CEES: The First Dataset that Links Firm Performance with Worker Heterogeneity in China-质量院英文网
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CEES: The First Dataset that Links Firm Performance with Worker Heterogeneity in China

May 5, 2017

“The China Employer-Employee Survey (CEES) is the first dataset that links firm performance with worker heterogeneity in China, and therefore is a precious data resource for various research topics,” Professor Yu Miaojie commented in his introduction to the CEES data in the Special Issue Editorial of China Economic Journal (Issue 1, 2017). “In other words, the CEES dataset is a treasury for both economist and policy makers for future research. Its impact will become more and more important and evident for years to come.” 


Yu Miaojie, Deputy Dean of National School of Development (NSD) of Peking University and Ph.D. in Economics of the University of California, Davis, is Economist with Highly Cited Papers ranking Top 1% in Global Economics and Management. He serves as Consultant for the United Nations, Asian Development Bank Institute, Ministry of Finance (China), Ministry of Commerce (China), Counselors’ Office of the State Council (China) and some local governments. His publication obtained the Annual Best Papers Award of the Royal Economic Society. Due to this respect, he won the Royal Economic Society Award and has become the first Chinese Economist Awardee.


Why does Professor Yu Miaojie speak highly of the CEES dataset? What indicators does the CEES dataset include?


China Employer-Employee Survey, initiated by Institute of Quality Development of Strategy (IQDS) of Wuhan University in cooperation with Hong Kong University of Science and Technology and the Chinese Academy of Social Sciences, is the unique matched dataset in the large economics like China. After the 3-year questionnaire design, pilot survey and effective coordination, the Survey was successfully completed in 2015, and in 2016, it expanded new survey samples and traced its original surveyed samples. It includes more than 500 variables of over 1,000 firms and 10,000 workers on firm’s characteristics, including not only many firm’s financial variables as shown in the standard accounting sheets but also many variables on product quality, technology innovation and transformation, and human resources. Regarding worker heterogeneity, the dataset includes variables on employee’s personal information, income, education, and health.


The CEES dataset is a precious data resource for various research topics. With joint efforts of IQDS and NSD scholars, seven papers took the initial step in applying the CEES dataset and were published in the Special Issue (Issue 1, 2017) of China Economic Journal. Their topics cover interaction between firm-level behavior and worker-level features, for example, firm innovation, quality upgrading, government intervention, worker’s cognitive and non-cognitive abilities, and labor protection.


As Deputy Editor of China Economic Journal, Yu Miaojie explained the academic and social values of the CEES dataset with detailed narration. “The matched datasets with firm performance and worker heterogeneity are rarely available today. Indeed, only few small rich countries such as Denmark have such an employer-employee survey dataset. Generally, the matched employer-employee datasets are not available in large OECD countries such as the United States and Japan. Needless to say, such data are rare in developing countries. A million thanks to the colleagues at the Institute of Quality Development Strategy at Wuhan University and their collaborators for their great efforts and tremendous work, now the employer-employee survey (CEES) datasets are available for China, the second largest economy and the largest trading country in the world.”


Now, the CEES is widely recognized as a great success among domestic and international academics. It success owes much to the perseverance of the survey team. Just like one of the CEES founders Professor Cheng Hong’s words, “Perseverance makes miracles.” It is perseverance that creates the first dataset liking firm performance with worker heterogeneity in China.