6 research outputs found
Impact of contemporary pension reforms on householdsβ welfare
Purpose: Identification and assessment of the consequences of raising the retirement age and possible changes in the householdsβ welfare because a part of the pre-retirement age population will remain in the labor force five years longer. Design/Methodology/Approach: The initial data for the analysis and modeling are the data of a representative survey on the βRussian Longitudinal Monitoring Survey - HSEβ project for 2017. The object of the analysis were women aged 55 and older and men of 60 years and older. Microsimulation was carried out, that is all men aged from 60 to 65 and women from 55 to 60 were conditionally transferred to the working population, and changes in their employment and incomes were estimated. Based on the econometric model, an assessment of factors that are incentives to continue working after retirement has been obtained. Results: The presented calculations indicated the fact that despite an increase in the labor supply due to an increase of the retirement age, no employment surplus in the labor market is foreseen. Currently, the poverty level among retired households is significantly lower than the average one, and this trend will continue in the future. Practical implications: The results are important for the adjustment of social policy for retirees. Originality/Value: The study revealed the following new trends: 1) with the growth of the educational level, the probability of employment after the retirement age increases; 2) all other things being equal, women after retirement have a greater chance of being employed than men do; 3) for the majority of retirees employment is not traumatic.The reported study was funded by RFBR according to the research project β19-010-00009.peer-reviewe
Inter-vulnerability of financial institutions and households in the system of national financial security assessment
Purpose: The aim of this article is to study the concept of financial institutions and households' interrelation of vulnerabilities to the risk of money laundering and the integration of this concept into the methodology of a national ML/TF (Money Laundering and Terrorist Financing) risk assessment.
Design/Methodology/Approach: At the theoretical and methodological levels, authors utilized a risk-based approach, which involves the separation of the object of study in risk levels and its impact on each risk level. At the methodological and analytical levels, authors utilized methods of grouping, descriptive analysis, comparison, synthesis, and graphic visualization of data.
Findings: The most significant scientific results obtained in the course of the study include: proprietary algorithm for calculating the intensity coefficient of threats to national financial security, which practical approval on data of 27 countries allowed determining the structure of threats to financial security in the international landscape in the period 2013-2018; originally developed questionnaire on the assessment of the risks of deviations in the financial behavior of households and individuals.
Originality/Value: The key findings are targeted at their widespread application in assessing money laundering risks at the national and international levels, in developing strategic documents on the development of systems to fight money laundering and terrorist financing. The methodology for identifying the propensity to deviations of financial behavior, based on a questionnaire survey, could serve as the basis for developing scoring systems.The research was supported by Russian Foundation for Basic Research # 18-010-00657.peer-reviewe
Determinants of householdsβ credit behavior in Russia
Purpose: The main goal of this work is to substantiate the need to consider microeconomic statistics when analyzing consumer lending to the population, as well as implementing approaches to modeling household credit behavior at the micro level.
Design/Methodology/Approach: The article proposes and implements a comprehensive statistical approach that allows identifying the specificity of the influence of demographic, socio-economic characteristics of households on their credit activity.
Findings: The article states that loan borrowings are more often found in households with children of preschool age who are in relatively high-income groups, who much more often inform about cash incomes that do not correspond to the declared level of consumption. Members of these households are more likely to work. The age range of borrowers expanded during the study period, and no prevalence of any age group was observed.
Practical Implications: This result is of great practical importance, since, as already indicated, in assessing the solvency of the borrower, credit organizations are mainly focused on individual characteristics.
Originality/value: It was found that the hypothesis that individual characteristics are important determinants of household lending activity has not been confirmed. And variables that characterize households significantly affect their credit behavior.peer-reviewe
Influence ΞΏf householdsβ borrowings ΞΏn consumer spending during the escalation of the crisis
This article investigates the relationship between the borrowing activity of Russian households and their current conumer expendatures in the period of escalation of the social and economic crisis.
The analysis was conducted on the basis of data provided by the Russian Longitudinal Monitoring Survey, RLMS-HSE for 2015.
The paper proposes and implements an approach that makes it possible to assess the impact of borrowings on inequality in consumption and poverty among households.
