Because government-funded R&D may increase the earnings of a firm, firms may beat earnings forecasts more often. To examine this conjecture, we perform a logit regression analysis.
We construct a dummy variable that equals one if the firm beats analyst earnings forecasts (i.e., actual EPS is higher than forecasted EPS), and zero otherwise. We use the same control variables as in Table 2. Table 8 shows the regression results. The coefficient on Government-funded R&D ratio is 0.0059 (t-stat = 36.50) in Model 1 without extra controls and 0.0060 (t-stat = 27.68) in Model 2 with extra controls. Both coefficients are highly significant at the 1% level. The results suggest that firms with government-funded R&D are more likely to beat analyst earnings forecasts. This could be because analysts are too conservative and therefore do not fully incorporate the impact of government-funded R&D into their earnings forecasts.
Insert Table 8 around here
Government Funded R&D and Innovation Performance
The premise of our certification hypothesis is that a government has an information advantage and in-house experts who can identify high-quality R&D firms for R&D grant or contract awards. If this is the case, firms receiving government R&D grants or contracts should have a high degree of innovation efficiency and performance. We use eight innovation performance measures as the dependent variable. Following Hirshleifer, Hsu, and Li (2013), Innovation efficiency is the logarithm of one plus the number of patents divided by R&D expenditures. Number of patents is the logarithm of one plus the number of patents that a firm has applied for. Patent citations is the logarithm of one plus the number of truncation-adjusted citations that an awarded patent receives. Patent generality is the average of patent-level generality, where Patent-level generality is the sum of squared ratios of forward citations divided by the number of total forward citations in the same International Patent Classification (IPC) code. Patent originality is measured using a similar formula but replacing forward citations by backward references. Cumulative number of patents is the logarithm of one plus the aggregate number of patents a firm was awarded in the past three years. Cumulative patent citations is the logarithm of one plus the aggregate patent citations a firm has received in the past three years.
Cumulative relative patent citations is the logarithm of one plus cumulative patent citations divided by the median of citations per patent in the same IPC classification. These are popular measures of innovation activities in the innovation literature (e.g., Hall, Jaffe, and Trajtenberg, 2001, 2005; Lerner, Sorensen, and Strömberg, 2011; Aghion, van Reenen, and Zingales, 2013;
Bena and Li, 2014; Hsu, Tian, and Xu, 2014; Lin and Wang, 2016).
Table 9 reports the regression results of innovation performance in eight separate panels. In most cases, innovation performance measures show a positive relation between
government-funded R&D and innovation performance, except for Patent generality. These results are consistent with past evidence. Also note that Innovation efficiency is positively related to government-funded R&D, which implies that government-funded R&D enhances the successful rate of a firm’s risky R&D projects.
Insert Table 9 around here
Value Relevance and Firm Performance
We noted earlier that ASU No. 2015-340, Government Assistance (Topic 832), calls for firms to disclose information on financial assistance from governments, such as government grants and low-interest loans. The implication is that the FASB sees government-funded R&D as value relevant. We therefore examine how government-funded R&D influences value relevance.
Specifically, we examine the impact of disclosing information about public R&D and the impact of public R&D on stock returns. We follow Lev and Sougiannis (1996) on defining value relevance as the holding-period returns from nine months before to three months after the fiscal year t end. We then regress the value relevance on government-funded R&D ratio. Untabulated results show that government-funded R&D embedded in revenue or cost reduction information helps improve equity value. Our results in part support Chen et al. (2020), who suggest a positive relation between stock returns and state-level public R&D spending.23
Furthermore, we revisit the effect of public-funded R&D on firm performance. While prior
23 In a further test, we examine the effect of government-funded R&D on the cost of equity capital, which also reflects the degree of information uncertainty (Lara, Osma, and Penalva, 2011). It is plausible that reduced forecast errors due to government-funded R&D could help a firm reduce the cost of equity capital. To explore this possibility, we calculate the implied cost of equity capital using the residual income model of Feltham and Ohlson (1995). We use a composite measure of the cost of equity capital that is the average of four individual cost of capital estimates in Claus and Thomas (2001), Gebhardt, Lee, and Swaminathan (2001), Gode and Mohanram (2003), and Easton (2004). This average approach has been used extensively in recent papers (e.g., Cao, Myers, Myers, and Omer, 2015;
Goh, Lee, Lim, and Shevlin, 2016). We then regress the average cost of capital on government-funded R&D ratio.
The results show that the coefficient on Government-funded R&D ratio is around 0.7, which is significant at the 5% level. The results are generally consistent with the certification hypothesis.
studies have mainly used non-U.S. or industry-specific data to investigate this issue (e.g., Jacob and Lefgren, 2011; Azoulay, Zivin, Li, and Sampat, 2018), we re-examine this effect of public R&D by U.S. listed firms that have at least once disclosed information regarding government research grants or R&D contracts. We measure firm performance by return-on-assets (ROA) and Tobin’s q. Our untabulated results confirm findings in the literature that firms with more government-funded R&D improve their firm performance using firm-level data.
