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Section 8. Population Economics
Omar Jraid Mustafa Alhanaqtah, Tafila Technical University, Jordan, Assistant Professor, College of Business E-mail: omarhanaqtah@yahoo.com
ETHNO-LINGUISTIC AND RELIGIOUS FRACTIONALIZATION OF WESTERN ASIA: POLITICAL ECONOMY APPROACH
Abstract: The purpose of the research is to configure Western Asian countries in three dimensions: ethnicity, language and religion. While some studies provide measures of ethnic, linguistic and religious fractionalization and revisit a question of the effects of this fractionalization on the quality of institutions and growth, there are no studies which evaluate ethno-linguistic and religious homogeneity of Western Asian region. In the research we discuss why these three issues remain such sensitive and how it relates to the level of trust in a society, explain the possible causes and consequences of societal fragmentation, point shortcomings in the data collection and measurement.
Keywords: homogeneity, ethnicity, language, religion, trust, indices.
1. Introduction Which countries are we 'configuring'? We investi-
The world diversity and its political implications gate 17 countries of Western Asia: Armenia, Azer-
continue to attract attention of economists and social scientists. If we want to configure the world and its regions we first have to disassemble it into its component parts. Many social scientists, as well as the author of this article, use the state as the unit of analysis. We use data on ethnicity, language and religion for international comparisons and, basically, to configure the target region - Western Asia - in three political economy categories. 'Political Economy is not so much a social science discipline as a series of overlapping questions that lie at the intersection between economics, sociology and politics' [22]. Current economic and political reality deeply rooted in history and culture of nations. Thus, one of the objects of the study is to reopen the field and to configure the target region in categories of a cultural economics and an economic sociology as subfields of a political economy.
baijan, Bahrain, Georgia, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestinian Territories, Qatar, Saudi Arabia, Syrian Arab Republic, Turkey, United Arab Emirates and Yemen. The majority of countries of the region are the Middle East Arabic countries.
What are the variables for analysis? The first set of data we will examine is ethnicity, the second is language and the third is religion. We are interested in these categories because we hypothesize that they may directly influence the level of trust in a society. Social trust (e. g. [10; 12; 13]) refers to trust in general and is related to many economic and political issues, such as, for example, better governance [27], economic growth [9; 28; 46], higher rates of subjective wellbeing [24] and higher education [11; 36].
How do we configure the region? We use a comparative analysis technique as a methodology of the research. We begin with ranking the data of all the
world economies in ascending order. This way we see how countries are located in the world on a chosen criterion - ethnicity, language or religion. Then we place our target region - Western Asia - along the world spectrum. Then we describe whether the countries of a target region are at the top, middle, bottom or scattered randomly; whether they are similar or clustered, or diverge radically. After that we analyze the nature of the data and offer possible explanations for the observed results.
The paper contains the results of the serial team research an objective of which is to configure the region of Western Asia in several dimensions such as population, capital income, human development [5], economic globalization, trade, foreign direct investment [3], trust [6], rule of law and control of corruption [4] and other political economy categories. At this stage we analyze the diversity ofWestern Asian countries in the categories of ethnicity, language and religion.
In short, we contribute to the literature by conducting the first study on ethno-linguistic and religious fractionalization ofWestern Asian region. We report first results and encourage further investigation about the diversity of Western Asia from the standpoint of other political economy categories.
2. Configuring Western Asia in terms of ethnicity
Why does ethnic fragmentation matter? First, it does not matter how many ethnicities in the country, what matters is the way they might interact. Second, ethnicity matters because different groups may have different aspirations that, in turn, might have an impact on society, including political issues.
In the XIX century the concept of ethnicity suddenly became very popular. Darwin's theories of evolution, combined with the drive towards imperial domination and exploitation, gave momentum to the idea that there was a definite racial hierarchy in the world. The pseudoscience of eugenics and Nazi ideology in 1920th and 1930th culminated in the slaughter of millions of innocent victims [7; 22; 29;
31; 33; 35; 44]. It cast a dark cloud over almost any neutral discussion of ethnicity, which has became not an abstract concept but a matter of life and death.