It was revealed that the need of repayment results in saving on food, medical treatment and other vital needs for an overwhelming number of households. This is especially acute among families being beyond the poverty threshold.peer-reviewe
ΠΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΠΊΡΠ΅Π΄ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π½Π° ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΠ΅ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ Ρ ΠΎΠ·ΡΠΉΡΡΠ²: ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅
This article presents qualitative characteristics of the impact consumer crediting has on household consumption. The research was conducted on the basis of empirical data and methods of mathematical statistics. The assessment of the impact of credit debt on the volume of consumption elasticity was carried out using the equation of multiple regression, where consumer expenses of a household -are dependent variables, and the size of credit exposure, calculated as the relation of credit payments to the available resources of households, and some other characteristics of households - are regressors. In the introductory part the author proves the importance of determining the mechanisms for smoothing the consumption amid growing household expenditures on payments for credits. The first section of the article analyses data sources used in the authorβs models and describes the Russian monitoring of economic situation and health of the population of the Higher School of Economics (RLMS-HSE) (from 2006 to 2013). The second section depicts modern global trends and Russian situation in credit debt of households, while the third section comments on statistics of their credit load. The forth and final section presents models demonstrating the magnitude of credit load in regard to householdsβ consumption. The essence of the authorβs position is that determining the consumption smoothing mechanisms with increasing household expenditures on payments for credits; clarifying the structure of households prone to borrowing, and households with an altered revenue and expenditure structure create a foundation for developing the policy of compliance between interests of financial institutions and general public.ΠΠ²ΡΠΎΡΠΎΠΌ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΌΠΏΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
ΠΈ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ Π΄Π°ΡΡΡΡ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΊΡΠ΅Π΄ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π½Π° ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΠ΅ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
Ρ
ΠΎΠ·ΡΠΉΡΡΠ². ΠΡΠ΅Π½ΠΊΠ° Π²Π»ΠΈΡΠ½ΠΈΡ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠΉ Π·Π°Π΄ΠΎΠ»ΠΆΠ΅Π½Π½ΠΎΡΡΠΈ Π½Π° Π²Π΅Π»ΠΈΡΠΈΠ½Ρ ΡΠ»Π°ΡΡΠΈΡΠ½ΠΎΡΡΠΈ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²Π΅Π΄Π΅Π½Π° Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ, Π² ΠΊΠΎΡΠΎΡΠΎΠΌ Π·Π°Π²ΠΈΡΠΈΠΌΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π²ΡΡΡΡΠΏΠ°ΡΡ ΠΏΠΎΡΡΠ΅Π±ΠΈΡΠ΅Π»ΡΡΠΊΠΈΠ΅ ΡΠ°ΡΡ
ΠΎΠ΄Ρ Π΄ΠΎΠΌΠ°ΡΠ½Π΅Π³ΠΎ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π°, a Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΠ΅Π³ΡΠ΅ΡΡΠΎΡΠΎΠ² - Π²Π΅Π»ΠΈΡΠΈΠ½Π° ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΈ, Π²ΡΡΠΈΡΠ»Π΅Π½Π½Π°Ρ ΠΊΠ°ΠΊ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅ Π²ΡΠΏΠ»Π°Ρ ΠΏΠΎ ΠΊΡΠ΅Π΄ΠΈΡΡ ΠΊ ΡΠ°ΡΠΏΠΎΠ»Π°Π³Π°Π΅ΠΌΡΠΌ ΡΠ΅ΡΡΡΡΠ°ΠΌ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
Ρ
ΠΎΠ·ΡΠΉΡΡΠ², a ΡΠ°ΠΊΠΆΠ΅ ΡΡΠ΄ Π΄ΡΡΠ³ΠΈΡ
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Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
