Data often contain information on a relatively small number of cross-sectional units observed over time. For example, you may have time series data on GDP for a number of European nations. Or perhaps you have state level data on unemployment observed over time. We term such data pooled time series, cross-section data.

EViews provides a number of specialized tools to help you work with pooled data. EViews will help you manage your data, perform operations in either the time series or the cross-section dimension, and apply estimation methods that account for the pooled structure of your data.

The EViews object that manages time series/cross-section data is called a pool. The remainder of this chapter will describe how to set up your data to work with pools, and how to define and work with pool objects.

Note that the data structures described in this chapter should be distinguished from data where there are large numbers of cross-sectional units. This type of data is typically termed panel data. Working with panel structured data in EViews is described in “Working with Panel Data” and “Panel Estimation”.