One type of arithmetic mean is the chronological mean. Calculated from the totality of the values ​​of the attribute 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.

Unlike the variational series, which characterizes the change in phenomena in space, the dynamic series is a series of numbers that characterizes the change in phenomena over time. Sometimes they are called temporal or chronological. Depending on the type of time series, appropriate methods for calculating the average chronological value can be applied to determine their average levels. So, when an average level is generated in a periodic series of dynamics, it is possible to use the arithmetic mean, simple or weighted. If it is necessary to calculate the average level of the moment series of dynamics with equal time intervals between the moments, then it is advisable to use the technique average chronological moment series at equal intervals:

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

For example, in an agricultural organization (ACO) at the beginning of each month in 2010, there was the following number of pigs:

Conventionally, it is considered that the intervals (intervals) of time between the initial moments (dates) of each previous and subsequent month are equal to each other. Therefore, formula (6.5) can be applied to calculate the average quarterly number of pigs.

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

Substitute the corresponding data and get:

This means that on average monthly in the first quarter of 2010 there were 717 heads of pigs in agricultural enterprises.

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

For example, the number of employees in the SHO 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 employees in the brigade for April.

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

Thus, in April there were an average of 32 workers in the SHO brigade.

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

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(at the beginning of 2000)

Even higher differences in the degree of concentration of the urban population in 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-Mansi Autonomous Okrug (91.2%); the minimum indicators are in the Chechen Republic (23.5%), in the Republic of Altai (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.

At present, the process of urbanization is going on more and more intensively - the spread of urban forms and living conditions to the countryside. In the broad sense of the word, urbanization is an integral part of urbanization.

Rural population Russia is 27%.

Share of urban and rural population by economic regions

The location of rural settlements depends on natural and geographical factors, primarily on soil and climatic conditions. Most high concentration rural population in the North Caucasian (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 affects the increase in mortality and the reduction medium duration life (Table 5.4).

Table 5.5.

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Average chronological

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

3.3. Share of urban population in total population1)

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

Depending on the type of time series, various methods of its calculation are used, namely, the calculation of the average chronological interval series and the average chronological moment series.

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

where is the average level of the series;

- the level of a series of dynamics;

- the number of members of the series

For example, consider data on children's health facilities in Pskov and the region.

Table. Children's health institutions

The studied series is an interval one, using the chronological average formula, we can calculate the average number of health facilities:

institutions.

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

However, as a rule, there are no data on continuous observation of the value at the disposal of statistics. Therefore, depending on the nature of the change in the indicator and the available data, various methods calculation.

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

where is the level of the series;

is the number of all members of the series;

- average level.

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

where is the time during which the given level of the series remained unchanged.

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The 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 close connection with their qualitative content in specific conditions of place and time

the main tasks of SES.

1. Statistical observation of 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 formation of savings; use of savings for accumulation).

Population placement 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 of national wealth, characteristics of the labor market, economic growth rates, labor productivity growth rates, price indices and inflation rates, deficit (surplus) of the state budget, level of public debt, etc.).

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

5. Analysis of trends, patterns throughout the country and individual regions (decrease in the death rate, growth in the birth rate, dynamics of the level of employment and unemployment, dynamics of the inflation rate, growth in labor productivity and consumer prices, dynamics of the level poverty, 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 of material costs and energy intensity, profit growth and reduction of unprofitable production, growth in labor productivity and average wages, rising producer prices, etc.).8

6. Improvement of systems of indicators that characterize socio-economic phenomena and processes, classifications (classifiers), their consistency and interconnection, methods for evaluating individual indicators.

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

8. Providing authorities government controlled demanded information on the socio-economic development of the country and its regions for taking measures to reduce their intensity).

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

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

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

12. Introduction of new technologies for the collection, processing, transmission and dissemination of statistical information, etc.

Methods for calculating the average annual population.

the choice of the method of its calculation depends on the initial data.

1. If data are available at the beginning (S1) and the end of the period (S2), then the average population is determined by the simple arithmetic mean formula:

3. If the intervals between the dates are not equal, then the calculation by 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 groupings which is carried out on:

the social composition

areas of activity and sectors of the economy,

professions

age,

marital status,

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Chapter 3

Axes and planes of the human body - The human body consists of certain topographic parts and areas in which organs, muscles, blood vessels, nerves, etc. are located.

