How to find the share of cities. Share of the urban population of Siberia

Biysk was located next to the Altai Mountains and its mineral resources. The development of Biysk was also influenced by trade with Mongolia after the construction of a horse-drawn road through Kosh-Agach. The growth of Irkutsk was particularly favorably influenced by its proximity to Lake Baikal, the presence of rich hunting grounds and fertile lands, as well as salt and iron deposits.
The discovery of Siberian gold deposits in the first quarter of the 19th century was a powerful impetus for the development of Tomsk, Krasnoyarsk, Mariinsk, Yeniseisk, and Chita. Here were the offices of gold miners, workers were hired, supplies and tools were prepared, commission agents and contractors associated with the mines operated. The cities experienced periodic influxes of mine people. For example, in an official report on Chita in the mid-19th century it was noted: “There is a large gathering of workers in the city in the autumn, precisely in October, after workers leave the mines, but they are immediately hired again to the gold mines and the smallest number of them remain in Chita.” " It was gold, before it dried up, that built and decorated these cities. The development of the urban economy, under the influence of gold mining, began to intensify construction activities. Capital began to flow here, people began to arrive, and vigorous trade began to flow. However, the same gold mining led to the complete decline of handicraft production in Yeniseisk. The city turned into a supply center for taiga mines. Rich townspeople furnished their houses beautifully. But even today we have a lot of options on how to create comfort in our home. For example, you can buy glossy furniture for your rooms. Even provincial Krasnoyarsk, despite the fact that it was the seat of many gold miners and the center of management of the mines, over the years was decorated with only “a few churches and private buildings, but did not receive the development that could be expected from the confluence of favorable circumstances.”
The gold mining industry has caused a new surge in practical research into the territory of Siberia. Simultaneously with the search for gold, information was accumulating about the presence of other natural resources. In taiga regions, remote from the established settlement framework, numerous mine settlements were formed, which were connected by a new network of roads with the central settlements of the regions. At this stage of network formation settlements Simultaneously with the process of accumulation of socio-economic potential in the main urban centers, there was a process of dispersal of settlements along new, secondary planning axes, directed from the main settlement zone to the hinterlands.
Specific gravity The urban population of Siberia, which, however, had a constant growth trend, was at the level of the outlying regions of the European part of Russia: 7.2% in 1858, 8.5% in 1897, 11% in 1914. At the end of the 19th century, the city had an average of 8.2, and in 1917, 12.2 thousand inhabitants. Almost until the end of the 19th century, urban growth was moderate. Even a city like Irkutsk, which played the role of a leading center, grew slowly. In 1836 its population was about 20 thousand people, by the time of the reform of 1861 - 25, and by 1897 - 51.5 thousand inhabitants.

One of the varieties of the arithmetic mean is the chronological mean. Calculated from the totality of the values ​​of a characteristic at different moments or for different periods of time, it is customary to call average chronological, used to find the average level in time series.

In contrast to the variation series, which characterizes the change in phenomena in space, the dynamic series is a series of numbers that characterizes the change in phenomena in time. They are sometimes called temporal or chronological. Depending on the type of time series, to determine their average levels, appropriate methods for calculating the average chronological value can be applied. Thus, when an average level appears in a periodic dynamics series, it is possible to use a simple or weighted arithmetic average. If it is necessary to calculate the average level of the moment series of dynamics with equal time intervals between moments, then it is advisable to use the technique average chronological moment series with equal intervals:

where are the ordinal levels of the moment series; n is the number of moments in the series.

For example, at the beginning of each month of 2010, an agricultural organization (AHO) had the following pig population:

It is conventionally considered that the time intervals (intervals) between the starting moments (dates) of each previous and subsequent month are equal to each other. Therefore, to calculate the average quarterly pig population, formula (6.5) can be applied.

The indicators used to assess population distribution are given in the following table

Let's substitute the corresponding data and get:

This means that on average every month for the first quarter of 2010, the agricultural enterprise had 717 pigs.

In cases where it is necessary to determine the average level of the moment series of dynamics with at unequal intervals between moments, the arithmetic weighted average formula (6.4) is usually used.

