54 research outputs found
Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ Π΄Π»Ρ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΈ ΡΡΡΡΠΊΡΡΡΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Statistical study of the primary real estate market is always associated with the problem that the object is in a constant, and very intense change, both in quantitative terms and in its internal content. Therefore, the issues of constant adaptation of statistical methodology in relation to the primary real estate market are relevant continuously. Among the tasks that are constantly in the field of statistical science and practice in relation to the primary real estate market are the following. First, a critical analysis of the content of the modern primary real estate market, which should allow to identify its fundamental features as an object of statistical research, to systematize the economic relations of the subjects of this market segment for a comprehensive statistical analysis of its functioning and development in any region of Russia. Secondly, it is the construction of analytical classifications of the primary real estate market, systematization of criteria for their construction, which should allow for a qualitative analysis of the structure of this market segment in the modern market economy. Third, the continuous improvement of the system of statistical indicators of the primary real estate market, whichΒ should be constantly supplemented by various blocks of indicators, the use of which will link the development of the primary real estate market with indicators of the standard of living of the population and socio-economic development of a particular region on the basis of the formation and ordering of its various subsystems, which will increase their consistency with indicators of living standards and socio-economic development. To Develop the theory and statistical methodology of the complex study of the primary real estate market in terms of the development of criteria for the division of the object into homogeneous groups by typological characteristics and the construction on their basis of statistical classifications necessary for the structural analysis of the primary real estate market. To obtain scientific results in this article, General scientific methods of cognition, such as scientific abstraction, analysis and synthesis, are used, since it is a question of dividing a single whole into typologically homogeneous complexes, the organic relationship between which ensures the integrity and unity of the studied object β the primary real estate market. In addition, the use of the statistical grouping method is considered throughout the work, as it is an applied application of typological criteria. The main classification features of economic assets traded in the primary real estate market of the region are Substantiated and formulated. The development of criteria for the typological division of the object allowed to build statistical classifications necessary for a comprehensive analysis of the structure and structural changes in the primary real estate market. In the scientific article deals with the problematic aspects of a statistical study of the primary real estate market in parts of its etymology on the basis of clear criteria against which to understand the quality and properties of the traded on its economic assets, to build a statistical classification. All this is a step in the first stage of the statistical study in the sequence that is classically considered by the General theory of statistics. Statistical classifications and groupings by typological features precede the science-intensive substantiation and application of complex mathematical and static methods for factor analysis and forecasting of primary real estate market indicators.Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π²ΡΠ΅Π³Π΄Π° ΡΠΎΠΏΡΡΠΆΠ΅Π½ΠΎ Ρ ΡΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΎΠΉ, ΡΡΠΎ ΠΎΠ±ΡΠ΅ΠΊΡ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡΡ Π² ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΌ, ΠΏΡΠΈΡΡΠΌ Π²Π΅ΡΡΠΌΠ° ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΠΌ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΈ, ΠΊΠ°ΠΊ Π² ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌ Π°ΡΠΏΠ΅ΠΊΡΠ΅, ΡΠ°ΠΊ ΠΈ Π² ΡΠ²ΠΎΡΠΌ Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΌ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠΈ. ΠΠΎΡΡΠΎΠΌΡ ΠΈ Π²ΠΎΠΏΡΠΎΡΡ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΉ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π°ΠΊΡΡΠ°Π»ΡΠ½Ρ Π½Π΅ΠΏΡΠ΅ΡΡΠ²Π½ΠΎ. Π‘ΡΠ΅Π΄ΠΈ Π·Π°Π΄Π°Ρ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ Π½Π°Ρ
