
9
2
)
2
0
.
1
0
3
7
*
*
*
(
0
.
0
2
9
1
)
2
0
.
1
0
1
8
*
*
*
(
0
.
0
2
8
8
)
2
0
.
1
0
5
1
*
*
*
(
0
.
0
2
8
9
)
P
o
l
i
t
y
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
2
(
0
.
0
0
0
8
)
2
0
.
0
0
0
2
(
0
.
0
0
0
8
)
0
(
0
.
0
0
0
8
)
A
r
e
a
1
:
s
i
z
e
o
f
g
o
v
e
r
n
m
e
n
t
(
t
2
1
)
0
.
0
0
3
(
0
.
0
0
2
1
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
1
(
t
2
1
)
2
0
.
0
1
5
0
*
*
*
(
0
.
0
0
3
6
)
A
r
e
a
2
:
l
e
g
a
l
s
t
r
u
c
t
u
r
e
a
n
d
p
r
o
p
e
r
t
y
r
i
g
h
t
s
(
t
2
1
)
2
0
.
0
0
2
(
0
.
0
0
2
2
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
2
(
t
2
1
)
2
0
.
0
1
0
4
*
*
*
(
0
.
0
0
3
3
)
A
r
e
a
3
:
a
c
c
e
s
s
t
o
s
o
u
n
d
m
o
n
e
y
(
t
2
1
)
2
0
.
0
0
0
7
(
0
.
0
0
1
7
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
3
(
t
2
1
)
2
0
.
0
1
2
1
*
*
(
0
.
0
0
5
0
)
2
0
.
0
1
0
6
*
*
(
0
.
0
0
4
9
)
A
r
e
a
4
:
f
r
e
e
d
o
m
t
o
t
r
a
d
e
i
n
t
e
r
n
a
t
i
o
n
a
l
l
y
(
t
2
1
)
0
.
0
0
2
(
0
.
0
0
2
5
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
4
(
t
2
1
)
2
0
.
0
1
3
7
*
*
*
(
0
.
0
0
3
5
)
A
r
e
a
5
:
r
e
g
u
l
a
t
i
o
n
o
f
c
r
e
d
i
t
,
l
a
b
o
r
,
a
n
d
b
u
s
i
n
e
s
s
(
t
2
1
)
2
0
.
0
0
1
5
(
0
.
0
0
2
4
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
5
(
t
2
1
)
2
0
.
0
1
0
9
*
*
*
(
0
.
0
0
3
7
)
A
r
e
a
3
C
(
t
2
1
)
2
0
.
0
0
2
2
*
*
*
(
0
.
0
0
0
8
)
A
r
e
a
3
(
t
2
1
)
w
i
t
h
o
u
t
3
C
(
t
2
1
)
0
.
0
0
0
6
(
0
.
0
0
1
3
)
C
o
n
s
t
a
n
t
0
.
1
3
5
2
*
*
*
(
0
.
0
2
0
8
)
0
.
1
4
0
9
*
*
*
(
0
.
0
2
1
9
)
0
.
1
3
5
3
*
*
*
(
0
.
0
2
0
7
)
0
.
1
3
4
4
*
*
*
(
0
.
0
2
2
8
)
0
.
1
2
3
7
*
*
*
(
0
.
0
2
2
8
)
0
.
1
3
2
8
*
*
*
(
0
.
0
2
0
5
)
0
.
1
3
8
0
*
*
*
(
0
.
0
2
2
6
)
P
s
e
u
d
o
R
2
2
0
.
8
2
0
.
7
9
2
0
.
7
9
2
0
.
7
9
2
0
.
7
9
2
0
.
7
9
2
0
.
8
O
b
s
e
r
v
a
t
i
o
n
s
4
8
9
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
s
t
a
n
d
a
r
d
e
r
r
o
r
s
i
n
p
a
r
a
n
t
h
e
s
e
s
;
a
l
l
v
a
r
i
a
b
l
e
s
a
r
e
d
e
?
n
e
d
i
n
T
a
b
l
e
I
I
;
h
i
g
h
e
r
v
a
l
u
e
s
i
n
A
r
e
a
3
C
i
m
p
l
i
e
s
l
o
w
e
r
i
n
?
a
t
i
o
n
Table IV.
Tobit analysis:
determinants of
Sovereign Bond Spreads
Sovereign credit
ratings and
default risk
157
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Notes
1. Standard & Poors, Moody’s, and Fitch are the three main credit rating agencies which assign
letter ratings to a country’s sovereign debt. Ratings by different credit rating agencies for
foreign currency sovereign ratings are consistent with each though there are minor
inconsistencies.
2. We used the following seven rating categories: Aaa, Aa, A, Baa, Ba, B, and C. The results
when using all rating categories were substantively the same.
3. We experimented with alternative functional forms for the EFW index variable (quadratics
and high/middle/low dummy variable interactions) but ultimately rejected statistically the
non-linear forms. We included the change in the EFW index (DEFW ¼ EFW
t
2 EFW
t21
) as
an additional independent variable but also rejected its inclusion in the ?nal model on
statistical grounds. The core results were unaffected by these choices. Finally, we ran the
models as single-year cross-sections instead of as a panel and found the EFW index variable
to be negative and signi?cant in each individual year sample as well. The dataset is
available upon request for anyone wanting to verify our ?ndings.
4. We want to thank participants at the Auburn University Finance Department Seminar and
the Southwestern Finance Association meeting for this suggestion to used lagged values of
the EFW index.
5. The variance in?ation factor for each of our right-hand-side variable in our basic regression
is low with the highest being 1.91 for the lagged EFW index. Even in the regressions using
the EFW areas the highest VIF was 2.37 which is highly acceptable.
6. Per capita GDP was signi?cant in Table III but not in Table IV however.
References
Berggren, N. (2003), “The bene?ts of economic freedom: a survey”, Independent Review, Vol. 8
No. 2, pp. 193-211.
Boubakri, N., Cosset, J.C. and Guedhami, O. (2005), “Liberalization, corporate governance and the
performance of newly privatized ?rms”, Journal of Corporate Finance, Vol. 11, pp. 747-946.
Brooks, R., Faff, R.W., Hillier, D. and Hillier, J. (2004), “The national market impact of sovereign
rating changes”, Journal of Banking & Finance, Vol. 28, pp. 233-50.
Butler, A.W. and Fauver, L. (2006), “Institutional environment and sovereign credit ratings”,
Financial Management, Vol. 35 No. 3, pp. 53-79.
Cantor, R. and Packer, F. (1996), “Determinants and impact of sovereign credit ratings”, FRBNY
Economic Policy Review, October, pp. 37-54.
Damodaran, A. (2010), “Equity risk premiums (ERP): determinants, estimation and implications –
a post-crisis”, available at SSRN: http://ssrn.com/abstract¼1492717 (accessed
February 20, 2010).
De Haan, J., Lundstro¨m, S. and Sturm, J.E. (2006), “Market-oriented institutions and policies and
economic growth: a critical survey”, Journal of Economic Surveys, Vol. 20 No. 2, pp. 157-91.
D’Souza, J., Megginson, W. and Nash, R. (2005), “Effect of institutional and ?rm-speci?c
characteristics on post-privatization performance: evidence from developed countries”,
Journal of Corporate Finance, Vol. 11, pp. 747-66.
Erb, C.B., Harvey, C.R. and Viskanta, T.E. (1996), “Expected returns and volatility in 135
countries”, Journal of Portfolio Management, Vol. 22, pp. 46-58.
