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Non-Household Populations: Implications for measuring inequality Contribution to Session One, Radical Statistics Conference, 23 rd February, 2013, Priory.

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Presentation on theme: "Non-Household Populations: Implications for measuring inequality Contribution to Session One, Radical Statistics Conference, 23 rd February, 2013, Priory."— Presentation transcript:

1 Non-Household Populations: Implications for measuring inequality Contribution to Session One, Radical Statistics Conference, 23 rd February, 2013, Priory Street Centre, YORK Roy Carr-Hill

2 Household Surveys Omitted from Sampling Frames by Design Homeless populations Institutional populations Mobile, nomadic or pastoralist populations Under-represented in Practice Fragile, disjointed or multiple occupancy households Slum populations Difficult to reach areas

3 Numbers Missing Homeless: c.85,000 households assessed as unintentionally homeless + 1,250 rough sleepers; but Crisis estimates that there are about 350,000 households actually homeless but staying with family or friends Institutionalised: – Hospitals: c.160,000 adults in hospital on any one night; given that 29% live alone, a minimum of 48,000 wrongly counted as empty on any day – Care Homes: c.418,000 in publicly or privately provided homes in UK – Military: c.108,000 service personnel serving abroad or living in barracks

4 Gypsies – Prison population: c.85,000 – Refugees: officially c.238,000, unofficially double Mobile / Nomadic Population: c. 82,000 Gypsies and c.8i000 New Age Travellers Fragile and Disjointed Households: 22,000 children in care Urban Slums: not relevant for UK Insecure Areas: not relevant for UK

5 How Many are Poor All those in or just released from prison (90,000), the 90,000 gypsies and 238,000 unofficial refugees will have low or very low money incomes making 413,000. About a quarter of those living alone c.12,000, all those council supported (c.220,000) and a quarter of those in nursing homes (c.11,000). Estimate that, among the 1,216,500 missing, 545,300 are from the poorest decile, leading to a clear bias in estimates of inequality


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