ΠΎΠ΄ΡΡΡΡ Π² ΠΏΠΎΠ»Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°ΡΠΊΠΈ ΠΈ ΠΏΡΠ°ΠΊΡΠΈΠΊΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΌΠΎΠΆΠ½ΠΎ Π²ΡΠ΄Π΅Π»ΠΈΡΡ ΡΠ»Π΅Π΄ΡΡΡΠΈΠ΅. ΠΠΎ-ΠΏΠ΅ΡΠ²ΡΡ
, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΊΡΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΡΠΎ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡΡ Π²ΡΡΠ²ΠΈΡΡ Π΅Π³ΠΎ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΈΠ°Π»ΡΠ½ΡΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΡΠ·ΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ½ΠΊΠ° Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π΅Π³ΠΎ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π² Π»ΡΠ±ΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π ΠΎΡΡΠΈΠΈ. ΠΠΎ-Π²ΡΠΎΡΡΡ
, ΡΡΠΎ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΈΡ
ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ, ΡΡΠΎ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡΡ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΡΡΡΠΊΡΡΡΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ½ΠΊΠ° Π² ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. Π-ΡΡΠ΅ΡΡΠΈΡ
, ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠ΅ ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ Π΄ΠΎΠ»ΠΆΠ½Π° Π΄ΠΎΠΏΠΎΠ»Π½ΡΡΡΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌΠΈ Π±Π»ΠΎΠΊΠ°ΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ ΡΠ²ΡΠ·Π°ΡΡ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΈΠΎΠ½Π° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π΅Π΅ ΠΏΠΎΠ΄ΡΠΈΡΡΠ΅ΠΌ, ΡΡΠΎ ΠΏΠΎΠ²ΡΡΠΈΡ ΠΈΡ
ΡΠΎΠ³Π»Π°ΡΠΎΠ²Π°Π½Π½ΠΎΡΡΡ Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ. Π¦Π΅Π»Ρ: Π Π°Π·Π²ΠΈΡΠΈΠ΅ ΡΠ΅ΠΎΡΠΈΠΈ ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² ΡΠ°ΡΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° Π½Π° ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ ΠΏΠΎ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ Π½Π° ΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΡ
Π΄Π»Ρ ΡΡΡΡΠΊΡΡΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΠ»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ Π½Π°ΡΡΠ½ΡΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΎΠ±ΡΠ΅Π½Π°ΡΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ, ΡΠ°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ Π½Π°ΡΡΠ½Π°Ρ Π°Π±ΡΡΡΠ°ΠΊΡΠΈΡ, Π°Π½Π°Π»ΠΈΠ· ΠΈ ΡΠΈΠ½ΡΠ΅Π·, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΡΠ΅ΡΡ ΠΈΠ΄Π΅Ρ ΠΎ ΡΠ°Π·Π±ΠΈΠ΅Π½ΠΈΠΈ Π΅Π΄ΠΈΠ½ΠΎΠ³ΠΎ ΡΠ΅Π»ΠΎΠ³ΠΎ Π½Π° ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ, ΠΎΡΠ³Π°Π½ΠΈΡΠ½Π°Ρ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Ρ ΠΌΠ΅ΠΆΠ΄Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ ΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π΅Ρ ΡΠ΅Π»ΠΎΡΡΠ½ΠΎΡΡΡ ΠΈ Π΅Π΄ΠΈΠ½ΡΡΠ²ΠΎ ΠΈΠ·ΡΡΠ°Π΅ΠΌΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ° β ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π½Π° ΠΏΡΠΎΡΡΠΆΠ΅Π½ΠΈΠΈ Π²ΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΎΠΊ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΡΠ΅ΡΡ ΠΈΠ΄Π΅Ρ ΠΎ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΠΌ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π΅Π΄ΠΈΠ½ΠΈΡ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ Π² ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Ρ ΠΈ ΡΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΎΠ±ΡΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°. Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»Π° ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΠ΅ Π΄Π»Ρ Π²ΡΠ΅ΡΡΠΎΡΠΎΠ½Π½Π΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΡΡΡΠΊΡΡΡΡ ΠΈ ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΡΠ΄Π²ΠΈΠ³ΠΎΠ² Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅: Π Π½Π°ΡΡΠ½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ½ΡΠ΅ Π°ΡΠΏΠ΅ΠΊΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² ΡΠ°ΡΡΠΈ Π΅Π³ΠΎ ΡΡΠΈΠΌΠΎΠ»ΠΎΠ³ΠΈΠ·Π°ΡΠΈΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΡΠΊΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π², ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΡ
