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Financial and corporate social performance in the UK listed firms: the relevance of non-linearity and lag effects

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Abstract

Using environmental, social and governance scores compiled by Reuters Datastream for each company’s corporate social performance (CSP), we examine the relationship between CSP and corporate financial performance (CFP) of 314 UK listed companies over the period 2002–2015. We further evaluate the relationship between prior and subsequent CFP and prior and subsequent CSP. Based on the system-GMM estimation method, we provide direct evidence that suggests that while CFP and CSP can be linked linearly; however, when we examine the impact of CSP on CFP, the association is more non-linear (cubic) than linear. Our results suggest that firms periodically adjust their level of commitment to society, in order to meet their target CSP. The primary contributions of this paper are testing (1) the non-monotonous relationship between CSP and CFP, (2) the lagged relationship between the two and the optimality of CSP levels, and (3) the presence of a virtuous circle. Our results further suggest that CSP contributes to CFP better during post-crisis years. Our findings are robust to year-on-year changes in CFP and CSP, financial versus non-financial firms, and the intensity of corporate social responsibility (CSR) engagement across industries.

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Notes

  1. A study by Deloitte showed that in 2007, 80 of the FTSE 100 firms now report on their CSR, up from 56 in 2002. This highlights that firms are increasingly recognizing the need to include CSR practices in core business strategies.

  2. Nelling and Webb (2009) obtain a significant relationship between CSP and CFP when the traditional statistical methods are used but the link weakens significantly when they employ the fixed effects method. Similarly, coupled with emphasizing the importance of endogeneity concerns, Surroca et al.’s (2010) fixed effects estimates show that CSP and CFP are not directly related. This highlights the sensitivity of results to the methods and importance of choosing the precise method. Baron et al. (2011) use the difference-GMM method for the same context. As raised by Nelling and Webb (2009), therefore, additional analyses using more advanced estimation techniques are necessary, despite the extensive empirical research in this area.

  3. We thank the referee for suggesting this dimension to us.

  4. Jiraporn and Chintrakarn (2013) provide tests to find out if the effect of the CEO power on their CSR activities is non-linear. Their regression analysis clearly detects a parabolic (reverse-U) association and they explain the connection of this nature within the ‘agency theory’ perspective.

  5. This section is based on the partial adjustment mechanism (Blinder 1986), and error correction mechanism that discusses long-term relationship between two factors and short-term deviation from equilibrium (Engle and Granger 1987; Johansen 1988). As discussed in Blundell and Bond (1998), the long-term link between the dependent variable and its determinants may differ from the short-term effects. Brammer and Millington (2008) raise the issue of deviation from ‘normal’ CSP and examine this by using the residual figures of the regression model.

  6. Any missing data were obtained from the company annual reports. Also, the time period for the variables ‘share price performance’ and ‘sales growth rate’ is 2001–2015 due to their definitions.

  7. It should further be noted that our simple correlation analysis between CSP and corporate governance quality yielded a Pearson coefficient of 0.53. This suggests that higher CSR activities go hand in hand with higher corporate governance scores, and that the combination of CSP and corporate governance scores would have qualitatively similar effects on CFP when compared with our current results.

  8. According to Chen and Metcalf (1980), CSP and size may be positively linked as larger firms have greater visibility and can invest better in CSR. One reason for this could be that bigger firms are under more pressure from stakeholders, and they need to respond to these demands more attentively or larger firms will benefit from economies of scale, better management and access regarding external stakeholders and resources, and better promotional opportunities. Orlitzky et al. (2003) and Stanwick and Stanwick (1998) show that, when size is controlled for, there still exists a positive link between CFP and CSP. Orlitzky et al. (2003) show that Chen and Metcalf’s (1980) finding that size was the real cause of both CSP and CFP was as a result of sampling error as, when analyzed over many samples, neither a significantly positive correlation between CSP and size nor a significantly positive correlation between CFP and size is found to exist.

  9. For brevity, in our regression analysis, we report industry dummies with significant effects.

  10. See also Jo et al. (2015) who consider several advanced techniques, including this specification, when they examine the link between environmental responsibility and financial performance. In addition, Shahzad and Sharfman (2015) highlight the importance of the sample selection bias, which is another type of endogeneity problem, when they investigate the effects of CSP on CFP, and they find a positive impact.

  11. Three diagnostics should be met for the system-GMM results to be reliable and consistent. Our regression results are robust to these three criteria: The Hansen test confirms the validity of the instrument sets; AR(1) test suggests the presence of first-order autocorrelation; and AR(2) test confirms the absence of second-order autocorrelation. We also tested for the potential endogeneity of the factors following the Difference-in-Hansen statistic, for which the null hypothesis states that the variable is exogenous. This test suggests that, except for the time and industry dummy variables, all other explanatory variables should be treated as endogenous; it also reveals that the differenced-instruments used in level equations are exogenous.

  12. The two inflection points for this cubic association are 2.8286 (first derivative) and 3.7228 (second derivative) in logarithmic values. These calculations suggest that when the CSP score is between 0.00 and 16.92%, or higher than 41.38%, the link between CSP and CFP is positive; when the CSP range is between 16.92 and 41.38%, CSP actually reduces CFP. We also tested for the presence of a parabolic relationship in this model but failed to detect one.

  13. Lagged CFP is not used as one of the explanatory variables in the models in Table 3 because firms are expected to maximise rather than optimize CFP. Moreover, when we investigate the dynamic aspect of the CSP and CFP link we do not include the non-linear terms, and vice versa, in order to see the clear impact of each aspect.

  14. Further note that the effect of CFPt−2 on CSPt−1 can be considered as that of CFPt−1 on CSPt.

  15. The two inflection points for the cubic link in model 3 are − 0.0709 (first derivative) and 1.3982 (second derivative). These calculations suggest that when ROA is lower than − 7.1% or higher than 139.8%, CSP decreases when CFP increases; and when ROA is between − 7.1 and 139.8%, an increase in CFP actually improves CSP. We also tested for the presence of a parabolic relationship in this model but failed to detect one.

  16. For brevity, we only report in Table 8 the results for the variables related to CSP and CFP, although the models include the other explanatory variables mentioned in Sect. 4.1.

  17. In our sample, the average CSP value is 61.73% for the pre-crisis period and 64.01% for the post-crisis period, which is in line with the conjecture that CSR activities would be given more importance by both corporate managers and capital markets following crises. One can therefore assert that UK firms became more socially responsible after Lehman Brothers filed for bankruptcy in September 2008.

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Authors and Affiliations

  1. Department of Accounting and Finance, De Montfort University, Leicester, LE2 7BY, UK

    Emmanuel Adegbite & Frank Kwabi

  2. Business School, University of Hull, Hull, HU6 7RX, UK

    Yilmaz Guney

  3. Department of Economics, Usumanu Danfodiyo University, PMP 2346, Sokoto, Nigeria

    Suleiman Tahir

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  1. Emmanuel Adegbite
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  2. Yilmaz Guney
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  3. Frank Kwabi
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  4. Suleiman Tahir
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Correspondence to Frank Kwabi.

Appendix

Appendix

See Tables 13 and 14.

Table 13 Industry classification
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Table 14 Definitions of Variables
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Adegbite, E., Guney, Y., Kwabi, F. et al. Financial and corporate social performance in the UK listed firms: the relevance of non-linearity and lag effects. Rev Quant Finan Acc 52, 105–158 (2019). https://doi.org/10.1007/s11156-018-0705-x

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