Arturas Juodis, "A Regularization Approach to Common Correlated
Effects Estimation", Journal of Applied Econometrics, Vol. 37, No. 4,
2022, pp. 788-810.

The data used in this article are the same as used by

  Shou-Yung Yin, Chu-An Liu, and Chang-Ching Lin (2021) "Focused
  Information Criterion and Model Averaging for Large Panels With a
  Multifactor Error Structure", Journal of Business and Economic
  Statistics, Vol. 39, No. 1, 2021, pp. 54-68.
 
The dataset is provided in *.csv and *.xlsx format zipped in the file
aj-data.zip; see Voigtlander (2014) for a detailed description of the
data and their source. 

Following Yin et al. (2021), to ensure the balanced panel, we exclude
several sectors having missing values. The dataset can be also
downloaded from the Data Archive of the Journal of Business and
Economic Statistics:

https://www.tandfonline.com/doi/suppl/10.1080/07350015.2019.1623044?scroll=top.

All results were obtained in Python 3.7 with Numpy Random Seed 2.

Please address any questions to:

Arturas Juodis
Amsterdam School of Economics
University of Amsterdam