THE IMPACT OF INSTITUTIONAL CONDITIONS ON MODERNIZATION OF STEM EDUCATION IN RUSSIAN REGIONS

2019 ◽  
Author(s):  
Liudmila Bannikova ◽  
Elena Kemmet ◽  
Elena Nidergaus
Keyword(s):  
Stem Education ◽  
Russian Regions ◽  
Institutional Conditions ◽  
The Impact

Investment climate and government turnover in russian regions

2014 ◽  
pp. 88-117 ◽  
Author(s):  
G. Syunyaev ◽  
L. Polishchuk
Keyword(s):  
Economic Development ◽  
Theoretical Model ◽  
Private Sector ◽  
Authoritarian Regimes ◽  
Russian Regions ◽  
Investment Climate ◽  
Regional Data ◽  
Endogenous Property Rights ◽  
The Impact

We study the impact of Russian regional governors’ rotation and their affiliation with private sector firms for the quality of investment climate in Russian regions. A theoretical model presented in the paper predicts that these factors taken together improve “endogenous” property rights under authoritarian regimes. This conclusion is confirmed empirically by using Russian regional data for 2002—2010; early in that period gubernatorial elections had been canceled and replaced by federal government’s appointments. This is an indication that under certain conditions government rotation is beneficial for economic development even when democracy is suppressed.

Impact of regulatory framework rigidity on poverty in the regions of Russia

2020 ◽  
pp. 62-79
Author(s):  
P. N. Pavlov
Keyword(s):  
Economic Activity ◽  
Regional Level ◽  
Institutional Factors ◽  
Federal Regulations ◽  
Russian Regions ◽  
Poverty Dynamics ◽  
Regulatory Burden ◽  
Sectoral Structure ◽  
The Impact ◽  
Regions Of Russia

The paper analyzes the impact of the federal regulatory burden on poverty dynamics in Russia. The paper provides regional level indices of the federal regulatory burden on the economy in 2008—2018 which take into account sectoral structure of regions’ output and the level of regulatory rigidity of federal regulations governing certain types of economic activity. Estimates of empirical specifications of poverty theoretical model with the inclusion of macroeconomic and institutional factors shows that limiting the scope of the rulemaking activity of government bodies and weakening of new regulations rigidity contributes to a statistically significant reduction in the level of poverty in Russian regions. Cancellation of 10% of accumulated federal level requirements through the “regulatory guillotine” administrative reform may take out of poverty about 1.1—1.4 million people.

Retrospective analysis of the resilience of Russian regions as socio-economic systems

2019 ◽  
pp. 46-64 ◽  
Author(s):  
Vladimir V. Klimanov ◽  
Sofiya М. Kazakova ◽  
Anna A. Mikhaylova
Keyword(s):  
Panel Data ◽  
Economic Systems ◽  
Financial Indicators ◽  
Russian Regions ◽  
Integral Index ◽  
Negative Effects ◽  
Economic Resilience ◽  
Correlation Dependence ◽  
The Impact ◽  
The Relationship

The article examines the impact of various socio-economic and financial indicators on the resilience of Russian regions. For each region, the integral index of resilience is calculated, and its correlation dependence with the selected indicators is revealed. The study confirms the relationship between fiscal resilience and socio-economic resilience of the regions. The analysis of panel data for 75 regions from 2007 to 2016 shows that there are significant differences in the dynamics of indicators in different periods. In particular, the degree of exposure to the negative effects of the crises of 2008—2009 and 2014—2015 in non-resilient regions is higher than in resilient ones.

On the diversity of the effects of the state support for agriculture

2019 ◽  
pp. 59-73 ◽  
Author(s):  
Nikolai M. Svetlov ◽  
Renata G. Yanbykh ◽  
Dariya A. Loginova
Keyword(s):  
Agricultural Production ◽  
The State ◽  
Russian Regions ◽  
Negative Effects ◽  
State Support ◽  
Soft Budget Constraints ◽  
Institutional Conditions ◽  
Positive Effects ◽  
Production Factors ◽  
Corporate Farms

In this paper, we assess the effects of agricultural state support of corporate farms on their revenues from agricultural production sales in 14 Russian regions that differ in technology, environment and institutional conditions. In addition to the direct effect of the state support, the indirect effects via labor and capital are revealed. For this purpose, we identify production functions and statistical models of production factors for each of these regions separately. We find out diverse effects of the state support on revenues among the regions. Positive effects prevail. Negative effects are mainly caused by labor reductions that follow subsidy inflows. Another cause of negative effects is the soft budget constraints phenomenon.

The Impact of STEM Education on Mathematical Development in Children Aged 5-6 Years

2021 ◽  
Vol 109 ◽  
pp. 101795
Author(s):  
Xinyu He ◽  
Tingting Li ◽  
Ofir Turel ◽  
Yong Kuang ◽  
Hui Zhao ◽  
...  
Keyword(s):  
Stem Education ◽  
Mathematical Development ◽  
The Impact

scholarly journals Evaluation of the impact of human capital on innovation activity in Russian regions

2021 ◽  
Vol 8 (1) ◽  
pp. 109-126
Author(s):  
Valentina Teslenko ◽  
Roman Melnikov ◽  
Damien Bazin
Keyword(s):  
Human Capital ◽  
Innovation Activity ◽  
Russian Regions ◽  
The Impact

Revealing of the specificity of mortgage housing lending based on the results of clustering of regions

2021 ◽  
Vol 27 (12) ◽  
pp. 2679-2697
Author(s):  
Lyudmila E. ROMANOVA ◽  
Anna L. SABININA ◽  
Andrei I. CHUKANOV ◽  
Dar’ya M. KORSHUNOVA
Keyword(s):  
Systems Approach ◽  
Mortgage Lending ◽  
Effective Algorithm ◽  
Russian Regions ◽  
Local Conditions ◽  
Partitioning Around Medoids ◽  
Analysis And Synthesis ◽  
The Russian Federation ◽  
The Impact ◽  
Regions Of Russia

Subject. This article deals with the particularities of the development of housing mortgage lending in the regions of Russia. Objectives. The article aims to substantiate the need for clustering of territorial entities by level of development of mortgage housing lending in Russia and test the most effective algorithm for mortgage clustering of regions. Methods. For the study, we used a systems approach, including scientific abstraction, analysis and synthesis, and statistical methods of data analysis. The algorithm k-medoids – Partitioning Around Medoids (PAM) was also used. Results. Based on the results of the study of regional statistics of the Russian Federation, the article reveals a significant asymmetry in the values of key socioeconomic indices that determine the level and dynamics of housing mortgages in the regions. This necessitates the clustering of territorial entities according to the level of development of mortgage housing lending in the country. To take into account the impact of various local conditions in assessing the prospects for the development of regional housing mortgages, the article proposes an indicator, namely, the integral regional mortgage affordability index. On its basis, in accordance with the selected clustering procedure, the article identifies five mortgage clusters in Russia and identifies their representative regions. Conclusions. Based on the analysis of the specificity of the development of regional mortgages in the Tula Oblast, taking into account the implementation of the target State programme, the article concludes that it is necessary to improve the mechanisms for financing regional mortgage programmes and justifies the need to develop differentiated programmes for the development of housing mortgages in groups of Russian regions.

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