Исследование взаимосвязи бизнес-моделей банков и стабильности экономического развития

Depending on the chosen business model, banks can act as both shock absorbers and crisis catalysts. In this regard, the analysis of the relationship between banks’ business models and financial cycles becomes a useful tool for diagnosing and predicting crisis phenomena. The purpose of the research is to identify the relationship between the volume of debt of the banking and the debt burden of the economy. The research uses econometric methods. The key result of the research is two new econometric models, which were calibrated for the Russian economy. The models differ from each other by the types of bank liabilities used in the calculation of independent variables. The models also differ from the existing models by the calculation algorithm of independent variables. The source of information is the official statistics of the Bank of Russia for the period 2008–2019. The tests of the models confirmed the presence of a statistically significant cointegration relationship between the debt burden of the banking sector and the debt burden of the economy. Coupling coefficients in the models are identified as debt multipliers of the banking sector and characterize the multiplier effect of changes in the debt burden of banks. For the model containing banks’ balance sheet liabilities, the debt multiplier for the Russian economy was 6.7; and for the model using banks’ total liabilities was 3.1. The developed models are easy-to-use for forecasting financial cycles.В зависимости от выбранной бизнес-модели банки могут быть как амортизаторами, так и катализаторами кризиса. В связи с этим анализ взаимосвязи бизнес-моделей банков и финансовых циклов становится полезным инструментом диагностики и прогнозирования кризисных явлений. Цель исследования — выявление связи между объемом задолженности банковского сектора и долговой нагрузкой экономики. В исследовании используются эконометрические методы. Результатом исследования являются две новые эконометрические модели, которые были откалиброваны применительно к российской экономике. Модели отличаются друг от друга видами банковских обязательств, используемых при расчете независимых переменных, а от существующих моделей — алгоритмом вычисления независимых переменных. Источником информации является официальная статистика Банка России за период 2008–2019 гг. Тесты моделей подтвердили наличие статистически значимой коинтеграционной связи между долговыми нагрузками банковского сектора и экономики. Коэффициенты связи в моделях идентифицируются как мультипликаторы долга банковского сектора и характеризуют мультипликативный эффект изменения долговой нагрузки банков. Для модели, содержащей балансовые обязательства банков, мультипликатор долга для экономики России составил 6,7; а для модели с использованием показателя совокупных обязательств банков — 3,1. Разработанные модели удобны в использовании для прогнозирования финансовых циклов

Russian population health-related quality of life indicators calculated using the EQ-5D-3L questionnaire

Objectives. The paper aims was forming the first health-related quality of life population indicators using EQ-5D–3L survey that represents the Russian population by gender and age, as well as by the attained level of education. Material and methods. For compiling population indicators, we use the EQ-5D-3L questionnaire. The study was conducted on the adult Russian population aged 18 to 75 years. A representative sample was 12616 respondents. Results. 59.3 % of the sample is in good health (profile 11111). The proportion of respondents reporting any health problems increases with age. The average score on a 100-point visual analogue scale is 72.4 (standard deviation 18,1; 95 per cent confidence interval from 72,1 to 72,7). Men, on average, tend to assess their health higher than women. However there are no statistically significant differences in health scores among educational groups, taking into account gender and age data. Conclusions. Comparison of health-related quality of life estimations with normative population data allows us to track differences in health between population groups, as well as to analyze the health status and progress in treating patients. The Russian health-related quality indicators from EQ-5D-3L survey are similar to the Hungary population indices, as well as to many European countries, the USA, and Argentina for age cohorts under 45 years of age. For the cohorts of respondents older than 45 years, Russian estimations are much lower than in other countries. This evidence confirms that borrowing scales from other countries for converting EQ-5D-3L values into a preference EQ-5D-3L index is not acceptable for Russian patients, especially for the elderly

Total expenditure elasticity of healthcare spending in Russia

In this study we estimate the income elasticity of spending on different healthcare services and medication in Russia, taking into account the non-linear relationship between income level and expenditure. We employ the RLMS-HSE data, 2006–2017, to estimate the elasticities at household level. Our findings show these elasticities have not changed over the years. Additionally, we show that low-income and high-income households demon­strate different levels of elasticities, which is consistent with the fact that healthcare is less affordable for the poor. The study confirms that healthcare and medication are close to luxury level for low-income households and drugs are almost income inelastic for rich households. The results could help to reveal which services are the least affordable for the population