Presentation on the ethno-linguistic regional diversity in Russia and the impact on redistribution policy

1. Совмещенная модель распределения
доходов в России
The ethno-linguistic regional diversity in Russia:
Impact on redistribution policy
Kristina Butaeva
Center for Study of Diversity and Social Interactions, NES
Denis Davydov
Center for Study of Diversity and Social Interactions, NES
Alexey Khazanov
Boston College, Boston
Shlomo Weber
Center for Study of Diversity and Social Interactions, NES
Presented at the Conference “Russian economy - stagnation or modernization?”
SITE, Stockholm School of Economics, Stockholm, June 13, 2017

2. At the entrance to Higashi Honganji Temple in Kyoto, the
ancient capital of Japan, a visitor is greeted by two sentences
written on the wall:
“Living together in diversity. Learning to accept our
differences.”
Diversity is a fact of life, whether we want it or not, whether
we like it or not.
Before discussing the impact of diversity in Russia,
Is diversity good or bad?

3. Good: Saxenian (1996, 1999) argued that the success of Silicon
Valley in 80s and 90s was due to a diverse cultural and professional
background of scientists and entrepreneurs, coming from India,
China, Russia, Israel, Europe. At that time 40% of businesses there
had a foreign-born co-owner.
Florida (2002), Florida and Gates (2001) examined the importance
of diversity to urban high-tech growth. They ranked 50 US cities in
terms of diversity (number of artists, foreign-born) and showed the
success of more diverse ones (from San Francisco to Buffalo).
Otaviano and Peri (2011) show that earnings in in more diverse cities
are higher than in less diverse ones.

4. Bad: Ethnic, religious and linguistic conflicts everywhere (Asia,
Africa, Latin America, Europe)
Tragedy of African growth.
Papua New Guinea - 857 active languages. And this is not that
exceptional. Most of the countries have more than 100 languages.
Example: Production of cocoa in Ghana (Kwame Nkrumah).
European Union. Excessive degree of diversity? (24 official
languages!)
If we look at diversity as a spice for the society, then maybe a little
amount of diversity is good but if too much of diversity could have a
negative effect.

5. How many spoons of sugar do we put in a cup of tea?
How much salt or pepper do we put in our meal?
How much color do we like in painting we see?
Why diversity is important?
Big shocks (economic changes, financial crises, fluctuation of oil
prices, natural disasters) impacts various groups in different ways, and
one has to account for group differences.
Even if we talk about the rapid growth, there are sectors in population
and economy, and various regions, that may suffer.

6. Diversity covers a large range of aspects:
religious, historical, economic, ideological,
geographical, genetic, linguistic, ethnic, and many
others.
We focus on ethno-linguistic diversity.

7. Suppose we have several linguistic groups in the region. Then we
calculate the probability that two randomly chosen individuals in
the region belong to different groups.
This regional index is given by
where the is the proportion of members of group k in the entire
region.
The first time the A-index (the mutuality index) has been proposed
by Gini (1912). Then Simpson (1948) in biodiversity, and Greenberg
(1956) in linguistics, and many other fields. It is also one minus
Hirschman-Herndahl index.

8. In order to use the A-index one needs Group Identification (a
partition of society into the groups).
The first and most famous linguistic and ethnic fractionalization
datasets has been compiled by the Institute Miklucho-Maklay (Atlas
Narodov Mira, 1964) in Moscow, called ELF (ethnolinguistic
fractionalization).
Till now the most often used index of ethnolinguistic
fractionalization is the A-index based on the MM dataset.
Group identification: Are Italian and Venetian different
languages? Are Serbian and Croatian different languages?

9. Proximity between the groups
We introduce the notion of similarity (or dissimilarity) of
characteristics (languages) and determine the distance between every
pair of languages. We have the B-index, which is the average distance
between two randomly chosen residents:
Periphery index P. It assumes, the existence of the central group, and
several peripheral ones. The index takes into account only the
distances or the tension between the center and the periphery, and
ignoring any tension between peripheral groups. Let group 1 be the
center. Then:

10. In this paper we introduce another index that could be relevant in the
Russian context. Namely, we would like to evaluate the distance between a
given region and the rest of the country. This index may indicate the strength of
separatist tendencies of the region viewed in the context of political stability.
Let i = 1,…., R be the set of the regions and be the proportion of group j in
region i. Then we calculate the average distance between a random citizen of
region i and the rest of the country, namely:
A variant of D-index was used by Khazanov (2016), where he estimated
effect of impact of ethno-linguistic diversity and some economic indicators on
Russian budget transfers policy. He showed that the D-index was the most
significant in explaining the redistribution patterns.

