The Economic Impact of The Economic Impact of HIV/AIDSHIV/AIDS

Shanta DevarajanShanta Devarajan

How HIV/AIDS affects the How HIV/AIDS affects the economyeconomy

Labor supply (e.g., South African Labor supply (e.g., South African labor force expected to decline by labor force expected to decline by 12.8 percent by 2010)12.8 percent by 2010)• But: But: a 13 percent decline in labor a 13 percent decline in labor

supply reduces GDP by only 8 percent or supply reduces GDP by only 8 percent or so, implying that GDP per capita so, implying that GDP per capita risesrises

How HIV/AIDS affects the How HIV/AIDS affects the economy (cont’d)economy (cont’d)

Productivity losses (absenteeism, Productivity losses (absenteeism, retraining workers, death benefits)retraining workers, death benefits)• Estimated to add upto 15 percent to Estimated to add upto 15 percent to

companies’ wage bill (South Africa, Cote companies’ wage bill (South Africa, Cote d’Ivoire)d’Ivoire)

• But:But: Large companies especially are Large companies especially are able to adapt, reducing productivity able to adapt, reducing productivity losseslosses

How HIV/AIDS affects the How HIV/AIDS affects the economy (cont’d)economy (cont’d)

Public financesPublic finances• Increased health expenditures, reducing Increased health expenditures, reducing

public investmentpublic investment• Reduces GDP growthReduces GDP growth• But: But: Assumes that public investment Assumes that public investment

would have been productivewould have been productive

Previous estimates of thePrevious estimates of theimpact of AIDS on GDP growth (%)impact of AIDS on GDP growth (%)

Arndt and Arndt and Lewis (2000)Lewis (2000)

South AfricaSouth Africa -0.8 to –1.0-0.8 to –1.0

Bonnel (2000)Bonnel (2000) 47 countries47 countries -0.7-0.7

Kambou, Kambou, Devarajan and Devarajan and Over (1992)Over (1992)

CameroonCameroon -0.5 to –1.2-0.5 to –1.2

Over (1992)Over (1992) 30 countries30 countries -0.3 to –0.6-0.3 to –0.6

Sackey and Sackey and Raparla (2000)Raparla (2000)

Swaziland, Swaziland, Lesotho, Lesotho, NamibiaNamibia

-0.8 to –1.5-0.8 to –1.5

How HIV/AIDS affects the How HIV/AIDS affects the economy (cont’d)economy (cont’d)

Human capitalHuman capital• AIDS kills young adultsAIDS kills young adults• Reduces incentive and means to invest Reduces incentive and means to invest

in children’s educationin children’s education• Reduces parents’ transmission of Reduces parents’ transmission of

knowledge to their childrenknowledge to their children

ImplicationsImplications

Children’s ability to invest in Children’s ability to invest in theirtheir children’s education is lower, and so children’s education is lower, and so on…on…

Vicious cycleVicious cycle Previous estimates of impact of AIDS Previous estimates of impact of AIDS

may seriously underestimate the may seriously underestimate the long-run impactlong-run impact

Overlapping-generations modelOverlapping-generations model

ΛΛtt = family’s human capital at = family’s human capital at tt

s=state of family (father dies, mother s=state of family (father dies, mother dies, etc.)dies, etc.)

z(s)Λz(s)Λtt(s) = transmission of knowledge (s) = transmission of knowledge from parents to childrenfrom parents to children

e=amount of educatione=amount of education

Then: ΛThen: Λt+1t+1 = z(s)Λ = z(s)Λttf(e) + 1f(e) + 1

Overlapping generations model Overlapping generations model (cont’d)(cont’d)

Note that Note that ee is the result of the family is the result of the family solving :solving :

Max EU (cMax EU (ctt, Λ, Λt+1t+1) s.t. ) s.t.

y=α[Λy=α[Λtt + 2(1-e)] + 2(1-e)]

Increase in probability of premature Increase in probability of premature adult mortality lowers both Λadult mortality lowers both Λt t and and ΛΛt+1t+1

45

1

Λt+1

Λ* Λt

South Africa: ProbabilitiesSouth Africa: Probabilities

Both Both alivealive

Father Father deaddead

Mother Mother deaddead

Both Both deaddead

1990 1990 (no (no AIDS)AIDS)

