The Performance of Panel Cointegration Methods: Results from a Large Scale Simulation Study
By Martin Wagner, Jaroslava Hlouskova. 2009
235 citations recorded by the source corpus.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/bc3d4881fb554460c270587e2b3f580302421b57
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Mehdi Ben Jebli
- Slim Ben Youssef
- Muhammad Shahbaz
- M. Pesaran
- Joerg Breitung
- Christian Dreger
- A. Belke
- Frauke Dobnik
Citations in the corpus
- Energy consumption and economic growth: New insights into the cointegration relationship (2011, methodology): “According to Wagner and Hlouskova (2010), the DOLS estimator outperforms all other studied estimators, both single equation estimators and system estimators, even for large samples.”
- Testing for Bubbles in Housing Markets: A Panel Data Approach (2009, unknown): “To calculate the values of the Pedroni test statistic, we used Gauss code from Wagner and Hlouskova (2007).”
- Output, renewable energy consumption and trade in Africa (2013, methodology): “It is useful to confirm the existence of cointegration for the error correction model by using a second test for panel cointegration proposed by Kao (1999), which is based on ADF statistic.”
- Unit Roots and Cointegration in Panels (2005, background): “An empirical application to the analysis of house prices in the US is provided in Holly et al. (2007). Bai and Kao (2005), Westerlund (2007b), and Bai, Kao and Ng (2007) suggest estimators for the cointegrated panel data model given by”
- Energy Consumption and Economic Growth – New Insights into the Cointegration Relationship (2010, unknown): “According to Wagner and Hlouskova (2010), the DOLS estimator outperforms 6Since the panel unit root tests of the idiosyncratic components suggest stationarity, we do not test for cointegration between the idiosyncratic components of energy consumption, GDP and energy prices.”