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Preference Heterogeneity in the Structural Estimation of Efficient Pigovian Incentives for Insecticide Spraying to Reduce Malaria

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Abstract

This paper bridges the theoretical and empirical literatures on the role of preference heterogeneity in characterizing externalities related to disease transmission. We use a theoretical structure similar to locational sorting models, which characterize equilibria in terms of marginal individuals who are indifferent between locations. In our case, the ‘locations’ are binary, consisting of whether or not to take a discrete preventative action. Individual heterogeneity arises in this structure due to variation in the costs and disutility associated with prevention. We demonstrate application of this approach in the context of participation in insecticide-based indoor residual spraying programs for malaria control in northern Uganda. We identify the parameters of our theoretical model using a stated preference choice experiment combined with estimates from published epidemiological studies. The model implies that Pigovian subsidies for participation in this context should decrease household malaria risk by 19–25%. Our approach can be applied to other bioeconomic externalities with spillovers from discrete preventative actions, including agricultural pest management and the control of pest infestations and invasive species.

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Notes

  1. To see this, examine the second line of (2): \(\underline{\eta }=- \mathop {\overbrace{\theta }}\limits ^{\left( - \right) } \mathop {\overbrace{\left[ {\rho _1 -\rho _0 } \right] }}\limits ^{\left( - \right) } - \mathop {\overbrace{\alpha C}}\limits ^{\left( + \right) } <0\).

  2. To complete this calculation, first compute the partial derivative \(\frac{\partial Q}{\partial \underline{\eta }}=\frac{\partial \left[ {\int _ {\underline{\eta }}^\infty f\left( \eta \right) d\eta } \right] }{\partial \underline{\eta }}=-f\left( \underline{\eta }\right) \).

  3. Comparative statics of laissez faire and socially optimal equilibria \(Q^{*}\) and \(Q^{o}\) with respect to any model parameter then proceed using the Implicit Function Theorem applied to equation system (2) and (5) respectively, as shown in the supplementary material.

  4. While tangential to the focus of this paper, it should be noted that a rebel insurgency that began in the 1980s and persisted into the 2000s demolished much of the infrastructure in northern Uganda, and resulted in the displacement of a number of inhabitants in the north. These “internally displaced persons” (IDPs) were relocated into IDP camps. IRS was used extensively in these camps because the high population densities made it a relatively cost-effective control strategy. However, once the IDPs returned to their home-sites (a process that occupied a period between 2008 and 2009), IRS services continued intermittently, though their frequency was reduced due to increased cost of accessing the more remote locations.

  5. This information is based on an in-person interview with a field manager of the USAID-funded spray teams in 2009.

  6. The algorithm was implemented by the author by pre-defining the levels for the relevant attributes and maximizing the determinant of the Fischer information matrix assuming a multinomial probit model estimated on the set of 30 choice tasks, and subject to the constraint that in each choice task IRS alternatives were always associated with a lower level of malaria risk than in the money-only option. While the probit model was not an ideal choice for this procedure, this does not threaten the consistency of the econometric estimates (since respondents were randomly assigned to one of the ten versions of the questionnaire), only their efficiency.

  7. See Annex for additional econometric specifications with estimates. In general, respondent characteristics were not significant in any estimations (with the exception of the variables included above), and most importantly the estimated coefficients on the attributes were robust to the inclusion of respondent characteristics.

  8. Without any commitment mechanism to bind households to multiple spray rounds, our theoretical formulation seems most suitable for the research aim of identifying efficient per-round Pigovian incentives for disease exteranalities.

  9. A derivation of this formula is available on request from the authors.

  10. Oster hence argues that an effective behavioral intervention to increase vaccination would be to more widely publicize recent outbreaks. While intuitive, such an approach seems inherently inadequate for preventing outbreaks. The model presented above suggests that Pigovian subsidies combined with educational campaigns informing respondents about actual disease risks may provide a more effective preventative intervention.

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Authors and Affiliations

  1. Department of Agricultural and Resource Economics and Genetic Engineering and Society Center, North Carolina State University, Raleigh, NC, USA

    Zachary S. Brown

  2. Nicholas School of the Environment and Duke Global Health Institute, Duke University, Durham, NC, USA

    Randall A. Kramer

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  1. Zachary S. Brown
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  2. Randall A. Kramer
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Correspondence to Zachary S. Brown.

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Brown, Z.S., Kramer, R.A. Preference Heterogeneity in the Structural Estimation of Efficient Pigovian Incentives for Insecticide Spraying to Reduce Malaria. Environ Resource Econ 70, 169–190 (2018). https://doi.org/10.1007/s10640-017-0115-x

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