The Effect of Bank Loan Dependence on Management and Analyst Forecasts

Saori Nara and Mikiharu Noma
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Saori Nara: School of Commerce, Meiji University, Japan
Mikiharu Noma: Graduate School of International Corporate Strategy, Hitotsubashi University, Japan

The Japanese Accounting Review, 2019, vol. 9, 1-29

Abstract: This paper investigates whether and how dependence on bank loans affects management and analyst forecasts in Japan, where indirect finance has played an important role in financial arrangements for many years. We study 4,681 firm-year observations listed on the Japanese equity market from 2001 to 2011, and we show the following results. First, the dependence on bank loans increases management forecast errors. Second, the dependence on bank loans increases analyst forecast errors and dispersions but decreases analyst coverage. Third, dependence on bank loans decreases the value relevance of management and analyst forecasts. These empirical results show that disclosure and information environment are not good for firms that depend on bank loans. Furthermore, management and analyst forecasts are less incorporated in stock prices because investors rely on bank monitoring and do not utilize firms’ public disclosures or other information, such as analyst forecasts, for those who depend on bank loan. Analyst coverage, analyst forecast accuracy, and forecast agreement are all lower for firms having long term-established relationships with banks in Japan. By contrast, our research contributes two things. First, we show that disclosure of firms that are dependent on bank loans are inadequate. More specifically, management forecasts of firms that are dependent on bank loans are less accurate. Second, we reveal that management and analyst forecasts are less incorporated in stock prices in firms that are reliant on bank loans.

Keywords: Management forecasts; Analyst forecasts; Disclosure; Bank loan; Bank monitoring; Value relevance (search for similar items in EconPapers)
JEL-codes: G21 G32 M41 (search for similar items in EconPapers)
Date: 2019
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