High-Level Politically Connected Firms, Corruption, and Analyst Forecast Accuracy Around the World

Jieping Chen (First Author), Yuan Ding (Participant Author), Chansog (Francis) Kim (Participant Author)

Research output: Contribution to journalJournal

139 Citations (Web of Science)

Abstract

The international business (IB) literature has widely recognized political forces as major factors that complicate the strategic decisions of multinational enterprises (MNE). Analyses by financial intermediaries can help to reduce the risk of information asymmetry caused by such factors. Using firm-level data from 17 jurisdictions between 1997 and 2001, this study investigates the association between a firm's high-level political connections and earnings forecasts made by financial analysts, an important group of financial intermediaries. We find that, after controlling for other determinants of forecast accuracy, analysts experience greater difficulty in predicting the earnings of firms with political connections than those of firms with no such connections. However, in jurisdictions in which corruption level is relatively high, earnings forecast accuracy is influenced more by a firm's political connections. Our findings contribute to the IB literature by demonstrating that political connections exacerbate the information asymmetry between investors and managers, and also that anti-corruption measures can curb the adverse effect of political connections on the corporate information environment. These findings bear the practical implication that MNEs must consider political issues when making resource allocation decisions. [PUBLICATION ABSTRACT]
Original languageEnglish
Pages (from-to)1505-1524
JournalJournal of International Business Studies
Volume41
Issue number9
DOIs
Publication statusPublished - 2010

Keywords

  • DETERMINANTS
  • EARNINGS
  • EQUITY
  • FOREIGN DIRECT-INVESTMENT
  • GOVERNMENT
  • INFORMATION
  • MULTIPLE-REGRESSION
  • PERSPECTIVE
  • RISK
  • STRATEGIES
  • accounting
  • orruption
  • political relationships
  • primary data source

Indexed by

  • FT
  • ABDC-A*
  • Scopus
  • SSCI

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