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ΠΎΠ·ΡΠΉΡΡΠ². ΠΠΎ Π²Π²Π΅Π΄Π΅Π½ΠΈΠΈ Π°ΡΠ³ΡΠΌΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π° Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ Π²ΡΡΡΠ½Π΅Π½ΠΈΡ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΎΠ² ΡΠ³Π»Π°ΠΆΠΈΠ²Π°Π½ΠΈΡ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ ΠΏΡΠΈ Π²ΠΎΠ·ΡΠ°ΡΡΠ°Π½ΠΈΠΈ ΡΠ°ΡΡ
ΠΎΠ΄ΠΎΠ² Π΄ΠΎΠΌΠ°ΡΠ½Π΅Π³ΠΎ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π° Π½Π° Π²ΡΠΏΠ»Π°ΡΡ ΠΊΡΠ΅Π΄ΠΈΡΠΎΠ². Π 1-ΠΌ ΡΠ°Π·Π΄Π΅Π»Π΅ ΡΡΠ°ΡΡΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ Π΄Π°Π½Π½ΡΡ
, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΡ
Π² Π°Π²ΡΠΎΡΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»ΡΡ
, Π΄Π°Π½Π° Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° Β«Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΈ Π·Π΄ΠΎΡΠΎΠ²ΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΠΠ£ ΠΠ¨ΠΒ» (ΠΏΠ΅ΡΠΈΠΎΠ΄Ρ Ρ 2006 ΠΏΠΎ 2013 Π³.); Π²ΠΎ 2-ΠΌ ΡΠ°Π·Π΄Π΅Π»Π΅ ΠΎΡΡΠ°ΠΆΠ΅Π½Ρ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΠΌΠΈΡΠΎΠ²ΡΡ
ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΉ ΠΈ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π°Π»ΠΈΠΉ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠΉ Π·Π°Π΄ΠΎΠ»ΠΆΠ΅Π½Π½ΠΎΡΡΠΈ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
Ρ
ΠΎΠ·ΡΠΉΡΡΠ²; Π² 3-ΠΌ - ΠΏΡΠΎΠΊΠΎΠΌΠΌΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π° ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ° ΠΈΡ
ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΈ. Π Π·Π°ΠΊΠ»ΡΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΌ, 4-ΠΌ ΡΠ°Π·Π΄Π΅Π»Π΅ ΡΡΠ°ΡΡΠΈ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡΠΈΠ΅ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΈ Π½Π° ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΠ΅ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
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ΠΎΠ·ΡΠΉΡΡΠ². Π€ΠΎΡΠΌΡΠ»ΠΈΡΡΠ΅ΡΡΡ Π°Π²ΡΠΎΡΡΠΊΠ°Ρ ΠΏΠΎΠ·ΠΈΡΠΈΡ, ΡΡΡΡ ΠΊΠΎΡΠΎΡΠΎΠΉ ΡΠΎΡΡΠΎΠΈΡ Π² ΡΠΎΠΌ, ΡΡΠΎ Π²ΡΡΡΠ½Π΅Π½ΠΈΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΎΠ² ΡΠ³Π»Π°ΠΆΠΈΠ²Π°Π½ΠΈΡ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ ΠΏΡΠΈ Π²ΠΎΠ·ΡΠ°ΡΡΠ°Π½ΠΈΠΈ ΡΠ°ΡΡ
ΠΎΠ΄ΠΎΠ² Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
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ΠΎΠ·ΡΠΉΡΡΠ² Π½Π° Π²ΡΠΏΠ»Π°ΡΡ ΠΊΡΠ΅Π΄ΠΈΡΠΎΠ², ΡΡΠΎΡΠ½Π΅Π½ΠΈΠ΅ ΡΡΡΡΠΊΡΡΡΡ Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
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ΠΎΠ·ΡΠΉΡΡΠ², ΡΠΊΠ»ΠΎΠ½Π½ΡΡ
ΠΊ Π·Π°ΠΈΠΌΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡΠΌ, Ρ Π΄Π΅ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΠΎΠΉ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ², ΡΠ°ΡΡ
ΠΎΠ΄ΠΎΠ² ΡΠΎΠ·Π΄Π°Π΅Ρ ΠΎΡΠ½ΠΎΠ²Ρ Π΄Π»Ρ Π²ΡΡΠ°Π±ΠΎΡΠΊΠΈ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ Π³Π°ΡΠΌΠΎΠ½ΠΈΠ·Π°ΡΠΈΠΈ ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠΎΠ² ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΡΡ
ΠΈΠ½ΡΡΠΈΡΡΡΠΎΠ² ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΡΡΡΠ°Π½Ρ
Indicators of financial security on the micro-level : approach to empirical estimation
The article suggests an original approach to economic security system indicators formation at micro level based on the assessment of changes in householdsβ living and financial behavior under economic crisis.
An econometric implementation based on the triangular recursive system of equations is used with a multivariate probit model, dealing with unobservable individual heterogeneity, with the bias atributed to omitted variables and endogeneity.
The estimation was performed according to the representative survey of the population βThe Russia Longitudinal Monitoring Survey - Higher School of Economics (RLMS-HSE) (RLMS-HSE, 2017).peer-reviewe