Panel Data Analysis Tutorial - Overview

Background

Panel data denotes data sets where the same entities (e.g., people, countries, firms, keywords, products) have been observed at multiple times or in different contexts. Each entity has a unique panel ID, and the multiple observations of the entities could occur across time (say, product sales data obtained in daily intervals), across geographies (say, product sales in different cities), or across other contexts. The usual structure for panel data are observations of the same entities at different times; such data are referred to as cross-sectional time-series data, where the cross-sections refer to the different entities, and the multiple observations of those entities occur at different times. Panel data is now readily available in many areas of marketing because of continuous data collection through web logs, sensors, transactions, mobile Apps, etc. Because of the multiple observations we have about the same entities, more information is available to obtain more precise estimates of the effects of marketing variables.

The use of panel data analytics (also known as panel regression) can help us answer questions such as the following:

• What is the incremental effect of each keyword on conversions after accounting for the effects of other variables such as number of impressions, clicks, and the average position of the keyword in paid search advertising?
• Effect of advertising on sales after accounting for the effects of unobserved characteristics of each ad copy.