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Quality of Institutions and Transmission of Social Traits: The Case of Tolerance

  • Muhammad Tariq MajeedEmail author
Original Research Article
  • 39 Downloads

Abstract

Tolerance- willingness to accept others’ feelings and beliefs- who are different from us- is one of the important humankind virtues. It is a valuable asset for the young generation. Tolerance equips the children with the potential to bear diversity, interact with others who are different and to get chances of success in this integrated world. This study investigates whether the quality of institutions plays any role to induce parents’ willingness to teach and instill tolerance in their children. To study this relationship, we used a survey measure of tolerance from World Value Survey (WVS) for a sample of 57 countries over the period 1984–2014. The empirical results show that overall quality of institutions strengthens parents’ willingness to instill tolerance in their children. In a comparative analysis, institutional measures control of corruption and democratic accountability are more conducive for parents’ willingness to teach tolerance to their kids. These findings remain robust to various robustness checks.

Keywords

Social values Tolerance Institutions Adults 

JEL Classifications

C33 D73 K42 

Introduction

Recently, economists have begun to pay attention to institutional and cultural roots of economics. They are not only considering their separate effects on various socioeconomic outcomes, but also observing how they interact with each other (Alesina and Giuliano 2013). The literature shows that market oriented institutions and policies affect people’s way of thinking of others and cultural attitudes (Bowles 1998; Weiss 2003; Mayda and Rodrik 2005; Berggren and Nilsson 2013).

A better institutional infrastructure creates an environment which reduces suspicion that people who are different are exploitative. In a recent study, Kirchner et al. (2011) explore the relationships between institutions and social tolerance and develop institutional theory of social tolerance. They argue that institutional qualities such as fairness, inclusiveness and universality help to reduce status anxiety and stimulant tolerance.

Tolerance- willingness to accept others’ feelings and beliefs who are different from us- is one of the important humankind virtues. It is a valuable asset for the young generation. The literature on tolerance shows that tolerant societies are likely to function better as compared to non-tolerant societies both economically and socially (see, for details, Berggren and Nilsson 2014).

In recent years, the literature has pointed out many favorable outcomes of tolerance. For instance, the studies by Corneo and Jeanne (Corneo and Jeanne 2009a; b), Inglehart et al. (2013) and Berggren and Nilsson (2015) pointed out that tolerance brings happiness among the people of tolerant societies. Corneo and Jeanne (Corneo and Jeanne 2009a, b) are of the view that this is beneficial for the minorities living in any country, as they are affected by the beliefs of the majority living in their surroundings. Berggren and Elinder (2012) and Bomhoff and Lee (2012) argue that tolerance fosters economic growth through innovative productivity of minority group and by allocation of labor and talent within the country.

Berggren and Elinder (2012) argue that an open attitude towards the minorities cause favorable economic outcomes. They provide the evidence from the economies of United Kingdom, Sweden and Netherlands which let enter minority groups in their countries and flourished in technological terms. Mokyr (1990) reviewed historical perspectives of economic development and stated “innovation requires diversity and tolerance”.

The above discussion shows that importance of tolerance for favorable economic outcomes has been widely observed. However, what constitutes tolerance itself is not discussed much in the literature. What are the factors that play a central role in changing the tolerance levels of societies? Surprisingly, these questions have received little attention. In a recent study Berggren and Nilsson (2015) explore whether globalization induces parents to instill tolerance in their children. They argue that this quality equips children for greater success in a more integrated world. Using a sample of 59 countries, they show that globalization increases parents’ willingness to transmit tolerance in their kids. However, they do not consider the role of institutional infrastructure in determining tolerance levels across countries.

This study disentangles the relationship between institutions and tolerance using the data on five proxies of institutions taken from International Country Risk Guide (ICRG). These measures are corruption, rule of law, democracy, bureaucracy quality, and government stability. In this study we try to answer the following two questions: (1) Does high quality of institutions induce parents to instill tolerance in their children? (2) Do different measures of institutions impact tolerance differently? To the best of knowledge, this is the first empirical study of its kind that determines the relationship of tolerance with institutions for a large number of countries over a long period of time. In addition, this study attempts to resolve the issue of endogeneity between tolerance and institutions using both internal and external instruments. Finally, we perform sensitivity analysis to check the robustness of results.

Rest of the study is organized as follows: Section 2 provides theory and evidence on the relationship of tolerance with institutions. Section 3 provides the framework for empirical analysis. Section 4 describes the data and its sources. Empirical findings are discussed in Section 5. Finally, Section 6 concludes the study.

Quality of Institutions and Tolerance: Theoretical Links

In recent decades social values are changing all over the world. For instance, the importance of traditional relationships (such as family) has decreased, orientation patterns (such as religious convictions) are rapidly changing, and the speed of information flow has rapidly increased. These social changes have led to diverse living styles, social groups and attitudes. Concurrently, divergent macro structures and the modernization processes are transforming attitudes, values and the perceptions of (out-) groups (Wernet et al. 2005). How these changes have impacted the societies, however, is somewhat ambiguous. Whereas these changes lead to cultural, political and social diversity, they also compete with one another and increase the importance for tolerance.

