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Demand for sex

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This study explores the demand for sexual services and its relation to condom use among clients of street sex workers in the United States. It employs ordered logit models to analyze the probability distribution of using condoms, estimating marginal effects of various socioeconomic factors. The findings highlight significant indicators affecting clients' choices, while also addressing the broader implications of risk and detection in illicit activities such as tax evasion. The results aim to inform public health strategies and policy interventions for safer sexual practices.

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Demand for sex

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Presentation Transcript

  1. Demand for sex

  2. Dependent variable

  3. Ordered structure

  4. Choice probability

  5. Probability distribution, Logistic

  6. Ordered Logit

  7. Ordered logit

  8. Likelihood

  9. Marginal effects

  10. Marginal effects

  11. Utility function, use of condoms

  12. Probability of using condoms

  13. Log likelihood

  14. What money buys: clients of street sex workers in the US • Maria Laura Di Tommaso, Marina della Guista, Isilda Shima and Steinar Strøm

  15. Table A1. Dependent variable for the ordered logit

  16. Table 6. Estimation results. Standard errors in parentheses. (Blank: Not significant. ***:Significant at 1%, **: Significant at 5%, *:Significant 10%)

  17. Table 7: Marginal effects in the ordered logit

  18. Other examples • Tax evasion and detection probabilities • What is the chance for being detected when evading taxes?

  19. The questions What is the chance of being detected: • Will certainly be detected • Will almost certainly be detected • Will perhaps be detected • Will almost certainly not be detected • Will certainly not be detected

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