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Expected economic growth and investment in corporate tax planning


This study investigates whether expected economic growth is associated with investment in corporate tax planning. We predict that higher expected economic growth increases the net present value of tax planning opportunities and that thus firms’ investment in tax planning will be higher in periods when expectations about economic growth are optimistic. Consistent with expectations, we find that changes in fees for auditor-provided tax services are positively associated with GDP growth forecasts after controlling for known determinants of tax avoidance. Using path analysis, we find that expected macroeconomic growth influences firms’ investment in tax planning directly, rather than indirectly through other investments. Cross-sectional analyses show this association is more pronounced for firms that are financially constrained and those that are more likely to experience a change in tax status. Our study highlights that growth expectations at the macroeconomic level are an important determinant of time-series variation in firm’s investment in corporate tax planning.

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Fig. 1


  1. 1.

    To assess the reasonableness of our hypothesis, we spoke with a recently retired senior tax director of a Fortune 500 company. While acknowledging that some tax planning occurs, regardless of the economic climate, this person believes that tax planning is more likely to occur when economic prospects are favorable for at least three reasons. First, the desire to minimize taxes is greater when companies expect more profits and corresponding taxes. Second, a favorable economic outlook often results in company expansion both domestically and abroad, which necessitates planning with respect to the best tax structures. Finally, companies have more funds for outside tax services during better economic times.

  2. 2.

    We argue that SPF’s consensus forecasts are correlated with managers’ expectations about real GDP growth. We use U.S. GDP forecasts for both multinational and domestic firms, because we are not aware of a dataset that provides GDP forecasts for foreign countries and U.S. GDP growth is also highly correlated with foreign countries’ GDP growth. During our sample period of 2003–2014, quarterly U.S. GDP growth has average correlations of 0.69 with quarterly GDP growth of OECD countries.

  3. 3.

    Outcome-based measures of tax planning, such as the cash effective tax rate (ETR), provide an alternate approach to measuring firms’ total investment in tax planning. However, outcome-based measures are problematic in our setting, because expectations about economic growth and outcome-based measures of tax planning may be simultaneously determined or tax savings may affect expected economic growth (i.e., reverse causality). Despite these concerns, we conduct supplemental analysis using cash ETRs as an outcome-based measure of tax planning and find that our inferences generally remain the same (see the online appendix).

  4. 4.

    We also examine the level of tax fees and find similar results.

  5. 5.

    Our sample begins in 2003 and ends in 2014, due to data requirements for some variables.

  6. 6.

    A firm’s discount rate also influences the NPV of expected tax savings. However, the influence of discount rates on firms’ overall investment in tax planning is unclear. A firm’s overall tax planning consists of strategies that create either permanent or temporary differences between financial reporting income and taxable income. Because strategies that create a permanent difference resemble an annuity, the NPV of permanent tax planning strategies decreases as the discount rate increases. In contrast, a strategy that creates a temporary difference resembles an interest free loan from the government, because it generates tax savings in the current period that are paid back to the government in future periods. As a result, the NPV of temporary tax planning strategies increases with the discount rate. Because a firm’s overall level of tax avoidance is a combination of permanent and temporary tax planning strategies, the association between the discount rate and firms’ overall level of tax planning is unclear.

  7. 7.

    We acknowledge that not all tax planning strategies produce benefits that scale dollar-for-dollar with pretax income. However, most strategies do produce benefits that increase with pretax income. For example, investing in a municipal bond provides a fixed tax benefit that will not change as the firm’s operating income increases. However, a tax strategy that shifts some portion of earnings into a low tax jurisdiction may scale proportionally with increases in future cash flows. Wilkie (1988) models ETRs as a function of pretax income and tax preferences, and he finds effective tax rates and income are positively correlated. This is consistent with tax preferences not scaling up in perfect proportion with income.

  8. 8.

    Marginal tax rate volatility is also important, because Scholes et al. (2014) argue that taxpayers bear additional costs on the purchase of highly implicitly or explicitly taxes assets if they are not in the appropriate tax clientele. For example, a firm would not accept the lower rates of returns on tax-advantaged municipal bonds, relative to corporate bonds, if the firm has a 0 % marginal tax rate. To the extent that firms bear costs for being in the wrong tax clientele, changes in marginal tax rates can necessitate changes in tax planning.