A tolerant person respects diversity and accepts the participation of every type of individual in the society (Berggren and Nilsson 2013). Our understanding about tolerance is based upon the concept given by Corneo and Jeanne (Corneo and Jeanne 2009a, b, p. 691), they define it as “respect for diversity”. We also follow Florida (2003, p.10) who defines it as “openness, inclusiveness and diversity to all ethnicities, races and walks of life”.

In the literature, tolerance is used in different ways. Some studies linked it to generality and non-discrimination (Buchanan and Congleton 1997), others prove it as virtue (Vernon and LaSelva 1984). There are some empirical studies which link tolerance with urbanism and economic freedom (Berggren and Nilsson 2013), income and growth (Florida et al. 2008; Ottaviano and Peri 2006; Das et al. 2008; Berggren and Elinder 2012). This study is linked with the literature on transmission of social traits in adults through institutional development.

Generally sociologist and political scientists explain cross-country differences of tolerance levels following the theories of cultural modernization. These theories suggest that as economic prosperity increases along with the deepening market relations, respectful orientations promote democratic personalities and liberal attitude. This causes growing tolerance of human diversity (see, for example, Nevitte 1996; Inglehart 1997).

Theoretically, the literature highlights two main links connecting institutions and tolerance: one relating to government activities and other relating to market activities. Governments decide on central issues of concern for how people behave and think through taxation, expenditures and regulation. Citizens trust on government in the presence of high quality institutions and expect equal treatment and therefore demonstrate high tolerance. Market actives also shape tolerance in the society. There is a long, not least Marxist tradition of telling a pessimistic story about markets. Some elements of this story, such as markets giving rise to exploitation, economic inequality and selfishness, can be related to social attitudes like tolerance. (See, for details, Berggren and Nilsson 2016). These effects are dampened when societies invest in institutional infrastructure (Arampatzi et al. 2019; Woolcock 2019).

Corneo and Jeanne (Corneo and Jeanne 2009a; b) develop an economic theory of tolerance where lifestyles and traits are invested with symbolic value by people. The theory considers value systems as endogenous which are taught by parents. These value systems influence the honor enjoyed by individuals. On the one hand, intolerant individuals attach all symbolic value to a limited number of traits and become disrespectful of people with different traits. On the other hand, tolerant people have diversified values and respect social alterity.

Kirchner et al. (2011) explore the relationships between political institutions and social tolerance and develop institutional theory of social tolerance. “Specific facets of political institutions such as inclusiveness, universality, and fairness are capable of reducing the threat of losing social status and thereby contribute to the development of social tolerance. When people come to believe that political institutions exhibit these qualities, they will generally tolerate others in their society Kirchner et al. (2011, p. 203).” Based on hierarchical analyses of the World Values Survey (2005–08) and national statistics for 28 countries, they show that institutional qualities such as fairness, inclusiveness and universality help reduce status anxiety and stimulant tolerance.

Relating to market institutions, a high quality of the rule of law brings about tolerance, because individuals expect that the legal system will treat everyone equally, fairly and in accordance with the rule of law. Relating to the market process, the tendency for tolerance to be internalized can be expected, since it makes people less suspicious of others and more relaxed in their attitudes.

Berggren and Nilsson (2013) argue that a free economy is characterized by dynamism and development – and therefore by uncertainty. This argument can be extended to expect a favorable influence of institutions on tolerance because with high quality institutions, people are less prone to fear that they will lose out and that others, for whom they have no sympathy, benefit. Berggren and Nilsson (2013) investigate the relationship between economic freedom and different measures of tolerance. They argue that a tolerant person accepts the participation of every type of person in the society. Using a cross-country data of 65 economies they found out that economic freedom is associated with greater tolerance.

Berggren and Nilsson (2015) investigate the impact of globalization and its different dimensions on tolerance using a panel data. They point out two basic grounds for the question why adults think it important to teach tolerance to their children. One is imperialistic base and the other is altruistic. They found out that only social and economic globalization have positive impact on transmitting social values like tolerance but not political. Korobeynikova (2015) argued that only soft globalization- the implementation of globalization with mental form- is successful in increasing tolerance, while material globalization causes the destruction of civilization. In the process of soft globalization, non-suppressive mechanism of social regulation is realized.

We can conclude that tolerance, an emerging field in economics, does not simply mean to understand the feelings of others but has wider implications such as acceptance and recognition. Some studies linked it to generality and non-discrimination, other prove it as virtue. Some studies claimed that it as a sufficient condition to boost economic growth. The empirical studies link tolerance with urbanism, economic freedom, and globalization. However, the empirical literature has largely ignored the role of institutional infrastructure in explaining cross-country differences of tolerance levels. In this study we focus on the quality of institutions as a main cause of tolerance.

Theoretical Framework

Why and how quality of institutions affect parents’ attitude in transmitting values in their children? To answer this question, it is important to understand the theoretical links of quality of institutions with this social trait. We relate these processes of social norms to institutions with a view that quality of institutions affects behavior of people, their standard of living is changing and above all their wellbeing.

