Bachelor
Syktyvkar State University named after Pitirim Sorokin
Scientific supervisor: Nekrasova Galina Andreevna, senior lecturer of the Department of Financial Management, SSU named after. Pitirim Sorokin. Orlova Valeria, Pimankina Anna, Polyakova Anastasia, Razmyslova Maria, students of the Institute of Economics and Finance of SSU named after. Pitirim Sorokina
Annotation:
This article discusses the main indicators that influence the dynamics of the population of the Komi Republic. The population structure of the Komi Republic and the Russian Federation for 2013-2017 is compared. Using correlation and regression analysis, a study is carried out of factors that have a direct impact on the population dynamics of the region. Based on the analyzed data, problems associated with an increase or decrease in population are identified. Several solutions are outlined for each of the problems based on expert assessments. The main methods of demographic forecasting are analyzed, from which the most optimal one is selected. A forecast is being made for the further dynamics of the population of the Komi Republic based on the extrapolation method.
This article considers key indicators which affect the dynamics of population of the Komi Republic. The structure of population of the Komi Republic is compared to structure of population of the Russian Federation for 2013-2017. The research of factors which makes direct impact on the dynamics of population of the region is conducted by means of the correlation and regression analysis. Problems which are connected with increase or reduction of population are allocated on the basis of the analyzed data. Several solutions are designated on each of problems on the basis of expert estimates. The main methods of demographic forecasting are analyzed, the most optimum gets out of them. The forecast of further dynamics of population of the Komi Republic is under construction on the basis of an extrapolation method.
Keywords:
Population; population analysis; Komi Republic; migration; natural growth; unemployment rate; incidence rate; natural decline; forecasting methods; population forecasting; demographic forecasting
population; analysis of population; Komi Republic; migration; natural increase; unemployment rate; incidence; natural losses; forecasting methods; forecasting of the population; demographic forecasting
UDC 332.1
Introduction
Demographic processes underlie many long-term trends that determine stable socio-economic development and national security of the country. Recently, depopulation has become one of the most significant social problems in the republic: the total population is constantly decreasing. According to the 2018 population census, about 40 towns and villages of the Komi Republic were left without inhabitants. Over the 10 years from 2007 to 2017, the permanent population of Komi decreased by 89 thousand people, the outflow of population from the republic is mainly due to migration, and in recent years there has been a decrease in natural population growth.
From time immemorial, the region was sparsely populated, but during the Soviet period the number of inhabitants began to grow rapidly. According to Rosstat, at the beginning of 2018, 840,788 people made up the population of Komi. The republic has an area of 416,774 square kilometers. Of these, 7.7% are swamps and 1.5% are water, that is, non-residential surface. Thus, the average population density of the Komi Republic is 2.02 people per square meter. km. For comparison: the region ranks 13th in the country in terms of area. However, in terms of the number of inhabitants, Komi is only 16th. There is only one city in the Republic with a population of more than one hundred thousand people.
The purpose of the work is to forecast the population of the Komi Republic.
The following tasks follow from this goal:
The object of the study is the population of the Komi Republic.
The subject is an analysis of the population of the Komi Republic.
The methodological basis of the study is provided by official statistics from Komistat and Rosstat, government programs, materials on the Internet, as well as materials from periodicals, the main one of which was: “Population dynamics in the Komi Republic” by A.S. Shiryaeva and A.R. Mikhailova.
The research methods are analysis and synthesis, mathematical method, comparative analysis method, grouping and methods of tabular and graphical presentation of information, study of literature and documents, extrapolation method.
1. Data analysis
Table 1.1 presents indicators that have a direct impact on changes in the value of the indicator selected in the project work.
Table 1.1 - Pindicators characterizing changes in numbers
Indicators / Year |
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Unemployment rate (%) |
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We can conclude that, in general, the population in the Komi Republic has been decreasing throughout the entire period, from 2007-2017. Thus, the greatest influence is exerted by such factors as: the rate of general morbidity of the population (an increase is observed) and the number of health care institutions (decreasing every year). But other indicators are also quite important, for example, the unemployment rate, which increases rapidly from 2014 to 2017.
The growth rates of indicators are presented in Table 1.2.
Table 1.2 - Growth rate, %
Indicators / Year |
2008/2007 |
2009/2008 |
2010/2009 |
2011/2010 |
2012/2011 |
2013/2012 |
2014/2013 |
2015/2014 |
2016/2015 |
2017/2016 |
Population in the Republic of Kazakhstan (persons) |
||||||||||
Natural increase, decrease (-) per 1000 people. |
||||||||||
General morbidity rate of the population (per 1000 people) |
||||||||||
Number of state healthcare institutions of the Republic of Kazakhstan |
||||||||||
Number of state educational institutions of the Republic of Kazakhstan |
||||||||||
Migration loss (total people) |
||||||||||
Unemployment rate (%) |
||||||||||
Average price of 1 sq.m. total area of apartments on the housing market (RUB) |
Let's look at each indicator separately:
1. Natural increase/decrease per 1000 people. - from 2007 to 2010 the population decreases. The growth rate is -4.5%. Then from 2011 to 2012 the number increases and the growth rate is 1.57%. In the period from 2012 to 2013, the number again decreases, the growth rate is 0.22%. From 2013 to 2016, the population continues to fall and the growth rate is -1.43%.
2. Indicator of general morbidity of the population (per 1000 people) - from 2010 to 2017, the number of morbidity increases from year to year.
3. Number of state healthcare institutions of the Republic of Kazakhstan - judging by the data, the number of institutions decreases from year to year. In 2008 there were 113, but by 2017 there were 82.
4. The number of general education institutions of the Republic of Kazakhstan - in 2008 this figure was 475 institutions, in 2016 their number decreased to 352.