Gwartney, J. and Lawson, R. (2003), “The concept and measurement of economic freedom”,
European Journal of Political Economy, Vol. 19, pp. 405-30.
JFEP
2,2
158
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Gwartney, J. and Lawson, R. (2008), Economic Freedom of the World: 2008 Annual Report,
Fraser Institute, Vancouver.
Gwartney, J., Holcombe, R. and Lawson, R. (2006), “Institutions and the impact of investment on
growth”, Kyklos, Vol. 59 No. 2, pp. 255-73.
Hanke, S. and Walters, S. (1997), “Economic freedom, prosperity, and equality: a survey”,
Cato Journal, Vol. 17, pp. 117-46.
IMF (2005), World Economic Outlook: Building Institutions, International Monetary Fund,
Washington, DC.
Kaminsky, G. and Schmukler, S. (2002), “Emerging markets instability: do sovereign credit
ratings affect country risk and stock returns?”, World Bank Economic Review, Vol. 16,
pp. 171-95.
Kraeussl, R. (2003), Do changes in Sovereign Credit Ratings Contribute to Financial Contagion in
Emerging Market Crises?, CFS Working Paper No. 2003/22, Center for Financial Studies,
Frankfurt.
Lawson, R. (2006), “On testing the connection between economic freedom and growth”,
Econ Journal Watch, Vol. 3 No. 3, pp. 398-406.
Lothian, J.R. (2006), “Institutions, capital ?ows, and ?nancial integration”, Journal of
International Money and Finance, Vol. 25, pp. 358-69.
McDonald, J.F. and Mof?tt, R.A. (1980), “The uses of tobit analysis”, The Review of Economics
and Statistics, Vol. 62, pp. 318-87.
Martell, R. (2005), “The effect of sovereign credit rating changes on emerging stock markets”,
SSRN, available at: http://ssrn.com/abstract¼686375
Reinhart, C.M. and Rogoff, K.S. (2004), “Serial default and the ‘Paradox’ of rich-to poor capital
?ows”, American Economic Review, Vol. 94, pp. 53-8.
Roychoudhury, S. and Lawson, R.A. (2008), “Economic freedom and equity prices among US
states”, The Credit and Financial Management Review, Vol. 14 No. 4, pp. 33-46.
Stocker, M.L. (2005), “Equity returns and economic freedom”, Cato Journal, Vol. 25 No. 3, pp. 583-94.
Further reading
Beers, D.T. and Cavanaugh, M. (2004), “Sovereign credit ratings: a primer”, Standard & Poor’s
Ratings Direct, available at: www.2.standardandpoors.com/spf/pdf/products/SovRatings
Primer_sov.pdf
Appendix 1. The areas, components, and sub-components of the EFW index
Area 1. Size of government: expenditures, taxes, and enterprises
A. General government consumption spending as a percentage of total consumption.
B. Transfers and subsidies as a percentage of GDP.
C. Government enterprises and investment.
D. Top marginal tax rate:
i. top marginal income tax rate; and
ii. top marginal income and payroll tax rates.
Area 2. Legal structure and security of property rights
A. Judicial independence.
B. Impartial courts.
Sovereign credit
ratings and
default risk
159
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
C. Protection of property rights.
D. Military interference in rule of law and the political process.
E. Integrity of the legal system.
F. Legal enforcement of contracts.
G. Regulatory restrictions on the sale of real property.
Area 3. Access to sound money
A. Money growth.
B. Standard deviation of in?ation.
C. In?ation: most recent year.
D. Freedom to own foreign currency bank accounts.
Area 4. Freedom to trade internationally
A. Taxes on international trade:
i. revenues from trade taxes (percent of trade sector);
ii. mean tariff rate; and
iii. standard deviation of tariff rates.
B. Regulatory trade barriers:
i. non-tariff trade barriers; and
ii. compliance cost of importing and exporting.
C. Size of trade sector relative to expected.
D. Black-market exchange rates.
E. International capital market controls:
i. foreign ownership/investment restrictions; and
ii. capital controls.
Area 5. Regulation of credit, labor, and business
A. Credit market regulations:
i. ownership of banks;
ii. foreign bank competition;
iii. private sector credit; and
iv. interest rate controls/negative real interest rates.
B. Labor market regulations:
i. minimum wage;
ii. hiring and ?ring regulations;
iii. centralized collective bargaining;
iv. mandated cost of hiring;
v. mandated cost of worker dismissal; and
vi. conscription.
C. Business regulations:
i. price controls;
ii. administrative requirements;
JFEP
2,2
160
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
iii. bureaucracy costs;
iv. starting a business;
v. extra payments/bribes;
vi. licensing restrictions; and
vii. cost of tax compliance.
Appendix 2
1 Argentina
2 Armenia
3 Australia
4 Austria
5 Azerbaijan
6 Bahamas
7 Bahrain
8 Barbados
9 Belgium
10 Belize
11 Bolivia
12 Bosnia and Herzegovina
13 Botswana
14 Brazil
15 Bulgaria
16 Canada
17 Chile
18 China
19 Colombia
20 Costa Rica
21 Croatia
22 Cyprus
23 Czech Rep.
24 Denmark
25 Dominican Rep.
26 Ecuador
27 Egypt
28 El Salvador
29 Estonia
30 Fiji
31 Finland
32 France
33 Germany
34 Greece
35 Guatemala
36 Honduras
37 Hong Kong
38 Hungary
39 Iceland
40 India
41 Indonesia
42 Ireland
43 Israel
(continued)
Table AI.
List of countries
in our dataset
Sovereign credit
ratings and
default risk
161
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Corresponding author
Saurav Roychoudhury can be contacted at: [email protected]
44 Italy
45 Jamaica
46 Japan
47 Jordan
48 Kazakhstan
49 Kuwait
50 Latvia
51 Lithuania
52 Luxembourg
53 Malaysia
54 Malta
55 Mauritius
56 Mexico
57 Moldova
58 Morocco
59 The Netherlands
60 New Zealand
61 Nicaragua
62 Norway
63 Oman
64 Pakistan
65 Panama
66 Papua New Guinea
67 Paraguay
68 Peru
69 Philippines
70 Poland
71 Portugal
72 Romania
73 Russia
74 Singapore
75 Slovak Rep.
76 Slovenia
77 South Africa
78 South Korea
79 Spain
80 Sweden
81 Switzerland
82 Taiwan
83 Thailand
84 Trinidad and Tobago
85 Tunisia
86 Turkey
87 Ukraine
88 United Arab Emirates
89 The UK
90 The USA
91 Uruguay
92 Venezuela
93 Vietnam
Table AI.
