10 research outputs found
ΠΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΡ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΈΠΉ, ΡΠ²ΡΠ·Π°Π½Π½ΡΡ Ρ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠ΅ΠΉ, ΠΈ ΠΈΡ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½Π°Ρ Π³Π΅ΡΠ΅ΡΠΎΠ³Π΅Π½Π½ΠΎΡΡΡ Π² Π ΠΎΡΡΠΈΠΈ
Received June 3, 2020; accepted August 25, 2020.ΠΠ°ΡΠ° ΠΏΠΎΡΡΡΠΏΠ»Π΅Π½ΠΈΡ 3 ΠΈΡΠ½Ρ 2020 Π³.; Π΄Π°ΡΠ° ΠΏΡΠΈΠ½ΡΡΠΈΡ ΠΊ ΠΏΠ΅ΡΠ°ΡΠΈ 25 Π°Π²Π³ΡΡΡΠ° 2020 Π³.Relevance. The spatial dimension of economic development is always in the focus of the political and research agenda. Regional disparities, along with different rates of the spread of the coronavirus pandemic and decentralization of restrictive measures, resulted in significant differences in Russian regionsβ economic responses to the pandemic. The relevance of this study is determined by the need to investigate the reasons behind these regional discrepancies. Research objective. This study aims to analyze the economic consequences of the pandemic-related restrictions and the degree of the spatial heterogeneity of these effects in Russia. Data and methods. We rely on the Rosstat data to build the indicator of the level of economic activity in Russian regions in April-May 2020. We tested the hypothesis that developed regions, large cities and small businesses will suffer more, and considered the impact of the reduced demand in world markets. The significance of the factors was tested by using regression analysis. Results. The results of our analysis have shown that economic activity in the country decreased by almost 25% due to the lockdown measures, and in some regions, the decline in production output was more than twofold. The urban economy proved to be more resilient to the restrictive measures compared to the average business activity in the country. Due to its diversified structure, the urban system has a wider adaptive capacity and survived the first period of the lockdown with less losses. SMEs, due to their flexibility and entrepreneurial initiative, supported the economies of their regions. Larger and more developed regions, all other things being equal, suffered more from the pandemic. This influence, however, was offset by other factors, and the expected trend towards spatial convergence was not observed. Conclusions. While all the previous crises that Russia experienced in the post-Soviet period were accompanied by decreasing regional discrepancies, during the COVID-19 pandemic, the spatial differences, on the contrary, increased.ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ. ΠΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°ΡΠΏΠ΅ΠΊΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π²ΡΠ΅Π³Π΄Π° Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡΡ Π² ΡΠ΅Π½ΡΡΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΡ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΎΠ² ΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π΅ΠΉ. Π Π΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡ, Π½Π°ΡΡΠ΄Ρ Ρ ΡΠ°Π·Π½ΠΎΠΉ ΡΠΊΠΎΡΠΎΡΡΡΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ ΠΊΠΎΡΠΎΠ½Π°Π²ΠΈΡΡΡΠ° ΠΈ Π΄Π΅ΡΠ΅Π½ΡΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠ΅ΠΉ ΠΎΠ³ΡΠ°Π½ΠΈΡΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΌΠ΅Ρ, ΠΏΡΠΈΠ²Π΅Π»ΠΈ ΠΊ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠΌ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΌ Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠ²Π΅ΡΠ°Ρ
ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π½Π° ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΡ. ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΡΠΈΡΠΈΠ½ ΡΡΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΡΠΈΠΉ. Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΡΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΎ Π½Π° Π°Π½Π°Π»ΠΈΠ· ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΈΠΉ, ΡΠ²ΡΠ·Π°Π½Π½ΡΡ
Ρ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠ΅ΠΉ, ΠΈ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π½Π΅ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΡΡΠΈ ΡΡΠΈΡ
ΡΡΡΠ΅ΠΊΡΠΎΠ² Π² Π ΠΎΡΡΠΈΠΈ. ΠΠ°Π½Π½ΡΠ΅ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡ ΠΎΠΏΠΈΡΠ°Π΅ΠΌΡΡ Π½Π° Π΄Π°Π½Π½ΡΠ΅ Π ΠΎΡΡΡΠ°ΡΠ° Π΄Π»Ρ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΈΠ½Π΄ΠΈΠΊΠ°ΡΠΎΡΠ° ΡΡΠΎΠ²Π½Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
Π ΠΎΡΡΠΈΠΈ Π² Π°ΠΏΡΠ΅Π»Π΅Π°Π΅ 2020 Π³ΠΎΠ΄Π°. ΠΡ ΠΏΡΠΎΠ²Π΅ΡΠΈΠ»ΠΈ Π³ΠΈΠΏΠΎΡΠ΅Π·Ρ ΠΎ ΡΠΎΠΌ, ΡΡΠΎ ΡΠ°Π·Π²ΠΈΡΡΠ΅ ΡΠ΅Π³ΠΈΠΎΠ½Ρ, ΠΊΡΡΠΏΠ½ΡΠ΅ Π³ΠΎΡΠΎΠ΄Π° ΠΈ ΠΌΠ°Π»ΡΠΉ Π±ΠΈΠ·Π½Π΅Ρ ΠΏΠΎΡΡΡΠ°Π΄Π°ΡΡ Π² Π½Π°ΠΈΠ±ΠΎΠ»ΡΡΠ΅ΠΉ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ, ΠΈ ΡΡΠ»ΠΈ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠΏΡΠΎΡΠ° Π½Π° ΠΌΠΈΡΠΎΠ²ΡΡ
ΡΡΠ½ΠΊΠ°Ρ
. ΠΠ½Π°ΡΠΈΠΌΠΎΡΡΡ ΡΠ°ΠΊΡΠΎΡΠΎΠ² ΠΏΡΠΎΠ²Π΅ΡΡΠ»Π°ΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠ½Π°Π»ΠΈΠ· ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠ°Ρ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ Π² ΡΡΡΠ°Π½Π΅ ΡΠ½ΠΈΠ·ΠΈΠ»Π°ΡΡ ΠΏΠΎΡΡΠΈ Π½Π° 25% ΠΈΠ·-Π·Π° ΠΎΠ³ΡΠ°Π½ΠΈΡΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΌΠ΅Ρ, Π° Π² Π½Π΅ΠΊΠΎΡΠΎΡΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
ΠΏΠ°Π΄Π΅Π½ΠΈΠ΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° Π±ΡΠ»ΠΎ Π±ΠΎΠ»Π΅Π΅ ΡΠ΅ΠΌ Π΄Π²ΡΠΊΡΠ°ΡΠ½ΡΠΌ. ΠΠΎΡΠΎΠ΄ΡΠΊΠ°Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠ° ΠΎΠΊΠ°Π·Π°Π»Π°ΡΡ Π±ΠΎΠ»Π΅Π΅ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΠΉ ΠΊ ΠΎΠ³ΡΠ°Π½ΠΈΡΠΈΡΠ΅Π»ΡΠ½ΡΠΌ ΠΌΠ΅ΡΠ°ΠΌ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠΎ ΡΡΠ΅Π΄Π½Π΅ΠΉ Π΄Π΅Π»ΠΎΠ²ΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡΡ Π² ΡΡΡΠ°Π½Π΅. ΠΠ»Π°Π³ΠΎΠ΄Π°ΡΡ ΡΠ²ΠΎΠ΅ΠΉ Π΄ΠΈΠ²Π΅ΡΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΠ΅ Π³ΠΎΡΠΎΠ΄ΡΠΊΠ°Ρ ΡΠΈΡΡΠ΅ΠΌΠ° ΠΎΠ±Π»Π°Π΄Π°Π΅Ρ Π±ΠΎΠ»Π΅Π΅ ΡΠΈΡΠΎΠΊΠΎΠΉ Π°Π΄Π°ΠΏΡΠΈΠ²Π½ΠΎΠΉ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΡΡ ΠΈ ΠΏΠ΅ΡΠ΅ΠΆΠΈΠ»Π° ΠΏΠ΅ΡΠ²ΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΈΠ·ΠΎΠ»ΡΡΠΈΠΈ Ρ ΠΌΠ΅Π½ΡΡΠΈΠΌΠΈ ΠΏΠΎΡΠ΅ΡΡΠΌΠΈ. ΠΠ‘Π, Π±Π»Π°Π³ΠΎΠ΄Π°ΡΡ ΡΠ²ΠΎΠ΅ΠΉ Π³ΠΈΠ±ΠΊΠΎΡΡΠΈ ΠΈ ΠΏΡΠ΅Π΄ΠΏΡΠΈΠ½ΠΈΠΌΠ°ΡΠ΅Π»ΡΡΠΊΠΎΠΉ ΠΈΠ½ΠΈΡΠΈΠ°ΡΠΈΠ²Π΅, ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΈΠ²Π°Π»ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΡ ΡΠ²ΠΎΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ². ΠΠΎΠ»Π΅Π΅ ΠΊΡΡΠΏΠ½ΡΠ΅ ΠΈ ΡΠ°Π·Π²ΠΈΡΡΠ΅ ΡΠ΅Π³ΠΈΠΎΠ½Ρ, ΠΏΡΠΈ ΠΏΡΠΎΡΠΈΡ