Wall trimming and jamb cutting - When the house lacks windows and doors, a beautiful high porch is still only in the imagination, you have to climb the stairs from the street into the house.

Second Order Differential Equations (Price Forecast Market Model) - In simple market models, supply and demand are usually assumed to depend only on the current price of a good.

population statistics, formulas for their calculation

Basic concepts and indicators

Basic concepts of demographic statistics
Census	Demographic qualification, designed to characterize the demographic situation in the country. In Russia, continuous population censuses were conducted in 1920, 1926, 1939, 1959, 1970, 1979, 1989 and 2002.
Microcensus	Conducted between population censuses, usually covers 5% of the population (for example, the census in Russia in 1994)
Age-sex pyramids	Graphic image that allows you to visually display the age and sex composition of the population
Vital movement of the population	Population change due to births and deaths
Natural increase (decrease) of the population	Positive (negative) difference between the number of births and deaths: , where N- the number of births; M- number of deaths
Mechanical increase (decrease) of the population (balance of migration)	Positive (negative) difference between the number of arrived and departed population: , where P IN
Migration	The movement of people (migrants) across the borders of territories with a change of residence forever or for a certain time. Migration can be internal and external
Internal migration	Movement of population within a certain territory
External migration	Movement of population across territorial 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 a population into a particular area or country
Emigration	Departure of the population from a given area or country

Continuation of the table. 3.1

Population indicators (categories) in censuses
Current population (HH)	Category of the population that unites people actually located at the time of the census in this locality: NN \u003d PN - VO + VP, where Mon- permanent population IN- temporarily absent; VP - temporary residents
Permanent population (PN)	A category of the population that unites people for whom this settlement represents their place of usual residence, regardless of their actual location at the time of registration (census): PN \u003d NN - VP + VO
Temporarily absent (VO)	These are persons who have a permanent place of residence in this locality, 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 this 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- the number of deaths; P- the number of arrivals in this settlement; IN- the number of those who left the given settlement
Average annual population	For a certain date for equal periods is calculated by the formula , where n– number of levels (dates); S 1… P is the population at a certain date. At the beginning and end of the year is defined as the arithmetic mean: , where S n.g– population at the beginning of the year; S k.g is the 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

The end of the table. 3.1

Among the many parameters characterizing the properties of materials, there is one such as specific gravity. Sometimes the term density is used, but this is not entirely true. But one way or another, both of these terms have their own definitions and are used in mathematics, physics and many other sciences, including materials science.

Specific Gravity Determination

The physical quantity, which is the ratio of the weight of a material to the volume it occupies, is called the HC of the material.

Materials science of the 21st century has gone far ahead and has already mastered technologies that were considered science fiction just a hundred years ago. This science can offer modern industry alloys that differ from each other in qualitative parameters, but also in physical and technical properties.

To determine how a certain alloy can be used for production, it is advisable to determine the HC. All items made with the same volume, but different types of metals were used for their production, will have a different mass, it is in a clear relationship with the volume. That is, the ratio of volume to mass is a certain constant number characteristic of this alloy.

To calculate the density of the material, a special formula is used that has a direct relationship with the HC of the material.

By the way, the HC of cast iron, the main material for creating steel alloys, can be determined by the weight of 1 cm 3, reflected in grams. The more HC metal, the heavier the finished product will be.

Specific Gravity Formula

The formula for calculating HC looks like the ratio of weight to volume. To calculate the SW, it is permissible to apply the calculation algorithm, which is set out in the school physics course.
To do this, it is necessary to use the law of Archimedes, or rather the definition of the force that is buoyant. That is, a load with a certain mass and at the same time it rests on the water. In other words, it is influenced by two forces - gravity and Archimedes.

The formula for calculating the Archimedean force is as follows

where g is the SW of the fluid. After the substitution, the formula takes the following form F=y×V, from here we obtain the formula for the SW load y=F/V.

The difference between weight and mass

What is the difference between weight and mass. In fact, in everyday life, it does not play any role. Indeed, in the kitchen, we do not develop between the weight of the chicken and its mass, but between these terms there are serious differences.

This difference is clearly visible when solving problems related to the movement of bodies in interstellar space and not related to our planet, and under these conditions these terms differ significantly from each other.
We can say the following, the term weight has meaning only in the zone of action of gravity, i.e. if an object is located near a planet, star, etc. Weight can be called the force with which the body presses on an obstacle between it and the source of attraction. This force is measured in newtons. As an example, we can imagine the following picture - there is a plate next to the paid education, with a certain object located on its surface. The force with which the object presses on the surface of the plate and will be the weight.

