TIME SERIES|L-3|ECONOMETRICS

A time series is a sequence of data points that occur in successive order over some period of time. This can be contrasted with cross-sectional data, which captures a point in time.

In investing, a time series tracks the movement of the chosen data points, such as a security’s price, over a specified period of time with data points recorded at regular intervals. There is no minimum or maximum amount of time that must be included, allowing the data to be gathered in a way that provides the information being sought by the investor or analyst examining the activity.

Cross-sectional data refer to observations of many different individuals (subjects, objects) at a given time, each observation belonging to a different individual. A simple example of cross-sectional data is the gross annual income for each of 1000 randomly chosen households in New York City for the year 2000. Cross-sectional data are distinguished from longitudinal data, where there are multiple observations for each unit, over time.

Pooled data occur when we have a “time series of cross sections,” but the

observations in each cross section do not necessarily refer to the same unit.

HGL is ambiguous about this and sometimes use pooled to refer to panel

data. Panel data refers to samples of the same cross-sectional units observed at multiple

points in time. A panel-data observation has two dimensions: xit, where i runs from 1 to N and denotes the cross-sectional unit and t runs from 1 to T and denotes the timeof the observation.

 A balanced panel has every observation from 1 to N observable in every

period 1 to T.

An unbalanced panel has missing data.

Panel data commands in Stata start with xt, as in xtreg. Be careful about

models and default assumptions in these commands.