Ethnic Diversity in Compulsory Schooling and Occupational Choices: Can Diversity Increase the Supply in Care‐Oriented Occupations

Migration can contribute to economic growth. Its impact on ethnic diversity may also generate socio-cultural tensions and political instability. Having said that, ethnic diversity can play a role in both promoting and hindering economic growth depending on its form and extent. This role often rests on the levels of either ethnic fractionalization (usually related to higher economic growth) or ethnic polarization (more commonly associated with lower economic growth). Such considerations raise a question about the ways ethnic diversity mediates the relationship between internal migration and economic growth. The following paper responds to that question by focusing on different regions of Indonesia. Drawing on comprehensive statistics and updated classification of Indonesia’s ethnic groups, it presents new evidence on the archipelago’s ethnic diversity which is cross-referenced with recent fractionalization and polarization indexes. This methodological enhancement allows the study to translate with a greater degree of accuracy the mediation of ethnic diversity on the relationship between internal migration and economic growth across Indonesia’s regions than previously carried out. What emerges is a rather mixed picture of the intermediating role of ethnic diversity. There is a significant influence in various regions, but different sets of variables also modulate the relationship in others. We can also discern an identifiable link between the economic region in question, the indicators of ethnic diversity referenced, and the given rate of migration. Placed in composite relief, the findings draw attention to the uneven and complex character of Indonesia’s regional development.

The increasing incidence of ethnic conflicts, and the much-publicized consequences of these conflicts, have attracted the interest of many researchers in the social sciences. Many studies have addressed directly the issue of ethnic diversity and its effects on social conflicts and civil wars. Political scientists have stressed the importance of institutions in the attenuation or intensification of social conflict in ethnically divided societies. Recently economists have connected ethnic diversity with important economic phenomena like investment, growth, or the quality of government (William Easterly and Ross Levine, 1997; Alberto Alesina et al., 2003; Rafael La Porta et al., 1999). The number of papers dealing with the effects of ethnic diversity on issues of economic interest is growing rapidly. In this respect, it is common in recent work to include as a regressor in empirical growth estimations an index of ethnic fractionalization. There are several reasons to include such an indicator. First, some authors have argued that ethnically diverse societies have a higher probability of ethnic conflicts, which may lead to civil war. The political instability caused by potential ethnic conflicts has a negative impact on investment and, indirectly, on growth. Second, ethnic diversity may generate a high level of corruption which, in turn, could deter investment. Finally it has been argued that in heterogeneous societies the diffusion of technological innovations is more difficult, especially when there is ethnic conflict among groups in a country. Business as usual is not possible in a society with a high level of potential ethnic conflict, since this situation affects all levels of economic activity. Trade may be restricted to individuals of the same ethnic group; public infrastructure may have an ethnic bias; government expenditure may favor some ethnic groups, etc. The common element in all these mechanisms is the existence of an ethnic conflict which, through social and political channels, spreads to the economy. However, many empirical studies find no relationship between ethnic fractionalization, ethnic conflict, and civil wars. There are at least three alternative explanations for this. First, it could be the case that the classification of ethnic groups in the Atlas Nadorov Mira (henceforth ANM), source of the traditional index of ethnolinguistic fractionalization (ELF), is not properly constructed. Some authors have used other sources to construct datasets of ethnic groups for a large sample of countries. In general, the correlation between the index of fractionalization obtained using these alternative data sources is very high (over 0.8). Second, James D. Fearon (2003) has argued that it is important to measure the “ethnic distance” across groups in order to obtain indicators of cultural diversity. He measures these distances in terms of the proximity in a tree diagram of the families of languages of different countries. As in the case of alternative data sources, the correlation of the index of ethnic fractionalization, using these distances, with the original ELF index is very high, 0.82. * Montalvo: Department of Economics, Universitat Pompeu Fabra, C/Ramon Trias Fargas 25-27, Barcelona 08005 Spain, and Instituto Valenciano de Investigaciones Economicas (e-mail: montalvo@upf.es); Reynal-Querol: the World Bank, 1818 H Street, NW, Washington, DC 20433 (e-mail: mreynalquerol@worldbank.org). We are grateful for comments by Antonio Villar, Joan Esteban, Paul Collier, Tim Besley, and two anonymous referees. We thank the participants of seminars at the World Bank, Institut de la Mediterranea, Toulouse, Brown University, the European Economic Association Meetings, and the Winter Meetings of the Econometric Society. We would like to thank Sergio Kurlat, William Easterly, and Anke Hoeffler for sharing their data. Financial support from the BBVA Foundation and the Spanish Secretary of Science and Technology (SEC2003-04429) is kindly acknowledged. Jose G. Montalvo thanks the Public Services Group of the Research Department (DECRG) of the World Bank, where most of the revision of this paper was done, for their hospitality. The conclusions of this paper are not intended to represent the views of the World Bank, its executive directors, or the countries they represent. 1 Measured by the ELF index using the data of the Atlas Nadorov Mira. 2 Montalvo and Reynal-Querol (2000), Alesina et al. (2003), or Fearon (2003). 3 See also Francesco Caselli and W. John Coleman (2002).