  9. 9.

    Evidence on accuracy of macroeconomists’ GDP forecasts is mixed (Davies and Lahiri 1995; Wieland and Wolters 2011). To the extent that corporate managers rely on professional macroeconomists’ GDP forecasts, there is no obvious reason why inaccuracy of macroeconomists’ GDP forecasts would bias our results.

  10. 10.

    In cross-sectional analysis, Shevlin et al. (2019) find the positive association between tax avoidance and future economic growth is due to countries with greater government corruption and corporate tax planning.

  11. 11.

    We deflate fees paid for auditor-provided tax services by average total assets to be consistent with the investment literature in finance and economics. In addition, this specification resembles that of Mills et al. (1998), who measure a firms’ total investment in tax planning as a percentage of selling, general, and administrative expenses.

  12. 12.

    Survey evidence finds that tax directors believe they can alter 69.2 (100) percent of tax positions within one year (three to five years) (Hoopes et al. 2012). Kim et al. (2019) also find that firms can close between approximately 70 and 84% of the gap between actual and estimated target ETRs within three years.

  13. 13.

    We take averages of the BEA’s advance estimates of realized quarterly GDP growth.

  14. 14.

    We acknowledge that broader economic events potentially influence our results. In an untabulated analysis, we use an indicator variable to control for the Financial Crisis in 2008 and 2009. In a separate analysis, we use an indicator variable to control for the repatriation tax holiday created by the American Jobs Creation Act in 2004 and 2005. Our inferences remain the same after controlling for both of these periods. We also re-estimate our primary test after removing observations in 2008 and 2009, and our inferences remain the same.

  15. 15.

    Equation 1 includes industry-fixed effects since the dependent variable is a first difference, which removes time-invariant across-firm variation. Our model does not include year-fixed effects, because GDP FORECAST varies only over time. Thus our study extends research on the firm-specific determinants of tax avoidance by exploring a factor, expected economic growth, that influences firms’ tax planning investment over time.

  16. 16.

    We delete observations with missing auditor-provided tax fees, because it is unclear whether these firms do not purchase tax services from their auditors or do not report those services. We acknowledge that this choice could lead to sample selection bias if the purchase of tax services from an external auditor is systematically associated with both the magnitude of auditor-provided tax fees and expected economic growth. To mitigate any selection concerns, we employ the Heckman (1979) two-step correction procedure, whereby we model the decision to purchase auditor-provided tax services in a first-stage regression. Inferences are generally consistent when employing a two-stage approach, and these results can be found in the online appendix.

  17. 17.

    In an untabulated analysis, we re-estimate Equation 1 after including loss firms in our sample. Our inferences remain the same in terms of both economic and statistical significance.

  18. 18.

    Calculated as $181 in tax fees per million dollars of lagged total assets multiplied by $933 million, the average firm size in our sample [e^6.838 sample mean of LOG_ASSETS]. The average firm in our sample spends approximately $405,000 on tax fees per year [e^6.838 * $435 of tax fees per million dollars of lagged total assets, the sample mean of TAX_FEES].

  19. 19.

    To examine the relative importance of GDP FORECAST as a determinant of tax planning, we standardize the coefficients in our levels analysis and compare the magnitude of the coefficient on GDP FORECAST to the absolute magnitude for the control variables. Among the standardized coefficients, GDP FORECAST is the fifth largest coefficient. The top five coefficients (in order) are TREND, LOG_ASSETS, AUDFEES, TBILL 3YR, and GDP FORECAST. This result provides additional evidence that expectations about economic growth are a significant determinant of firms’ investment in tax planning.

  20. 20.

    Our path analysis includes all control variables except for TREND. We exclude TREND to allow our model to converge.

  21. 21.

    For brevity, we do not present the coefficients on the control variables in Equation 1 in Tables 6-7.

  22. 22.

    In an untabulated analysis, we find that EPS GROWTH FORECAST and GDP FORECAST are significantly correlated at 0.047. This result is consistent with research that finds that analysts underreact to macroeconomic news (Hann et al. 2012; Hugon et al. 2016), suggesting that GDP FORECAST likely includes information not contained in EPS GROWTH FORECAST.

