This document summarizes an economics perspective on sex work in developing countries. It discusses three main points:
1) Sex work plays an integral role in the spread of HIV/AIDS due to unprotected commercial sex being a major transmission vector. HIV prevalence is much higher among sex workers than other groups in many countries.
2) Sex work provides employment for many women in poor countries and involves large financial flows. It is a significant source of income for women in developing nations.
3) Prior policy prescriptions aimed at educating sex workers on health risks have had limited success because they do not address the demand side incentives. Sex workers may rationally choose to engage in risky unprotected sex if clients are willing
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Shah 12 4-13
1. The Economics of Sex Work:
A Developing Country Perspective
Manisha Shah
Department of Public Policy
UCLA
2. Motivation
Why should we as economists/social scientists care
about sex market?
1. Integral role in spread of disease including HIV/AIDS
3. Unprotected Commercial Sex is a
Major HIV Transmission Vector
• Each day 20,000 people become infected with
HIV (UNAIDS, 2002)
• More new cases in developing countries
– Condoms are effective defense against infection
– Large amounts spent on education of SWs
– Still many SWs risk infection by not using condoms
• SW HIV infection rates are high, esp in countries
with epidemic
5. Motivation
Why should we as economists/social scientists care
about sex market?
1. Integral role in spread of disease including HIV/AIDS
2. Source of employment for many women in poor
countries (micro/macro implications)
6. COUNTRY
Africa
Benin
Burkina Faso
Cameroon
Ivory Coast
Niger
Ethiopia
Kenya
Madagascar
Location
Area
% FSW
Cotonou
Capital
1.20%
Ouagadougou Capital
4.30%
Yaoundé
Capital
2.20%
Abidjan
Capital
0.70%
Niamey
Capital
2.60%
Addis Ababa Capital
2.10%
Kisumu
Provincial town 3.00%
Busia, Mumias Provincial town 6.90%
Diego-Suarez Provincial town 12.00%
Year
2001
2000–03
1997
2000
2004
2002
1997
1999
2001
Asia
India
Nepal
Indonesia
Cambodia
Mumbai
Kathmandu
Jakarta
Phnom Penh
Capital of State
District
Province
Province
0.50%
1.00%
1.40%
2.80%
2001
2001
2002
2003
Latin America
Dom Republic
Belize
Haiti
Bolivia
Colombia
Peru
Venezuela
–
–
–
–
–
–
–
–
–
–
–
–
–
–
1.80%
7.40%
2.00%
0.20%
0.70%
0.30%
1.50%
2001
2001
2001
2001
2001
2001
2001
Source: J Vandepitte, R Lyerla, G Dallabetta, F Crabbé, M Alary, A Buvé. (2006)
"Estimates of the number of female sex workers in different regions of the world,"
BMJ.
7. Labor market issues
• Huge source of employment for women in developing
countries, and growing (see BMJ table)
• Financial turnover of sex sector is quite large
– Indonesian financial turnover of sex sector was estimated at
between U.S 1.2 and 3.3 billion, or between 0.8 and 2.4% of the
country's GDP (Lim, 1998).
– Thailand, close to US 300 million was transferred annually from
urban SWs to rural areas in the form of remittances (Lim, 1998).
8. Motivation
Why should we as economists/social scientists care
about sex market?
1. Integral role in spread of disease including HIV/AIDS
2. Source of employment for many women in poor
countries (micro/macro implications)
3. Failure of policy prescriptions
9. Today we will….
•
Discuss three questions from an economists
perspective:
1. Why do sex workers engage in non-condom use?
(Gertler, Shah, Bertozzi, JPE 2005; Rao et. al JDE 2003)
10. Today we will….
•
Discuss three questions from an economists
perspective:
1. Why do sex workers engage in non-condom use?
(Gertler, Shah, Bertozzi, JPE 2005; Rao et. al JDE 2003)
