Top PDF Living standards, poverty and inequality in the UK : 2019

Living standards, poverty and inequality in the UK : 2019

Living standards, poverty and inequality in the UK : 2019

is particularly important when comparing incomes across age groups – pensioners are much more likely to own their homes outright than working-age adults. Fourth, comparing changes in AHC incomes may provide better information about relative changes in living standards when some households have seen large changes in their housing costs that are unrelated to changes in housing quality. This is particularly relevant when looking at the period between 2007–08 and 2009–10, as rapid falls in mortgage interest rates reduced the housing costs of those with a mortgage significantly, while the housing costs of those who rent their homes (or own them outright) were not directly affected. When incomes are measured BHC, changes over time in the incomes of all households are adjusted for inflation using a price index that accounts only for average housing costs. This will understate the effect of falling housing costs on living standards for those with a mortgage and overstate it for those without a mortgage. Changes in income measured AHC do not suffer from this issue, since changes in housing costs are accounted for by subtracting each household’s actual housing costs from its income. This difference is important to bear in mind when looking at changes in poverty and inequality.
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Living Standards, Poverty and Inequality in the UK: 2014

Living Standards, Poverty and Inequality in the UK: 2014

• Income is measured both before housing costs have been deducted (BHC) and after they have been deducted (AHC). It is worth noting that since the publication of the 2011–12 HBAI data in June 2013, the data between 2002–03 and 2011–12 have been revised. These revisions reflect new information about the demographic characteristics of the UK population collected in the 2011 Census. The effects of these revisions on average incomes, inequality and poverty have been small and all the analysis in this report uses the revised data. 1 Our analysis of the latest HBAI data begins in Chapter 2 with a look at average living standards and how they have changed over time. Chapter 3 analyses how changes in incomes have differed across the income distribution and between different age groups. Chapter 4 examines trends in poverty, looking at absolute and relative measures of poverty, as well as additional indicators of low living standards, such as material deprivation. Chapter 5 analyses in detail the living standards of young adults – a group that has been hit particularly hard since the start of the Great Recession.
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Poverty, Inequality, Child Abuse and Neglect: Changing the Conversation across the UK in Child Protection?

Poverty, Inequality, Child Abuse and Neglect: Changing the Conversation across the UK in Child Protection?

Poverty, child abuse and neglect Definitions of poverty are much debated. Some of the debates tend to revolve around whether to use measures of absolute or relative poverty and whether to focus on material resources or to include broader measures of what allows for acceptable living standards and social inclusion. In recent years, the government in England has proposed a radical departure from either approach, with its proposals to uncouple any link with income. This is out of line with the vast majority of organisations working in this field and other countries, most of whom incorporate approaches to income measurement which have a relational component. Currently, for example, the Child Poverty Action Group uses the definition advanced by one of its founders, Peter Townsend, in 1979:
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Spatial Comparisons of Poverty and Inequality in Living Standards in Malawi

Spatial Comparisons of Poverty and Inequality in Living Standards in Malawi

2.1.1 Consumption Expenditure The money-metric measurement of poverty and inequality is done using either house- hold income or household consumption expenditure. In keeping with most poverty and inequality studies in Africa we use household consumption expenditure as an indicator of poverty and inequality rather than income. The household consumption expenditure in this study is annualised. To ensure that households are comparable, we generate per capita expenditure for each household. Using per capita expenditure raises two contro- versial issues. First, by using per capita expenditure we ignore the fact that di¤erent individuals have di¤erent needs. For example, a young child typically requires less food than an adult. Second, there are economies of scale in consumption for such items as housing, kitchen utensils, and utilities such as electricity. It costs less to house two people than to house two individuals separately. Thus, using per capita expenditure assumes these economies of scale away. We don’t interrogate these issues further in this study, but follow an empirical precedent set by Murkhejee & Benson (2003) for Malawi. They use per capita expenditure as a money-metric indicator of household welfare.
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Poverty and Inequality in Standards of Living in Malawi: Does Religious Affiliation Matter?

Poverty and Inequality in Standards of Living in Malawi: Does Religious Affiliation Matter?

