What Is Panel Data? (With Uses, Advantages, and Examples)

By Indeed Editorial Team

Published May 31, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Researchers commonly use panel data to conduct studies on various topics involving quantitative data. It can predict trends, provide correlations and allow researchers to pursue many other forms of data analysis. Learning more about this type of data can help you use it to evaluate long-term changes or trends.

In this article, we answer the question, “What is panel data?”, explain its uses and advantage, compare it to pooled data, and provide an example table of how you can collect this data for a study.

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What is panel data?

Knowing the answer to, “What is panel data?” can help you collect, understand, and use it effectively. Professionals collect this data by observing particular variables over a period of time at a regular frequency. This type of data can help experts establish trends, make correlations and guide further analysis of the variables included in the data.

For example, this data may comprise annual income information and the age of individuals over a 10-year period. This data may allow you to establish a connection between age and average income or contribute to the analysis of another related subject, such as age and employment rates. It often involves the observation of many variables simultaneously to maximize the size of analysis you can conduct with the data. Countries, organizations, demographic groups, and individuals are some common examples of these data subjects you can study.

Read more: Top Data Scientist Interview Questions With Sample Answers

Uses of panel data

You can find the use of this data in a lot of industries for several reasons. For example, a hospital may use this type of data to determine the number of patients that came to receive the treatment for a particular ailment over a set period. Researchers essentially use it for statistical, financial, or economical research. Here are the common uses for which you may collect this data:


You may use this data to conduct a statistical analysis to understand various data trends that relate to health care, human development, child care, housing, or education. This can help you determine conclusions for various studies. For example, a data study may help you understand what electronics products people prefer, or what are the common causes for insurance claims in a particular demographic.

A more complex study involving statistics may use it to help analyze the cities with the best educational systems using different variables, such as graduation rates, post-graduation employment rates, grades, and standardized testing scores.

Read more: How to Calculate the Median of a Data Set in Statistics


This data can be useful in studying macroeconomic trends. You can use the data to identify and analyze national or global economic factors. These may include socioeconomic data, the value of the currencies of various countries, and international trade data. For example, a study on the spending capacity of different currencies over the past 10 years may use it to derive information on specific currency values at regular intervals during that period.


You can use this data type to conduct studies on various microeconomic factors. These may include small-scale economic factors like housing values, unemployment rates and goods and services markets. It also includes the behaviour of an individual or a firm during resource allocation and the actions they may take when changes occur in market prices or production methods. For example, you may use this data to understand the actions individuals take when the price of a particular product increases. This may help find if they continue to use that product or choose a cheaper option.


You can use this data in finance to conduct studies on monetary data in various fields. For instance, you can gather information on stock prices, market volatility, and individual wealth using financial data. Professionals conducting a study on the best-performing stocks over the past 15 years may use this type of data to gather specific data on price points at regular intervals during that period. This can help them predict the fluctuations in stock prices and trade with minimum risks.

Advantages of using panel data

Here are some advantages of using this data type for conducting research:

Forming correlations

This data can help form correlations between two elements upon which you want to conduct a study. It can help determine a connection over a long time period with maximum accuracy. For example, you can conduct a study that includes the monthly income and expenditure of 1000 individuals over five years. This study may help you understand to spending patterns of that particular group of individuals, and determine whether their income affects their expenditures.

You can also add variables to this study. For example, adding age as a variable may help you understand the spending patterns of individuals under different age groups. You can also determine the correlation between the income of individuals and their age.

Predicting future trends

You can use this data to predict future trends for two or more variables in a study. You can examine the past performance of those variables to predict how they may perform in the future. This can be helpful while conducting research on macroeconomic or microeconomic factors of a demographic.

For example, you can look at the data collected over 10 years for the average rent of a one-bedroom house in a province, and analyze it to predict whether the rent is likely to increase or decrease in the coming years. Researchers often use it to predict factors affecting a country like the GDP or national interest rates.

Gathering data for future analysis

This data can also be useful in conducting future analyses. You can collect the data for a study and use it at a later date to understand the differences in the outcome of the study at two different periods. For example, a university may collect data for students' enrolment rate and graduation rate for a period of two years. The university can then use the same data after a few years to optimize its study and compare the outcomes of both.

Identifying causes

Conducting research using this data type can be a great way to identify the causes of certain issues. It can also be helpful in determining the potential source of an issue and how long that source had been causing it. For example, researchers want to find the reason behind increased burglaries in a specific demographic. To determine the cause, researchers may look at the past data on the number of security cameras installed in that demographic, the time of burglaries reported, and the items that were stolen.

Researchers may collect this data for the last two years to find common data points like the time of burglaries or the items that were stolen. This may help them determine if there's a pattern among the burglaries that happened over the last two years. It may also help researchers suggest specific safety measures to reduce or prevent that crime in that particular area.

Difference between panel and pooled data

Panel and pooled data are both data sets researchers collect over a certain period to study specific variables. Pooled data involves collecting data over a certain time period for a set of units. These units are typically variables, which may include housing rent, unemployment rates, and interest rates. Panel data also includes data collection for specific units over a set time period.

The main difference between the two types of data is that, in pooled data, researchers generally collect the data for the units from different individuals or groups. For panel data, researchers collect the data for the units from the same set of individuals throughout the course of the study. While both have their own advantages, studies using panel data may allow researchers to perform a concentrated analysis in comparison to pooled data.

Panel data example

Here's an example of a table of this data that compares the monthly rent and the annual income of five individuals over a period of two years:

Person 12019$1,000$65,000
Person 12020$1,100$65,000
Person 22019$1,000$80,000
Person 22020$1,200$82,000
Person 32019$1,300$70,000
Person 32020$1,300$70,000
Person 42019$1,200$64,000
Person 42020$1,200$65,000
Person 52019$1,300$61,000
Person 52020$1,400$61,000

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