Impact of the Collection Mode on Labor Income Data. A Study in the Times of COVID-19

44 Pages Posted: 30 Sep 2022

See all articles by Andrés Felipe García-Suaza

Andrés Felipe García-Suaza

Universidad del Rosario

Jose Lobo

Superintendencia Nacional de Salud

Sergio Montoya

Organization for Economic Co-Operation and Development (OECD)

Juan Ordoñez-Herrera

Departamento Administrativo Nacional de Estadística - DANE

Juan Daniel Oviedo Arango

Universidad del Rosario

Abstract

The strict confinement implemented by the National Government of Colombia to contain the expansion of the pandemic caused by COVID-19 generated challenges in data collection operations through household surveys. As a result, the surveys with face-to-face collection methods migrated to a remote mode, through telephone surveys, which could have changed the possible reporting biases of variables, such as income. This paper studies the effect of the change in the information collection model in the Great Integrated Household Survey (Gran Encuesta Integrada de Hogares) of Colombia on the report of labor income. To do this, we exploit the geographical variation in implementing collection methods and an integration of the survey with a social security administrative record to quantify the variation on the report.

Keywords: Household surveys, measurement bias, labor income, administrative data, COVID-19, Colombia

Suggested Citation

García-Suaza, Andrés Felipe and Lobo, Jose and Montoya, Sergio and Ordoñez-Herrera, Juan and Oviedo Arango, Juan Daniel, Impact of the Collection Mode on Labor Income Data. A Study in the Times of COVID-19. Available at SSRN: https://ssrn.com/abstract=4234486 or http://dx.doi.org/10.2139/ssrn.4234486

Andrés Felipe García-Suaza (Contact Author)

Universidad del Rosario ( email )

Calle 12 No. 6-25
Bogota, DC
Colombia

Jose Lobo

Superintendencia Nacional de Salud ( email )

Sergio Montoya

Organization for Economic Co-Operation and Development (OECD) ( email )

Juan Ordoñez-Herrera

Departamento Administrativo Nacional de Estadística - DANE ( email )

Juan Daniel Oviedo Arango

Universidad del Rosario ( email )

Calle 12 No. 6-25
Bogota, DC
Colombia

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