JFEP
2,2
162
To purchase reprints of this article please e-mail: [email protected]
Or visit our web site for further details: www.emeraldinsight.com/reprints
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
This article has been cited by:
1. Sang-Heui Lee, Jay van Wyk. 2015. National institutions and logistic performance: a path analysis. Service
Business 9, 733-747. [CrossRef]
2. Ariel R. Belasen, Rik W. Hafer, Shrikant P. Jategaonkar. 2015. ECONOMIC FREEDOM AND STATE
BOND RATINGS. Contemporary Economic Policy 33:10.1111/coep.2015.33.issue-4, 668-677. [CrossRef]
3. Kun-Li Lin, Anh Tuan Doan, Shuh-Chyi Doong. 2015. Changes in ownership structure and bank
efficiency in Asian developing countries: The role of financial freedom. International Review of Economics
& Finance . [CrossRef]
4. Benjamin M. Blau, Tyler J. Brough, Diana W. Thomas. 2014. Economic freedom and the stability of
stock prices: A cross-country analysis. Journal of International Money and Finance 41, 182-196. [CrossRef]
5. Peter T. Calcagno, Justin D. Benefield. 2013. Economic freedom, the cost of public borrowing, and state
bond ratings. Journal of Financial Economic Policy 5:1, 72-85. [Abstract] [Full Text] [PDF]
6. Georgios E. Chortareas, Claudia Girardone, Alexia Ventouri. 2013. Financial freedom and bank efficiency:
Evidence from the European Union. Journal of Banking & Finance 37, 1223-1231. [CrossRef]
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
doc_136721483.pdf
The purpose of this paper is to show that economic policy impacts sovereign debt risk in
addition to economic performance
Journal of Financial Economic Policy
Economic freedom and sovereign credit ratings and default risk
Saurav Roychoudhury Robert A. Lawson
Article information:
To cite this document:
Saurav Roychoudhury Robert A. Lawson, (2010),"Economic freedom and sovereign credit ratings and
default risk", J ournal of Financial Economic Policy, Vol. 2 Iss 2 pp. 149 - 162
Permanent link to this document:
http://dx.doi.org/10.1108/17576381011070201
Downloaded on: 24 January 2016, At: 21:39 (PT)
References: this document contains references to 24 other documents.
To copy this document: [email protected]
The fulltext of this document has been downloaded 609 times since 2010*
Users who downloaded this article also downloaded:
David G. Tarr, (2010),"The political, regulatory, and market failures that caused the US financial
crisis: What are the lessons?", J ournal of Financial Economic Policy, Vol. 2 Iss 2 pp. 163-186 http://
dx.doi.org/10.1108/17576381011070210
Sven Blank, J onas Dovern, (2010),"What macroeconomic shocks affect the German banking system?:
Analysis in an integrated micro-macro model", J ournal of Financial Economic Policy, Vol. 2 Iss 2 pp.
126-148 http://dx.doi.org/10.1108/17576381011070193
J ames Barth, J ohn J ahera, (2010),"US enacts sweeping financial reform legislation", J ournal of Financial
Economic Policy, Vol. 2 Iss 3 pp. 192-195 http://dx.doi.org/10.1108/17576381011085412
Access to this document was granted through an Emerald subscription provided by emerald-srm:115632 []
For Authors
If you would like to write for this, or any other Emerald publication, then please use our Emerald for
Authors service information about how to choose which publication to write for and submission guidelines
are available for all. Please visit www.emeraldinsight.com/authors for more information.
About Emerald www.emeraldinsight.com
Emerald is a global publisher linking research and practice to the benefit of society. The company
manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as
providing an extensive range of online products and additional customer resources and services.
Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee
on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive
preservation.
*Related content and download information correct at time of download.
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Economic freedom and sovereign
credit ratings and default risk
Saurav Roychoudhury
School of Management and Leadership, Capital University,
Columbus, Ohio, USA, and
Robert A. Lawson
Department of Finance, College of Business, Auburn University,
Auburn, Alabama, USA
Abstract
Purpose – The purpose of this paper is to show that economic policy impacts sovereign debt risk in
addition to economic performance.
Design/methodology/approach – Regression analysis was employed to determine the factors that
contribute to sovereign bond ratings and bond spreads for a sample of 93 countries from 2000 to 2006.
Findings – After controlling for common factors like per capita gross domestic production, growth,
and political regime, the results suggest that a two unit (or a 2.4 standard deviation) drop in the
economic freedom index represents approximately a 50 percent higher cost of borrowing for a country.
Originality/value – The paper contributes to the empirical literature on sovereign credit risk by
identifying factors found to be the most signi?cant in determining sovereign credit ratings and bond
spreads.
Keywords National economy, Risk analysis, Bonds, Borrowing, Fiscal policy
Paper type Research paper
1. Introduction
With the unfolding sovereign debt crisis in Greece and other European countries as well
as increasing concern about the ability of the US Government to carry its ever-increasing
debt load into the future, it is all the more important to develop an increased
understanding of the root causes of such crises.
The credit ratings of sovereign bonds re?ect anevaluation of a national government’s
willingness and ability to repay its debts. These ratings are given considerable attention
because some of the largest issuers on the international capital markets are
governments, and these assets represent the backbone of the world’s ?nancial
system. As such defaults on sovereign debt can and have real economic consequences.
This paper contributes to the empirical literature on sovereign credit risk by identifying
factors that we ?nd to be the most signi?cant in determining sovereign credit ratings
and bond spreads.
2. Literature review
The sovereign credit ratings are an important determinant for foreign institutional
investment and foreign direct investment. It has been found that the ?ows of capital
fromrich to poor countries are impacted by sovereign default risk (Reinhart and Rogoff,
2004). Sovereign credit ratings have been found to be strongly related to the cost of
government borrowing (Butler and Fauver, 2006). The ratings also affect the credit
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
Sovereign credit
ratings and
default risk
149
Journal of Financial Economic Policy
Vol. 2 No. 2, 2010
pp. 149-162
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381011070201
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
ratings and cost of borrowing of a large number of other borrowers of the same country.
The rating agencies generally do not assign ratings to debt issuers that are higher than
their home country’s sovereign rating; therefore, sovereign ratings in?uence the ratings
given to local municipalities, provincial governments, and ?rms headquartered
within the same country. This directly impacts the ability of ?rms in that country to
access international capital markets (Martell, 2005). The sovereign bond yields tend to
rise as ratings fall, re?ecting the rise in default risk premium (Cantor and Packer, 1996).
Sovereign ratings also affect the required rate of return on the equities as we would
expect the sovereign equity risk premium to be wider than the sovereign bond default
spread since stocks are riskier than bonds (Damodaran, 2010). Consequently, sovereign
bond ratings are found to be strong predictors of a country’s equity market
returns (Erb et al., 1996). For emerging market economies, downgrades in sovereign
rating led to a 2 percent increase in average bond yield spreads and about 1 percent
decrease in average stock returns (Kaminsky and Schmukler, 2002). Foreign
currency rating downgrades are associated with signi?cant negative wealth effects
(Brooks et al., 2004). There is also some evidence of negative spillover effects in the
regional emerging economies when a neighboring emerging economy is downgraded
(Kraeussl, 2003).
In recent years, empirical measures of the quality of institutions and policies have
greatly enhanced the ability of researchers to examine the impact of the institutional
environment on economic performance (IMF, 2005). One such measure is the Economic
Freedom of the World (EFW) index by Gwartney and Lawson (2008). The EFW index
is designed to measure the consistency of a jurisdiction’s institutions and policies with
economic freedom. In order to achieve a high rating, a jurisdiction must provide secure
protection of privately owned property, evenhanded enforcement of contracts, and
a stable monetary environment. It also must keep taxes low, refrain from creating
barriers to both domestic and international trade, and rely more fully on markets rather
than the political process to allocate goods and resources.
The EFW index has been shown to be highly correlated with economic growth
and other measures of economic performance in dozens of studies (Berggren, 2003;
De Haan et al., 2006).
Comparatively few empirical papers have utilized the EFW index in ?nance. In the
area of macro-?nance Gwartney et al. (2006) ?nd that both the quantity and
productivity of investment are greater when economic freedom, measured by the EFW
index, is greater and increasing. Using the EFW index, Lothian (2006) ?nds that “good
policies – pursuit of price stability, fewer direct investments, and sound institutional
structures – are accompanied by higher capital ?ows.” On a more micro-?nance level,
Boubakri et al. (2005) and D’Souza et al. (2005) use certain components of the EFW
index, both ?nding that the stock performance of privatized state-owned enterprises
was better in countries with greater market liberalization.
