Business group and analyst earnings forecast: evidence from China

ABSTRACT

This study examines the economic consequences of financial analysts with business group concentration (analysts covering several member firms within a business group). Based on Chinese sample, we find that analysts covering one member firm within a group produce less accurate earnings forecasts. However, analysts covering several firms within a group predict earnings more accurately. Moreover, group concentration analysts provide superior earnings forecasts for those member firms when they share stronger information links. Furthermore, they are more likely to move to a bigger brokerage house after obtaining better forecasts. Finally, they help alleviate investors’ inattention to information links among group-affiliated firms.

KEYWORDS:

• Financial analyst
• earnings forecast accuracy
• business group
• information link
• capital market efficiency

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1. We use ‘group member firms’, ‘group firms’, ‘member firms’, and ‘group-affiliated firms’ interchangeably.

2. In our study, analysts with business group concentration or group concentration analysts represent analysts covering two or more member firms within a business group. We use them interchangeably.

3. The most similar studies to our paper are Luo and Nagarajan (2015) and Han and Liu (2019). Luo and Nagarajan (2015) investigate analysts covering firms along supply chains, and Han and Liu (2019) concentrate on analysts covering firms with interlocking relationships. However, until now, no work has investigated the implications of analysts covering firms within a business group in the emerging market, and our study tries to do this work. Also, we perform a series of cross-sectional analyses to find the mechanism that business group impacts analyst earnings forecast performance. In addition, Luo and Nagarajan (2015) and Han and Liu (2019) mainly focus on analyst earnings forecast accuracy. Our study also examines the importance of analysts with business group concentration to their forecast boldness (measurement of analysts’ private information in the forecast) and timeliness (measurement of analysts’ influence in the capital market), providing a more complete picture about analyst earnings forecast performance.

4. Precisely speaking, the four listed member firms are ultimately owned by Mr. Guanqiu Lu, the founder of Wanxiang Group. Wanxiang Group has been founded by Mr. Guanqiu Lu since the year 1969, and it is more famous than other firms controlled by him. Thus, people get used to calling the business group owned by Mr. Guanqiu Lu as Wanxiang Group in China.

5. In Wanxiang Group, Shunfa Hengye belongs to the real estate industry, Wanxiang Qianchao operates in the automotive manufacturing industry, Wanxiang Doneed is in the agriculture industry, and Chengde LoLo operates in the beverages industry.

6. ST firm represents a firm labeled as a ‘Special Treatment’ firm by the Shanghai or Shenzhen Stock Exchanges in China due to its poor financial situation (e.g. two continuous years of financial loss).

7. Because we need to compare the analyst earnings forecast accuracy between the stand-alone and group member firms, the raw earnings forecast accuracy is used in our study instead of the relative measure.

8. To keep consistency with other data, we use the logarithm of the number of employees to measure total employees for calculating employee fluctuation.

9. As shown in Panel A of Table 2, the number of distinct ‘stand-alone firm-year’ observations is 7,487(9,027–1,540). And in Panel B of Table 2, the number of distinct ‘analyst-stand-alone firm-year’ observations satisfying an analyst following a stand-alone firm in a certain year is 70,039. Thus, we can figure out that a stand-alone firm is covered by 9.35 (70,039/7,487) analysts on average. Similarly, Table 2 implies that a group-affiliated firm is covered by 2.84 [(3,757 + 622)/1,540] analysts on average. However, the above statistics are smaller than the average number (13.2872) of analysts following a firm in Table 3. The underlying reason is that we use the original distinct analyst-firm-year sample from the CSMAR database to measure analyst coverage in Table 3, whereas the analyst coverage information in Table 2 is based on our final sample for regressions, which has been subject to further attrition from the original sample.

10. The probit regressions with a large number of fixed effects may lead to inconsistent coefficient estimations (Lancaster 2000). We also run the OLS regressions to verify the robustness of all the probit regression results in our study, and our results still hold.

11. We also try the one-to-one matching method without replacement at the maximum propensity score distance (caliper) of 0.5% and 3%, and our results remain robust.

12. For instance, if there are three member firms, firm M, firm N, and firm Q within a business group, when we focus on investors’ stock reactions on firm M, firm M is the focal firm, firm N and firm Q are firm M’s group-linked firms. So, there are two observations in our sample, firm M-firm N pair and firm M-firm Q pair. Similarly, if we focus on firm N, firm N-firm M pair and firm N-firm Q pair also exist in our sample.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number 71602160] and the Natural Science Basic Research Plan in Shaanxi Province of China [grant number 2023-JC-YB-608].