MatyKonte

Economic and Political Effects of Remittances in the Developing World

Economic and Political Effects of Remittances inthe Developing World

Maty Konte

United-Nations University (UNU-MERIT)

EMAEE, Maastricht, June, 2015


General Introduction

Overview

Overview

I Significant increase in international inflows in many developing countries(ODA, FDI, migrant remittances).

I Remittances in 2013: three times larger than ODA; second largest inflows;World Bank (October, 2014)).

I World Bank (2014) projections: grow by 5.0% to reach US-dollar 435billion in 2014 (accelerating from the 3.4% expansion of 2013), and risefurther by 4.4 percent to US-dollar 454 billion in 2015

I Remittances as share of GDP amounted to more than 10% (Honduras,Senegal); Over 20% (Lesotho, Moldova, Nepal), up to 30% in Tajikistanor 42% in Kirgiz Republic.



Background

BackgroundI Remittances have been associated with many desirable economic and

development features:

I Inequality and Poverty alleviation (Adams and Page(2005)).

I Education (Edwards and Ureta (2003)).

I Consumption smoothness (Gupta et al(2009)).

I Remittances and growth? Mixed results, different potentialmechanisms, inconclusive debate.

I Beyond the economic angle: Remittances and institutionsI Promote corruption (Abdih et al(2012))

I Decline government effectiveness and accountability (Berdiev etal(2013)) and rule of law.

I Reduce the legitimacy of autocratic regimes and favor the likelihoodof a democratic transition (Wright et al(2012)

I Remittances and democracy in Africa weakly documented.



Main Results

Main Results

I Do Remittances Not Promote Growth in Developing countries?I Main results: Remittances do promote growth depending on the type

of growth regime that a country has. For a large number of SSAcountries remittances have the potential of increasing the level of theeconomic growth.

I Towards another Resource Curse? Remittances and Support forDemocracy in Africa

I Main results: Remittances receivers may have a lower support fordemocracy than their counterpart depending on the subtype ofindividuals that we consider.The perception of the main nationalpriority helps to determine the sub-types of individuals. Choosingfreedom and rights decreases the likelihood to be in the subtypewhere remittances reduce the degree of support for democracy.



Outline

Outline

1. Do Remittances Not Promote Growth? Konte(2014), UNU-MERITworking paper.

2. The Effects of Remittances on Support for Democracy in Africa: AreRemittances a Curse or a Blessing? Konte(2015), UNU-MERITworking paper.

3. General Conclusion


Part I: Do Remittances Not Promote Growth?

Introduction

Growth and Remittances: Mixed Results

1. Optimistic view (Catrinescu et al(2009), WB(2006)):

I Remittances stimulate the investment in human capital (Edwardsand Ureta(2003)); and the stock of physical capital(Lucas(2005),Glytos (2002)).

I Source of investment for small businesses and good talentedentrepreneurs financially constrained (Amuedo-Dorantes and Pozo(2006a)).

2. Skeptical view: (chami et al(2003), Rao and hassan (2011); Singh etal(2011)).

I Not oriented towards growth-enhancing activities: Stark (1995)I Moral Hazard effect(Amuedo-Dorantes and Pozo (2006b), Lokshin

and Glinskaya(2009), Ebeke(2012) etc..)I Dutch Disease hypothesis: Acosta et al(2012); Bourdet and

Falck(2006).



Introduction

Remittances and Growth Regimes

I Do all countries follow the same and unique growth regime?

I Unobserved heterogeneity: deeply explored by Durlauf and Jonson(1995),recent work by Owen et al(2009), Bos et al(2010) among others.

I Yet, studies on remittances and growth have not really considered theexistence of multiple growth regimes.

I Heterogeneity is considered by either dividing the sample based onobserved characteristics (income, geographical location, financialdevelopment), or by terms of interactions with a-priori chosen variables.



introduction

Correcting Heterogeneity

I Is dividing the sample fully correct possible unobserved heterogeneity?