The EFW index was used to build a stock portfolio by Stocker (2005) who argued
that “the rate of increase in economic freedom is directly related to equity returns and
that an investment strategy based on economic freedom earned attractive investment
returns.” A related study by Roychoudhury and Lawson (2008) found evidence that
?rms located in US states with increasing economic freedom experience higher stock
market returns.
JFEP
2,2
150
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
3. Data
We utilize the Moody’s long-term foreign currency sovereign bond rating system[1]
which has rating categories ranging from Aaa down to D (for default). A rating of Baa3
and above is regarded as an investment grade rating. Table I lists the number of
observations in each of the categories; note that not all of Moody’s rating categories
are represented in our data set. If the country has bonds denominated in US dollars, the
sovereign bond spreads are estimated by looking at the Moody’s ratings and the
associated default spreads over the ten-year US Treasury bond. For countries which do
not have government bonds denominated in US dollars but are rated by Moody’s, we use
the typical default spread for countries that have the same Moody’s rating. This method
is followed in Damodaran (2010), based on the assumption that countries with the same
sovereign credit rating will have similar default risk. The credit default swaps (CDS)
markets for countries that yield measures of default spreads may be more updated and
precise than bond default spreads data (Damodaran, 2010), but the sovereign CDS
market data is available only fromthe end of 2004. The data on Moody’s credit ratings as
well as the default spread is obtained from Aswath damodaran’s web site at: http://
pages.stern.nyu.edu/,adamodar/
The EFW index published by the Fraser Institute and the Heritage Foundation/Wall
Street Journal’s index of economic freedom are the two most widely used measures of
economic freedom. The methodologies to construct the two indices are actually very
different. We use the EFW index as it is more precise and transparent (Gwartney and
Lawson, 2003) and has been more widely cited in the literature (De Haan et al., 2006).
However, in spite of their methodological differences the country rankings of the
Heritage/Wall Street Journal and EFW indexes are highly correlated (Hanke and
Walters, 1997).
The EFW index measures the degree of economic freedom present in ?ve major
areas:
(1) Size of government: expenditures and taxes, enterprises.
(2) Legal structure and security of property rights.
(3) Access to sound money.
Investment grade Below investment grade
Aaa 116 Ba1 35
Aaa3 1 Ba2 29
Aa1 17 Ba3 15
Aa2 16 B1 32
Aa3 15 B2 30
A1 32 B3 29
A2 55 Caa1 12
A3 24 Caa2 2
Baa1 42 Ca 2
Baa2 31
Baa3 36
Note: Moody’s sovereign ratings are obtained from Aswath Damodaran’s web site at: http://pages.
stern.nyu.edu/,adamodar/ at the Stern School of Business at New York University
Table I.
Moody’s sovereign
ratings (2000-2006)
Sovereign credit
ratings and
default risk
151
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
(4) Freedom to trade internationally.
(5) Regulation of credit, labor, and business.
Within the ?ve major areas, there are 23 components incorporated into the index. Many
of those components are themselves made up of sub-components. Each component and
sub-component is placed on a scale from 0 to ten that re?ects the distribution of the
underlying data. The subcomponent ratings are averaged to determine each component.
In turn, the ?ve area ratings are averaged to derive the summary rating for each country.
On a scale of 0 to ten, a higher EFW score implies better economic freedom. For our
sample, the EFWindex has mean score of 6.84 with a high of 8.68 for Singapore (in 2005)
and a low of 3.99 for Venezuela (in 2003). The scores on the components and
sub-components of the EFW index for each country are provided in the annual EFW
Reports. Appendix 1 lists all the areas, components and sub-components of the EFW
index. This paper uses the chain-linked version of the EFW index which is the most
consistent index when doing times-series or longitudinal studies.
For the control variables, we obtain the real per capita gross domestic production
(GDP) data (based on purchasing power parity) and the growth rate of real per capita
GDP. The polity variable measures the level of democracy and the political regime
stability.
Our ?nal dataset contains information from 2000 to 2006 spanning 93 countries
with 571 useable observations. Descriptive statistics and source information of all the
quantitative variables can be found in Table II. The list of countries included in the
dataset can be found in Appendix 2.
4. Results
A very casual look at the data indicates that the EFW index and sovereign bond
ratings may be linked. For example, both the EFW and Moody’s ratings fell for
Argentina in 2001. The EFW for Argentina fell sharply by about 10 percent from the
2000 level and the Moody’s rating fell from B2 to Ca re?ecting a higher probability of
default. Incidentally, Argentina defaulted on its payment on January 3, 2002. Ukraine,
which is rated very low in the EFW index throughout the period of our analysis,
defaulted on its scheduled repayment of 16 percent Deutsche Mark-denominated bonds
in 2000. The Moody’s rating for Ukraine in 2000 and 2001 was Caa1 which indicated a
high probability of default.
For a graphical representation of the relationship, we divide our sample into four
quartiles based on their EFW levels. We then calculate the mean of the sovereign bond
spread for the two extreme quartiles. Figure 1 shows that there is a large difference in
sovereign bond spreads between the quartile having the lowest EFW rating and the
quartile having the highest EFW rating. The average spread between the extreme
quartiles is 545 basis points in our data period.
Since the EFW scores are available in consecutive years from 2000 onwards, our
sample period is from 2000 to 2006. Table II presents the summary of the variables
used in our analysis. The average per capita GDP is $16,621.50 with the lowest per
capita GDP of $1,720 and the highest of $70,762. The average GDP growth rate per
capita is 3.19 percent. The average sovereign bond spread over a ten-year US bond is
about 265 basis points.
