# Longitudinal Data: Definition and Uses in Finance and Economics

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## What Is Longitudinal Data?

Longitudinal data, sometimes called panel data, is data that is collected through a series of repeated observations of the same subjects over some extended time frame—and is useful for measuring change.

Longitudinal data is collected through longitudinal studies and effectively follows the same sample over time, which differs fundamentally from [cross-sectional data](https://www.investopedia.com/terms/c/cross_sectional_analysis.asp) because it follows the same subjects over some time, while cross-sectional data samples different subjects (whether individuals, firms, countries, or regions) at each point in time. Meanwhile, a cross-sectional data set will always draw a new [random sample](https://www.investopedia.com/terms/s/simple-random-sample.asp).

Longitudinal data is used widely in the social sciences, including among economists, political scientists, and sociologists.

### Key Takeaways

*   Longitudinal data is data that is collected sequentially from the same respondents over time.
*   This type of data can be very important in tracking trends and changes over time by asking the same respondents questions in several waves carried out of time.
*   Longitudinal data is used in finance to track company profitability, risk, and to understand the effect of economic shocks.

## Understanding Longitudinal Data

Often, analysts are interested in how things change over time. In a typical cross-sectional sample, even if you measure some variable today and then again a year from now, you will probably be sampling different people each time. To get a better handle on how things change for the same people over time, you need to be able to track them and follow up with them a year from now, and in future waves. This is longitudinal data.

Longitudinal data is often used in economic and financial studies because it has several advantages over repeated cross-sectional data. For example, because longitudinal data measures how long events last, it can be used to see if the same group of individuals remain unemployed during a [recession](https://www.investopedia.com/terms/r/recession.asp), or whether different individuals are moving in and out of [unemployment](https://www.investopedia.com/terms/u/unemployment.asp). This can help determine the factors that most affect unemployment.  

### What Is a Longitudinal Study?

A longitudinal study involves repeated observations of the same variables (such as people) over long time periods (i.e., using longitudinal data). It is often an observational study, but can also be structured as a longitudinal randomized experiment. It is also known as a longitudinal survey or panel study.

## Example of a Longitudinal Study

In a longitudinal study, researchers repeatedly examine the same individuals to detect any changes that might occur over a period of time. The benefit of a longitudinal study is that researchers are able to detect developments or changes in the characteristics of the target population at both the group and the individual level.

An example of a longitudinal study would be a study conducted to understand the similarities or differences between identical twins who are brought up together vs. identical twins who are not. The study observes several variables, but the constant is that all the participants have identical twins.  

## Applications of Longitudinal Data

Longitudinal analysis can also be used to calculate a portfolio’s [value at risk (VaR)](https://www.investopedia.com/terms/v/var.asp), using the historic simulation method. This simulates how the value of the current [portfolio](https://www.investopedia.com/terms/p/portfolio.asp) would have fluctuated over previous time periods, using the observed historical fluctuations of the assets in the portfolio during those times. It provides an estimate of the maximum likely loss over the next time period.

Longitudinal data is also used in [event studies](https://www.investopedia.com/terms/e/eventstudy.asp) to analyze what factors drive abnormal stock returns over time, or how stock prices react to merger and earnings announcements. It can also be used to measure poverty and income inequality by tracking individual households. And because standardized test scores in schools are longitudinal, they can be used to assess teacher effectiveness and other factors affecting student performance.

Social scientists also use longitudinal data to try to understand causation of events that may have occurred in the past and how they lead to outcomes observed in later waves of the data—for instance, the effect of the passage of a new law on crime statistics, or a natural disaster on births and deaths years later.

## What Is the Difference Between Longitudinal Data and Panel Data?

Longitudinal data are sometimes called panel data, but there is a subtle difference between the two. Longitudinal data refer to repetitive measurements over time that could be the same units or otherwise. Panel data are a type of longitudinal data where the observed units are the same.

## Is a Longitudinal Study Qualitative or Quantitative?

Longitudinal studies are primarily qualitative research because the researcher observes and records changes in variables over an extended period. However, they can also be used to gather quantitative data depending on your research context.

## Is There a Drawback to Longitudinal Studies?

A drawback to any longitudinal study is the great amount of time necessary to collect all the data that is needed before you can start making patterns.

## The Bottom Line

Longitudinal data is data that is collected sequentially through repeated observations of the same subjects over time. It is useful for measuring change and is used in finance to track company profitability, risk, and to understand the effect of economic shocks.

> **Article Sources**
>
> 1.  National Longitudinal Surveys, U.S. Bureau of Labor Statistics. “[What Are Longitudinal Data?](https://www.nlsinfo.org/content/getting-started/what-are-longitudinal-data)”