The mass of a body is directly related to inertia. If we consider this concept in detail, then we can say that the mass determines the size of the gravitational field created by the body. In fact, this is one of the key characteristics of the universe. The key difference between weight and mass is that mass is independent of the distance between the object and the source of the gravitational force.

Many quantities are used to measure mass - a kilogram, a pound, etc. There is an international SI system in which kilograms, grams, etc., which are familiar to us, are used. But besides it, many countries, for example, the British Isles, have their own system of measures and weights, where weight is measured in pounds.

Difference Between Specific Gravity and Density

UV - what is it?

Specific gravity is the ratio of the weight of matter to its volume. In the international SI measurement system, it is measured as a newton per cubic meter. To solve certain problems in physics, hydrocarbons are determined as follows - how much the substance being examined is heavier than water at a temperature of 4 degrees, provided that the substance and water have equal volumes.

For the most part, such a definition is used in geological and biological research. Sometimes, the SW calculated by this method is called relative density.

What are the differences

As already noted, these two terms are often confused, but since the weight is directly dependent on the distance between the object and the gravitational source, and the mass does not depend on this, therefore the terms SW and density differ from each other.
But it must be taken into account that, under certain conditions, mass and weight may coincide. It is almost impossible to measure HC at home. But even at the level of a school laboratory, such an operation is quite easy to perform. The main thing is that the laboratory should be equipped with scales with deep bowls.

The item must be weighed under normal conditions. The resulting value can be designated as X1, after which the bowl with the load is placed in water. In this case, in accordance with the law of Archimedes, the cargo will lose part of its weight. In this case, the yoke of the scales will warp. To achieve balance, a weight must be added to the other bowl. Its value can be designated as X2. As a result of these manipulations, the SW will be obtained, which will be expressed as the ratio of X1 and X2. In addition to substances in the solid state, specific ones can also be measured for liquids and gases. In this case, measurements can be performed under different conditions, for example, when elevated temperature environment or low temperature. To obtain the desired data, instruments such as a pycnometer or a hydrometer are used.

Specific Gravity Units

In the world, several systems of measures and weights are used, in particular, in the SI system, hydrocarbons are measured in the ratio of N (Newton) to a cubic meter. In other systems, for example, the CGS, specific gravity uses such a unit of measurement d (dyn) to a cubic centimeter.

Metals with the highest and lowest specific gravity

In addition to the fact that the concept of specific gravity, used in mathematics and physics, exists and quite Interesting Facts, for example, about specific gravity metals from the periodic table. if we talk about non-ferrous metals, then gold and platinum can be attributed to the most “heavy” ones.

These materials exceed in specific gravity such metals as silver, lead and many others. The "light" materials include magnesium with a weight lower than that of vanadium. We must not forget radioactive materials, for example, the weight of uranium is 19.05 grams per cubic cm. That is, 1 cubic meter weighs 19 tons.

Specific gravity of other materials

Our world is hard to imagine without many materials used in production and everyday life. For example, without iron and its compounds (steel alloys). The HC of these materials fluctuates in the range of one or two units and these are not the highest results. Aluminum, for example, has a low density and low specific gravity. These indicators allowed it to be used in the aviation and space industries.

Copper and its alloys have a specific gravity comparable to lead. But its compounds - brass, bronze are lighter than other materials, due to the fact that they use substances with a lower specific gravity.

How to Calculate the Specific Gravity of Metals

How to determine HC - this question often arises among specialists employed in heavy industry. This procedure is necessary in order to determine exactly those materials that will differ from each other with improved characteristics.

One of the key features of metal alloys is what metal is the basis of the alloy. That is, iron, magnesium or brass, having the same volume, will have a different mass.

The density of the material, which is calculated on the basis of a given formula, is directly related to the issue under consideration. As already noted, SW is the ratio of body weight to its volume, we must remember that this value can be defined as the force of gravity and the volume of a certain substance.

For metals, hydrocarbons and density are determined in the same proportion. It is permissible to use another formula that allows you to calculate the SW. It looks like this: SW (density) is equal to the ratio of weight and mass, taking into account g, a constant value. It can be said that the hydrocarbon of a metal can, is called the weight of a unit volume. In order to determine the HC, it is necessary to divide the mass of dry material by its volume. In fact, this formula can be used to get the weight of the metal.

