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Information about the authors
Bobkov Vyacheslav Nikolaevich (Moscow, Russia) — Public Limited Company «All-Russian Centre of Living Standard», Honored Science Worker, Doctor of Economics, Professor, General Director (29, 4th Parkovaya str., Moscow, 105043, Russia, e-mail: bobkovvn@mail.ru).
Matveyeva Tatyana Alekseyevna (Moscow, Russia) — Master Student of Economics of the MSU Department, (3 new educational building, Economics Faculty, GSP-1, Leninskiye Gory, Moscow State University, Moscow, 119991, Russia, e-mail: clara_m@list.ru).
UDC 314
A. I. Kuzmin, Ye. H. Tukhtarova, Ye. A. Ilinbayeva
SOCIO-DEMOGRAPHIC MEASURING OF RELATION OF LIFE QUALITY AND LEVEL OF POPULATION REPRODUCTION IN RUSSIAAND FOREIGN COUNTRIES ON BASIS OF RATING EVALUATIONSi
During the finishing of the second demographic transition in the countries with relatively high level of socio-economic development, the tendencies of rise in the total birthrate and the changing of a calendar of births were revealed. At the same time, the process of delayed marriage of both men and women, and increased number of single households were continued. The developing tendency of rise in births required from demographers an additional analysis of causes of this phenomenon, especially as the growth of total birthrate coefficient become stable after millennium. The attempt to analyze the newest tendencies of the influencing of growth of the life quality on the differential birthrate in safe regions of the world, to compare the pro-
1 © Kuzmin A. I., Tukhtarova Ye. H., Ilinbayeva Ye. A. Text. 2014.
cesses of socio-economic, sociocultural, and reproductive differentiation of indexes of population movement on Russian territories with rating evaluations were made in the article.
The hypothesis of the research is related to the assumption that the global changes in life quality in a number of the world's regions stimulated the renewal of the tendency to alternation of generations in demographic processes. The authors of the research draw a conclusion that this process in Russia was just started and developing. It gives a chance to develop the tendency of alternation of generations in the future and reduce the treats of depopulation and the need of superfluous recruiting of foreign labor force.
Keywords: quality of life, demographic transition, alternation of generations, safe region
The first decade of the XXI century is marked by a dynamic formation of a new structural fertility model in most developed countries. In Europe, in particular, there is a widespread growth in the average number of children born by women of the hypothetical generation and, more importantly, this is noted in those countries which previously showed clear evidence of depopulation in contrast to the catching up countries. This new fertility model, at the same time, is observed to be only partially affected by the active governmental pronatalist policy measures and migration trends. We should agree that it took a while for the shift in the births calendar caused by transformation of marriage to come from Europe to Russia.
Several observations can be made in this regard. Firstly, the growing trends in total fertility rate after 2000 in Central, Southern and Eastern Europe in general are evidently clear. This fact is noted by J. Bongaarts and T. Sobotka [9, p. 220, 10, p. 272273]. In their review of the total fertility trend the researchers noted that European countries (including those of Eastern Europe and Russia) have experienced an increase in the total fertility (TFR). Having discussed the problem related to the period of dynamic growth in fertility and contributions made thereto by different groups of women, J. Bongaarts and G. Fini accentuated the usefulness of a new index, namely the correction for rate and parity with correction for total fertility rate (TFRp*) or TFR = TFR*(1 - c) [5, p. 274-275]. The second observation was made later and it was a severer one. The point is that the total fertility continued to grow also during the protracted global economic recession [7, p. 270-271]. Thirdly, the second demographic transition in post-communist countries was of a more depressed nature due to a decline in fertility (Ukraine, for example, reached an average of 1.1 births per woman of hypothetical generation). The exceptions to these are countries such as Albania and Serbia & Montenegro where the TFR index stayed at 2.00-1.75 [8, p. 221]. Anyhow, the activities of the golden billion countries population have changed its quality during the first decade of the new century in science, technology and many other realms, as well as in terms of social and
professional mobility of the population. The concepts of the third demographic transition and of migration as a determining factor influencing the population reproduction trends set forth by Van de Kaa, Ron Lesthaeghe and David Coleman can not provide an irrefragable answer to how the quality of life affects the reproductive behavior of family and individual [9, 132]. Being highly multidimensional and complex, this relationship does not fit into the framework of the demographic transition concept. In this we can agree with M. Klupta, who believes that proper consideration of the effects that factors of socio-economic development of modern countries have on their fertility trends requires at least the methods of cluster and historical analysis [10].