Therefore, it was rather surprising when in 1997 the World Bank economists Easterly and Levine constructed the ethno-linguistic fragmentation (ELF) index. In their paper Easterly and Levine [14] show that ethnic diversity helps to explain cross-countries differences in public policies and different economic indicators. In the case study of Sub-Saharan Africa they argued that Africa's high ethnic fragmentation explains a significant part of low schooling, political instability, under developed financial systems, distorted foreign exchange markets, high government deficits and insufficient infrastructure.
The methodology of computation of the ELF index is based on the technique of Herfindahl-Hirschmann index: the variables are lined up in a line and each of them is counted in percentages of the whole, then sum up them and divide by 100 or 10000 (to get the results in decimals). The lower the number the more homogeneous the country is. Even though the study of Easterly and Levine was pioneering, the ELF index could be criticized on the following ground: the most used data was rather old taken from the Soviet Atlas. It had been collected by Soviet ethnographers in the 1960s, provided data on 112 countries.
Therefore, in 2003 another World Bank group of economists, led by Alesina, produced an improved ELF index, based on an analysis of650 ethnic groups, 1055 major linguistic groups and about 294 separate religious groups [1; 2]. They also revisited the question of effects of ethnic, linguistic and religious heterogeneity on the quality of institutions and growth.
It should be mentioned that ethnicity is a very difficult concept to operationalize. It certainly involves race (biological and physiological features), but it is also related to socio-cultural aspirations. There are several complications about data on ethnicity: the problem of legal definition of nationality and ethnicity, difficulties with self-identification,
especially in a case of shared identities, the problem of determination the degree of cultural differences, whether to rely on self-identifiers or external identifiers, whether to look at the context in which the question was asked (political pressures, discrimination, illegality in status, etc.) [22; 37].
Even though the concept and the definition of ethnicity are highly contested, Alesina and his coauthors tried to quantify it. The methodology of ethnic fractionalization index provided by Alesina is also based on Herfindahl-Hirschman technique, and it measures the degree of fragmentation in each part: ethnicity, language and religion. The sources of data are more up-to-date and include the Encyclopedia of Britannica and the CIA Fact Book. The index is expressed in a range of 1 to 0, with the lowest number expressing the greatest degree of homogeneity and the highest showing the greatest diversity.
In accordance with the world map of ethnic frac-tionalization provided by Griffiths [22], the most ethnically homogeneous 15 countries in the world (in descending order) are North Korea, Japan, South Korea, Tunisia, Bangladesh, Portugal, Norway, Sweden, Hong Kong, Denmark, Australia, Haiti, France, Netherlands, Austria. The most ethnically fragmented are
the following 15 countries in the world (in descending order): Uganda, Liberia, Madagascar, Democratic Republic of the Congo (Formerly known as Zaire (capital Kinshasa), Republic of the Congo (Sometimes referred to as Congo-Brazzaville (capital Brazzaville), Cameroon, Chad, Kenya, Nigeria, Central African Republic, Ivory Coast, Sierra Leone, Somalia, Guinea Bissau, Gabon. The analyzed countries of Western Asia neither in the list of the most ethnically homogeneous countries nor in the list of the most ethnically fragmented countries of the world.
Now we will examine countries of Western Asia in terms of ethnic fragmentation. For this purpose we use data on ethnic fractionalization provided by Alesina [1]. The outcomes of ethnic fractionalization of Western Asia are as follows.
In the regional context countries ofWestern Asia diverge radically. The box-plot in Figure 1, constructed by the author in R-Studio (R-script for the box-plot and descriptive statistics on the ethnicity criterion is in 'Appendix'), shows that the distribution of countries is close to symmetric (a bit left skewed, so observations mostly deviate towards heterogeneity) with the median value 0.4373, the mean value 0.41808 and the standard deviation of 0.199.
Figure 1. Box-and-whiskers plot: distribution of Western Asian countries by the criterion of ethnicity
The (Figure 2), constructed by the author in the most ethnically homogeneous country in the
MS Excel based on data provided by Alesina [1], region is Armenia followed by Lebanon and Saudi
represents the distribution of countries of Western Arabia (2nd decile). The most ethnically fragmented
Asia by the criterion of ethnicity. There are no data country in the region is Qatar (9th decile) preceded
on Palestine and Yemen. The bar plot shows that by Kuwait (8th decile), UAE and Jordan (7th decile).
