3rd TIAC-BNM Monetary and Financial Economics Workshop, 16 … · 2018-07-20 · 3.026 0.314 1.058...
Transcript of 3rd TIAC-BNM Monetary and Financial Economics Workshop, 16 … · 2018-07-20 · 3.026 0.314 1.058...
Law Siong Hook, Ph.D Department of Economics
Universiti Putra Malaysia
Email: [email protected]
Faculty of Economics and
Management
Universiti Putra Malaysia
3rd TIAC-BNM Monetary and Financial Economics
Workshop, 16 July 2018, Sasana Kijang, BNM
Introduction
Literature Review
Objective of the Study
Research Question
Contributions
Empirical Model and Methodology
Empirical Results
Conclusion
The issue of government debt has become the main concern after the 2007 – 2008 global financial crisis
Advanced economies are facing high debt accumulation due to stimulus expenditure programs and higher costs of stabilizing the financial system
The issue of debt with respect to fiscal sustainability in advanced economies may also spread and create a significant impact on developing countries.
From a theoretical point of view, a higher debt level tends to have deleterious effects on economic growth (Snider, 1998; Pattillo et al., 2002; Reinhart and Rogoff, 2010; Minea and Parent, 2012; Afonso and Jalles, 2013; Baum et al., 2013; Kourtellos et al., 2013; Panizza and Presbitero, 2014).
The negative effect of debt on growth also leads to strengthening the importance of fiscal consolidation programs that aim for debt reduction
In recent studies, the threshold of the debt-to-GDP ratio and the nonlinear effects of debt on growth have been gaining significant attention.
In their seminal article, Reinhart and Rogoff (2010) use the comparison of means of the debt-growth nexus in advanced countries (OECD) and emerging countries. ◦ The public debt-economic growth relation is weak for
debt/GDP ratios below a threshold 90 percent to GDP. ◦ Public debt starts to have a negative effect when it reaches 90
percent of GDP
Similar threshold (90%) - Kumar and Woo (2010), Checherita-Westphal and Rother (2012) and Cecchetti et al. (2011).
Reinhart and Rogoff (2010) - the threshold for public debt is similar in advanced and emerging markets. Emerging markets face lower thresholds for external debt (public and private) that usually denominated in a foreign currency
These findings have attracted the attention of economists and policymakers because the threshold level is a crucial parameter in designing fiscal policy to avoid an excessive debt level
Caner et al. (2010) - lower threshold of 77% of public debt to GDP in both developed and developing countries. If debt is above this threshold, each additional % point of debt costs 0.017 % points of annual real growth.
◦ Much lower threshold in emerging markets alone - 64% debt-to-GDP ratio
Cecchetti et al. (2010) - for public debt, the threshold is around 85% of GDP in 18 OECD countries.
Egert (2015) - the negative relation between public debt and economic growth is found to kick in at a very lower level of debt (between 20 percent and 60 percent of debt)
Presbitero (2012) - public debt – economic growth nexus for developing countries solely (panel data analysis of low- and middle-income countries from 1990 to 2007)
◦ Public debt has a negative impact on output growth until it reaches 90 per cent of GDP. Beyond this threshold, the public debt effect on growth becomes irrelevant.
◦ The nonlinear effect can be explained by country-specific effects - only in countries with sound macroeconomic policies and institutional quality.
Pattillo et al. (2002) - the sample period covers until 1998. It is crucial to update the datasets and revisit the public debt-economic growth nexus using more recent estimation technique. ◦ Evaluate the non-linear impact of external debt on
economic growth using a panel data set of 93 developing countries
◦ A country with average indebtedness, doubling the debt ratio tends to reduce half and a full percentage point of annual per capita growth.
◦ Under the Highly Indebted Poor Countries (HIPCs) initiative, per capita growth might increase by 1 percentage point
◦ The average impact of debt becomes negative at about 35 – 40 percent of GDP
Cordella et al. (2005) – examine the effect of public debt on economic growth in HIPCs using panel data analysis. ◦ There is a negative marginal relationship between public debt and
economic growth at intermediate levels of debt, but not at very low debt levels, or at very high levels.
Chen et al. (2016) - public debt in China could change from positive to negative when the public debt ratio reaches a 41.14% threshold in 2014. The optimal level may vary in different economies.
