Panel Time Series. Review of the Methodological Evolution

Tamara Burdisso and Máximo Sangiácomo

No 201568, BCRA Working Paper Series from Central Bank of Argentina, Economic Research Department

Abstract: The document focuses on the econometric treatment of macro panels, known in literature as panel time series. This new approach rejects the assumption of slopes’ homogeneity and handles nonstationarity. It also recognizes that the presence of crosssection dependence (CSD), i.e. some correlation structure in the error term between units due to the presence of unobservable common factors, squanders efficiency gains by operating with a panel. This led to a new set of estimators known in literature as Common Correlated Effect (CCE), which essentially consists of increasing the model to be estimated by adding the averages of the individuals in each time t, of both the dependent variable and the specific regressors of each individual. Finally, two Stata codes developed for the evaluation and treatment of the cross-section dependence are presented.

Keywords: panel time series; nostationarity; panel unit root; mean group estimator; cross-section dependence; common correlated effect (search for similar items in EconPapers)
JEL-codes: C13 C23 C87 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2015-11
New Economics Papers: this item is included in nep-ecm and nep-ets
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.bcra.gov.ar/Pdfs/Investigaciones/WP_68_2015e.pdf Versión en Español (application/pdf)

Related works:
Journal Article: Panel time series: Review of the methodological evolution (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bcr:wpaper:201568

Access Statistics for this paper

More papers in BCRA Working Paper Series from Central Bank of Argentina, Economic Research Department Contact information at EDIRC.
Bibliographic data for series maintained by Federico Grillo ().