For example, the number of workers in the agricultural team was: on April 1 - 20 people, on April 11 - 25, on April 30 - 36 people. It is necessary to calculate the average monthly number of workers in the team for April.

As can be seen from the above data, the time intervals between the indicated moments (dates) are not equal to each other: it can be assumed that the brigade had 20 people for 1 day, 25 for 10 days, 36 for 19 days. Therefore, to calculate the average monthly strength workers in the team, we use formula (6.4) and get:

Thus, in April the agricultural team had an average of 32 workers.

In system agro-industrial complex the average chronological value can be used when calculating the average annual, quarterly, monthly number of workers, livestock various types and groups of farm animals, the presence of various types of machine and tractor fleets and other cases.

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(at the beginning of 2000)

There are even higher differences in the degree of concentration of the urban population among the subjects of the Federation. More than 90% of the urban population in the Magadan region (92.0%), in the Murmansk region (91.9%), in the Khanty-Mansiysk Autonomous Okrug(91.2%); the minimum indicators are in the Chechen Republic (23.5%), in the Altai Republic (25.5%), in the Komi-Permyak Autonomous Okrug (25.8%).

The process of increasing the role of cities is called urbanization. Urbanization entails suburbanization - growth and development around large cities and their satellite cities, which form agglomerations.

Currently, the process of urbanization is increasingly underway - the spread of urban forms and living conditions to the countryside. In the broad sense of the word, urbanization is integral part urbanization.

Rural population Russia is 27%.

Share of urban and rural population by economic region

Accommodation rural settlements depends on natural geographical factors, primarily on soil and climatic conditions. Highest concentration rural population in the North Caucasus (45.1%) and Central Black Earth (37.4%) economic regions, where there are the most favorable conditions for agricultural production.

Urban and rural populations differ in demographic characteristics. IN rural areas the average life expectancy is lower, the birth and death rates are higher, the proportion of the elderly population is higher, which influences the increase in the mortality rate of the population and the decrease in average life expectancy (Table 5.4).

Table 5.5.

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Average chronological

Average chronological is the average level of a series of dynamics, i.e.

3.3. Share of urban population in the total population1)

i.e. average, calculated from the totality of indicator values ​​at different moments or periods of time.

Depending on the type of row, the dynamics are used various ways its calculation, namely the calculation of the average chronological interval series and the average chronological moment series.

The average chronological interval (more common) series is average value from the levels of the interval dynamics series, which is calculated by the formula:

where is the average level of the row;

— level of the dynamics series;

- number of members of the series

As an example, let’s look at data on children’s health institutions in Pskov and the region.

Table. Children's health facilities

The series under study is interval, using the average chronological formula we can calculate the average number of health institutions:

Institutions.

The average chronological moment series is the average value of the levels of the moment series dynamics. If there is a function expressing the change in a moment indicator over time, then for the time from to the average chronological moment series is equal to:

However, as a rule, statistics do not have continuous observation data available. Therefore, depending on the nature of the change in the indicator and the available data, various calculation methods are used.

Given equal time intervals between the dates for which data are available and a uniform change in the size of the indicator between dates, the average chronological moment series is usually calculated using the formula:

where is the row level;

- the number of all members of the series;

- average level.

If the time periods separating one date from another are not equal, then the average chronological moment series is calculated using the weighted arithmetic average formula, the weights of which are taken as the time intervals between dates, i.e., according to the formula:

where is the time during which this level the row remained unchanged.

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Subject and main tasks of socio-economic statistics

The subject of socio-economic statistics (SES) is the quantitative side of mass social and economic phenomena in inextricable connection with their qualitative content in specific conditions of place and time

main tasks of SES.

1. Statistical observation over the activities of all subjects of the country's economy at all stages of the reproduction cycle (production of goods and services; formation and distribution of primary income; redistribution of income; use of income for final consumption and the formation of savings; use of savings for accumulation).