The literature suggests that market oriented institutions and policies affect people’s way of thinking of others and cultural attitudes (Bowles 1998; Weiss 2003; Mayda and Rodrik 2005; Berggren and Nilsson 2013). A better institutional infrastructure creates an environment which reduces suspicion that people who are different are exploitative. Kirchner et al. (2011) argue that institutional qualities such as fairness, inclusiveness and universality help to reduce status anxiety and stimulant tolerance. We specify the following econometric equations to estimate the impact of different dimensions of institutions on tolerance:

$$ {Tol}_i={\alpha}_0+{\beta}_1{ins}_{it}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(1)
$$ \left(i=1,\dots \dots \dots N;t=1,..\dots \dots T\right) $$
Where ‘i’ indicates country and ‘t’ indicates time.

Where, Toli is importance of teaching tolerance to children by their parents. The term insi refers to the quality of institutions. It is average of government stability, corruption, law and order, democratic accountability and bureaucracy quality. The vector Z includes control variables which affect tolerance. Note that in the last part of the equation that A, the unobservable country effect, has zero correlation with explanatory variables and is ‘fixed’ overtime; εit is the residual term with normally distributed random disturbances. It is important to note that a higher score on all institutional measures refer to the better quality of institutions and vice versa. For instance, 6 score on corruption index means no corruption at all while zero score refers to full corruption. To include institutional measures, eq. (1) can be extended as follows:

$$ {Tol}_i={\alpha}_0+{\beta}_1{corruption}_{it}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(1.1)
$$ {Tol}_i={\alpha}_0+{\beta}_1 law\&{order}_{it}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(1.2)
$$ {Tol}_i={\alpha}_0+{\beta}_1{democracy}_{\mathrm{i}t}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(1.3)
$$ {Tol}_i={\alpha}_0+{\beta}_1{bureaucracy}_{it}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(1.4)
$$ {Tol}_i={\alpha}_0+{\beta}_1{govt\ stab}_{it}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(1.5)

The Data Description

To study the relationship between quality of institutions and tolerance, this study uses a sample of 57 countries over the period 1984–2014. To empirically investigate whether quality of institutions makes more parents willing to instill tolerance in their children, we use as our dependent variable the share of people in different countries who answer “Tolerance” when being asked the question: “Here is a list of qualities that children can be encouraged to learn at home. Which do you consider to be especially important?”. The data on tolerance has been taken from World Value Survey ( 2015). We measure institutions using corruption, rule of law, democracy, quality of bureaucracy and government stability. The data on institutions is derived from International Country Risk Guide (ICRG 2015).
Table 1

Descriptive Statistics

Variable

Obs

Mean

Std. Dev.

Min

Max

Tolerance

57

68.2055

11.32261

36.8

86.88

GDP per capita

57

12,188.38

14,695.48

290.297

56,813.3

Corruption

57

3.211277

1.219046

1.46481

5.98148

Law & Order

57

3.792833

1.332089

1.55278

6

Democracy

57

4.099277

1.331278

.959722

6

Bureaucratic Quality

57

2.423681

1.05479

0

4

Govt. Stability

57

7.73502

.8179163

6.340741

9.994445

Urban Population

57

61.8844

21.41019

9.70073

98.6573

Quality of Institutions

57

4.252418

.9781002

2.39694

6.16398

In addition, control variables are added following previous studies on causes of tolerance. The high level of national income is expected to increase the tolerance of a society. High income increases level of satisfaction in individuals thus enhancing the capability to accept diversity (Berggren and Nilsson 2015; Corneo and Jeanne Corneo and Jeanne 2009a, b). Urban population growth is expected to be positively related to create tolerance in the society because urban areas have greater diversity than that of less dynamic rural areas (Berggren and Nilsson 2013, 2014). To measure the impact of global interactions we use trade as a control variable. Globalization can cause both positive and negative effects on parents’ willingness to tech tolerance to their kids (Berggren and Nilsson 2015). As globalization creates opportunities, profit seeking firms and well-being maximizing individuals have stronger incentives to be tolerant and to try to make their children tolerant. In contrast, it is also possible that globalization might contain some elements that reduce tolerance and a willingness to teach it to kids. Two main reasons for expecting a negative effect are cultural exclusivism and fear. Lastly, we include geographical dummies to control certain regional effects. The description of data sources and definitions are given in Appendix (Table 6, 7, and 8).
  • Table 1 reports descriptive statistics of data used for empirical analysis. The lowest value of tolerance 36.8 belongs to Bahrain while highest value 86.88 belongs to Sweden. For institutional quality Iraq represents weak institutions (2.40) while Finland shows strong institutions (6.16).

Table 2

Correlation Matrix

  

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Tolerance

(1)

1.00

         

GDP per cap.

(2)

0.47

1.00

        

Corruption

(3)

0.51

0.86

1.00

       

Law & Order

(4)

0.31

0.85

0.86

1.00

      

Democracy

(5)

0.60

0.64

0.72

0.55

1.00

     

Bureau. Qual.

(6)

0.44

0.84

0.86

0.81

0.66

1.00

    

Govt. Stab

(7)

0.13

0.52

0.50

0.59

0.09

0.52

1.00

   

Urban Pop.