5. Migration decline - based on the results of 2016, a decrease in the migration decline of the population was noted in the Komi Republic. In January-March, the migration population loss amounted to 1,337 people. 8,761 people left the region. 7,424 people arrived. During the same period last year, the region’s migration losses amounted to 2,109 people.
6. The unemployment rate - from 2007 (12.3%) to 2012 (6.7%) decreases, then in 2013 it increases by 0.5%. In 2014, it again decreases by 0.9%, and in subsequent years it increases to 12.6%.
7. Average price of 1 sq.m. total area of apartments on the housing market (rub.) - from 2007 to 2010, price per 1 sq.m. the total area of apartments is reduced by 3374.7 rubles. From 2011 to 2014, the price increases to 60,945.7 rubles, and then by 2017 it decreases again to 47,482.4 rubles.
As we can see, all the main indicators that can affect the population in the Republic of Kazakhstan are decreasing, therefore, for these reasons, the population itself is decreasing.
2. Comparative analysis, building a regression model
2.1 Analysis of the population structure of the Komi Republic
Indicators of the population structure of the Komi Republic and their comparison with the average values for Russia over 5 years are presented in Table 2.1.
Table 2.1 - Structure of selected indicators of the Republic of Kazakhstan and the Russian Federation (persons)
Indicators / Year |
|||||
Population in the Republic of Kazakhstan |
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Population in the Russian Federation |
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Men in the Republic of Kazakhstan |
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Men in the Russian Federation |
|||||
Women in the Republic of Kazakhstan |
|||||
Women in the Russian Federation |
|||||
Below working age in the Republic of Kazakhstan |
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Below working age in the Russian Federation |
|||||
Working age in the Republic of Kazakhstan |
|||||
Working age in the Russian Federation |
|||||
Over working age in the Republic of Kazakhstan |
|||||
Over working age in the Russian Federation |
|||||
Urban population in the Republic of Kazakhstan |
|||||
Urban population in the Russian Federation |
|||||
Rural population in the Republic of Kazakhstan |
|||||
Rural population in the Russian Federation |
The population in the Republic of Kazakhstan is decreasing, including both men and women, while in the Russian Federation as a whole there is an increase in population, which is associated with rising unemployment, high housing prices and population migration to other cities.
The population younger and older than working age in both the Republic of Kazakhstan and the Russian Federation is increasing. This is due to the fact that natural population growth is negative; in the Republic of Kazakhstan, since 2013, there has been a gradual decrease in this indicator (mortality exceeds birth rate). This may be due to the fact that the incidence in the Republic of Kazakhstan and the Russian Federation is increasing every year, while the number of state. healthcare and educational institutions are decreasing from year to year.
The Komi Republic's working-age population is declining as unemployment rises and people migrate to larger cities in search of work. In Russia as a whole, the working-age population is also decreasing, perhaps due to the fact that the birth rate is low and the population is aging, moving into the group older than working age.
The urban population of the Komi Republic is decreasing, this is due to the outflow of the population to other constituent entities of the Russian Federation, which are more developed and where there will be opportunities to find work, so the urban population in Russia is increasing. But the rural population, both in the Republic of Kazakhstan and in the Russian Federation, is decreasing, since there is no work in the villages (various factories, combines, etc. are closing).
To analyze factors that have a direct impact on population changes, we conducted a correlation and regression analysis.
Y - Population in the Republic of Kazakhstan (persons)
X1 - Natural increase, decrease (-) per 1000 people
X2 - General morbidity rate of the population (per 1000 people)
X3 - Number of state healthcare institutions of the Republic of Kazakhstan
X4 - Number of state. educational institutions of the Republic of Kazakhstan
X5 - Migration loss (total people)
X6 - Unemployment rate (in%)
X7 - Average price of 1 sq.m. total area of apartments on the housing market (RUB)
Figure 2.1 Correlation matrix
After conducting a correlation analysis, we can draw the following conclusions:
We observe a strong direct linear relationship between the population and: the number of state. healthcare institutions of the Republic of Kazakhstan and the number of state. general educational institutions of the Republic of Kazakhstan. There is a strong inverse linear relationship between population size and: natural increase, the rate of general morbidity of the population and the average price of 1 sq. m of total area of apartments in the housing market. A weak linear relationship is observed between population size and unemployment rate.
Building models:
y^ = 712067.45 - 1655.95 x1 - 9.16 x2 + 804.92 x3 + 275.28 x4 - 1.29 x5 +93.06 x6 - 0.23 x7
Fstat. > Fcr., in general the equation is statistically significant at α = 5%
R^2 = 99.5% Therefore, we can talk about a fairly strong linear relationship between the variables and a strong influence in general on the population size on average of selected exogenous variables.
We exclude (since they correlate):
2) x4 (Number of state educational institutions of the Republic of Kazakhstan)
3) x6 unemployment rate
Include:
2) X3 - Number of state. healthcare institutions of the Republic of Kazakhstan
3) X5 - Migration loss (total people)
4) X7 - Average price of 1 sq.m. total area of apartments on the housing market (RUB)
We get:
y^= 806574.3 - 18.047 x2 + 1031 x3 - 4.024 x5 - 0.52 x7
Fstat. >
R^2 = 99.1% Therefore, we can talk about a fairly strong linear relationship between the variables and a strong influence in general on the population size on average of selected exogenous variables.
We exclude:
1) x2 (General morbidity rate of the population per 1000 people)
3) x5 (Migration loss of total people)
4) x6 (Unemployment rate%)
Include:
1) X1 - Natural increase, decrease (-) per 1000 people
2) X4 - Number of state. educational institutions of the Republic of Kazakhstan
3) X7 - Average price of 1 sq.m. total area of apartments on the housing market (RUB)
We get:
y^= 657791.1 - 2803.68 x1 + 604.86 x4 - 0.343 x7
Conclusions:
Fstat. > Fcr., in general the equation is statistically significant at α = 5%.