Population distribution indicators

A comprehensive study of the state and development of the economy of the country and its regions (reproduction of fixed assets, investment activity, dynamics national wealth, characteristics of the labor market, pace economic growth, labor productivity growth rates, price indices and inflation rates, state budget deficit (surplus), level government debt and etc.).

3. Comprehensive study of the condition and development social sphere the country and its regions (vital population movement, infant mortality, life expectancy, household income and consumption, nominal and real wage indices, real disposable income indices cash income, social stratification of society, dynamics of poverty levels, etc.). 4. Analysis of macroeconomic proportions (for example, between production and consumption, accumulation and consumption, growth in labor productivity and growth in average wages and etc.).

5. Analysis of trends, patterns throughout the country and individual regions (decrease in the mortality rate, increase in the birth rate, dynamics of employment and unemployment, dynamics of inflation, growth in labor productivity and consumer prices, dynamics of the poverty level, etc.), as well as types of economic activity (dynamics of the number of enterprises and organizations, including small and medium-sized enterprises, dynamics of production volume and turnover of goods and services, reduction material costs and energy intensity, profit growth and reduction in unprofitability of production, growth in labor productivity and average wages, rising producer prices, etc.).8

6. Improving systems of indicators characterizing socio-economic phenomena and processes, classifications (classifiers), their consistency and interrelation, methods for assessing individual indicators.

7. Improving the methodology for analyzing socio-economic phenomena and processes, including the methodology of national accounting.

8. Providing government authorities with required information on the socio-economic development of the country and its regions in order to take measures to reduce their intensity).

9. Providing heads of enterprises and companies, managers, production organizers and businessmen with information on the development of the economy and social sphere necessary to study the external environment in which their companies or enterprises operate, when making decisions on investments and expansion of production , sales organizations, etc.

10. Informing society, educational and research institutions and other organizations and individuals about the main results and trends in the socio-economic development of the country and its regions.

11. Providing information on the state and development of the Russian economy in international organizations: UN, International Monetary Fund (IMF), The World Bank and etc.

12. Introduction of new technologies for collecting, processing, transferring and distributing statistical information, etc.

Methods for calculating the average annual population.

the choice of method for calculating it depends on the source data.

1. If there are data for the beginning (S1) and the end of the period (S2), then the average population is determined using the simple arithmetic average formula:

3. If the intervals between dates are unequal, then the calculation using the weighted arithmetic mean method:

To characterize the change population in time are used:

1. population growth rate:

2. population growth rate:

Having determined the population size, the SES studies its composition using the method factions, which is carried out according to:

social composition,

areas of activity and sectors of the economy,

·professions,

age,

marital status,

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population statistics, formulas for their calculation

Basic concepts and indicators

Basic concepts of demographic statistics
Census	Demographic qualification intended to characterize demographic situation in the country. In Russia, complete population censuses were carried out in 1920, 1926, 1939, 1959, 1970, 1979, 1989 and 2002.
Microcensus	Conducted in the intervals between population censuses, it usually covers 5% of the population (for example, the census in Russia in 1994)
Age and sex pyramids	A graphic image that allows you to clearly display the age and sex composition of the population
Natural population movement	Change in population due to births and deaths
Natural increase (decrease) of population	Positive (negative) difference between the number of births and deaths: , Where N– number of births; M– number of deaths
Mechanical increase (decrease) of population (balance of migration)	Positive (negative) difference between the number of arriving and leaving population: , Where P IN
Migration	Movement of people (migrants) across the borders of territories with a change of residence permanently or for a certain time. Migration can be internal and external
Internal migration	Movement of population within a certain territory
External migration	Population movement across territory boundaries
Gross migration (gross migration)	Shows the total number of migrating residents: P + V. This indicator is also called migration turnover
Balance of migration	The difference between the number of arrivals and departures: P – V
Immigration	Entry of population into a particular area or country
Emigration	Exit of population from a given area or country