Acts of xenophobia are a persistent feature of life in South Africa. Daily animosity often spills over into violence against both locals and mostly migrants and their economic enterprises. One argument is that xenophobia has characterized post-apartheid South Africa partly due to increased migration flows. Can migration cause xenophobia? Using data from Xenowatch Reports, we examine the impact of migration flows from Zimbabwe on the onset and persistence of acts of collective violence targeted at foreign nationals’ lives and their foreign-owned businesses in South Africa. Results show that increased migration flows from Zimbabwe into South Africa leads to ethnic polarization, cultural diversity, and intolerance by residents toward immigrants. The variable migrants has a positive but statistically insignificant effect on xenophobia. However, migration can impact xenophobia through inducing ethnic fractionalization, cultural diversity and ethnic polarization, intolerance, and hostility with the coefficients of ethnic fractionalization and cultural diversity being positive and statistically significant and supporting the hypothesis that more migration flows from Zimbabwe lead to more xenophobic attacks in South Africa. These findings aid our understanding of the economic consequences of xenophobia. JEL codes: Q15, Q32, Q54

This paper analyzes the relationship between ethnic fractionalization, polarization, and conflict. In recent years many authors have found empirical evidence that ethnic fractionalization has a negative effect on growth. One mechanism that can explain this nexus is the effect of ethnic heterogeneity on rent-seeking activities and the increase in potential conflict, which is negative for investment. However the empirical evidence supporting the effect of ethnic fractionalization on the incidence of civil conflicts is very weak. Although ethnic fractionalization may be important for growth, we argue that the channel is not through an increase in potential ethnic conflict. We discuss the appropriateness of indices of polarization to capture conflictive dimensions. We develop a new measure of ethnic heterogeneity that satisfies the basic properties associated with the concept of polarization. The empirical section shows that this index of ethnic polarization is a significant variable in the explanation of the incidence of civil wars. This result is robust to the presence of other indicators of ethnic heterogeneity, other sources of data for the construction of the index, and other data structures.

Ethnic diversity has an impact on many areas of social life, which has led to an extensive layer of research on relationships in this area. Many authors have studied in detail the impact of ethnic diversity on conflicts, instability, domestic politics, other various social and cultural aspects. At the same time, the relationship between ethnic fractionalization and economic parameters remains insufficiently studied, which leaves a wide field for relevant research, especially at the level of individual countries, since most of the work is devoted to cross-country comparative analysis of the relevant parameters. One of the most actual problems in the context of ethnic heterogeneity is its relationship with income inequality. This article presents the results of a study of the relationship between ethnic diversity, estimated on the basis of the ethno-linguistic fractionalization (ELF) index, and two indicators of income inequality — the Gini coefficient and the inter-decile income share ratio (S90/S10). The analysis of this relationship was carried out on the example of one country — Kazakhstan — by comparing the corresponding indicators for seventeen regions. The results of the analysis showed the presence of a stable and noticeable relationship, expressed in the growth of income inequality as ethnic diversity grows in the regions of the country. It was revealed that in the most ethnically homogeneous regions, income inequality indicators are minimal, while in the most ethnically diverse regions they are much higher. A significant correlation was also found between ethnic fractionalization and indicators of income inequality. The results obtained are generally correspond to the results of a number of cross-country studies, but in the case of Kazakhstan they are more distinct, which can be interpreted as confirmation of the relationship between ethnic diversity and income inequality in general.