2. Why do women enter the sex market?
(Robinson and Yeh, 2011; Edlund and Korn, JPE 2002;
Arunachalam and Shah, AER 2008)
11. Today we will….
•
Discuss three questions from an economists
perspective:
1. Why do sex workers engage in non-condom use?
(Gertler, Shah, Bertozzi, JPE 2005; Rao et. al JDE 2003)
2. Why do women enter the sex market?
(Robinson and Yeh, 2011; Edlund and Korn, JPE 2002;
Arunachalam and Shah, AER 2008)
3. How can public policy/laws/regulations related to sex
market impact the spread of disease? (Gertler and Shah JLE
2011, Shah and Cunningham 2013)
•
Use economic methods to investigate these
questions
12. Question:
• Do you think a sex worker should get more or less
money from a client when she does not use a
condom?
– Why or why not?
13. 1. Why do SWs engage in non-condom use?
Conventional Wisdom: Sex Workers do not use
Condoms because …
• Sex workers uninformed of risks
– Would protect themselves if understood risks
• Condoms not available or in short supply,
especially when needed
• Forced
– Physical-economic threats
– Psychological & social norms
14. Alternatively: SWs may be willing to
risk infection if compensated
• Could be rational response to client demand
– Clients value unprotected sex & are willing to pay for it
– SWs take risk if adequately compensated
• Happens in other sectors
– Compensating wage differentials for risky work
• Ex: police, firemen
15. Public Agencies Focus
Interventions on Supply Side
• Supply side interventions
– Educating SWs about risks and how to protect themselves
– Creating safe and supportive work environment – social capital
– Creating accessible supply of condoms
• However, supply-side alone will not stop unprotected sex
– If clients are willing to pay, SWs will take risk if compensated
• Alternatives
– Educate clients & lower demand for unprotected sex as well
16. We Investigate Whether SWs are
“Rationally” Responding to Incentives
• Are Sex Workers charging more to take the risk of
providing unprotected services?
17. Data Source
• Summer of 2001, wrote, piloted and attached economic
questionnaire to UNAIDS “Second Generation” study in
Mexico
• 2nd generation study tried to map universe of sex workers
in cities in 2 states
– Used this as a sampling frame
– How good was it?
• Sample of about 1034 sex workers
• Information on details of last 3-4 transactions for 3,884
observations
18. Transaction Specific Information
•
•
•
•
•
Price paid by client & received by sex worker
Services: vaginal, oral, anal, talk, dance, strip, massage
Condom use & who suggested
Non condom use & who suggested
CSW report of client characteristics: appearance,
wealth, education, personality, hygiene
• Alcohol & Drug use during transaction
• Client abused/hit sex worker
19. Table 2. Sex Worker Characteristics (N=1034)
Characteristics
Age
Age of first sexual experience
Years in sex work
Have had STIs/vaginal problems (=1)
Sex Worker is Very Attractive (=1)
Have Children (=1)
Education
Ever gone to school (=1)
Some secondary school or more (=1)
Civil Status
Single (=1)
Married or in Partnership (=1)
Divorced or Widowed (=1)
Primary Work Site
Bar/Club (=1)
Street (=1)
Other (=1)
Mean
27.82
15.65
6.04
0.17
0.21
0.62
0.84
0.36
0.41
0.22
0.38
0.82
0.12
0.06
St. Dev
7.77
2.36
6.83
20. Table 3. Client Characteristics Reported By Sex Worker (N=3837)
Regular Client (=1)
Age
Nice or Pleasant Personality (=1)
Wealth
Poor (=1)
Average Wealth (=1)
Above Average Wealth (=1)
Very Wealthy (=1)
Attractiveness
Handsome (=1)
Average (=1)
Ugly (=1)
Cleanliness
Dirty (=1)
Clean (=1)
Very Clean (=1)
Mean
0.64
36.04
0.66
0.17
0.70
0.08
0.05
0.10
0.66
0.24
0.10
0.73
0.17
Std. Dev.
