Does a Firm’s Life Cycle Explain Its Propensity to Engage in Corporate Tax Avoidance?

Abstract

This study examines whether a firm’s life cycle explains its propensity to engage in corporate tax avoidance. Based on the Dickinson (2011) model of firm life cycle stages and a large dataset of US publicly listed firms over the 1987–2013 period, we find that tax avoidance is significantly positively associated with the introduction and decline stages and significantly negatively associated with the growth and mature stages using the shake-out stage as a benchmark. We observe a U-shaped pattern in tax avoidance outcomes across the various life cycle stages in line with the predictions of dynamic resource-based theory. Our findings are consistent using several robustness checks. Overall, our results show that a firm’s life cycle stage is a significant determinant of tax avoidance.

Acknowledgments

We would like to thank participants at the 2015 Accounting and Finance Association of Australia and New Zealand (AFAANZ) Annual Conference in Hobart and the 2015 Pacific Basin Finance Journal Conference in Perth for their valuable comments on previous versions of the paper. We are also indebted to the anonymous referee of the European Accounting Review and Martin Jacob (Associate Editor) for their insightful suggestions which have significantly improved the paper. All remaining errors are our own.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Supplemental Material

Supplemental material for this paper can be accessed on the Taylor and Francis website, doi:10.1080/09638180.2016.1194220.

Notes

1 We also employ the alternative life cycle proxy measure of DeAngelo et al. (2006) as a robustness check of our main results. They use retained earnings scaled by total assets or total equity to proxy for a firm's life cycle.

2 Although firm age and size have been used to measure life cycle stages in prior research (e.g. Bhattacharya, Black, Christensen, & Mergenthaler, 2004; Bradshaw, Drake, Myers, & Myers, 2012; Chen, DeFond, & Park, 2002), there is likely to be a degree of divergence between these attributes and stages because a firm's demise can occur at any point in its life cycle, although the probability of failure is greater in the early stages (Javanovic, 1982) and is contingent upon initial resource endowment (Dickinson, 2011).

3 For instance, a firm may be in the growth stage at 10 years of age, while another firm may be in the introduction stage at 15 years of age. As asserted by Dickinson (2011), the reason for this is that a firm may develop new products, enter into new markets or restructure such that it can move across life cycle stages non-sequentially, so a monotonic association between firm age and life cycle stages is not directly observed.

4 For example, some firms are likely to have moved rapidly into the shake-out or decline phase during the 2008 global financial crisis before recovering. Further, innovation in a particular sought-after pharmaceutical product may propel a firm into a high-growth phase, whereas rapid changes in commodity prices may expose a firm in the extractive industries to periodic growth and shake-out stages within its overall life cycle progression.

5 Pecking-order theory suggests that as a result of adverse selection costs, firms prefer debt to equity when raising external financing (Myers & Majluf, 1984).

6 In terms of corporate governance, Ramaswamy et al. (2007) find that in the initial and growth stages, a firm often has weak governance structures as it may lack the time, resources, managerial expertise or leadership needed to establish operative governance structures, especially when exposed to rapid change and uncertainty.

7 In particular, dynamic resource-based theory is derived from evolutionary economics, strategic management and organizational science. It focuses on resource patterns and trajectories and capability evolution across a firm's life cycle. Helfat and Peteraf (2003) define organizational capabilities as: ‘ … the ability of an organization to perform a coordinated set of tasks, utilizing organizational resources, for the purpose of achieving a particular end result,’ and resources as ‘ … an asset or input to production (tangible or intangible) that an organization owns, controls, or has access to on a semi-permanent basis’ (p. 999).

8 For instance, Drobetz et al. (2015) observe increases in asset tangibility, operating income, net working capital and capital expenditures in the growth and mature stages as compared to the other stages, and higher levels of market-to-book ratios, R&D, equity issuances and financing deficits in the introduction and decline stages.

9 Research by Cai and Liu (2009) finds that where a firm is under substantial competitive pressure, it is more likely to avoid corporate taxes because it can then use the additional funds to compete.