1. Heterogeneity on one variable ignores potential heterogeneity onother variables.

2. Countries with similar observed characteristics may share differentgrowth regimes (Owen et al(2009), Bos et al(2010), Konte(2014))

3. Countries with different observed characteristics may have commongrowth regime (Owen et al(2009), Bos et al(2010))

I This paper re-examines the effect of remittances on growth in asample of developing countries, and relaxes the hypothesis of theuniqueness of growth regime in favor of multiple growth regimes.



Introduction

Contribution

I First, we test whether countries follow different growth regimes, and testwhether the effect of remittances on growth depends on the growthregime to which a country belongs.

I Second, investigating to what extent the level of financial developmentand geography may explain the classification of the countries into thedifferent growth regimes found.

I Application of the Mixture of regression method (Owen et al(2009), Boset al(2010), Flachaire et al(2014), Konte(2014)..).

I But using the recent Three-step Mixture regression (Vermunt etal(2013)): More flexibility and a better fit.



Introduction

Related literature

1. The effect of remittances on growth in developing countries:

I Different samples and different econometrics techniques, but resultsremains mixed (Singh et al(2011), Catrinescu et al(2009), Chami etal(2003)..)

2. Multiple growth regimes: correcting unobserved heterogeneity in growthregressions

I Starting with Durlauf and Johnson (1995), pooling all the countriesinto one growth model is questionable

I Recent studies have applied semi and nonparametric approach to testthe multiplicity of regimes (Bos et al(2010), Owen et al(2009)).

I Institutions and multiple growth regimes (Flachaire et al(2014));natural resources and growth (Konte(2014)).

3. Financial development and remittances: Substitutes or complements?

I Giuliano and Ruiz-Arranz (2009), Bettin and Zazzaro (2011);Nyamongo et al(2012).



Data

Descriptive Statistics

I 5-years panel data covering 1970-2010, yielding 8 time periods.

I Two samples: Full (121 developing countries with at least oneobservations); restricted (91 countries with at least 4 observations)

Table: Descriptive Statistics

Variable Obs Mean Std. Dev. Min Max Sourcegrowth 951 1.48 3.94 -23.14 24.14 Penn World Table 7.1remit 674 .05 .09 0 .89 World Development Indicatorsln(findev) 707 3.35 .65 .54 5.38 World Development Indicatorsln(pop+0.05) 1040 1.92 .24 -2.52 2.61 Penn World Table 7.1ln(gdp) 951 7.74 .95 5.08 10.17 Penn World Table 7.1ln(invest) 970 2.98 .57 .43 4.29 Penn World Table 7.1ln(open) 970 4.08 .67 .64 5.53 Penn World Table 7.1ln(inflation) 847 2.39 1.31 -3.73 8.68 World Development Indicators



Standard Estimation

Parametric estimations

growthi,t = 0 + 1gdp0,i,t + 2(popi,t + 0.05) + 3invi,t

+5remiti,t + 6opennessi,t + 7inflati,t + 8Xi,t + i,t

OLS FE RE OLS FE OLS-IV FE-IVremit -0.0548 -4.199 0.138 0.328 -2.842 0.924 -4.656

(1.509) (2.884) (2.007) (1.530) (1.955) (1.648) (4.513)ln(gdp) -0.285* -5.931*** -0.624*** -0.320** -5.284*** -0.258 -5.507***

(0.152) (0.557) (0.219) (0.159) (0.564) (0.167) (0.707)pop -1.567*** 0.347 -0.600 -1.060** 0.484 -0.952* 0.667

(0.501) (0.481) (0.492) (0.503) (0.473) (0.499) (0.467)invest 1.323*** 1.635*** 1.468*** 1.423*** 1.634*** 1.383*** 1.535***

(0.282) (0.389) (0.329) (0.283) (0.389) (0.303) (0.418)open 0.237 1.357*** 0.779** -0.0564 1.347*** -0.188 1.522***

(0.246) (0.455) (0.332) (0.261) (0.464) (0.278) (0.514)inflation 0.00616 -0.352*** -0.162 -0.150 -0.433*** -0.0329 -0.274*