JFEP
2,2
152
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Given the discrete and ordinal nature of the dependent variable (Moody’s sovereign
credit ratings), it is important to use an ordered probit estimator. We encode the
alphanumeric ratings into a linear scale assigning a number re?ecting the ordinal
nature of credit ratings[2]. A lower number on the scale re?ects a higher quality credit
rating. The advantage of using an ordered probit model is that it endogenously
determines the statistical break point within the linear scale. The regression
speci?cations are as follows:
Moody’s ratings
it
¼ b
0
þb
1
EFW
i;t21
þb
2
X
i;t
þb
3
CNTRY
i
þb
4
YEAR
t
þu
i;t
ð1Þ
Moody’s ratings
it
¼ b
0
þb
1
A
k;i;t21
þb
2
EFW_A
k;i;t21
þb
3
X
i;t
þb
4
CNTRY
i
þb
5
YEAR
t
þu
i;t
ð2Þ
where Moody’s ratings represent the dependent variable which is ordinal in nature,
EFW
i,t21
denotes the economic freedom level for country i in period t 2 1, A
k,i,t21
is
the EFW rating for area k, where (k ¼ 1, 2, . . . ,5), EFW_A
k,it21
is the EFW overall
rating re-calculated to omit that particular area k, X is a matrix of control variables,
CNTRY represents the matrix of country dummies and YEAR
t
represents the matrix
of year dummies[3]. The EFW variables are all included lagged one period to allow the
bond rating agency time to re?ect any changes in the EFW index and to minimize
endogeneity[4]. The set of control variables includes GDP per capita, growth rate of
Variable Mean SD Min. Max. n
Per capita GDP (in ’000s of ppp$) 16.6215 12.52371 1.72 70.76 571
Growth rate of per capita GDP 3.19% 3.31% 212.52% 28.54% 571
Sovereign bond spreads 2.65% 2.94% 0.00% 13.50% 571
Polity 6.6025 5.334883 29 10 571
EFW overall index 6.8429 0.809133 3.99 8.68 571
Area 1: size of government 6.1557 1.43636 2.41 9.25 571
Area 2: legal structure and property rights 6.1542 1.898765 1.43 9.62 571
Area 3: access to sound money 8.4079 1.416655 2.71 9.84 571
Area 4: freedom to trade internationally 7.2464 0.818831 4.29 9.37 571
Area 5: regulation of credit, labor, and business 6.2500 0.881329 3.95 8.7 571
EFW: all areas except Area 1 6.984623 1.025108 3.8 8.92 571
EFW: all areas except Area 2 7.074764 0.702775 4.59 8.78 571
EFW: all areas except Area 3 6.438581 0.768421 3.84 8.41 571
EFW: all areas except Area 4 6.73648 0.886781 3.7 8.68 571
EFW: all areas except Area 5 6.980158 0.843366 4.04 8.9 571
Notes: The per capita GDP and growth rate data were obtained from the World Bank’s World
Development Indicators web site at: http://.go.worldbank.org/6HAYAHG8H0 The Moody’s credit
ratings and the sovereign bond spreads were obtained from Aswath Damodaran’s web site at: http://
pages.stern.nyu.edu/,adamodar/ The sovereign bond spread is the difference between the ten-year
sovereign bond rate of country and the ten-year bond rate. The political regime characteristics and
transitions or the polity data were obtained from the Polity IV Project data at: www.systemicpeace.org
The Polity data is based on a 21-point scale ranging from 210 (hereditary monarchy) to þ10
(consolidated democracy). The Polity conceptual scheme is unique in that it examines concomitant
qualities of democratic and autocratic authority in governing institutions, rather than discreet and
mutually exclusive forms of governance. The EFW index and the sub-areas are available from the
database maintained by the Fraser Institute, www.freetheworld.com
Table II.
Descriptive statistics
Sovereign credit
ratings and
default risk
153
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
per capita GDP, and the Polity IV democratic/autocratic measure. Though the
explanatory and control variables may seem to be closely related we do not ?nd any
problems due to multicollinearity and our coef?cient estimates were quite precise[5].
The results are presented in Table III. Column (1) reports the ordered probit
regression results for equation (1). The variables behave as expected. The lagged EFW
index, the per capita GDP, and the growth rate of GDP all have negative coef?cients
which indicate that an increase in the respective variable is associated with a better bond
rating. The polity variable was negative as expected but insigni?cant throughout.
Columns (2)-(6) in Table III showthe results of equation (2) isolating the impact of each of
the ?ve EFWindex areas. In no case do we ?nd the individual area to be signi?cant, but
the overall index, omitting the respective area, was signi?cant and negative as expected
in four of ?ve cases. In Column (4) we ?nd that neither the Area 3 (sound money) rating
nor the corresponding overall index is signi?cant. However, Column (7) estimates the
impact of just component 3C (current in?ation). The component 3C takes on a higher
value if in?ation is lower. The coef?cient is negative and signi?cant as expected
indicating the better (i.e. lower) in?ation corresponds with better bond ratings. Because
interpreting ordered probit coef?cients is comparatively dif?cult and because the
ensuing results for sovereign bond spreads are qualitatively similar, we will reserve any
discussion of the quantitative magnitude of the results for that model.
Next, we look at the EFW index and its ?ve areas as related to the sovereign bond
spread over US ten-year Treasury bonds. There are many countries, e.g. most
organisation for economic co-operation and development countries, where the sovereign
bond spread vs US Treasuries is zero, and thus tobit is appropriate as it allows for the
censored nature of the dependent variable. The regression equations we estimate are:
Country spread
i;t
¼ b
0
þb
1
EFW
i;t21
þb
2
X
i;t
þb
3
CNTRY
i
þb
4
YEAR
t
þj
i;t
ð3Þ
Figure 1.
Difference in bond spread
between countries with
high EFW index and low
EFW index
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
P
e
r
c
e
n
t
a
g
e
2000 2001 2002 2003 2004 2005 2006
Sovereign bond spread (high EFW)
Sovereign bond spread (low EFW)
Notes: The countries are sorted into four quartiles based on their
EFW levels. The “high EFW” is the quartile with the highest EFW
scores and “low EFW” is the quartile with the lowest EFW scores.
The sovereign bond spreads are the average bond spreads in the
two respective quartiles. The data sovereign bond spreads were
obtained from Aswath Damodaran’s web site at: http://pages.stern.
nyu.edu/~adamodar/
JFEP
2,2
154
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
D
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
¼
M
o
o
d
y
’
s
s
o
v
e
r
e
i
g
n
c
r
e
d
i
t
r
a
t
i
n
g
s
(
1
)
(
2
)
(
3
)
(
4
)
(
5
)
(
6
)
(
7
)
E
F
W
o
v
e
r
a
l
l
i
n
d
e
x
(
t
2
1
)
2
0
.
8
9
6
6
*
*
*
(
0
.
3
3
9
8
)
P
e
r
c
a
p
i
t
a
G
D
P
(
i
n
’
0
0
0
s
o
f
$
)
2
0
.
4
1
6
0
*
*
*
(
0
.
0
8
0
5
)
2
0
.
4
0
6
4
*
*
*
(
0
.
0
8
1
4
)
2
0
.
4
0
0
4
*
*
*
(
0
.
0
8
1
4
)
2
0
.
4
1
0
1
*
*
*
(
0
.
0
8
1
1
)
2
0
.
4
0
6
7
*
*
*
(
0
.
0
8
1
1
)
2
0
.
4
0
8
1
*
*
*
(
0
.
0
8
1
3
)
2
0
.
4
0
3
9
*
*
*
(
0
.
0
8
1
0
)
G
r
o
w
t
h
r
a
t
e
p
e
r
c
a
p
i
t
a
G
D
P
2
7
.
2
3
1
6
*
*
(
3
.
2
0
2
6
)
2
6
.
8
8
9
0
*
*
(
3
.
2
0
5
0
)
2
7
.
2
2
7
4
*
*
(
3
.
2
4
3
4
)
2
7
.
8
9
3
6
*
*
(
3
.
3
0
5
8
)
2
6
.
8
6
2
3
*
*
(
3
.
2
3
4
9
)
2
6
.
7
1
2
3
*
*
(
3
.
2
0
7
6
)
2
8
.
6
6
5
0
*
*
*
(
3
.
3
5
3
5
)
P
o
l
i
t
y
2
0
.
0
1
1
3
(
0
.
0
7
9
4
)
2
0
.
0
1
2
7
(
0
.
0
7
9
5
)
2
0
.
0
1
4
9
(
0
.
0
7
9
5
)
2
0
.
0
1
2
7
(
0
.
0
7
9
5
)
2
0
.
0
1
6
5
(
0
.
0
8
0
3
)
2
0
.
0
0
9
1
(
0
.
0
8
1
7
)
2
0
.
0
0
3
6
(
0
.
0
7
9
5
)
A
r
e
a
1
:
s
i
z
e
o
f
g
o
v
e
r
n
m
e
n
t
(
t
2
1
)
0
.
0
6
9
8
(
0
.
2
2
8
0
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
1
(
t
2
1
)
2
0
.
9
6
7
4
*
*
(
0
.
