Who Profits from Patents?

By Heidi Williams

Posted on August 2, 2019


Image: Heidi WilliamsRecently picked by The Economist as one of the decade’s eight best young economists (see “MIT’s Heidi Williams Named as One of the Decade’s Eight Best Young Economists”), Heidi Williams is particularly interested in the causes and consequences of innovation. Here, she presents a recent paper in which she investigates how patent allowances affect firm performance and worker pay.


In standard competitive models of the labor market, we think of firms as being price takers. That is, workers are paid a wage that is a function of their skill level, and firms take market-level prices of skill as given. However, there is growing empirical evidence that firms contribute substantially to wage inequality across identically skilled workers. Put simply, how much you earn seems to depend in part on the firm at which you work (as opposed to depending solely on your skills).


One natural explanation is that perhaps firm performance matters for worker pay, in the sense that workers employed at firms that are doing better might earn more. However, testing for causal evidence on whether firm performance matters for worker pay has been challenging for two reasons.


First, from an empirical perspective, we would ideally isolate clear shocks to firm performance, and trace through how those shocks propagate into worker pay. Although that thought experiment is simple enough to describe, nearly all past attempts to analyze this question have instead analyzed observed fluctuations in firm performance over time, without making an attempt to understand their source.


Second, in the small number of cases where researchers have successfully identified clear shocks researchers have lacked the type of detailed data needed to cleanly analyze wage responses among incumbent workers. That type of data is critical because the composition of workers employed at a firm may change in response to firm-level shocks. To be concrete, when a firm discovers a new invention it may hire more skilled workers to develop and market that invention. Average wages at the firm would then go up, but that could solely reflect a compositional change in the average skill level of workers employed at the firm, even if no rents from the innovation were being passed through to worker wages.


This piece summarizes a recent academic paper that I wrote with Patrick Kline (UC-Berkeley), Neviana Petkova (US Treasury) and Owen Zidar (Princeton), in which we investigate how patent allowances affect firm performance and worker pay using a new linkage of US patent applications to US Treasury business and worker tax records.


Empirical Approach: Comparing Accepted and Rejected Patent Applications


Patents provide firms with a temporary period of market power, during which they can charge supra-competitive prices and earn rents which allow them to recoup the fixed costs of their research investments. Our idea in this paper is to try to isolate quasi-random variation in which firms receive patents, and to leverage that variation in order to look at how patent-induced rents propagate into worker wages.


Specifically, consider the following thought experiment. Take two patent applications submitted by two separate firms to the US Patent and Trademark Office (USPTO) in the same year, covering the same general type of technology (in USPTO parlance, the two patent applications are sufficiently similar that they will be reviewed in the same Art Unit, or specialized group of USPTO examiners). One of the two applications is initially allowed (that is, granted on the first round of review) whereas the second application is initially rejected. We can, under some assumptions, use the initially rejected firm as a comparison for what would have happened to firm and worker outcomes at the initially allowed firm in the absence of the patent being granted.


Of course, a priori, it isn’t clear that this thought experiment offers a clean comparison: it may be that better patent applications are more likely to be granted patents, in which case initially rejected firms might not be a good comparison for initially accepted firms. My research with Bhaven Sampat (‘How Do Patents Affect Follow-on Innovation? Evidence from the Human Genome’, American Economic Review, 2019 ) has documented a potentially large idiosyncratic component to patent grants - namely, variation across patent examiners in their likelihood of granting patents to observably similar applications. More directly relevant to our study, we can assess empirically whether initially accepted and initially rejected firms look similar in terms of the levels and trends in their outcomes in the years prior to patent applications being submitted, and we find that they do, lending credibility to this empirical approach.




Our empirical analysis relies on a new linkage of two datasets: the census of published patent applications submitted to the USPTO between roughly 2001-2011, and the universe of US Treasury business tax filings and worker earnings histories drawn from W2 and 1099 tax filings.