(8)

0.20

0.57

0.64

0.53

0.42

0.56

0.27

1.00

  

Trade

(9)

−0.14

−0.11

−0.13

−0.08

−0.20

−0.14

0.11

−0.32

1.00

 

Institutions

(10)

0.49

0.89

0.96

0.91

0.76

0.92

0.59

0.59

−0.12

1.00

Table 2 reports correlation matrix. It is evident from the model that all institutional measures are positively associated with the importance of teaching tolerance to kids. In a comparative analysis democratic accountability and control of corruption show the highest correlation of 0.60 and 0.51, respectively. The institutional measure government stability shows comparatively lower correlation of 0.13. Figure 1 displays a positive association between quality of institutions and tolerance.
Fig. 1

Quality of institutions and tolerance

Empirical Results

We estimate the relationship between tolerance and institutional quality in the context of cross sectional estimation techniques. Table 3 contains the results for the different measures of quality of institutions and the willingness to teach children tolerance, controlling one measure at a time. The empirical estimates show that all measures of quality of institutions are positively associated with tolerance. In a comparative analysis, control of corruption, democratic accountability and bureaucratic quality are more effective in producing tolerance as these measures are statistically significant with positive signs. The overall impact of institutional quality is reported in column 6 of Table 3. It shows that 1 unit increase in overall quality of institutions increases 0.20% of tolerance level.
Table 3

Tolerance and Quality of Institutions: Cross Sectional Estimates

 

(1)

(2)

(3)

(4)

(5)

(6)

VARIABLES

Tolerance

Tolerance

Tolerance

Tolerance

Tolerance

Tolerance

Control of

0.127***

     

Corruption

(0.0343)

     

Law & Order

 

0.0287

    
 

(0.0376)

    

Democratic

  

0.0866***

   

Accountability

  

(0.0216)

   

Bureaucratic

   

0.140***

  

Quality

   

(0.0400)

  

Government

    

0.0206

 

Stability

    

(0.0344)

 

Quality of

     

0.210***

Institutions

     

(0.0472)

Urbanization

−0.00546***

−0.00384**

−0.00443***

−0.00383**

−0.00360*

−0.00436***

(0.00169)

(0.00186)

(0.00161)

(0.00165)

(0.00189)

(0.00156)

Trade

−0.0116*

−0.0122*

−0.0125**

−0.0128**

−0.0117*

−0.0128**

(0.00594)

(0.00680)

(0.00582)

(0.00602)

(0.00680)

(0.00565)

GDP per capita

0.0118

0.0628***

0.0548*

−0.0121

0.0735**

−0.0228

(0.0334)

(0.0394)

(0.0280)

(0.0386)

(0.0340)

(0.0352)

South Asia

−0.0358

−0.0478

0.0244

−0.165

−0.0448

0.00221

(0.150)

(0.172)

(0.149)

(0.155)

(0.174)

(0.144)

Middle East &

0.0153

−0.0973

0.0709

−0.0553

−0.116

0.0483

North Africa

(0.124)

(0.137)

(0.125)

(0.121)

(0.136)

(0.118)

East Asia

−0.0472

−0.0900

0.0172

−0.106

−0.102

−0.0163

(0.113)

(0.129)

(0.114)

(0.114)

(0.129)

(0.108)

Sub-Saharan

−0.0201

−0.0106

0.0956

−0.0342

−0.0235

0.0676

Africa

(0.135)

(0.156)

(0.136)

(0.137)

(0.155)

(0.130)

Latin America

0.153

0.0690

0.124

0.109

0.0372

0.232*

(0.120)

(0.143)

(0.115)

(0.119)

(0.133)

(0.119)

Europe

0.0748

0.0448

0.0557

0.104

0.0431

0.115

(0.107)

(0.122)

(0.104)

(0.110)

(0.123)

(0.103)

Constant

3.995***

3.812***

3.593***

4.198***

3.671***

3.683***

(0.247)

(0.277)

(0.241)

(0.271)

(0.337)

(0.230)

Observations

54

54

54

54

54

54

R-squared

0.514

0.367

0.533

0.501

0.364

0.561

Regarding control variables the impact of GDP per capita is significant and positive implying that people become more tolerant at higher levels of economic development. However, this effect is not robust in all models. High income increases level of satisfaction in individuals thus enhancing the capability to accept diversity (Berggren and Nilsson 2015; Corneo and Jeanne Corneo and Jeanne 2009a, b). The impact of trade on tolerance is consistently negative and significant indicating that tolerance levels are lower in more open economies. The likely reason could be that openness might comprise some elements that decrease tolerance. For example, two main reasons for expecting a negative effect are cultural exclusivism and fear (see Berggren and Nilsson 2015). The impact of urbanization is also negative and significant implying that more urbanization decreases the tolerance levels.

Since the possible problem of endogeneity can weaken the strength of causal relationship and may provide biased results, we resolve this problem using internal and external instruments following La Porta et al. (1999), Acemoglu et al. (2001), Klerman et al. (2009) and Tebaldi and Mohan (2010). To address the possible problem of endogeneity, we use initial values of institutional measures. Moreover, we also use exogenous instruments of colonial origins (Tebaldi and Mohan 2010) and religious fractionalization (La Porta et al. 1999) for institutional variables.

The empirical literature on quality of institutions shows that historical and geographical factors explain cross-country heterogeneity of institutions (La Porta et al. 1999; Acemoglu et al. 2001; Klerman et al. 2009). For example, Acemoglu et al. (2001) argued that European designed dissimilar institutional policies in different colonies. The colonies which were having the problems of infectious diseases, such as malaria, were viewed disadvantageous by the European. In these colonies, they discouraged the formation of institutions which promote property rights and treated these colonies as extractive states.