By the way, the concept of specific gravity is widely used in the creation of metal calculators used to calculate the parameters of rolled metal. different type and appointments.

The HC of metals is measured under qualified laboratory conditions. In practice, this term is rarely used. Much more often, the concept of light and heavy metals is used, metals with a low specific gravity are classified as light, respectively, metals with a large specific gravity are classified as heavy.

Biysk was located near the Altai Mountains and its minerals. 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 especially favorably influenced by the proximity to Baikal, the presence of rich hunting grounds and fertile lands, as well as deposits of salt and iron.
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. There were offices of gold miners, workers were hired, supplies and tools were prepared, commission agents, contractors associated with the mines acted. Cities experienced periodic influxes of mining people. For example, in the official report on Chita in the middle of the 19th century, it was noted: “There is a large confluence of workers in the city in the autumn, precisely in October, after the workers leave the mines, but they are immediately hired again at the gold mines and their smallest number remains in Chita. ". It was gold, before running out, that built and adorned these cities. In the development of the urban economy, under the influence of gold mining, the intensification of construction activities began. Capital began to flow here, the population began to arrive and vigorous trade rushed. However, the same gold industry led to the complete decline of handicraft production in Yeniseisk. The city turned into a supply center for taiga mines. Wealthy citizens furnished their houses beautifully. But even today we have a lot of options on how to create comfort in the house. For example, you can buy glossy furniture for your rooms. Even the provincial Krasnoyarsk, despite the fact that it was the seat of many gold miners and the center of management of the fields, over the years was decorated with only "a few churches and private buildings, but far from received the development that could be expected from the confluence of favorable circumstances."
The gold mining industry caused a new upsurge in practical research on the territory of Siberia. Simultaneously with the search for gold, there was an accumulation of information about the presence of other natural resources. In the taiga regions, remote from the established framework of settlement, numerous mining settlements were formed, which were connected by a new network of roads with the central settlements of the regions. At this stage of the formation of a network of settlements, simultaneously with the process of accumulating 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 strip of settlement to the hinterland.
The proportion of 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.

Page 1

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

The entire population of the city is divided into three structural groups: city-forming, serving and non-amateur. The population of the city is calculated according to the labor balance method; it is defined as a function of the prospective number of personnel employed at enterprises, institutions of city-forming significance and their proportion in the composition of the urban population. The calculation is made according to the formula:

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

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

a is the proportion 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 task.

The proportion of the city-forming and service groups of the population 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 taken at least 40% for the first stage of construction and at least 35% for the estimated period. The proportion of the city-forming group of settlements located in the climatic regions ΙΑ, 1B and II should be taken at least 50% for the first stage of construction, and for the estimated period - no more than 40% of the design population.

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

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

δ - specific weight of the service group, %.

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

b - proportion of non-amateur group, %.

Building codes and regulations recommend that the share of service groups be taken within 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, respectively, 15-17% and 19-22%.

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

The results of the performed calculations should be summarized in the table of the project balance of the city's population according to the form below.

Table 1. Project balance of the city's population

Example. It is required to determine the design size of the city.

Initial data. The construction area is located in the IIIΒ climatic zone (Volgograd). The number of city-forming personnel is: for the 1st stage of construction - 21 thousand people, for the estimated period - 47 thousand people.

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

where N1 is the design population of the city at the first stage of construction;

Νρ - project population of the city for the estimated period.

The proportion of the serving group of the population should be taken at the 1st stage of construction 17%, and for the estimated period - 22%. The number of the serving group, according to formula (2), is equal to:

where B; - the design number of the service group of the population at the first stage of construction;

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

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

Table 5.4.

Population placement indicators

Data on the share of the urban population on an international scale are not comparable due to different ways his selection. For example, when applying the population qualification, this qualification ranges from several hundred inhabitants to 30,000 (in Japan).

The development of cities and their connections with the surrounding area raised the question of isolating an even larger unit, the so-called urban agglomeration- the city center and adjacent small towns and villages. Usually their boundaries are set individually. In general, each settlement can be considered as part of the agglomeration, a certain part of the economically active population of which is employed in the central city.

