EFFECT OF CORPORATE GOVERNANCE ON RELATIONSHIP BETWEEN CORPORATE SOCIAL RESPONSIBILITY AND FIRM SIZES WITH EARNINGS MANAGEMENT (International Conference of Graduate School on Sustainability (ICGSS), 2018)
This study aims to empirically examine the influence of corporate social responsibility and firm size on earnings management, as well as how corporate governance influences the relationship between corporate social responsibility and firm size with earning management. The concept of earning management in this study adopted a model developed by Beneish (1999). Beneish implementation of M-Score Model will be modified and adjusted for firms in Indonesia. Beneish M-Score Model is developed to differentiate between manipulator and non-manipulator firms, using financial report element based on 8 ratio index. Agency theory (Jensen dan Meckling, 1976) implies the existence of information asymmetry. Information asymmetry arises when managers are more aware of internal information compared to the stakeholders. Gargouri et al. (2010) shows a positive relationship between corporate social responsibility with earning management, caused by expensive environmental activities. The results of Chih et al. (2008) study shows that companies with a high commitment to corporate social responsibility tend to do earning management. Based on positive accounting theory (Watts dan Zimmerman, 1986), earning management occurs because of political cost motives. Political costs include all costs that must be borne by the company related to government regulations, one of which is the tax burden. Large companies in a tax avoidance effort tend to reduce their profits. Lee and Choi (2002) states that firm size has a negative effect on earning management. In the other hand Rahmani and Mir (2013) states that firm size has a positive effect on earning management. The population in this study is based on manufacturing companies listed on the Indonesia Stock Exchange for the period 2013-2017, using a purposive sampling method with a specified criteria. The analysis technique uses statistical descriptive and Moderated Regression Analysis (MRA).