Estimating long-run effects and the exponent of cross-sectional dependence:: an update to xtdcce2

• Autores: Jan Ditzen
• Localización: The Stata journal, ISSN 1536-867X, Vol. 21, Nº. 3, 2021, págs. 687-707
• Idioma: inglés
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• Resumen

  • In this article, I describe several updates to xtdcce2 (Ditzen, 2018,Stata Journal 18: 585–617). First, I explain how to estimate long-run effects in models with cross-sectional dependence. I review three methods to estimate the long-run effects and discuss their implementation into Stata using xtdcce2. Two of the estimation methods build on Chudik et al. (2016, Advances in Econometrics:Vol. 36—Essays in Honor of Aman Ullah, 85–135): the cross-sectionally augmented distributed lag and the cross-sectionally augmented autoregressive distributed lag estimator. As a third alternative, I review an error-correction model in the presence of cross-sectional dependence. Second, I explain how to estimate the exponent ofcross-sectional dependence using xtcse2 following Bailey, Kapetanios, and Pesaran(2016, Journal of Applied Econometrics 31: 929–960; 2019, Sankhy ̄a 81: 46–102).