The relationships between the degree of ethnic heterogeneity of an area and other variables have been examined in scientific studies.

One cause for the problems in areas with high ethnic heterogeneity has been argued to be that when an area is no longer ethnically homogeneous, then ethnic nepotism will cause the different ethnicities to try to promote their own ethnic interests and it becomes difficult to govern the whole area rationally.

Trust, social capital, and “hunkering down”

A well-known study by Robert D. Putnam found that higher ethnic heterogeneity was associated with lower trust between people, lower social capital and a “hunkering down” where people avoid engagement with their local community. This occurs both between different ethnic groups and within ethnic groups. This has been associated with many negative effects, many of which are mentioned in different sections in this article.

A 2015 study in Denmark found that the negative effect of ethnic diversity on trust occurred when there was high ethnic diversity in the immediate surrounding residential area, but not when the ethnic diversity was further away. This was interpreted as supporting that “interethnic exposure” decreases trust.

A 2019 meta-review stated that “this article reviews the existing literature on the relationship between ethnic diversity and social trust through a narrative review and a meta-analysis of 1,001 estimates from 87 studies. The review clarifies the core concepts, highlights pertinent debates, and tests core claims from the literature on the relationship between ethnic diversity and social trust. Several results stand out from the meta-analysis. We find a statistically significant negative relationship between ethnic diversity and social trust across all studies. The relationship is stronger for trust in neighbors, and when studied in more local contexts.“

“The researchers looked investigated whether “continued immigration and the corresponding growing ethnic diversity” have positive impacts on social unity, cohesion, and togetherness. In short, the study found that “continued immigration and corresponding growing ethnic diversity” exerts the exact opposite effect on society. The results mean that it undermines and degrades social cohesion, unity, and togetherness.“

Participation in organizations, volunteer activity, census response rate and voting

An overview of different studies published in 2003 stated that higher ethnic heterogeneity in an area is associated with negative effects regarding many variables, such as participation in organizations, volunteer activity, census response rate, and voting.

Labor unions / trade unions

Various forms of evidence is argued to support that high ethnic heterogeneity is negative for labor unions / trade unions and forms of employer organizing. Some employers may consider this to be positive and have been argued to therefore have aimed to racially mix their employees.

Charity

A 2011 study in Canada found that higher ethnic heterogeneity reduced the size of individual donations to private charities.

Life satisfaction

A 2004 study in the UK found that higher ethnic heterogeneity in an area was associated with lower life satisfaction.

A 2016 study in the UK found “that an increase in “diversity” makes existing residents of an area feel unhappier and more socially isolated, while those leaving for more homogenrous areas populated by their own ethic group often get happier.“

Depression, psychosis, and suicide

Studies have found that higher ethnic heterogeneity in an area is associated with a higher risk of depression.

A 2012 study in the UK found that the risk of psychosis increased when a person lived in an area with a lower percentage of people from the same ethnicity.

A 2003 study found that higher ethnic heterogeneity in a country was associated with a higher frequency of suicide.

Health

A 2012 study found that higher ethnic heterogeneity was associated with higher rates of cardiovascular disease and cancer for elderly individuals.

A 2016 study found that higher ethnic heterogeneity was associated with poorer health outcomes for 91 studied countries.

Environment

A 2010 study found that countries with “moderate” levels of ethnic diversity had the best scores on the “Environmental Performance Index” and that increasing ethnic diversity beyond this was associated worsening environmental performance.

Educational performance

A 2010 study found that higher ethnic diversity in a country was associated with lower results on the Program for International Student Assessment (PISA).

Higher education

A 2017 study found that higher ethnic heterogeneity in US states was associated with less public spending on higher education.

Innovation

A 2016 study found that higher ethnic diversity was associated with lower innovation.

Economic development

A 2009 review stated that higher ethnic heterogeneity was associated with lower economic development. Possible causes included less support for public goods, increased rent seeking, and lower levels of social capital.

