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Does economic policy uncertainty matter for financial reporting quality? Evidence from the United States

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Abstract

We examine the effect of economic policy uncertainty (EPU) on the financial reporting quality of US firms over 1999–2015. We use accruals-based earnings management as a proxy for financial reporting quality and the index of Baker et al. (Quart J Econ 131:1539–1636, 2016) as an EPU measure to show that they exhibit a positive and significant association. We also find a causal effect by employing three political polarization instruments for EPU. In a cross-sectional analysis, we further show that the positive relationship between EPU and earnings management strengthens for firms operating in politically sensitive industries, for firms in more financial distress, and during recessionary periods. We also provide evidence that increased financial constraints facilitate the positive relationship between EPU and earnings management. These findings are robust to the use of alternative measures of economic policy uncertainty and when we employ real earnings management as a dependent variable. These results indicate that managers aim to provide outsiders with an improved financial position of the company when EPU is high. Our findings suggest that investors, analysts, creditors, and regulators should be wary of firms’ financial reporting quality in periods of high economic policy uncertainty.

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Notes

  1. In more detail, Baker et al. (2016) show that economic policy uncertainty reacts more strongly than financial uncertainty to incidents that involve major policy concerns such as political battles over government spending and taxation.

  2. We recognize that economic policy uncertainty and financial uncertainty measures, such as the option implied volatility of stocks, exhibit correlation. However, as Baker et al. (2016) argue, economic policy uncertainty and financial uncertainty display also a distinct variation. For example, Baker et al. (2016) show that economic policy uncertainty reflects more strongly than financial uncertainty to periods of uncertainty regarding significant economic policies such as government spending and taxation. Several other studies provide empirical evidence that although economic policy uncertainty and financial uncertainty are related, they also display distinct traits (Pastor and Veronesi 2017; Tiwari et al. 2019; Bialkowski et al. 2021). We also address the correlation between economic policy uncertainty and financial uncertainty in our empirical tests regarding endogeneity in Sect. 4.3 of the paper. We thank an anonymous Referee for motivating us to carefully distinguish economic policy uncertainty from financial uncertainty theoretically (i.e., in terms of the hypotheses development) and empirically.

  3. For example, the rising uncertainty about an important economic policy, which is the trade policy regarding China, during President’s Trump administration. The eventual increase in tariffs on imported goods from China to the US have led several US firms with production facilities in China to incur significant adjustment and compliance costs. Such costs comprise the costs of relocation of production from China to other countries, revamping supply chains, hire and train new employees in the new locations and investment in new machinery and equipment. As an illustration, Associated Press (2019) reports that Xcel Brands, a US-based clothing company, has moved production from China to Vietnam, Cambodia, Bangladesh and Canada in response to the increasing trade policy uncertainty and trade barriers between US and China. CNBC (2019) reports that several others US companies made similar moves as Xcel Brands incurring significant adjustment costs.

  4. There is anecdotal evidence on the prompt response of managers to uncertainty around future economic policies. For example, in response to the result of the 2016 UK “Brexit” referendum, the CEO of JP Morgan Jamie Dimon suggests that ‘If the EU imposes new conditions on Britain … the worst-case scenario is we would have to move some thousands of employees to other branches in the euro zone’ (Reuters 2016). This shows that managers respond promptly and look at the most recent information available to devise their strategies to adapt to the rising uncertainty. As another example, the tariffs on China imposed by President Trump’s administration in 2018 has increased economic policy uncertainty in the US and the business world. Many managers in the US have reacted to these announcements quickly, as they aim to decrease any negative effects on the profitability of firms. In that respect, the CEO of Primex Family of Companies, Mr Paul Shekoski examines the option of relocating all his production activities in Mexico to avoid the increased costs due to tariffs (Fortune 2019). Such anecdotal evidence supports the use of contemporaneous economic policy uncertainty measures in academic research about the effects of such uncertainty on firm outcomes.

  5. We thank an anonymous Referee for pointing out these issues and motivating us to perform additional test to address these concerns.

  6. During the period of the study (1999–2015), four US presidential elections have occurred (i.e., in 2000, 2004, 2008, and 2012).

  7. We estimate Eq. (6) using data with just the time dimension (i.e. the 17 observations that represent the 17 years of the study). This is because the variables that we use in Eq. (6) are macroeconomic variables. Results are similar when we estimate Eq. (6) with the firm level dataset (i.e., by assigning the macroeconomic variables at each firm-year data point).

  8. In the change regression (model 3 of Panel A in Table 6) we do not include firm fixed effects as these are wiped out by construction in such a regression. Ho et al. (2018) posit that the change regression is also a good robustness test for the firm fixed effects regression because the former is free from bias stemming from firm-level omitted variables that are constant over time. In the other specifications of Panel A in Table 6 (models 1 and 2) we include firm fixed effects. We report the results from the fixed effects specifications in order to economize space, but the results are similar when we do not use firm fixed effects.

  9. The 2SLS-IV estimation results are similar when we do not use firm fixed effects.

  10. As an additional test to address endogeneity concerns, we use the two-step system generalized method of moments (GMM) estimator. The analysis using this estimator is available in the internet appendix and the results are available in Table IA.1 of the internet appendix. The results continue to lend support to hypothesis H1.

  11. Higher values of the KZ index imply increased financial constraints. See Table 1 for the formula we use to calculate the KZ index.

  12. The Sobel (1982) test has to be significant (i.e., p-value < 0.10) to reject the null of no channel effect.

  13. \(\Delta CA_{i,t}\) is the change of current assets from the to the previous year (t-1) to current year (t), \(\Delta CL_{i,t}\) is the change of current liabilities from the previous year (t-1) and the current year (t), \(\Delta Cash_{i,t}\) is the change of cash between the previous year (t-1) and the current year (t). \(\Delta STDEBT_{i,t}\) is the change in debt in current liabilities from the previous year (t-1) to the current year (t).

  14. \(CFO_{i,t} = NIBE_{i,t} - TA_{i,t}\), where \(NIBE_{i,t}\) is firm’s net income before extraordinary items. \(TA_{i,t} = \Delta CA_{i,t} - \Delta CL_{i,t} - \Delta Cash_{i,t} + \Delta STDEBT_{i,t} - DEPN_{i,t}\). and~stands~for~firm's~total~accruals~in~the~current~year (t) \(DEPN_{i,t}\) is the firm’s value of depreciation expenses in the current year (t).

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Authors and Affiliations

  1. Finance Centre, Essex Business School, University of Essex, Colchester, UK

    Theodora Bermpei

  2. Department of Banking and Finance, Southampton Business School, University of Southampton, Southampton, UK

    Antonios Nikolaos Kalyvas

  3. Department of Management, Birkbeck University of London, London, UK

    Lorenzo Neri

  4. Department of Accounting and Finance, Greenwich Business School, University of Greenwich, London, UK

    Antonella Russo

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  1. Theodora Bermpei
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Correspondence to Lorenzo Neri.

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Bermpei, T., Kalyvas, A.N., Neri, L. et al. Does economic policy uncertainty matter for financial reporting quality? Evidence from the United States. Rev Quant Finan Acc 58, 795–845 (2022). https://doi.org/10.1007/s11156-021-01010-2

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