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On the Plausibility of the Latent Ignorability Assumption

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  • Martin Huber

    (Department of Economics, University of Fribourg, Bd. de Pérolles 90, 1700 Fribourg, Switzerland
    Center for Econometrics and Business Analytics, St. Petersburg State University, 199034 St. Petersburg, Russia)

Abstract

The estimation of the causal effect of an endogenous treatment based on an instrumental variable (IV) is often complicated by the non-observability of the outcome of interest due to attrition, sample selection, or survey non-response. To tackle the latter problem, the latent ignorability (LI) assumption imposes that attrition/sample selection is independent of the outcome conditional on the treatment compliance type (i.e., how the treatment behaves as a function of the instrument), the instrument, and possibly further observed covariates. As a word of caution, this note formally discusses the strong behavioral implications of LI in rather standard IV models. We also provide an empirical illustration based on the Job Corps experimental study, in which the sensitivity of the estimated program effect to LI and alternative assumptions about outcome attrition is investigated.

Suggested Citation

  • Martin Huber, 2021. "On the Plausibility of the Latent Ignorability Assumption," Econometrics, MDPI, vol. 9(4), pages 1-6, December.
    • Handle: RePEc:gam:jecnmx:v:9:y:2021:i:4:p:47-:d:698810
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    References listed on IDEAS

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    1. Hans Fricke & Markus Frölich & Martin Huber & Michael Lechner, 2020. "Endogeneity and non‐response bias in treatment evaluation – nonparametric identification of causal effects by instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 481-504, August.
    2. Markus Frölich & Martin Huber, 2014. "Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1697-1711, December.
    3. Barnard J. & Frangakis C.E. & Hill J.L. & Rubin D.B., 2003. "Principal Stratification Approach to Broken Randomized Experiments: A Case Study of School Choice Vouchers in New York City," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 299-323, January.
    4. repec:mpr:mprres:2951 is not listed on IDEAS
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