Abstract
This study fills an important gap in the literature by providing causal evidence of the impact of relaxing financial constraints on corporate social responsibility (CSR). To isolate this causal link, we examine the enactment of anti-recharacterization laws in some U.S. states, an exogenous shock that has strengthened creditor rights and eased financial constraints of the treated firms. Our difference-in-difference analysis suggests that relaxing financial constraints leads to higher CSR. This evidence is more pronounced in financially constrained firms, firms with more analyst dispersion and increased volatility of cash flows. We also find that the most impacted firms are those with increased post-shock debt financing. In sum, our evidence suggests that easing access to external finance drives corporate goodness, in particular in firms that value external financing.
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Notes
The UN PRI is an UN-supported global initiative promoting the integration of environmental, social and governance (ESG) factors into institutional investing practices.
The literature on whether firms can ‘do well by doing good’ is abundant and provides mixed evidence. Margolis and Walsh (2003) show that 48 of 109 reviewed studies do not find a distinguishable relationship between CSR and financial performance, and 54 (7) document a positive (negative) relationship. The meta-analytic findings of Orlitzky et al. (2003) support a modest positive correlation between CSR and financial performance. Recent evidence, however, appears to lend support to the stakeholder maximization view of CSR (e.g., Attig et al., 2013; Cheng et al., 2014, among others).
For instance, while financial slack is relevant for CSR spending, Cheng et al. (2014) show that CSR lowers financial constraints.
ARL is particularly relevant for the purpose of our study because collateral pledging enhances a firm’s financial capacity (e.g. Hart and Moore, 1994; Stiglitz and Weiss, 1981). ARL offer protection to secured lenders from the automatic stay, providing an enhanced creditor rights for borrowers located in ARL-states and, thus, represent an ideal source of variation in easing financial constraints of ARL firms. By increasing creditors’ ability to recover collateral in bankruptcy, ARL adoption increases the value of pledgeable collateral, which reduces the costs of debt financing and improves access to credit (e.g., Chu, 2020; Ersahin, 2020; Fairhurst and Nam, 2022; Favara et al., 2021; Li et al., 2016; Tut, 2021).
We use CSR, ESG, and sustainability interchangeably.
Cheng et al., (2014, and references therein) argue that CSR may function in similar ways to advertising, leading to an increase in demand for the firm’s products and services.
Almeida et al. (2004) show that financially constrained firms tend to save cash out of cash flows. As such, these firms may limit their CSR investments because such investments may not generate cash flows in the short term. Campello et al.’s (2010) survey of CFOs of financially constrained firms suggests that these firms are more likely to cut strategic investments in a wide range of activities. Thus, financially constrained firms may limit CSR investment, even though it is viewed as a strategic investment. Further, CSR potential benefits are difficult to attribute to CSR investments ex post (Scherer et al., 2016).
This corroborates the findings of the CFA Institute survey (2018) that 65% of the surveyed financial professionals cited risk management as a main driver of ESG integration in equity investments.
Early related work suggests that strengthening creditor rights increases credit supply and improves firms’ access to debt financing (Aghion and Bolton, 1992; Hart and Moore, 1994). Vig (2013) argues that strengthening creditor rights increases the liquidation value of collateral, improves borrowing capacity, and reduces the cost of borrowing. Djankov et al. (2007) show that stronger creditor rights increase the supply of credit, and Haselmann et al. (2010) find that greater enforcement of creditor rights in some European countries increases lending.
This shock is distinct from other financial constraints shocks used in prior related work. For instance, Faulkender and Petersen (2012) examine the role of capital constraints in firms' investment decisions. They focus on the passage of The American Jobs Creation Act in 2004, which lowered the cost of repatriating foreign capital and the cost of funding domestic investments with internal foreign cash. Chaney et al. (2012) use local variations in real estate prices as shocks to the collateral value of firms to examine the impact of real estate prices on corporate investment.
The three-judge panel concluded, “in spite of its label and the terminology used, the agreement executed between Fidelity and Sunbelt was not truly a sale of accounts receivable but was in substance a secured lending agreement under which Fidelity held all of Sunbelt's accounts (and other assets) as collateral and Sunbelt remained personally liable for any shortfall". An article that appeared on the website of the American Bankruptcy Institute (2004) states, “A Fifth Circuit decision from this summer has attracted very little attention, but it could be a pivotal case in some hard-hitting litigation over asset securitization that is sure to come” and adds “The reason this case could be a sleeper is that the billions of dollars changing hands through asset securitization and bankruptcy remote vehicles typically depend on a rock-solid conclusion that the transaction involved a true sale, not a disguised security interest or other device. If the courts are willing to look past form to substance, a number of these so-called bankruptcy remote financing devices would be swept back into bankruptcy—much to the consternation of those who set up the deals and the attorneys who wrote the opinion letters”.
“Chief executive office” means the place from which the debtor manages the main part of its business operations or other affairs” (American Law Institute 2010, p. 18).
https://sraf.nd.edu/data/augmented-10-x-header-data/. These data are relevant in the context of our study because Compustat reports the most recent state of incorporation. We however use Compustat to complete the missing data.
In untabulated results, we fit an augmented difference-in-difference regression that allows for group-specific linear trend. Our F-test results fail to reject the null that the interaction treated x trend is zero. We thank an anonymous reviewer for this suggestion.
Further, implementing CSR strengths is more costly but more beneficial than avoiding CSR concerns (Hart, 1995).
Interpreting the negative and significant coefficient of ARL on product characteristics is not straightforward. We posit that this result may indicate that financially constrained firms consider this a priority area and invest in the strengths of product characteristics (e.g. R&D and innovation). Once their constraints are relaxed, firms may put less emphasis on this area. To some extent, our evidence that relaxing financial constraints leads to more investments in the area of environmental performance corroborates the recent finding of Goetz (2019) that lower financing costs reduce toxic emissions and boost investments in emission reduction activities.