Baharumshah et al. (2014) – after the public debt exceeds 55 percent of the GDP, it is negatively correlated with economic activity in Malaysia
Whether the same debt-to-GDP threshold value can be observed in developing countries?
Perhaps the 90% and 85% debt-to-GDP threshold suggested by Reinhart and Rogoff (2010) and Cecchetti et al (2010), respectively are too high for developing countries.
Panizza and Presbitero (2013) - provide a cautionary note that “thresholds and non-linearities play a key role in influencing the relationship between debt and economic growth” - more research is required to assess the presence of debt thresholds.
Is there a non-linearities or threshold public debt – economic growth exist in developing countries?
This study examines the effect of public debt on economic growth for 71 developing countries from 1984 to 2015, using a dynamic panel threshold technique. ◦ If there is a threshold level beyond which the
detrimental impact of debt on economic growth is significant, then a debt ceiling should propose rather than just expanding the debt level to influence economic development.
◦ Knowing the debt threshold is crucial for policymakers, who can focus on other growth-enhancing policies if the appropriate debt threshold has been achieved
1) There is no clear consensus benchmark of the public debt threshold value for developing countries. Even though the debt threshold value has been identified for the cases of developed countries and emerging countries, the threshold level of the debt-growth nexus may not be uniform between developed and developing countries due to different economics, institutions, and political structures
2) Uses a dynamic panel threshold model proposed by Kremer et al. (2013). The method used by Reinhart and Rogoff (2010) namely: compare the average, means that their conclusions are sensitive to the sample countries if there are outliers. In addition, the average threshold value may not apply to all countries
3) The modeling strategy used in the literature, such as Smyth and Hsing (1995), Pattillo et al. (2002) and Clements et al. (2003), to search for a non-linear relationship between debt and growth is based on the square term of the debt, which has an important limitation
14`
U shape (black line) and Curve shape (dot line) divided into
two regimes
Threshold Square term (over estimate)
To develop the threshold modelling for the public debt-growth nexus, this study uses the economic growth model: rgdpcgit = αi + β0Initialit + β1Debtit + β2Xit + t + it rgdpcg is the measurement of economic growth (real
GDP per capita growth) Initial is initial income Debt is the public debt X is a vector of controls. The specification also contains an unobservable country-specific effect αi, time specific effect t and error term it
Besides capital stock, population growth and human capital that appear in the growth model, institutions variable has been found to promote growth [Knack and Keefer (1995), Hall and Jones (1999), Barro (2000), Acemoglu et al. (2001), Rodrik et al. (2004), Davis (2010) and Vieira et al. (2012)].
Financial development - has been found to facilitate growth (Levine, 1997, 2003; Rajan and Zingales, 1998; Levine et al., 2000; Beck and Levine, 2004; Fang and Jiang, 2014).
Inflation has adverse effect on economic growth (Vinayagathasan, 2013; Eggoh and Khan, 2014).
Trade openness has been found to promote economic growth, as shown by Montalbano, 2011; Musila and Yiheyis, 2015.
The dynamic panel threshold regression approach proposed by Kremer et al. (2013) to evaluate the relationship between public debt and growth, which can show the effect before and after a particular threshold point of pulic debt
I ∙ is the indicator function; represents the debt threshold. Two regimes are divided by the threshold variable debtit, - below or above the threshold value and
distinguished by differing the regression slopes, 𝛽1and 𝛽2.
rgdpcgit = μi+ 𝛽1debtit I (debtit ≤ ) +δ1 I (debtit ≤ γ)+
𝛽2debtit I (debtit > ) +αXit+t + εit (1)
itititit
itititiit
ZdebtIdebt
debtIdebtIdebtY
)(
)()(
2
11
• Zit contains a vector of controlling variables that are partially endogenous, which the slope parameter are assumed to be regime independent
• The Z1it contains set of exogenous variables, while Z2it contains endogenous variables
• it is the error term which assume to be it ~ (0, 2) • The estimator allows for different regime intercepts (1) • The impact of debt on economic growth can be explained by
𝛽1 (𝛽2
) which denote the marginal effect of debt on economic growth in the low (high) debt regime
(2)
Most of the threshold values for debt in the literature are estimated based on a non-dynamic framework such as Hansen (1999) and González et al. (2005), which ignore the effect of initial income on the growth model.
This might result in a misleading conclusion on the level of debt sustainability and growth performance of a country.
