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A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses

Author

Listed:
  • Giampiero Marra
  • Rosalba Radice
  • Till Bärnighausen
  • Simon N. Wood
  • Mark E. McGovern
Abstract
Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population and to evaluate the effectiveness of population-based interventions and campaigns. However, participation rates in testing for surveillance conducted as part of household surveys, on which many of these estimates are based, can be low. HIV positive individuals may be less likely to participate because they fear disclosure, in which case estimates obtained using conventional approaches to deal with missing data, such as imputation-based methods, will be biased. We develop a Heckman-type simultaneous equation approach which accounts for non-ignorable selection, but unlike previous implementations, allows for spatial dependence and does not impose a homogeneous selection process on all respondents. In addition, our framework addresses the issue of separation, where for instance some factors are severely unbalanced and highly predictive of the response, which would ordinarily prevent model convergence. Estimation is carried out within a penalized likelihood framework where smoothing is achieved using a parametrization of the smoothing criterion which makes estimation more stable and efficient. We provide the software for straightforward implementation of the proposed approach, and apply our methodology to estimating national and sub-national HIV prevalence in Swaziland, Zimbabwe and Zambia.

Suggested Citation

  • Giampiero Marra & Rosalba Radice & Till Bärnighausen & Simon N. Wood & Mark E. McGovern, 2016. "A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses," Economics Working Papers 16-02, Queen's Management School, Queen's University Belfast.
    • Handle: RePEc:qub:wpaper:1602
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    References listed on IDEAS

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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Sam Watson’s journal round-up for 21st August 2017
      by Sam Watson in The Academic Health Economists' Blog on 2017-08-21 16:00:35

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    4. Nadja Klein & Thomas Kneib & Giampiero Marra & Rosalba Radice & Slawa Rokicki & Mark E. McGovern, 2018. "Mixed Binary-Continuous Copula Regression Models with Application to Adverse Birth Outcomes," CHaRMS Working Papers 18-06, Centre for HeAlth Research at the Management School (CHaRMS).
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    7. Wojtyś, Małgorzata & Marra, Giampiero & Radice, Rosalba, 2018. "Copula based generalized additive models for location, scale and shape with non-random sample selection," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 1-14.
    8. Giampiero Marra & Rosalba Radice & David M. Zimmer, 2020. "Estimating the binary endogenous effect of insurance on doctor visits by copula‐based regression additive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 953-971, August.
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    11. McGovern, Mark E. & Canning, David & Bärnighausen, Till, 2018. "Accounting for non-response bias using participation incentives and survey design: An application using gift vouchers," Economics Letters, Elsevier, vol. 171(C), pages 239-244.
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    15. Dettoni, Robinson & Gil-Alana, Luis Alberiko, 2023. "Testing the hypothesis of duration dependence in the U.S. housing market," Finance Research Letters, Elsevier, vol. 58(PD).

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    More about this item

    Keywords

    Heckman-Type Selection Model; HIV; Penalized Regression Splines; Selection Bias; Simultaneous Equation Models; Spatial Dependence;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General

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