Chapter 16
Diving into Pooled Cross-Section Analysis
In This Chapter
Understanding the nature of pooled cross-sectional data
Revealing the flexibility of pooled cross-section econometric analysis
Estimating treatment or policy effects using the difference-in-difference estimator
A pooled cross section combines independent cross-sectional data that has been collected over time. For example, the Current Population Survey collects independent cross-sectional data by surveying 60,000 randomly selected households in the United States each month. Combining or merging CPS data collected over many years into one dataset gives you a pooled cross section.
The advantage of pooled cross-sectional data is that more observations tend to improve the accuracy of econometric estimates, and the added time element allows you to explore dynamic adjustment (how your outcome of interest, or Y variable, responds to factors as they change over time). In this chapter, I show you how you can modify traditional econometric estimation techniques to handle pooled cross-sectional data and how this type of analysis can be particularly useful in examining changing relationships between variables and evaluating ...
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