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Corporate R&D intensity and high cash holdings: post-crisis analysis

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Abstract

This paper examines the effect of R&D investment on firms’ level cash holdings in the UK market after the financial market crisis, using the trade-off model and the pecking order model as a theoretical backdrop. For this purpose, we employ a sample of UK listed non-financial no-utility firms throughout 2010–2018. Our findings indicate that R&D spending provides a reasonable explanation for UK firms’ increased cash ratio during post-crisis. Using Fama and French’s (Industry costs of equity. J Financ Econ 43(2): 153–193, 1997) classification, we conduct cross-sectional linear regression analysis for industry and firm groups’ sub-samples. The analysis provides evidence of considerable heterogeneity in terms of cash holding and investment spending across industries. What is more, technology and healthcare firms have contributed to the increase in cash levels. The findings reveal a positive and significant effect of R&D intensity on cash holdings, while R&D-intensive firms hoard cash driven by industry concentration. We confirm our findings’ persistence after performing various additional analyses and robustness checks. This is the first study to provide empirical evidence in the post-crisis era on how R&D influences firm-level cash holdings in the UK market setting.

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Notes

  1. There is limited evidence in the academic literature on post-crisis recovery at the firm level. A recent effort in this direction is the study of Jin et al. (2018), that examined the business performance after the 2007–2008 financial crisis. Hence, we consider that focusing on a post-financial crisis sample can provide important information to stakeholders for the cash-R&D investment nexus.

  2. According to the Office for National Statistics (2019a), statistics revealed that total research and development expenditure by UK firms amounted to approximately 25.0 billion British pounds in 2018, with an increase of 5.8% from the previous year.

  3. To give an example, a Financial Times’ article “UK’s largest companies sit on £53bn mountain of cash”, published on October 6, 2014 indicates that the cash held of UK firms has increased by more than four times relative to the cash level reported on 2008’s financial statements (see https://www.ft.com/content/e29a1cee-4c95-11e4-a0d7-00144feab7de).

  4. In terms of the trade-off theory, the theoretical framework relates to both optimal debt ratios and optimal cash balances. Throughout the study, we employ the Miller-Orr’s (1966) model of cash management and the transaction motive by Bates et al. (2009) to examine the firm-level cash holding in the UK market.

  5. We follow Haushalter et al. (2007) who defines predation risk as the likelihood of market share loss due to insufficient investment.

  6. Based on Froot et al. (1993), we define hedging as the firm’s use of cash to gain advantage on profitable investment projects at the expense of its’ rivals.

  7. We acknowledge that financial firms, such as banks, insurance companies, have different accounting requirements (see, Deloof 2003). We exclude firms in the financial sector, as they have different cash requirements and can be subject to some form of monitoring supervision rather than firms in the non-financial sector; therefore, we choose to exclude these firms from our analysis to ensure the legitimacy of our findings.

  8. To assess the economic significance, we multiply the standard deviation of the XRD score by the coefficient (Column 1) and divide by average CASH: (st.dev. XRD x coeff. XRD)/ mean CASH = (0.441 × 0.088)/16.8 = 0.231 or 23.10%.

  9. In an unreported analysis, we investigate the association between a firm’s R&D investment and its excess cash. We first estimate yearly cross-sectional regressions based on Eq. (1) after excluding the R&D ratio. The abnormal firm-level cash ratio is calculated using the residuals (see Dittmar and Mahrt-Smith 2007; Opler et al. 1999). We then regress the abnormal cash measure on the R&D ratio to examine the empirical prediction. Consistent with our main inferences, the result reveals a positive association between the two variables. Hence, we cannot reject the empirical hypothesis (H1).

  10. The analysis covers ten groups of firms since firms in financial and utility industries are excluded. For example, we construct a dummy variable “fama1” that takes the value of 1 for the industry of Consumer Non-Durables and 0 otherwise. Kenneth French’s website details the mapping of SIC codes for the Fama–French 12 industries: https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/Data_Library/det_12_ind_port.html.

  11. In untabulated analysis, we use lagged independent variables in the empirical model to allay endogeneity concerns. Specifically, we lag by one period (t-1) the R&D ratio and the control variables of Eq. (1). The coefficient on XRD is positive and statistically significant, where the dependent variable is CASH, which is consistent with the main regression results. Hence, we confirm our first proposed hypothesis stating a positive relation between R&D investment and cash holding at the firm level. Although not tabulated for brevity, the results are available upon request.

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Authors and Affiliations

  1. Department of Economics, University of Patras, University Campus–Rio, 26504, Patras, Greece

    Efstathios Magerakis

  2. Department of Business Administration, University of Patras, University Campus–Rio, P.O. Box 1391, 26500, Patras, Greece

    Konstantinos Gkillas

  3. Department of Accounting and Finance, Hellenic Mediterranean University, Heraklion, Greece

    Christos Floros

  4. School of Social Sciences, Hellenic Open University, Aristotelous 18, 26335, Patras, Greece

    George Peppas

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Appendices

Appendix A

See Table 13.

Table 13 Variable definition
Full size table

Appendix B

See Table 14.

Table 14 Theoretical model predictions
Full size table

Appendix C: Cross-industry cash holding

Panel 1: Consumer non-durables

figure a

Panel 2: Consumer–durables

figure b

Panel 3: Machinery, trucks, planes, etc.

figure c

Panel 4: Oil, gas, and coal extracted products

figure d

Panel 5: Chemicals and allied products

figure e

Panel 6: Business equipment

figure f

Panel 7: Telephone and tv transmission

figure g

Panel 8: Wholesale, retail, some services

figure h

Panel 9: Health, medical equipment

figure i

Panel 10: Other, mines, construction, etc.

figure j

This figure provides the average cash holdings for UK listed firms, based on the fama–french 12 groupings, resulting in a total of 10 industries, as displayed in panels 1–10, after excluding non-financial and non-utility firms. Dash lines indicate the average cash to total assets ratio

Appendix D: The trend in the R&D investment proxies

Panel A: Coefficient on R&D-to-Sales

figure k

Panel B: Coefficient on R&D-to-total assets

figure l

Panel C: Coefficient on R&D dummy

figure m

Figure plots the coefficients on R&D to Sales (Panel A), R&D to total assets (panel B), R&D dummy (Panel C) in yearly linear regressions of cash-to-assets ratio, including the same controls used in the baseline model and industry fixed effects. Dash lines indicate the 95% confidence intervals. The R&D Dummy is an indicator that equals 1 if the firm spends R&D and 0 otherwise (He and Wintoki 2016). The sample includes all publicly traded non-financial and non-utility UK firms with positive assets, sales, and non-missing values for cash ratio and the main variables in Amadeus from 2010 to 2018. Standard errors are two-way clustered (by firm and year)

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Magerakis, E., Gkillas, K., Floros, C. et al. Corporate R&D intensity and high cash holdings: post-crisis analysis. Oper Res Int J 22, 3767–3808 (2022). https://doi.org/10.1007/s12351-021-00660-3

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