We use cookies to provide you with the best possible website experience. This includes cookies that are necessary for the operation of the site, as well as cookies used for anonymous statistics, comfort settings, or displaying personalized content. You can decide which categories you want to allow. Please note that depending on your settings, some features of the website may not be available.

Cookie settings

These necessary cookies are required to enable the core functionality of the website. Opting out of these cookies is not possible.

cb-enable
This cookie stores the user's cookie consent status for the current domain. Expiry: 1 year.
laravel_session
Stores the session ID to recognize the user when the page reloads and to restore their login session. Expiry: 2 hours.
XSRF-TOKEN
Provides CSRF protection for forms. Expiry: 2 hours.
IZA Discussion Paper No. 7288
March 2013
Estimating Obesity Rates in the Presence of Measurement Error

published as 'Bounding Obesity Rates in the Presence of Self-Reporting Errors' in; Empirical Economics, 2016, 50, 857-871

Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. In this paper we examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. We combine self-reported data on BMI with estimated misclassification rates obtained from auxiliary data to derive upper and lower bounds for the population obesity rate for ten European countries. For men it is possible to obtain meaningful comparisons across countries even after accounting for measurement error. In particular the self-reported data identifies a set of low obesity countries consisting of Denmark, Ireland, Italy, Greece and Portugal and a set of high obesity countries consisting of Spain and Finland. However, it is more difficult to rank countries by female obesity rates. Meaningful rankings only emerge when the misclassification rate is bounded at a level that is much lower than that observed in auxiliary data. A similar limit on misclassification rates is also needed before we can begin to observe meaningful gender differences in obesity rates within countries.

Kommunikation
Mark Fallak
mark.fallak@liser.lu
+352 585-855-526
World of Labour
Olga Nottmeyer
olga.nottmeyer@liser.lu
+352 585-855-501
Netzwerkkoordination
Christina Gathmann
christina.gathmann@liser.lu

Das IZA@LISER-Netzwerk ist eine weltweite Gemeinschaft für exzellente Forschung in der Arbeitsmarktökonomie und angrenzenden Fachgebieten. Nach dem Wechsel von Bonn wird das Netzwerk nun am Luxembourg Institute of Socio-Economic Research (LISER) koordiniert.

Über das IZA@LISER Network
Contact
IZA Network (Current Site Operator):

Luxembourg Institute of Socio-Economic Research (LISER)
11, Porte des Sciences
Maison des Sciences Humaines
L-4366 Esch-sur-Alzette / Belval, Luxembourg

IZA Institute (In Liquidation):

Forschungsinstitut zur Zukunft der Arbeit GmbH i. L.
Schaumburg-Lippe-Str. 5-9, 53113 Bonn. Germany
Phone: +49 228 3894-0 | Fax: +49 228 3894-510
E-Mail: info@iza.org | Web: www.iza.org
Represented by: Martin T. Clemens (Liquidator)