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Прожиточный минимум в липецке

The photographs which have not been seen and personal facts which have not been told: the unique Hvorostovsky family album is the first time on display at the Museum of Krasnoyarsk railroad. So it was to the Museum of Krasnoyarsk railroad that the family passed several dozens of family photographs and documents. Dmitry Hvorostovsky is still an ordinary boy on them, and no one can see that literally the whole world will know him in time. A photograph from the Hvorostovsky family archive. A primary school teacher.

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ПОСМОТРИТЕ ВИДЕО ПО ТЕМЕ: Минимальные пенсии в 2020 году! Таблица по регионам

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To browse Academia. Skip to main content. Log In Sign Up. Irina Denisova. Marina Kartseva. The scope of poverty as well as the poverty profile is still an open question, however.

The question is even more open with respect to the Russian regions. We also draw regional poverty profiles by identifying the factors which influence poverty rates and poverty gaps.

The exercise is based on NOBUS database — a nationally and regionally for 46 regions representative survey of households done in April- May We find that poverty rates vary significantly — up to threefold difference - across regions.

The list of factors that influence poverty rate and poverty gap in regions are similar, with variation in relative weights of the factors. The former conforms with other studies on poverty in Russia that conclude that there are no major differences in determinants of transitory or persistent poverty.

Some interesting insights in regional-specific patterns of poverty are found. MacArthur Foundation. Introduction Policies to reduce poverty are in high political demand in Russia. Understanding of the nature of current poverty in Russia is still a challenge for researchers, especially when regional poverty is concerned.

The list of papers on regional aspect of poverty in Russia is very limited, however. Kolenikov and Shorrocks utilize regional data to decompose changes in indicators of regional poverty into changes in mean incomes and in inequality. They also use regional data to test for determinants of regional poverty rates in Kolenikov and Shorrocks The recent Poverty Assessment Report on Russia by the World bank is the first to report using household level data to analyze regional determinants of poverty.

The report is based on household budget survey data. The report shows significant variation across regions in returns to poverty determining factors, with living in rural areas, education, employment and number of children being the factors. We use the first publicly available micro dataset which is regionally representative for 46 Russian regions — NOBUS — to study regional aspects of poverty.

In particular, we measure poverty rate and severity of poverty in Russian regions by estimating poverty rate and severity of poverty for the national level and for each of the 46 regions. The measures are also calculated for potentially vulnerable subgroups of population — households with children, households of pensioners, households with members in bad health, etc.

We further test for factors that determine poverty rates and severity of poverty for households in each of the 46 regions. We then compare significance of factors and size of the coefficients across regions to test for heterogeneity of regions and to identify possible clusters of regions with respect to poverty profile. We then test for factors that determine poverty rate and severity of poverty in the four groups of regions, using logit regression for poverty rate and tobit regression for severity of poverty analysis.

It could be that the list of factors that determine probability to get into poverty is heterogeneous with respect to the position of the household relative to poverty line. To identify households in relatively more need, we divide the sample of households into: those with per capita consumption higher that regional subsistence level; with per capita consumption in the range of 0. We then we test for the factors that determine the relative position of households ordered logit regression for the national sample and regional sub samples.

The paper is organized as follows. Section 2 introduces data and measurement issues. Section 3 discusses methodology used, including reasoning behind factors to explain variation in poverty rates and severity of poverty. Section 4 discusses results. Section 5 concludes and provides some policy implications. The questionnaire and the sample were designed by Rosstat in close cooperation with the World bank.

The survey is nationally and regionally - for 46 Russian regions - representative. The household part of the questionnaire includes detailed questions on household composition, household income, including benefits, and expenditures. Individual part of the questionnaire provides detailed information on the labor market status of adult household members. Absolute poverty concept is adopted in the paper.

In particular, the welfare measure we use is household consumption per capita relative to regional subsistence level. Official regional subsistence level is calculated based on the regional cost of the minimum consumption basket.

The composition of the consumption basket is unified across regions with some adjustment to the regional variation in basic needs1. Consumption measure of family economic welfare is implemented.

Methodology 3. The most widely used measures are poverty rate, poverty gap and severity of poverty. Poverty rate is defined as a headcount index of poverty, i. In what follows we utilize poverty rate and severity of poverty measures. In particular, we identify determinants of probability to be in poverty in each region by applying logit regression analysis. Severity of poverty is estimated using tobit regression given that the dependent variable is truncated at zero.

To check whether the level of poverty affects the list of factors shaping poverty profile, we group the regions according to a threshold in poverty rates and test for variation in poverty determining factors. To identify determinants of the relative position of a households we run ordered logit regression for the total sample and for each for the 46 regions. In particular, one needs to take into account labor market opportunities of family members, as well as the availability to attract redistributed income to receive benefits.

Flow of income from accumulated assets is very limited in Russia, not to mention that the source is rarely applicable to the poor. In particular, the following hypothesis are tested: 1.

Larger families tend to be poor. Families with more children tend to be poor. The larger the share the lesser the poverty incidence. The higher the education the higher is labor productivity and hence wages. Affiliation with the state sector tend to provide higher job security but lower wages. Involvement in subsistence farming tend to counteract poverty. Job market opportunities are worse for those living in rural areas though there are better opportunities for subsistence farming.