  23. 23.

    In an untabulated analysis, we find that firm-specific growth expectations predict tax fees when year fixed effects are included along with firm level control variables. (Macro-level controls are excluded due to year fixed effects.) These results suggest that firm-level growth expectations predict cross-sectional variation in tax planning within a given year, whereas macro-level growth expectations explain variation in tax planning across time.

  24. 24.

    In Table OA5 of the online appendix, we control for lagged Tobin’s Q as an alternative measure of firm-specific growth expectations. We find that the relation between ΔTAX_FEES (TAX_FEES) and GDP FORECAST remains significantly positive (p < 0.01) after controlling for Tobin’s Q.

  25. 25.

    We define CASHETR as cash taxes paid divided by pre-tax income in year t. We define ΔCASHETR as the change in CASHETR from year t-2 to year t, which enables year t-2 to serve as a baseline for a firm’s cash ETR and allows investment in tax planning in year t-1 to manifest in cash ETR outcomes in year t.

  26. 26.

    Publicly available data on tax compliance services is limited. Klassen et al. (2016) proxy for auditor-provided tax compliance services using proprietary IRS data that identifies which party signed the corporate tax return. Although some firms separately disclose the tax compliance and consulting fees paid to their external auditor, the availability of these fee disclosures is extremely sparse in Audit Analytics. For example, our sample is reduced from 13,553 to 772 if we control for tax compliance fees paid to the external audit firm.

  27. 27.

    In our levels specification, we find that the coefficient on GDP FORECAST is significantly negative (significantly positive) when audit fees (non-audit, nontax fees) serves as our dependent variable (both p < 0.05). In addition, we find that the coefficient on GDP FORECAST is significantly larger when the level of tax fees is the dependent variable, compared to when the level of non-audit, nontax fees is the dependent variable (p < 0.01).


  1. Aghion, P., P. Askenazy, N. Berman, G. Cette, L. Eymard, and L. (2012). Credit constraints and the cyclicality of R&D investment: Evidence from France. Journal of the European Economic Association 10 (5): 1001–1024.

    Article  Google Scholar 

  2. Armstrong, C.S., J.L. Blouin, A.D. Jagolinzer, and D.F. Larcker. (2015). Corporate governance, incentives, and tax avoidance. Journal of Accounting and Economics 60 (1): 1–17.

    Article  Google Scholar 

  3. Barlevy, G. (2007). On the cyclicality of research and development. American Economic Review 97 (4): 1131–1164.

    Article  Google Scholar 

  4. Beatty, A., S. Chamberlain, and J. Magliolo. (1995). Managing financial reports of commercial banks: The influence of taxes. Journal of Accounting Research 33 (2): 231–261.

    Article  Google Scholar 

  5. Blouin, J., J. Core, and W. Guay. (2010). Have the tax benefits of debt been overestimated? Journal of Financial Economics 98 (2): 195–213.

    Article  Google Scholar 

  6. Chen, H. (2010). Macroeconomic conditions and the puzzles of credit spreads and capital structure. The Journal of Finance 65 (6): 2171–2212.

    Article  Google Scholar 

  7. Chen, S., X. Chen, Q. Cheng, and T. Shevlin. (2010). Are family firms more tax aggressive than non-family firms? Journal of Financial Economics 95 (1): 41–61.

    Article  Google Scholar 

  8. Cochrane, J.H. (2011). Presidential address: Discount rates. The Journal of Finance 66 (4): 1047–1108.

    Article  Google Scholar 

  9. Davies, A., and K. Lahiri. (1995). A new framework for analyzing survey forecasts using three-dimensional panel data. Journal of Econometrics 68: 205–227.

    Article  Google Scholar 

  10. De Simone, L., K.J. Klassen, and J.K. Seidman. (2017). Unprofitable affiliates and income shifting behavior. The Accounting Review 92 (3): 113–136.

    Article  Google Scholar 

  11. Dyreng, S.D., M. Hanlon, and E.L. Maydew. (2008). Long-run corporate tax avoidance. The Accounting Review 83 (1): 61–82.

