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Unformatted text preview: f learning HIV results with the following regression:
(2) Yij 5 a 1 b1 GotResultsij 1 b2 1GotResultsij 3 HIVij 2 1 b3 HIVij 1 X9 m 1 eij .
ij Y indicates condom purchase at the time of the follow-up survey (as measured by whether the
respondent purchased condoms or the total number of condoms purchased) or if the respondent
reported having sex; and GotResults indicates knowledge of HIV status. The fact that individuals
choose to learn their HIV status means that OLS estimates are likely to be biased, but estimating
the effects of knowing HIV status with exogenous instruments provides unbiased estimates. In
particular, I instrument GotResults with being offered any incentive, the amount of the incentive, the amount of the incentive squared, the distance from the HIV result center, and distancesquared. Table 6 presents first-stage OLS regressions; the f-statistics for this specification and
sample of sexually active respondents are equal to 74.98 and 193.29, respectively. To account for
differential effects among men and women, I also include interactions with gender:
(3) 1 b6 1Anyij 3 Maleij 2 1 b7 1Amtij 3 Maleij 2 1 b8 1Amt2 3 Maleij 2
1 b9 1Distij 3 Maleij 2 1 b10 1Dist2 3 Maleij 2 1 X9 m 1 eij .
ij GotResultsij 5 a 1 b1 Anyij 1 b2 Amtij 1 b3 Amt2 1 b4 Distij 1 b5 Dist2
ij In equation (2), GotResults3HIV represents the differential effect of receiving an HIV-positive
diagnosis, and this is instrumented with the same set of instruments as in (3) above, interacted
by HIV status. Because the monetary incentives and distances to VCT centers were both exogenously assigned to each individual, they are uncorrelated with the error term. In the analysis,
although the measure of purchasing condoms is binary, estimates do not differ greatly from a
nonlinear specification. Both specifications are presented.
Covariates, X, include age, age-squared, a dummy for male, simulated average distance to the
VCT center, and district dummies. It is also important to point out that the IV estimates in (2) are
local average treatment effects (LATE), which represent a weighted average per-unit treatment
effect, where the weight is proportional to the number of people affected by the instruments, not
necessarily equal to the average treatment effect (Guido W. Imbens and Angrist 1994; Ang...
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