What is longitudinal research and why is it so useful?

Kelsey Martinez, PhD, Researcher
May 20, 2020

Photo by Simon

Today, we look at a type of research, known as longitudinal research, that the Utah Data Research Center (UDRC) uses frequently. I’ll discuss what I mean by the term ‘longitudinal research’ and why this type of research is so useful in government and public policy.

What is longitudinal research or longitudinal analysis?

Longitudinal research follows a group of people over time. You might hear this group of people examined in the research referred to as a ‘cohort’. In this type of research, multiple observations are made on a group of people at regular time intervals. After we collect the observations, or data points, we can assess them according to our research needs.

The other type of analysis we use a lot at the UDRC is cross-sectional research. Cross-sectional research looks at a group of people at a single point in time. Sometimes this is the only type of research that is feasible due to data limitations.

Why is longitudinal research so useful in government?

Longitudinal studies can get us close to a causal explanation of an observed social change - but not quite all the way there. In many cases though, longitudinal analysis gets us much, much closer to a cause than other types of analyses. For example, if we understand a social pattern pre- and post- political change or major economic event, it is a lot easier to argue that the political change or economic event may have been the cause of said social change.

Suppose a change is made to policy governing eligibility for services such as SNAP or TANF. Assessment of the group of people using these services in the years leading up to the policy change and the years following the policy change could help to determine if the desired outcome was achieved. Are more or less people receiving the benefits? Are certain demographic groups using the services more or able to access the services more readily? These are questions we can answer with a longitudinal study.

How does the UDRC use longitudinal analysis in its research?

Intergenerational Poverty: This research for 2020 is currently in progress. It follows a cohort of individuals affected by intergenerational poverty from 2013 to 2019. The study attempts to understand the career development and workforce attachment patterns of individuals impacted by poverty over this time period.

A longitudinal analysis is necessary here because a single snapshot of a person’s wage earnings or employer at given time does not illustrate how they interact with the workforce over a period of time. From this research, we hope to gain a better understanding of how intergenerational poverty impacts a person’s ability to build a career or maintain gainful employment. Look for this research to be released later in 2020.

Workforce Retention of Graduates: This study follows a cohort of students after they graduate from public post-secondary institutions in Utah. The cohort’s wage earnings were sampled across a time period to determine if they remained employed in Utah after graduating.

A longitudinal approach was necessary for this study because a single snapshot of students one or two years post-graduation was not enough to imply that they are remaining in the state after graduation.

ROI of Career and Technical Education: Here, the return on Utah state investment in career and technical education (CTE) (Utah System of Technical Colleges - UTech) is assessed using a longitudinal analysis. From 2011 to 2018, wages of recent UTech graduates were tabulated to assess state income tax return from career and technical degrees. From the tax revenue collected from UTech graduates wages, a payback time period was calculated for the state’s CTE investment.

A longitudinal analysis was especially useful here since examining a single time point following a graduation event was not enough to determine the payback period. Unsurprisingly, the increased wages earned in a single year by UTech graduates are not enough to cover the state’s investment. Therefore, multiple years of income from graduates, or a longitudinal approach, was needed for the study.