Purpose

This study examined the effect of different types of politically connected (PCON) Malaysian firms on analysts' forecast accuracy and dispersion.

Design/methodology/approach

The study identified different types of PCON firms according to Wong and Hooy's (2018) classification, which divided political connections into government-linked companies (GLCs), boards of directors, business owners and family members of government leaders. The sample covered the period 2007–2016, for which earnings forecast data were obtained from the Institutional Brokers' Estimate System (IBES) database and financial data were extracted from Thomson Reuters Fundamentals. We deleted any market consensus estimates made by less than three analysts and/or firms with less than three years of analyst forecast information to control for the impact of individual analysts' personal attributes.

Findings

The study found that PCON firms were associated with lower analyst forecast accuracy and higher forecast dispersion. The effect was more salient in GLCs than in other PCON firms, either through families, business ties or boards of directors. Further analyses showed that PCON firms—in particular GLCs—were associated with more aggressive reporting of earnings and poorer quality of accruals, hence providing inadequate information for analysts to produce accurate and less dispersed earnings forecasts. The results were robust even after addressing endogeneity issues.

Research limitations/implications

This study found new evidence of the impact of different types of PCON firms in exacerbating information asymmetry, which was not addressed in prior studies.

Practical implications

This study has a significant practical implication for investors that they should be mindful of high information asymmetry in politically connected firms, particularly government-linked companies.

Originality/value

This is the first study to provide evidence of the impact of different types of PCON firms on analysts' earnings forecasts.

中文翻译：

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政治关联公司的类型和分析师的盈利预测

目的

本研究考察了不同类型的政治关联 (PCON) 马来西亚公司对分析师预测准确性和分散性的影响。

设计/方法/方法

该研究根据 Wong 和 Hooy (2018) 的分类确定了不同类型的 PCON 公司，该分类将政治联系分为政府关联公司 (GLC)、董事会、企业主和政府领导人的家庭成员。样本涵盖 2007-2016 年期间，盈利预测数据来自机构经纪商估计系统 (IBES) 数据库，财务数据来自汤森路透基本面。我们删除了少于三名分析师和/或拥有少于三年分析师预测信息的公司做出的任何市场共识估计，以控制个别分析师个人属性的影响。

发现

研究发现，PCON 公司与较低的分析师预测准确度和较高的预测离散度有关。这种影响在 GLC 中比在其他 PCON 公司中更为显着，无论是通过家族、业务关系还是董事会。进一步的分析表明，PCON 公司——尤其是官联公司——与更积极的收益报告和较差的应计项目质量相关，因此为分析师提供准确且分散程度较低的收益预测的信息不足。即使在解决了内生性问题之后，结果也是稳健的。

研究限制/影响

这项研究发现了不同类型的 PCON 公司在加剧信息不对称方面的影响的新证据，这在之前的研究中没有得到解决。

实际影响

这项研究对投资者具有重要的实际意义，即他们应该注意政治关联公司，尤其是政府关联公司的高度信息不对称。

原创性/价值

这是第一个提供证据证明不同类型的 PCON 公司对分析师盈利预测的影响的研究。