R^2 = 98.8% Therefore, we can talk about a fairly strong linear relationship between the variables and a strong influence in general on the population size on average of selected exogenous variables.
We exclude:
1) x1 (Natural increase, decrease (-) per 1000 people)
2) x3 (Number of state healthcare institutions of the Republic of Kazakhstan)
3) x4 (Number of state educational institutions of the Republic of Kazakhstan)
4) x7 (Average price of 1 sq.m. of total area of apartments on the housing market (RUB)
Include:
1) X2 - General morbidity rate of the population (per 1000 people)
2) X5 - Migration loss (total people)
3) X6 - Unemployment rate (in%)
We get:
y^= 803806.9 - 19.135 x2 - 9.708 x5 + 2645.43 x6
Conclusions:
Fstat. > Fcr., in general the equation is statistically significant at α = 5%.
R^2 = 96.57% Therefore, we can talk about a fairly strong linear relationship between the variables and a strong influence in general on the population size on average of selected exogenous variables.
3. Justification of possible directions for solving the problem. Making forecasts
3.1 Problems related to the population of the Komi Republic and ways to solve them
Based on the analysis carried out and the indicators we studied that affect the population of the Komi Republic, the following problems were identified:
Since unemployment is a serious macroeconomic problem and is an indicator of macroeconomic instability, the state is taking measures to combat it.
Having analyzed the opinions of various experts (Kashepov A., Safarov P.M., Gryaznova, A.G., Ishkin, V.V., etc.), we propose the following solutions to reduce the unemployment rate:
A problem such as housing affordability can only be solved with the help of the state. For example, to increase the affordability of housing and the quality of housing provision for the population, as well as to improve the quality and reliability of the provision of housing and communal services to the population, the state program of the Russian Federation “Providing affordable and comfortable housing and communal services to citizens of the Russian Federation” was created.
So with the help given by the state. The program will increase the annual volume of housing commissioned by 2025, reduce the average market value of housing, and achieve a level of housing stock that meets all requirements.
To reduce the level of population migration from the Republic. Komi to other cities of Russia you need the following:
Morbidity in the Republic Komi is increasing every year, perhaps this is directly related to climatic conditions, but also to the level of timely diagnosis of diseases.
First of all, it is necessary to carry out timely clinical examination of the population, which is a set of measures, including a medical examination by doctors of several specialties and the use of the necessary examination methods carried out in relation to certain groups. The Ministry of Health of the Russian Federation carries out medical examinations in Russia once every 3 years as the age stipulated by the medical examination procedure approaches.
The next stage on the path to reducing morbidity is timely diagnosis of diseases.
There is a state program of the Komi Republic “Health Development” for 2013-2020. The goal is to ensure accessibility of medical care and increase the efficiency of medical services, the volumes, types and quality of which must correspond to the level of morbidity and the needs of the population of the Komi Republic, and to the advanced achievements of medical science.
Such a problem as reducing the number of government. healthcare and education institutions should be decided at the state level, the allocation of funds to open new institutions or maintain existing ones.
3.2 Methods for forecasting the population of the Komi Republic
Forecasting methods are a major component of demographic forecasting. Depending on how correctly a particular forecasting method is chosen, the level of accuracy of the demographic forecast depends.
The main methods of demographic forecasting are: methods based on the use of a certain mathematical function (extrapolation and analytical methods), as well as the method of moving ages, or the component method.
1. Methods based on the use of mathematical functions
Typically, such methods are used when forecasting the population of small areas (for example, regions of a country), since the likelihood of errors due to not taking into account changes in the components of population growth and in the age-sex structure can be reduced by the additional condition that that the total population of the regions should not differ from the forecast results for the country as a whole.
That is, the main disadvantage of these methods is that they only provide a forecast of the total population.
A variety of mathematical functions can be used to make predictions. The most commonly used functions are linear, exponential and logistic functions. At the same time, forecasting based on the use of linear and exponential functions is sometimes purely conventionally called extrapolation method, and forecasting based on the use of logistic and other functions - analytical method.
The extrapolation method is based on the direct use of linear and exponential functions, i.e. data on average annual absolute changes in population for a period or on average annual growth or increment rates. If these indicators are known, then it is possible to calculate the population size for any number of years in advance, simply by assuming that they remain unchanged throughout the entire forecast period.
That is, this method is one of the simplest methods of forecasting, since it is based on the assumption that the average annual absolute population growth calculated for the reporting period will continue in the future.
In other words, in this case, for future calculations, we use linear function:
P t = P 0 + a cf * t
where P t is the projected population level;
P 0 - basic population level;
ар - absolute average annual population growth;
t - forecasting period.
The disadvantage of this method is that the average annual absolute growth rate can remain unchanged only for a short time, so population forecasting using the specified linear function can only be used in short-term forecasts.
Also when using this method it can be used exponential function. The mathematical model in this case will look like:
P t = P 0 * e kt
where e is the base of the natural logarithm (2.7183).
The use of an exponential function is more preferable than a linear function, because this ensures that the population does not become negative.
The analytical method is based on the fact that, based on past demographic dynamics, a function with the closest description is selected. In principle, this can be any function. However, one way or another, this function is of an empirical nature, and there is no general mathematical law of demographic dynamics.
Often used logistic function, the peculiarity of which in demographic forecasting is that its increment decreases as the population grows.
Thus, the main advantage of using mathematical methods is their ease of calculation, and the disadvantage is the forecast of only the total population.
2. Method of moving ages (component method)
The component method opens up broader opportunities for demographic forecast developers. Unlike extrapolation and analytical methods, it allows one to obtain not only the total population, but also its distribution by gender and age.