ΡΠ°Π²Π½ΡΡ
, Π±ΠΎΠ»ΡΡΠ΅ ΠΏΠΎΡΡΡΠ°Π΄Π°Π»ΠΈ ΠΎΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ. ΠΠ΄Π½Π°ΠΊΠΎ ΡΡΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π±ΡΠ»ΠΎ ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½ΠΎ Π΄ΡΡΠ³ΠΈΠΌΠΈ ΡΠ°ΠΊΡΠΎΡΠ°ΠΌΠΈ, ΠΈ ΠΎΠΆΠΈΠ΄Π°Π΅ΠΌΠΎΠΉ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΈ ΠΊ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΊΠΎΠ½Π²Π΅ΡΠ³Π΅Π½ΡΠΈΠΈ Π½Π΅ Π½Π°Π±Π»ΡΠ΄Π°Π»ΠΎΡΡ. ΠΡΠ²ΠΎΠ΄Ρ. ΠΡΠ»ΠΈ Π²ΡΠ΅ ΠΏΡΠ΅Π΄ΡΠ΄ΡΡΠΈΠ΅ ΠΊΡΠΈΠ·ΠΈΡΡ, ΠΊΠΎΡΠΎΡΡΠ΅ Π ΠΎΡΡΠΈΡ ΠΏΠ΅ΡΠ΅ΠΆΠΈΠ»Π° Π² ΠΏΠΎΡΡΡΠΎΠ²Π΅ΡΡΠΊΠΈΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄, ΡΠΎΠΏΡΠΎΠ²ΠΎΠΆΠ΄Π°Π»ΠΈΡΡ ΡΠΎΠΊΡΠ°ΡΠ΅Π½ΠΈΠ΅ΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΡΠΈΠΉ, ΡΠΎ Π²ΠΎ Π²ΡΠ΅ΠΌΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19 ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡ, Π½Π°ΠΎΠ±ΠΎΡΠΎΡ, ΡΠ²Π΅Π»ΠΈΡΠΈΠ»ΠΈΡΡ.The research was supported by the Russian Foundation for Basic Research, Project 19-010-00094 βSpatial Development of Modern Russia: Trends, Factors, and Mechanismsβ.Π Π°Π±ΠΎΡΠ° Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π° ΠΏΡΠΈ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ΅ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠΎΠ½Π΄Π° ΡΡΠ½Π΄Π°ΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, ΠΏΡΠΎΠ΅ΠΊΡ 19-010-00094 Β«ΠΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π ΠΎΡΡΠΈΠΈ: ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΈ, ΡΠ°ΠΊΡΠΎΡΡ ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡΒ»
Assessment of the Impact of Agglomeration Factors on the Economic Activity: Microeconomic Analysis
ΠΠ³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΡΡΠ΅ΠΊΡΡ ΡΠ²Π»ΡΡΡΡΡ Π²Π°ΠΆΠ½ΡΠΌ ΡΠ²ΠΎΠΉΡΡΠ²ΠΎΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ΅Π΄Ρ, ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡΠΈΠΌ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π±ΠΈΠ·Π½Π΅ΡΠ° ΠΎ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΠΈ ΠΈ ΠΎ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΏΡΠΎΠ΅ΠΊΡΠΎΠ², Π΄Π»Ρ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ Π²ΠΎΡΡΠΎΠΊΠ° Π ΠΎΡΡΠΈΠΈ ΠΈΡ
ΠΏΡΠΎΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΡΠ°Π²ΠΈΡΡΡ ΠΏΠΎΠ΄ ΡΠΎΠΌΠ½Π΅Π½ΠΈΠ΅. ΠΠΎΠ²ΠΎΡΠΈΠ±ΠΈΡΡΠΊΠ°Ρ ΠΎΠ±Π»Π°ΡΡΡ ΠΈΠΌΠ΅Π΅Ρ ΡΠΎΡΠ΅ΡΠ°Π½ΠΈΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΡΠ°Π·Π²ΠΈΡΠΈΡ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ ΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ ΠΏΡΠΎΡΠΈΠ²ΠΎΡΠ΅ΡΠΈΠ²ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠΈΠ»Ρ. Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ ΡΠΎΡΡΠΎΡΠ»Π° Π² ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠΈ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΎΡΠ΅Π½ΠΎΠΊ Π²Π»ΠΈΡΠ½ΠΈΡ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΡΡΠ΅ΠΊΡΠΎΠ² Π½Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ. ΠΡΡΠΎΡΠ½ΠΈΠΊΠΎΠΌ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π²ΡΡΡΡΠΏΠ°Π»Π° Π±Π°Π·Π° Π΄Π°Π½Π½ΡΡ