While the development impacts of finance have been extensively documented in the empirical growth and financial development literatures on the one hand, the list of drivers of financial development is undoubtedly expansive to accommodating some other important variables on the other hand. Owing to the growing importance of fragmentation on development outcomes, this study specifically queries how fragmentation influences financial development for a panel of Thirty-five (35) sub-Saharan African countries, over the period 2005–2015. We proxy fragmentation with broad measures of ethnicity and religion which are further decomposed into their subcomponent indices viz.: fractionalization and polarization, respectively. The empirical evidence is based on Pooled Ordinary Least Squares, Fixed Effects Model and Dynamic System Generalized Method of Moments with forward orthogonal deviations. The following are the main findings. First, ethnic polarization is found to exert a positive significant impact on various measures of financial development thus validating the Ethnic Diversity Dividend Thesis. Second, the much prevalent view of the Ethnic Diversity Debit Thesis finds application in ethnic fractionalization and religion diversity measures. Lastly, the significant roles of some conditioning variables like GDP per capita, infrastructure, institutional quality, legal origins and latitude are also empirically validated. On policy ground; we suggest, applaud and welcome any private sector-led reform which could help strengthening healthy competition between/among the ethnically polarized groups within the African society.

Using data from U.S. states, I investigate the relationship between ethnic diversity and trust. I find a negative relationship between ethnic polarization and trust and a U-shaped relationship between ethnic fractionalization and trust. According to my estimations, (a) going from an ethnic polarization index (PI) of 0 to an ethnic PI of 1 decreases trust by almost 12% points; and (b) trust is minimized when the ethnic fractionalization index is equal to 0.34. (JEL D74, J15, Z13)

The purpose of this research is to determine the degree of ethnic fractionalization and polarization in the parent districts of the new Indonesian Capital of Nusantara (IKN), namely Kutai Kartanegara (Kukar) and North Penajam Paser (PPU) Districts, and assess the potential of ethnic conflict. The research involves quantitative analysis, where statistical formulas are used to calculate the ethnic fractionalization index (EFI) and ethnic polarization index (EPOI). The 2010 BPS population census, the most recent census based on ethnicity, is the primary data used for the core analysis. The study results reveal that both districts have a high level of ethnic diversity, with Kukar having a higher EFI than PPU (0.80 versus 0.75). However, PPU has a greater potential for conflict, as it has a higher EPOI (0.66) than Kukar (0.59-0.60). Considering the socio-political situation, the condition of ethnopolitics in Kukar is relatively conducive to providing support for the IKN development. In PPU, its ethnopolitical climate appears favorable for supporting the development of IKN. However, it is crucial to pay due attention to the issue of indigenous Paser people in IKN, as they represent the third largest ethnic group in Rings 1 and 2 of the IKN areas.

Despite recent efforts to increase the participation of women in advanced educational training and high-status professional fields, women and men are still concentrated in different occupations and educational programs, and women are still underrepresented in many high-status occupational fields—particularly those associated with physical science, engineering, and applied mathematics. Many factors, ranging from outright discrimination to the processes associated with gender role socialization, contribute to these gendered patterns of educational and occupational choices. This paper summarizes a set of social and psychological factors that Eccles and her colleagues have been studying for the past 15 years in an effort to understand the occupational and educational choices of women and men. The paper summarizes the key features of the theoretical model they developed and provides an overview of the empirical support now available for key aspects of this model. The implications of this model for understanding the link between gender roles and gendered educational and occupational decisions are discussed.