11. (1) (2) (3) (4) (5) (6) (7) (8) (9)
Dependent variable: ratio of transfers to GRP
GRP per capita -0.089* -0.087* -0.087* -0.090* -0.090* -0.06 -0.054 -0.055 -0.091*
-0.051 -0.051 -0.051 -0.051 -0.051 -0.05 -0.049 -0.049 -0.054
Unemployement 0.826*** 0.823*** 0.811*** 0.833*** 0.826*** 0.678*** 0.578*** 0.578*** 0.559***
-0.243 -0.243 -0.24 -0.246 -0.247 -0.237 -0.217 -0.217 -0.128
Ratio of State Employees 12.82 11.544 18.762 1.872 3.242 24.193 65.575 66.142 25.779
-81.185 -81.299 -81.129 -84.77 -83.953 -68.991 -63.308 -66.01 -85.919
Population -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001
-0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001
Territory 0 0 0 0 0 -0.001 -0.001 0 0
-0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001
A-index (ethnic) -9.5 -9.358 -22.439*** -24.433***
-9.82 -10.06 -6.686 -5.547
Republic 8.998* 8.985* 9.877** 8.707* 9.055** -7.377** -2.814 6.557***
-4.597 -4.642 -4.148 -4.52 -4.465 -2.872 -3.132 -2.084
RQ-index (ethnic) -38.632
-28.699
A-index (language) -7.817
-8.56
B-index (internal) -2.325
-2.218
D-index (external) 8.919*** 11.046*** 10.235***
-1.951 -1.315 -1.122
Gini -11.112
-10.58
Constant 4.634 4.741 5.231 4.779 7.035 -12.207* -16.288** -15.002** 7.831
-8.336 -8.352 -8.376 -8.338 -9.225 -7.044 -6.586 -6.122 -10.301
Number of bservations 1,021 1,021 1,021 1,021 1,021 1,021 1,021 1,021 1,016
Number of regions 79 79 79 79 79 79 79 79 79
Time effects YES YES YES YES YES YES YES YES YES
Oil and gas producing regions NO YES YES YES YES YES YES YES YES

12. High value of D index D
North Ossetia 3.5256
Chuvashia 3.4091
Bashkortostan 3.3171
Tatarstan 3.3162
Yakutia 3.2765
Mordovia 2.8042
Altai Krai 2.7083
Adygea 2.5121
Astrakhan Oblast 2.3280
Udmurtia 2.3213
High unemployment rates (UR) UR
Altai Republic 12.20
Kurgan Oblast 12.10
Zabaykalsky Krai 11.10
Kaliningrad Oblast 10.30
Irkutsk Oblast 10.10
Komi Republic 10.10
High value of both D index and UR D UR
Ingushetia 4.8770 49.70
Chechnya 4.8328 43.30
Dagestan 4.7599 14.80
Tuva 4.2139 21.70
Kabardino-Balkaria 4.0439 12.70
Karachay-Cherkessia 3.7057 10.30
Republic of Kalmykia 3.6901 14.80
Mari El 2.8271 10.50
Buryatia 2.3830 10.40
- other.
Classification of
Russian Regions

13. Classification of Russian Regions

14. Conclusions
We have estimated the effect of ethnolinguistic diversity of Russian regions
on federal budget transfer policy. It terns out that the internal index of diversity B
is not significant. However the index D and the republican status of region are.
Also we show that economic factors, such as unemployment rate, impact the
redistribution policy.
We identified tree types of Russian regions that receive relatively high level
of transfers:
- regions with high D-index (North Ossetia, Chuvashia)
- regions with high UR (Altai Republic, Kurgan Oblast)
- regions with high D-index and high UR (Ingushetia, Chechnya, Dagestan).
This result can be interpreted as the support of regions that are very
distinct from the majority of population or are economically disadvantaged.

15. 
i
ipD 
1SD
Future research
Subjective diversity index:
- α can be different in different regions;
- α can change over time;
- it is important how the society views diversity.