The rapid worldwide development of expert and evaluation technologies has made it possible to compare well-being ratings of various countries as aggregate estimates of quality of life with total fertility rates differentiation. Such total fertility rates are fully comparable from territorial and historical aspects. We acquired the most recent quality of life indexes of the so-called good countries («The Good Country Index», 2014) [11]. The total fertility rate (TFR) and the «Aggregated rating» proved to be interdependent, which allows to formulate a working hypothesis of a positive relationship possibly existing between the reproduction levels in the group of countries having a high level of general well-being. This implies not only the characteristics and indexes of socio-economic development, but a social and cultural context of the problem as well. The regional demographics in the good countries turned out to be quite good (Fig. 1).
The aggregated index «The Good Country Index, 2014» revealed Russia's generally outlying position in respect to the groups of countries with favorable quality of life levels and modes of generations replacement.
Decomposition of the index into its constituent elements revealed a vast heterogeneity in the relationship between index components within the group of high ranking «good countries» and total fertility (Table 1).
Table 1
Evaluation of reproduction levels by components of The Good Country Index [2], [11]
Good countries component rating by relationship closeness to TFR Component denomination Correlation index value (R2) TFR value to gross rate Net coefficient of reproduction Share of countries with TFR >2 per woman of hypothetical generation
1 Culture 0.263 1.900 / 0.927 0.909 0.462
2 Science and technology 0.187 1.885 / 0.920 0.902 0.384
3 Prosperity and equality 0.181 2.115 / 1.031 1.010 0.384
4 Global stability 0.159 2.108 / 1.029 1.008 0.384
5 Health and well-being 0.120 2.092 / 1.021 1.001 0.384
6 Planet and climate 0.082 2.077 / 1.014 0.994 0.384
7 Peace and safety 0.065 1.992 / 0.972 0.953 0.538
Decomposition of the index into its constituent elements revealed a vast heterogeneity in the relationship between index components within the region of high ranking good countries and total fertility.
The countries rating 1st through 20th were found to be within the total fertility rates of av-eragely 1.7-2 children per woman of hypothetical generation. Thus, almost half of the good countries remains threatened by a prospect of depopulation processes capable of destroying the conservative ethnic basis of statehood. The other half of the most well-off countries of the first twenty has moved towards maintaining the ordinary mode of generations replacement. The key position in determination of the narrowed mode of generations replacement is held by culture, which is the strongest component of the rating. Similar positions belong to science and technology components. The latter correlates directly with low total fertility and population reproduction rates. The combination of these depopulation factors
determines the lion's share (43% total) of fertility in the most well-off countries. The opposing group of factors includes prosperity, stability and health. But their total contribution to demographic processes development amounts to only one third. The climate factors effect is generally positive but at the same time paradoxical, since it is the countries with extreme temperatures that display higher fertility than that of the countries with moderate climates. Statistically the relationship turned out to be significant enough.
Extended reproduction and generations replacement is maintained due to the following components: prosperity and equality (gross rate = 1.031), global stability (1.029), health and well-being (1.021) and planet and climate (1.014).