The major reason for the choice to use the dynamic threshold model is mainly to address the endogeneity problem of the growth model, which might result in severely biased estimates if not addressed appropriately
Equation (2) is estimated using the least square for a fixed threshold where the endogenous variables are replaced by the predicted values in the reduced form regression.
Finally, the estimator of the threshold value with the
smallest sum of squared residuals is selected. As is determined, the slope coefficients can be estimated using the generalized method of moments (GMM).
Note that the confidence interval for the threshold estimate:
Γ= {: LR() ≤ C(α)} ◦ where C(α) is the 95th percentile of the asymptotic distribution
of the likelihood ratio statistic LR().
Panel data of 71 developing countries from 1984 to 2015
The time period is averaged into four-year intervals and a maximum of 8 observations for each variable per country
The real GDP per capita growth as the dependent variable is obtained from World Development Indicators (WDI).
The public debt-to-GDP ratio, which is constructed from general government gross debt over GDP, is collected from Historical Public Debt Database, International Monetary Fund (IMF).
The control variables datasets namely the initial income, population growth, financial development, inflation, human capital, and
trade openness are collected from WDI.
The initial income is measured by the initial gross domestic product (GDP) per capita.
The capital stock is constructed from the gross investment figures following the
perpetual inventory method.
Financial development = domestic credit to the private sector (% of GDP)
Human capital = life expectancy (World Bank).
Trade openness = summing total exports and imports of goods and services as a percentage of GDP.
Institutional quality index = equal-weight aggregation of 5 indicators (corruption, law and order, bureaucratic quality, government stability, and democratic accountability), and these datasets are collected from the International Country Risk Guide (ICRG).
Variable Unit of Measurement Mean Standard
Deviation Minimum Maximum
Economic growth ln RGDPCt – ln RGDPCt-1 2.808 3.569 -10.037 19.928
ln Public Debt % of GDP 4.251 4.114 0.101 6.417
ln Initial Income US Dollar
(constant 2005) 6.987 1.113 4.415 8.957
ln Capital stock
% of GDP
3.026
0.314
1.058
3.763
ln Population growth Annual % 15.374 1.547 11.857 20.47
ln Institutions Scale 1 – 50 3.258 0.206 2.439 3.711
ln Financial development % of GDP 4.940 0.258 3.509 5.651
ln Inflation Annual % 4.375 0.656 -1.863 5.197
ln Human capital Life Expectancy
(number of years) 3.923 0.631 1.729 4.707
ln Trade openness % of GDP 4.290 0.446 2.857 5.374
Notes: RGDPC = real gross domestic per capita.
AlbaniaAngola
Armenia
AzerbaijanBelarus
Bolivia
Bostwana
Bulgaria
Burkina Faso
Cameroon
China
Colombia
Congo, Dem. Rep.
Congo, Rep.Costa Rica
Cote d'lvoire
Croatia
Dominican Rep.
Ecuador
Egypt
El SalvadorEthiopia
Gabon
Gambia
Ghana
GuatemalaGuinea
Guinea-Bissau
GuyanaHondurasIran JamaicaJordan
Kenya
Latvia Lebanon
Liberia
LibyaLithuania
Madagascar
Malawi
Malaysia
MaliMexico
MoroccoMozambique
Namibia
Nicaragua
Niger
PakistanPanama
ParaguayPeru
Philippines
Poland
SenegalSierra Leone
South AfricaSuriname
SyrianTanzania
Thailand
Togo
TunisiaUganda
Ukraine
Uruguay
Venezuela
Vietnam
Yemen
Zambia
-50
510
Gro
wth
(%)
0 100 200 300 400Debt-to-GDP Ratio(%)
AlbaniaAngolaArmenia
AzerbaijanBelarus
Bolivia
Botswana Bulgaria
Burkina FasoCameroon
China
Colombia
Congo, Dem. Rep.
Congo, Rep.
Costa Rica
Cote d'Ivoire
Croatia
Dominican RepublicEcuador
Egypt, Arab Rep.