ΠΏΠΎΠ½ΡΡΡ ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΠΎΠ±ΡΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ Π½Π° Π½Π΅ΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ. ΠΡΡ ΡΡΠΎ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π³ΠΎΠΌ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΏΠ΅ΡΠ²ΠΎΠ³ΠΎ ΡΡΠ°ΠΏΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΠΎΠΉ Π΅Π³ΠΎ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΎΠ±ΡΠ΅ΠΉ ΡΠ΅ΠΎΡΠΈΠ΅ΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ. Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΊΠΈ ΠΏΠΎ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΏΡΠ΅Π΄ΡΠ΅ΡΡΠ²ΡΡΡ Π½Π°ΡΠΊΠΎΠ΅ΠΌΠΊΠΎΠΌΡ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΡΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Π‘Π’ΠΠ’ΠΠ‘Π’ΠΠ§ΠΠ‘ΠΠΠ Π ΠΠ‘Π£Π Π‘Π« Π ΠΠΠ’ΠΠΠ« ΠΠ ΠΠΠΠΠΠΠ ΠΠΠΠΠΠ― ΠΠΠΠΠΠΠ’ΠΠΠ― ΠΠΠ ΠΠΠΠ’ΠΠΠ ΠΠΠΠ’Π« ΠΠΠΠΠΠ«Π₯ Π ΠΠΠΠ’ΠΠΠΠΠ
The article is devoted to the formation of the original database and the justification of forecasting techniques for average monthly gross wages and salaries of employees at the regional level of the Russian Federation. The conceptual basis of the proposed approach in the article is a method of calculating the average monthly gross wages and salaries of employees in organizations, individual entrepreneurs and natural persons, introduced into the practice by the Federal State Statistics Service, in April 2016.Particular attention is given to forecast evaluation of wages in the formal and informal sectors of the economy based on the aggregation of different sources of information: statistical reporting and results of the federal sample surveys. The practical significance of the proposed algorithm is in its approbation on real statistical data for the Russian Federation and the city of Moscow.Π ΡΡΠ°ΡΡΠ΅ ΠΈΠ·Π»ΠΎΠΆΠ΅Π½Ρ Π²ΠΎΠΏΡΠΎΡΡ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π°Π·Ρ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΠΉ Π΄Π»Ρ ΡΠ°ΡΡΠ΅ΡΠ° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ ΡΡΠ΅Π΄Π½Π΅ΠΌΠ΅ΡΡΡΠ½ΠΎΠΉ Π·Π°ΡΠ°Π±ΠΎΡΠ½ΠΎΠΉ ΠΏΠ»Π°ΡΡ, ΠΈ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΈΠ΅ΠΌΡ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΠΎΠ³ΠΎ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ Π½Π° ΡΡΠΎΠ²Π½Π΅ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ. Π ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΎΡΠ½ΠΎΠ²Ρ Π°Π²ΡΠΎΡΡ ΠΏΡΠ΅Π΄Π»Π°Π³Π°ΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ ΡΠ°ΡΡΠ΅ΡΠ° ΡΡΠ΅Π΄Π½Π΅ΠΌΠ΅ΡΡΡΠ½ΠΎΠΉ Π½ΠΎΠΌΠΈΠ½Π°Π»ΡΠ½ΠΎΠΉ Π½Π°ΡΠΈΡΠ»Π΅Π½Π½ΠΎΠΉ Π·Π°ΡΠ°Π±ΠΎΡΠ½ΠΎΠΉ ΠΏΠ»Π°ΡΡ Π½Π°Π΅ΠΌΠ½ΡΡ
ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² Π² ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡΡ
, Ρ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΡΠ½ΡΡ
ΠΏΡΠ΅Π΄ΠΏΡΠΈΠ½ΠΈΠΌΠ°ΡΠ΅Π»Π΅ΠΉ ΠΈ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΡ
Π»ΠΈΡ, Π²Π²Π΅Π΄Π΅Π½Π½ΡΡ Π² ΠΏΡΠ°ΠΊΡΠΈΠΊΡ ΡΠ°Π±ΠΎΡΡ Π ΠΎΡΡΡΠ°ΡΠ° Π² Π°ΠΏΡΠ΅Π»Π΅ 2016 Π³.ΠΡΠΎΠ±ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π² ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΈ ΡΠ΄Π΅Π»Π΅Π½ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π²ΠΎΠΏΡΠΎΡΠΎΠ² ΠΏΡΠΎΠ³Π½ΠΎΠ·Π½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ Π·Π°ΡΠ°Π±ΠΎΡΠ½ΠΎΠΉ ΠΏΠ»Π°ΡΡ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ ΡΠΎΡΠΌΠ°Π»ΡΠ½ΠΎΠΌΡ ΠΈ Π½Π΅ΡΠΎΡΠΌΠ°Π»ΡΠ½ΠΎΠΌΡ ΡΠ΅ΠΊΡΠΎΡΠ°ΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π³ΡΠ΅Π³ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΏΠΎ ΠΎΡ
Π²Π°ΡΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π΅Π΄ΠΈΠ½ΠΈΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ ΠΈ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡΠΈ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠ² ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ: ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΡΠ΅ΡΠ½ΠΎΡΡΠΈ ΠΈ Π²ΡΠ±ΠΎΡΠΎΡΠ½ΡΡ
ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΠΈΠ·Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ Π² ΡΡΠ°ΡΡΠ΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π°Π΅ΡΡΡ Π΅Π³ΠΎ Π°ΠΏΡΠΎΠ±Π°ΡΠΈΠ΅ΠΉ Π½Π° ΡΠ΅Π°Π»ΡΠ½ΡΡ
ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
ΠΏΠΎ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ ΠΈ Π³ΠΎΡΠΎΠ΄Ρ ΠΠΎΡΠΊΠ²Π΅
Π‘Π’ΠΠ’ΠΠ‘Π’ΠΠ§ΠΠ‘ΠΠΠ Π ΠΠ‘Π£Π Π‘Π« Π ΠΠΠ’ΠΠΠ« ΠΠ ΠΠΠΠΠΠΠ ΠΠΠΠΠΠ― ΠΠΠΠΠΠΠ’ΠΠΠ― ΠΠΠ ΠΠΠΠ’ΠΠΠ ΠΠΠΠ’Π« ΠΠΠΠΠΠ«Π₯ Π ΠΠΠΠ’ΠΠΠΠΠ
The article is devoted to the formation of the original database and the justification of forecasting techniques for average monthly gross wages and salaries of employees at the regional level of the Russian Federation. The conceptual basis of the proposed approach in the article is a method of calculating the average monthly gross wages and salaries of employees in organizations, individual entrepreneurs and natural persons, introduced into the practice by the Federal State Statistics Service, in April 2016.Particular attention is given to forecast evaluation of wages in the formal and informal sectors of the economy based on the aggregation of different sources of information: statistical reporting and results of the federal sample surveys. The practical significance of the proposed algorithm is in its approbation on real statistical data for the Russian Federation and the city of Moscow.Π ΡΡΠ°ΡΡΠ΅ ΠΈΠ·Π»ΠΎΠΆΠ΅Π½Ρ Π²ΠΎΠΏΡΠΎΡΡ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π°Π·Ρ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΠΉ Π΄Π»Ρ ΡΠ°ΡΡΠ΅ΡΠ° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ ΡΡΠ΅Π΄Π½Π΅ΠΌΠ΅ΡΡΡΠ½ΠΎΠΉ Π·Π°ΡΠ°Π±ΠΎΡΠ½ΠΎΠΉ ΠΏΠ»Π°ΡΡ, ΠΈ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΈΠ΅ΠΌΡ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΠΎΠ³ΠΎ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ Π½Π° ΡΡΠΎΠ²Π½Π΅ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ. Π ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΎΡΠ½ΠΎΠ²Ρ Π°Π²ΡΠΎΡΡ ΠΏΡΠ΅Π΄Π»Π°Π³Π°ΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ ΡΠ°ΡΡΠ΅ΡΠ° ΡΡΠ΅Π΄Π½Π΅ΠΌΠ΅ΡΡΡΠ½ΠΎΠΉ Π½ΠΎΠΌΠΈΠ½Π°Π»ΡΠ½ΠΎΠΉ Π½Π°ΡΠΈΡΠ»Π΅Π½Π½ΠΎΠΉ Π·Π°ΡΠ°Π±ΠΎΡΠ½ΠΎΠΉ ΠΏΠ»Π°ΡΡ Π½Π°Π΅ΠΌΠ½ΡΡ
ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² Π² ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡΡ
, Ρ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΡΠ½ΡΡ
ΠΏΡΠ΅Π΄ΠΏΡΠΈΠ½ΠΈΠΌΠ°ΡΠ΅Π»Π΅ΠΉ ΠΈ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΡ
Π»ΠΈΡ, Π²Π²Π΅Π΄Π΅Π½Π½ΡΡ Π² ΠΏΡΠ°ΠΊΡΠΈΠΊΡ ΡΠ°Π±ΠΎΡΡ Π ΠΎΡΡΡΠ°ΡΠ° Π² Π°ΠΏΡΠ΅Π»Π΅ 2016 Π³.ΠΡΠΎΠ±ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π² ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΈ ΡΠ΄Π΅Π»Π΅Π½ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π²ΠΎΠΏΡΠΎΡΠΎΠ² ΠΏΡΠΎΠ³Π½ΠΎΠ·Π½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ Π·Π°ΡΠ°Π±ΠΎΡΠ½ΠΎΠΉ ΠΏΠ»Π°ΡΡ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ ΡΠΎΡΠΌΠ°Π»ΡΠ½ΠΎΠΌΡ ΠΈ Π½Π΅ΡΠΎΡΠΌΠ°Π»ΡΠ½ΠΎΠΌΡ ΡΠ΅ΠΊΡΠΎΡΠ°ΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π³ΡΠ΅Π³ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΏΠΎ ΠΎΡ
Π²Π°ΡΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π΅Π΄ΠΈΠ½ΠΈΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ ΠΈ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡΠΈ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠ² ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ: ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΡΠ΅ΡΠ½ΠΎΡΡΠΈ ΠΈ Π²ΡΠ±ΠΎΡΠΎΡΠ½ΡΡ
ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΠΈΠ·Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ Π² ΡΡΠ°ΡΡΠ΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π°Π΅ΡΡΡ Π΅Π³ΠΎ Π°ΠΏΡΠΎΠ±Π°ΡΠΈΠ΅ΠΉ Π½Π° ΡΠ΅Π°Π»ΡΠ½ΡΡ
ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
ΠΏΠΎ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ ΠΈ Π³ΠΎΡΠΎΠ΄Ρ ΠΠΎΡΠΊΠ²Π΅
ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ Π½Π°ΡΠΈΠ»ΠΈΡ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ
Despite the numerous achievements and success in various spheres of human activity, the modern civilization, unfortunately, has not yet been able to completely get rid of such a serious and shameful problem as violence against children. Not only in economically backward and developing countries, where numerous forms of infringement of the childrenβs rights have deep historical roots, but in the vast majority of the most developed countries of the world, violence against children has now acquired massive and catastrophic proportions. If we follow the ancient wisdom, that the maturity of any society emerges fully in terms of the relations that have developed in it with regard to the elderly and children, then a rather simple conclusion is drawn: the earth population has not yet reached the understanding of a number of eternal and simple truths. After all, any violent actions committed against children at present create objective and subjective prerequisites for the further reproduction of such actions in the future, but in relation to even younger generations. In this context, it is quite obvious that there is an urgent need to unite the efforts of the world community, states and individual citizens to stop and actively pursue any violent actions against children not only within the framework of existing legislation, but also in everyday life, where the moral support or condemnation are of great practical importance. In addition, there is an urgent need to develop special international and state projects and programs, aimed at protecting childrenβs rights and protecting them from any form of physical and spiritual violence. It is difficult to imagine a deep substantive justification of any measures to eliminate violence against children as a negative phenomenon of public life without a comprehensive quantitative description of such a unique object of research, which by definition is impossible without detailed and reliable statistical information. At present, obtaining such information causes great difficulties, which, naturally, creates additional obstacles to the knowledge of the true extent of the spread and consequences of the violence against children. For the above reasons, it is of great scientific and practical interest to improve the methodological foundations of statistical research on violence against children, implying both a clear interpretation of the subject of cognition and the development of a modern system of indicators that allows displaying various aspects of such a complex and negative social phenomenon.Β Π‘ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½Π°Ρ ΡΠΈΠ²ΠΈΠ»ΠΈΠ·Π°ΡΠΈΡ, Π½Π΅ΡΠΌΠΎΡΡΡ Π½Π° ΠΌΠ½ΠΎΠ³ΠΎΡΠΈΡΠ»Π΅Π½Π½ΡΠ΅ Π΄ΠΎΡΡΠΈΠΆΠ΅Π½ΠΈΡ ΠΈ ΡΡΠΏΠ΅Ρ
ΠΈ Π² ΡΠ°ΠΌΡΡ
ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΡΠ΅ΡΠ°Ρ
ΡΠ΅Π»ΠΎΠ²Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, ΠΊ ΡΠΎΠΆΠ°Π»Π΅Π½ΠΈΡ, ΠΏΠΎΠΊΠ° Π½Π΅ ΡΠΌΠΎΠ³Π»Π° ΠΏΠΎΠ»Π½ΠΎΡΡΡΡ ΠΈΠ·Π±Π°Π²ΠΈΡΡΡΡ ΠΎΡ ΡΠ°ΠΊΠΎΠΉ ΡΠ΅ΡΡΠ΅Π·Π½ΠΎΠΉ ΠΈ ΠΏΠΎΡΡΡΠ΄Π½ΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΊΠ°ΠΊ Π½Π°ΡΠΈΠ»ΠΈΠ΅ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ. ΠΠ΅ ΡΠΎΠ»ΡΠΊΠΎ Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈ ΠΎΡΡΡΠ°Π»ΡΡ
ΠΈ ΡΠ°Π·Π²ΠΈΠ²Π°ΡΡΠΈΡ
ΡΡ ΡΡΡΠ°Π½Π°Ρ
, Π³Π΄Π΅ ΠΌΠ½ΠΎΠ³ΠΎΡΠΈΡΠ»Π΅Π½Π½ΡΠ΅ ΡΠΎΡΠΌΡ ΡΡΠ΅ΠΌΠ»Π΅Π½ΠΈΡ ΠΏΡΠ°Π² Π΄Π΅ΡΠ΅ΠΉ ΠΈΠΌΠ΅ΡΡ Π³Π»ΡΠ±ΠΎΠΊΠΈΠ΅ ΠΈΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠΎΡΠ½ΠΈ, Π½ΠΎ ΠΈ Π² ΠΏΠΎΠ΄Π°Π²Π»ΡΡΡΠ΅ΠΌ Π±ΠΎΠ»ΡΡΠΈΠ½ΡΡΠ²Π΅ ΡΠ°ΠΌΡΡ
ΡΠ°Π·Π²ΠΈΡΡΡ
ΡΡΡΠ°Π½ Π·Π΅ΠΌΠ½ΠΎΠ³ΠΎ ΡΠ°ΡΠ° Π½Π°ΡΠΈΠ»ΠΈΠ΅ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ ΡΠ΅Π³ΠΎΠ΄Π½Ρ ΠΏΡΠΈΠΎΠ±ΡΠ΅Π»ΠΎ ΠΌΠ°ΡΡΠΎΠ²ΡΠ΅ ΠΈ ΠΊΠ°ΡΠ°ΡΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ°ΡΡΡΠ°Π±Ρ. ΠΡΠ»ΠΈ ΠΆΠ΅ ΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΡ Π΄ΡΠ΅Π²Π½Π΅ΠΉ ΠΌΡΠ΄ΡΠΎΡΡΠΈ, ΠΏΠΎΠ΄ΡΠ°Π·ΡΠΌΠ΅Π²Π°ΡΡΠ΅ΠΉ, ΡΡΠΎ Π·ΡΠ΅Π»ΠΎΡΡΡ Π»ΡΠ±ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΡΡΠ²Π° Π² ΠΏΠΎΠ»Π½ΠΎΠΉ ΠΌΠ΅ΡΠ΅ ΠΏΡΠΎΡΡΡΠΏΠ°Π΅Ρ ΠΏΠΎ ΡΠ΅ΠΌ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡΠΌ, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠ»ΠΎΠΆΠΈΠ»ΠΈΡΡ Π² Π½Π΅ΠΌ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ ΡΡΠ°ΡΠΈΠΊΠ°ΠΌ ΠΈ Π΄Π΅ΡΡΠΌ, ΡΠΎ Π½Π°ΠΏΡΠ°ΡΠΈΠ²Π°Π΅ΡΡΡ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ ΠΏΡΠΎΡΡΠΎΠΉ Π²ΡΠ²ΠΎΠ΄ β Π·Π΅ΠΌΠ½Π°Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΡ Π΅ΡΠ΅ Π½Π΅ Π΄ΠΎΡΠ»Π° Π΄ΠΎ ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΡ ΡΠ΅Π»ΠΎΠ³ΠΎ ΡΡΠ΄Π° Π²Π΅ΡΠ½ΡΡ
ΠΈ ΠΏΡΠΎΡΡΡΡ