Let us make this supposition more precise. The following is the recalculation of the gross rate, as applied to the most well-off countries, into net rate. Thus the net generation replacement value will exceed 1 only for the following components: prosperity and equality, global stability, health
Planet and climate 8%
Healt and well-being" 11%
Global stabiltiy 15%
World and safety 6%
Culture 25%
Science and technology 18%
Success and equality 17%
Fig. 2. Countries aggregate rating structure by components
and well-being. The overall picture of the components structure by demographic criteria is shown in bar chart in Fig.2. Recalculation showed the most significant share in The Good Country Index
belongs to the components of culture, science and technology, prosperity of the territory.
It is worth noting that the least share belongs to peace and safety component. This is quite surprising considering the current military and political situation in the world. Component specific fields in the index do not overlap. The requirements of safety, stability, prosperity and well-being are applied primarily to the developing countries, not just those rated as well-off. Oddly enough, the value of health is within the fields of the most well-off countries and corresponds to the fields of science, culture, stability and prosperity of the countries considered good by its quality of life (Table 2).
Cultural component (Fig. 3) proved to be the strongest due to the systemic nature inherent to the formation of public and individual views on the acceptable number of children in the family or reproductive attitudes and ideas about normal number of children existing on society and eth-
Table 2
Morphological table of the well-off countries quality of life components
Country name Component Rating nucleus
Science Culture Peace and safety Stability Climate Prosperity Health
USA + - + - - - + +
Finland + + - + + + + +
Iceland + + - + + - - +
Ireland + + - + - + + +
Norway + + - + + + + +
Sweden + + + + + + + +
Great Britain + + + + - + + +
Belgium + + + + - + + +
France + + + + + + + +
Australia + + - + + - + +
New Zealand + + - + + - + +
The Netherlands + + + + + + + +
Denmark + + - + - - + +
Malaysia - + + - - + - -
Mexico - - + - - - - -
Dominica - - + - - - - -
Azerbaijan - - + - - - - -
Turkey - - + - - - + -
Vietnam - - + - - - - -
Albania - - + - - + - -
Costa Rica - - - + + - - -
Brazil - - - - + - - -
Chile - - - - + - - -
Colombia - - - - + - - -
Uruguay - - - - + - - -
Trinidad and Tobago - - - - - + - -
Sri Lanka - - - - - + - -
Georgia - - - - - + - -
Developed countries
Azerbaijan ♦ ♦
Sri Lanka
0,5
Albania ♦ Russia
Venezuela
♦ Iran
Georgia
y = 0,0034x+ 1,8296 R2 = 0,2631
20 40 60 80 100 120
Fig. 3. Total fertility rate and culture component relationship
140
Kuwait ♦
1
0,5
Bangladesh Venezuela
♦♦éj
-^ Ф Katar
ф Domonican Albania RePublic
and
Denmark
y=0,0027x+1,8603 R2 = 0,1868
20 40 60 80 100 120
Fig. 4. Total fertility rate and science and technology component relationship
140
20 40 60 80 100 120
Fig. 5. Total fertility rate and prosperity and equality component relationship
140
nical levels. The only component which is more powerful than that of culture is the religious affiliation.
Statistically, the relationship between culture and fertility is significant, but, unfortunately, it is of an inverse type. It is clearly evident that the most culturally developed countries are found on
the left side of the chart and represent the cluster of the top twenty countries. Moreover, the United States, let alone Brazil and Russia, are found close to the periphery of the cluster, among the countries rated 40 through 60. The relationship between general vector of rating and total fertility is shaped in a clearly negative manner.
A similar pattern is observed in Fig. 4 presenting the relationship between the level of scientific and technological development and the total fertility rate. However, the boundaries of the first cluster (Great Britain, Denmark, USA, etc.) are better outlined. The intermediate cluster of the catching up countries (Turkey, Chile, Russia, etc.) and that of the least well-off countries (Dominica, Bangladesh, Venezuela, etc.) are clearly identifiable.
The distribution of countries by prosperity and equality component relationship to the total fertility rate is entirely different (Fig. 5). Almost all of the countries are densely grouped in the proximity of the ordinary generations replacement axis. Statistically the relationship between prosperity component and the total fertility rate is worth considering.