El Salvador
Ethiopia
Gabon
Gambia, TheGhana
Guatemala
Guinea Guinea-Bissau
GuyanaHonduras
Iran, Islamic Rep. Jamaica
Jordan
Kenya
Latvia
Lebanon
Liberia
LibyaLithuania
MadagascarMalawi
Malaysia
Mali
Mexico
Morocco
Mozambique
Namibia
Nicaragua
NigerPakistan
Panama
Paraguay
Peru
Philippines
PolandSenegal
Sierra LeoneSouth Africa
Suriname
Syrian Arab Republic
Tanzania
Thailand
Togo
Tunisia
Uganda
Ukraine
Uruguay
Venezuela, RBVietnamYemen, Rep. Zambia
-50
00
0
50
00
10
00
015
00
0
Re
al G
DP
pe
r C
ap
ita (
US
$ c
onst
ant p
rice
s 2
01
0)
0 100 200 300Public Debt (% of GDP)
linear fit 95% CI
Model 1(a) Model 1(b) Model 1(c) Model 1(d) Model 1(e)
Threshold Estimates
48.65% 48.65% 48.65% 48.65% 48.65%
95% confidence interval [32.42, 57.56] [33.20, 56.02] [33.20, 56. 02] [33.20, 56.02] [34.58, 55.09]
Impact of Debt-to-GDP Ratio
β 1 -0.0797
(0.0598)
-0.0334
(0.0350)
-0.0694
(0.0514)
-0.0662
(0.0514)
-0.0605
(0.0703)
β 2 -0.0138**
(0.0056)
-0.0129*
(0.0067)
-0.0127**
(0.0057)
-0.0138***
(0.0049)
-0.0130**
(0.0061)
Impact of Covariates
initial incomeit−1 -2.8711
(0.0598)
-7.6173*
(3.9371)
-2.8144
(1.9150)
-2.7629
(1.9430)
-7.4203*
(3.8590)
capital stockit 0.2819**
(0.1225)
0.2725
(0.4270)
0.2828
(0.3052)
0.2868*
(0.3162)
0.3182
(0.3231)
𝐩𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐠𝐫𝐨𝐰𝐭𝐡it -0.2204**
(0.0993)
-0.2037**
(0.0848)
-0.1825**
(0.0776)
-0.1957**
(0.0829)
-0.1516**
(0.0647)
human capitalit 0.5462*
(0.2905)
0.5389*
(0.3044)
0.5372*
(0.2904)
0.5366*
(0.2840)
1.1521**
(0.4892)
institutionsit 2.8498***
(0.9999)
2.8523**
(1.1453)
2.8272***
(1.0877)
2.4945**
(0.9731)
3.1628***
(0.9521)
financial developmentit - 3.0290**
(1.2726) - -
3.6020**
(1.5262)
inflationit - - -0.2411**
(0.1180) -
-0.2787*
(0.1451)
trade opennessit - - - 0.2422*
(0.1288)
0.7651*
(0.4133)
crisis dummyit - - - - 0.2568
(0.3214)
𝛿 1 1.5785
(2.4884)
0.1210
(2.8559)
1.4246
(2.2030)
1.1821
(2.0801)
1.0014
(2.9803)
28
A function has downward sloping, flat and then downward again
The relationship is monotone. Entirely non-increasing, or entirely non-decreasing
0
20
40
60
80
100
120
140
160
180
200
Latv
ia
Lebanon
Lit
huania
Madagascar
Mala
wi
Mala
ysia
Mali
Mexic
o
Moro
cco
Mozam
biq
ue
Nam
ibia
Nic
ara
gua
Nig
er
Pakis
tan
Panam
a
Para
guay
Philip
pin
es
Senegal
Sie
rra L
eone
South
Afr
ica
Suri
nam
e
Tanzania
Thailand
Togo
Tunis
ia
Ugand
a
Ukra
ine
Uru
guay
Venezuela
Vie
tnam
Yem
en
Zam
bia
2005 2015
Based on the finding of 48.65% threshold value, the average debt accumulation for each country during ◦ the full sample period (1984 to 2015) indicates 48 of
the 71 countries (or 68%) > threshold value.
◦ more recent sample period (2006 to 2015), only 22 of the 71 developing countries (or 31%) > 48.65% threshold value.