3
9
1
1
)
A
r
e
a
2
:
l
e
g
a
l
s
t
r
u
c
t
u
r
e
a
n
d
p
r
o
p
e
r
t
y
r
i
g
h
t
s
(
t
2
1
)
0
.
2
3
4
3
(
0
.
2
3
2
6
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
2
(
t
2
1
)
2
0
.
9
5
6
5
*
*
*
(
0
.
3
6
7
3
)
A
r
e
a
3
:
a
c
c
e
s
s
t
o
s
o
u
n
d
m
o
n
e
y
(
t
2
1
)
2
0
.
2
8
2
7
(
0
.
1
9
3
3
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
3
(
t
2
1
)
2
0
.
3
0
8
6
(
0
.
5
3
0
8
)
2
0
.
1
9
4
3
(
0
.
5
3
8
7
)
A
r
e
a
4
:
f
r
e
e
d
o
m
t
o
t
r
a
d
e
i
n
t
e
r
n
a
t
i
o
n
a
l
l
y
(
t
2
1
)
0
.
0
8
8
9
(
0
.
2
7
2
4
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
4
(
t
2
1
)
2
0
.
9
1
2
6
*
*
(
0
.
3
8
0
6
)
A
r
e
a
5
:
r
e
g
u
l
a
t
i
o
n
o
f
c
r
e
d
i
t
,
l
a
b
o
r
,
a
n
d
b
u
s
i
n
e
s
s
(
t
2
1
)
0
.
0
3
6
4
(
0
.
2
5
6
4
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
5
(
t
2
1
)
2
0
.
8
5
7
2
*
*
(
0
.
3
9
9
4
)
A
r
e
a
3
C
(
t
2
1
)
2
0
.
2
9
0
1
*
*
*
(
0
.
1
0
9
5
)
A
r
e
a
3
(
t
2
1
)
w
i
t
h
o
u
t
3
C
(
t
2
1
)
2
0
.
1
2
7
2
(
0
.
1
4
9
7
)
P
s
e
u
d
o
R
2
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
0
.
7
3
O
b
s
e
r
v
a
t
i
o
n
s
4
8
9
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
;
s
t
a
n
d
a
r
d
e
r
r
o
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
;
a
l
l
v
a
r
i
a
b
l
e
s
a
r
e
d
e
?
n
e
d
i
n
T
a
b
l
e
I
I
;
h
i
g
h
e
r
v
a
l
u
e
s
i
n
A
r
e
a
3
C
i
m
p
l
i
e
s
l
o
w
e
r
i
n
?
a
t
i
o
n
Table III.
Ordered probit analysis:
determinants of Moody’s
Sovereign Credit ratings
Sovereign credit
ratings and
default risk
155
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Country spread
i;t
¼ b
0
þb
1
A
k;i;t21
þb
2
EFW
A
k;i;t21
þb
3
X
i;t
þb
4
CNTRY
i
þb
5
YEAR
t
þj
i;t
ð4Þ
By following McDonald and Mof?tt (1980) we truncate the tobit regression at zero:
Sovereign bond spread
*
i;t
¼
Country spread
i;t
if Country spread
i;t
. 0
0 if Country spread
i;t
# 0
(
It is assumed that the error term, j , Nð0; s
2
I Þ and sovereign bond spread
*
i;t
is the
latent variable used in tobit estimation. We use the same set of seven equations as we did
in previous analysis replacing the sovereign bond rating dependent variable with the
sovereign default spread. The results are presented in Table IV.
The results are qualitatively similar in both Tables III and IV[6]. Column (1) reports
the basic regression results with the EFW overall index as the independent variable in
addition to the controls. The negative sign on the coef?cient indicates that the bond
default spread is lower as economic freedom is higher. The next columns, (3)-(6),
highlight the independent effect of the ?ve areas of the EFW index. Column (7) isolates
the impact of Component 3C (current in?ation) within Area 3 of the EFW index. As
before, we ?nd the individual areas to be insigni?cant in all speci?cations. The overall
index however is negative and signi?cant in each case as is the 3C variable.
The magnitude of the EFW index coef?cient was similar in all the regressions. In
Column (1), the coef?cient of 20.0126 indicates that a two unit difference in the EFW
rating (about 2.4 standard deviations or the difference between the market-oriented the
USA and Pakistan or between reforming China and autarkic Myanmar) corresponds to
a lower sovereign bond spread against US Treasuries of about 250 basis points. Given
that the average interest rate on the ten-year US Treasury bond was about 5 percent in
our dataset, this represents approximately a 50 percent higher cost of borrowing for a
two unit difference in the EFW rating.
5. Conclusion
The credit risk of sovereign debt is an important consideration in ?nancial markets
and has important real economic consequences in a number of areas. This paper ?nds
that countries with higher values on the EFW index, enjoy lower sovereign bond
default risk as measured by Moody’s credit ratings and by sovereign bond spreads
over ten-year US Treasury bonds.
Many of the relationships illustrated in the regressions above re?ect the impact
of economic freedom perhaps as it works through other variables such as increasing
economic growth, and political stability. We have controlled for a few commonly used
economic and political variables and we cannot claim that the controls are exhaustive.
However, the results presented appear to be robust to numerous alternate speci?cations.
No one area of the EFW index appears to stand out, with the possible exception of
Component 3C which re?ects current in?ation. This is consistent the argument made
by Lawson (2006) that economic freedom is a bundle that is dif?cult to disaggregate
either statistically or conceptually.
JFEP
2,2
156
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
D
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
¼
S
o
v
e
r
e
i
g
n
b
o
n
d
s
p
r
e
a
d
s
(
1
)
(
2
)
(
3
)
(
4
)
(
5
)
(
6
)
(
7
)
E
F
W
o
v
e
r
a
l
l
i
n
d
e
x
(
t
2
1
)
2
0
.
0
1
2
6
*
*
*
(
0
.
0
0
3
1
)
P
e
r
c
a
p
i
t
a
G
D
P
(
i
n
’
0
0
0
s
o
f
$
)
2
0
.
0
0
1
1
(
0
.
0
0
0
7
)
2
0
.
0
0
1
2
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
1
(
0
.
0
0
0
8
)
2
0
.
0
0
1
(
0
.
0
0
0
7
)
G
r
o
w
t
h
r
a
t
e
p
e
r
c
a
p
i
t
a
G
D
P
2
0
.
1
0
2
4
*
*
*
(
0
.
0
2
8
6
)
2
0
.
1
0
2
0
*
*
*
(
0
.
0
2
8
6
)
2
0
.
0
9
9
5
*
*
*
(
0
.
0
2
8
9
)
2
0
.
1
0
5
4
*
*
*
(
0
.
0
2
9
2
)
2
0
.
1
0
3
7
*
*
*
(
0
.
0
2
9
1
)
2
0
.
1
0
1
8
*
*
*
(
0
.
0
2
8
8
)
2
0
.
1
0
5
1
*
*
*
(
0
.
0
2
8
9
)
P
o
l
i
t
y
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
1
(
0
.
0
0
0
8
)
2
0
.
0
0
0
2
(
0
.
0
0
0
8
)
2
0
.
0
0
0
2
(
0
.
0
0
0
8
)
0
(
0
.
0
0
0
8
)
A
r
e
a
1
:
s
i
z
e
o
f
g
o
v
e
r
n
m
e
n
t
(
t
2
1
)
0
.
0
0
3
(
0
.
0
0
2
1
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
1
(
t
2
1
)
2
0
.
0
1
5
0
*
*
*
(
0
.
