Mcshane et al 2011 used sp erm credit rating scores

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McShane et al. (2011) used S&P ERM credit rating scores representing ERM, control variables which can influence firm value, and Tobin's Q as representative of firm value. In their study, there was a positive relationship between ERM and firm value, but they found that firm value did not increase as ERM application level increased. Hoyt and Liebenberg (2011) found positive effects of ERM on firm value in the study of the American insurance industry between 1998-2005. Bertinetti et al. (2013) sought to test the impact of the 200 financial and non-financial European firm examples and ERM practices on firm value. For this, while Tobin's Q was used to represent firm value, ERM applicati ons were made from firms’ annual financial statements. A positive relationship was found between the firm value and ERM practice in the study, which was also found to be statistically significant. Li and et al. (2014) used return on equity to represent firm value, sample of 135 insurance firms in China (in 2010). The Pearson correlation matrix between ERM and firm value was found to be positive and significant in the study, but in the regression analysis it was found that the level of relationship was statistically lower than the significance level. There are also studies on the effects of ERM on financial performance indicators: Gordon et al. (2009) developed an ERM index primarily to investigate the relationship between ERM and firm performance in their work. The work was done by the US Securities and Exchange Commission (SEC) on the 112 US firms from the 2005 list. As a result, it was observed that there is a strong positive relationship between ERM and firm performance. Pagach and Warr (2010) investigated the effects of ERM on long-term firm performance by explaining how ERM changed financial, asset and market characteristics. In a study conducted using 106 firms that were disclosed to the public and risk manager (Chief Risk Officer-CRO), it was found that in some firms ERM reduced earnings volatility, but in general it was found that ERM effect on firm variables was low. The results of the study fail to find that the ERM will support the situation regarding value creation.
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Financial Studies 2/2017 11 Baxter et al. (2013) used S&P ratings and Tobin's Q in 165 firms and banking and insurance sectors between 2006 and 2008. Using the S&P credit rating measures, they found a positive relationship between ERM quality and firm performance. Eckles et al (2014) tested the hypothesis that ERM implementation would reduce firms' risk reduction costs. In the study, it was seen that the fluctuations of the earnings belonging to the shares of ERM applying firms decreased and the profitability of operating per risk (fluctuation of return on assets / return of shares) increased after ERM applications. Grace et al. (2015) tested the impact of ERM on cost and revenue effectiveness. In the study, efficiency was measured from zero to one by data envelopment analysis and a comparison of firms was produced. Later, multiple regression analysis showed that ERM applications provide economically and statistically significant increases in cost and revenue effectiveness.
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