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5.2. Adjusting ROE for effects of R&D accounting We report rates of return adjusted for capitalization and amortization of R&D investments in Table 4. Again, to obtain mean values, weights are set to the share of book equity in the total equity of pharmaceutical firms in each country-year. ROE of pharmaceutical firms is adjusted for the effects of R&D accounting using three techniques: (1) Linear amortization – R&D expenditure is capitalized and amortized on a straightline basis over 10 years; (2) Declining balance – R&D expenditure is capitalized and amortized over 10 years using declining balance amortization; (3) Empirical rates – R&D expenditure is capitalized and amortized over 10 years using empirically determined amortization rates.
The empirical rate of amortization was obtained by estimating equation (7) and inserting the estimated coefficients into equation (8). We find that the most recent three years have the strongest impact on current year’s operating income with estimated regression coefficients equal 1.500, 0.849, and 0.526 for year t–1, t–2, and t–3, respectively. The coefficients are significantly different from zero at the conventional level using robust standard errors clustered at firm (p 0.01). The coefficients on other past R&D outlays range from 0.047 to 0.356. We estimate that on average $1 spent on R&D generates $3.88 in operating income over the next 10 years. Due to data availability, we report results using this approach only for our U.S. sample. Rather than assuming how the benefits from R&D accrue, this approach aims to match R&D outlays to future benefits they help generate using observed relationship between R&D outlays and future benefits.
To illustrate the use of the approach, we estimate that in the U.S. the amortization rate on t–1 and t–2 R&D investment is 1.500/3.883 = 38.6% and 0.849/3.883 = 21.9%, respectively.
Looking at the U.S. sample in Table 4, we find that adjusting for accounting distortions leads to lower ROE regardless of the approach used to adjust ROE. We find that over all methods adjusted ROE equals 14.1%, which is about 6 p.p. lower than reported ROE of 19.8%.
This decrease is economically and statistically pronounced (t-stat. 18.44). Similar, the difference between ROE of pharmaceutical firms and ROE of firms from other industries declines from 8.7 p.p. to 2.9 p.p. after adjusting for accounting distortions caused by immediate R&D expensing.
Thus, ROE of U.S. pharmaceutical and non-pharmaceutical firms converge after eliminating accounting distortions. Our international sample provides further support for this conjecture.
Particularly, we find that the difference in ROE declines from –4.9 p.p. to –2.0 p.p. after adjusting ROE of pharmaceutical firms for accounting distortions caused by immediate R&D expensing.
5.3. ROE and regulatory activity Our previous tests show that U.S. firms’ ROE is overstated. Do regulators base their laws on this overstated ROE? Table 5 tests this prediction. We find that despite the low number of data points, our models fit the data well and explain up to 50% of variation in regulatory outcomes. Supporting hypothesis 3, Panel A reports that higher profitability levels lead to greater restrictions (coef. 0.795; t-stat. 3.54) and greater scope of regulation (coef. 0.385; t-stat. 2.53) in the pharmaceutical industry. We also find that the ruling party affects restrictiveness of issued regulations, but not their scope. As a robustness test we control for lagged R&D investments.
However, we do not find that R&D investments affect regulation. Importantly, controlling for R&D intensity does not affect our inferences in respect to our main test variables. To assess the economic significance of these results, we reestimate models (9) and (10) after substituting raw changes in the number of words and restrictions for the log changes of these variables as our dependent variable. Untabulated results reveal that a 1 p.p. increase in ROE leads to an increase in the law text of 74,000 words and 483 restrictions per year.
We next test hypothesis 4 and examine whether regulators fixate on earnings and ignore accounting bias. To provide some preliminary support for hypothesis 4, we run a regression of regulatory changes on one of the two ROE measures: reported ROE and ROE adjusted using empirical amortization rates as above (results are not tabulated). Looking at the explanatory power of two regressions will reveal which earnings measure is more relevant for the regulators’ decision-making. Despite high correlation between the two performance measures (0.54), we find that reported ROE explains about 9 p.p. more of the variation in the restrictiveness of issued laws (35% vs. 26%). This evidence is in line with hypothesis 4. While reported ROE better explains changes in the scope of regulation than adjusted ROE, the difference in adjusted R2s is economically small (1 p.p.).