0
0
3
6
)
A
r
e
a
2
:
l
e
g
a
l
s
t
r
u
c
t
u
r
e
a
n
d
p
r
o
p
e
r
t
y
r
i
g
h
t
s
(
t
2
1
)
2
0
.
0
0
2
(
0
.
0
0
2
2
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
2
(
t
2
1
)
2
0
.
0
1
0
4
*
*
*
(
0
.
0
0
3
3
)
A
r
e
a
3
:
a
c
c
e
s
s
t
o
s
o
u
n
d
m
o
n
e
y
(
t
2
1
)
2
0
.
0
0
0
7
(
0
.
0
0
1
7
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
3
(
t
2
1
)
2
0
.
0
1
2
1
*
*
(
0
.
0
0
5
0
)
2
0
.
0
1
0
6
*
*
(
0
.
0
0
4
9
)
A
r
e
a
4
:
f
r
e
e
d
o
m
t
o
t
r
a
d
e
i
n
t
e
r
n
a
t
i
o
n
a
l
l
y
(
t
2
1
)
0
.
0
0
2
(
0
.
0
0
2
5
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
4
(
t
2
1
)
2
0
.
0
1
3
7
*
*
*
(
0
.
0
0
3
5
)
A
r
e
a
5
:
r
e
g
u
l
a
t
i
o
n
o
f
c
r
e
d
i
t
,
l
a
b
o
r
,
a
n
d
b
u
s
i
n
e
s
s
(
t
2
1
)
2
0
.
0
0
1
5
(
0
.
0
0
2
4
)
E
F
W
:
a
l
l
a
r
e
a
s
e
x
c
e
p
t
A
r
e
a
5
(
t
2
1
)
2
0
.
0
1
0
9
*
*
*
(
0
.
0
0
3
7
)
A
r
e
a
3
C
(
t
2
1
)
2
0
.
0
0
2
2
*
*
*
(
0
.
0
0
0
8
)
A
r
e
a
3
(
t
2
1
)
w
i
t
h
o
u
t
3
C
(
t
2
1
)
0
.
0
0
0
6
(
0
.
0
0
1
3
)
C
o
n
s
t
a
n
t
0
.
1
3
5
2
*
*
*
(
0
.
0
2
0
8
)
0
.
1
4
0
9
*
*
*
(
0
.
0
2
1
9
)
0
.
1
3
5
3
*
*
*
(
0
.
0
2
0
7
)
0
.
1
3
4
4
*
*
*
(
0
.
0
2
2
8
)
0
.
1
2
3
7
*
*
*
(
0
.
0
2
2
8
)
0
.
1
3
2
8
*
*
*
(
0
.
0
2
0
5
)
0
.
1
3
8
0
*
*
*
(
0
.
0
2
2
6
)
P
s
e
u
d
o
R
2
2
0
.
8
2
0
.
7
9
2
0
.
7
9
2
0
.
7
9
2
0
.
7
9
2
0
.
7
9
2
0
.
8
O
b
s
e
r
v
a
t
i
o
n
s
4
8
9
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
4
8
6
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
s
t
a
n
d
a
r
d
e
r
r
o
r
s
i
n
p
a
r
a
n
t
h
e
s
e
s
;
a
l
l
v
a
r
i
a
b
l
e
s
a
r
e
d
e
?
n
e
d
i
n
T
a
b
l
e
I
I
;
h
i
g
h
e
r
v
a
l
u
e
s
i
n
A
r
e
a
3
C
i
m
p
l
i
e
s
l
o
w
e
r
i
n
?
a
t
i
o
n
Table IV.
Tobit analysis:
determinants of
Sovereign Bond Spreads
Sovereign credit
ratings and
default risk
157
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Notes
1. Standard & Poors, Moody’s, and Fitch are the three main credit rating agencies which assign
letter ratings to a country’s sovereign debt. Ratings by different credit rating agencies for
foreign currency sovereign ratings are consistent with each though there are minor
inconsistencies.
2. We used the following seven rating categories: Aaa, Aa, A, Baa, Ba, B, and C. The results
when using all rating categories were substantively the same.
3. We experimented with alternative functional forms for the EFW index variable (quadratics
and high/middle/low dummy variable interactions) but ultimately rejected statistically the
non-linear forms. We included the change in the EFW index (DEFW ¼ EFW
t
2 EFW
t21
) as
an additional independent variable but also rejected its inclusion in the ?nal model on
statistical grounds. The core results were unaffected by these choices. Finally, we ran the
models as single-year cross-sections instead of as a panel and found the EFW index variable
to be negative and signi?cant in each individual year sample as well. The dataset is
available upon request for anyone wanting to verify our ?ndings.
4. We want to thank participants at the Auburn University Finance Department Seminar and
the Southwestern Finance Association meeting for this suggestion to used lagged values of
the EFW index.
5. The variance in?ation factor for each of our right-hand-side variable in our basic regression
is low with the highest being 1.91 for the lagged EFW index. Even in the regressions using
the EFW areas the highest VIF was 2.37 which is highly acceptable.
6. Per capita GDP was signi?cant in Table III but not in Table IV however.
References
Berggren, N. (2003), “The bene?ts of economic freedom: a survey”, Independent Review, Vol. 8
No. 2, pp. 193-211.
Boubakri, N., Cosset, J.C. and Guedhami, O. (2005), “Liberalization, corporate governance and the
performance of newly privatized ?rms”, Journal of Corporate Finance, Vol. 11, pp. 747-946.
Brooks, R., Faff, R.W., Hillier, D. and Hillier, J. (2004), “The national market impact of sovereign
rating changes”, Journal of Banking & Finance, Vol. 28, pp. 233-50.
Butler, A.W. and Fauver, L. (2006), “Institutional environment and sovereign credit ratings”,
Financial Management, Vol. 35 No. 3, pp. 53-79.
Cantor, R. and Packer, F. (1996), “Determinants and impact of sovereign credit ratings”, FRBNY
Economic Policy Review, October, pp. 37-54.
Damodaran, A. (2010), “Equity risk premiums (ERP): determinants, estimation and implications –
a post-crisis”, available at SSRN: http://ssrn.com/abstract¼1492717 (accessed
February 20, 2010).
De Haan, J., Lundstro¨m, S. and Sturm, J.E. (2006), “Market-oriented institutions and policies and
economic growth: a critical survey”, Journal of Economic Surveys, Vol. 20 No. 2, pp. 157-91.
D’Souza, J., Megginson, W. and Nash, R. (2005), “Effect of institutional and ?rm-speci?c
characteristics on post-privatization performance: evidence from developed countries”,
Journal of Corporate Finance, Vol. 11, pp. 747-66.
Erb, C.B., Harvey, C.R. and Viskanta, T.E. (1996), “Expected returns and volatility in 135
countries”, Journal of Portfolio Management, Vol. 22, pp. 46-58.
Gwartney, J. and Lawson, R. (2003), “The concept and measurement of economic freedom”,
European Journal of Political Economy, Vol. 19, pp. 405-30.
JFEP
2,2
158
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Gwartney, J. and Lawson, R. (2008), Economic Freedom of the World: 2008 Annual Report,
Fraser Institute, Vancouver.
Gwartney, J., Holcombe, R. and Lawson, R. (2006), “Institutions and the impact of investment on
growth”, Kyklos, Vol. 59 No. 2, pp. 255-73.
Hanke, S. and Walters, S. (1997), “Economic freedom, prosperity, and equality: a survey”,
Cato Journal, Vol. 17, pp. 117-46.