Π‘ΠΠΠ Π-ΠΠ½ΡΠ΅ΡΡΠ°ΠΊΡ Π·Π° 2019 Π³. ΠΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° Π²ΠΊΠ»ΡΡΠ°Π»ΠΈ ΡΡΠ΅Π΄ΡΡΠ²Π° Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π²ΡΠ±ΠΎΡΠΊΠΈ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ, ΡΡΠ΅Π΄Π½ΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π²ΡΠΏΡΡΠΊΠ° ΠΈ ΠΏΡΠΈΠ±ΡΠ»ΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· Π²Π»ΠΈΡΠ½ΠΈΡ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΡΠ°Π±ΠΎΡΡ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΌΠΈΠΊΡΠΎΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠ΄ΠΈΠ»ΠΈ Π·Π½Π°ΡΠΈΠΌΡΠΉ Π²ΠΊΠ»Π°Π΄ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΡΡΠ΅ΠΊΡΠΎΠ² Π² ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΈΡΠΌ ΠΠΎΠ²ΠΎΡΠΈΠ±ΠΈΡΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ. Π ΠΎΡΡ ΡΠ°ΡΡΡΠΎΡΠ½ΠΈΡ Π΄ΠΎ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΉ ΡΡΠΎΠ»ΠΈΡΡ Π² 2 ΡΠ°Π·Π° ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ ΡΠΎΠΊΡΠ°ΡΠ΅Π½ΠΈΡ Π²ΡΠΏΡΡΠΊΠ° ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ΅Π½ΡΠ°Π±Π΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ Π½Π° 3,5 %. ΠΠ°ΠΌΠ΅ΡΠ½ΡΠΉ Π²ΠΊΠ»Π°Π΄ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π² ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°Π±ΠΎΡΡ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉ ΠΠΎΠ²ΠΎΡΠΈΠ±ΠΈΡΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π°ΡΠ³ΡΠΌΠ΅Π½ΡΠΎΠΌ Π² ΠΏΠΎΠ»ΡΠ·Ρ ΠΈΠ½ΠΈΡΠΈΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ°ΡΡΠ½ΡΡ
ΠΈ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΡΡ
ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΏΡΠΎΠ΅ΠΊΡΠΎΠ². ΠΠ½Π°Π»ΠΈΠ· ΡΠ°ΠΊΠΆΠ΅ ΠΏΠΎΠΊΠ°Π·Π°Π» Π±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΡΡ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°ΡΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΡΠΈΠ±ΡΠ»ΠΈ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ Π² Π³ΠΎΡΠΎΠ΄Π°Ρ
ΠΈ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΠΏΠ°Π΄Π΅Π½ΠΈΠ΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠΈΡΠΌ Π² Π±Π»ΠΈΠΆΠ°ΠΉΡΠ΅ΠΌ ΠΎΠΊΡΡΠΆΠ΅Π½ΠΈΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΉ ΡΡΠΎΠ»ΠΈΡΡ. ΠΡΡΠ²Π»Π΅Π½Π½ΡΠ΅ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ Π½Π΅ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ, Π²Ρ
ΠΎΠ΄ΡΡΠΈΡ
Π² ΠΠΎΠ²ΠΎΡΠΈΠ±ΠΈΡΡΠΊΡΡ ΠΎΠ±Π»Π°ΡΡΡ, ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΏΠΎΠ»Π΅Π·Π½ΡΠΌΠΈ Π΄Π»Ρ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΠΈ ΠΌΠ΅ΡΡΠ½ΡΡ
ΠΎΡΠ³Π°Π½ΠΎΠ² Π²Π»Π°ΡΡΠΈ ΠΏΡΠΈ ΠΏΡΠΈΠ½ΡΡΠΈΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΉ ΠΎ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ΅ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΠΈ Π±ΠΈΠ·Π½Π΅ΡΠ°.While agglomeration effects are an essential element of the economic environment determining the decision-making on the capacity allocation and implementation of infrastructure projects, their impact in the East of Russia is questioned. Development conditions of Novosibirsk oblast can have a contradictory effect on agglomeration forces. The paper aims to obtain