Figure 2. Distribution of countries of Western Asia by the criterion of ethnicity
In the world context Western Asian countries scatter randomly along the world spectrum of ethnic frac-tionalization. In the lower (heterogeneous) deciles we observe oil-rich countries (Qatar, Kuwait and UAE) where there are many labor-immigrants from different cultures making the society diversified. Jordan is in the lower deciles too; the reason of high degree of ethnic fragmentation is a great refugee problem (from Syria, Palestine, Lebanon and Iraq). Former-USSR countries (Armenia, Azerbaijan and Georgia) occupy upper deciles and they are rather homogeneous in terms of ethnicity. The research by Alhanaqtah [5] showed that the level of immigration in these countries either satisfactory or too low. The results on the other countries of the region are explained by historical reasons.
3. Configuring Western Asia in terms of language
Why does linguistic fragmentation matter? First, since the core of the problem with fragmentation is communication, we analyze language diversity. Second, different language groups access different news media and get exposed to different political messages and this enhances cultural differences that inhibit the construction of trust. These factors also affect economic performance not only through the trust mechanism, but also directly by fragmenting markets, raising transaction costs and inhibiting labor productivity. Third, in a polarized society
the dominant group tends to use its power to shape policies in its own interests. If sufficiently powerful it may even do so at the expense of property rights and civil rights. Moreover such dominate groups may promote a 'culture of intolerance' [22]. None of this, of course, is consistent with enhancing trust.
The concept of linguistic diversity is also ambiguous concept to operationalize. There are difficulties with data collection [22]. The first difficulty here is the one's mother's tongue. Language a one speaks at home and the language that is most generally used in a society is not necessarily the same, especially in migrant families. There are also multilingual societies, in which people are bilingual. For example, in Belgium citizens could converse in both French and Flemish. Since recently the country is becoming politically more polarized. Is that because of languages or because of the political issues? [45]. Similar examples we may observe in African countries.
The second difficulty is when does a language become a dialect and when does a dialect become a language? To answer this question linguists usually apply the idea of 'mutual intelligibility'. It means that speech is not counted as a separate language if it can be understood from another language. Looking easy in theory this idea becomes difficult to operationalize in practice. For example, Scandinavians can understand each other, even though they speak different
languages, listed as separate languages [20]. Additionally, Posner [37] argues that the ability to understand another language to some extent also depends on the willingness to do so. Otherwise, the language will be defined as an ethnically different.
Even though the linguistic concept is contested, the attempts to measure the degree of fragmentation of a society by the language criterion have been made. There are two major sources of data: (1) the data by Alesina [1] and his associates, used exclusively the Encyclopedia Britannica and the CIA Factbook, which identified 1055 language groups; and (2) the data by the Ethnologue project collected by the group of linguists interested in preserving languages, which identified 7097 living languages [16]. There is an obvious discrepancy between the two sources, which may be solved by the introduction of the concept of language distance (linguistic trees) in order to capture the degree of similarity between languages.
For our analysis we use the data from the Ethnologue project, which seems more reliable and which takes into account the language distance. The language fractionalization index, constructed by the Ethnologue project in 2009, is expressed in a range of 1 to 0. The lowest number shows the greatest degree of homogeneity, while the highest
number shows the greatest diversity. The map of language fractionalization (divided into deciles), provided by Griffiths [22], shows that the most linguistically homogeneous countries are China, Indonesia, Mexico, Argentina, Belgium, France, Netherlands (1st decile). In the 2nd decile there are Russia and Vietnam. The 3rd decile covers Thailand, Miramar, Sri Lanka and Afghanistan. On the contrary, the 9th decile is represented by seven African countries, India and Israel. There are not any counties of Western Asia in the list of the most linguistically homogeneous countries of the world, while two countries of Western Asia - UAE and Qatar - belong to the list of the most linguistically fragmented countries of the world.
The outcomes of linguistic fractionalization of Western Asia are as follows.
In the regional context countries ofWestern Asia are clustered on the world map of linguistic fragmentation. The box-plot in (Figure 3), constructed by the author in R-Studio R-script for the box-plot and descriptive statistics on the language criterion is in 'Appendix'), shows that the distribution of countries is close to symmetric (a bit left skewed, so observations mostly deviate towards heterogeneity) with the median value 0.578, the mean value 0.5208, the standard deviation value 0.196 and one left outlier.