0.8550.855 0.0.101101 0.0.039039 0.0.005005

South Africa: ProbabilitiesSouth Africa: Probabilities

Both Both alivealive

Father Father deaddead

Mother Mother deaddead

Both Both deaddead

1990 1990 (no (no AIDS)AIDS)

0.8550.855 0.0.101101 0.0.039039 0.0.005005

2010 2010 (with (with AIDS)AIDS)

0.2940.294 0.1680.168 0.3470.347 0.1940.194

Effect of AIDS (with pooling)Effect of AIDS (with pooling)No AIDSNo AIDS

yearyear Human Human capitalcapital

EducationEducation Household Household incomeincome

19601960 2.622.62 0.500.50 19.519.5

19901990 3.143.14 0.640.64 22.322.3

20202020 4.324.32 0.970.97 29.629.6

20502050 7.867.86 1.001.00 53.753.7

20802080 13.8513.85 1.001.00 94.794.7

Effect of AIDSEffect of AIDSNo AIDSNo AIDS AIDSAIDS

yearyear Human Human capitalcapital

EducationEducation Household Household incomeincome

Human Human capitalcapital

EducatioEducationn

Household Household incomeincome

19601960 2.622.62 0.500.50 19.519.5 2.622.62 0.50.5 19.519.5

19901990 3.143.14 0.640.64 22.322.3 3.143.14 0.20.2 26.426.4

20202020 4.324.32 0.970.97 29.629.6 2.012.01 00 17.817.8

20502050 7.907.90 1.001.00 53.753.7 1.001.00 00 12.912.9

20802080 13.8513.85 1.001.00 94.794.7 1.001.00 00 12.912.9

Policy responsesPolicy responses

Spend on public goods to reduce Spend on public goods to reduce premature mortalitypremature mortality• Need additional spending of 3-4% of Need additional spending of 3-4% of

GDP per year to restore growthGDP per year to restore growth Lump-sum subsidies to familiesLump-sum subsidies to families

• Modest growth restoredModest growth restored School-attendance subsidiesSchool-attendance subsidies

• Rapid growth restoredRapid growth restored

Kenya: Probability of premature Kenya: Probability of premature adult mortalityadult mortality

19901990 20102010 20302030 20402040

No AIDSNo AIDS 0.1480.148 0.0800.080 0.00250.0025 0.0220.022

AIDSAIDS 0.3530.353 0.3590.359 0.1540.154 0.1110.111

KenyaKenya

No AIDSNo AIDS AIDSAIDS

yearyear Human Human capitalcapital

EducationEducation Household Household incomeincome

Human Human capitalcapital

EducationEducation Household Household incomeincome

19901990 3.73.7 0.570.57 27152715 3.73.7 0.440.44 27252725

20002000 3.93.9 0.660.66 23172317 3.53.5 0.500.50 22102210

20202020 6.06.0 1.001.00 29212921 4.54.5 0.780.78 23232323

20302030 8.18.1 1.001.00 34383438 5.85.8 0.950.95 27762776

20402040 10.210.2 1.001.00 41684168 7.47.4 1.001.00 32943294

IndiaIndia

Overall prevalence rate <1%Overall prevalence rate <1% BUT: Six states have BUT: Six states have generalized generalized

epidemicsepidemics (>1% prevalence reported in (>1% prevalence reported in prenatal clinics)prenatal clinics)

In one of these states (Tamil Nadu), In one of these states (Tamil Nadu), percentage of truckers paying for sex rose percentage of truckers paying for sex rose in 2002 (to 21%)in 2002 (to 21%)• Only 37% of them used condomsOnly 37% of them used condoms

In Orissa, 61% of women have never heard In Orissa, 61% of women have never heard of AIDSof AIDS

ConclusionConclusion

AIDS is different from other diseases since AIDS is different from other diseases since it affects young adultsit affects young adults

Economic impact of AIDS is not just on this Economic impact of AIDS is not just on this generation, but the next, whose education generation, but the next, whose education will sufferwill suffer

Economic costs can be huge, and felt Economic costs can be huge, and felt many years from nowmany years from now

Early and strong action can reduce these Early and strong action can reduce these costscosts