However, the relationship as a whole is inverse, the highly rated good countries are grouped closer to the axis of values obtained for the top twenty. Those with a low rating tend to have higher rates of total fertility which «pulls up» the axis. The overall picture is presented in composition table 3. Russia has been included for value comparison. Generally, Russia's position is in the intermediate group, outside the boundaries of the good countries cluster. The demographic status of the country, however, looks quite good thanks to its total fertility rates and generations replacement level (such an evaluation can not yet be given referring to life span criterion).
Given the impressive life span in the most welloff countries and practically negligible probability of mortality among mothers in reproductive period, it is quite easy to recalculate the total fertility rate into the generations replacement coefficient. TFR value is multiplied by the biological constant of probability of a female baby being
2,2
2
1,8 1,6 1,4
1,2
Krasndar Krai
born to a mother (0.488). This allows to accurately determine the probability threshold of ordinary generations replacement in the country not requiring engagement of migrants (gross reproduction rate, Table 4). Conversely, if the generation replacement goes below 1, a deficit of reproduced stationary population with respective need for further engagement of human capital from outside the country will be observed.
Let's assume the aspirations for material and spiritual well-being are a quality of life indicator of the Russian population everyday life. It is clear that less well-off countries are marked by generally higher fertility rates. This is proved by the law of well-being and fertility inverse relationship, commonly known since J. Bertillon's times. However, the group of most well-off countries demonstrates total fertility rates allowing to come tightly close to the ordinary generations replacement level.
As examples we can mention Ireland (where abortions are prohibited), New Zealand, France, Spain and Great Britain. However, practically all of these countries are actively engaging borrowed foreign man power. Russia's position in the rating just by culture component turned out to be higher than that obtained w a combination of all components (technology, safety, etc.).
Component method has been used for a long time in Russia for quality of life rating evaluation. The number of components is still seven, but the nominations are different. An aggregated rating of regions by differentiated quality of life rates (including factors as life span, income rates, living conditions, infrastructure, ecological conditions and safety) has been prepared by RIA rating agency (RIA Novosti group) experts under a project shared with Moscow News newspaper [11].
Based on the RIA group rating, we have identified a group of the best areas of Russia for well-be-
¿lyabinsk region £dimir region.
Tomsk, Samara regions +
region
regions in the Central -European part of the RF: Kaluga, ♦ Voronezh, Rostov, Lipetsk
y = 0,0045x+1,5863 /? = 0,0367
5 10 15 20 25
Fig. 6. Russian regions rated by RIA rating scores and TFR value
30
—I
35
ЭКOHOМMКA PETMOHA № 4 (2014)
Table 3
Summary table of countries differentiation by level of well-being and its components, Russia included (index per
2014 rating)
Continent, Territory, Country Total fertility rate (average number of children per woman) №1 №2 №3 №4 №5 №6 №7 Rating
Most well-off
Great Britain 2 1 12 94 9 30 9 6 7
Ireland 2 20 7 33 4 45 1 9 1