The ratio between the population and the territory it occupies measures density(or density) of the population. These are the number of inhabitants (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 to attribute the population to - to the inhabited territory or to the entire land density. Russian demography excludes large inland waters, such as Lake Baikal, from the territory.

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

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

An analysis of demographic facts convinces us that their explanation should be sought in laws public life. In the complex intertwining of factors influencing the movement of the population, 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 individual people largely through their conscious will.

Of all economic conditions, one should first of all keep in mind belonging to one or another social stratum. A different attitude towards property, a different nature of the sources of income determines a different attitude towards the issues of family, marriage, childbearing, puts in different conditions regarding mortality. Further, great importance has an income that is associated with social class and at the same time varies greatly within each social class. An important factor influencing the movement of the population is housing conditions. Employment is closely related to the level of well-being, incomes and their structure. At the same time, demographic phenomena are influenced not only by the employment of these individuals themselves, but also by 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 that characterize the measure of satisfaction of the basic vital needs of people." In other words, the standard of living is the degree of development and satisfaction of the needs of a person living in society. Satisfaction of needs is determined by the level of utility of the consumer set. Thus, theoretically, a change in standard of living means moving the consumer to a higher or lower indifference curve.

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

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

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 particular 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.

For indicators used on practice, can be attributed to:

1/ macroeconomic cost aggregates

The volume of gross domestic product,

national income,

Net national disposable income;

2/ demographics

infant mortality rate,

life expectancy at birth,

3/ free time

One of the main shortcomings of the listed cost generalizing 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 expenditures for the maintenance of the army, the state apparatus, etc.). In addition, as noted in modern studies, an increase in GDP and related indicators can be obtained due to the deterioration of the quality of the environment, which in developed countries is the most important component of the quality of life.

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 was based on the well-known statement of K. Marx that the time used for leisure, study, self-education, sports, etc., will become a measure of social wealth in the future. However, modern statistics do not provide constant monitoring of this indicator; its study is possible only with the help of periodically specially organized sample surveys.

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

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

pensioners, students, etc.). To calculate the index, the value 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 the change in the standard of living as the influence of one factor on it - consumer prices. In addition, the use of a 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 foregoing, it follows that the indicators of the standard of living used in practice focus on the quantitative or qualitative assessment of any one aspect of the welfare 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 experts from the United Nations Development Program (UNDP). The HDI is a composite index that includes the most important components of the standard of living:

Life expectancy at birth;

Achieved level of education;

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

The HDI is defined as the arithmetic average of the indexes 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, the minimum value is assumed to be 25 years, and the maximum value is 85 years.

The Educational Achievement Index is calculated as the arithmetic weighted average of two sub-indices: the Adult Literacy Index (aged 15 and over) weighing 2/3 and the Index of Primary, Secondary and Tertiary Aggregate Enrollment (for those under 24) weighing 1/3. The limit values ​​for both shares are 0 and 100%.

The method for calculating the index of real GDP per capita is somewhat more complicated. Real GDP, calculated in US dollars on a purchasing power parity basis, 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 for reasonable 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 assumption that the significance of higher income sharply decreases. An approach that changes the performance of only some countries cannot be called objective, moreover, the discounting method used had too strong a downward effect on income.

In 1999, the methodology was improved. Now a single approach is applied to all income indicators, and the calculation of the GDP index (I) is carried out according to the following formula:

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

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

The revision of the methodology does not allow for direct comparison of the values ​​of the indices given in the last report of the United Nations Development Program, published in 1999, with previous periods. Nevertheless, an analysis of trends in economic growth rates and the 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 top three places in terms of human development (out of 174 countries for which the Human Development Index is calculated) were occupied by Canada, Norway and the United States, and the last places in the list were Ethiopia, Niger and Sierra Leone, which three times lower than in the countries of the top ten.

It should be noted that the relationship between the income level of a society and the development of its human potential is not automatic. For 77 of the 174 countries surveyed, the GDP per capita 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 of the countries studied (92 out of 174), the HDI ranking was higher than the GDP ranking. This shows that increasing the cost of human development is becoming a priority for the development of the world economy. At the same time, 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, ranking 71st. The HDI rating was eight positions higher than the real GDP rating. According to the index of the level of education of the population, our country was approaching 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 countries former USSR Russia was ahead of Estonia, Belarus and Lithuania (54th, 60th and 62nd places respectively).

