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Qu, X. E., Hu, Y. X., & Zhao, Y. J. (2018). The Impact of Industrial Agglomeration on Manufacturing Green Total Factor Productivity—An Empirical Analysis Based on the Perspective of Long- and Short-Term Industry Heterogeneity. Journal of Beijing Institute of Technology (Social Science Edition), 21, 27-36.

has been cited by the following article:

• TITLE: Does Industrial Agglomeration Affect the Accuracy of Analysts’ Earnings Forecasts?

  AUTHORS: Xiaoyuan Liu

  KEYWORDS: Industrial Agglomeration, Analysts Forecasts, Information Asymmetry

  JOURNAL NAME: American Journal of Industrial and Business Management, Vol.10 No.5, May 8, 2020

  ABSTRACT: In China, the unbalanced geographical distribution of economic activities is an important feature of modern economic growth. Accordingly, a large number of industrial clusters characterized by industrial clusters have emerged, making important contributions to regional economic development. This article uses 2003-2017 Chinese A-share listed companies as a sample to study the impact of industrial agglomeration on analysts’ earnings forecast accuracy. This paper finds that industrial agglomeration can significantly improve the accuracy of analysts’ earnings forecasts by reducing the in- herent mechanism of information asymmetry, which is more obvious in state-owned enterprises. This paper expands the relevant research on industrial agglomeration and analyst forecasting, and proves that industrial agglomeration improves the information environment of the capital market and enables analysts to better play the role of information intermediaries.