11.01
21. Conducted focus groups with SWs
& Clients to Describe Market
• Clients
–
–
–
–
May not know prices or quality
Clients approach SW based on physical characteristics
Obtain information about prices & services
Clients value SW physical & personality characteristics
(e.g. beauty); pay more for these
– Client heterogeneity in tastes
– High search costs (time)
22. Sex Workers Negotiate Prices
• High search costs & client heterogeneity
able
to charge different prices to different clients
• Collects info based on appearance & conversation
to determine willingness to pay
–
–
–
–
Clothes, car, rings, cleanliness,…
Job, married, hotel, etc…
How much client likes SW …
Regular client gets charged more
23. Negotiation up front & renegotiate
as client preferences revealed
• Heterogeneity in timing of negotiation
• Some SWs (or agents) try to negotiate everything
up front – prices, services & condom use
• Terms almost always renegotiated in room
because clients ask for more or different services
• Condom use negotiated by SW and client
– Heterogeneity in client & SW preferences for condoms
24. A Bargaining Model
• Two agents
– A client who we will call “Richard”
– A sex worker called “Julia”
• Negotiate over Price & Condom Use
– Payoff functions
– Recursive solution
• Condom use
• Prices
25. Our Approach is Estimate a
Transaction Model
• Data: survey of 1050 SWs in Mexico
– Collected information on last 3-4 transactions
– Price, services, condom use & client characteristics
• Have SW panel where i indexes Sex Worker and t indexes
the transaction
• Estimate SW Fixed Effects models to control for selection
on SW characteristics
• Control for client characteristics with SW reports of client
looks, wealth, cleanliness, risk preferences
26. Table 5. Basic Log Price Fixed Effects Regressions
Whole Sample
Random
Effects
No Condom
Used
0.093
(3.91)***
Hausman Test
Fixed
Effects
Exclude
SWs Who
Never Use
Condoms
Exclude SWs
Who Always
Use
Condoms
Fixed
Effects
Fixed Effects
Exclude
Both Always
& Never
Condom
Users
Fixed
Effects
496.51***
0.132
(5.52)***
0.133
(4.19)***
0.135
(4.19)***
27.86***
F Stat SW FEs
0.131
(5.49)***
27.72***
16.09**
15.36**
# of Obs
3,837
3,837
3,753
1,309
1,225
# of SWs
1,029
1,029
1,007
363
341
27. Policy Implications (1)
• Strong evidence that
– SWs are willing to take the risk of providing
unprotected sex for a higher price
• Suggests why just educating sex workers has not
stopped HIV transmission thru unprotected sex
• Need to educate clients or provide financial
incentives for condom use to offset client WTP
28. 2. Why might women enter the sex
market?
•
•
Economic shocks/Poverty (Robinson and Yeh,2011)
Sex work pays well
(Edlund and Korn Marriage market hypothesis)
•
•
Lack of outside option
Force, kidnapping, trafficking (not discussed too
much in economics lit as we tend to assume free
choice)
29. Sex Work as a Response to Risk in Western Kenya
(Robinson and Yeh, 2011)
• Collect daily self-reported data on sexual
behavior, income shocks, expenditures, and labor
supply for sample of 237 women Western Kenya.
• Find significant day-to-day fluctuations in sex
worker decisions
• Women engage in sex-for-money transactions in
part to deal with unexpected non-labor income
shocks.
30. Pays Well
Sex work puzzle: Female dominated, low skilled,
low education—yet it pays really well.
