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During this project we have generated many resources which we feel are of wider benefit to occupational researchers. These can be downloaded from this page. At present these resources are in Stata format. We are currently working on producing the resources in other formats.

Most of these resources can be found Geode - Grid Enabled Occupational Data Environment. GEODE serves to collate and distribute occupational resources for the benefit of social science research. For a richer source of occupational research resources, visit http://www.geode.stir.ac.uk/ Please contact Dave Griffiths or Paul Lambert if you have any questions or comments regarding these files.

CAMSIS files


This .dta file adds HIS-CAM scores to HISCO values.

Microclass conversion files

These resources enable occupational data to be converted into the Microclass scheme, as documented in: Jonsson, Jan O., David B. Grusky, Matthew Di Carlo, Reinhard Pollak, and Mary C. Brinton. 2009. "Microclass Mobility: Social Reproduction in Four Countries", American Journal of Sociology, Volume 114, Number 4.

ISCO-08 to Microclass

This .dta file translates from ISCO-08 to microclasses

ISCO-88 to Microclass

This .dta file translates from ISCO-88 to microclasses

ISCO-68 to Microclass

This .dta file translates from ISCO-68 to microclasses

3 digit HISCO to Microclass

This .dta file translates from the 3 digit HISCO scheme to microclasses

2 digit HISCO to Microclass

This .dta file translates from the 2 digit HISCO scheme to microclasses

Microclass labels

This file adds labels to the microclass variable generated through other resources from this project.

Stata .do files for analysing occupational structure

Converting occupational connections to Pajek

This file predicts an expected number of marriage pairings between members of occupational unit groups, based on the numbers of male and females in each job. The actual number of pairings, and the value of over/under-representation is also calculated. If this data is used to drop marriage pairings under certain thresholds of frequency or value of over/under-representation, a text outsheet of the male and female occupation can be saved as a matrix for use in Pajek and other social network analysis software.

Convering occupational connections to Pajek using educational qualifications

This file splits occupational unit groups into graduate members and non-graduate members by adding 10,000 to the code for graduates.

Identifying percentage of graduates within occupations

This file obtains the percentage of graduates within an occupational unit group amongst different age groups from Ipums_international data. This enables researchers to construct their own versions of the SOC(HE) scheme, created by Peter Eilas and Kate Purcell in SOC (HE): A classification of occupations for studying the graduate labour market, Researching Graduate Careers Seven Years On research paper no.6, Peter Elias and Kate Purcell, March 2004. (Available at http://www2.warwick.ac.uk/fac/soc/ier/research/completed/7yrs2/rp6.pdf)

Grouping individuals by age

This file groups individuals from Ipums-International datasets into the following age-groups. http://www.camsis.stir.ac.uk/sonocs/do/agegr.do

IPUMS International occupational labels

These files enable occupation labels to be automatically generated for surveys found within IPUMS International.

The command files for IPUMS can become confused if you are downloading multiple samples. For instance, if you download the 1991 and 2001 UK data in the same download, the value "111", in the variable "occ", refers to "authors, writer, journalists", for the 1991 data and "corporate managers and senior officals", in the 2001 data. These files enable the correct labels to be easily attached.

These files can be run from their online address, or downloaded to a computer. To run them automatically online, the command syntax is :
do "http://www.camsis.stir.ac.uk/sonocs/occ_labels/county_year_occ_labels.do"

The country is always the two digit internet domain version. The year is always four digit. We hope this standard will enable researchers to easily obtain labels if working on multiple datasets.

Argentina 1970
Argentina 1980
Argentina 1991
Argentina 2001
Austria 1971
Austria 1981
Austria 1991
Austria 2001
Bolivia 1976
Bolivia 1992
Bolivia 2001
Brazil 1960
Brazil 1970
Brazil 1980
Brazil 1990
Brazil 2000
Belarus 1999
Cambodia 1998
China 1982
China 1990
Chile 1960
Chile 1970
Chile 1982
Chile 1992
Chile 2002
Chile 1960
Costa Rica 1984
Costa Rica 2000
Cuba 2002
Ecuador 1974
Ecuador 1982
Ecuador 1999
Ecuador 1999
Ghana 2000
Guinea 1983
Guinea 1996
Greece 1971
Greece 1981
Greece 1991
Greece 2001
Hungary 1970
Hungary 1980
Hungary 1990
Hungary 2001
India 1983
India 1987
India 1993
India 1999
India 2004
Iraq 1997
Kenya 1989
Kyrgyz Republic 1999
Malaysia 1970
Malaysia 1980
Malaysia 1991
Malaysia 2000
Pakistan 1973
Mali 1987
Mali 1998
Mongolia 2000
Mexico 1960
Mexico 1970
Mexico 1990
Mexico 2000
Pakistan 1973
Panama 1960
Panama 1970
Panama 1980
Panama 1990
Panama 2000
Peru 1993
Peru 2007
Philippines 1990
Philippines 2000
Portugal 1981
Portugal 1991
Portugal 2001
Puerto Rica 1970
Puerto Rica 1980
Puerto Rica 1990
Puerto Rica 2000
Puerto Rica 2005
Romania 1977
Romania 1992
Romania 2002
Rwanda 2002
St Lucia 1991
Senegal 1988
Senegal 2002
Spain 1981
Spain 1991
Spain 2001
Switzerland 1970
Switzerland 1980
Switzerland1 990
Switzerland 2000
Thailand 1970
Thailand 1980
Thailand 1990
Thailand 2000
Uganda 1991
Uganda 2000
United Kingdom 1991
United Kingdom 2001
USA 1960
USA 1970
USA 1980
USA 1990
USA 2000
USA 2005
Venezuela 1981
Venezuela 1991
Venezuela 2001
Vietnam 1989
Vietnam 1999
South Africa 1996
South Africa 2001
South Africa 2007


Missing datasets

The following countries and time-points have occ data available on IPUMS but we are yet to generate the occ_labels .do file. We intend to make them available online soon to enable this resource to be comprehensive. Please contact Dave Griffiths if you have any questions or comments regarding this files.