The history of measuring Socioeconomic Status

I found this new review study via Christian Bokhove and dr. Rachel Renbarger, and it’s quite fascinating. Together with her colleagues, dr. Renbarger examined the shift that has happened over time:

The construct of SES is measured via an extremely wide set of variables. The number of SES variables used has drastically compounded within the last century, leaving SES an ill-defined and rarely assessed measure. Typically, these variables are used without consideration of a theoretical framework, leaving them uninformed and less effective than they could be. This study used a systematic literature review protocol to identify SES variables and components used thus far. We also sought to track how the measure of SES has shifted over time. Finally, we sought to tie these variables to theoretical frameworks to assist researchers who wish to use SES in future.
Results of this study show that there are 61 SES components commonly used in research, with an additional 331 components used sporadically throughout time. The most popular components used to measure SES are those of the Big 3—parental education, parental occupation, and income—although measures of personal education and occupation and household possessions are also commonly used. Comparing these results to a previous review of SES measures (although in health), Bollen et al. (2001) found that there was no consensus on measuring SES; here, it appears that education researchers have at least mild consensus in using SES components that have a connection to capital through the use of the Big 3. Yet, given the overly abundant number of variables, there are implications for the research community to work on creating a standardized, simplified measure of SES. Doing so may allow for a more uniform and intuitive means of analyzing SES in the future.

One of my favourite elements in this review is this historical overview:

Decade Socioeconomic Status Components Common Groups
Prior to 1970 Home language, paternal education, telephone, number of books in the home, furnace, automobile that is not a truck, and mother’s clubs/organizations Cultural questions, education, utilities, books, transportation
1970s Maternal education, personal occupation, and personal education Education, occupation
1980s Highest parental education and income Education, wealth
1990s Paternal and maternal education, paternal and maternal occupation, and income Education, occupation, wealth
2000s Paternal and maternal education, highest parental education, maternal and paternal occupation, full-time/part-time/no work status, number of cars, having one’s own bedroom, number of family holidays, number of computers, income, income (needs), poverty level, own/rent dwelling, single/dual parent household, dishwasher, educational software, internet, presence of a dictionary, place to study, study desk, textbooks, number of calculators in the home, classic literature, poetry books, works of art, free/reduced lunch, family size, receiving welfare, receiving food stamps, subjective measure (rungs of the ladder), personal education, travel abroad for holidays (number in last year), personal occupation, bathing facility, type of transportation, radio, servant does washing, own tumble dryer, air conditioner, answering machine, bicycle, boat/cabin, cable/satellite TV, camera, CD player, cassette player, central heating, computer/video games, cordless phone, encyclopedia, garage, house, microwave oven, newspaper/magazines, own books, own CD/video player, own television, piano/organ/violin, record player, own telephone, recreational vehicle, refrigerator, stereo/audio system, summer/weekend house, family telephone, family television, 2 or more bathrooms, 2 or more cars, vacuum cleaner, video camera, VCR, Walkman, and home postcode Education, occupation, transportation, home quality, leisure, games and technology, wealth, needs, family makeup, house upkeep and cooking, other study items, utilities, books, cultural capital items, needs, family makeup, subjective questions, individual characteristics, home size
2010s Maternal/paternal education, highest education, paternal/maternal occupation, number of cars, having your own bedroom, number of family holidays, number of computers, savings, income, rent/own dwelling, type of dwelling, crowding in dwelling, single/dual parent household, private/public school, dishwasher, educational software, internet, number of cell phones, number of TV sets, number of bathrooms, presence of a dictionary, quiet place to study, study desk, textbooks, number of calculators, classic literature, books of poetry, works of art, visited a museum/art gallery, attended an opera/ballet/symphony, watched live theater, social activities, medical and dental needs, financial status (subjective “well off”) measure, how often participate in lessons, had to skip meals in past month, free/reduced price lunch, family size, subjective (rungs on the ladder), number of times traveled abroad last year, servant does washing, type of transportation, personal computer, own iPod or personal music player, own CD/video player, vehicle ownership, and insurance Education, occupation, transportation, home size, leisure, games and technology, wealth, home quality, home size, family makeup, school, utilities, other study items, books, cultural capital items, access to care, subjective questions, nutrition, needs, house upkeep and cooking
2020 Number of cars, number of computers, income, electricity in the home, personal education, personal occupation, refrigerator, television, and receiving public assistance Transportation, games and technology, wealth, utilities, education, occupation, needs

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.