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4**. This indicator combined lifeexpectancy, educationalattainment, and income to create human development index – HDI. Since the only other waypermitting to evaluate development levels was GDP, many researchers sought another, morecomprehensive social and economic indicator. HDI was elaborated as a result of this search. TheReport stated that no indicator per se can comprehensively measure such a complex phenomenon. The Report alsoindicated that the search for further methodological and data refinements to theHDI continued. It shall be noted that HDI was not intended to replace othersocial and economic indicators used in the Report, since they are veryimportant for more comprehensive evaluation of situation across individualcountries*


The longevity index is measured aslife expectance at birth in the reported year. Index of educational attainment is measured as thecomposite adult literacy index (2/3 of weight) and combined primary, secondary,and tertiary enrollment(1/3 of weight). Until 1995 the average term of education was used in stead ofthe combined enrollment.Living standards are measured basing on per capita real GDP adjusted for localcost of living (in purchasing power parity (PPP) US $). The PPP determines thepurchasing power of localcurrency, i.e. the number of currency units necessary to purchase a similar representativeconsumer goods and services basket purchased for 1 US $ in the USA.

In order to build the composite humandevelopment index, fixed minimal and maximal values were set for each indicator:

  • Life expectancy at birth: 25 to 85 years
  • Adult literacy: 0% – 100%
  • Aggregate enrollment: 0% – 100% (before 1995 average termof education 0 – 15years)
  • Per capita real GDP (in PPP US $): 100 PPP US $ - 4,000 PPP US $.

For each HDI component individual indicescan be calculated as:

Index =

Actual value Xi –minimal value Xi

Maximal value Xi – minimal value Xi.

It is somewhat more difficult to computethe income index. The threshold level (y*) is set as the average per capitaworld income (PPP US $ 5,711), any excess is discounted according to thefollowing formula of utility of income, based on the Atkinsonformula*


W (y) = y* for 0 < y < y*

= y* + 2 ((y – y*) ) fory* < y < 2y*

= y* +2 (y* ) + 3 (y – 2y*) for 2y* < y < 3y*

In order to compute the discounted value ofmaximal income (PPP US $ 40,000) the following part of the Atkinson formula isused:

W (y) = y* + 2 (y*) + 3 (y*) +4 (y*) + 5 (y*) + 6 (y*) + 7 (y*) + 8 [(40000– 7y*)]

It is explained by the fact that the valueof PPP US $ 40,000 is between values of 7y* and 8y*. According to the aboveformula, the discounted value of maximal income (PPP US $ 40,000) is equal toPPP US $ 6,040.

6. Analysis of Tendencies of Russia's Regions
Development (typology ofregions, conclusions
andrecommendations), TACIS project
(contract BIS/95/321/057).

This study comprises two typologies.

1) The basetypology of regions in accordance with respective social and economic situationuses simple indicators: dynamics of per capita incomes and dynamics ofindustrial production. Each indicator was initially divided into five levels.As a result, there were obtained 25 correlations of two indicators, forpurposes of this study integrated into 9 types>

Typology of regions as broken down by social(income level dynamics) and economic component (output volumeindex)

Economic component

Social component

> 107






Republic of Sakha (Yakutia), Irkutsk oblast,Kemerovo oblast, Tyumen oblast

Vologda oblast, Krasnoyarsk krai, Arkhangelskoblast

Belgorod oblast, Lipetsk oblast, Ulianovskoblast, Republic of Khakasia, Republic of Bashkortostan, Orenburg oblast,Astrakhan oblast

100 – 120

Perm oblast, Republic ofKarelia

Republic of Komi, Samara oblast,Murmansk oblast, Magadan oblast, Sakhalin oblast

Republic of Buryatia, Nizhny Novgorodoblast, Primorsky krai, Republic of Tyva

Kursk oblast, Republic of Tatarstan,Tambov oblast, Tomsk oblast, Penza oblast, Krasnodar krai

89 – 100

Novgorod oblast, Amur oblast,Sverdlovsk oblast

Smolensk oblast, Chelyabinsk oblast,Kirov oblast, Tula oblast

Omsk oblast,
Novosibirsk oblast

89 – 70

Kamchatka oblast, Republic ofAltai,
Moscow city

Saint-Petersburg city, Republic ofAdygea, Yaroslavl oblast, Chita oblast

Leningrad oblast, Udmurt Republic,Kaluga oblast, Kostroma oblast

Volgograd oblast, Saratov oblast,Rostov oblast, Ryazan oblast, Republic of Mordovia, Tver oblast, Oryol oblast,Voronezh oblast, Altai krai, Kaliningrad oblast, Bryansk oblast, Vladimiroblast

Republic of Mariy El, Stavropolkrai,
Kurgan oblast

< 70

Khabarovsk krai

Chuvash Republic, Moscow oblast, Republic ofKabardino-Balkaria, Karach-Cherkesian Republic, Pskov oblast, Republic ofNorth Osetia (Alania)

Ivanovo oblast, Republic of Kalmykia,Republic of Dagestan

Group 1. Regions,where output and income dynamics were at the same pace.

Type 1. Mostsuccessful regions in social and economic terms:

  1. Republic of Sakha, Irkutsk, Kemerovo, Tyumen oblasts;
  2. Republic of Komi, Samara, Murmansk, Magadan, Sakhalin oblasts.

Type 2. Regionswhere medium values of social and economic components were observed: Smolensk,Chelyabinsk, Kirov, Tula oblasts.

Type 3. Regionslagging behind in terms of both economic and social component:

  1. Volgograd, Saratov, Rostov, Ryazan oblasts, Republic of Mordovia,Tver, Oryol, Voronezh oblasts, Altai krai, Kaliningrad, Bryansk, Vladimiroblasts;
  2. Ivanovo oblast, Republics of Kalmykia, Dagestan.