Continuation of the table. 3.1

Population indicators (categories) in censuses
Present population (NP)	A category of population that unites people actually located in a given locality at the time of the census: NN = PN – VO + VP, Where Mon– permanent population; IN– temporarily absent; VP – temporary residents
Resident population (PN)	A category of population that unites people for whom a given locality represents their place of usual residence, regardless of their actual location at the time of registration (census): PN = NN – VP + VO
Temporarily absent (VO)	These are persons who have a permanent place of residence in a given locality and who are absent at the time of registration. Their absence should not exceed 6 months
Temporary residents (TP)	These are persons who are at the time of registration in a given locality, but have a permanent place of residence in another locality
Population figures
Population at the end of the year	, Where S n.g. N – number of births; M– number of deaths; P– the number of arrivals to a given locality; IN– the number of people who left a given locality
Average annual population	On a certain date for equal periods is calculated using the formula , Where n– number of levels (dates); S 1… P– population size on a certain date. At the beginning and end of the year it is determined as the arithmetic average: , Where S n.g.– population at the beginning of the year; S k.g– population at the end of the year. In an interval series with unequally spaced levels, it is determined by the formula , where is the average population i-th period; – duration i th period

Continuation of the table. 3.1

Continuation of the table. 3.1

End of table. 3.1

Table 5.4.

Population distribution indicators

transport network

, per 1 sq. km of area; с – total energy consumption per capita (fuel standard)– the center city and adjacent small towns and villages. Usually their boundaries are set individually. In general, each settlement, a certain part of the economic active population which is occupied in the central city.

The relationship between the population and the territory it occupies measures density(or density) of the population. These are the number of residents (more precisely, permanent residents) per unit area of ​​the territory, usually per 1 sq. km. When calculating population density, it is important to correctly determine which territory the population is attributed to - to the inhabited territory or to the entire land density. Russian demography excludes large inland water spaces, such as Lake Baikal, from its territory.

A country's population density is the average of widely varying values. More precisely, it is the arithmetic average of the densities of individual regions, weighted by the size of their territory.

The density indicator is influenced by the nature of human settlement, the density and size of settlements. Large cities, whose territory is relatively small, are much more densely populated than rural areas. Therefore, the density of the rural population in relation to the territory of rural areas and the density of the urban population in relation to the territory of cities is often considered separately. Since rural residents are also associated with the territory and the economy, such a division has an important economic meaning.

5. The quality of the population as a factor in economic development.

An analysis of demographic facts convinces us that their explanation should be sought in the laws of social life. In the complex web of factors influencing population movement, the main role is played by factors related to economic relations.

However, they do not act directly, but through the living conditions of individual families and individuals, largely through their conscious will.

Of all economic conditions One should first of all keep in mind belonging to one or another social stratum. Different attitudes towards property, different nature of sources of income determine different attitudes towards issues of family, marriage, childbirth, and place different conditions regarding mortality. Further, the size of income is of great importance, which is associated with social class and at the same time varies greatly within each social class. An important factor influencing population movement is living conditions. Employment is closely related to the level of well-being, income and their structure. At the same time, demographic phenomena are influenced not only by the employment of these individuals themselves, but also general position with employment at a given time and in a given country. This also includes the employment of women, which has a great influence on demographic phenomena.

A comprehensive consideration of the factors influencing demographic processes leads us to such a complex category as the standard of living.

“The standard of living of the population is the level of well-being of the population, consumption of goods and services, a set of conditions and indicators characterizing the extent to which people’s basic life needs are satisfied.” In other words, the standard of living represents the degree of development and satisfaction of the needs of a person living in society. Need satisfaction is determined by the level of utility of the consumer bundle. Thus, theoretically, a change in living standards means a consumer moves to a higher or lower indifference curve.

The standard of living in the narrow sense refers to the provision of the population with necessary material benefits and services, the achieved level of their consumption and the degree of satisfaction of reasonable (rational) needs. This is how well-being is understood. Monetary value goods and services actually consumed by an average household over a certain period of time and corresponding to a certain level of satisfaction of needs represents the cost of living.

The standard of living in the broad sense of the word includes the entire complex of socio-economic living conditions of society. In a broad sense, the concept of “standard of living” includes living conditions, work and employment, everyday life and leisure, health, level of education, natural environment, etc. However, in this case, the term “quality of life” is more often used. Standard of living is an essential element of the broader concept of lifestyle.

