The impact of corruption on analyst coverage. [Presentation]

Hassan, Omaima; Giorgioni, Gianluigi

Abstract

This study aims to investigate the impact of country-level corruption and firms' anti-bribery policies on analyst coverage. Analyst coverage has been identified as a powerful tool to detect fraud and should equally act as a possible tool to reduce corruption. Although the literature on corruption at the country level is rich, it is geared towards the determinants of corruption rather than its consequences; in addition there are fewer studies that have focused on the impact of corruption at firm level, because of data limitations. This paper addresses this gap and contributes to the literature on the consequences of corruption at firm level. The research used a negative binomial count regression method on a longitudinal dataset, consisting of a sample of S&P Global 1200 companies for the years 2010-2015. To control for potential endogeneity bias and improve the reliability of the estimation, both country-level corruption and firms' anti-bribery policies variables were instrumented. After controlling potential endogeneity bias, the results show that the adoption of anti-bribery policies at firm level attracts more analysts to follow a firm. The results for corruption at country level show that analyst coverage increases in less corrupted countries indicating that the costs of corruption exceed its potential benefits. When the variables - i.e. corruption at country level and anti-bribery policies - interact, the relationship is positive and highly significant. Given the potentially important role played by anti-corruption measures, firms are encouraged to adopt them to reduce the incidence of corruption and to increase analyst coverage, which will reinforce the benign effect of monitoring. This was an invited presentation. The conference was originally meant to be hosted in Seoul, South Korea, but was moved online due to COVID-19 concerns.

Citation

HASSAN, O. and GIORGIONI, G. 2022. The impact of corruption on analyst coverage. Presented at the 3rd International conference on modern management based on big data (MMBD 2022), 15-18 August, [virtual event].

• Presentation Conference Type: Presentation / Talk
• Conference Name: 3rd International conference on modern management based on big data (MMBD 2022)
• Start Date: Aug 15, 2022
• End Date: Aug 18, 2022
• Deposit Date: Aug 19, 2022
• Publicly Available Date: Aug 19, 2022
• Peer Reviewed: Peer Reviewed
• Keywords: Corruption; Financial analysts; Analyst coverage; Bribery
• Public URL: https://rgu-repository.worktribe.com/output/1739815