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Too much or too little? New tools for the CCE estimator

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  • Jan Ditzen

    (Free University of Bozen-Bolzano)

Abstract

This talk will cover new developments in the literature of common correlated effects (CCE) and their implementation in Stata. First, I will discuss regularized CCE. CCE is known to be sensitive to the selection of the number of cross-section averages. CCE overcomes the problem by regularizing the cross-section averages. Secondly, I will discuss the test for the rank condition based on DeVos, Everaert, and SaraFdis (2024, Econometrics Reviews). If the rank condition fails, CCE will be inconsistent and therefore testing the condition is key for any empirical application. Finally, I will show the selection of cross-section averages using the information criteria from Karabiyik, Urbain and Westerlund (2019, Journal of Applied Econometrics) and Margaritella and Westerlund (2023, The Econometrics Journal).

Suggested Citation

  • Jan Ditzen, 2024. "Too much or too little? New tools for the CCE estimator," Italian Stata Users' Group Meetings 2024 04, Stata Users Group.
    • Handle: RePEc:boc:isug24:04
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