European formed property rights and European style institutional infrastructure in colonies which were geographically advantageous such as having better environment. Acemoglu et al. (2001) assert that initial institutional infrastructure provides the bases for the establishment of current institutions and economic development.

Similarly, La Porta et al. (1999) assert that historical factors such as the legal origin provide the bases for current institutions. The geographic specific factors such as distance from the equator and ethno-linguistic heterogeneity are viewed as essential factors for the formation of present institutions. Figure 2 provides the summary of discussion on instruments of instituions.
Fig. 2

Legal and colonial origin, institutions and tolerance

The above discussion can be summarized in the forma of an equation as follows:
$$ {Institutions}_{it}={\delta}_{it}+{\delta}_1{legal}_{it}+{\delta}_2{colonial}_{it}+{\delta}_3{Z}_{it}+{\omega}_{it} $$
(a)
Equation (a) is the first stage regression equation for 2SLS. The variable legal represents legal origin that is English, French or Socialist law. This variable is extracted from La Porta et al. (1999). It is measured as a set of binary outcome variables where 1 is assigned to country belonging to a particular legal system and 0 otherwise. The variable colonial region depicts colonial history of a country. It is also measured as s set of binary outcome variables where 1 is given to a country having a particular colonial history and 0 otherwise. The data on colonial origin is taken from Klerman et al. (2009). The row vector ω given in equation (a) represents other instruments such as initial values of endogenous variables, absolute latitude ethno-linguistic fragmentation and black market exchange rates. The data on latitude and ethno is derived from La Porta et al. (1999). While the data on black market exchange rate is derived from Gwartney et al. (2006). That said, we specify second stage equation for 2SLS which uses the estimated values of financial development and institutions generated from first stage regressions.
$$ {Tol}_i={\alpha}_0+{\beta}_1 ins{(estimated)}_{it}+{\beta}_2{GDP}_{it}+\varnothing Z+{A}_{it}+{\varepsilon}_{it} $$
(b)
The results reported in columns (1–5) of Table 4 indicate that institutional measures corruption, law and order, democratic accountability and bureaucratic quality have positive and significant impact on the level of tolerance. Similarly, the results reported in column 6 indicate that 1 unit increase in quality of institutions causes 0.20% increase in tolerance level of a society. The result on government stability is insignificant suggesting that the individual impact of government stability is perhaps not important whereas its collective effect with other measures of institutions turns out to be consistently significant.
Table 4

Tolerance and Quality of Institutions: 2SLS (Cross Sectional Data)

 

(1)

(2)

(3)

(4)

(5)

(6)

Variables

Tolerance

Tolerance

Tolerance

Tolerance

Tolerance

Tolerance

Control of

0.153***

     

Corruption

(0.0392)

     

Law & Order

 

0.0857*

    
 

(0.0472)

    

Democratic

  

0.124***

   

Accountability

  

(0.0285)

   

Bureaucratic

   

0.122***

  

Quality

   

(0.0467)

  

Government

    

0.0479

 

Stability

    

(0.0523)

 

Quality of

     

0.201***

Institutions

     

(0.0643)

Urbanization

−0.00590***

−0.00258

−0.00478***

−0.00388***

−0.00336*

−0.00440***

(0.00153)

(0.00170)

(0.00149)

(0.00148)

(0.00174)

(0.00139)

Trade

−0.0116**

−0.00921

−0.0127**

−0.0126**

−0.0115*

−0.0127**

(0.00523)

(0.00616)

(0.00536)

(0.00540)

(0.00611)

(0.00504)

GDP per capita

−0.00336

0.0209

0.0427

−0.000851

0.0641*

−0.0194

(0.0324)

(0.0401)

(0.0265)

(0.0398)

(0.0338)

(0.0394)

South Asia

−0.0421

0.00179

0.0534

−0.157

−0.0263

−0.00704

(0.133)

(0.151)

(0.139)

(0.141)

(0.159)

(0.129)

Middle East

0.0370

−0.0678

0.148

−0.0646

−0.122

0.0393

& North Africa

(0.111)

(0.120)

(0.123)

(0.109)

(0.123)

(0.112)

East Asia

−0.0400

−0.0279

0.0659

−0.107

−0.104

−0.0219

(0.100)

(0.114)

(0.108)

(0.102)

(0.116)

(0.0985)

Sub-Saharan

−0.0287

0.0350

0.143

−0.0387

−0.0174

0.0574

Africa

(0.119)

(0.139)

(0.129)

(0.123)

(0.139)

(0.118)

Latin America

0.194*

0.159

0.177

0.106

0.0543

0.233**

(0.109)

(0.136)

(0.109)

(0.108)

(0.123)

(0.116)

Europe

0.0811

0.0688

0.0642

0.0937

0.0559

0.111

(0.0945)

(0.107)

(0.0963)

(0.0994)

(0.112)

(0.0935)

Constant

4.060***

3.827***

3.524***

4.158***

3.516***

3.701***

(0.222)

(0.243)

(0.227)

(0.257)

(0.386)

(0.207)

Observations

53

52

53

53

54

53

R-squared

0.531

0.326

0.507

0.502

0.355

0.567

Elements of good institutions like less corruptions, strong property rights, justice and rule and law with its rich interaction, disciplined by reputation effects, make people realize that whom they do not know can be decent and honest as a result the level of tolerance boosts up (Berggren and Nilsson 2014).