IMF (2005), World Economic Outlook: Building Institutions, International Monetary Fund,
Washington, DC.
Kaminsky, G. and Schmukler, S. (2002), “Emerging markets instability: do sovereign credit
ratings affect country risk and stock returns?”, World Bank Economic Review, Vol. 16,
pp. 171-95.
Kraeussl, R. (2003), Do changes in Sovereign Credit Ratings Contribute to Financial Contagion in
Emerging Market Crises?, CFS Working Paper No. 2003/22, Center for Financial Studies,
Frankfurt.
Lawson, R. (2006), “On testing the connection between economic freedom and growth”,
Econ Journal Watch, Vol. 3 No. 3, pp. 398-406.
Lothian, J.R. (2006), “Institutions, capital ?ows, and ?nancial integration”, Journal of
International Money and Finance, Vol. 25, pp. 358-69.
McDonald, J.F. and Mof?tt, R.A. (1980), “The uses of tobit analysis”, The Review of Economics
and Statistics, Vol. 62, pp. 318-87.
Martell, R. (2005), “The effect of sovereign credit rating changes on emerging stock markets”,
SSRN, available at: http://ssrn.com/abstract¼686375
Reinhart, C.M. and Rogoff, K.S. (2004), “Serial default and the ‘Paradox’ of rich-to poor capital
?ows”, American Economic Review, Vol. 94, pp. 53-8.
Roychoudhury, S. and Lawson, R.A. (2008), “Economic freedom and equity prices among US
states”, The Credit and Financial Management Review, Vol. 14 No. 4, pp. 33-46.
Stocker, M.L. (2005), “Equity returns and economic freedom”, Cato Journal, Vol. 25 No. 3, pp. 583-94.
Further reading
Beers, D.T. and Cavanaugh, M. (2004), “Sovereign credit ratings: a primer”, Standard & Poor’s
Ratings Direct, available at: www.2.standardandpoors.com/spf/pdf/products/SovRatings
Primer_sov.pdf
Appendix 1. The areas, components, and sub-components of the EFW index
Area 1. Size of government: expenditures, taxes, and enterprises
A. General government consumption spending as a percentage of total consumption.
B. Transfers and subsidies as a percentage of GDP.
C. Government enterprises and investment.
D. Top marginal tax rate:
i. top marginal income tax rate; and
ii. top marginal income and payroll tax rates.
Area 2. Legal structure and security of property rights
A. Judicial independence.
B. Impartial courts.
Sovereign credit
ratings and
default risk
159
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
C. Protection of property rights.
D. Military interference in rule of law and the political process.
E. Integrity of the legal system.
F. Legal enforcement of contracts.
G. Regulatory restrictions on the sale of real property.
Area 3. Access to sound money
A. Money growth.
B. Standard deviation of in?ation.
C. In?ation: most recent year.
D. Freedom to own foreign currency bank accounts.
Area 4. Freedom to trade internationally
A. Taxes on international trade:
i. revenues from trade taxes (percent of trade sector);
ii. mean tariff rate; and
iii. standard deviation of tariff rates.
B. Regulatory trade barriers:
i. non-tariff trade barriers; and
ii. compliance cost of importing and exporting.
C. Size of trade sector relative to expected.
D. Black-market exchange rates.
E. International capital market controls:
i. foreign ownership/investment restrictions; and
ii. capital controls.
Area 5. Regulation of credit, labor, and business
A. Credit market regulations:
i. ownership of banks;
ii. foreign bank competition;
iii. private sector credit; and
iv. interest rate controls/negative real interest rates.
B. Labor market regulations:
i. minimum wage;
ii. hiring and ?ring regulations;
iii. centralized collective bargaining;
iv. mandated cost of hiring;
v. mandated cost of worker dismissal; and
vi. conscription.
C. Business regulations:
i. price controls;
ii. administrative requirements;
JFEP
2,2
160
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
iii. bureaucracy costs;
iv. starting a business;
v. extra payments/bribes;
vi. licensing restrictions; and
vii. cost of tax compliance.
Appendix 2
1 Argentina
2 Armenia
3 Australia
4 Austria
5 Azerbaijan
6 Bahamas
7 Bahrain
8 Barbados
9 Belgium
10 Belize
11 Bolivia
12 Bosnia and Herzegovina
13 Botswana
14 Brazil
15 Bulgaria
16 Canada
17 Chile
18 China
19 Colombia
20 Costa Rica
21 Croatia
22 Cyprus
23 Czech Rep.
24 Denmark
25 Dominican Rep.
26 Ecuador
27 Egypt
28 El Salvador
29 Estonia
30 Fiji
31 Finland
32 France
33 Germany
34 Greece
35 Guatemala
36 Honduras
37 Hong Kong
38 Hungary
39 Iceland
40 India
41 Indonesia
42 Ireland
43 Israel
(continued)
Table AI.
List of countries
in our dataset
Sovereign credit
ratings and
default risk
161
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Corresponding author
Saurav Roychoudhury can be contacted at: [email protected]
44 Italy
45 Jamaica
46 Japan
47 Jordan
48 Kazakhstan
49 Kuwait
50 Latvia
51 Lithuania
52 Luxembourg
53 Malaysia
54 Malta
55 Mauritius
56 Mexico
57 Moldova
58 Morocco
59 The Netherlands
60 New Zealand
61 Nicaragua
62 Norway
63 Oman
64 Pakistan
65 Panama
66 Papua New Guinea
67 Paraguay
68 Peru
69 Philippines
70 Poland
71 Portugal
72 Romania
73 Russia
74 Singapore
75 Slovak Rep.
76 Slovenia
77 South Africa
78 South Korea
79 Spain
80 Sweden
81 Switzerland
82 Taiwan
83 Thailand
84 Trinidad and Tobago
85 Tunisia
86 Turkey
87 Ukraine
88 United Arab Emirates
89 The UK
90 The USA
91 Uruguay
92 Venezuela
93 Vietnam
Table AI.
JFEP
2,2
162
To purchase reprints of this article please e-mail: [email protected]
Or visit our web site for further details: www.emeraldinsight.com/reprints
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
This article has been cited by:
1. Sang-Heui Lee, Jay van Wyk. 2015. National institutions and logistic performance: a path analysis. Service
Business 9, 733-747. [CrossRef]
2. Ariel R. Belasen, Rik W. Hafer, Shrikant P. Jategaonkar. 2015. ECONOMIC FREEDOM AND STATE
BOND RATINGS. Contemporary Economic Policy 33:10.1111/coep.2015.33.issue-4, 668-677. [CrossRef]
3. Kun-Li Lin, Anh Tuan Doan, Shuh-Chyi Doong. 2015. Changes in ownership structure and bank
efficiency in Asian developing countries: The role of financial freedom. International Review of Economics
& Finance . [CrossRef]
4. Benjamin M. Blau, Tyler J. Brough, Diana W. Thomas. 2014. Economic freedom and the stability of
stock prices: A cross-country analysis. Journal of International Money and Finance 41, 182-196. [CrossRef]
5. Peter T. Calcagno, Justin D. Benefield. 2013. Economic freedom, the cost of public borrowing, and state
bond ratings. Journal of Financial Economic Policy 5:1, 72-85. [Abstract] [Full Text] [PDF]
6. Georgios E. Chortareas, Claudia Girardone, Alexia Ventouri. 2013. Financial freedom and bank efficiency:
Evidence from the European Union. Journal of Banking & Finance 37, 1223-1231. [CrossRef]
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
doc_136721483.pdf