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The Economic Impact of HIV/AIDS Shanta Devarajan How HIV/AIDS affects the economy Labor supply (e.g., South African labor force expected to decline by 12.8 percent by 2010) • But: a 13 percent decline in labor supply reduces GDP by only 8 percent or so, implying that GDP per capita rises How HIV/AIDS affects the economy (cont’d) Productivity losses (absenteeism, retraining workers, death benefits) • Estimated to add upto 15 percent to companies’ wage bill (South Africa, Cote d’Ivoire) • But: Large companies especially are able to adapt, reducing productivity losses How HIV/AIDS affects the economy (cont’d) Public finances • Increased health expenditures, reducing public investment • Reduces GDP growth • But: Assumes that public investment would have been productive Previous estimates of the impact of AIDS on GDP growth (%) Arndt and Lewis (2000) South Africa -0.8 to –1.0 Bonnel (2000) 47 countries -0.7 Kambou, Devarajan and Over (1992) Over (1992) Cameroon -0.5 to –1.2 30 countries -0.3 to –0.6 Sackey and Swaziland, Raparla (2000) Lesotho, Namibia -0.8 to –1.5 How HIV/AIDS affects the economy (cont’d) Human capital • AIDS kills young adults • Reduces incentive and means to invest in children’s education • Reduces parents’ transmission of knowledge to their children Implications Children’s ability to invest in their children’s education is lower, and so on… Vicious cycle Previous estimates of impact of AIDS may seriously underestimate the long-run impact Overlapping-generations model Λt = family’s human capital at t s=state of family (father dies, mother dies, etc.) z(s)Λt(s) = transmission of knowledge from parents to children e=amount of education Then: Λt+1 = z(s)Λtf(e) + 1 Overlapping generations model (cont’d) Note that e is the result of the family solving : Max EU (ct, Λt+1) s.t. y=α[Λt + 2(1-e)] Increase in probability of premature adult mortality lowers both Λt and Λt+1 Λt+1 1 45 Λ* Λt South Africa: Probabilities 1990 (no AIDS) Both alive Father dead Mother dead Both dead 0.855 0.101 0.039 0.005 South Africa: Probabilities Both alive Father dead Mother dead Both dead 1990 (no AIDS) 0.855 0.101 0.039 0.005 2010 (with AIDS) 0.294 0.168 0.347 0.194 Effect of AIDS (with pooling) No AIDS year Human capital Education Household income 1960 2.62 0.50 19.5 1990 3.14 0.64 22.3 2020 4.32 0.97 29.6 2050 7.86 1.00 53.7 2080 13.85 1.00 94.7 Effect of AIDS No AIDS AIDS Household income Human Education Household income 0.50 19.5 2.62 0.5 19.5 3.14 0.64 22.3 3.14 0.2 26.4 2020 4.32 0.97 29.6 2.01 0 17.8 2050 7.90 1.00 53.7 1.00 0 12.9 2080 13.85 1.00 94.7 1.00 0 12.9 year Human capital Education 1960 2.62 1990 capital Policy responses Spend on public goods to reduce premature mortality • Need additional spending of 3-4% of GDP per year to restore growth Lump-sum subsidies to families • Modest growth restored School-attendance subsidies • Rapid growth restored Kenya: Probability of premature adult mortality 1990 2010 2030 2040 No AIDS 0.148 0.080 0.0025 0.022 AIDS 0.353 0.359 0.154 0.111 Kenya No AIDS AIDS year Human capital Education Household income Human capital Education Household income 1990 3.7 0.57 2715 3.7 0.44 2725 2000 3.9 0.66 2317 3.5 0.50 2210 2020 6.0 1.00 2921 4.5 0.78 2323 2030 8.1 1.00 3438 5.8 0.95 2776 2040 10.2 1.00 4168 7.4 1.00 3294 India Overall prevalence rate <1% BUT: Six states have generalized epidemics (>1% prevalence reported in prenatal clinics) In one of these states (Tamil Nadu), percentage of truckers paying for sex rose in 2002 (to 21%) • Only 37% of them used condoms In Orissa, 61% of women have never heard of AIDS Conclusion AIDS is different from other diseases since it affects young adults Economic impact of AIDS is not just on this generation, but the next, whose education will suffer Economic costs can be huge, and felt many years from now Early and strong action can reduce these costs