More detailed information about the economic and social development Russia in comparison with other countries of the world are given in table 5.5.

Table 5.5.

The main indicators of the standard of living of the population

The methodology for calculating the HDI, as well as a generalized assessment of the standard of living, remains debatable. The issues of selection of indicators, the values ​​of weight coefficients, as well as the very necessity 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 generalizing indicator of the standard of living on the basis of particular indicators.

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

The 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 the 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 applied for stimulating indicators (such as life expectancy) and the reverse order for destimulating indicators (for example, infant mortality rates, the number of accidents, etc.) . By assigning ranks for individual indicators, they find the average rank for their totality. The lower its value, the more developed the country or region in terms of the characteristics under consideration.

To disadvantages this method refers to the mechanical connection of the initial indicators, as well as the fact that the resulting average ranks do not reflect the actual distance between the objects of study. In this sense, ordering by the values ​​of principal components or principal factors is preferable. In addition to the above methods, for a generalized assessment of the standard of living, one can also use synthetic indexes, built on the basis of standardized value of the initial indicators. In this case, standardization is performed 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 by all indicators occurs in relation to a certain sample, and all indicators act as equivalent.

Demographics are significantly affected by poverty rate population, which is currently regarded as a complex multifaceted phenomenon and is not associated only with the level of well-being.

The problem of measuring poverty currently does not descend from the pages of economic publications, not only in developing countries, but also in industrialized countries. The strengthening of the processes of globalization of the world economy is accompanied by an increase in inequality in the distribution of income and the spread of poverty.

The traditional definition of poverty based on income levels does not allow for international comparisons of national levels and incidences of poverty. In 1990, the World Bank set a single poverty line for all developing countries at $1 a day (purchasing power parity in 1985 prices). According to World Bank experts, this amount was sufficient to purchase the minimum amount of food needed for one person for one day. For comparison: in the mid-90s, the daily average income of each inhabitant of the planet was 16 dollars.

As important as it is, an income-only approach to measuring poverty is not sufficient. Poverty is multifaceted and qualitative. That is why in 1997 the UN Development Program experts 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 life expectancy is less than 40 years); access to knowledge is measured by the proportion of illiterates in the adult population; material living conditions are assessed using the following three indicators: the proportion of the population without access to health care; proportion of the population without access to drinking water; proportion of children under five who are malnourished. 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

(in % 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 of the developing world are shown in Table 5.7.

Table 5.7.

Per capita income and NPI indicators

for selected developing countries in 19947

As Table 6 shows, in most countries there is a fairly strong correlation between per capita income and NPI. 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 MPI in some of them sometimes approaches that of individual African countries. This is due to the fact that in the mid-1990s the proportion of illiterates among the adult population was 43%. Latin America is characterized by a rather low level of sanitary and hygienic conditions, since here the proportion of residents without access to health care is 30%; only in sub-Saharan Africa, where 47% of the population does not have access to such services, the situation is worse in this regard.

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

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

Ibid, p. 62-63.

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

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

Demography Course: Textbook / Pod. ed. prof. Boyarsky A.Ya. - M.: Statistics, 1967, p.64-66.

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

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

Combined application of censuses and sample surveys. Series: Methodology of Selective Research. 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 of 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 of NGAEiU, M.: INFRA - M, 1999, p. 201.

Andreev E.M., Bondarskaya G.A. Can 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 of 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 of 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 of NGAEiU, M.: INFRA-M, 1999, p. 197..

There. S. 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 of NGAEiU, M.: INFRA-M, 1999, p. 207-208..

There. pp. 206-210.

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

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

Demography Course: Textbook / Pod. 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 of NGAEiU, M.: INFRA-M, 1999, p. 211.

Demography Course: Textbook / Pod. 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 of NGAEiU, M.: INFRA-M, 1999, p. 212.

Demography Course: Textbook / Pod. 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 of NGAEiU, M.: INFRA - M, 1999, pp. 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 of NGAEiU, M.: INFRA - M, 1999, p. 250.

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

Demographic aging of the population Russian Federation(Based on the materials of 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 of 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. The human development index and other indicators of the socio-economic development of Russia and certain 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. About indicators of poverty / Questions of statistics, 2000, No. 3, p.24.

Zubchenko L.A. About poverty indicators / Questions of statistics, 2000, No. 3, p.25.

Purchasing power parity of currencies