Some of the developing countries have reduced their public debt burden over the last 10 years
Region Africa Asia Model 2(a) Model 2(b) Model 2(c) Model 2(d)
Threshold Estimates
γ 42.98% 42.98% 45.43% 45.43%
95% confidence interval [35.98, 45.11] [34.73, 46.08] [35.75, 56.88] [35.25, 56.75]
Impact of Debt-to-GDP Ratio
β 1 0.2184**
(0.0979)
0.1190**
(0.0583)
-0.1436
(0.6829)
-0.1565
(2.4954)
β 2 -0.0152***
(0.0052)
-0.0141**
(0.0064)
-0.1471**
(0.0656)
-0.1514**
(0.0720)
Impact of Covariates
initial incomeit−1 1.7926**
(0.8753)
2.8605***
(1.0310)
2.0494*
(1.0901)
1.9604*
(1.0427)
capital stockit 0.1105
(0.3986)
0.1103
(0.4521)
0.3172
(1.8891)
0.3205
(7.2297)
𝐩𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐠𝐫𝐨𝐰𝐭𝐡it 3.6724***
(1.3835)
4.9165***
(1.8929)
-1.2913*
(0.6725)
-1.1949*
(0.6321)
institutionsit 3.1418
(2.2659)
2.9901
(2.3217)
7.5737***
(2.4115)
6.3144***
(2.8315)
financial developmentit 2.2640
(1.8542)
3.1260*
(1.7364)
0.8897***
(0.3177)
0.8993***
(0.2965)
human capitalit 0.1859
(0.2584)
0.1024
(0.2539)
0.2565
(0.6217)
1.4973**
(0.701 0)
trade opennessit -0.7732**
(0.3633)
-0.5133**
(0.2398)
5.8524**
(2.5445)
5.2440**
(2.2701)
crisis dummyit - -0.8884
(0.5813) -
-10.5166
(8.1066)
𝛿 1 0.4231
(1.7631)
-2.9193*
(1.6605)
0.7418
(23.4704)
1.1248
(85.8466)
Region Europe Latin America Model 2(e) Model 2(f) Model 2(g) Model 2(h)
Threshold Estimates
γ 40.08% 40.08% 48.36% 48.36%
95% confidence interval [35.02, 47.88] [34.58, 47.23] [40.11, 52.79] [40.33, 51.82]
Impact of Debt-to-GDP Ratio
β 1 -0.6487**
(0.2774)
-0.6551***
(0.2263)
-0.0095
(0.0663)
-0.1690
(0.1135)
β 2 -0.0638
(0.0963)
-0.0444
(0.0703)
-0.1269**
(0.0576)
-0.1207**
(0.0524)
Impact of Covariates
initial incomeit−1 1.6853*
(0.9069)
1.5826*
(0.8601)
3.7112**
(1.6869)
3.6795***
(1.1430)
capital stockit 0.3258
(3.2118)
0.3341
(3.4790)
0.2358
(0.3026)
0.2352
(0.5079)
population growthit -1.1272
(1.0813)
-1.1100
(1.5936)
-1.4946
(1.1167)
-1.4700
(1.0609)
institutionsit 4.3671***
(1.2196)
4.6248***
(1.4607)
3.400**
(1.5774)
7.9418***
(2.6862)
financial developmentit 3.9131*
(2.0704)
3.6175*
(2.0097)
-3.9273
(5.4887)
-5.9884
(6.8778)
human capitalit 0.5834**
(0.2536)
0.5773**
(0.2749)
-0.5564*
(0.3112)
-0.5719
(0.4522)
trade opennessit 4.9510*
(2.9489)
4.6173*
(2.5652)
0.2705
(0.3303)
0.4253
(0.3529)
crisis dummyit - -2.3676*
(1.2406) -
-3.5281**
(1.7725)
𝛿 1 10.4669**
(4.6900)
11.2923**
(4.4029)
3.6995
(2.8238)
4.7077
(4.7630)
Observation 39 39 82 82
N 11 11 18 18
Model 3(f) Model 3(g) Model 3(h) Model 3(i) Model 3(j) Threshold Estimates
γ 48.65% 48.65% 48.65% 48.65% 48.65%
95% confidence interval [14.91, 84.91] [14.91, 84.91] [14.91, 84.91] [14.91, 84.91] [14.91, 84.91]
Impact of Debt-to-GDP Ratio
β 1 -0.0923
(0.0651)
-0.0920
(0.0662)
-0.0757
(0.0500)
-0.0259
(0.0500)
-0.0725
(0.0562)
β 2 -0.0117**
(0.0053)
-0.0106**
(0.0049)
-0.0159**
(0.0076)
-0.0168**
(0.0071)
-0.0156**
(0.0072)
Impact of Covariates
initialincomeit−1 -3.2809
(2.2570)
-2.2150
(2.2570)
-3.0665
(1.9848)
-2.7571
(1.9056)
-2.9950
(2.2009)
capital stockit 0.2222
(0.2750)
0.2210
(0.2742)
0.2346
(0.2762)
0.2651
(0.2702)
0.2440
(0.2714)
population growthit 8.4678***
(2.8308)
8.4678***
(2.8205)
7.5589***
(2.4487)
6.7334***