In modern statistical theory and practice, there are several indicators of the level of social welfare, which are either widely used in practice as measures of the standard of living of the population, or are of certain scientific interest. The calculation of such indicators is necessary for an integral assessment of the standard of living, as well as its comparative analysis by region and country.

To the indicators used on practice, can be attributed to:

1/ macroeconomic cost general indicators

Volume of gross internal product,

National income,

Net national disposable income;

2/ demographic indicators

Infant mortality rate,

Life expectancy at birth,

3/ free time

One of the main disadvantages of the listed cost general indicators used to analyze the standard of living is that they contain elements that are not directly related to the standard of living (for example, GDP includes expenses for the maintenance of the army, the state apparatus, etc.). In addition, as noted in modern studies, an increase in the volume of GDP and related indicators can be obtained by deteriorating the quality environment, which is an essential component of quality of life in developed countries.

The advantage of demographic indicators is that they reflect not only a quantitative characteristic of the standard of living, but also a qualitative one.

The proposal for the possibility of using the indicator of free time as a general assessment of the standard of living came from the famous statement of K. Marx that the time used for leisure, study, self-education, sports, etc., in the future will become a measure of social wealth. However, modern statistics do not provide constant monitoring of this indicator; its study is possible only with the help of periodic specially organized sample surveys.

The cost of living index in the statistical practice of our country has become

used back in the 20s. When calculating it, a set of consumer goods (consumer basket) is determined, typical for the structure of expenses of a certain group of the population (highly paid workers,

pensioners, students, etc.). To calculate the index, the cost of this set in current and basic prices is compared. Moreover, the base period in developed countries remains unchanged for several (five or more) years. However, this calculation methodology actually reflects not so much a change in the standard of living as the influence of one factor on it - consumer prices. In addition, the use of fixed consumer basket for a long time does not allow taking into account qualitative changes in the structure of consumption, and also complicates the problem of comparability of goods.

From the above it follows that the indicators of living standards used in practice place emphasis on quantitative or qualitative assessment any one aspect of the well-being of society. In this regard, economic science is faced with the acute question of constructing aggregate indicator standard of living.

One of the proposed indicators of this kind is human development index (HDI), proposed by specialists from the United Nations Development Program (UNDP). The HDI is a composite index that includes the most important components of living standards:

Life expectancy at birth;

Achieved level of education;

Real GDP per capita (in US dollars based on parity purchasing power).

The HDI is defined as the arithmetic mean of the indices of the three indicated indicators. In turn, the index of each indicator is the ratio of the difference between the actual and minimum values ​​of the indicator to the difference between its maximum and minimum values.

To calculate the life expectancy index at birth minimum value is taken to be 25 years, and the maximum is 85 years.

The index of the achieved level of education is calculated as the arithmetic mean weighted of two sub-indices: the literacy index among the adult population (aged 15 years and older) with a weight of 2/3 and the index of the total share of primary, secondary and high school students educational institutions(for persons under 24 years old) weighing 1/3. The limit values ​​of both shares are 0 and 100%.

Index calculation method real GDP per capita is somewhat more complicated. Real GDP, calculated in US dollars based on purchasing power parity of currencies, was adjusted until 1999 to take into account the fact that it is not necessary to have too high an income to have a decent standard of living. As a threshold value sufficient to reasonably high level well-being, the average per capita volume for the world as a whole is taken. At the same time, the value of the excess for “rich” countries was discounted based on the premise that the importance of higher income sharply decreases. An approach in which the indicators of only some countries change cannot be called objective, moreover, the discounting method used had too strong a downward impact on income.

In 1999, the technique was improved. Now a single approach is applied to all income indicators, and the GDP index (I) is calculated using the following formula:

I = (log Y – log Ymin)/(log Ymax – log Ymin)

Where Y is the real GDP per capita of a country at PPP in US dollars.

