Microeconometrics with Partial Identiﬁcation

Molinari, Francesca

doi:10.1920/wp.cem.2020.1520

Cited by 38 publications

(28 citation statements)

References 302 publications

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“…Given such assumptions, the partial-identification sub-literature on intersection bounds shows how to proceed formally to tighten inference. See Manski (2020) and Molinari (2020).…”

Section: Discussionmentioning

confidence: 99%

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Estimating the COVID-19 infection rate: Anatomy of an inference problem

Manski

Molinari

2021

Journal of Econometrics

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130

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As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that, assuming accurate reporting of deaths, the infection fatality rates in Illinois, New York, and Italy are substantially lower than reported.

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“…Given such assumptions, the partial-identification sub-literature on intersection bounds shows how to proceed formally to tighten inference. See Manski (2020) and Molinari (2020).…”

Section: Discussionmentioning

confidence: 99%

“…See Manski (1995Manski ( , 2003Manski ( , 2007 for monograph expositions at different technical levels. See Tamer (2010) and Molinari (2020) for review articles.…”

Section: Introductionmentioning

confidence: 99%

Estimating the COVID-19 infection rate: Anatomy of an inference problem

Manski

Molinari

2021

Journal of Econometrics

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130

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“…See Manski (1995;2003;2007) for monograph expositions at different technical levels. See Tamer (2010) and Molinari (2020) for review articles.…”

Section: Data Uncertaintiesmentioning

confidence: 99%

Forming COVID-19 Policy Under Uncertainty

Manski¹

2020

J. Benefit Cost Anal.

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This paper presents my thinking and concerns about formation of COVID-19 policy. Policy formation must cope with substantial uncertainties about the nature of the disease, the dynamics of transmission, and behavioral responses. Data uncertainties limit our knowledge of the past trajectory and current state of the pandemic. Data and modeling uncertainties limit our ability to predict the impacts of alternative policies. I explain why current epidemiological and macroeconomic modeling cannot deliver realistically optimal policy. I describe my recent work quantifying basic data uncertainties that make policy analysis difficult. I discuss approaches for policy choice under uncertainty and suggest adaptive policy diversification.

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“…1 Completeness can be difficult to interpret, and has been shown to be untestable (Canay, Santos, and Shaikh, 2013). Not assuming either large variation or completeness leads naturally to partial identification (Tamer, 2010;Ho and Rosen, 2017;Molinari, 2020).…”

Section: Methodological Contributionmentioning

confidence: 99%