quantitative estimates of the impact of agglomeration effects on enterprise performance by analysing the SPARK-Interfax database for 2019. To this end, the visualisation of the spatial distribution of the sample data, average output and profit characteristics was performed. Additionally, the econometric analysis of the influence of agglomeration factors on enterprise performance was conducted. As a result, the microeconomic analysis showed a statistically significant impact of agglomeration effects on the productivity of firms in Novosibirsk oblast. A two-fold increase in the distance to the regional capital leads to a reduction in output and profitability of enterprises by 3.5 %. This finding supports the development and implementation of private and public infrastructure projects. The analysis demonstrated a higher differentiation of profit indicators in cities, as well as a significant drop in performance and efficiency of companies located in the immediate neighbourhood of the regional capital. The revealed patterns characterising the heterogeneous functioning of Novosibirsk economy can be considered by regional and local authorities when making decisions to support and develop business.Π€ΠΈΠ½Π°Π½ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΠΎ Π³ΡΠ°Π½ΡΡ Π ΠΠ€ β 23-28-10007 Β«ΠΡΠ΅Π½ΠΊΠ° ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΠΎΠ²ΠΎΡΠΈΠ±ΠΈΡΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ Π±Π°Π· ΠΌΠΈΠΊΡΠΎΠ΄Π°Π½Π½ΡΡ
, Π³Π΅ΠΎΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ ΠΈ Π°ΠΏΠΏΠ°ΡΠ°ΡΠ° ΡΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡΒ» ΠΈ ΠΡΠ°Π²ΠΈΡΠ΅Π»ΡΡΡΠ²Π° ΠΠΎΠ²ΠΎΡΠΈΠ±ΠΈΡΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ (Π‘ΠΎΠ³Π»Π°ΡΠ΅Π½ΠΈΠ΅ 00 00005406995998235120662/β Ρ-54).The article has been prepared with the support of the Russian Scientific Foundation, the project No. 23-28-10007 βAssessment and forecasting of the spatial development of the Novosibirsk region based on the integration of microdata databases, geoinformation systems and econometric modeling apparatusβ and the Government of the Novosibirsk Region (Agreement 0000005406995998235120662/ no. r-54). The authors would like to thank Andrey Kostin, Cand. Sci. (Econ.), Senior Research Associate of IEIE SB RAS for the provided program to work with the SPARK database
Interregional Disparities in Russia: Economic and Social Aspects
The dynamics of interregional differences in Russia by the following three indicators is analyzed: the gross regional product, monetary incomes of the population, and fiscal capacity. Estimations of - convergence and betaβconvergence for the period of 1995-2007 are used
PROBLEMS OF TAX BUDGET REVENUE FORECASTING IN RUSSIA
The paper consider the methodological problems of forecasting of tax budget revenues in Russia. The particular attention is paid to the usage of time series analysis and to the discussion of issues related to benchmarking, Β«edge effectsΒ», structural and cycle components of tax revenue. It is concluded that the objective limitation for the correct and reliable long-term forecasting is the lack of sufficiently long time series of comparable data. Forecasting time horizon should correspond to the period for which trends are identified and parameters of the dynamics are estimated. Short-term forecasts have the necessary information, and they can be used in the practical work of public authorities