Figure 3. Box-and-whiskers plot: distribution of Western Asian countries
by the criterion of language
As we may see from Figure 4, constructed by the flows as well as refugee problem from neighboring author in MS Excel, among the least linguistically states, convulsed with wars and social conflicts. At the
homogeneous are oil-rich Arabic countries and hi- same time we should also admit that there is no direct
tech Israel. It might be explained by immigrant labor correlation between welfare and linguistic diversity.
Figure 4. Distribution of countries of Western Asia by the criterion of language
In the world context Western Asian countries mostly represent the middle of the world spectrum of ethnic fractionalization. The 3rd decile is represented by the most linguistically homogeneous countries of the region such as Armenia (left outlier in Figure 3), Lebanon and Palestine. In the 5th decile we observe (in descending order) Turkey, Azerbaijan and Jordan. Syria, Kuwait, Yemen and Georgia are in the 6th decile. Qatar, Saudi Arabia and Israel are in the 7th decile. Oman, Iraq, UAE are the most linguistically diversified countries of Western Asia and occupy the 8th decile. However, we guess, we can't entirely rely on statistical data. Perhaps, Ethnologue project tends to overestimate the number of living languages.
4. Configuring Western Asia in terms of religion
Why does religious fragmentation matter? Religion is a shared belief system which is exercised through a set of shared rituals. It touches the core of one's existence, therefore, might trigger strong and even violent emotions. On the positive side, religious teachings emphasize the benefits of generosity towards others and disapprove of anti-social behavior. Orbel et al. [34], in particular, reports that religious persons are thought to be more cooperative in a prisoner's dilemma experiment. And indeed, there
are arguments for a positive effect on trust, mainly based on the idea that religions generally encourage adherents to do well towards others. In Islam, Mohammed's farewell sermon includes the assertion 'Hurt no one so that no one may hurt you'. Likewise, in Christianity, through Luke 6:31 ('Do unto others as you would have them unto you'), this is embedded in the Golden Rule (Similar rules can be found in all major world religions) see [43].On the other hand, religious teachings might create a clear divide between the religious and the non-religious (see [15, 19, 21, 23, 39]; on religion and domestic conflict - see, e. g., [18]). Of course, it militates against trust creation.
Religion has until recently remained relatively unexplored in the trust literature and, indeed, in economics and political science overall (with some exceptions, such as [25, 30, 41, 42]). We support the point of view of Berggren and Bjornskov [8] who state that 'this relative neglect is unfortunate, since there are reasons to believe that people's perceptions and behavior, both in economic and political realms, are influenced by religiosity'.
Religion can be seen as another form of social construction. It is expected that its impact on trust in a society may be greater than the impact of such variables as ethnicity and language. Note,
that in our analysis we are looking at societal fragmentation by the criterion of religion, and not for the impact of a specific religion.
Along with ethnicity and language there is a problem of measurement of religious diversity. It is very difficult to obtain qualitative data. There are two sources of data collection: (1) asking people and (2) evaluating visible participation in religious services. In the first case people might not answer truthfully because the issue is so personal, as well as it can be insecure to reveal religious affiliation for fear of discrimination. In the second case religious institutions tend to consider a member as a member for life, even if a person does not attend a religious institution any longer [8]. Thus, the reliable data is very scarce, and we keep it in mind when we conduct an analysis on religion fragmentation.
In this research we use data by Alesina and his colleagues [1], who exclusively relied on the data set from the World Christian Encyclopedia. Here we expect that the authors of the Encyclopedia could not undercount Christian churches: they tend to include everyone within the range of a church as its member. One more drawback of data is that the Encyclopedia tends to underestimate syncretic and animistic cults. For example, the Encyclopedia records that 93% of the population of Bolivia is Christians, while other sources record that 43% hold syncretic beliefs [32]. Despite these drawbacks social scientists do not have a better alternative to using the World Christian Encyclopedia as a source of religious fragmentation [22]. Note, the question of religious fragmentation is relevant only if religion is experienced as an important factor in a daily life.