    Article  Google Scholar 

  12. Dyreng, S.D., M. Hanlon, E.L. Maydew, and J.R. Thornock. (2017). Changes in corporate effective tax rates over the past 25 years. Journal of Financial Economics 124 (3): 441–463.

    Article  Google Scholar 

  13. Dyreng, S.D., and K.S. Markle. (2016). The effect of financial constraints on income shifting by US multinationals. The Accounting Review 91 (6): 1601–1627.

    Article  Google Scholar 

  14. Edwards, A., C. Schwab, and T. Shevlin. (2016). Financial constraints and cash tax savings. The Accounting Review 91 (3): 859–881.

    Article  Google Scholar 

  15. Erel, I., B. Julio, W. Kim, and M.S. Weisbach. (2011). Macroeconomic conditions and capital raising. The Review of Financial Studies 25 (2): 341–376.

    Article  Google Scholar 

  16. Fama, E.F., and K.R. French. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics 25: 23–49.

    Article  Google Scholar 

  17. Gow, I., G. Ormzabal, and D. Taylor. (2010). Correcting for cross-sectional and time-series dependence in accounting research. The Accounting Review 85 (2): 483–512.

    Article  Google Scholar 

  18. Hackbarth, D., J. Miao, and E. Morellec. (2006). Capital structure, credit risk, and macroeconomic conditions. Journal of Financial Economics 82 (3): 519–550.

    Article  Google Scholar 

  19. Haddad, V., E. Loualiche, and M. Plosser. (2017). Buyout activity: The impact of aggregate discount rates. The Journal of Finance 72 (1): 371–414.

    Article  Google Scholar 

  20. Hadlock, C.J., and J.R. Pierce. (2010). New evidence on measuring financial constraints: Moving beyond the KZ index. Review of Financial Studies 23: 1909–1940.

    Article  Google Scholar 

  21. Hanlon, M., J. Hoopes, and N. Shroff. (2014). The effect of tax authority monitoring and enforcement on financial reporting quality. Journal of the American Taxation Association 36 (2): 137–170.

    Article  Google Scholar 

  22. Hann, R.N., M. Ogneva, and H. Sapriza. (2012). Forecasting the macroeconomy: Analysts versus economists. Available at SSRN 2194179.

  23. Heckman, J.J. (1979). Sample selection bias as a specification error. Econometrica 47 (1): 153–161.

    Article  Google Scholar 

  24. Hoopes, J.L., D. Mescall, and J.A. Pittman. (2012). Do IRS audits deter corporate tax avoidance? The Accounting Review 87 (5): 1603–1639.

    Article  Google Scholar 

  25. Hugon, A., A. Kumar, and A. Lin. (2016). Analysts, macroeconomic news, and the benefits of active in-house economists. The Accounting Review 91 (2): 513–534.

    Article  Google Scholar 

  26. Kim, J., S. McGuire, S. Savoy, and R. Wilson. (2019). How quickly do firms adjust to optimal levels of tax avoidance? Contemporary Accounting Research 36 (3): 1824–1860.

    Article  Google Scholar 

  27. Klassen, K.J., P. Lisowsky, and D. Mescall. (2016). The role of auditors, non-auditors, and internal tax departments in corporate tax aggressiveness. The Accounting Review 91 (1): 179–205.

    Article  Google Scholar 

  28. Konchitchki, Y., and P.N. Patatoukas. (2014). Accounting earnings and gross domestic product. Journal of Accounting and Economics 57: 76–88.

    Article  Google Scholar 

  29. Korajczyk, R.A., and A. Levy. (2003). Capital structure choice: Macroeconomic conditions and financial constraints. Journal of Financial Economics 68 (1): 75–109.

    Article  Google Scholar 

  30. Kubick, T.R., T.C. Omer, and Z. Wiebe. (2019). The effect of voluntary clawback adoptions on corporate tax policy. The Accounting Review 95 (1): 259–285.

    Article  Google Scholar 

  31. Landsman, W.R., E.L. Maydew, and J.R. Thornock. (2012). The information content of annual earnings announcements. Journal of Accounting and Economics 53: 34–54.

    Article  Google Scholar 

  32. Law, K.K., and L.F. Mills. (2015). Taxes and financial constraints: Evidence from linguistic cues. Journal of Accounting Research 53 (4): 777–819.