Russian "Macro-regions": Economic integration and interaction with the world economy: Final Report
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190
NATIONAL DIVERSITY AND ECONOMIC DEVELOPMENT IN RUSSIAN REGION
The paper discusses the impact of national diversity on economic development and presents a detailed review of foreign studies, which serves as a basis for the formulation of testable hypotheses. The ethnic structure of the Russian regions population is analyzed based on the censuses data for 2002 and 2010; the fractionalization index, entropy and polarization indexes are used. The analysis of these characteristics shows that, despite the more active migration processes in modern Russia, there have been no major changes in the ethnic composition of the population of the regions. At the same time, a wide variety of the national structures is observed in the regions. The impact of the national heterogeneity on economic development is estimated using regression analysis. We run panel regression of the regional value added on labor, capital, control variables, and on the indexes of the national heterogeneity. The results showed: 1) the absence of noticeable changes in the national structure in the observed period; 2) the positive impact of ethnic diversity on economic development; 3) the absence of a statistically significant relationship between the ethnic polarization and development
Π Π΅ΡΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π° ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π² Π―ΠΊΡΡΠΈΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠ΅ΡΠ΅ΠΏΠΈΡΠ΅ΠΉ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ
The article assesses the intensity of transformation of settlement pattern in Yakutia, the largest northern region of Russia, based on an analysis of 1939-2010 censuses and contemporary statistics. Scope of the work includes the following: to assess key socio-economic results of rural and urban settlement pattern transformation in the 20th century, to determine the most persistent primary units of settlement pattern, and to identify current trends in the settlement pattern of Yakutia. The research database was built based on digitization of Federal State Statistics Service in the Sakha Republic (Yakutia) population censuses archives. The period under review shows a trend toward larger size of settlements due to two parallel processes: urbanization as a result of industrial development, and compression of rural settlement system due to amalgamation of rural settlements. From 1939 to the present time, Yakutiaβs settlement system has been evolving from dispersed type to large settlement type. There were two major waves in the structuring of space in Yakutia. During