a post by Adm Corlett for the Resolution Foundation blog
It may go unnoticed amid the current political turmoil, but today we learnt a lot about the recent state of Britain via the publication of official statistics on incomes, poverty and inequality. We already know how the economy and labour market have performed over recent years, but today’s stats give us much more information about how this all fed through into households’ living standards in 2017-18. And the results are concerning.
Typical incomes stagnated
2017-18 was a year in which average prices rose by around 3 per cent – faster than most earnings, benefits or other income. As a result, typical household incomes fell by around 0.2 per cent in real terms. This fall is similar to separate ONS stats released last month, and our own income projections.
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Showing posts with label household_income. Show all posts
Showing posts with label household_income. Show all posts
Tuesday, 2 April 2019
Wednesday, 30 January 2019
Reliability of Longitudinal Social Surveys of Access to Higher Education: The Case of Next Steps in England
an article by Nadia Siddiqui, Vikki Boliver and Stephen Gorard (Durham University, UK) published in Social Inclusion Volume 7 Number 1 (2019)
Abstract
Longitudinal social surveys are widely used to understand which factors enable or constrain access to higher education.
One such data resource is the Next Steps survey comprising an initial sample of 16,122 pupils aged 13–14 attending English state and private schools in 2004, with follow up annually to age 19–20 and a further survey at age 25.
The Next Steps data is a potentially rich resource for studying inequalities of access to higher education. It contains a wealth of information about pupils’ social background characteristics—including household income, parental education, parental social class, housing tenure and family composition—as well as longitudinal data on aspirations, choices and outcomes in relation to education.
However, as with many longitudinal social surveys, Next Steps suffers from a substantial amount of missing data due to item non-response and sample attrition which may seriously compromise the reliability of research findings. Helpfully, Next Steps data has been linked with more robust administrative data from the National Pupil Database (NPD), which contains a more limited range of social background variables, but has comparatively little in the way of missing data due to item non-response or attrition.
We analyse these linked datasets to assess the implications of missing data for the reliability of Next Steps.
We show that item non-response in Next Steps biases the apparent socioeconomic composition of the Next Steps sample upwards, and that this bias is exacerbated by sample attrition since Next Steps participants from less advantaged social backgrounds are more likely to drop out of the study. Moreover, by the time it is possible to measure access to higher education, the socioeconomic background variables in Next Steps are shown to have very little explanatory power after controlling for the social background and educational attainment variables contained in the NPD.
Given these findings, we argue that longitudinal social surveys with much missing data are only reliable sources of data on access to higher education if they can be linked effectively with more robust administrative data sources. This then raises the question—why not just use the more robust datasets?
Full text (PDF 10pp)
Abstract
Longitudinal social surveys are widely used to understand which factors enable or constrain access to higher education.
One such data resource is the Next Steps survey comprising an initial sample of 16,122 pupils aged 13–14 attending English state and private schools in 2004, with follow up annually to age 19–20 and a further survey at age 25.
The Next Steps data is a potentially rich resource for studying inequalities of access to higher education. It contains a wealth of information about pupils’ social background characteristics—including household income, parental education, parental social class, housing tenure and family composition—as well as longitudinal data on aspirations, choices and outcomes in relation to education.
However, as with many longitudinal social surveys, Next Steps suffers from a substantial amount of missing data due to item non-response and sample attrition which may seriously compromise the reliability of research findings. Helpfully, Next Steps data has been linked with more robust administrative data from the National Pupil Database (NPD), which contains a more limited range of social background variables, but has comparatively little in the way of missing data due to item non-response or attrition.
We analyse these linked datasets to assess the implications of missing data for the reliability of Next Steps.
We show that item non-response in Next Steps biases the apparent socioeconomic composition of the Next Steps sample upwards, and that this bias is exacerbated by sample attrition since Next Steps participants from less advantaged social backgrounds are more likely to drop out of the study. Moreover, by the time it is possible to measure access to higher education, the socioeconomic background variables in Next Steps are shown to have very little explanatory power after controlling for the social background and educational attainment variables contained in the NPD.