A student self-determination profile of occupational and educational choices was examined through the concepts of Locus of Causality and Locus of Orientation. Research questions associated with respondents’ certainty of occupation and orientation to vocational education were answered. The tested hypotheses were as follows: (a) Independence, initiative, self-guidance, choice of discussion forums, and gender are related to certainty of future occupation choice and choice of vocational education; (b) certainty of occupation relates to choosing vocational education; (c) negatively biased media lessens interest in vocational education; and (d) vocational education choices are related to gender. A survey of ninth-grade students in Finnish comprehensive school was conducted after implementation of a work-orientation program defined in the national comprehensive school curriculum. At the local school system level, 649 subjects of the mean ages of 16.0 years participated in an Internet survey in two school districts in southwestern Finland in 2008. The variables were inserted in Linear Multiple Regression Analysis in IBM SPSS. The means of vocational school choice and certainty of occupation, and vocational school choice and negative media image were compared in SPSS means. An independent-samples t test for vocational school choice and sex was conducted. Statistically significant regression models of loci of orientation and locus of causality were found. The more the respondents were certain of their occupation choice, the more they expressed their secondary education orientation to be vocational school. When students discussed their choices less at home, their orientation to vocational education weakened. A negative media image was not associated with vocational school choice in this data. The measured means for girls’ and boys’ orientations to vocational school did not show statistically significant differences.

Ethnic Diversity and Poverty

This study investigates the influence of ethnic and political fractionalisation on the provision of public goods at a district level in Sri Lanka. Evidence shows that political fractionalisation has a greater negative impact on the provision of public goods compared with ethnic fractionalisation. Similarly, political polarisation has a greater negative effect on the provision of public goods compared with ethnic polarisation. The interaction between ethnic and political measures suggests that political fractionalisation (political polarisation) exacerbates the negative effects of ethnic fractionalisation (ethnic polarisation) on the provision of public goods. The ethnolinguistic fractionalisation (ELF) index assumes greater statistical significance under fixed effects estimation suggesting greater within district effects in the relationship between ELF and public good provision.

Using cross-country data, we explore the relationship between ethnic and religious diversity and income inequality. For 58 countries spanning a 10-year period, we find a positive relationship between ethnic and religious polarization and income inequality and an inverse U-shaped relationship between ethnic and religious fractionalization and income inequality. According to our estimations (i) going from an ethnic (religious) polarization index of 0, to an ethnic (religious) polarization index of 1 would increase the Gini coefficient by almost 6 (respectively, 3) percentage points; and (ii) the Gini coefficient would be maximized when the ethnic (religious) fractionalization index is equal to 0.44 (respectively, 0.34). Implications are considered.

Dramatic changes in the ethnic composition of countries in the last decades have sparked new interest among social scientists in studying and uncovering the role of ethnic diversity on social, political and economic outcomes. Yet, most ethnic fractionalization indices used by scholars to study these effects treat ethnic heterogeneity as time-invariant, thus concealing its long-term effects. However, failing to take into account historical developments in ethnic composition might seriously hinder our understanding of their effects on social, economic, and political outcomes. This paper introduces a new dataset containing an annual ethnic fractionalization index for 162 countries across all continents in the period of 1945–2013. The Historical Index of Ethnic Fractionalization (HIEF) dataset is a natural extension of previous ethnic fractionalization indices. It offers the opportunity to study the effects of ethnic fractionalization across countries and over time. The article concludes by offering some preliminary descriptive analysis of patterns of change in ethnic fractionalization over time.

The study investigated the need for students of technology and vocational education to be adequately informed when making decision in occupational choice and job opportunities. The information required by students when making informed decision in occupational choice and job opportunities were self profile evaluation; information on available occupations and job opportunities; information on the recognizable risk in various occupations and job opportunities as well as socio-economic information. One hundred and twenty seven (127) NCE II (200 Level) students of Technical Education, Federal College of Education (Technical), Omoku, Nigeria constituted the study population. The study sample was sixty (60) students. The Arithmetic Mean was used to determine whether in the opinion of the students there was need for informed decision-making in occupational choice and job opportunity. The Median score was 2.50. The Chi-square(X2) statistical method was used to test whether there was a significant relationship between the opinion of the students on the need for informed decision –making, and occupational choice and job opportunity in technology and vocational education. The findings established that at probability level of 0.50, there was a significant relationship between students’ opinion on the need for informed decision-making and choice of occupation and job opportunities. DOI: 10.5901/jesr.2014.v4n1p453