The revision of the methodology does not allow for direct comparisons of the indices given in the latest report of the UN Development Program, published in 1999, with previous periods. Nevertheless, an analysis of trends in economic growth rates and social components of the index shows that over the past decade, life in many countries of the world has become more prosperous.

According to UNDP estimates, in 1997 the first three places in terms of human development(out of 174 countries for which the Human Development Index is calculated) Canada, Norway and the USA were occupied, and Ethiopia, Niger and Sierra Leone closed the list, whose indicators are approximately three times lower than in the top ten countries.

It should be noted that the connection between the level of income of a society and the development of its human potential is not automatic. For 77 of the 174 countries surveyed, the per capita GDP ranking was higher than the HDI ranking; among them in such rich countries as Kuwait, Saudi Arabia, Luxembourg and others. the discrepancy was 10 positions or more. It can be said that these countries do not sufficiently use the results of their economic development for the corresponding development of the nation.

For most countries studied (92 out of 174), the HDI ranking was higher GDP rating. This shows that increasing costs of human development are becoming priority direction development of the world economy. In this case, it is not so much the amount of income that is of particular importance, but the nature of the distribution of the results of economic growth in the interests of the development of the nation.

Russia, according to UNDP estimates, in 1997 was included in the category of countries with an average level of human development, occupying 71st place. The HDI ranking was eight positions higher than the real GDP ranking. According to the index of the level of education of the population, our country was close to industrialized countries, but the values ​​of the other two indices were at the level of developing countries. Our country's closest neighbors in the HDI rankings were Western Samoa, Ecuador, and Macedonia. Among the countries former USSR Estonia, Belarus and Lithuania were ahead of Russia (54th, 60th and 62nd places, respectively).

More detailed data on economic and social development Russia in comparison with other countries of the world are given in Table 5.5.

Table 5.5.

Main indicators of the standard of living of the population

The methodology for calculating the HDI, as well as the general assessment of living standards, remains controversial. Both the issues of selecting indicators, the meaning of weighting coefficients, and the very need and possibility of constructing a single indicator for such a complex and multidimensional phenomenon as the level (quality) of life are discussed.

There are also other proposals for constructing a general indicator of the standard of living based on specific indicators.

An example of such an indicator is the “tension indicator”, the components of which are:

Degree of provision with consumer goods,

Crime level,

The degree of dissatisfaction of the population with a complex of unresolved socio-political, economic and environmental problems.

Since indicators of the level and quality of life have different dimensions, the construction of an integral indicator involves a transition to some uniform characteristics. As such, it is proposed to use ranks for each indicator. In this case, the ordering of the considered indicators from 1 to n is used for stimulant indicators (such as, for example, life expectancy) and the reverse order for disincentive indicators (for example, such as infant mortality rates, the number of accidents, etc.) . Having assigned ranks for individual indicators, the average rank for their totality is found. The lower its value, the more developed the country or region is in terms of the characteristics under consideration.

The disadvantages of this method include the mechanical connection of the initial indicators, as well as the fact that the obtained average ranks do not reflect the actual distance between the objects of study. In this sense, ordering by the values ​​of the principal components or principal factors is preferable. In addition to the listed methods, for a general assessment of living standards can also be used synthetic indices, constructed on the basis of standardized values ​​of initial indicators. In this case, standardization is carried out by dividing by the range of variation, and not by the standard deviation, as is usually done. This method also has disadvantages, essentially assuming that the comparison of objects for all indicators occurs in relation to a certain sample, and all indicators act as equivalent.

Demographic indicators are significantly influenced by poverty level population, which is currently considered as a complex multidimensional phenomenon and is not associated only with the level of well-being.

The Problem of Poverty Assessment is currently on the pages of economic publications not only in developing, but also in industrialized countries. The intensifying processes of globalization of the world economy are accompanied by increased inequality in income distribution and the spread of poverty.

Traditional income-based definitions of poverty do not allow for international comparisons of national levels and extent of poverty. In 1990, the World Bank set a single poverty threshold for all developing countries equal to $1 per day (at purchasing power parity in 1985 prices). According to experts World Bank, this amount was sufficient to purchase the minimum amount of food required for one person for one day. For comparison: in the mid-90s, the daily average income of each person on the planet was $16.

