2020
DOI: 10.2139/ssrn.3601143
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The Cost of Privacy: Welfare Effects of the Disclosure of Covid-19 Cases

Abstract: for helpful comments. We use proprietary data from SK Telecom and thank Geovision at SK Telecom and Brian Kim for their assistance with the data. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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Cited by 26 publications
(33 citation statements)
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“…3 Our planning problem determines the fraction of each origin-destination commuting flow allowed to operate at each point in time, under a probability that a vaccine becomes available, to minimize the discounted economic costs and the loss of lives. A planner could control the full commuting matrix through policies that close businesses, preclude commutes from specific areas, or disclose publicly the location of confirmed cases so residents take precautionary measures, as in the case of Seoul (see Argente et al, 2020). We apply the model using real-time commuting data across districts in two South Korean cities, Seoul and Daegu, and cellphone mobility data across counties in the NYC Metro area (NYM).…”
Section: Introductionmentioning
confidence: 99%
“…3 Our planning problem determines the fraction of each origin-destination commuting flow allowed to operate at each point in time, under a probability that a vaccine becomes available, to minimize the discounted economic costs and the loss of lives. A planner could control the full commuting matrix through policies that close businesses, preclude commutes from specific areas, or disclose publicly the location of confirmed cases so residents take precautionary measures, as in the case of Seoul (see Argente et al, 2020). We apply the model using real-time commuting data across districts in two South Korean cities, Seoul and Daegu, and cellphone mobility data across counties in the NYC Metro area (NYM).…”
Section: Introductionmentioning
confidence: 99%
“…Early contributions in this respect include Goenka and Liu (2012), Geoffard and Philipson (1996). Recent work includes Acemoglu et al (2020b), Aguirregabiria et al (2020), Argente et al (2020), Bethune and Korinek (2020), Farboodi et al (2020), Fernandez-Villaverde and Jones (2020), Greenwood et al (2019), Keppo et al (2020), Toxvaerd (2020), as well as several of the papers cited above regarding spatial extensions of SIR; see Bisin and Moro (2020b) for an introduction to formal modeling of forward looking rational choice in SIR.…”
Section: Related Literaturementioning
confidence: 99%
“…We conduct the heterogeneity analysis by age to further examine potential mechanisms which would cause a decrease in foot traffic in the cluster during weekdays. Since the coronavirus presents a more severe health risk to older individuals, existing studies have shown that older people have a stronger incentive to avoid the risk of infection (Argente, Hsieh, and Lee, 2020;Brotherhood et al, 2020). However, the individuals linked to this building were ordered to selfquarantine, and their average age was 38 years (Park et al, 2020).…”
Section: Effects On Foot Trafficmentioning
confidence: 99%
“…Recent simulation-based studies, investigating trade-offs between health benefits and economic costs by the form and intensity of NPIs, predict that the pandemic can be controlled without complete lockdowns (Acemoglu et al, 2020;Argente, Hsieh, and Lee, 2020;Aum, Lee, and Shin, 2020;Chen and Qiu, 2020;Chudik, Pesaran and Rebucci, 2020;Fajgelbaum et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
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