Table 5 presents the results using GMM (IV) estimation method. In the presence of cross-country heterogeneity GMM (IV) method gives more efficient results. The baseline findings remain same that is a higher level of quality of institutions produces more tolerance in the society. Column (6) indicates that 1 unit increase in quality of institutions causes 0.19% incline in tolerance level of a society. The null hypothesis that instrumental variables are exogenous is not rejected. The coefficients of institutional measures control of corruption, democratic accountability and bureaucratic quality indicate significant and positive impact on the level of tolerance. The answers to research questions are as follows: (1) High quality of institutions induces parents to instill tolerance in their children? (2) The direction of the effect of different measures of institutions on tolerance is same, however, comparatively control of corruption, democratic accountability and bureaucratic quality are more significant in improving the tolerance levels of the societies.
Table 5

Tolerance and Quality of Institutions: GMM (IV)

 

(1)

(2)

(3)

(4)

(5)

(6)

Variables

Tolerance

Tolerance

Tolerance

Tolerance

Tolerance

Tolerance

Control of

0.114***

     

Corruption

(0.0311)

     

Law & Order

 

0.129***

    
 

(0.0414)

    

Democratic

  

0.117***

   

Accountability

  

(0.0260)

   

Bureaucratic

   

0.0997***

  

Quality

   

(0.0356)

  

Government

    

0.0259

 

Stability

    

(0.0533)

 

Quality of

     

0.191***

Institutions

     

(0.0490)

Urbanization

−0.00466***

−0.00143

−0.00517***

−0.00308***

−0.00410***

−0.00401***

(0.000948)

(0.00153)

(0.00104)

(0.000825)

(0.00135)

(0.000808)

Trade

−0.0138***

−0.0115**

−0.0138***

−0.0118***

−0.0144***

−0.0145***

(0.00394)

(0.00490)

(0.00450)

(0.00357)

(0.00467)

(0.00358)

GDP per capita

0.00221

−0.0313

0.0574**

0.00252

0.0851**

−0.0330

(0.0258)

(0.0420)

(0.0226)

(0.0300)

(0.0352)

(0.0270)

South Asia

−0.0701

−0.0332

0.135

−0.156

−0.00441

−0.0399

(0.0747)

(0.108)

(0.118)

(0.114)

(0.0998)

(0.0966)

Middle East

−0.0283

−0.0649

0.179**

−0.0235

−0.0747

−0.0193

& North Africa

(0.0546)

(0.0766)

(0.0722)

(0.0823)

(0.118)

(0.0545)

East Asia

−0.0717

−0.0390

0.0798

−0.131*

−0.0897

−0.0515

(0.0437)

(0.0504)

(0.0631)

(0.0693)

(0.0806)

(0.0498)

Sub-Saharan

−0.0550

0.0172

0.161

−0.0537

0.00817

−0.00775

Africa

(0.0600)

(0.0928)

(0.0999)

(0.0849)

(0.0984)

(0.0668)

Latin America

0.130***

0.179***

0.194***

0.0787

0.0594

0.194***

(0.0378)

(0.0674)

(0.0611)

(0.0541)

(0.0683)

(0.0620)

Europe

0.0781***

0.112***

0.0572

0.107**

0.0525

0.117***

(0.0266)

(0.0336)

(0.0436)

(0.0474)

(0.0605)

(0.0388)

Constant

4.100***

4.036***

3.442***

4.151***

3.542***

3.877***

(0.182)

(0.236)

(0.180)

(0.230)

(0.299)

(0.131)

Observations

53

52

53

53

54

53

R-squared

0.523

0.205

0.507

0.462

0.357

0.550

Table 6

Data Sources and Variable Definitions

Variables

Definitions

Sources

Tolerance

Share of the population answering important to the quality “Tolerance” when asked question “Here is the list of qualities that children can be encouraged to learn at home. Which do you consider important?

[1]

Corruption

ICRG index 0–6 scale; where 0 indicate high degree of corruption and 6 indicate no corruption.

[3]

Law and Order

ICRG index 0–6 scale; where 6 indicate high degree of law and order.

[3]

Democratic Accountability

ICRG index 0–6 scale; where 6 indicate high degree of democracy.

[3]

Bureaucratic Quality

ICRG index 0–4 scale; where 4 indicate high degree of bureaucratic quality.

[3]

Government Stability

ICRG index 0–12 scale; where 0 indicates very high risk and 12 indicates very low risk.

[3]

Real GDP per capita

Log real GDP per capita, constant prices

[4]

Urban Population

Share of population living in urban areas

[2]

Trade Openness

It is the sum of exports and imports (% of GDP).

[2]

Colonial Origin

A value of 1 is assigned if the country belongs to a particular colony and 0 otherwise.