Given these findings, we argue that longitudinal social surveys with much missing data are only reliable sources of data on access to higher education if they can be linked effectively with more robust administrative data sources. This then raises the question—why not just use the more robust datasets?
Full text (PDF 10pp)
Sunday, 5 November 2017
Why are Households that Report the Lowest Incomes So Well-off?
an article by Mike Brewer (University of Essex; Institute for Fiscal Studies), Ben Etheridge (University of Essex) and Cormac O’Dea (Institute for Fiscal Studies) published in The Economic Journal Volume 127 Issue 605 (October 2017)
Abstract
We document that households in the UK with extremely low measured income tend to spend much more than those with merely moderately low income.
This phenomenon is evident throughout three decades worth of microdata and across different employment states, levels of education and marital statuses. Of the likely explanations, we provide several arguments that discount over-reporting of expenditure and argue that under-reporting of income plays the major role.
In particular, by using a dynamic model of consumption and saving, and paying special attention to poverty dynamics, we show that consumption smoothing cannot explain all the apparent dissaving.
Full text (PDF 26pp)
Abstract
We document that households in the UK with extremely low measured income tend to spend much more than those with merely moderately low income.
This phenomenon is evident throughout three decades worth of microdata and across different employment states, levels of education and marital statuses. Of the likely explanations, we provide several arguments that discount over-reporting of expenditure and argue that under-reporting of income plays the major role.
In particular, by using a dynamic model of consumption and saving, and paying special attention to poverty dynamics, we show that consumption smoothing cannot explain all the apparent dissaving.
Full text (PDF 26pp)
Wednesday, 4 January 2012
Understanding household income poverty at small area level
an article by Robert Fry (Office for National Statistics) published in Regional Trends 43 (2011)
Abstract
A new ONS data release provides experimental estimates of the proportion of households in poverty, after housing costs, at Middle Layer Super Output Area (MSOA) level in England and Wales. These complement the experimental estimates of average household income for MSOAs already published by ONS.
These estimates are based on Family Resources Survey (FRS) data and the Department for Work and Pensions (DWP) publication Household Below Average Income derived from FRS data. They use a similar modelling approach to that used for the average household income estimates. The first set of these estimates relate to the 2007/08 period. Future updates will be released alongside the estimates of average household income.
This article looks at spatial patterns in the proportion of households in poverty, in particular looking at how poverty is distributed within regions and local authorities. The article shows that there are wide variations in the patterns of the proportions of households in poverty in each region. Looking across all MSOAs, Wales, the North East and London had the highest median values of the proportion of households in poverty1. London had the largest spread, that is, it had both areas with very low and high proportions of households in poverty.
The article also provides an introduction to these estimates and some summary guidance on their use. It will be of interest to people with a focus on poverty at a local level such as politicians, charities, planners, regeneration specialists, and academics.
1 Official estimates of the proportions of individuals in low income by region are given in the Households Below Average Income publication here [published May 2011]
Abstract
A new ONS data release provides experimental estimates of the proportion of households in poverty, after housing costs, at Middle Layer Super Output Area (MSOA) level in England and Wales. These complement the experimental estimates of average household income for MSOAs already published by ONS.
These estimates are based on Family Resources Survey (FRS) data and the Department for Work and Pensions (DWP) publication Household Below Average Income derived from FRS data. They use a similar modelling approach to that used for the average household income estimates. The first set of these estimates relate to the 2007/08 period. Future updates will be released alongside the estimates of average household income.
This article looks at spatial patterns in the proportion of households in poverty, in particular looking at how poverty is distributed within regions and local authorities. The article shows that there are wide variations in the patterns of the proportions of households in poverty in each region. Looking across all MSOAs, Wales, the North East and London had the highest median values of the proportion of households in poverty1. London had the largest spread, that is, it had both areas with very low and high proportions of households in poverty.
The article also provides an introduction to these estimates and some summary guidance on their use. It will be of interest to people with a focus on poverty at a local level such as politicians, charities, planners, regeneration specialists, and academics.
1 Official estimates of the proportions of individuals in low income by region are given in the Households Below Average Income publication here [published May 2011]
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