A 2011 study in China found that higher ethnic heterogeneity in Chinese provinces was associated with lower economic growth. A 2013 study in China found decreased quality of export goods in Chinese provinces with higher ethnic heterogeneity. Possible explanations included increased communication difficulties and antagonism between workers.

A 2012 study found that higher ethnic heterogeneity decreased the tourism competitiveness of a country. Possible causes included negative effects on political institutions, the economy and the environment.

A 2017 study found that higher ethnic heterogeneity was associated with increased poverty in studied developing countries.

Income inequality

A 2007 study stated that “One frequently voiced concern is that as populations become more diverse, socioeconomic inequalities within countries will become greater. The present study presents new measures of ethnic, racial and religious diversity for 198 countries and territories. These measures were used as predictors of the Gini index in regression models with other predictors. Ethnic and religious diversity were found to be virtually unrelated to the Gini index. However, a high level of racial diversity independently predicts a high Gini index.“

Corruption, informal economy, and tax morale

Higher ethnic heterogeneity in an area has been associated with higher corruption.

A 2007 study found that higher ethnic heterogeneity in a country was associated with a larger “informal economy“.

A 2010 study found that higher ethnic heterogeneity in country was associated with lower tax morale.

Crime

A large number of studies have examined if ethnically heterogeneous areas have higher crime rates than ethnically homogeneous areas. The areas that have been studied are often different areas in large cities. Almost all studies have found that higher ethnic heterogeneity is associated with higher crime rates.

Studies have found that higher ethnic heterogeneity in a country is associated with a higher rate of homicide.

Ethnic conflicts

Tatu Vanhanen stated in the book Ethnic Conflicts – Their Biological Roots in Ethnic Nepotism (2012) that differences in ethnic heterogeneity between countries explained 66% of the global variation in ethnic conflicts. The degree of democracy and the degree of economic development explained only small parts.

Vanhanen’s earlier book Ethnic Conflicts Explained by Ethnic Nepotism (1999) examined the countries that partly differed from the general pattern that ethnic heterogeneity is associated with more ethnic conflicts. One such group was harsh authoritarian states, such as Communist countries and oil-rich Arab countries with a large population of foreign guest workers, who could be quickly expelled, if conflicts emerged. However, large ethnic conflicts quickly emerged in ethnically heterogeneous Communist countries once the harsh state control disappeared.

Another group that partially differed consisted of poor countries, where most of the populations were farmers, who had little contact with other ethnic groups. Vanhanen predicted that the degree of ethnic conflicts would increase, if these countries modernized.

Ethnically heterogeneous democratic countries that gave a large degree of autonomy to different ethnic areas, or that explicitly divided the state apparatus between different ethnicities, also had relatively low degree of ethnic conflicts (but still higher than ethnically homogeneous countries). A counter-example was the long civil war in Lebanon, that had occurred despite the state apparatus being explicitly divided between the different ethnicities, but Vanhanen thought this was war was in large parts caused by foreign influences.

Countries that had an unusually high degree of ethnic conflicts included countries where the different groups markedly differed in physical appearance. One example was the conflict between Tutsi and Hutu in Rwanda and Burundi. Another example was countries in the Sahara region that had populations from both Sub-Saharan Africa and North Africa. Vanhanen described the situation in many of these countries as being close to civil war. Civil wars between the northern and southern parts of many of these countries have also occurred, after the book was written. Some countries, such as Sudan and Ethiopia, have been formally divided.

Vanhanen saw no easy solution to the ethnic conflicts, which were argued to be largely caused by genetically caused ethnic nepotism. He recommended that countries with a high degree of ethnic heterogeneity should be divided along ethnic lines whenever possible. This could be an alternative in the future even for countries such as the United States, as ethnic conflicts were predicted to increase due to the demographic changes.

See also the Political spectrum article, in particular the sections “Ethnic homogeneity/heterogeneity” and “Increasing polarization,” on aspects such as increasing political polarization in the United States, argued to be related to the increasing ethnic heterogeneity. Race now outweighs all other demographic divides regarding which party to vote for, with factors such as income not even coming close.

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