the first one, caused by industrialization and complete collectivization, shrinking of rural settlement system was accompanied by setup of rural and urban settlements; it started in the 1930s and lasted until late 1950s. The second wave, concurrent with controlled compression of rural settlement pattern as part of elimination of unpromising sovkhoz state farms, was associated with a full-scale development of urban settlement pattern under planned Soviet deployment. Starting from 2002, market mechanisms have changed the direction of development of settlement system and spatial structure of economic activity. Despite several constraints, which include high transportation costs, focal development, key role of mining and resource sector, distinctive features of traditional economies and agriculture, agglomeration processes have gained momentum in the region. Spatial concentration of population is taking place at relatively high rates, primarily in the core of the system - Yakutsk agglomeration. Compression capacity of settlement system in the region is far from being exhausted, as evidenced by behavior of Theil and Herfindahl-Hirschman indices, as well as by average population density of settlements.Π‘ΡΠ°ΡΡΡ ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π² Π―ΠΊΡΡΠΈΠΈ, ΠΊΡΡΠΏΠ½Π΅ΠΉΡΠ΅ΠΌ ΡΠ΅Π²Π΅ΡΠ½ΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π ΠΎΡΡΠΈΠΈ, Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠ΅ΡΠ΅ΠΏΠΈΡΠ΅ΠΉ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ 1939-2010 Π³Π³. ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ. ΠΠ°Π΄Π°ΡΠΈ ΡΠ°Π±ΠΎΡΡ Π²ΠΊΠ»ΡΡΠ°ΡΡ ΠΎΡΠ΅Π½ΠΊΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΠΈ Π³ΠΎΡΠΎΠ΄ΡΠΊΠΎΠ³ΠΎ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π² XX Π²Π΅ΠΊΠ΅, ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΡΡΠΎΠΉΡΠΈΠ²ΡΡ
ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ
Π΅Π΄ΠΈΠ½ΠΈΡ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ, Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΠ΅ΠΊΡΡΠΈΡ
ΡΡΠ΅Π½Π΄ΠΎΠ² Π² ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΠΈ Π―ΠΊΡΡΠΈΠΈ. Π€ΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π±Π°Π·Ρ Π΄Π°Π½Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»ΠΎΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΡΠΈΡΡΠΎΠ²ΠΊΠΈ Π°ΡΡ
ΠΈΠ²ΠΎΠ² ΠΏΠ΅ΡΠ΅ΠΏΠΈΡΠ΅ΠΉ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π‘Π°Ρ
Π°(Π―ΠΊΡΡΠΈΡ)ΡΡΠ°ΡΠ°. Π ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΏΡΠΎΡΠ»Π΅ΠΆΠΈΠ²Π°Π΅ΡΡΡ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡ ΠΊ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ ΡΠ°Π·ΠΌΠ΅ΡΠ° Π½Π°ΡΠ΅Π»Π΅Π½Π½ΡΡ
ΠΏΡΠ½ΠΊΡΠΎΠ² Π²ΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠ΅ Π΄Π²ΡΡ
ΠΏΠ°ΡΠ°Π»Π»Π΅Π»ΡΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ²: ΡΡΠ±Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ ΠΊΠ°ΠΊ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ° ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΡΠ²ΠΎΠ΅Π½ΠΈΡ ΠΈ ΡΠΆΠ°ΡΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π·Π° ΡΡΠ΅Ρ ΡΠΊΡΡΠΏΠ½Π΅Π½ΠΈΡ ΡΠ΅Π»ΡΡΠΊΠΈΡ