The religious fractionalization index (by Alesina [1]) is expressed in a range from 1 to 0, with the lowest number expressing the greatest degree of homogeneity and the highest showing the greatest diversity. In accordance with the world map of religious fractionalization provided by Griffiths [22], the most homogeneous 15 countries in the world (in descending order) are Yemen, Somalia, Mo-
rocco, Turkey, Algeria, Tunisia, Mauritania, Libya, Jordan, Mongolia, Qatar, Cambodia, Gambia, Thailand and Iran. Alternatively, the most diversified 15 countries are South Africa, USA, Australia, Malawi, New Zealand, Ghana, Central African Republic, Lebanon, Kenya, Ivory Coast, Zambia, Cameroon, Netherlands, Lesotho, Democratic Republic Congo. As we may see, the list of homogeneous countries is dominated by Muslim countries and two Buddhist countries - Mongolia and Cambodia. Thus, among the most homogeneous countries are four Western Asian countries and among the most diversified countries is one Western Asian country.
The outcomes of religious fractionalization ofWestern Asia are as follows.
The box-plot in (Figure 5), constructed by the author in R-Studio (R-script for the box-plot and descriptive statistics on the religion criterion is in 'Appendix'), shows that the distribution ofWestern Asian countries is left skewed (the vast majority of observations deviate towards heterogeneity) with the median value 0.431, the mean value 0.368 and the standard deviation value 0.240.
The (Figure 6), constructed by the author in MS Excel, represents the distribution of countries of Western Asia by the criterion of religion. The most homogeneous country in the region is Yemen, followed by Turkey, Jordan, Qatar and others. The most diversified in the region is Lebanon, which is quite expectable, since there are several creeds of Muslim religion and several creeds of Christianity. By the way, this religious diversity has recently used as an instrument to enkindle civil war in the country and destabilize it.
In the world context Western Asian countries mostly represent the top and the middle of the world spectrum of religion fractionalization. The majority of Muslim states (Yemen, Turkey, Jordan, Qatar, Saudi Arabia) cluster the most homogeneous end of the scale (1st decile). The majority of states from the rest of the group is in the middle. We may see Palestine, UAE, Israel, Syria, Oman, Armenia, Iraq,
Azerbaijan from 4th to 6th deciles. The most diversi- fied country Lebanon is in the 10th decile.
Figure 5. Box-and-whiskers plot: distribution of Western Asian countries by the criterion of religion
Figure 6. Distribution of countries of Western Asia by the criterion of religion
We should mention that in Muslim states, which represent the majority of Western Asian countries, religiosity is highly supported on the state level and embedded into the daily life. Thus, it influences formal and informal norms of people's interactions, as well as the level of trust. To support this observation we refer to Tan and Vogel [40] who report that 'trustees are trusted more, especially by religious trusters'. Also, interestingly, Johansson-Stenman et al. [26] found that Muslims and Hindus trust people of their own religion more than they trust others, thus suggesting a role for religious diversity.
5. Conclusion
In theory it is hypothesized that ethnicity, language and religion influence the level of trust, re-
vealing the homogeneity of a society from different standpoints. In the research we discussed why these three issues remain such sensitive, pointed shortcomings in the data collection and measurement, explained the mechanisms by which these phenomena (ethnicity, language and religion) affect a level of trust in a society as well as configured Western Asian countries in these three categories. Through a comparative analysis technique we analyzed the diversity within a target region and showed where it fits in the world spectrum.
Ethnicity, language and religion are very difficult concepts to operationalize. As regards the ethnicity there are the following problems: legal definition of nationality and ethnicity; difficulties
with self-identification; the problem of determination the degree of cultural differences; the context in which the question about ethnicity was asked (political pressures, discrimination, illegality in status, etc.). Concerning the language there are the following problems: what is one's mother's tongue in bilingual or multilingual societies; when does a language become a dialect and when does a dialect become a language. As far as the religion there is also a problem of measurement of religious diversity: the issue is so personal, as well as it can be insecure to reveal religious affiliation for fear of discrimination; religious institutions tend to consider a member as a member for life, even if a person does not attend a religious institution any longer. Thus, the reliable data is very scarce. Even though the mentioned concepts are contested, the attempts to measure the degree of fragmentation of a society by the ethnic, language and religion criterions have been made.