(0.120) (0.128) (0.125) (0.134) (0.147) (0.137) (0.156)findev -0.0141 -0.286 -0.491 0.213 -0.468 0.0181 -0.388

(0.230) (0.410) (0.299) (0.234) (0.424) (0.243) (0.493)Constant 3.263* 41.06*** 3.369 2.574 36.11*** 3.031 36.57***

(1.876) (4.798) (2.341) (1.872) (4.840) (1.889) (5.702)time .. .. .. .. ..R-squared 0.154 0.344 0.160 0.335 0.167Nb obs 579 579 579 517 517 450 450Nb country 121 121 121 92 92 92 92



Mixture of regression model

Single versus Multiple growth regimesI if K=1 then:

growthi,t = 0 + 1remiti,t + 2xi,t + , i,t N(0, 2)

I If K=2 then:

Group 1: growthi,t = 01 + 11remiti,t + 21xi,t + i,t,1, 1 N(0, 21),Group 2: growthi,t = 02 + 12remiti,t + 22xi,t + i,t,2, 2 N(0, 22)

I If K=3 then:

Group 1: growthi,t = 01 + 11remiti,t + 21xi,t + 1, 1 N(0, 21),Group 2: growthi,t = 02 + 12remiti,t + 22xi,t + 2, 2 N(0, 22),Group 3: growthi,t = 03 + 13remiti,t + 23xi,t + 3, 1 N(0, 23).......



Mixture of regression model: Step 1

Goodness of fitI What is the optimal number of growth regimes? (the optimal value for

K)?

Table: Goodness of fit

Number of regimes BIC CAIC

K=1 2558.37 2574.37K=2 2524.42 2557.42K=3 2530.48 2580.48K=4 2535 2602

f (growth|remit, x; ) =Kk=1

pik fk (growth|remit, x; k , k ) (1)

I K: Number of growth regimes.

I pik: Proportion of countries that follow follow the given growth regime k

I : Set of parameters.




Selected Model Estimation Results

growth Class1 Class2 Wald(=) p-valuepi1=0.47 pi2=0.53

remit -4.4505 3.7368*** 4.4422 0.035(3.6469) (1.2785)

ln(gdp) -1.4347*** -0.0783 10.2808 0.0013(0.3876) (0.1523)

ln(pop+0.05) -5.883*** 0.1233 0.21




Classification of countries in regime 1, and in regime 2

Albania(0.974) Armenia(1) Azerbaijan(1) Belize(0.999)Botswana(1) Cambodia(1) Cameroon(0.99) Cape Verde(0.99)Dominica(0.99) Dominican Republic(0.99) Egypt(1) El Salvador(0.71)Gambia(0.98) Grenada(1) Guinea-Bissau(0.99) Guyana(0.99)Indonesia(0.99) Jamaica(0.99) Jordan(1) Kazakhstan(1)Kyrgyzstan(0.93) Laos(1) Malaysia(1) Mauritius(0.89)Moldova(0.92) Mozambique(0.99) Panama(1) Papua New Guinea(0.98)Paraguay(0.99) Peru(0.93) Romania(0.96) Seychelles(0.99)Sierra Leone(0.69) Sri Lanka(0.99) St, Lucia(0.99) St.Vincent Grenadines(0.99)Suriname(1) Swaziland(1) Syria(0.87) Tanzania(0.66)Thailand(1) Tonga(0.87) Vanuatu(0.99)

Bangladesh(0.84) Benin(0.84) Bolivia(0.96) Brazil(0.96)Burkina Faso(0.99) Central African Republic(0.60) Colombia(0.98) Congo, Republic of(0.99)Costa Rica(0.86) Cote dIvoire(0.87) Djibouti(0.78) Ecuador(0.52)Ethiopia(0.63) Fiji(0.97) Gabon(0.92) Ghana(0.85)Guatemala(0.83) Guinea(0.95) Honduras(0.58) India(0.94)Iran(0.85) Kenya(0.98) Lesotho(0.98) Madagascar(0.99)Malawi(0.62) Maldives(0.79) Mali(0.89) Mauritania(0.80)Mexico(0.99) Morocco(0.94) Namibia(0.70) Nepal(0.82)Nicaragua(0.89) Niger(1) Nigeria(0.89) Pakistan(0.84)Philippines(0.94) Rwanda(1) Samoa(0.97) Senegal(0.99)South Africa(0.98) Sudan(1) Togo(0.99) Tunisia(0.89)Turkey(0.99) Venezuela(0.52) Yemen(0.81) Zimbabwe(0.89)