VI. CONCLUSION
Our examination of the relationship between government-funded R&D and analyst forecast accuracy reveals that firms with more government-funded R&D are associated with lower analyst forecast errors, even after we control for disclosure quality measures. This result is consistent with the certification hypothesis, which posits that research grants and contracts from government could convey a certification effect to firms, and that certification embedded in government-funded R&D reduces forecast errors.
We take advantage of a quasi-natural experiment of changes in influential congressional committee chairmanships to address potential endogeneity concerns. We find that firms in the state whose congressperson initially assumes the chair of an influential committee have lower forecast errors than firms in other states. We also perform two-stage regression analysis using the instrumental variable of state-level government spending, and find that our results continue to hold.
We conduct channel tests in an attempt to support the certification hypothesis. We find as expected that government-funded R&D on forecast errors has a more pronounced effect when firms are established government R&D grantees or politically connected. The same is true for
firms with greater information uncertainty and asymmetry (i.e., greater analyst forecast dispersion, higher earnings volatility, or higher bid-ask spread). In an additional test, we further uncover evidence that firms with more government-funded R&D tend to beat analyst earnings forecasts. Finally, we find that government-funded R&D is positively related to better innovation performance.
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Appendix
Table A1 Examples of firms that treat government-funded R&D as revenue
1. Aduro Biotech, Inc.
Collaboration and license revenue $71,689 $13,038 $ —
Grant revenue 1,290 351 828
Total revenue $72,979 $13,389 $828
Revenue Recognition
We have historically generated revenue through government grants and, beginning in 2014, from funds received under research and license arrangements. Government grants provide funding for certain types of expenditures in connection with research and development activities over a contractually defined period. Revenue related to government grants is recognized in the period during which the related costs are incurred and the related services are rendered, provided that the applicable performance obligations under the government grants have been met. We intend to continue to evaluate pursuing additional government grant opportunities on a case-by-case basis.
2. Universal Display Corporation
Technology development and support revenue
Technology development and support revenue were as follows for the years ended December 31, 2015 and 2014 (amounts in thousands):
Year Ended
December 31 (Decrease)
2015 2014 $ %
Technology development and support revenue $207 $954 $(747) (78)%
Technology development and support revenue is revenue earned from government contracts, development and technology evaluation agreements and commercialization assistance fees, which includes reimbursements by the U.S. government for all or a portion of the research and development expenses we incur related to our government contracts. Technology development and support revenue for the year ended December 31, 2015, decreased by $0.7 million compared to the year ended December 31, 2014. The decrease was primarily related to the smaller number of government contracts. We do not anticipate this to be a material revenue stream in the future.
Table A2 Examples of firms that treat government-funded R&D as R&D reduction
1. Amtech Systems, Inc.
Research, Development and Engineering
Research, development and engineering (“RD&E”) expenses consist of the cost of employees, consultants and contractors who design, engineer and develop new products and processes as well as materials and supplies used in producing prototypes. We receive reimbursements through governmental research and development grants which are netted against these expenses when certain conditions have been met.
Years Ended September 30
2015 2014 Inc (Dec) %
(dollars in thousands)
Research, development and engineering $13,214 $10,863 $2,351 22%
Grants earned (6,296) (4,572) (1,724) 38%
Net research and development and engineering $6,918 $6,291 $627 10%
RD&E expense, net of grants earned, for the fiscal year ended September 30, 2015, increased $0.6 million compared to fiscal 2014. Gross RD&E spending increased due primarily to the acquisition of BTU and SoLayTec.
Increased RD&E spending was partially offset by increased recognition of grants earned. We receive reimbursements through governmental research and development grants which are netted against these expenses.
2. Medicines Co
Research and Development
The Company performs research and development for US government agencies under a cost-reimbursable contract in which the Company is reimbursed for direct costs incurred plus allowable indirect costs. The Company recognizes the reimbursements under research contracts when a contract has been executed, the contract price is fixed and determinable, delivery of services or products has occurred and collection of the contract price is reasonably assured. The reimbursements are classified as an offset to research and development expenses. Payments received in advance of work performed are deferred. The Company recorded approximately $22.5 million and $9.5 million of reimbursements by the government as a reduction of research and development expenses for the years ended December 31, 2015, and December 31, 2014, respectively.
Table A3 Types of government-funded R&D
This table describes government-funded R&D in terms of R&D grants, R&D contracts, and unknown type. Only firm-years that show receipts of positive government-funded R&D in 10-K report are included.
Types of government funded R&D N Mean Std Dev p5 p25 Median p75 p95
R&D grants 641 49.7 219.1 0.0 0.3 1.4 5.5 185.0
R&D contracts 943 336.2 1,300.7 0.4 3.3 14.5 99.6 1,601.8
Unknown 208 569.0 2,186.5 0.2 1.3 5.0 44.5 2,278.8
Table 1 Summary statistics and correlation coefficient matrix
This table presents summary statistics (Panel A) and a correlation coefficient matrix (Panel B). Government-funded R&D is the dollar amount of R&D funded by governments (in millions). Government-funded R&D ratio is government-funded R&D scaled by book assets. Size is market value of common equity (in
This table presents summary statistics (Panel A) and a correlation coefficient matrix (Panel B). Government-funded R&D is the dollar amount of R&D funded by governments (in millions). Government-funded R&D ratio is government-funded R&D scaled by book assets. Size is market value of common equity (in