Codes
This variable is not available for any of the currently selected samples.
Explore how IPUMS created this variable
Most IPUMS data transformations are performed using variable harmonization tables that specify how each value in the source data is recoded. Some variables also require programming logic in addition to the harmonization table. The harmonization documents for this variable are:
- Harmonization table
- No supplemental programming
- Instructions for interpreting harmonization documents
Description
CITYMX indicates the city of residence for households located in identifiable cities in the Mexico labor force surveys from 2005 to present.
The full set of geography variables for Mexico can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here.
Comparability — General
CITYMX is only available for Mexico Labor Force Surveys. There are no boundary files associated with the delineation of the city. Users should be aware that the boundary of the city might change from one survey to another.
This variable is comparable across samples, but not all cities are identified in each survey. Cities identified in each sample are determined by the Encuesta Nacional de Ocupación y Empleo (ENOE). ENOE incorporates cities with strategic economic importance linked to airports, ports, transportation of cargo and passengers, tourist centers and foreign trade (customs), as indicators of the regional and urban development of the country.
Universe
Availability
- Mexico: 2005Q1, 2005Q2, 2005Q3, 2005Q4, 2006Q1, 2006Q2, 2006Q3, 2006Q4, 2007Q1, 2007Q2, 2007Q3, 2007Q4, 2008Q1, 2008Q2, 2008Q3, 2008Q4, 2009Q1, 2009Q2, 2009Q3, 2009Q4, 2010Q1, 2010Q2, 2010Q3, 2010Q4, 2011Q1, 2011Q2, 2011Q3, 2011Q4, 2012Q1, 2012Q2, 2012Q3, 2012Q4, 2013Q1, 2013Q2, 2013Q3, 2013Q4, 2014Q1, 2014Q2, 2014Q3, 2014Q4, 2015Q1, 2015Q2, 2015Q3, 2015Q4, 2016Q1, 2016Q2, 2016Q3, 2016Q4, 2017Q1, 2017Q2, 2017Q3, 2017Q4, 2018Q1, 2018Q2, 2018Q3, 2018Q4, 2019Q1, 2019Q2, 2019Q3, 2019Q4, 2020Q1, 2020Q3
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