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The Economics of Sex Work:
A Developing Country Perspective
Manisha Shah
Department of Public Policy
UCLA
Motivation
Why should we as economists/social scientists care
about sex market?
1. Integral role in spread of disease incl...
Unprotected Commercial Sex is a
Major HIV Transmission Vector
• Each day 20,000 people become infected with
HIV (UNAIDS, 2...
HIV Prevalence (Per Hundred) 1999
Country
Benin
Burkina Faso
Cameroon
Congo D.R.
Congo, Rep
Ivory Coast
Ethiopia
Gambia
Gh...
Motivation
Why should we as economists/social scientists care
about sex market?
1. Integral role in spread of disease incl...
COUNTRY
Africa
Benin
Burkina Faso
Cameroon
Ivory Coast
Niger
Ethiopia
Kenya
Madagascar

Location

Area

% FSW

Cotonou
Cap...
Labor market issues
• Huge source of employment for women in developing
countries, and growing (see BMJ table)
• Financial...
Motivation
Why should we as economists/social scientists care
about sex market?
1. Integral role in spread of disease incl...
Today we will….
•

Discuss three questions from an economists
perspective:
1. Why do sex workers engage in non-condom use?...
Today we will….
•

Discuss three questions from an economists
perspective:
1. Why do sex workers engage in non-condom use?...
Today we will….
•

Discuss three questions from an economists
perspective:
1. Why do sex workers engage in non-condom use?...
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...
1. Why do SWs engage in non-condom use?
Conventional Wisdom: Sex Workers do not use
Condoms because …
• Sex workers uninfo...
Alternatively: SWs may be willing to
risk infection if compensated
• Could be rational response to client demand
– Clients...
Public Agencies Focus
Interventions on Supply Side
• Supply side interventions
– Educating SWs about risks and how to prot...
We Investigate Whether SWs are
“Rationally” Responding to Incentives
• Are Sex Workers charging more to take the risk of
p...
Data Source
• Summer of 2001, wrote, piloted and attached economic
questionnaire to UNAIDS “Second Generation” study in
Me...
Transaction Specific Information
•
•
•
•
•

Price paid by client & received by sex worker
Services: vaginal, oral, anal, t...
Table 2. Sex Worker Characteristics (N=1034)
Characteristics
Age
Age of first sexual experience
Years in sex work
Have had...
Table 3. Client Characteristics Reported By Sex Worker (N=3837)

Regular Client (=1)
Age
Nice or Pleasant Personality (=1)...
Conducted focus groups with SWs
& Clients to Describe Market
• Clients
–
–
–
–

May not know prices or quality
Clients app...
Sex Workers Negotiate Prices
• High search costs & client heterogeneity
able
to charge different prices to different clien...
Negotiation up front & renegotiate
as client preferences revealed
• Heterogeneity in timing of negotiation
• Some SWs (or ...
A Bargaining Model
• Two agents
– A client who we will call “Richard”
– A sex worker called “Julia”

• Negotiate over Pric...
Our Approach is Estimate a
Transaction Model
• Data: survey of 1050 SWs in Mexico
– Collected information on last 3-4 tran...
Table 5. Basic Log Price Fixed Effects Regressions

Whole Sample

Random
Effects
No Condom
Used

0.093
(3.91)***

Hausman ...
Policy Implications (1)
• Strong evidence that
– SWs are willing to take the risk of providing
unprotected sex for a highe...
2. Why might women enter the sex
market?
•
•

Economic shocks/Poverty (Robinson and Yeh,2011)
Sex work pays well
(Edlund a...
Sex Work as a Response to Risk in Western Kenya
(Robinson and Yeh, 2011)
• Collect daily self-reported data on sexual
beha...
Pays Well
Sex work puzzle: Female dominated, low skilled,
low education—yet it pays really well.
Table 1: Summary statistics

Last week’s earnings
Age
None/some primary(%)
Completed primary(%)
Secondary(%)
High School(%...
Edlund-Korn (2002)
Marriage Market Hypothesis
• First formal model of prostitution in economics
• Draws intriguing link be...
Empirical test of the model
• Arunachalam and Shah, 2008 American Economic
Review P&P test the model
• Major findings:
– S...
200
150
Weekly earnings
0
50
100
10

20

30

40
Age

Fitted sex workers
Fitted non−sex workers
Non−sex workers

50

60
95%...
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...
An alternative hypothesis?
• Data seem to contradict prima facie case for marriage
market explanation for high returns to ...
Policy Implications (2)
• Programs to get women out of sex industry will
fail if alternatives don’t pay as well (most like...
New Indonesia Project: Promoting Public Health
Through Savings for Sex Workers in Indonesia
• Provide mobile banking savin...
3. How can public policy/laws/regulations impact
the spread of disease?
• Ecuador project: Collected data on 2000 SWs in 8...
Rhode Island Study
• Indoor prostitution decriminalized “accidentally”
from 2003-2009 in RI
• Indoor sex sector grows—supp...
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  1. 1. The Economics of Sex Work: A Developing Country Perspective Manisha Shah Department of Public Policy UCLA
  2. 2. Motivation Why should we as economists/social scientists care about sex market? 1. Integral role in spread of disease including HIV/AIDS
  3. 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
  4. 4. HIV Prevalence (Per Hundred) 1999 Country Benin Burkina Faso Cameroon Congo D.R. Congo, Rep Ivory Coast Ethiopia Gambia Ghana Kenya Malawi Mali Nigeria Rwanda Uganda Zimbabwe Guyana Haiti Honduras Jamaica Mexico Cambodia India Myanmar Thailand Adult Pregnant Women Sex Workers 1.2 6.7 3.0 3.7 7.2 6.8 2.5 2.1 2.3 8.3 13.6 1.3 2.2 7.2 14.5 17.4 1.3 4.4 1.6 0.9 0.4 1.9 0.4 1.5 2.1 0.4 12.0 1.9 4.6 7.1 11.6 4.9 1.7 2.2 13.7 32.8 3.5 3.8 25.3 21.2 35.2 6.9 8.4 1.0 0.7 0.0 3.2 0.3 1.3 2.4 53.3 60.4 21.2 30.3 49.2 67.6 67.5 34.7 30.8 85.5 78.0 55.5 22.5 87.9 86.0 86.0 25.0 41.9 20.5 24.6 0.1 43.0 51.0 18.2 18.8
  5. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 16. We Investigate Whether SWs are “Rationally” Responding to Incentives • Are Sex Workers charging more to take the risk of providing unprotected services?
  17. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 30. Pays Well Sex work puzzle: Female dominated, low skilled, low education—yet it pays really well.
  31. 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. 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. 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.
  34. 34. 200 150 Weekly earnings 0 50 100 10 20 30 40 Age Fitted sex workers Fitted non−sex workers Non−sex workers 50 60 95% CI Sex workers Figure 1: Weekly earnings of female workers in Ecuador (U.S. dollars) 70
  35. 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. 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. 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. 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. 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. 40. Rhode Island Study • Indoor prostitution decriminalized “accidentally” from 2003-2009 in RI • Indoor sex sector grows—supply increases • Gonorrhea incidence decreases
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