Panel Regression is a statistical method used to analyze data that involves multiple subjects over time. It combines both cross-sectional data (data collected from multiple subjects at a single point in time) and time series data (data collected from the same subjects over multiple time periods). This approach allows researchers to observe how variables change over time while controlling for individual differences. By using Panel Regression, analysts can better understand the relationships between variables and identify trends that may not be visible in traditional regression models. This technique is particularly useful in fields like economics, social sciences, and health research, where data is often collected from various subjects across different time frames.