[5]

Ethno-Linguistic

It is ethno-linguistic fragmentation

[5]

Legal Origin

It is a dummy variable. The legal origin of a country can be British, French German, Socialist or Scandinavian

[6]

Sources: [1] World Values Survey, online data base, 2015; [2] World Bank, World Development Indicators online data base ( 2015); [3] ICRG ( 2015); [4] Penn World Table 8.1; [5] Klerman et al. (2009); [6] La Porta et al. (1999)

Table 7

Cross Sectional Data of Tolerance and Institutions

Country

Tolerance

Institutions

Corruption

Law

Democracy

BQ

GS

Albania

80.55

3.64139

2.67037

3.0625

4.21806

1.41667

6.83935

Algeria

57.7

3.52324

2.35787

2.45

3.08889

1.68889

8.03056

Argentina

63.1333

4.04574

2.8662

3.32037

4.4213

2.58056

7.04028

Australia

81.4

5.87426

4.86204

5.84583

6

4

8.66343

Bahrain

36.8

4.12083

2.82361

4.8088

2.64815

2.36389

7.95972

Bangladesh

70.05

2.99667

1.62083

1.96019

3.24444

1.31389

6.84398

Brazil

64.7

3.8837

3.02731

2.65556

4.09167

2.41944

7.22454

Bulgaria

49.7

4.20935

3.04167

4.00139

4.95833

2

7.04537

Canada

81.6

5.90935

5.50139

5.90278

5.93056

4

8.21204

Chile

75.52

4.47972

3.75694

4.61296

3.98889

2.71111

7.3287

China

58.84

4.02446

2.7

4.0961

2.00139

2.02897

9.29583

Colombia

79.6

3.6575

2.71481

1.56944

3.91389

2.4

7.68935

Dominican Rep.