Iceland 2 24 37 27 15 1 101 44 17
New Zealand 2 10 25 37 17 7 41 17 5
France 2 12 26 92 18 10 28 15 11
Denmark 1.7 14 9 88 5 26 35 5 9
The Netherlands 1.7 18 2 97 3 23 8 2 4
Belgium 1.8 15 1 100 16 56 5 3 10
Norway 1.8 40 24 58 7 4 14 16 8
Finland 1.8 7 18 53 12 14 3 12 2
Australia 1.9 16 38 89 13 6 36 14 15
USA 1.9 26 41 114 28 39 53 7 21
Sweden 1.9 8 14 111 8 3 4 8 6
Less well-off countries
Tunis 2.2 58 86 31 82 59 54 68 56
Costa Rica 1.9 61 64 35 25 19 42 76 22
Mexico 2.2 70 73 91 69 84 47 30 66
Jamaica 2.1 65 59 23 62 87 51 72 45
Trinidad and Tobago 1.8 76 42 25 64 110 22 86 51
Argentina 2.4 67 46 55 29 25 105 112 57
Brazil 1.8 75 49 83 37 5 123 52 49
Chile 1.9 52 47 42 27 18 31 114 24
Colombia 2.3 57 83 43 107 15 29 29 31
Uruguay 2 104 58 5 35 13 94 95 41
Malaysia 2.1 49 28 113 87 73 10 91 58
Albania 1.8 101 54 95 65 50 18 99 73
Georgia 1.7 63 77 51 102 105 13 87 77
Least well-off countries
Dominica 2 108 69 99 46 89 113 35 101
Venezuela 2.4 117 117 34 77 33 124 118 117
Azerbaijan 2.3 95 107 122 74 94 86 100 122
Kuwait 2.4 85 70 18 108 104 72 83 93
Qatar 2.2 112 95 50 118 81 68 78 110
Turkey 2.1 51 50 112 111 60 97 20 79
United Arab Emirates 1.9 82 45 74 122 61 76 53 87
Bangladesh 2.3 100 94 52 67 117 55 34 91
India 2.4 56 53 44 91 107 117 37 81
Iran 1.9 93 119 72 97 103 56 73 115
Sri Lanka 2.1 87 97 54 55 90 23 94 78
Vietnam 2.1 89 76 103 123 123 79 111 124
Russia 1.7 41 68 90 106 88 112 42 95
ing level. The following table shows the relationship between rating indicators, both by number and total score, and total fertility rate value in the best well-off regions of Russia (Table 5).
It should be noted that Russia's axis of relationship between rating scores and total fertility rates is located relatively «lower» than the respective one on the global chart (Fig. 6). The Russia's
Table 4
Reproduction rates by culture component for groups of countries
Most well-off countries Gross reproduction rate Culture component rating Country's overall rating
Belgium 0.878 1 10
The Netherlands 0.830 2 4
Ireland 0.976 7 1
Denmark 0.830 9 9
Great Britain 0.976 12 7
Sweden 0.927 14 6
Finland 0.878 18 2
Norway 0.878 24 8
New Zealand 0.976 25 5
France 0.976 26 11
Malaysia 1.025 28 58
Iceland 0.976 37 17
Australia 0.927 38 15
Less well-off countries
USA 0.927 41 21
Trinidad and Tobago 0.878 42 51
United Arab Emirates 0.927 45 87
Argentina 1.171 46 57
Chile 0.927 47 24
Brazil 0.878 49 49
Turkey 1.025 50 79
India 1.1712 53 81
Albania 0.878 54 73
Uruguay 0.976 58 41
Jamaica 1.025 59 45
Costa Rica 0.927 64 22
Russia 0.830 68 95
Least well-off countries
Dominica 0.976 69 101
Kuwait 1.171 70 93
Mexico 1.074 73 66
Vietnam 1.025 76 124
Georgia 0.830 77 77
Colombia 1.122 83 31
Tunis 1.074 86 56
Bangladesh 1.122 94 91
Qatar 1.074 95 110
Sri Lanka 1.025 97 78
Azerbaijan 1.122 107 122
Venezuela 1.171 117 117
Iran 0.927 119 115
«best well-off areas» (regions) turned out to be located in the field of clearly depopulation type with total fertility rates less than 1.5-1.7. However, statistically the relationship between indicators of total fertility rating is not sufficient enough for formulation of working hypotheses.
A thorough examination of how the regions of the most well-off group are distributed by total
fertility rate revealed no significant relationship, but showed there are big differences between central regions of Russia and other regions. More importantly, the relationship between reproduction rate and rating score (which already includes life span and health along with other components) is positive (Fig. 7).
