Demographic and poverty dynamics with high AIDS mortality

1. Demographic and poverty dynamics with high AIDS mortality Ian M. Timæus London School of Hygiene & Tropical Medicine

2. Intellectual justification • The project examines the impact of the AIDS epidemic and measures to mitigate it in sub-Saharan Africa • Most demographic analyses treat socioeconomic status as an exogenous explanation of demographic phenomena • Likewise, microeconomic analysis usually treats demographic change as exogenous or even ignores it entirely. • The challenge to welfare posed by the HIV/AIDS epidemic in Africa demands a more sophisticated understanding of inter-relationships between demographic and poverty dynamics • The response to both demographic and economic shocks can be demographic as well as economic

3. HIV AND AIDS MORTALITY HIV AIDS HOUSEHOLD AND FAMILIAL IMPACTS LIVELIHOODS AND ACTIVITIES POVERTY DEMOGRAPHY ECONOMY AIDS and population change

4. Objectives To synthesize economic and demographic perspectives in order to: • Improve the measurement of poverty dynamics • Understand better the impact of deaths of working-age adults on household welfare, households’ responses, and the determinants of differential vulnerability and resilience • Examine the effects of demographic change, including the AIDS epidemic, on poverty dynamics across the life course in South Africa • Assess social policy interventions designed to mitigate impact and their distributional implications across the life course.

5. Longitudinal data on AIDS impact • Phase 1 – analysis of two complementary longitudinal population-based studies from KwaZulu-Natal – ACDIS and KIDS (KwaZulu-Natal Income Dynamics Study) • Longitudinal studies provide data on people who later get sick and die • They allow analysis of changes in social and economic behaviour that follow shocks such as AIDS and AIDS deaths • One can compare movements into and out of poverty in affected and unaffected households and distinguish transitory from chronic poverty • Finally, they can document both early responses to and the longer-term consequences of AIDS sickness and deaths • Phase 2 – development of a micro-simulation model in order to assess different social policy interventions for a population affected by AIDS • Qualitative study of how households cope with illness and death

6. Africa Centre DSS (ACDIS) • Surveillance of the entire population of part of the Hlabisa sub-district of KwaZulu-Natal • Run by the Africa Centre for Health and Population Studies • part of the University of KwaZulu-Natal • principal funder: The Wellcome Trust • Data collection started in January 2000 • 90,000 household members (88,000 individuals) • 11,000 households • Two rounds of data collection per year • births • deaths  a verbal autopsy is conducted for all deaths • moves • demographic and health data • socioeconomic module (every 2nd/3rd round)

7. Africa Centre for Health and Population Studies

8. KwaZulu-Natal Income Dynamics Study • Panel study based on 1354 African and Indian households interviewed in KZN in 1993 • Uses a World Bank LSMS-style questionnaire with detailed expenditure data • 2nd wave of interviews in 1998 and 3rd wave in 2004 • Interviews all branches of households that have split and households established by the next generation as well as the original households • Although the panel has suffered substantial attrition (38%), in aggregate its characteristics remain broadly representative of those of the province according to the 2001 Census

9. Location of KIDS 2004 households

10. Deaths by age in 1998 and year, KIDS(* prorated to a full calendar year)

11. ADaPT – a multidiscipinary team • The project builds on existing partnerships between: • Centre for Population Studies (CPS), LSHTM • Ian Timæus (demography) • Alessandra Garbero (demography, economics) • School of Development Studies (SDS), UKZN • Julian May (economics, social policy) • Lucia Knight(demography, sociology – PhD student) • Africa Centre for Health and Population Studies, UKZN • Vicky Hosegood (demography, social policy) • The core partners are supported by specialist expertise from: • University of Southampton • Jane Falkingham (demography, economics, social policy) • University of Cape Town • Ingrid Woolard (economics)

12. Work plan and collaborative mechanisms • Three-year project (October 2006 – October 2009) • Funded under a joint initiative of the UK’s Economic and Social Research Council and Department for International Development • North-South collaboration with annual project workshops and periods of intensive face-to-face work • Exchange sabbaticals in Durban and London in 2007 and 2008 • Full-time research assistant and linked PhD studentship for a young South African researcher, both based at LSHTM • Final dissemination workshop in South Africa

13. Household size and expenditureKIDS – 1993, 1998 and 2004 waves(Child weights: aged 0-6 = 0.5, aged 7-13 = 0.75; θ = 0.75) Median household size ≈ 5

14. Adult death and poverty dynamics

16. Depending on what an adult who died contributed to their household the impact of premature deaths on per capita expenditure may be negative or positive. A straightforward regression model mixes together these two different regimes The effect is a data-weighted average of these two regression relationships, which we estimate as negative but, unsurprisingly, insignificant. To allow for heterogeneous effects of premature deaths, we modify a basic fixed effects regression equation as follows: where the coefficient 2 allows the impact of a premature adult mortality to change with the household’s level of initial economic well-being. A heterogeneous effects model of the impact of premature adult deaths

17. Impact of premature adult mortality (PAM) on estimated livelihood trajectories