The essence of the method is that the initial population, as it were, “moves” into the future, decreasing due to the dead (and those who left) and replenished due to those born (and those who arrived). Therefore, for a forecast it is necessary to know the basic size and structure of the population, as well as hypotheses regarding trends in population reproduction and migration in the forecast period.
Movement is carried out in time steps equal to the length of the age group. To do this, the size of the age group of the population at the beginning of the forecast period is multiplied by the coefficient of movement (survival). The movement coefficient is the ratio of two numbers of adjacent age groups: those living at age “x+1” and “x” (L x+1 and L x), taken from the mortality table. In this case, the migration balance should be taken into account.
The age movement model has the form:
P x+1 =P x *(L x+1 /L x)+MC
where P x is the number of age group “x”;
P x+1 - number of age group "x+1";
L x+1 /L x - coefficient of movement to the next age (probability of living at age "x+1");
MS - migration balance.
Thus, the main advantage of the component method is the forecast of not only the total population, but also its distribution by sex and age; the disadvantage is the complexity of the calculation.
So, the extrapolation method is the most optimal, since for this method we have all the necessary indicators. It also allows you to predict the total population for any number of years in advance, simply by assuming constant absolute average annual population growth throughout the entire forecast period.
3.3 Constructing a population forecast for the Komi Republic
To build the forecast, we chose an extrapolation method using a linear function.
First, we calculated the absolute average annual population growth for 2017, which took a negative value equal to -6277 people.
We took the number of people living in the territory of the Komi Republic in 2017 as the base population level.
Table 3.1 - Forecast of the population of the Komi Republic (persons)
Thus, we can conclude that if the absolute average annual population growth continues to decline, the population level will rapidly fall, and this does not take into account migration loss, which decreases slightly every year.
Conclusion
Having analyzed the population dynamics of the Komi Republic from 2007 to 2017. and the factors influencing it, we can conclude that in general the population has been decreasing throughout the entire period. Thus, the greatest influence is exerted by such factors as: the rate of general morbidity of the population (an increase is observed) and the number of health care institutions (decreasing every year). But other indicators are also quite important, for example, the unemployment rate, which increases rapidly from 2014 to 2017.
Indicators of the population structure of the Komi Republic have generally been decreasing over the past 5 years, only the population younger and older than working age is increasing. Compared to the Russian Federation as a whole, the population is increasing, but it can be noted that the selected indicators of the structure of the Republic. Komi and the Russian Federation are changing equally.
To analyze factors that have a direct impact on population changes, a correlation and regression analysis was carried out. A strong direct linear relationship is observed between the population size and: the number of state. healthcare institutions of the Republic of Kazakhstan and the number of state. general educational institutions of the Republic of Kazakhstan. There is a strong inverse linear relationship between population size and: natural increase, the rate of general morbidity of the population and the average price of 1 sq. m of total area of apartments in the housing market. A weak linear relationship is observed between population size and unemployment rate.
Based on the analysis carried out, the indicators we studied that affect the population of the Komi Republic, some problems were identified - an increase in unemployment, the availability of housing for some categories of the population, migration of the population from the region, an increase in morbidity, a reduction in the number of government agencies. healthcare and educational institutions.
Of course, there are ways to solve these problems, mainly in the fight against them the main role is played by the state and its socio-economic policy.
The main methods of demographic forecasting are: methods based on the use of various mathematical functions (extrapolation and analytical methods), as well as the method of moving ages, or the component method.
The most optimal of these methods is the extrapolation method, since we have all the necessary indicators for its application. It also allows you to predict the total population for any number of years in advance, simply by assuming constant absolute average annual population growth throughout the entire forecast period.
Having calculated the absolute average annual population growth, using a linear function, we predicted the population size for 10 years, until 2027 inclusive.
Based on the forecast obtained, a rapid population decline is observed. Thus, if the absolute average annual population growth continues to decline, the population level will fall rapidly, and this does not take into account migration loss, which decreases slightly every year.
Bibliography:
Reviews:
02/27/2019, 14:09 Ashmarov Igor Anatolyevich
Review: The article is written on a current topic and is of practical interest. The material of the work is well structured, theoretical calculations are given to confirm the conclusions. The work is structured in accordance with the requirements of the journal. The abstract corresponds to the content of the article, as does its English-Russian translation. Please specifically clarify the scientific novelty of the article. Conclusions have been drawn. I can recommend this material for publication in an open access scientific journal.
3.03.2019, 7:48 Yatsky Sergey Alexandrovich
Review: In the article by Nekrasova G. A., Petrakova A. M., Orlova V., Pimankina A., Polyakova A. and Razmyslova M., based on statistical data, the main indicators that influence the dynamics of the population of the Komi Republic are considered. The authors made a forecast of the further dynamics of the population of the republic based on the extrapolation method. Therefore, this article is recommended for publication in its presented form. Sincerely, Yatsky S.A.
In Komi, the average age of the population was 38.2 years, including in urban areas - 37.7, in rural areas - 40.1. Women are on average 5 years older than men. Among the regions of the Northwestern Federal District, Komi is the “youngest”, says the report on the state of sanitary and epidemiological well-being of the population in the Republic of Kazakhstan in 2017, prepared by Rospotrebnadzor Komi.
According to the department, the population at the beginning of 2018 in the region was 840.9 thousand people. In 2017, the number of residents decreased by 9.7 thousand people, or 1.1%. The decrease was greatest in rural areas, where the number of residents decreased by 1.6%, and there were fewer city dwellers by 1%.
The main reason for the decline in the republic's population was migration outflow. Population losses were also increased by natural decline, which replaced the natural increase observed from 2011 to 2016. In urban areas, the excess of the number of births over the number of deaths has persisted since 2008. In rural areas, natural decline has been recorded for the last three years.