3.1.1 Consumption Expenditure The money-metric measurement of poverty and inequality is done using either house- hold income or household consumption expenditure. In keeping with most poverty and inequality studies in Africa we use household consumption expenditure as an indicator of poverty and inequality rather than income. The household consumption expenditure in this study is annualised. To ensure that households are comparable, we generate per capita expenditure for each household. Using per capita expenditure raises two contro- versial issues. First, by using per capita expenditure we ignore the fact that di¤erent individuals have di¤erent needs. For example, a young child typically requires less food than an adult. Second, there are economies of scale in consumption for such items as housing, kitchen utensils, and utilities such as electricity. It costs less to house two people than to house two individuals separately. Thus, using per capita expenditure assumes these economies of scale away. We don’t interrogate these issues further in this study, but follow an empirical precedent set by Murkhejee and Benson (2003) for Malawi. They use per capita expenditure as a money-metric indicator of household welfare.
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NESG 2019 Poverty & Inequality Alert

NESG 2019 Poverty & Inequality Alert

Rural dwellers who generate income from Agriculture only are more vulnerable to Poverty A further breakdown of the Poverty Statistics showed that many Nigerians who generate income from agricultural activities only and are domiciled in the rural areas were more prone to a higher incidence of poverty. Furthermore, paid employee across the country - irrespective of settlements (urban & rural) - had a moderate incidence of poverty relative to other categories of Nigerians engaged in other income- generating activities (see Table 2). This segment of Nigeria’s population recorded the lowest poverty headcount ratio with a national average of 15.7%, disaggregated into 11.7% and 24.9% for urban and rural settlements respectively.
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The change in Inequality in the Distribution of Living Standards

The change in Inequality in the Distribution of Living Standards

3.0 Methodology and Data Requirement The methodology proposed here, performs exact decomposition of changes in aggregate measure inequality into Within and Between sector components that hinge on Shapley value (as concerning the exposition of the Shapley value submitted here, see the succinct discussion in Baye, 2007). An important issue in distributive analysis would be how to assign weights to the factors that contribute to an observed level or change in a measure of living standards. For instance, the level and/or change of a distributive index between two dates may be attributable to factors such as Within-sector and Between-sector effects and analysts are interested in quantifying the relative importance of each component. There are different methods to perform the attribution, all of which must have to deal with the fact that the contribution of a factor depends on the presence of the other factors. This issue is similar to problems that arise in cooperative game theory and recent literature in distributive analysis is proposing and applying an attribution according to the Shapley Value (see Shorrocks, 1999; Kabore, 2002; Rongve, 1995;
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RISING INCOME INEQUALITY AND LIVING STANDARDS

RISING INCOME INEQUALITY AND LIVING STANDARDS

6. The evolution of living standards and inequality Having examined how median household incomes and income inequality have evolved over time across the OECD countries, we now bring these together to see how they are aligned. Has rapidly rising inequality been associated with stagnating real incomes around the middle? A comparison of the way countries are grouped in Table 1 versus Table 2 shows some such cases: Japan and the USA have had big increases in income inequality and slow median income growth, and rapid median income growth has accompanied little or no increase in overall inequality in Ireland and Greece. However, there are also counterexamples, including for example Belgium, the Czech Republic, and the UK, which (in LIS data) saw both median income and inequality rising rapidly, and Austria, Denmark and France which saw only modest real income growth with inequality stable or declining. Focusing on top incomes rather than the Gini would change the story for specific countries, but it would not change the overall conclusion.
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The Living Wage: Reducing inequality in the UK?

The Living Wage: Reducing inequality in the UK?

remained but only if higher pay, conditions and staffing levels fell to imitate those lower levels of pay, conditions and staffing exhibited in the private sector. The development and spread of low pay within a highly segmented labour market is suggested to have been a direct consequence of the rise of a new unequal geography of globalisation. 8 Globalisation has permitted rising profitability within business occurring at the expense of the share of wealth going into wages and salaries. 9 While living standards were maintained it was only done so at the cost of rapidly rising levels of personal debt which itself triggered the current global economic crisis. 10 As a result, Wilkinson and Pickett suggest, contemporary advanced societies have seen rapidly rising levels of inequality across a range of social indicators including income, health and wellbeing, crime, violence and social dislocation. 11 Further, the ability to resist these processes has been reduced by falling trade union membership and weakening of trade union influence in pay bargaining with the result that the least skilled, least educated and most vulnerable workers are the most likely to face low wages and poor working
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The cost of living in China : implications for inequality and poverty

The cost of living in China : implications for inequality and poverty

Total 56 437 14 929 3.79 58 601 16 035 3.66 IND: individuals, HH: households, MHH: mean household size, PW: population weights. 3.1 Implementation and Variables The empirical strategy is implemented in the following steps. We define measures of income for rural and urban households. Then we run separate regressions for urban and rural areas, from which we identify province-specific cost-of-living indices for rural and urban areas, separately. However, since these indices are only identified up to a normalization, the urban cost-of-living index is not directly comparable with the rural index. To make these rural–urban price indices comparable, we estimate the overall rural–urban price gap by running a pooled regression. The overall urban and rural price levels are adjusted to match this price gap. This provides us with a spatial price index for all of China. We compare the change in prices over time implied by our cost-of-living index (“COL”) with that of the consumer price index (“CPI”). Further, real incomes are calculated using our cost-of-living price deflator and new inequality and poverty measures are provided. Again, the measures are compared with those based on the CPI. In addition, we run several robustness checks.
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The cost of living in China: Implications for inequality and poverty

The cost of living in China: Implications for inequality and poverty

China since reforms started in 1978 From centrally planned, low-productive, low inequality and widespread poverty to high growth, more market orientation and poverty reduction. Forces contributing to differences in the cost of living (COL) within China:

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Poverty, inequality and living standards in rural China 1978-90 : A comparative study of Anhui and Yunnan.