31. Table 1: Summary statistics
Last week’s earnings
Age
None/some primary(%)
Completed primary(%)
Secondary(%)
High School(%)
University + (%)
Observations
Ecuador
(1)
Female
SWs
113.5
(154.6)
27.9
(8.01)
4.1
41.3
50.4
2.2
1.2
2782
Ecuador
(2)
Female
NSWs
50.7
(66.3)
36.2
(12.2)
2.5
23.8
40.4
1.5
31.6
1872
Ecuador
(3)
Domestic
Worker NSWs
37.6
(44.6)
37.1
(12.8)
4.1
35.8
45.2
0.7
14.0
1020
Ecuador
(4)
Male
SWs
80.4
(134.1)
24.0
(6.92)
2.3
25.6
63.2
3.8
4.5
574
Ecuador
(5)
Male
NSWs
67.1
(123.2)
36.7
(12.8)
1.9
32.5
42.9
1.1
21.4
3319
Mexico
(6)
Female
SWs
3886
(9785)
27.7
(7.6)
16.2
46.8
28.5
6.4
1.7
1038
Mexico
(7)
Female
NSWs
2117
(4101)
33.3
(11.3)
11.1
20.0
40.4
11.5
17.0
2454
Earnings from Ecuador are in US dollars and Mexican earnings are in pesos. Standard deviations are given in parenthesis.
11
32. Edlund-Korn (2002)
Marriage Market Hypothesis
• First formal model of prostitution in economics
• Draws intriguing link between labour and marriage
market that holds for one profession: prostitution
• Central assumption of model is that sex workers
cannot marry--in choosing SW, women relinquish
compensation otherwise received in marriage.
• Compensating differential due to foregone opportunity
to “sell” their fertility in marriage market.
33. Empirical test of the model
• Arunachalam and Shah, 2008 American Economic
Review P&P test the model
• Major findings:
– Sizable earnings premium for sex work (around 33%)
– Fail to find support for Edlund-Korn explanation
– Sex workers are actually more likely to be married than
non-sex workers at younger ages—when the earnings
premium for sex work is highest.
35. 1
Marriage rate by age
0
.2
.4
.6
.8
10
20
30
40
Age
Fitted sex workers
Fitted non−sex workers
Non−sex workers
50
60
95% CI
Sex workers
Figure 2: Marriage rates of female workers in Ecuador
70
36. An alternative hypothesis?
• Data seem to contradict prima facie case for marriage
market explanation for high returns to prostitution
• Natural competing explanation is compensating differential
due to risk
• Ecuador female sex worker data includes disease results
– Calculate DALYs lost due to observed increase in disease burden
from STIs
– Implies a compensating differential of at least 8% of sample
average earnings for sex work
• Sex work, like policework or other risky professions,
draws hazard pay.
37. Policy Implications (2)
• Programs to get women out of sex industry will
fail if alternatives don’t pay as well (most likely
won’t)
• How might we improve women’s outside option
in the labor market?
• Access to credit, savings, health insurance
(address these market failures) may reduce risky
sex and increased sex work labor supply
38. New Indonesia Project: Promoting Public Health
Through Savings for Sex Workers in Indonesia
• Provide mobile banking savings accounts to sex workers in
Indonesia
• Randomize into 3 groups:
1.
2.
3.
Control (business as usual)
T1: Offer savings account
T2: Offer savings account + financial incentive
• Follow sex workers for year, collecting daily data to test
hypotheses like:
1.
2.
3.
Do formal savings accounts increase savings for FSWs?
Do formal savings accounts improve strategies for coping with negative income shocks?
Do formal savings accounts decrease risky behavior among FSWs during commercial sex
transactions?
39. 3. How can public policy/laws/regulations impact
the spread of disease?
• Ecuador project: Collected data on 2000 SWs in 8
cities (plus biologicals) and collected data from
police about # of enforcement visits of carnet laws
• Increased enforcement in street decreases STI
prevalence but increases in brothel sector
– Why?
• Marginal woman on street moves to brothel sector (less risky,
less disease). Street prices increase, clients decrease
• Marginal woman from brothel moves to street
40. Rhode Island Study
• Indoor prostitution decriminalized “accidentally”
from 2003-2009 in RI
• Indoor sex sector grows—supply increases
• Gonorrhea incidence decreases