A decrease in population was noted in all urban districts and municipal areas of the republic, except for Syktyvkar and the Syktyvdinsky district. In Syktyvkar, the population increased due to natural growth, which exceeded migration decline, in the Syktyvdinsky district - due to natural and migration growth.
Estimation of the population of the Komi Republic (in thousands of people and in%)
As of January 1, 2017, the region had an excess of women over men by 47.5 thousand people. By the beginning of 2017, 449 thousand women and 401.5 thousand men lived in the republic (52.8% and 47.2% of the region’s population, respectively). For every thousand men there were 1118 women. In urban areas, compared to rural areas, the predominance of women is more pronounced (1153 and 1003, respectively).
On average in Russia, by the beginning of 2016, there were 1,158 women for every thousand men.
By the beginning of 2017, the population under 15 years old was 171.5 thousand people, the working age population from 16 to 54 years old was 493.2 thousand people, the population older than the working age population (men 60 years old and women 55 years old or more) was 185.9 thousand. Human.
In general, in Komi, by the beginning of 2017, the number of children and adolescents increased by 1% compared to 2016, the number of the working-age population decreased by 2.4%, and the number of those older than the working-age population increased by 2.4%.
As a result, the share of the working-age population decreased from 59% to 58%, those under working age increased from 19.8% to 20.2%, those older than working age increased from 21.2% to 21.9%.
The structure of the urban population, compared to the rural one, is distinguished by a smaller share of the population of children and adolescents (19.8% versus 21.6% in rural areas) and the elderly (20.8% versus 25.4%) and a larger share of the working-age population (59. 4% versus 53%).
Among the regions of the Northwestern Federal District, Komi has the most favorable age structure: the highest proportion of people under working age (20.2% versus 16.7% for the federal district as a whole) and the lowest proportion of people over working age (21. 9% versus 26.2%).
Also, the demographic aging of the population continues in the republic (when the share of the population aged 65 years and older is more than 7%): at the beginning of 2016, the proportion of people of these ages was 10.4%, at the beginning of 2017 - 10.9%.
In total, 20 settlements in the region saw an increase in the number of residents.
In 2016, according to the Comistat, the population of the republic decreased by 6 thousand 277 people. Compared to previous years, the rate of population decline has decreased: back in the early 2010s, the region was losing 8.5-9 thousand people annually.
Imagine that the Ukhta village of Vodny, or Troitsko-Pechorsk, or Ust-Kulom seemed to be completely depopulated - the number of people living there is comparable to the one that Komi lost in a year.
Only two municipalities have a population - in Syktyvkar (plus 1042 people) and Syktyvdinsky district (83 people). The Vorkuta (minus 1,381 people), Pechora (999 people) and Ukhta districts (minus 776 people) lost the most people.
We provide a table of the number of people living in a particular settlement, specifying whether the number of people has increased (“+”), decreased (“-”) or remained unchanged (“/”) ( We are talking specifically about settlements, which may administratively include several settlements; Komistat cannot provide accurate data for all villages and towns).
Komi Republic | |||
Urban population | |||
Rural population | |||
Syktyvkar | |||
Syktyvkar | |||
Ezhvinsky district | no data | ||
Verkhnyaya Maksakovka | |||
Krasnozatonsky | |||
Sedkyrkeshch | |||
Vorkuta district | |||
Vorgashor | |||
Zapolyarny | |||
Komsomol | |||
Northern | |||
Intinsky district | |||
Verkhnyaya Inta | |||
Usinsky district | |||
Ukhtinsky district | |||
Vuktylsky district | |||
Lemtybozh | |||
Sub-daughter | |||
Ust-Soplesk | |||
Izhemsky district | |||
Brykalansk | |||
Kelchiyur | |||
Krasnobor | |||
Knyazhpogostsky district | |||
Seregovo | |||
Chinyavoryk | |||
Koygorodsky district | |||
Koygorodok | |||
Lower Turunyu | |||
Kortkeros district | |||
Bogorodsk | |||
Bolshelug | |||
Kortkeros | |||
Podjelsk | |||
Podtybok | |||
Poztykeres | |||
Lakeside | |||
Storozhevsk | |||
Ust-Lekchim | |||
Pechora district | |||
Kajer | |||
Priuralskoe | |||
Priluzsky district | |||
Verkholuzie | |||
Guryevka | |||
Obyachevo | |||
Prokopyevka | |||
Spasporub | |||
Cheremukhovka | |||
Sosnogorsk district | |||
Sosnogorsk | |||
Nizhny Odes | |||
Syktyvdinsky district | |||
Vylgort | |||
Palevitsy | |||
Sysolsky district | |||
Vizindor | |||
Zaozerye | |||
Kuratovo | |||
Pyeldino | |||
Troitsko-Pechorsky district | |||
Troitsko-Pechorsk | |||
Priuralsky | |||
Znamenka | |||
Komsomolsk-on-Pechora | |||
Mitrofan-Dikost | |||
Lower Omra | |||
Ust-Ilych | |||
Udora district | |||
Blagoevo | |||
Mezhdurechensk | |||
Usogorsk | |||
Big Puchkoma | |||
Big Pyssa | |||
Chernutevo | |||
Ust-Vymsky district | |||
Kozhmudor | |||
Student | |||
Ust-Vym | |||
Ust-Kulomsky district | |||
Voldino | |||
Nizhny Voch | |||
Diaserya | |||
Derevyansk | |||
Kebanyel | |||
Kerchomya | |||
Myeldino | |||
Pomozdino | |||
Ust-Kulom | |||
Ust-Tsilemsky district | |||
Middle Bugaevo | |||
Cow Creek | |||
Novy Bor | |||
Okunev Nos | |||
Zamezhnaya | |||
Ust-Tsilma | |||
Khabarikha | |||
* Komistat explains the absence of some data by the administrative unification of settlements, although people did not stop living there. So, last year Vuktyl was transformed from a municipal district into an urban district with the unification of the settlements of Dutovo, Lemtybozh, Podcherye and Ust-Sopleks. In the Koygorod district, Nizhny Turunyu became part of Kazhym. In the Priluzsky district, the settlements of Vaymes and Verkholuzye became part of Noshul, and Chitaevo became part of Obyachevo.