As important as it is, approaching poverty in terms of income alone is not sufficient. Poverty is multidimensional and qualitative in nature. That is why in 1997, experts from the UN Development Program proposed a new indicator - Human Poverty Index (HPI), the calculation of which takes into account three factors that determine the opportunity for each individual to have a decent life: life expectancy (this factor is estimated by the proportion of the population whose expected life expectancy is less than 40 years); access to knowledge is measured by the proportion of illiterate people in the adult population; material conditions of existence are assessed using the following three indicators: the proportion of the population without access to medical care; proportion of the population without access to drinking water; proportion of children under five years of age who are undernourished. Data on these indicators in selected regions of the world are shown in Table 5.6.

Table 5.6.

Indices of human poverty in selected regions of the world in 1995.

(% of the total population of the region)

The overall human poverty index is expressed as the proportion of the population affected by these factors. Data on HBI in selected countries and regions developing world are given in table 5.7.

Table 5.7.

Indicators of per capita income and HBI

for selected developing countries in 19947

As Table 6 shows, in most countries there is a fairly close correlation between per capita income and HBI. However, there is also a significant discrepancy between these indicators. Although per capita income in Arab countries is on average three times higher than in sub-Saharan Africa, the HBI in some of them sometimes approaches those of individual African countries. This is due to the fact that in the mid-90s the proportion of illiterate people among the adult population was 43%. Latin America is characterized by a rather low level of sanitary and hygienic conditions, since the proportion of residents here who do not have access to medical care is 30%; The only worse situation in this regard is in sub-Saharan Africa, where 47% of the population does not have access to such services.

Modern poverty is a phenomenon not limited to developing countries. By setting the poverty threshold for Eastern European countries at $4 per person per day and for industrialized countries at half the average median wage, the UNDP determined that in Eastern European countries the number of poor people is 120 million, and in industrialized countries - 100 million (10% of their population), of which 37 million people are unemployed.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p. 59.

Ibid., p. 62-63.

Social statistics: Textbook / Ed. member-corr. RAS I.I. Eliseeva. - M.: Finance and Statistics, 1997, p.4.

International statistics: Textbook. manual / I.I. Eliseeva, T.V. Kosteeva, L.N. Khomenko, - MN.: Vysh.shk., 1995, p. 26-41.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, pp. 64-66.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p.42.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, pp. 43-44.

Combined use of censuses and sample surveys. Series: Methodology of sampling studies. Issue 2, Moscow, 1991, pp. 60-61.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p.9.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.200-201.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.201.

Andreev E.M., Bondarskaya G.A. Can data on the expected number of children be used in population projections? / Questions of Statistics, 2000, No. 11, p.61.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, pp. 213, 277.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, pp. 178-180.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.202.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p. 144.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p. 140.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.203.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p. 105.

Statistics: Course of lectures / Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc. ; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.: INFRA-M, 1999, p. 197..

Right there. P. 199.

Statistics: Course of lectures / Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc. ; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.: INFRA-M, 1999, p. 207-208..

Right there. pp. 206-210.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p. 140.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p. 171.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p. 266.

Statistics: Course of lectures / Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc. ; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.: INFRA-M, 1999, p. 211.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p. 267.

Statistics: Course of lectures / Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc. ; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.: INFRA-M, 1999, p. 212.

Demography course: Textbook / Under. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, pp. 272-274.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.205-206.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.250.

International statistics: Textbook. allowance / I.I. Eliseeva, T.V. Kosteeva, L.N. Khomenko. - Mn.: Vysh. school, 1995, p.196.

Demographic aging of the population Russian Federation(based on materials from the State Statistics Committee of Russia) / Questions of Statistics, 2000, No. 1, p. 61.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p.69.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p.70.

Statistics: Course of lectures/Kharchenko L.P., Dolzhenkova V.G., Ionin V.G. and etc.; Ed. Ph.D. V.G.Ionina. - Novosibirsk: Publishing house NGAEiU, M.:INFRA - M, 1999, p.203.