(2.4134)
8.1777***
(2.8726)
institutionsit 2.9515**
(1.3122)
2.9314**
(1.3132)
2.7513***
(0.8949)
2.7149***
(0.9955)
3.0074***
(0.9397)
financial developmentit -5.7455*
(3.4529)
-5.7446
(3.5707)
-4.9785
(3.1412)
-3.8091
(3.0156)
-5.7352
(3.5644)
human capitalit 0.5754*
(0.3402)
0.5754*
(0.3400)
1.6522
(1.6427)
0.4750
(0.3107)
0.5445
(0.3382)
trade opennessit 0.5299
(0.3415)
0.5287
(0.3412)
0.5055
(0.3297)
3.3432*
(1.8694)
0.4633
(0.3435)
crisis dummyit -0.0976
(0.4428)
-0.0968
(0.4422)
-0.0665
(0.4240)
-0.0449
(0.4203)
-0.0396
(0.4264)
debtsit × institutionsit 0.3009
(0.1475)** - - - -
debtsit × financial developmentit - 0.3309
(0.1354)** - - -
debtsit × human capitalit - - -0.5314
(0.7089) - -
debtsit × trade opennessit - - - -1.5793
(0.9441) -
𝛿 1 2.2354
(2.7038)
2.2354
(2.7038)
1.5595
(2.0167)
-0.4769
(1.9750)
1.3792
(2.3516)
The empirical findings demonstrate that the threshold value of public debt to GDP is 48.65% for developing countries.
The developing countries have a lower threshold debt-to-GDP ratio that found in the previous literature.
More public debt is harmful to economic growth in developing countries because above the threshold it has a negative and significant effect
The nonlinear or inverted U-shaped relationship between the debt-to-GDP ratio and economic growth is difficult to establish
• When the sample countries are divided into four regional groups - Lain America, Asia, Africa and Europe developing countries, the nonlinear
relation is detected only for African region.
• Different regions have different debt threshold values, where Latin America and Asia regions have higher threshold compared to Africa and
Europe developing countries.
• The public debt-economic growth threshold
relation is heterogeneous across regions.
Better institutions and developed financial system tend to moderate the negative impact of public debt on economic growth.
Knowing the debt ceiling is important if fiscal policy is to play a crucial role in restoring sustainable growth.
Since the developing countries have a much lower threshold of debt, policy makers in these countries must be cautious regarding their level of public debt to avoid excessive debt accumulation.
THANK
YOU
The author is grateful for the financial support from the Tun Ismail Ali Chair research grant, Bank Negara Malaysia. The author also thanks the editor and 4 reviewers’ comments and suggestions from Contemporary Economic Policy, a journal of the Western Economic Association International (WEAI), USA.
Law Siong Hook, Ph.D Department of Economics
Universiti Putra Malaysia
Email: [email protected]
Faculty of Economics and
Management
Universiti Putra Malaysia
3rd TIAC-BNM Monetary and Financial Economics
Workshop, 16 July 2018, Sasana Kijang, BNM
0
20
40
60
80
100
120
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
20
14
0
20
40
60
80
100
120
140
160
Alb
ania
Angola
Arm
enia
Azerb
aijan
Bela
rus
Bolivia
Bots
wana
Bulg
ari
a
Burk
ina F
aso
CÃ
´te
d'Ivoir
e
Cam
ero
on
Chin
a
Colo
mbia
Congo,
Republic o
f
Costa
Ric
a
Cro
ati
a
Congo
Ecuador
Egypt
El Salv
ador
Eth
iop
ia
Gab
on
Gam
bia
, T
he
Ghana
Guate
mala
Guin
ea
Guyana
Hond
ura
s
Iran
Jam
aic
a
Jord
an
Kenya
2005 2015