Photo from pixabay.com
|
population of the republic comics, population of the republic comme il faut
The population of the republic according to Rosstat is 864 424
people (2015). Population density - 2,06
people/km2 (2015). Urban population - 77,68
% (2015).
Population | |||||||
---|---|---|---|---|---|---|---|
1926 | 1928 | 1959 | 1970 | 1979 | 1989 | 1990 | 1991 |
207 314 | ↘204 200 | ↗815 799 | ↗964 802 | ↗1 118 421 | ↗1 261 024 | ↘1 248 891 | ↘1 239 885 |
1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 |
↘1 222 134 | ↘1 206 079 | ↘1 192 063 | ↘1 156 750 | ↘1 132 650 | ↘1 115 737 | ↘1 095 723 | ↘1 077 990 |
2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |
↘1 057 873 | ↘1 042 880 | ↘1 018 674 | ↘1 016 040 | ↘1 005 706 | ↘996 440 | ↘985 029 | ↘974 617 |
2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 |
↘968 164 | ↘958 544 | ↘901 189 | ↘899 215 | ↘889 837 | ↘880 639 | ↘872 057 | ↘864 424 |
250 000 500 000 750 000 1 000 000 1 250 000 1 500 000 1928 1990 1995 2000 2005 2010 2015
Fertility (number of births per 1000 population) | ||||||||
---|---|---|---|---|---|---|---|---|
1970 | 1975 | 1980 | 1985 | 1990 | 1995 | 1996 | 1997 | 1998 |
17,0 | ↗18,1 | ↗18,2 | ↗19,2 | ↘13,4 | ↘9,3 | ↘9,2 | ↘8,9 | ↗9,3 |
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |
↘8,5 | ↗8,8 | ↗9,2 | ↗10,1 | ↗11,3 | ↗11,5 | ↘11,1 | ↗11,1 | ↗11,9 |
2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | ||
↗12,2 | ↗12,4 | ↗12,9 | ↗13,0 | ↗13,9 | ↗14,2 | ↘14,1 |
Mortality rate (number of deaths per 1000 population) | ||||||||
---|---|---|---|---|---|---|---|---|
1970 | 1975 | 1980 | 1985 | 1990 | 1995 | 1996 | 1997 | 1998 |
6,5 | ↗7,0 | ↗8,1 | ↘7,7 | ↘7,4 | ↗12,6 | ↘11,6 | ↘10,5 | ↘10,0 |
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |
↗10,7 | ↗12,0 | ↗12,5 | ↗13,8 | ↗15,6 | ↘15,2 | ↗15,2 | ↘13,8 | ↘12,7 |
2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | ||
↗12,7 | ↗12,8 | ↗13,1 | ↘12,3 | ↘12,1 | ↘11,9 | ↗12,2 |
Natural population growth (per 1000 population, sign (-) means natural population decline) | ||||||||
---|---|---|---|---|---|---|---|---|
1970 | 1975 | 1980 | 1985 | 1990 | 1995 | 1996 | 1997 | 1998 |
10,5 | ↗11,1 | ↘10,1 | ↗11,5 | ↘6,0 | ↘-3,3 | ↗-2,4 | ↗-1,6 | ↗-0,7 |
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |
↘-2,2 | ↘-3,2 | ↘-3,3 | ↘-3,7 | ↘-4,3 | ↗-3,7 | ↘-4,1 | ↗-2,7 | ↗-0,8 |
2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | ||
↗-0,5 | ↗-0,4 | ↗-0,2 | ↗0,7 | ↗1,8 | ↗2,3 | ↘1,9 |
Life expectancy at birth (number of years) | ||||||||
---|---|---|---|---|---|---|---|---|
1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 |
68,2 | ↘67,9 | ↘65,5 | ↘62,0 | ↘60,4 | ↗61,0 | ↗62,9 | ↗64,9 | ↗65,5 |
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |
↘64,9 | ↘63,5 | ↘63,4 | ↘62,2 | ↘61,5 | ↗62,2 | ↗62,3 | ↗64,2 | ↗65,8 |
2008 | 2009 | 2010 | 2011 | 2012 | 2013 | |||
↗66,2 | ↗66,5 | ↗66,9 | ↗68,0 | ↗68,3 | ↗69,3 |
1926 people |
% | 1939 people |
% | 1959 people |
% | 1989 people |
% | 2002 people |
% from Total |
% from indicating- shih national nal- ness |
2010 people |
% from Total |
% from indicating- shih national nal- ness |
|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | 207314 | 100,00 % | 318996 | 100,00 % | 806199 | 100,00 % | 1250847 | 100,00 % | 1018674 | 100,00 % | 901189 | 100,00 % | ||
Russians | 13731 | 6,62 % | 70226 | 22,01 % | 389995 | 48,37 % | 721780 | 57,70 % | 607021 | 59,59 % | 59,92 % | 555963 | 61,69 % | 65,08 % |
Komi | 191245 | 92,25 % | 231301 | 72,51 % | 245074 | 30,40 % | 291542 | 23,31 % | 256464 | 25,18 % | 25,32 % | 202348 | 22,45 % | 23,69 % |
including Komi-Izhemtsy | 12.689 | 1,25 % | 1,25 % | 5.725 | 0,64 % | 0,67 % | ||||||||
Ukrainians | 34 | 0,02 % | 6010 | 1,88 % | 80132 | 9,94 % | 104170 | 8,33 % | 62115 | 6,10 % | 6,13 % | 36082 | 4,00 % | 4,22 % |
Tatars | 32 | 0,02 % | 709 | 0,22 % | 8459 | 1,05 % | 25980 | 2,08 % | 15680 | 1,54 % | 1,55 % | 10779 | 1,20 % | 1,26 % |