ΠΏΠΎΡΠ΅Π»Π΅Π½ΠΈΠΉ. Π‘ 1939 Π³. ΠΏΠΎ Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΡΠΈΡΡΠ΅ΠΌΠ° ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π―ΠΊΡΡΠΈΠΈ ΡΠ²ΠΎΠ»ΡΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π»Π° ΠΎΡ Π΄ΠΈΡΠΏΠ΅ΡΡΠ½ΠΎΡΡΠΈ ΠΊ ΠΊΡΡΠΏΠ½ΠΎΡΠ΅Π»Π΅Π½Π½ΠΎΡΡΠΈ. ΠΡΠ΄Π΅Π»ΡΡΡΡΡ Π΄Π²Π΅ Π±ΠΎΠ»ΡΡΠΈΡ
Π²ΠΎΠ»Π½Ρ Π² ΡΡΡΡΠΊΡΡΡΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π° Π―ΠΊΡΡΠΈΠΈ. Π Ρ
ΠΎΠ΄Π΅ ΠΏΠ΅ΡΠ²ΠΎΠΉ, Π²ΡΠ·Π²Π°Π½Π½ΠΎΠΉ ΠΈΠ½Π΄ΡΡΡΡΠΈΠ°Π»ΠΈΠ·Π°ΡΠΈΠ΅ΠΉ ΠΈ ΡΠΏΠ»ΠΎΡΠ½ΠΎΠΉ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠ²ΠΈΠ·Π°ΡΠΈΠ΅ΠΉ, ΡΠΊΡΡΠΏΠ½Π΅Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ ΡΠΎΠΏΡΠΎΠ²ΠΎΠΆΠ΄Π°Π»ΠΎΡΡ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠ΅Π»ΡΡΠΊΠΈΡ
ΠΈ Π³ΠΎΡΠΎΠ΄ΡΠΊΠΈΡ
Π½Π°ΡΠ΅Π»Π΅Π½Π½ΡΡ
ΠΏΡΠ½ΠΊΡΠΎΠ²; ΠΎΠ½Π° Π½Π°ΡΠ°Π»Π°ΡΡ Π² 1930-Ρ
Π³ΠΎΠ΄Π°Ρ
ΠΈ ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠ°Π»Π°ΡΡ Π²ΠΏΠ»ΠΎΡΡ Π΄ΠΎ ΠΊΠΎΠ½ΡΠ° 1950-Ρ
Π³ΠΎΠ΄ΠΎΠ². ΠΡΠΎΡΠ°Ρ Π²ΠΎΠ»Π½Π° Π½Π° ΡΠΎΠ½Π΅ ΠΊΠΎΠ½ΡΡΠΎΠ»ΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΡΠΆΠ°ΡΠΈΡ ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π»ΠΈΠΊΠ²ΠΈΠ΄Π°ΡΠΈΠΈ Π½Π΅ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΡΡ
ΡΠΎΠ²Ρ
ΠΎΠ·ΠΎΠ² Π±ΡΠ»Π° ΡΠ²ΡΠ·Π°Π½Π° Ρ ΠΏΠΎΠ»Π½ΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΡΠΌ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ΠΌ Π³ΠΎΡΠΎΠ΄ΡΠΊΠΎΠ³ΠΎ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π² Ρ
ΠΎΠ΄Π΅ ΠΏΠ»Π°Π½ΠΎΠ²ΠΎΠ³ΠΎ ΡΠΎΠ²Π΅ΡΡΠΊΠΎΠ³ΠΎ ΠΎΡΠ²ΠΎΠ΅Π½ΠΈΡ. ΠΠ°ΡΠΈΠ½Π°Ρ Ρ 2002 Π³. ΡΡΠ½ΠΎΡΠ½ΡΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡ ΠΈΠ·ΠΌΠ΅Π½ΠΈΠ»ΠΈ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ. ΠΠ΅ΡΠΌΠΎΡΡΡ Π½Π° ΡΡΠ΄ ΡΠ΄Π΅ΡΠΆΠΈΠ²Π°ΡΡΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ², ΠΊΠΎΡΠΎΡΡΠ΅ Π²ΠΊΠ»ΡΡΠ°ΡΡ Π²ΡΡΠΎΠΊΠΈΠ΅ ΡΡΠ°Π½ΡΠΏΠΎΡΡΠ½ΡΠ΅ ΠΈΠ·Π΄Π΅ΡΠΆΠΊΠΈ, ΠΎΡΠ°Π³ΠΎΠ²ΡΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ ΠΎΡΠ²ΠΎΠ΅Π½Π½ΠΎΡΡΠΈ, Π±ΠΎΠ»ΡΡΡΡ ΡΠΎΠ»Ρ Π΄ΠΎΠ±ΡΠ²Π°ΡΡΠΈΡ
ΠΎΡΡΠ°ΡΠ»Π΅ΠΉ ΠΈ ΡΠ΅ΡΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΠΊΡΠΎΡΠ°, ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΡ
ΠΏΡΠΎΠΌΡΡΠ»ΠΎΠ² ΠΈ ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π°, Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π° ΠΏΠΎΠ»ΡΡΠΈΠ»ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΏΡΠΎΡΠ΅ΡΡΡ. ΠΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎ Π±ΡΡΡΡΡΠΌΠΈ ΡΠ΅ΠΌΠΏΠ°ΠΌΠΈ ΠΈΠ΄Π΅Ρ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½Π°Ρ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΠΏΡΠ΅ΠΆΠ΄Π΅ Π²ΡΠ΅Π³ΠΎ Π² ΡΠ΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΌ ΡΠ΄ΡΠ΅ - Π―ΠΊΡΡΡΠΊΠΎΠΉ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΈ. ΠΠΎΡΠ΅Π½ΡΠΈΠ°Π» ΡΠΆΠ°ΡΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠ°ΡΡΠ΅Π»Π΅Π½ΠΈΡ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π΄Π°Π»Π΅ΠΊΠΎ Π½Π΅ ΠΈΡΡΠ΅ΡΠΏΠ°Π½, ΠΎ ΡΠ΅ΠΌ ΡΠ²ΠΈΠ΄Π΅ΡΠ΅Π»ΡΡΡΠ²ΡΠ΅Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΠΈΠ½Π΄Π΅ΠΊΡΠΎΠ² Π’Π΅ΠΉΠ»Π° ΠΈ Π₯Π΅ΡΡΠΈΠ½Π΄Π°Π»Ρ-Π₯ΠΈΡΡΠΌΠ°Π½Π°, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΡΠ΅Π΄Π½Π΅ΠΉ Π»ΡΠ΄Π½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½Π½ΡΡ
ΠΏΡΠ½ΠΊΡΠΎΠ²