Poverty, inequality and living standards in rural China 1978-90 : A comparative study of Anhui and Yunnan.

38 Correlations between different aspects of functioning are also presented in chapter f o u r . 39 In 1987 UNICEF conducted a survey of living standards in several provinces of China, it contained no tine series data. The data therefore provide only a snap shot of spatial inequalities in children's living standards in ten counties of Yunnan. The ten counties covered were: Qujing and Yuxi representing urban areas, Luliang and Menghai representing non-mountainous rural counties; and six mountainous counties: Suijiang, Xuanwei, Mile, Jingdong, Huaping and Yun. These counties and cities belonged to eight different prefectures and were quite widely scattered about the province. These data do shed some light on several issues central to this discussion of living standards, such as: differential access to education and health care, enrolment rates and drop out rates, as well as the incidence of inoculation against childhood diseases, and epidemiological data on child deaths. Spatially there were few surprises, urban areas had higher incidence of inoculation, lower d rop out rates, m ore children in day care or pre-school, and fewer drop outs for both primary and lower middle school education than any of the rural areas included in the study. Mountainous areas were most severely disadvantaged. The epidemiological data reinforced these conclusions, with the majority of child deaths from preventable diseases occurring in the mountainous counties.
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Inequality and living standards in Great Britain: some facts

Inequality and living standards in Great Britain: some facts

What time period should be covered? Having decided on income and expenditure as the measures that will be used to describe living standards, the choice of time period is important. Looking first at incomes: because people’s incomes tend to change over the course of their lives, and may fluctuate from week to week and year to year, the period over which incomes are measured is crucial to the picture of living standards that is drawn. Many income distribution studies in Great Britain are drawn from cross-sectional data, which only measure incomes and spending at a fixed snapshot in time, picking up incomes that are weekly or monthly. Much of the evidence presented in this Briefing Note is derived from information provided by households in two nationally representative household surveys – the Family Resources Survey 2 and the Family Expenditure Survey 3 – which provide cross-sections of income over these relatively short periods. The facts about the distribution of income set out in Sections II and III are based on incomes measured over this relatively short time frame.
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Growing Equal? Living Standards, Inequality and Poverty in Italy, Giovanni Vecchi Università di Roma Tor Vergata

Growing Equal? Living Standards, Inequality and Poverty in Italy, Giovanni Vecchi Università di Roma Tor Vergata

(civil code requires household accounts to be provided by the trustee of bankruptcy)  Public administration administrative records  Synthetic households  In short:  plenty [r]

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The consequences of Brexit for UK trade and living standards

The consequences of Brexit for UK trade and living standards

These standard ‘static’ effects of trade have been understood for many centuries since at least the work of David Ricardo. But in recent decades, studies of trade have revealed very large effects on wellbeing through other routes such as higher productivity and innovation. How would Brexit affect the UK’s trade, and what impact would this have on incomes in the UK? This briefing reports new estimates of how Brexit would affect UK living standards through trade (updating our earlier analysis in Ottaviano et al, 2014). We report a range of forecasts based on alternative estimation methods and different assumptions about how the UK’s relationship with the EU would change following Brexit. We primarily focus on the narrow, static trade consequences of Brexit rather than other channels through which Brexit could affect the UK’s economy, such as investment or migration.
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Inequality in Vietnamese Urban-Rural Living Standards, 1993-2006

Inequality in Vietnamese Urban-Rural Living Standards, 1993-2006

Using data from five waves of the Vietnam Household Living Standard Survey, we find evidence of significant urban-rural expenditure inequality. Urban-rural inequality in Vietnam increased dramatically from 1993 to 1998, and peaked in 2002 before reducing slightly in 2004, and significantly in 2006. The urban-rural gap also monotonically increases across the expenditure distribution. We use a variant of the Oaxaca-Blinder decomposition method, applied to the unconditional quantile regression method of Firpo, Fortin and Lemieux (2009), to explain the components of the per capita expenditure differentials between urban and rural households at selected quantiles of the distribution. We also compare these estimates with those at mean obtained by OLS. Our results show a number of factors contributing significantly to the high urban-rural gap. These include inter-group differences in education, household demographic structure, industrial structure and their related returns. Adjusting the average characteristics of rural households to those of urban households will reduce about a half of the overall urban-rural expenditure gap. A significant part of the remaining unexplained component lies in the intercept differences; that is, the inter-group differences in other factors not captured in the model that favor urban households.
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The Effect of Household Characteristics on Poverty and Living Standards in South Africa