Untabulated results suggest that our conclusions remain valid when we use propensity score matching (PSM).
Incorporation in Delaware may also affect firm value (Daines, 2001; Gompers et al., 2003) and thus the likelihood of receiving a takeover bid and being acquired (Daines, 2001). Relatedly, Delaware is subject to different tax and legal treatments (Black and Strahan, 2002; Dick and Lehnert, 2010). Black and Strahan (2002) argue that while the number of firms operating in Delaware is close to the average, the number of incorporations (per capita) is about 20 times the average number in the other states. They dropped Delaware from their analysis, however, and given the context of their study, they also excluded South Dakota.
For example, if firm Z is based in Texas, we randomly assign Firm Z a law passage year. The random ‘on’ period would be from this random law passage year plus six years (in our actual ARL shock, the ‘on’ period runs from 1997 to 2003).
The authors collect their data following the procedure developed in Feng et al. (2009) and use a computer algorithm that counts the number of subsidiaries or affiliates listed in Exhibit 21 (or in some cases Exhibit 22) of SEC Form 10-Ks with names that contain the words ‘‘Limited Partnership,’’ ‘‘Limited Liability Partnership,’’ ‘‘Limited Liability Corporation’’ (or their acronyms ‘‘L.P.,’’ ‘‘LP,’’ ‘‘LLP,’’ ‘‘L.L.P.,’’ ‘‘LLC,’’ ‘‘L.L.C.’’), or ‘‘trust.’’.
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Acknowledgements
I am indebted to Ming Jia (Section Editor) and three anonymous reviewers for their guidance and insightful comments throughout the review process. I thank Catherine Loughlin, Dana Kabat-Farr, Hamdi Driss, and participants at the AfriMed Finance Society Summer Conference (AFS 2022) for useful suggestions. I appreciate the generous financial support from Canada’s Social Sciences and Humanities Research Council.
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Appendix
Appendix
Variable definitions and data sources.
Variable | Definition | Source |
|---|---|---|
Panel B. Key variables | ||
ARL | As in Ersahin (2020), a dummy variable equal to 1 if a firm is “treated”; that is, if a firm, before 2004, is incorporated or headquartered in either Texas or Louisiana after 1997, or if a firm is incorporated or headquartered in Alabama after 2001, and 0 otherwise | Author’s calculation |
Placebo | A dummy variable equal to 1 for firms incorporated in a state neighboring a state in which ARL is adopted, and 0 otherwise | As above |
\({ARL}_{-1}\) | An indicator variable equals 1 if the observation occurs before the passing of the law (one to three years), and 0 otherwise | |
\({ARL}_{0}\) | An indicator variable equals 1 if the observation occurs in the year of the passing of the law, and 0 otherwise | |
\({ARL}_{+1}\) | An indicator variable equals 1 if the observation occurs one year after the passing of the law, and 0 otherwise | |
\({ARL}_{+2}\) | An indicator variable equals 1 if the observation occurs more than one year after the passing of the law (until 2003), and 0 otherwise | |
Panel B. Dependent variables | ||
CSR | For each qualitative issue area (i.e. community, diversity, employee relations, environment, human rights, and product characteristics) and for each firm-year, we calculate a score equal to the number of strengths minus the number of concerns. We then sum the qualitative issue areas scores to obtain an overall CSR score | Author’s calculations using MSCI ESG STATS (KLD data) |
CSR strengths | The sum of the total number of strengths in the different qualitative issue areas | As above |
CSR concerns | The sum of the total number of concerns in the different qualitative issue areas | As above |
Panel C. Control variables | ||
SIZE | Natural logarithm of the firm market capitalization | Authors’ calculations using Compustat data |
LEVR | Leverage ratio defined as the ratio of total debt to total assets | As above |
CAPEX | The ratio of capital assets to total assets | As above |
RD | The ratio of research and development to total assets | As above |
SGR | The annual sales growth rate | As above |
ROA | Return on assets | As above |
INTANG | The ratio of intangible assets to total assets | As above |
CINTENS | Capital intensity, measured as the ratio of net property, plant, and equipment to total assets | As above |
AGE | Firm age, computed as the number of years since the firm’s appearance in Compustat | As above |
CFOVOL | The volatility of cash flows from operations, measured using 10-year standard deviation | As above |
IOWN | Fraction of firm’s shares held by institutional investors | Authors’ calculations using Thomson 13-F data |
IOWN-LT | Fraction of firm’s shares held by long-term institutional investors, identified using Gaspar et al.’s (2005) approach | As above |
DISP | Dispersion of analyst forecasts defined as the coefficient of variation of one-year-ahead analyst forecasts of earnings per share in June of year t | I/B/E/S |
ILLIQ | Roll’s (1984) average effective bid-ask spread over the fiscal year | Authors’ calculations |
Redeployability | Asset redeployability measured using Kim and Kung’s (2017) index | Kim and Kung’s (2017) index |
Panel D: Macro variables | ||
GUBER | Binary variable equal to 1 if a gubernatorial election occurred in that state in that year | Carl Klarner (Harvard University) and the CQ Press Voting and Elections Collection |
SGDP | State GDP growth | Bureau of Economic Analysis (www.bea.gov) |
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Attig, N. Relaxed Financial Constraints and Corporate Social Responsibility. J Bus Ethics 189, 111–131 (2024). https://doi.org/10.1007/s10551-023-05353-9
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DOI: https://doi.org/10.1007/s10551-023-05353-9