10 For example, R&D investment is also predicted to be higher during the introduction stage as a firm seeks ways to rapidly increase cash flows (Koester et al., 2013). Prior research finds R&D expenditure to be positively associated with tax aggressiveness because R&D may be used to facilitate aggressive transfer pricing or income shifting activities (Dyreng et al., 2008; Waegenaere, Sansing, & Wielhouwer, 2013).

11 This assertion is consistent with the research findings of O’Connor and Byrne (2015) who provide evidence that a mature firm practices better overall strength of governance as compared to a younger firm.

12 Since the 1987 year, firms have been required to disclose cash flow data under the Statement of Financial Accounting Standards No. 95 (FASB, 1987).

13 We acknowledge that the different stages of a firm's life cycle may explain the unobserved time invariant features of tax avoidance. In fact, there may be partial co-movement between tax avoidance measures and life cycle stages. Fixed effects regression analysis may reveal if the determinants of life cycle stages stems from changes within a firm over time. Thus, a fixed effect model controls for the average differences in both observable and unobservable predictors across firms. The fixed effect coefficients incorporate all the across firm differences and what is retained is the within-firm differences (e.g. Wooldridge, 2010).

14 We also note that the number of observations in any given regression model varies depending on the model-specific data requirements.

15 We do not employ CASH_ETR as a main proxy measure of tax avoidance in this study as cash taxes paid are often fragmented in nature. For instance, it is possible that firms report nil or negligible amounts of cash taxes paid in some years followed by large absolute cash taxes paid upon IRS audit settlements in other years.

16 We also note that the GAAP_ETR is bounded between 0 and 1, which is consistent with prior research (e.g. McGuire et al., 2012).

17 Graham, Raedy, and Shackelford (2012) claim that permanent differences are important in tax planning because they can reduce the taxable income reported to the tax authorities, whil maintaining the accounting income reported to shareholders.

18 Anthony and Ramesh (1992) provide one of the first empirical methods for classifying firms into different life cycle stages. However, we do not use their method in our study for several reasons. First, their method requires a five year history of variables, removing true ‘introduction stage’ firms from the sample, so no data (and as such no meaningful analysis) on introduction stage firms are available. Second, Dickinson (2011) shows that using this method leads to an erronous classification of the stage of firms in the life cycle. Finally, their method is ‘ad hoc’ in nature, and relies on portfolio sorts to classify a firm into its different life cycle stages.

19 Huseynov and Klamm (2012) also report a mean GAAP_ETR of 0.310. Our GAAP_ETR differs from that in prior studies because our sample covers the 1987–2013 period, which was characterized by lower corporate statutory tax rates. Before 1987, the corporate statutory tax rate was more than 46%. It was then reduced to 40% in 1987 and further reduced to 34% in 1988, before finally settling at 35% in 1993. Thus, the time-series average tax rate in our sample was 35%, which is lower than that in prior studies.

20 Prior research by Hasan et al. (2015) and Habib and Hasan (2015) followed a similar approach in examining the association between firm life cycle and the cost of equity and risk-taking, respectively. However, in a robustness check (tabulated in the online supplemental material to this study), we also use the mature stage as the benchmark for our regression estimates and obtain qualitatively similar results.

21 We also include the financial reporting quality measure (FINRQ) of Dechow and Dichev (2002) and the management ability score (MAS) of Demerjian et al. (2012) in our regression model as additional control variables as a further robust check. We find that the regression results (tabulated in our online supplementary material) are consistent with the main regression results reported in Table 5.

22 In fact, the CASH_ETR measure may help to reduce any differences in financial reporting considerations across life cycle stages, which could possibly confound our empirical results (e.g. Dyreng et al., 2010).

23 Indeed, many empirical tax avoidance studies either delete or winsorize observations for which the tax avoidance measure is not meaningful, especially in cases of firms exhibiting losses.

24 We also test the association between firm life cycle stage and tax avoidance using the alternative RE/TE life cycle stage proxy measure developed by DeAngelo et al. (2006). Results tabulated in the online supplemental material are fairly similar in scope to the RE/TA life cycle stage proxy measure results reported in Table 8.

25 Specifically, a high RE/TA implies a mature or older firm with declining investments, whereas a low RE/TA firm tends to be in an early and growing stage of development (DeAngelo et al., 2006).