Determinants of the probability to be in regime 2

k(i)2 =

{1 if the country i has a higher probability of being in regime 2 ,

0 otherwise

(2)We can then estimate:

pi = Prob(k(i)p = 1, i) (3)




Determinants of the probability to be in regime 2

Table: Determinants of class membership

[1] [2] [3] [4] [5]Intercept 1.7239 2.9646 5.1256*** -0.5652 3.6206*

(1.6748) (1.8858) (1.7936) (0.4196) (2.0428)ln(credit/gdp) -0.4981

(0.4692)ln(liquid liab/gdp) -0.8635*

(0.5222)ln(broadmoney/gdp) -1.4595*** -1.1209**

(0.4917) (0.5314)SSA 1.2965** 0.8166

(0.6287) (0.6055)latincar 0.1587

(0.6625)landlock 0.0448

(0.6809)Nb obs 91 92 92 92 92



Conclusion

Part I: Conclusion

I This paper seeks to shed light why it has been so difficult to find apositive effect of remittances on growth rate.

I It has relaxed the hypothesis of a single unique growth regime in favor ofmultiple regimes.

I Remittances affect growth differently across the growth regimes.

I In one regime: remittances have a neutral effect on growth; in the otherone remittances have a positive effect (robust to different specificationsand sample size).

I Being a SSA country increases the chance of being in the remittancesgrowth-enhancing activity.

I Higher is the level of financial development, lower is the probability ofbeing in the remittances growth-enhancing regime.


Part II: The Effects of Remittances on Support for Democracy in Africa: Are Remittances a Curse or a Blessing?

Introduction

Remittances and political participation

I Resource model of political participation by Brady et al(1995): Resources(money, time and skills) are political participation enhancing.

I In contrast, negative effect of remittances on political participation ofreceivers.

I Decrease the political engagement in municipalities with high level ofout-migrants (Goodman and Hiskey (2008)).

I Decrease the likely to pressure and oppose politicians because they aremore optimistic about their economic conditions Germano (2013).

I Mixed results for the African context: Less likely to vote (Ebeke and Yogo(2013), Dione et al (2014)); more likely to contact government and totake part in demonstrations and protests Dione et al (2014).



Introduction

Remittances and legitimacy

I Remittances may sustain autocratic governments (Ahmed (2012))I Remittances and public spending as substitutes, thus leaders free-ride

and more patronage goods (Abdih et al(2011); Ahmed(2012))

I Remittances may reduce the legitimacy of autocracies (Wright etal(2012)) and favor process of democratization (Pfutze (2012,2014))

I Difficult to pay supporters through patronage private goods. itbreaks the clientelistic relationship between citizens and leaders.

I This paper tests whether remittances are a curse or a blessing for thelegitimacy of democracy in Africa.

I It also looks at to what extent individuals perception of the main nationalpriorities may explain the link between remittances and legitimacy ofdemocracy.



Introduction

Determinants of support for democracy

I Democracy is deposited as a universal value (Sen(1999)) and associatedto many desirable features (Persson and Tabellini (2006); Siegle et al(2004)).

I Micro level: Political scholars have pointed-out the legitimacy ofdemocracy (degree of support for democracy) as important determinantof the level of democracy in a country (Diamond(1999)).

I Different determinants of support for democracy (education, religion,gender, income among others); what about remittance income?

I We argue that the effect of remittances on support for democracy variesacross groups of individuals sharing similar but unobserved backgroundcharacteristics.



Introduction

Contribution

I First, we consider the possibility of the existence of hidden clusters ofindividuals sharing similar but unobserved background characteristics suchthat the effect of individual socio-economic characteristics (includingremittances) on the degree of endorsement and support for democracydepends on the cluster of individuals that we consider.