ΠΈΡΡΠΈΠ½. ΠΠ΅Π΄Ρ Π»ΡΠ±ΡΠ΅ Π½Π°ΡΠΈΠ»ΡΡΡΠ²Π΅Π½Π½ΡΠ΅ Π΄Π΅ΠΉΡΡΠ²ΠΈΡ, ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ΅ΠΌΡΠ΅ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ Π² Π½Π°ΡΡΠΎΡΡΠ΅ΠΌ, ΡΠΎΠ·Π΄Π°ΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠ΅ ΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠ΅ ΠΏΡΠ΅Π΄ΠΏΠΎΡΡΠ»ΠΊΠΈ Π΄Π»Ρ Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅Π³ΠΎ Π²ΠΎΡΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° ΠΏΠΎΠ΄ΠΎΠ±Π½ΡΡ
Π΄Π΅ΠΉΡΡΠ²ΠΈΠΉ Π² ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π΅, Π½ΠΎ ΡΠΆΠ΅ ΠΏΠΎ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΠΊ Π΅ΡΠ΅ Π±ΠΎΠ»Π΅Π΅ ΠΌΠΎΠ»ΠΎΠ΄ΡΠΌ ΠΏΠΎΠΊΠΎΠ»Π΅Π½ΠΈΡΠΌ. Π ΡΡΠΎΠΌ ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ΅ ΡΠΎΠ²Π΅ΡΡΠ΅Π½Π½ΠΎ ΠΎΡΠ΅Π²ΠΈΠ΄Π½ΠΎ, ΡΡΠΎ ΡΡΡΠ΅ΡΡΠ²ΡΠ΅Ρ Π½Π°ΡΡΡΠ½Π°Ρ ΠΏΠΎΡΡΠ΅Π±Π½ΠΎΡΡΡ Π² ΠΎΠ±ΡΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΈ ΡΡΠΈΠ»ΠΈΠΉ ΠΌΠΈΡΠΎΠ²ΠΎΠ³ΠΎ ΡΠΎΠΎΠ±ΡΠ΅ΡΡΠ²Π°, Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ² ΠΈ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
Π³ΡΠ°ΠΆΠ΄Π°Π½ Π΄Π»Ρ ΡΠΎΠ³ΠΎ, ΡΡΠΎΠ±Ρ Π»ΡΠ±ΡΠ΅ Π½Π°ΡΠΈΠ»ΡΡΡΠ²Π΅Π½Π½ΡΠ΅ Π΄Π΅ΠΉΡΡΠ²ΠΈΡ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ Π±ΡΠ»ΠΈ ΠΏΡΠ΅ΠΊΡΠ°ΡΠ΅Π½Ρ ΠΈ Π°ΠΊΡΠΈΠ²Π½ΠΎ ΠΏΡΠ΅ΡΠ»Π΅Π΄ΠΎΠ²Π°Π»ΠΈΡΡ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π΄Π΅ΠΉΡΡΠ²ΡΡΡΠ΅Π³ΠΎ Π·Π°ΠΊΠΎΠ½ΠΎΠ΄Π°ΡΠ΅Π»ΡΡΡΠ²Π°, Π½ΠΎ ΠΈ Π² ΠΏΠΎΠ²ΡΠ΅Π΄Π½Π΅Π²Π½ΠΎΠΉ ΠΆΠΈΠ·Π½ΠΈ, Π³Π΄Π΅ Π·Π°ΡΠ°ΡΡΡΡ ΠΏΡΠΎΡΡΠΎ ΠΌΠΎΡΠ°Π»ΡΠ½Π°Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ° ΠΈΠ»ΠΈ ΠΎΡΡΠΆΠ΄Π΅Π½ΠΈΠ΅ ΠΈΠΌΠ΅ΡΡ Π±ΠΎΠ»ΡΡΠΎΠ΅ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΠΎΡΡΡΠ°Π΅ΡΡΡ ΠΎΡΡΡΠ°Ρ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΌΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΡΡ
ΠΈ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΡΡ
ΠΏΡΠΎΠ΅ΠΊΡΠΎΠ² ΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ, ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΡΠΎΠ±Π»ΡΠ΄Π΅Π½ΠΈΠ΅ ΠΏΡΠ°Π² Π΄Π΅ΡΠ΅ΠΉ, ΠΈΡ
Π·Π°ΡΠΈΡΡ ΠΎΡ ΠΏΡΠΎΡΠ²Π»Π΅Π½ΠΈΡ Π»ΡΠ±ΡΡ
ΡΠΎΡΠΌ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈ Π΄ΡΡ
ΠΎΠ²Π½ΠΎΠ³ΠΎ Π½Π°ΡΠΈΠ»ΠΈΡ. ΠΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅ΡΡΡ, ΡΡΠΎ Π³Π»ΡΠ±ΠΎΠΊΠΎΠ΅ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π»ΡΠ½ΠΎΠ΅ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅ Π°Π±ΡΠΎΠ»ΡΡΠ½ΠΎ Π»ΡΠ±ΡΡ
ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉ ΠΏΠΎ Π»ΠΈΠΊΠ²ΠΈΠ΄Π°ΡΠΈΠΈ Π½Π°ΡΠΈΠ»ΠΈΡ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ, ΠΊΠ°ΠΊ Π½Π΅Π³Π°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ²Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΆΠΈΠ·Π½ΠΈ, ΡΠ»ΠΎΠΆΠ½ΠΎ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΠΈΡΡ Π±Π΅Π· Π²ΡΠ΅ΡΡΠΎΡΠΎΠ½Π½Π΅ΠΉ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ ΡΡΠΎΠ»Ρ ΡΠ²ΠΎΠ΅ΠΎΠ±ΡΠ°Π·Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΏΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π½Π΅Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Π° Π±Π΅Π· ΠΏΠΎΠ΄ΡΠΎΠ±Π½ΠΎΠΉ ΠΈ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. Π Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΠΎΠ΄ΠΎΠ±Π½ΡΡ
ΡΠ²Π΅Π΄Π΅Π½ΠΈΠΉ Π²ΡΠ·ΡΠ²Π°Π΅Ρ Π±ΠΎΠ»ΡΡΠΈΠ΅ ΡΡΡΠ΄Π½ΠΎΡΡΠΈ, ΡΡΠΎ, Π΅ΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ, ΡΠΎΠ·Π΄Π°Π΅Ρ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΠΏΡΠ΅Π³ΡΠ°Π΄Ρ Π½Π° ΠΏΡΡΠΈ ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ ΠΈΡΡΠΈΠ½Π½ΡΡ
ΠΌΠ°ΡΡΡΠ°Π±ΠΎΠ² ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΈ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ Π½Π°ΡΠΈΠ»ΠΈΡ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ. ΠΠΎ ΡΠΊΠ°Π·Π°Π½Π½ΡΠΌ Π²ΡΡΠ΅ ΠΏΡΠΈΡΠΈΠ½Π°ΠΌ Π±ΠΎΠ»ΡΡΠΎΠΉ Π½Π°ΡΡΠ½ΡΠΉ ΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠ½ΠΎΠ² ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ Π½Π°ΡΠΈΠ»ΠΈΡ Π½Π°Π΄ Π΄Π΅ΡΡΠΌΠΈ, ΠΏΠΎΠ΄ΡΠ°Π·ΡΠΌΠ΅Π²Π°ΡΡΠ΅Π΅ ΠΊΠ°ΠΊ ΡΠ΅ΡΠΊΠΎΠ΅ ΡΠΎΠ»ΠΊΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ°ΠΌΠΎΠ³ΠΎ ΠΏΡΠ΅Π΄ΠΌΠ΅ΡΠ° ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ, ΡΠ°ΠΊ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠ΅ΠΉ ΠΎΡΠΎΠ±ΡΠ°Π·ΠΈΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΡΡΠΎΡΠΎΠ½Ρ ΠΈ Π°ΡΠΏΠ΅ΠΊΡΡ ΡΡΠΎΠ»Ρ ΡΠ»ΠΎΠΆΠ½ΠΎΠ³ΠΎ ΠΈ Π½Π΅Π³Π°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ²Π»Π΅Π½ΠΈΡ.