Belarusians | 11 | 0,01 % | 3323 | 1,04 % | 22339 | 2,77 % | 26730 | 2,14 % | 15212 | 1,49 % | 1,50 % | 8859 | 0,98 % | 1,04 % |
Germans | 15 | 0,01 % | 2617 | 0,82 % | 19805 | 2,46 % | 12866 | 1,03 % | 9246 | 0,91 % | 0,91 % | 5441 | 0,60 % | 0,64 % |
Chuvash | 3 | 0,00 % | 246 | 0,08 % | 3493 | 0,43 % | 11253 | 0,90 % | 7529 | 0,74 % | 0,74 % | 5077 | 0,56 % | 0,59 % |
Azerbaijanis | 0 | 0,00 % | 112 | 0,04 % | 1374 | 0,17 % | 4728 | 0,38 % | 6066 | 0,60 % | 0,60 % | 4858 | 0,54 % | 0,57 % |
Bashkirs | 0 | 0,00 % | 56 | 0,02 % | 623 | 0,08 % | 5313 | 0,42 % | 3149 | 0,31 % | 0,31 % | 2333 | 0,26 % | 0,27 % |
Moldovans | 1 | 0,00 % | 63 | 0,02 % | 1612 | 0,20 % | 5155 | 0,41 % | 3447 | 0,34 % | 0,34 % | 2318 | 0,26 % | 0,27 % |
Mari | 0 | 0,00 % | 70 | 0,02 % | 706 | 0,09 % | 4067 | 0,33 % | 3202 | 0,31 % | 0,32 % | 2280 | 0,25 % | 0,27 % |
Armenians | 2 | 0,00 % | 164 | 0,05 % | 1894 | 0,23 % | 2171 | 0,17 % | 2102 | 0,21 % | 0,21 % | 1717 | 0,19 % | 0,20 % |
Udmurts | 2 | 0,00 % | 131 | 0,04 % | 999 | 0,12 % | 3573 | 0,29 % | 2336 | 0,23 % | 0,23 % | 1593 | 0,18 % | 0,19 % |
Mordva | 0 | 0,00 % | 328 | 0,10 % | 1802 | 0,22 % | 3927 | 0,31 % | 2390 | 0,23 % | 0,24 % | 1462 | 0,16 % | 0,17 % |
Lezgins | 0 | 0,00 % | 12 | 0,00 % | 930 | 0,07 % | 1198 | 0,12 % | 0,12 % | 1406 | 0,16 % | 0,16 % | ||
Lithuanians | 4 | 0,00 % | 33 | 0,01 % | 8284 | 1,03 % | 3066 | 0,25 % | 1607 | 0,16 % | 0,16 % | 977 | 0,11 % | 0,11 % |
Uzbeks | 0 | 0,00 % | 51 | 0,02 % | 1245 | 0,15 % | 2593 | 0,21 % | 709 | 0,07 % | 0,07 % | 939 | 0,10 % | 0,11 % |
Poles | 23 | 0,01 % | 569 | 0,18 % | 3053 | 0,38 % | 2181 | 0,17 % | 1456 | 0,14 % | 0,14 % | 843 | 0,09 % | 0,10 % |
Kyrgyz | 0 | 0,00 % | 16 | 0,01 % | 343 | 0,03 % | 767 | 0,08 % | 0,08 % | 731 | 0,08 % | 0,09 % | ||
Komi-Permyaks | 0 | 0,00 % | 99 | 0,01 % | 1076 | 0,09 % | 1118 | 0,11 % | 0,11 % | 659 | 0,07 % | 0,08 % | ||
Georgians | 0 | 0,00 % | 62 | 0,02 % | 1328 | 0,16 % | 1683 | 0,13 % | 896 | 0,09 % | 0,09 % | 614 | 0,07 % | 0,07 % |
Nenets | 2080 | 1,00 % | 974 | 0,31 % | 374 | 0,05 % | 376 | 0,03 % | 708 | 0,07 % | 0,07 % | 503 | 0,06 % | 0,06 % |
other | 77 | 0,04 % | 1869 | 0,59 % | 13466 | 1,67 % | 15330 | 1,23 % | 8556 | 0,84 % | 0,84 % | 6521 | 0,72 % | 0,76 % |
indicated nationality | 207260 | 99,97 % | 318942 | 99,98 % | 806156 | 99,99 % | 1250833 | 100,00 % | 1012974 | 99,44 % | 100,00 % | 854303 | 94,80 % | 100,00 % |
did not indicate nationality | 54 | 0,03 % | 54 | 0,02 % | 43 | 0,01 % | 14 | 0,00 % | 5700 | 0,56 % | 46886 | 5,20 % |
2010 Census data
Area (city) |
Komi | Russians | Ukrainians | Tatars | Belarusians | Germans | Chuvash | Bashkirs | Azerbaijanis |
---|---|---|---|---|---|---|---|---|---|
Syktyvkar | 25,9 % | 66,0 % | 2,8 % | … | … | … | … | … | … |
Vorkuta | 1,7 % | 77,7 % | 7,9 % | 2,9 % | 1,5 % | … | 1,1 % | … | 1,0 % |
Vuktyl | 10,8 % | 72,3 % | 8,3 % | 1,6 % | 1,4 % | … | 1,2 % | … | … |
Inta | 11,4 % | 72,6 % | 7,6 % | 1,8 % | 1,4 % | … | … | … | … |
Pechora | 13,2 % | 74,7 % | 5,7 % | … | 1,4 % | … | … | … | … |
Sosnogorsk | 8,9 % | 80,8 % | 4,3 % | … | 1,2 % | … | … | … | … |
Usinsk | 14,8 % | 59,6 % | 7,6 % | 7,2 % | 1,5 % | … | 1,0 % | 2,5 % | 1,5 % |
Ukhta | 7,9 % | 81,1 % | 4,1 % | 1,1 % | 1,1 % | … | … | … | … |
Izhemsky district | 88,9 % | 9,7 % | … | … | … | … | … | … | … |
Knyazhpogostsky district | 15,3 % | 70,4 % | 5,4 % | … | 1,7 % | … | … | … | 1,3 % |
Koygorodsky district | 35,5 % | 56,1 % | 3,0 % | … | … | 1,9 % | … | … | … |
Kortkeros district | 68,4 % | 26,8 % | 1,9 % | … | … | … | … | … | … |
Syktyvdinsky district | 45,9 % | 47,6 % | 2,3 % | … | … | … | … | … | … |
Sysolsky district | 64,8 % | 29,7 % | 1,9 % | … | … | … | … | … | … |
Priluzsky district | 55,2 % | 40,9 % | 1,6 % | … | … | … | … | … | … |
Troitsko-Pechorsky district | 26,2 % | 63,9 % | 4,3 % | … | 1,4 % | … | … | … | … |
Udora district | 40,3 % | 46,7 % | 3,8 % | … | 1,0 % | … | … | … | … |