I Second, we provide an analysis of the determinants of the subtypes ofindividuals using the perception of the national priorities as potentialdeterminants (freedom and rights, economic conditions....).

I Multilevel Mixture Regressions, recently developed for multilevel datastructure

I Account for both country and individual possible unobservedheterogeneity.



Introduction

Related literature1. Remittances and quality of institutions.

I Negative: Corruption (Abdih et al(2012); Government effectivenessand rule of law(Berdiev et al(2013));Sustain autocratic government(Ahmed (2012))I Remittances and public spending as substitutes, thus leaders free-ride

and more patronage goods (Abdih et al(2011); Ahmed(2012))

I Positive: Reduce the legitimacy of autocracies (Wright et al(2012));Favor process of democratization (Pfutze (2012,2014))I Difficult to pay supporters through patronage private goods. it break

the clientelistic relationship between citizens and leaders.

2. Remittances and political involvement, participation and choice.

I Remittances are associated with a decrease of political engagementin Mexico(Germano(2013)

I Mixed results for the African context (Dione et al(2014))

3. Determinants of support for democracy in Africa.

I Education (Evans and al(2007)); Gender (Garcia-Penalosa andKonte(2014)); Religion (MacCauley and Gyomah-Boadi(2009)).



Data

Dependent variable: support for democracy

I The Afrobarometer data contains series of national surveys on theattitudes of citizens towards democracy, market, civil society, and otheraspects of development in Africa.

I Round 4: 27.000 interviewees in 20 SSA countries in 2008.

I Which of these three statements is closest to your opinion?

1. Democracy is preferable to any other kind of government.

2. In some circumstances, a non-democracy government can bepreferable.

3. For some like me, it does not matter what kind of government wehave.

4. I dont know.

SDij =

{1 if the individual i living in country j answers 1,

0 otherwise



Data

Measuring remittances

I How often, if at all, do you receive money remittances from friends orrelative outside of the country?

remitij =

{1 if the individual i living in country j receives it at least one,

0 otherwise



Data

Measuring national priorities

I If you had to choose, which one of the following things is the mostimportant national priority?

1. Giving people to say more in government decisions.

2. Protecting peoples right to live freely; 0 otherwise.

3. Maintaining order in the nation; 0 otherwise.

4. Improving economic conditions of people.

I Rights is 1 if reply 1 or 2; Order is 1 if reply 3; Economy is 1 if the lastreply.

I And which would be the next most important?I Right2, Order2 and Economic2.



Empirical Analysis

Methodology: standard Multilevel specification

Prob(SDij = 1, ij) =1

1 + exp(ij) (4)

where,ij = 0j + 1remitij + 2Xij + ij (5)

0j = 0 + uj (6)



Empirical Analysis

Remittances and Support for DemocracyReference Variable (1) (2) (3) (4)No remit -0.116*** -0.135*** -0.164*** -0.156***

(0.0369) (0.0374) (0.0379) (0.0385)No formal educ1 0.216*** 0.238*** 0.200*** 0.191***

(0.0452) (0.0468) (0.0475) (0.0481)educ2 0.566*** 0.624*** 0.540*** 0.556***

(0.0415) (0.0448) (0.0465) (0.0472)educ3 0.708*** 0.778*** 0.652*** 0.674***

(0.0522) (0.0565) (0.0595) (0.0604)educ4 0.944*** 0.981*** 0.821*** 0.847***

(0.0602) (0.0649) (0.0689) (0.0699)Male Female -0.348*** -0.323*** -0.294*** -0.297***

(0.0278) (0.0302) (0.0307) (0.0312)> 26 < 25 < 35 0.113*** 0.120*** 0.0289

(0.0383) (0.0387) (0.0405)> 36 0.304*** 0.313*** 0.189***

(0.0402) (0.0406) (0.0428)rural urban 0.107*** 0.0515 0.0628*

(0.0317) (0.0338) (0.0343)No head -0.0185 -0.0326 -0.00433

(0.0340) (0.0343) (0.0349)Observations 27,352 26,736 26,422 26,022Number of country 20 20 20 20

** significant at 5%, * significant at 10%. Robust errors are in brackets.



Multilevel Mixture strategy

Unobserved categories of individuals?