To provide a formal test of hypothesis 4, we next decompose reported ROE into adjusted ROE (not affected by accounting distortions) and the component of ROE that represents accounting bias. This analysis is reported in Panel B of Table 5. Functional fixation on aggregate earnings predicts that regulators attach similar weights to adjusted ROE and the bias component.
That is, they do not distinguish between the two components. We find that the magnitude of the accounting bias predicts the number of issued restrictions (coef. 0.671; t-stat. 1.83). Critically, we find that the coefficient on the accounting-bias component of ROE (0.671) is similar to the coefficient on adjusted ROE (0.931) and is similar to the coefficient of reported ROE (0.795).
The F-test reported at the bottom of Panel B shows that regulators attach similar weights to the true and biased ROE in their decoction about the amount and restrictiveness of newly issued laws (F-stat. 0.79 and 0.21, respectively). These results support hypothesis 4 and suggest that regulators fixate on aggregate earnings and do not adjust for the accounting bias.
6. Discussion and concluding remarks Overall, we find that pharmaceutical firms report higher ROE than firms from other industries in the U.S. but not in our international sample. Consistent with the effects of R&D accounting on reported ROE, we find that pharmaceutical firms report relatively lower ROE during economic upturns, and relatively higher ROE when the economy contracts. We also find that ROE differences are significantly related to the higher R&D intensity of pharmaceutical firms. While higher R&D intensity increases the ROE of pharmaceutical firms in the U.S., international R&D-intensive pharmaceutical firms report lower ROE. This result can be explained by the composition of our international sample that includes less mature firms compared to the U.S. Young firms have high R&D outlays relative to sales, which depresses their reported ROE. However, the difference between U.S. and non-U.S. samples may be also due to the difference in accounting for R&D in the U.S. relative to other countries. While U.S.
GAAP prohibits capitalization of R&D outlays, accounting standards in other countries allow or even require capitalization of some R&D outlays. For example, under IFRS non-pharmaceutical firms can capitalize development costs, and the implementation of IFRS requirements also leads to some development costs capitalized on the balances of pharmaceutical firms.
When we adjust ROE for accounting distortions we observe consistently lower ROE in all three different adjustment approaches used. After adjusting for accounting distortions, ROE of pharmaceutical firms is generally comparable in magnitude to the ROE reported by firms from other industries. These results tentatively suggest that high profitability of pharmaceutical firms may be at least partly a kind of “optical illusion” created by the expensing of R&D investments.
Our final set of tests reveals that high profitability of pharmaceutical firms leads to greater scope and restrictiveness of regulation. Furthermore, similar to other stakeholders, pharmaceutical regulators focus on reported profitability and do not adjust for an upward bias caused by R&D accounting.
One policy implication of our study is that price regulation or rate of return regulation in the pharmaceutical market should be reviewed and applied with caution when it is solely motivated by the allegedly high profitability of the industry. This is especially true since such a policy also impedes R&D investments and innovation in the long run because profits serve as a major source of R&D investments (Civan and Maloney, 2009; Grabowski and Vernon, 2000;
Mahlich and Roediger-Schluga, 2006; Scherer, 2001) and signal to pharmaceutical firms to assess which products provide consumers the highest value. If profits accurately reflect that value, they will induce the pharmaceutical industry to invest in R&D at the optimal level. A regulatory regime which deviates from this optimality condition is likely to distort incentives to invest in R&D, which might either induce firms to over- or underinvest in R&D. While overinvestment will destroy shareholder value (Saad and Zantout, 2014), underinvestment is more likely to have far reaching economic costs induced by a future absence of new drugs and consecutive lost life years (Abbott and Vernon, 2007; Lichtenberg, 2007).
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