Demography course. Textbook: Ed. prof. Boyarsky A.Ya. M: Statistics, 1967, p.71.

Raizberg B.A., Lozovsky L.Sh., Starodubtseva E.B. Modern economic dictionary. - M., INFRA, 1997, p. 351.

Economic statistics: Textbook/Ed. Yu.N.Ivanova. - M.: INFRA-M, 1999, p.442.

Kuznetsova E.V., Dmitrieva E.D. Human Development Index and other indicators of socio-economic development of Russia and individual foreign countries/ Questions of Statistics, 2000, No. 3, p. 14.

Ibid., p. 15.

Social statistics: Textbook/Ed. Corresponding Member of the Russian Academy of Sciences I.I. Eliseeva. - M.: Finance and Statistics, 1997, p.76..

Zubchenko L.A. On poverty indicators / Questions of Statistics, 2000, No. 3, p. 24.

Zubchenko L.A. On poverty indicators / Questions of Statistics, 2000, No. 3, p. 25.

By currency purchasing power parity

Page 1

The projected population of the city should be established for the first stage of construction and for the estimated period.

The entire population of the city is divided into three structural groups: city-forming, service and independent. The city's population is calculated using the labor balance method; it is defined as a function prospective numbers personnel employed in enterprises and institutions of city-forming importance and their share in the urban population. The calculation is made using the formula:

where N is the total population of the city, thousand people;

A - number of city-forming personnel, thousand people;

a is the specific gravity of the city-forming group, %.

The number of city-forming personnel is determined according to the title list of institutions and enterprises given in the assignment.

The proportion of city-forming and service population groups is taken in accordance with the recommendations of building codes and regulations 2.07.01.89* “Urban planning. Planning and development of urban and rural settlements.” For new cities and towns, the share of the city-forming population group should be assumed to be at least 40% for the first phase of construction and at least 35% for the estimated period. The share of the city-forming group of settlements located in climatic regions ΙΑ, 1B and II should be taken for the first stage of construction at least 50%, and for the estimated period - no more than 40% of the project population.

The number of service and non-self-employed population groups is calculated using the following formulas:

where B is the number of the serving population group, thousand people;

δ - share of the service group, %.

where B is the number of the non-amateur group of the population, thousand people;

b is the share of the non-amateur group, %.

Building codes and the rules recommend that the share of service groups be taken within the range of 19-21% for the first stage of construction and 23-27% for the estimated period - for large and largest cities, and for medium and small cities and other settlements 15-17% and 19-22%, respectively.

The share of the non-amateur population group can be determined from the equation:

The results of the calculations performed should be summarized in a table of the project balance of the city’s population using the form below.

Table 1. Project balance of the city population

Example. It is necessary to determine the design population of the city.

Initial data. The construction area is located in the IIIB climate zone (Volgograd). The number of city-forming personnel is: for the first stage of construction - 21 thousand people, for the estimated period - 47 thousand people.

Solution. For a new city designed in climatic zone III, the share of the city-forming group is assumed to be 40% for the first stage of construction and 30% for the design period. Then using formula (1) we get:

where Ν1 is the projected population of the city for the first stage of construction;

Νρ is the projected population of the city for the estimated period.

The share of the serving population group should be assumed to be 17% for the first stage of construction, and 22% for the estimated period. The size of the service group, according to formula (2), is equal to:

where B; - the design number of the serving population group for the first stage of construction;

Br - the design number of the serving population group for the estimated period.

The share of the non-amateur group of the population in accordance with equation (4) will be:

The proportion of the urban population in France averages 60-80%. With a density of 107 people/sq. km, France is one of the densely populated areas of the planet, but moderately populated in Europe. In France, migrations are mainly represented by immigrations. People go to big cities this developed country, included in " Big seven" Mostly, of course, they head to Paris. Residents of the outback are also moving towards Paris and large cities. There are also internal migrations that are characteristic of all states, and there is also a process of suburbanization. The total fertility rate in France is one of the highest in Europe. Population Policy aimed at stimulating fertility. Population density by department.

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