I Being a remittance-recipient decreases the probability of supportingdemocracy.

I Do all the individuals behave similarly?

I There may exist different subtypes of individuals that share similar butunobserved characteristics.

I We now relax the hypothesis of the existence of a unique single equationthat links support for democracy and remittances.

I we provide an analysis of the determinants of the subtypes of individualsusing the perception of the national priorities as potential determinants.





I Recently developed for multilevel data structure (Asparouhov and Muthen(2009); Henry and Muthen (2010))

I Not yet widespread in social science.

I Account for both country and individuals possible unobservedheterogeneity.

I Two classes: Gclass for the number of clusters for countries, and Cclassfor clusters at the individual level

I The cluster of a country may have an impact on the cluster of anindividual living in this country.

I Two individuals with similar background characteristics may be sorted indifferent clusters because their countries belong to different clusters.




Specification

Prob(SDij = 1, ijGC) =1

1 + exp(ijGC ) (7)

where,ij = 0j + 1Cremitij + 2CXij + ijC (8)

0j = 0G + ujG (9)

I For a fixed value of G we estimate different models with different valuesfor C, and we move to the next G.

I Selection of the optimal (C*;G*) using statistical criteria

I Our best best model contains (2;6)




Multilevel Mixture: Remittances, Support for Democracyand First National Priority

Reference Variable Class 1 Class 2(pi1=0.73) (pi2=0.27)

No remit -0.2616** -0.0675(0.1175) (0.1283)

No formal educ1 0.23** 0.393**(0.1153) (0.1988)

educ2 0.4091*** 1.1836***(0.1158) (0.2022)

educ3 0.5915*** 1.2962***(0.1803) (0.227)

educ4 0.5984*** 1.6478***(0.2127) (0.2475)

Male female -0.4143*** -0.3758***(0.1105) (0.0918)

Constant 1.1806*** -2.0926***(0.3093) (0.2874)

ConcomitantOrder - 0.1148

- (0.0870)rights - 0.4632***

- (0.0868)Total observations 25800




Remittances, Support for Democracy and National Priority

Reference Variable Cluster 1 Cluster 2 Cluster1 Cluster2(pi1=0.80) (pi2=0.20) (pi1=0.73) (pi2=0.27)

No remit -0.2074*** -0.1421 -0.2432** 0.0859(0.0559) (0.1499) (0.1201) (0.1282)

No educ1 0.1982*** 0.537** 0.2085* 0.3883*(0.0618) (0.2627) (0.1201) (0.1999)

educ2 0.4403*** 1.4054*** 0.3797*** 1.1538***(0.062) (0.2875) (0.1198) (0.2035)

educ3 0.5735*** 1.481*** 0.551*** 1.2749***(0.0872) (0.3092) (0.1856) (0.2277)

educ4 0.6643*** 1.862*** 0.5568** 1.6292***(0.1021) (0.3305) (0.2199) (0.2496)

Male female -0.3292*** -0.3067*** -0.4141*** -0.3653***(0.0465) (0.102) (0.1164) (0.0921)

Concomitantrights1 - - 0.466***

- - (0.0915)order2 - -0.0558

- (0.1416)rights2 - -0.3140*** - 0.0592

- (0.1155) - (0.0645)



Conclusion

Part II: Conclusion

I Remittances effects on the quality of institutions: mixed results.

I At the individual level: little is known for the African context

I We have shown that such non-taxable income may hinder the muchneeded legitimacy of democracy in this region if the individuals are moreconcerned about the improvement of their economic conditions than theirrights and freedom.

I Further research

I Remittances and democracy in Africa: Short term versus long term

I Panel data: the negative effect may disappear with time aftereconomic satisfaction.

I Different rounds in the Afrobarometer but only one containsinformation about remittances.



General conclusion

General ConclusionI The economic benefits of migration for the countries of origin are realized

primarily through the receipt of remittances.