Ust-Vymsky district | 25,6 % | 62,8 % | 4,4 % | … | 1,1 % | … | … | … | … |
Ust-Kulomsky district | 76,9 % | 18,9 % | 1,7 % | … | … | … | … | … | … |
Ust-Tsilemsky district | 5,1 % | 93,0 % | … | … | … | … | … | … | … |
According to a large-scale survey by the Sreda research service conducted in 2012, the item “I believe in God (in a higher power), but I do not profess a specific religion” in the Komi Republic was chosen by 41% of respondents, “I profess Orthodoxy and belong to the Russian Orthodox Church” - 30% , “I don’t believe in God” - 14%, “I profess Christianity, but do not consider myself to be a member of any Christian denomination” - 4%, “I profess the traditional religion of my ancestors, I worship gods and the forces of nature” - 1%, “I profess Islam, but I am neither a Sunni nor a Shiite” - 1%, “I profess Orthodoxy, but I do not belong to the Russian Orthodox Church and am not an Old Believer” - 1%, “I profess Orthodoxy, I am an Old Believer” - 1%. The rest are less than 1%.
Map legend (when you hover over the marker, the real population is displayed):
Arhangelsk region Nenets Autonomous Okrug Arhangelsk region Kirov region Perm region Sverdlovsk region KHMAO Yamalo-Nenets Autonomous Okrug Sydney Parma Podtybok Sizyabsk Sindor Ust-Vym Chinyavoryk Shchelyayur Yugydyag Yaksha Populated areas of the Komi Republic
|
|
Population of the constituent entities of the Russian Federation | Amur Arkhangelsk Astrakhan Belgorod Bryansk Volgograd Vologda Voronezh Ivanovo Irkutsk Kaliningrad Kaluga Kemerovo Kirov Kurgan Kursk Leningrad Lipetsk Magadan Moscow Murmansk Nizhny Novgorod Novgorod Novosibirsk Omsk Orenburg Oryol Penza Pskov Rostov Ryazan Samara Saratov Sakhalin Sverdlovsk Smolensk Tambov Tver Tomsk Tula Tyumen Ulyanovsk Chelyabinsk Yaroslavl||
---|---|---|
Federal cities |
Moscow St. Petersburg Sevastopol |
|
Autonomous region |
Jewish |
|
Autonomous okrugs |
Nenets1 Khanty-Mansiysk - Yugra2 Chukotka Yamalo-Nenets2 |
|
1 Located on the territory of the Arkhangelsk region 2 Located on the territory of the Tyumen region |
Komi Republic | |||
---|---|---|---|
Administrative center: Syktyvkar Urban districts: Vorkuta Vuktyl Inta Usinsk Syktyvkar Ukhta Articles: Geography | Coat of arms | Anthem | History | Population| Administrative division | Flag |
population of the republic komiinform, population of the republic comics, population of the republic comme il faut, population of the republic commissar
The population of Komi as of January 1, 2018, according to preliminary estimates, was 840.8 thousand people. Over the past year, there were 9.8 thousand fewer residents in the region. The head of the Comistat, Marina Kudinova, spoke about this at a press conference today.
Photo by Victor Bobyr, Grigory Pil
She noted that the main reason for the decline in the republic’s population lies in migration - about 9.7 thousand people left the region last year, which is higher than in 2016.
Most often they chose the Northwestern, Central, Southern and Volga regions. Residents of the republic who left not only Komi, but also Russia most often left for Ukraine and Azerbaijan. There were also isolated cases of moving to foreign countries.
The trend of internal migration continued in 2017 - residents of the region continue to move from villages to cities. Last year, mortality in Komi again outpaced the birth rate.
Mortality rates in the region as a whole were declining, but the birth rate was declining at a faster pace, noted the head of the Comistat. - Over 11 months, 9034 children were born in Komi: 4519 boys and 4515 girls. But infant mortality rates have decreased - in cities by 10%, in rural areas - by half.
Residents of Komi in 2017 created families more often and divorced more often than the year before. Divorce statistics in the republic are higher than the national average.
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