Two large groups may be singled out amongthe regions displaying differing economic and social components.

Group 2. Regionswhere the rate of growth in incomes outpaced the all-Russian average, whileeconomic indicators fell more than in Russia on the whole. The regions in thisgroup can also be>

Type 4. A sharpcontrast between falling output volumes and increasing household incomes:

  1. Moscow and St. Petersburg;
  2. Kamchatka oblast, Republic of Altai;
  3. Republic of Adygea, Yaroslavl and Chita oblasts;
  4. Khabarovsk krai.

Type 5. Slightpreponderance of social indicators as compared to economic component, bothcomponents display rather high values:

    1. Perm oblast, Republic of Karelia;
    2. Novgorod, Amur, Sverdlovsk oblasts.

Type 6. Slightpreponderance of social indicators as compared to economic component, bothcomponents display rather low values:

  1. Leningrad oblast, Udmurtian Republic, Kaluga, Kostroma oblasts;
  2. Chuvash Republic, Moscow oblast, Kabardian-Balkarian,Karach-Cherkesian Republics, Pskov oblast, Republic of North Osetia.

Group 3. Regionswhere the rate of growth in incomes lagged behind the all-Russian average,while economic indicators fell more than in Russia on the whole. The regions inthis group can also be>

Type 7. A sharpcontrast between falling output volumes and increasing household incomes (notin favor of incomes):

  1. Belgorod, Lipetsk, Ulianovsk oblasts, Republic of Khakasia,Republic of Bashkortostan, Orenburg, Astrakhan oblasts;
  2. Kursk oblast, Republic of Tatarstan, Tambov, Penza oblasts,Krasnodar krai.

Type 8. Slightpreponderance of economic indicators as compared to the social component, bothcomponents display rather high values:

  1. Vologda oblast, Krasnoyarsk krai, Arkhangelsk oblast;
  2. Republic of Buryatia, Nizhny Novgorod oblast, Primorsky krai, Republic of Tyva.

Type 9. Slightpreponderance of economic indicators as compared to the social component, bothcomponents display rather low values.

  1. Omsk, Novosibirsk oblasts;
  2. Republic of Mariy El, Stavropol krai, Kurgan oblast.

At the next stage the typology was mademore precise according to living standards indicators. In order to measuredifferences in living standards across regions there were used the ratiobetween per capita household incomes and the subsistence minimum (i.e. purchasepower of incomes). There was also used the specific weight of households withper capita incomes below the subsistence minimum as an indicator characterizingthe structure of living standards. Coefficient of prosperity across differenttypes of regions was introduced as an additional characteristic of livingstandards. This coefficient demonstrates how many times average incomes ofrelatively well-to-do households (i.e. with incomes above the subsistencelevel) exceed the subsistence level (see Table).

Typology of regions of Russia according toprosperity
coefficient in 1995

Degree of stratification

Prosperity coefficient


(ranked by decrease incoefficient)


Over 2,0

Moscow city, Tyumen oblast, Amur oblast, Kemerovooblast, Krasnoyarsk krai, Magadan oblast, Saint-Petersburg city, Kamchatkaoblast, Republic of Komi, Perm oblast, Belgorod oblast, Samara oblast, Tulaoblast.

Above medium

1,7 – 2,0

Oryol oblast, Vologda oblast,Republic of Bashkortostan, Kaluga oblast, Kostroma oblast, Irkutsk oblast,Novgorod oblast, Tambov oblast, Ulianovsk oblast, Smolensk oblast, Murmanskoblast, Nizhny Novgorod oblast, Chelyabinsk oblast, Voronezh oblast, Sverdlovskoblast, Yaroslavl oblast.


1,3 – 1,7

Rostov oblast, Republic of Altai,Krasnodar krai, Kursk oblast, Kaliningrad oblast, Republic of Sakha (Yakutia),Bryansk oblast, Ivanovo oblast, Lipetsk oblast, Omsk oblast, Tomsk oblast,Republic of Tatarstan,Stavropol krai, Altai krai, Republic of Karelia, Udmurt Republic, Khabarovskkrai, Arkhangelsk oblast, Tver oblast, Republic of Khakasia, Republic ofBuryatia, Primorsky krai,Sakhalin oblast, Kirov oblast, Chuvash Republic, Leningrad oblast

Below medium

1,0 – 1, 3

Ryazan oblast, Volgograd oblast,Moscow oblast, Astrakhan oblast, Saratov oblast, Vladimir oblast, Pskovoblast, Penza oblast, Republic of North Osetia, Republic ofKabardino-Balkaria, Novosibirsk oblast.


Below 1,0

Republic of Mordovia, Kurgan oblast,Karach-Cherkesian Republic, Republic of Adygea, Republic of Mariy El, Republicof Kalmykia, Orenburg oblast, Republic of Dagestan, Chita oblast,Republic of Tyva

The importance of this coefficient (and,respectively, the typology, which bases on this coefficient) is that it permitsto measure how rich are relatively well-to-do strata of local populations andthe degree of property stratification.

The generalized (aggregate) typology ofregions in terms of living standards is based on two parameters: householdpurchasing power adjusted for the poverty level in 1995 and the change in realhousehold incomes in comparison with 1990 figures. Nine typological groups weresingled out according to these parameters. It shall be noted that the typologybased on living standards was somewhat different from the base typology ofregions according to social and economic situation (see Table).

Typology of regions of Russia as broken downby household
living standards in 1995

Purchasing power adjusted for povertylevel

Real household incomes by 1990

over 80%

60 to 80%

Below 60%

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