у = -0,0074х + 2,027 R2 = 0,0715
40 45 50 55 60 65 70 75
Fig. 7. Relationship between region's total fertility and score in overall rating of the best well-off regions
Table 5
Relationship between rating indicators and total fertility rate for Russia's 30 best regions for quality of life, 2012-2013
Rating Russian region Total rating score TFR
1 city of Moscow 72.9 1.323
2 city of St. Petersburg 68.6 1.483
4 Moscow region 60.6 1.493
5 The Republic of Tatarstan 58.4 1.796
6 Krasnodarskiy kray 54.3 1.699
7 Belgorodskaya region 53.4 1.515
8 The Khanty-Manskiysk-Ugra autonomous district 53.1 2.023
9 Tyumenskaya region 52.4 1.988
10 Voronezhskaya region 49.1 1.449
11 Nizhegorodskaya region 48.3 1.547
12 Kaluzhskaya region 48.0 1.623
13 Rostovskaya region 47.9 1.510
14 Yaroslavskaya region 47.8 1.604
15 Lipetskaya region 47.5 1.626
16 The Republic of Bashkortostan 47.5 1.859
17 Novosibirskaya region 46.9 1.711
18 Kaliningradskaya region 46.8 1.625
19 Leningradskaya region 46.7 1.220
20 Sverdlovskaya region 46.2 1.827
21 Omskaya region 46.0
22 The Yamalo-Nenetskiy autonomous district 46.0 2.053
23 Kurskaya region 44.8 1.695
24 Samarskaya region 44.6 1.539
25 Tomskaya region 44.4 1.549
26 Chelyabinskaya region 44.1
27 Vladimirskaya region 43.6 1.619
28 Sakhalinskaya region 43.4 1.713
29 Tul'skaya region 43.0 1.432
30 Permskiy kray 42.9 1.907
Quality of life index of Russia's regions included the following: income level, housing conditions, social infrastructure availability, environment and climate, safety, population satisfaction, demographics, health and education, industrial and economic development of the area, transportation infrastructure, business activities.
The current total fertility rate in the Urals Federal District was to some extent predicted by the authors of demographic adversity index of Russia's regions (A. G. Grishanova, N. I. Kozhev-nikova, L. L. Rybakovskiy), which based on the method of comparing standard total fertility and mortality rates to indices of mechanical movement of russian areas in 2006-2007 came to the conclusion that the Urals and the Southern districts are the demographically best regions [3, p. 36], [4, p. 34-35]. The authors of the method noted that the total fertility rate grew up significantly in the Middle and the Southern Urals in 2005-2008. The most demographically adverse regions of the Urals Federal District were then the Sverdlovsk and the Chelyabinsk region (1.031 and 1.034 respectively). Tyumen region areas looked less adverse (0.878), [4, p. 220]. We can't help but agree with this. The demographic situation in the compared regions depends on the differentiation of social groups and requires a correction to be introduced for particular historical and cultural developments [5, p. 30-32].
In general, the total rate dynamics in the Urals Federal District of Russia is in line with the nationwide Russian trend. But the clearly marked increase in the trend of years 2001 through 20122013 confirms the total fertility rate has almost fully recovered to the 1990 rate. The urban trend is especially remarkable. This is to partly confirm the hypothesis of an ongoing formation of a new fertility model. This model is influenced by an in-
Healthy environment 0,465
Participation in policy 0,174
Work 0,212
Success 384
Self fulfilment 0,225
Birth and child rearing 0,229
Communication 0,247
Quality of goods and services 0,376
valuable leisure time activities 0,329
Possibility freely to shift place of residence 0,308
Health 0,298
Personal security 0,264
Family 0,287
Rest 0,288
Fig. 8. Most important wishes for material and spiritual well-being, variables defined by Cramer's coefficient application
crease in the age of marriage and a shift towards the older age groups.
The selective sociological study of population that we conducted in 2013-2014 in the neighboring regions of the Urals Federal District revealed a significant relationship between the respondents' views of quality of life and material and spiritual well-being of family.
