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The Economic Impact of HIV/AIDS
Shekhar ShahShekhar Shah
Mainstreaming HIV/AIDS WorkshopMainstreaming HIV/AIDS Workshop
Bangkok, September 12, 2005Bangkok, September 12, 2005
Based on Bell, Devarajan, and Gerbasch, 2003 and 2004Based on Bell, Devarajan, and Gerbasch, 2003 and 2004
Messages
• 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 and well-being will suffer
• Economic costs can be huge, and felt many years from now
• Early and strong action can reduce these costs
When mostly young and prime-age adults fall ill or die…
• Morbidity reduces job productivity, death destroys human capital
• Firms & economies lose trained workers• Substantial public/private expenditures incurred
for treatment & care• Savings diverted from physical/human capital
investment to treatment & replacement of workers
When mostly young and prime-age adults fall ill or die
• Lifetime family income and ability to invest greatly reduced
• Children lose love, care, guidance and knowledge of one or both parents
• Tax base shrinks• Collaterization in credit markets becomes
difficult• Social cohesion and social capital decline
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 theimpact of AIDS on annual GDP growth rates (%)
-0.8 to –1.5-0.8 to –1.5Swaziland, Swaziland, Lesotho, Lesotho, NamibiaNamibia
Sackey and Sackey and Raparla (2000)Raparla (2000)
-0.3 to –0.6-0.3 to –0.630 countries30 countriesOver (1992)Over (1992)
-0.5 to –1.2-0.5 to –1.2CameroonCameroonKambou, Kambou, Devarajan and Devarajan and Over (1992)Over (1992)
-0.7-0.747 countries47 countriesBonnel (2000)Bonnel (2000)
-0.8 to –1.0-0.8 to –1.0South AfricaSouth AfricaArndt and Arndt and Lewis (2000)Lewis (2000)
How HIV/AIDS affects the economy
• 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
South Africa: Probabilities
0.0050.0050.0390.0390.1010.1010.8550.8551990 1990 (no (no AIDS)AIDS)
Both Both deaddead
Mother Mother deaddead
Father Father deaddead
Both Both alivealive
South Africa: Probabilities
0.1940.1940.3470.3470.1680.1680.2940.2942010 2010 (with (with AIDS)AIDS)
0.0050.0050.0390.0390.1010.1010.8550.8551990 1990 (no (no AIDS)AIDS)
Both Both deaddead
Mother Mother deaddead
Father Father deaddead
Both Both alivealive
Effect of AIDS (with pooling)
94.794.71.001.0013.8513.8520802080
53.753.71.001.007.867.8620502050
29.629.60.970.974.324.3220202020
22.322.30.640.643.143.1419901990
19.519.50.500.502.622.6219601960
Household Household incomeincome
EducationEducationHuman Human capitalcapital
yearyear
No AIDSNo AIDS
Effect of AIDS
12.912.9001.001.0094.794.71.001.0013.8513.8520802080
12.912.9001.001.0053.753.71.001.007.907.9020502050
17.817.8002.012.0129.629.60.970.974.324.3220202020
26.426.40.20.23.143.1422.322.30.640.643.143.1419901990
19.519.50.50.52.622.6219.519.50.500.502.622.6219601960
Household Household incomeincome
EducatioEducationn
Human Human capitalcapital
Household Household incomeincome
EducationEducationHuman Human capitalcapital
yearyear
AIDSAIDSNo AIDSNo AIDS
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
0.1110.1110.1540.1540.3590.3590.3530.353AIDSAIDS
0.0220.0220.00250.00250.0800.0800.1480.148No AIDSNo AIDS
20402040203020302010201019901990
Kenya
329432941.001.007.47.4416841681.001.0010.210.220402040
277627760.950.955.85.8343834381.001.008.18.120302030
232323230.780.784.54.5292129211.001.006.06.020202020
221022100.500.503.53.5231723170.660.663.93.920002000
272527250.440.443.73.7271527150.570.573.73.719901990
Household Household incomeincome
EducationEducationHuman Human capitalcapital
Household Household incomeincome
EducationEducationHuman Human capitalcapital
yearyear
AIDSAIDSNo AIDSNo AIDS
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
HIV Estimates : India 1981 to 2003
00.2
1.75
3.5 3.7 3.86 3.974.58 5.1
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
No
. est
imat
ed a
s H
IV in
fect
ed
(in
mill
ion
s)
1981 1990 1994 1998 1999 2000 2001 2002 2003
Year
0
20000
40000
60000
80000
100000
120000
No of AIDS cases 6 11 14 34 60 108 290 659 1017 2108 3161 545 6690 9966 16722 31336 42947 61201 102733
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Cumulative Number of AIDS cases in India December, 2004
(n=1,02,733)
Year
No. of AIDS cases
HIV Prevalence at ANC Site <1
HIV Prevalence at ANC Site 1-2
HIV Prevalence at ANC Site 2-3
HIV Prevalence at ANC Site >=3
Source: NACO’s Sentinel Surveillance data: ANC sites (2001, 2003)
Sub National Epidemics More Serious
Source:UNAID
S
25
20
15
10
5
0
Percent of infected adults
1990 91 92 93 94 95 96 97 98 99 2000
South Africa
Thailand
Year
Note: Thailand‘s aggressive HIV control program has hept the infection rate relatively low over the past decade. South Africa did not implement an HIV control program and the rate climbed precipitously.
HIV/AIDS in South Africa and ThailandEffect of intervention
You are HERE
Possible regional scenarios
• Containment and zero growth by 2007, i.e. the Indian official goal is met
• Epidemic continues – generalized epidemic in 6 Indian states, western Nepal, and concentrated epidemics elsewhere among vulnerable groups at high risk
• Full blown epidemic in large parts of the region
Research underway in India
• Long-term economic impact – Indian Statistical Institute, New Delhi
• Costing the Free ART Program of the Government of India – Institute of Economic Growth
• Others – NCAER, NACO, etc.
Conclusions
• AIDS is different from other diseases since it affects young adults
• Economic costs can be huge, and felt many years from now
• Economic impact of AIDS is not just on this generation, but on next as well
• Early and strong action can reduce these costs• Educate and generate policy and client demand• Use knowledge & research to drive supply of
sensible program design & implementation
References
• Bell, C., S. Devarajan, and H. Gerbasch, 2004 “Thinking about the Long-run Economic Costs of AIDS” in The Macroeconomics of HIV/AIDS, ed. by Markus Haacker, Washington DC: International Monetary Fund.
• Bell, C., S. Devarajan, and H. Gerbasch, 2003 “The Long-run Economic Costs of AIDS: Theory and an Application to South Africa,” The World Bank, Policy Research Working Paper No. 0-2723.
• Das, Sanghamitra, A. Mukhopadhyay and T. Ray, 2005 “The Economic Impact of an HIV/AIDS Epidemic in India—Long term Analysis: a Model,” Planning Unit, Indian Statistical Institute, New Delhi 110 016.
• Gupta, Indrani et al, 2005 “Costing of the Free ART Programme of the Government of India, Phase I Report,” and ‘Terms of Reference: Costing the Free ART Programme of the Government of India,” Health Policy Research Unit, Institute of Economic Growth, Delhi, 2005.