By: Janine Cerutti


There is a large body of research in public policy, sociology, epidemiology, psychology, and other fields studying the effects of socioeconomic status (SES), or “social class.” From this literature, it’s well understood that SES is a strong predictor of future health and well-being as well as the quality of educational opportunities.

Yet, despite the interest in SES, there is still no single agreed upon definition of what SES is and even less agreement on how to measure it. 

What is SES?

The American Psychological Association defines SES as the social standing or class of an individual or group. Some scholars take it a step further to define SES as differential access (realized and potential) to desired resources. 

No matter the definition, the overall goal of measuring SES is to locate an individual’s (or family’s) position in the social hierarchy—which is easier said than done. In reality, a person’s social standing is complex, encompassing various elements such as income, wealth, parental education, occupational prestige, neighborhood characteristics, welfare services, and even subjective perception of one’s own social class. These indicators may also be at odds with each other. Graduate students, for example, have high education levels and occupational prestige, but oftentimes low income.  

There are three key measures most commonly used to capture SES in most studies: incomeeducation, and occupation. At a glance, measuring each of these seems pretty straightforward, but issues often arise quickly.



Income is fairly easy to capture. Survey respondents can report the exact number of annual earnings or pick from a range of incomes provided by researchers. However, people are often uncomfortable disclosing their income and may feel tempted to “inflate” their earnings. Income can also fluctuate from year-to-year or even month-to-month. We also know that income does not equal wealth. While income refers to the amount of money earned by an individual or household, wealth refers to the amount of accumulated resources, which are often accrued over a lifetime or inherited. Indeed, wealth can vary dramatically across social groups, even among those with similar incomes.

2. Education


Education, or educational attainment, can be simply measured by asking people about the number of completed years of schooling or the highest level of degree received. It also tends to have a higher response rate in comparison to income. However, education level does not capture the quality of education, which prior studies have shown is an important determinant of cognitive skills (and subsequent job achievement/earnings). This means that education alone may not be the best proxy for income or wealth and subsequently SES. 

3. Occupation


Survey respondents usually have no problem in sharing information about their occupation. However, using occupation alone to quantify SES excludes a good chunk of the population. What about retired folks, students, people who are unemployed, and children? Additionally, although occupation can be a good indicator of education and income, simply checking off a job category does not capture more complicated aspects of an individual’s social standing, like job prestige or work-related health or other benefits. 

So given all this complexity, what is the best way to measure SES?  

Tips for measuring Ses

  • Carefully choose the constructs that are most important to you. Ideally, every research study would include as many measurements of SES as possible. However, this is often impractical, requiring researchers to select only a few measures. Depending on your goals, there may be different constructs within SES to capture. For example, if you’re looking to guide public policy, consider measuring income, wealth, and other indicators of financial capital that can be easily tracked across time to identify growing or shrinking inequality gaps. If you’re more interested in learning about the psychological effects of SES, consider assessing SES measures such as neighborhood characteristics and subjective socioeconomic status, across the lifecourse. Measuring SES continuously across the lifecourse can help tell the story of how SES influences health outcomes, not just that the two are linked. If you’re trying to build off the work of prior studies, consider choosing SES measures that are comparable to what has been done before. As mentioned in a previous Said&Dunn post, it is challenging to replicate prior study findings and especially difficult to find studies that use the exact same measures, so selecting similar measures can help facilitate replication efforts in the future.  

  • Avoid comparing SES measures across studies. Researchers typically only have access to one or two measures of SES in more cases than not. It may be tempting to try and compare different measures across studies—such as income in study A versus education in Study B. But keep in mind that income, education, and occupation are not interchangeable and efforts to equate them can create validity issues. In fact, differing SES measures can show pretty different effects on health outcomes and mortality. Thus, even though these measures are often correlated, you may be trying to compare apples to oranges.

  • Explicitly state how you defined SES and why. This kind of transparency will not only help other researchers be more informed when comparing across studies or building studies of their own, but it will also help you to draw more powerful—and specific—conclusions from your results. Justify your SES measurement: How did you define SES? Why? What was available in your data? What wasn’t? For example, a study may choose to use income data from the US Census Bureau to capture SES levels in a large population because it was the only SES-related data feasibly accessible across the entire sample. If this was the case, it’s helpful for readers to know that this was the reasoning behind their definition of SES, and not necessarily because income is the best proxy for SES. It’s also important to consider how unmeasured socioeconomic factors may be impacting your results.  

It’s clear that studying SES is important—it is one of the most significant predictors of physical and mental health, educational achievement, career aspirations, and more. Thus, it is important to create the best measurement of SES possible in order to accurately identify individuals at higher risk and at a greater societal disadvantage. If we can measure SES with consistency and validity across studies, then we can better identify the societal gaps in SES, understand the implications of SES, and influence public policy for those facing inequality. 

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