Development of statistical classifications to study the content and structure of the primary real estate market
Statistical study of the primary real estate market is always associated with the problem that the object is in a constant, and very intense change, both in quantitative terms and in its internal content. Therefore, the issues of constant adaptation of statistical methodology in relation to the primary real estate market are relevant continuously. Among the tasks that are constantly in the field of statistical science and practice in relation to the primary real estate market are the following. First, a critical analysis of the content of the modern primary real estate market, which should allow to identify its fundamental features as an object of statistical research, to systematize the economic relations of the subjects of this market segment for a comprehensive statistical analysis of its functioning and development in any region of Russia. Secondly, it is the construction of analytical classifications of the primary real estate market, systematization of criteria for their construction, which should allow for a qualitative analysis of the structure of this market segment in the modern market economy. Third, the continuous improvement of the system of statistical indicators of the primary real estate market, whichΒ should be constantly supplemented by various blocks of indicators, the use of which will link the development of the primary real estate market with indicators of the standard of living of the population and socio-economic development of a particular region on the basis of the formation and ordering of its various subsystems, which will increase their consistency with indicators of living standards and socio-economic development. To Develop the theory and statistical methodology of the complex study of the primary real estate market in terms of the development of criteria for the division of the object into homogeneous groups by typological characteristics and the construction on their basis of statistical classifications necessary for the structural analysis of the primary real estate market. To obtain scientific results in this article, General scientific methods of cognition, such as scientific abstraction, analysis and synthesis, are used, since it is a question of dividing a single whole into typologically homogeneous complexes, the organic relationship between which ensures the integrity and unity of the studied object β the primary real estate market. In addition, the use of the statistical grouping method is considered throughout the work, as it is an applied application of typological criteria. The main classification features of economic assets traded in the primary real estate market of the region are Substantiated and formulated. The development of criteria for the typological division of the object allowed to build statistical classifications necessary for a comprehensive analysis of the structure and structural changes in the primary real estate market. In the scientific article deals with the problematic aspects of a statistical study of the primary real estate market in parts of its etymology on the basis of clear criteria against which to understand the quality and properties of the traded on its economic assets, to build a statistical classification. All this is a step in the first stage of the statistical study in the sequence that is classically considered by the General theory of statistics. Statistical classifications and groupings by typological features precede the science-intensive substantiation and application of complex mathematical and static methods for factor analysis and forecasting of primary real estate market indicators
Poly-model complex in the information and analytical environment of the Situation Centre
Objective.Β The aim of this study is to develop proposals for improving decision support system, as a subsystem of information and analytical support of the Situation Centre, allowing to increase the validity, accuracy and reliability of decisions taken in modeling semi-structured systems (large-scale economic, organizational, technical or social systems), operating in conditions of significant uncertainty of the external environment and internal factors.Materials and methods.Β The basis of the study is a new paradigm the need for integration and convergence of various approaches and models (situation, simulation, expertise, cognitive, semiotic etc.), Software environments and technical solutions in the construction of information-analytical systems of Situation Centres. The analysis made it possible to justify the expediency of applying poly-model complexes with formalized decision-making procedures as part of decision support systems. When solving the problem of choosing the most preferable model, the main properties of models are evaluated, such as adequacy (qualitative and quantitative), simplicity and optimality, flexibility (adaptability), universality and problem orientation of the model. The joint use of heterogeneous models in the composition of a poly-model complex makes it possible to increase the accuracy and reliability of solving the problem of choosing the most preferable model of the object of investigation.Results.Β The necessity of integration and convergence of various approaches and models (situation, simulation, expertise, cognitive, semiotic and others) is presented in the construction of intelligent decision-making support system for the Situation Centre. Expediency description of the object under study by a set of heterogeneous and composite models with the possibility of accounting for the structural dynamics of the modeling object (organizational-technical, socio-economic systems, etc.) is shown, as well as adaptation of the modes with changes for the research object and then comparing the results obtained. An approach based on the use of poly-model complex is proposed, consisting of information analysis system of the Situation Centre that provides the synthesis of an adequate model of the study object. For this purpose, additional elements are introduced in the composition parameters and structures (redundancy) allowing for the direct use of the model to control the quality of the model, to ensure its robustness (insensitivity to changes in composition, structure and content of the original data).Β The conclusion.Β The article discusses proposals for improving the decision support system for the Situation Center, using poly-model complexes with formalized decision-making procedures. The advantage of poly-model complex is a possibility of solving the same problems with the use of different models and then comparing the results obtained, a description of the object under study by the set of heterogeneous and composite models, the possibility of taking into account the structural dynamics of the modeling object (organizational, technical, social and economic systems, and others) as well as adaptation of the model taking into account changes in the research object. The developed proposals are aimed at increasing the accuracy and reliability of the results of modeling of weakly structured systems for the validity of management decisions. The obtained results can be used to improve the scientific and methodological support of the functioning of decision support systems as an integral part of the nformation and analytical system of the Situation Centre