67.9

3.76833

2.71481

2.96806

4.31944

1.41944

7.41991

Ecuador

67.7

3.79509

2.89722

3.28194

3.94167

2

6.85463

Egypt

63.45

3.72102

2.10139

3.37731

2.76574

1.83333

8.52732

El Salvador

58.8

3.36574

2.65093

2.06574

3.675

1.25278

7.18426

Finland

84.6

6.16398

5.98148

6

6

3.98194

8.85648

France

86.8

5.3913

4.56482

5.13611

5.74444

3.525

7.98611

Ghana

68.4

3.54102

2.33194

2.31389

3.16667

2.05556

7.83704

Guatemala

59

3.04926

2.24861

1.72361

3.20926

1.26389

6.80093

Hong Kong

41.7

4.48194

4.34306

4.91528

2.09444

3.05694

8

India

58.44

4.19954

2.55417

3.56944

5.00278

2.90278

6.96852

Indonesia

61

3.53139

2.04861

2.74167

3.77361

1.58056

7.5125

Iran

61.75

3.71741

2.71991

3.67778

3.18333

1.86944

7.13657

Iraq

79.0667

2.39694

1.46481

1.55278

2.04259

0.570833

6.3537

Israel

81.9

4.90667

3.93704

4.27778

5.58611

3.6125

7.11991

Italy

73.9

4.6262

3.12639

4.74306

5.0375

2.87917

7.34491

Japan

61.4667

5.34444

4.11111

5.25278

5.41111

3.9875

7.95972

Jordan

72.8

4.22278

3.22037

3.64722

3.45

2.10278

8.69352

Malaysia

74.15

4.54454

3.40139

4.00278

4.04491

2.8

8.47361

Mali

59.9

2.96889

1.98148

2.73333

2.61111

0

7.51852

Mexico

64.55

4.12491

2.56157

2.75463

5.04167

2.58056

7.68611

Morocco

63.1667

4.29278

2.77685

4.49907

3.3213

2.06944

8.79722

Netherlands

85.9

5.94204

5.56111

6

6

4

8.14907

New Zealand

81.1667

5.85241

5.60278

5.83194

5.93333

4

7.89398

Nigeria

64.35

2.89269

1.55556

2.05556

2.81111

1.02222

7.01898

Norway

78.65

5.86157

5.40185

6

6

3.92361

7.98241

Pakistan

53.7

3.05102

1.82639

2.73704

1.97593

1.875

6.84074

Peru

67.35

3.37444

2.71481

2.51759

3.70278

1.58056

6.35648

Philippines

56.6667

3.49398

1.95556

2.40556

4.41944

2.12222

6.56713

Romania

65.3

3.8946

2.75509

3.76667

4.88611

0.825

7.24015

Saudi Arabia

56.4

3.81514

2.29514

4.66111

0.959722

2.19167

8.96806

Singapore

61.95

5.24306

4.55278

5.24167

2.63611

3.79028

9.99444

South Africa

64.4

4.35417

3.85046

2.54028

4.64306

2.79167

7.94537

Spain

73.74

5.08685

4.175

4.75833

5.61944

3.15417

7.72731

Sweden

86.88

5.91111

5.61574

6

6

4

7.93982

Switzerland

82.6667

6.05009

5.18102

5.56111

6

4

9.50833

Thailand

61.35

3.98352

2.33472

3.59583

3.87639

2.44861

7.66204

Trinidad &Tobago

83.2

3.98574

2.41944

3.36389

3.50278

2.58056

8.06204

Turkey

64.7

4.18546

2.67778

3.75602

4.33241

2.18611

7.975

Uganda

56.8

3.39796

2.03148

3.06389

2.10417

1.35556

8.43472

United Kingdom

85.5

5.73398

4.80602

5.66481

5.90833

4

8.29074

United States

71.86

5.79537

4.52778

5.57639

5.92083

4

8.95185

Uruguay

77.8

3.91009

3.09491

2.78194

4.42778

1.63611

7.60972

Venezuela

68.45

3.6462

2.11944

2.88611

4.18889

1.41944

7.61713

Zambia

57.9

3.3675

2.62593

3.37222

3.59583

0.902778

6.34074

Zimbabwe

71

3.03843

1.68102

2.53333

2.28611

2.07639

6.61528

Table 8

Description of Institutional Measures

Corruption – 6 Points

This is an assessment of corruption within the political system. Such corruption introduces an inherent instability into the political process. The most common form of corruption met directly by business is financial corruption in the form of demands for special payments and bribes connected with import and export licenses, exchange controls, tax assessments, police protection, or loans. Although our measure takes such corruption into account, it is more concerned with actual or potential corruption in the form of excessive patronage, nepotism, job reservations, ‘favor-for-favors’, secret party funding, and suspiciously close ties between politics and business. The greatest risk in such corruption is that at some time it will become so overweening, or some major scandal will be suddenly revealed, as to provoke a popular backlash, resulting in a fall or overthrow of the government, a major reorganizing or restructuring of the country’s political institutions, or, at worst, a breakdown in law and order, rendering the country ungovernable.

Law and Order – 6 Points

“Law and Order” form a single component, but its two elements are assessed separately, with each element being scored from zero to three points. To assess the “Law” element, the strength and impartiality of the legal system are considered, while the “Order” element is an assessment of popular observance of the law. Thus, a country can enjoy a high rating – 3 – in terms of its judicial system, but a low rating – 1 – if it suffers from a very high crime rate if the law is routinely ignored without effective sanction (for example, widespread illegal strikes).

Government Stability – 12 Points

This is an assessment both of the government’s ability to carry out its declared program(s), and its ability to stay in office. The risk rating assigned is the sum of three subcomponents, each with a maximum score of four points and a minimum score of 0 points. A score of 4 points equates to Very Low Risk and a score of 0 points to Very High Risk.

The subcomponents are:

• Government Unity

• Legislative Strength

• Popular Support

Bureaucracy Quality – 4 Points

The institutional strength and quality of the bureaucracy is another shock absorber that tends to minimize revisions of policy when governments change. Therefore, high points are given to countries where the bureaucracy has the strength and expertise to govern without drastic changes in policy or interruptions in government services. In these low-risk countries, the bureaucracy tends to be somewhat autonomous from political pressure and to have an established mechanism for recruitment and training. Countries that lack the cushioning effect of a strong bureaucracy receive low points because a change in government tends to be traumatic in terms of policy formulation and day-to-day administrative functions.

Democratic Accountability – 6 Points

This is a measure of how responsive government is to its people, on the basis that the less responsive it is, the more likely it is that the government will fall, peacefully in a democratic society, but possibly violently in a non-democratic one. The points in this component are awarded on the basis of the type of governance enjoyed by the country in question. For this purpose, the following types of governance have been defined:

Alternating Democracy

Dominated Democracy

De Facto One-Party State

De Jure One-Party State

Autarchy

Conclusion

Tolerance is arguably a valuable asset in any society as it seems to make the economy function better by enabling a fuller use of human talent. It is therefore important to know that whether it can be fostered through improving the quality of institutions. This study attempts to answer the question whether quality of institutions plays any role to induce parents’ willingness to teach and instill tolerance in their kids. To study this relationship, we used survey measure from World Value Survey (WVS) for tolerance in a sample of 57 countries spanning over 1984–2014.

We find that overall quality of institutions strengthens parents’ willingness to instill tolerance. This finding is robust to various robustness checks. In a disaggregated analysis of different measures of institutions, it is revealed that corruption, rule of law, democracy and bureaucratic quality are the important dimensions which significantly determine tolerance levels of the societies.

Overall conclusion of this study suggests that quality of institutions is essential in enhancing the tolerance level of a nation. The main policy suggestion from our results is that policy makers need to take care of values of their countries by investing in institutional infrastructure.

The significance of these results is that unlike what many probably would have expected, institutional reforms seem able to influence a widely embraced social attitude, tolerance, through increasing fairness, inclusiveness and universality help. Thus intuitional reforms reduce status anxiety and stimulant tolerance. If the government treats citizens equally, this can send a signal that freedom of expression for all, even for (sometimes despised) minorities, is worthy of public support.

Tolerance is very important now in this age of populism in much of the world. In fact, intolerance has in a matter of a few years become a major threat to the world order and to the survival of humanitarian values, to say nothing to the survival of humanity. Future research needs to focus on migration, immigration or even racial and religious tensions. Moreover, future research needs to focus on country specific or regional specific evidence on institutions and tolerance nexus.

Notes

Compliance with Ethical Standards

Conflict of Interest/Ethical Statement

It is to state that “I do not have any conflict of interest and this research is not sponsored by any organization”.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Economics, Quaid-i-Azam UniversityIslamabadPakistan

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