Overview
Florian Heiss is an econometrician, formerly at the Munich Center for the Economics of Aging (MEA) at Mannheim, later at the University of Munich (LMU). His research focuses on latent-variable models, discrete choice, and the econometrics of health and aging. He is co-author with Axel Börsch-Supan, Michael Hurd, and David Wise of Heiss et al. (2007), which estimated a latent-health model on HRS data addressing selective mortality, state dependence, unobserved heterogeneity, and misclassification error. He is also sole author of Heiss (2011), which provides the published econometric proof that an AR(1) latent health model dominates standard panel approaches and quantifies the survivorship bias decomposition for the HRS age profile.
Key Contributions
- Heiss et al. (2007) — co-author; latent Ornstein-Uhlenbeck health model on all four HRS cohorts; selective mortality bias; OR = 1.76 for work disability → mortality; 43 pp survival gap at age 70 by initial health status. See Morbidity-Mortality Distinction and DI Beneficiary Mortality.
- Heiss (2011) — sole author; published in Empirical Economics 40: 119–140; joint latent AR(1) health-mortality model; proves AR(1) dominates RE, state-dependence, and state-dep+RE on all standard model-selection criteria; survivorship decomposition: at ages 80–89, direct aging effect +13.95 pp but selection −12.28 pp; female SRHS paradox (direct −2.64 pp, selection +2.55 pp, net −0.08 pp). See Selective Mortality.
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