Peculiarities of construction of the system of indicators of the statistics of violence over children
Despite the numerous achievements and success in various spheres of human activity, the modern civilization, unfortunately, has not yet been able to completely get rid of such a serious and shameful problem as violence against children. Not only in economically backward and developing countries, where numerous forms of infringement of the childrenβs rights have deep historical roots, but in the vast majority of the most developed countries of the world, violence against children has now acquired massive and catastrophic proportions. If we follow the ancient wisdom, that the maturity of any society emerges fully in terms of the relations that have developed in it with regard to the elderly and children, then a rather simple conclusion is drawn: the earth population has not yet reached the understanding of a number of eternal and simple truths. After all, any violent actions committed against children at present create objective and subjective prerequisites for the further reproduction of such actions in the future, but in relation to even younger generations. In this context, it is quite obvious that there is an urgent need to unite the efforts of the world community, states and individual citizens to stop and actively pursue any violent actions against children not only within the framework of existing legislation, but also in everyday life, where the moral support or condemnation are of great practical importance. In addition, there is an urgent need to develop special international and state projects and programs, aimed at protecting childrenβs rights and protecting them from any form of physical and spiritual violence. It is difficult to imagine a deep substantive justification of any measures to eliminate violence against children as a negative phenomenon of public life without a comprehensive quantitative description of such a unique object of research, which by definition is impossible without detailed and reliable statistical information. At present, obtaining such information causes great difficulties, which, naturally, creates additional obstacles to the knowledge of the true extent of the spread and consequences of the violence against children. For the above reasons, it is of great scientific and practical interest to improve the methodological foundations of statistical research on violence against children, implying both a clear interpretation of the subject of cognition and the development of a modern system of indicators that allows displaying various aspects of such a complex and negative social phenomenon
Π Π²ΠΎΠΏΡΠΎΡΡ ΠΎ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ ΡΠ΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΊΠ°ΠΊ Π²ΠΈΠ΄Π° Π°ΠΊΡΠΈΠ²ΠΎΠ²
This article is devoted to the subjects of development of the directions of works on enhancement of federal statistical supervision over values. It concerns such essential units attributable to national wealth of the state as museum funds, antiques, unique collections, works of the fine arts, fund of Gokhran, diamond fund, etc. Creation of balance of assets and liabilities shall happen in the real market prices considering a large number of the parameters determining historical value of values. Research is connected with development of methodical recommendations about accounting and an assessment of values as economic assets for creation of balance of assets and liabilities. In article the main methodological problems of accounting and an assessment of values at the macrolevel are considered. The particular emphasis in article is placed on the organization of federal statistical supervision over structure and movement of values by reporting, as well as by interdepartmental flows of primary statistical information. All stages of works on the organization of accounting of values and to forming of the relevant statistical reporting are described in detail.ΠΠ°Π½Π½Π°Ρ ΡΡΠ°ΡΡΡ ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠΉ ΡΠ°Π±ΠΎΡ ΠΏΠΎ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ Π·Π° ΡΠ΅Π½Π½ΠΎΡΡΡΠΌΠΈ. ΠΠ° ΡΠ΅Π³ΠΎΠ΄Π½ΡΡΠ½ΠΈΠΉ Π΄Π΅Π½Ρ ΠΎΡΡΡΡΡΡΠ²ΡΠ΅Ρ ΡΠ΅Π°Π»ΡΠ½ΡΠΉ ΡΡΠ΅Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΡΠ΅ΠΌΡΡ
ΠΏΠΎ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π‘ΠΠ‘ ΠΊΠ°ΠΊ ΡΠ΅Π½Π½ΠΎΡΡΠΈ. ΠΡΠΎ ΠΊΠ°ΡΠ°Π΅ΡΡΡ ΡΠ°ΠΊΠΈΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ², ΠΎΡΠ½ΠΎΡΠΈΠΌΡΡ
ΠΊ Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΌΡ Π±ΠΎΠ³Π°ΡΡΡΠ²Ρ, ΠΊΠ°ΠΊ ΠΌΡΠ·Π΅ΠΉΠ½ΡΠ΅ ΡΠΎΠ½Π΄Ρ, Π°Π½ΡΠΈΠΊΠ²Π°ΡΠΈΠ°Ρ, ΡΠ½ΠΈΠΊΠ°Π»ΡΠ½ΡΠ΅ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠΈ, ΠΏΡΠΎΠΈΠ·Π²Π΅Π΄Π΅Π½ΠΈΡ ΠΈΠ·ΠΎΠ±ΡΠ°Π·ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΡΠΊΡΡΡΡΠ²Π°, Π€ΠΎΠ½Π΄ ΠΠΎΡ
ΡΠ°Π½Π°, ΠΠ»ΠΌΠ°Π·Π½ΡΠΉ ΡΠΎΠ½Π΄ ΠΈ Π΄Ρ. ΠΠΎ ΠΌΠ½Π΅Π½ΠΈΡ Π°Π²ΡΠΎΡΠΎΠ², ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠΈ Π±Π°Π»Π°Π½ΡΠ° Π°ΠΊΡΠΈΠ²ΠΎΠ² ΠΈ ΠΏΠ°ΡΡΠΈΠ²ΠΎΠ² Π² ΡΠ΅Π°Π»ΡΠ½ΡΡ
ΡΡΠ½ΠΎΡΠ½ΡΡ
ΡΠ΅Π½Π°Ρ
Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΡΠΈΡΡΠ²Π°ΡΡ Π±ΠΎΠ»ΡΡΠΎΠ΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ², ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡΠΈΡ
ΠΈΡΡΠΎΡΠΈΡΠ΅ΡΠΊΡΡ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΡΠ΅Π½Π½ΠΎΡΡΠ΅ΠΉ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠ°Π»ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΠΈΠΈ ΠΏΠΎ ΡΡΠ΅ΡΡ ΠΈ ΡΠΏΠΎΡΠΎΠ±Π°ΠΌ ΠΈΠ·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΊΠ°ΠΊ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ² Π΄Π»Ρ ΡΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΡ Π±Π°Π»Π°Π½ΡΠ° Π°ΠΊΡΠΈΠ²ΠΎΠ² ΠΈ ΠΏΠ°ΡΡΠΈΠ²ΠΎΠ². Π ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΡΡΠ΅ΡΠ° ΠΈ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠ΅Π½Π½ΠΎΡΡΠ΅ΠΉ Π½Π° ΠΌΠ°ΠΊΡΠΎΡΡΠΎΠ²Π½Π΅. ΠΡΠΎΠ±ΡΠΉ Π°ΠΊΡΠ΅Π½Ρ Π² ΡΡΠ°ΡΡΠ΅ ΡΠ΄Π΅Π»Π°Π½ Π½Π° ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ Π·Π° ΡΠΎΡΡΠ°Π²ΠΎΠΌ ΠΈ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΠ΅ΠΌ ΡΠ΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΊΠ°ΠΊ ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²ΠΎΠΌ ΠΎΡΡΠ΅ΡΠ½ΠΎΡΡΠΈ ΠΎΠ±ΡΠ΅ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ°, ΡΠ°ΠΊ ΠΈ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΌΠ΅ΠΆΠ²Π΅Π΄ΠΎΠΌΡΡΠ²Π΅Π½Π½ΡΡ
ΠΏΠΎΡΠΎΠΊΠΎΠ² ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. ΠΡ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΠΎΠ²Π°Π½Ρ Π²ΡΠ΅ ΡΡΠ°ΠΏΡ ΡΠ°Π±ΠΎΡ ΠΏΠΎ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ΅ΡΠ° ΡΠ΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΈ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠ΅ΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΡΠ΅ΡΠ½ΠΎΡΡΠΈ
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