The Effect of Household Characteristics on Poverty and Living Standards in South Africa

I estimate the probability of being poor by considering a probit estimation where the dependent variable is POV (as defined above). The poverty status depends on a set of household characteristics (including the race of the household) and region of residence. The explanatory variables included are the age (AGEHD), squared of the age (AGEHD2) and a dummy to indicate whether the household head is female (FHH) the highest level of education attained by the household head, which is measured by including three dummies: EDUCHD1, EDUCHD2, EDUCHD3. 3 I also include as explanatory variables the total number of children in the household (TOTCHILD), the total number of adults in the household (TOTADULT) and the total number of elderly in the household (TOTELDER). Individuals aged less than 18 years of age are categorised as children, males aged 18-64 and females aged 18-59 are categorised as adults and males aged 65 or higher and females aged 60 or higher are categorised as elderly. The definition follows the official definitions of the South African government. There is a social pension program in South Africa and every male aged 65 or higher (officially classified as elderly male) and every female aged 60 or higher (officially classified as elderly female) is eligible for social pension (subject to a means test). Note that both household size and composition are assumed to be exogenous. Edmonds, Mammen and Miller (2001) and Maitra and Ray (2001) argue that in the context of South Africa household composition cannot be regarded as necessarily being exogenous. While these are important issues they are ignored in the context of this paper. To account for the race of the household I include a race dummy (BLACK). Since standards of living vary significantly across regions, I also include dummy for rural residence (RURAL). This region of residence is of particular importance in the South Africa since movement and ownership of assets was restricted for the Non-Whites during the apartheid era.
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Real Wages, Wage Inequality and the Regional Cost of living in the UK

Real Wages, Wage Inequality and the Regional Cost of living in the UK

The categories of renters from which the cost of housing are derived, are very similar to those considered by the ONS, such as households renting from councils; those renting from housing associations; and those renting privately, in both unfurnished and furnished accommodation. Wages are usually deflated using the national RPI which does not capture any regional variation in prices. The measurement of changes in real living standard requires nominal wages to be converted into real wages. To investigate the role of housing costs on wages of workers located in different parts of Britain, the measure used is the cost of housing, specifically gross rent faced by households in region r (r=1…12). In a similar vein to the methodology followed by Moretti (2010), the cost of housing used in this paper reflects the increase in the cost of housing experienced by individuals working in the same British region. Using gross rents has the advantage of being easy to measure and comparable to the ones used by the ONS in the construction of the RPI. To derive the regional RPI, the national RPI calculated by the ONS is partially updated by the cost-of-housing represented by gross rents, i.e. rent plus main charges.
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Real Wages, Wage Inequality and the Regional Cost-of-living in the UK

Real Wages, Wage Inequality and the Regional Cost-of-living in the UK

The categories of renters from which the cost of housing are derived, are very similar to those considered by the ONS, such as households renting from councils; those renting from housing associations; and those renting privately, in both unfurnished and furnished accommodation. Wages are usually deflated using the national RPI which does not capture any regional variation in prices. The measurement of changes in real living standard requires nominal wages to be converted into real wages. To investigate the role of housing costs on wages of workers located in different parts of Britain, the measure used is the cost of housing, specifically gross rent faced by households in region r (r=1…12). In a similar vein to the methodology followed by Moretti (2010), the cost of housing used in this paper reflects the increase in the cost of housing experienced by individuals working in the same British region. Using gross rents has the advantage of being easy to measure and comparable to the ones used by the ONS in the construction of the RPI. To derive the regional RPI, the national RPI calculated by the ONS is partially updated by the cost-of-housing represented by gross rents, i.e. rent plus main charges.
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Poverty and Inequality

Poverty and Inequality

C OMPENSATORY EDUCATION . These programs, operated by CONAFE, a special agency within SEP, reach more than 4 million poor and indigenous children. The first such program was PARE. It focused on physical facilities, books and materials, teacher performance incentives, school management and supervision, and teacher training in the four poorest states. Another program, the CONAFE community schools, relies on specially trained lower secondary graduate volunteers to teach in schools built and maintained by the communities themselves, in return for scholar- ships to continue their own education. The community schools have been designed to overcome the problem of maintaining and staffing schools in remote areas where it is difficult to attract and retain teachers and where, given the small size of the com- munity, it would not be cost effective to establish regular schools. CONAFE recently launched PAREIB to support a gradual decentralization in the operation of compensatory programs, through a strengthening of the states’ institutional capac- ity and an increased participation of communities and school associations in school management. PAREIB also promotes a better quality of education and increased learning through teacher training, provision of standards for targeted schools, and national evaluation, as a tool to increase accountability at all levels.
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