Law Siong Hook, Ph.D Department of Economics

Universiti Putra Malaysia

Email: lawsh@upm.edu.my

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: lawsh@upm.edu.my

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