Labor market penalizes bad health by lower wages. It tends to reflect less bright prospects of females on the labor market in most of the economies. Pensions are known to be one of the regular transfers in Russia. Results 4. Our estimates show that poverty rate for Russia in was Severity of poverty is also higher than sample average for families with children. Households of pensioners show not higher than average poverty rate and even lower than sample average severity of poverty.

Families with no members with secondary professional or higher professional degree show higher values of both poverty measures. Female headed households are doing not worse than the average. Households in rural areas have higher than average poverty rate Households with members with bad health have higher poverty incidence and severity of poverty rates. The tables are to clarify the relative position of the regional subsistence level. Table 3 shows summary statistics of the basic family characteristics for younger children, older children, elderly and adults.

It is clear from the table that younger children tend to live in larger families, while elderly tend to live in smaller households. Column 2 of the table reflect the average number of younger children, older children, elderly and adults in households having younger children, column 3 — the same, but for households with older children, and column 4 - for households with elderly.

The table provides some understanding of the demographic composition of Russian households. In particular, it clear that every fourth family with young children have an elderly person in the household, and every fifth family with older children have elderly members.

Table 4 provides estimates of poverty rates and severity of poverty measures for the 46 regions for which the survey is representative. It is clear from the table that poverty head count rate and severity of poverty vary significantly across the regions.

Severity of poverty also varies significantly, with the extreme cases being the same. Variation in severity measure tends to be less than in head count poverty measure, however. It is clear that there is significant regional variation in all the factors. The explanatory variables are those discussed in section 3. It turns out that the larger the household, the more likely is the household in poverty.

This factor is significant for all the 46 regions, with coefficients varying from 0. The larger the share of children in a household, the larger the incidence of poverty in half of the regions 22 out of In the rest of the regions the share of children does not affect the incidence of poverty. Higher attachment to the labor market helps households to escape poverty: the higher the share of adults working, the lower the probability that the household is in poverty.

The relevant coefficient is highly statistically significant for 44 out of regions, with Adygeya and Dagestan being the exceptions the factor is only weakly statistically significant there. The magnitude of the coefficient varies across regions, with being as high in absolute terms as —4.

It is economically intuitive that the coefficient is higher in more developed regions since labor is more rewarded in pecuniary terms in those regions. Having at least one member of the family with higher professional education is rewarding in terms of lesser chances of getting into poverty as compared to the reference category of those who has secondary education only. Secondary professional education is also rewarding in the majority of the regions, though the relevant coefficients are always smaller than for higher professional degree.

Primary professional education as the highest level of education among household members is not better than secondary school degree complete or incomplete. The only exception from the pattern is Moscow for which the level of education of family members does not matter for chances to escape poverty. Larger share of those working for the state sector is a poverty increasing factor in Moscow, St.

Unknown Dmitry Hvorostovsky: wanted to be a doctor, not a singer

To browse Academia. Skip to main content. Log In Sign Up. Irina Denisova.

регионального прожиточного минимума, %'); pov_reg_bottomtxt fregion,​RU-LIP,Central,Липецкая область,,Липецкая область,

Детские пособия на ребенка — список документов

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Malaysian Boeing hit by an Ukrainian pilot - captain Voloshin

We checked his papers — he is not an actor and not a man of straw. Judging by the facts Alexandr told us let us name him so — his concerns are quite real. Here is the transcript of our conversation almost without any cuts. That is a usual airport.

Паспорт лица, заполнявшего заявление. Доступ к полному содержимому данного документа ограничен.

Будущему нанимателю предоставляют лицензии и документы, показывают много поддельных наград, дипломов и грамот. Так что решать. Если сумма не доходит до предельно установленной высокой, то она называется простой страховой суммой. Регрессное требование - это обратное требование в гражданском праве. Этот предмет нужен, чтобы перед выходом из здания человек мог оценить свой внешний вид.

Стройным высоким женщинам подойдут брюки-кюлоты, которые сочетаются с топом, рубашкой или джемпером. Участники торгов вносят задаток в размере, в сроки и в порядке, которые обозначены в информационных справках о проведении торгов. Истица от пошлины освобождена. Процедура снятия с регистрации в среднем занимает около двух недель. Расчеты могут использоваться при совершении сделок по купле-продаже недвижимости. Второй вариант - вы сообщаете работодателю о вашем праве на налоговый вычет, и он приостанавливает выплату налога из вашей зарплаты до момента, пока не будет исчерпана вся переплата.

Губернатор Липецкой области Артамонов нагло врал, что в В Липецкой области снизился прожиточный минимум ⠀ Постановление об этом.

Документ может быть составлен произвольно, однако в нем обязательно должна быть соблюдена структура заявления. Указана может быть даже преддипломная практика и приобретенные во время ее прохождения навыки. В ней надо кратко отобразить нейтральную информацию, полностью соответствующую действительности. Консультант департамента письменных обращений граждан и организаций Н.

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Следите за новыми идеями полезных авто советов в нашем канале. Особые требования вправе заявлять и те лица, которые подали заявление о банкротстве (например, наличие юридического образования и т.

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Из-за того, что случаи алкогольных отравлений напитками, купленными в сети, выросли, правительство задумалось о более тщательном контроле интернет-магазинов. За это необходимо уплатить еще 350 рублей. В детском парке г.

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