I Remittances are growing in many developing nations, surpassingsignificant ODA.

I Large amount of informal remittances inflows.

I The global average cost of sending remittances continued its downwardtrend in the third quarter of 2014, falling to 7.9 percent of the value sent(WB(2014)).

I Policies that are intended to increase the level of formal remittances havethe potential of increasing the level of growth rate for some countries,including many SSA countries.

I Towards another resource curse for democracy in Africa? It depends onthe degree to which freedom and rights are valued.

I More remittances may increase the growth rate which may be translatedinto a substantial improvement of the economic conditions of people.Beneficial for the legitimacy of democracy?



General conclusion

Thank you for your attention!!!

Bedankt voor uw aandacht!!!



General conclusion

Classification

Table: Classification of countries

Gclass1 Gclass2 Gclass3 Gclass4 Gclass5 Gclass6Cape Verde(1) Burkina Faso(1) Benin(1) Mozambique(1) Lesotho(1) Madagascar(1)Ghana(1) Nigeria(1) Botswana(1) Namibia(1)Kenya(1) Senegal(1) Uganda(1) South Africa(1)Liberia(0.99) liberia(0.01) Zambia(1)Malawi(1) Nigeria(1)Mali(1) Tanzania(1)

Zimbabwe(1)



General conclusion

Descriptive statistics

Country RemitBenin 12.28Botswana 11.43Burkina Faso 23.09Cape Verde 49.04Ghana 22.53Kenya 10.86Lesotho 30.05Liberia 22.29Madagascar 4.63Malawi 10.63Mali 24.27Mozambique 10.42Namibia 16.16Nigeria 24.76Senegal 31.13South Africa 15.76Tanzania 5.35Uganda 12.88Zambia 9.55Zimbabwe 30.42



General conclusion

National priorities

First most important Second most importantRights 24.95 50.01Order 16.49 23.2Economic 58.57 26.79Total 100 100



General conclusion

Goodness of fitClass Gclass BIC CAIC

1 1 30848.98 30869.982 1 30951.42 30994.423 1 31061.50 31126.504 1 31194.89 31281.895 1 31304.21 31413.216 1 31395.99 31526.992 2 29987.09 30032.093 2 30091.19 30159.194 2 30216.12 30307.125 2 30366.78 30480.786 2 30465.08 30602.082 3 30351.13 30465.133 3 29773.03 29844.034 3 29945.95 30040.955 3 30015.51 30134.516 3 30135.61 30278.612 4 29669.36 29718.363 4 29718.65 29792.654 4 29849.11 29948.115 4 29953.14 30077.146 4 30096.94 30245.942 5 29637.59 29688.593 5 29710.75 29787.754 5 29852.72 29955.725 5 29975.35 30104.356 5 30110.69 30265.696 6 30130.03 30291.032 6 29626.83 29679.833 6 29705.66 29785.664 6 29834.05 29941.055 6 2992.19 30126.192 7 29644.09 29699.093 7 29694.86 29777.864 7 29836.19 29947.195 7 30008.09 30147.096 7 30153.15 30320.15

General IntroductionOverviewBackgroundMain ResultsOutline

Part I: Do Remittances Not Promote Growth?IntroductionIntroductionintroductionIntroductionIntroductionDataStandard EstimationMixture of regression modelMixture of regression model: Step 1Mixture of regression model: Step 1Mixture of regression model: Step 2Mixture of regression model: Step 3Mixture of regression model: Step 3Conclusion

Part II: The Effects of Remittances on Support for Democracy in Africa: Are Remittances a Curse or a Blessing?IntroductionIntroductionIntroductionIntroductionIntroductionDataDataDataEmpirical AnalysisEmpirical AnalysisMultilevel Mixture strategyMultilevel Mixture strategyMultilevel Mixture strategyMultilevel Mixture strategyMultilevel Mixture strategyConclusionGeneral conclusion

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remittances receivers

migrant remittances

subtypewhere remittances

developing countriesoda

developing worldeconomic

developing worldpart

economic angle

typeof growth regime