    Article  Google Scholar 

  33. Lennox, C.S. (2016). Did the PCAOB's restrictions on auditors' tax services improve audit quality? The Accounting Review 91 (5): 1493–1512.

    Article  Google Scholar 

  34. Maydew, E., and D. Shackelford. (2007). The changing role of auditors in corporate tax planning. In Taxing corporate income in the 21st century, ed. A.J. Auerbach, J.R. Hines Jr., and J.B. Slemrod, 307–337. Cambridge University Press.

    Chapter  Google Scholar 

  35. McGuire, S., T. Omer, and D. Wang. (2012). Tax avoidance: Does tax-specific industry expertise make a difference? The Accounting Review 87 (3): 975–1003.

    Article  Google Scholar 

  36. Mills, L., M. Erickson, and E. Maydew. (1998). Investments in tax planning. Journal of the American Taxation Association 20 (1): 1–20.

    Article  Google Scholar 

  37. Petersen, M. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies 22 (1): 435–481.

    Article  Google Scholar 

  38. Roychowdhury, S., N. Shroff, and R.S. Verdi. (2019). The effects of financial reporting and disclosure on corporate investment: A review. Journal of Accounting and Economics 68 (2–3).

  39. Scholes, M., P. Wilson, and M. Wolfson. (1990). Tax planning, regulatory capital planning, and financial reporting strategy for commercial banks. Review of Financial Studies 3 (4): 625–650.

    Article  Google Scholar 

  40. Scholes, M., M. Wolfson, M. Erickson, M. Hanlon, E. Maydew, and T. Shevlin. (2014). Taxes and business strategy: A planning approach. In 5th edition: Boston. Prentice Hall.

    Google Scholar 

  41. Shevlin, T., L. Shivakumar, and O. Urcan. (2019). Macroeconomic effects of corporate tax policy. Journal of Accounting and Economics 68 (1): 1–22.

    Article  Google Scholar 

  42. Shroff, N. (2017). Corporate investment and changes in GAAP. Review of Accounting Studies 22 (1): 1–63.

    Article  Google Scholar 

  43. Whited, T.M., and G. Wu. (2006). Financial constraints risk. The Review of Financial Studies 19 (2): 531–559.

    Article  Google Scholar 

  44. Wieland, V., and M.H. Wolters. (2011). The diversity of forecasts from macroeconomic models of the US economy. Economic Theory 47: 247–292.

    Article  Google Scholar 

  45. Wilde, J.H., and R.J. Wilson. (2018). Perspectives on corporate tax avoidance: Observations from the past decade. Journal of the American Taxation Association 40 (2): 63–81.

    Article  Google Scholar 

  46. Wilkie, J.W. (1988). Corporate average effective tax rates and inferences about relative tax preferences. Journal of the American Taxation Association 10 (1): 75–88.

    Google Scholar 

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We appreciate helpful comments from Brad Badertscher, Erik Beardsley, Jenny Brown, Andy Call, John Campbell, Ciao-Wei Chen, Ted Christensen, William Ciconte, Paul Demere, Michael Donohoe, Katharine Drake, Matt Ege, Scott Emett, Florian Eugster, Fabio Gaertner, Ryan Huston, Michelle Hutchens, Dave Kenchington, Andrew Kitto, Allison Koester, Stacie Laplante, Dan Lynch, Pete Lisowsky, Lillian Mills, Henrik Nilsson, Tom Omer, Michael Overesch (discussant), Terry Shevlin, Erin Towery, Milda Tylaite, Oktay Urcan, and workshop participants at the Arizona State University, the 8th EIASM Conference on Current Research in Taxation, the Stockholm School of Economics, the University of Georgia, the University of Illinois at Chicago, the University of Illinois at Urbana-Champaign, the University of Notre Dame, the University of Wisconsin, and the 2017 UBCOW conference. We appreciate excellent research assistance from Young Hoon Kim. McGuire acknowledges funding from Mays Business School and the Ernst & Young Professorship.

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Table 8 Variable Definitions

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Kim, J., McGuire, S., Savoy, S. et al. Expected economic growth and investment in corporate tax planning. Rev Account Stud (2021).

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  • Macroeconomic growth
  • Tax planning
  • GDP Forecast