During the selective study of Ural Federal District population several attempts were made to «semiotize the dimensions of human life, providing an axiological significance to all of their elements» [1]. In our study «material» and «spiritual» well-being are understood as a combination, as most studies do not separate the categories one from another and note how much harmony there is in such a combination.
We used the Cramer coefficient of VORTEX statistical system to identify the statistical relationships between variables, that is when the value of one variable is completely determined by the value of the second variable that resembles the material and spiritual well-being of the population (Fig. 8).
According to Cramer coefficient, the value of the «material and spiritual well-being» variable is completely determined by variables with values equal to or exceeding 0.3. The healthy environment is at the first place among the most important factors (0.465). Personal interests aimed at «achieving success in life» hold the second place with 0.384, and to complete the list of the most important factors are the following respondents'
wishes: to «consume quality goods and services» (0.376), to take full advantage of free time (0.329), to «live where one wants and to freely change the place of residence»(0.308).
In general, the significant factors shown in italics in the table define the population's possibilities to achieve material and spiritual well-being. Most interestingly, healthy environment is at the top of the list, as it represents a set of favorable conditions understood as characterizing the quality of human environment and human life; integrally it is represented by the average life span and indicators of population's health.
Thus, the results of the study contribute to a deeper understanding of the respondents wishes and aspirations, as well as to identification of important functional elements needed to achieve well-being.
In conclusion it should be noted that the group of the most «good» countries and regions, both in cultural and socio-economic terms, the relationship between population reproduction rates and well-being turned out to be inverse. However, after 2000 high ratings of area's (region's) development tend to correlate with rates approaching those of ordinary reproduction of population. Ever more «good» countries and regions can demonstrate the ordinary generations replacement model which does not require vast engagement of foreign labor from outside the country or region. The structural changes in total fertility rate, in their turn, have somewhat acquired an inner impulse for a
new kind of development. This trend is starting to show also in the post-industrial areas of Russia. In the long run the positive relationship between quality of life indicators may occur in the regions
of the Urals and Siberia that have the most advantageous combination of components of scientific and technological development, culture, stability, prosperity and health.
The article has been prepared with the support of RFBR grant No.1306-00008 "Formation and improvement of quality of life as a priority of socio-economic development of Russian regions.»
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Information about the authors
Kuzmin Aleksandr Ivanovich (Yekaterinburg, Russia) — Doctor of Economics, Doctor of Social Sciences, Professor, the Leading Researcher, Institute of Economics of the Ural Branch of the Russian Academy of Sciences (29, Moskovskaya str., Yekaterinburg, 620014, Russia, e-mail: Kuz53@list.ru).
Tukhtarova Yevgeniya Khasanovna (Yekaterinburg, Russia) — Leading Economist, Institute of Economics of the Ural Branch of the Russian Academy of Sciences (29, Moskovskaya str., Yekaterinburg, 620014, Russia, e-mail: tyevgeniya@yandex.ru).
Ilinbayeva Yekaterina Aleksandrovna (Yekaterinburg, Russia) — Economist, Institute of Economics of the Ural Branch of the Russian Academy of Sciences (29, Moskovskaya str., Yekaterinburg, 620014, Russia, e-mail: e-ilinbaeva777@mail.ru).
UDC 339.13
G. Betti, F. Gagliardi, V. Salvucci
MULTIDIMENSIONAL AND FUZZY MEASURES OF POVERTY AT REGIONAL LEVEL IN MOZAMBIQUE1
This study provides a step-by-step account of how fuzzy measures of non-monetary deprivation and also monetary poverty may be constructed at the regional level, based on the Mozambican Household Budget Survey 2008-09 (IOF08). To our knowledge, this is the first attempt to apply Fuzzy Set Theory to poverty measurement in Mozambique.
1 © Betti G., Gagliardi F., Salvucci V. Text. 2014.