In terms of ethnicity and religion distribution of countries of Western Asia is close to symmetric, with a small value of skewness, i. e. the county-observations deviate mostly towards heterogeneity. In terms of religion the distribution of Western Asian countries is left skewed which means that the vast majority of country-observations deviate towards heterogeneity, i. e. rather fragmented.
We suppose that ethnic, linguistic and religious diversity adversely affect the level of trust in a society. The more homogeneous a society the higher the level of trust is. It is also expected that the impact of the religion on trust may be greater than the impact of such variables as ethnicity and language. In Muslim states, which represent the majority of Western Asian countries, religiosity is highly supported on the state level and embedded into the daily life. It influences formal and informal norms of people's interactions, as well as the level of personal and generalized trust. Personal trust is directly linked to trust in institutions, i. e. civic organizations, while interpersonal trust is linked to generalized trust, i. e. trust in most people. Fairholm [17] points out that trust suffers
when core moral principles, expressed in religious beliefs or other moral standards, are ignored. This moral vacuum weakens our willingness to trust others, with its negative consequences.
Religion can be seen as another form of social construction. Participation in civic institutions serves as a socialization mechanism which, through repeated reciprocal actions, leads to the construction of trust and, from there, the creation of good and effective institutions of government. If civic engagement declines it leads to fragmentation of a society, decline of social capital as well as decline in trust. In its turn, this fragmentation of a society poses a threat to democracy and a threat just about everything. It supports Putnam's point of view that trust is central to the formation of a society [38, 39]. Thus, it is very important to strengthen the morale of the nation because any positive change begins with spiritual change deep inside and then leads to the enhancement of the social world around.
There are directions for further research. We are going to use the results of this study to conduct the correlation and regression analysis in order to estimate a relationship between ethno-linguistic and religious fragmentation and the level of trust in a country. Currently we work upon creation of a complex estimator based on these three mentioned criterions. The complex estimator will allow us to rank countries of Western Asia by three categories simultaneously. For this purpose we will apply two mathematical methods: a method of places and a taksonometric (distance) method. In the next stage we will statistically verify the relationship between trust and three variables - ethnicity, language and religion. Then we will use the obtained information to construct different regression models and will opt for the most qualitative so as to explain the change in the trust indicator from three variables. For the best model we will further conduct econometrical tests and will give explanation for the observed results.
It should be mentioned separately that conclusions are largely influenced by statistical facts (data)
which sometimes are slightly better than random choice. That is why we must be critical of the data and interpret it with accuracy. Nevertheless, the current research is in the line with the studies that assume the influence of ethnicity, language and religion on the level of trust, as a social capital category which, in turn, influences social, economic and political sustainability.
Appendix: R-scripts in R-Studio for descriptive statistics and box-plots for ethnicity, language and religion
# Box-plot and descriptive statistics for ethnicity ethnicity<-c (0.1272,0.2047,0.5021,0.4923,0.3 689,0.3436,0.5926,0.6604,0.1314,0.4373, NA,0.74 56,0.18,0.5399,0.32,0.6252, NA)
boxplot (ethnicity, horizontal=TRUE, col="grey")
median (ethnicity, na.rm=TRUE) mean (ethnicity, na.rm=TRUE) sd (ethnicity, na.rm=TRUE)
# Box-plot and descriptive statistics for language language_Ethnologue<-c (0.125,0.457,0.663,0.
582,0.728,0.665,0.496,0.556,0.161,0.702,0.208,0.6 08,0.626,0.527,0.394,0.777,0.578)
boxplot (language_Ethnologue,
horizontal=TRUE, col="grey")
median (language_Ethnologue, na.rm=TRUE) mean (language_Ethnologue, na.rm=TRUE) sd (language_Ethnologue, na.rm=TRUE)
# Box-plot and descriptive statistics for religion religion<-c (0.4576,0.4899,0.5528,0.6543,0.484
4,0.3469,0.0659,0.6745,0.7886,0.4322,0.3095,0.09 5,0.127,0.431,0.0049,0.331,0.0023)
boxplot (religion, horizontal=TRUE, col="grey")
median (religion, na.rm=TRUE) mean (religion, na.rm=TRUE) sd (religion, na.rm=TRUE) Compliance with Ethical Standards: Conflict of interest: The author declares that he does not have any conflict of interest.
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