This paper reviews research issues in modeling panels of time series. Examples of this type of data are annually observed macroeconomic indicators for all countries in the world, daily returns on the individual stocks listed in the S&P500, and the sales records of all items in a retail store. A panel of time series usually concerns the case where the cross-section dimension and the time dimension are large. Usually, there is no a priori reason to select a few series or to aggregate the series over the cross-section dimension. In that case, however, the use of for example a vector autoregression or other types of multivariate systems becomes cumbersome. Panel models and associated estimation techniques are more useful. This paper discusses representation, estimation and inference in case the data have trends, seasonality, outliers, or nonlinearity. Various examples illustrate the various models.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number
274.
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)
Did you know? All full texts are decentralized with the publishers, none reside on this server, thus making it possible to offer this service for free to all parties.