In the US, we are able to observe both accepted and “rejected” patent applications filed since 29 November 2000 under the American Inventors Protection Act. This data is what enables us to analyze the thought experiment described above, because we observe all firms filing applications, including those firms granted patents as well as those firms not granted patents. In practice, constructing this data on US patent application filings is complicated, as it requires stitching together several different USPTO administrative datasets. But in the end, we are able to combine several different public-use files from the USPTO to construct a comprehensive dataset on applications filed over this period, including information on the timing and content of the USPTO’s initial decisions on each application, which is what we need to implement our empirical analysis.


We link the firms applying for patents (the so-called patent assignees) with firm names in the US Treasury business tax filings (form 1120 for C corporations, 1120S for S corporations, and form 1065 for partnerships). The business tax filings data offer a high-quality set of firm-level variables, from which we are able to construct multiple measures of firm performance. We then link these business tax filings with worker-level W2 and 1099 filings to measure the number of employees and independent contractors, as well as various worker compensation measures. The combination of the business and worker tax filings provide a window into compensation outcomes for many different types of workers, including firm officers and owners, who prevail at the top of the income distribution.


Identifying Valuable Patents


It is well known that most patents generate little ex post value to the firm. In our context, this means that considering the full universe of patent grants would provide very little insight into the relationship between firm-level outcomes and worker-level earnings, as most patent grants generate no shifts in firm-level outcomes. With that concern in mind, we designed our analysis to focus - in two ways - on a subsample of valuable patents which we expect, ex ante, to induce meaningful shifts in firm outcomes at the time they are allowed.


First, following the work of Farre-Mensa, Hegde, and Ljungqvist (“What Is a Patent Worth? Evidence from the US Patent ‘Lottery’,” 2017, NBER working paper no. 23268), we restrict our analysis to firms applying for a patent for the first time, for which patent decisions are likely to be most consequential.


Second, among this sample of first-time applicants, we build on the analysis of Kogan et al. (‘Technological Innovation, Resource Allocation, and Growth’, Quarterly Journal of Economics, 2017) to identify a subsample of ex ante valuable patents. Kogan’s team use event studies to estimate the excess stock-market return realized on the grant date of US patents assigned to publicly traded firms. We develop a methodology for extrapolating Kogan’s patent value estimates to both the non-publicly traded firms in our sample and the firms whose patent applications are never granted. Specifically, we use characteristics of firms and their patent applications that are fixed at the time of application as the basis for extrapolating patent values.


Figure 1 documents that these predicted value estimates are strong predictors of treatment effect heterogeneity in our sample. Each point in Figure 1 quantifies our treatment effect (using the accepted/ rejected variation described above) of patents of a given value (as measured on the x-axis) on two different outcomes on the y-axis: surplus per worker (one measure of firm performance) and wage bill per worker (one measure of worker compensation).

Image: Figure 1: Predicting Value

As expected, and comfortingly from the perspective of validating our empirical approach, low-value patents induce essentially no changes in either firm or worker outcomes. In contrast, patents with ex ante predicted values above roughly the 80th percentile of the predicted value distribution (denoted by the red vertical line in Figure 1) have larger, statistically significant treatment effects on both firm and worker outcomes. Given the pattern observed in Figure 1, our empirical analysis pools the bottom four quintiles together and focuses on estimating the impacts of patents in the top quintile of ex ante predicted patent value.


Figures 2 and 3 document event study estimates for these same two outcome variables: surplus per worker (Figure 2) and wage bill per worker (Figure 3). Comfortingly from the perspective of validating our empirical approach, firms whose patent applications are initially allowed exhibit similar trends in firm and worker outcomes to firms whose patent applications are initially rejected in years prior to the initial decision. However, surplus per worker rises differentially for firms whose high-value patent applications are initially allowed after the initial decision date, and remains elevated afterwards (Figure 2). Similar, although more muted, trends are observed for wage bill per worker (Figure 3). The ratio of these two impacts is roughly one-third. That ratio can be interpreted as implying that workers capture roughly 30 cents of every dollar of patent-induced surplus in the form of higher earnings.

Image: Figures 2 and 3: Patent Power

Our paper also documents evidence that, beyond simply raising average earnings at these firms, patents exacerbate within-firm inequality on a variety of margins. We find that earnings impacts are concentrated among employees in the top quartile of the within-firm earnings distribution and among employees listed on firm tax returns as “firm officers”. Similarly, the earnings of owner-operators rise more than the earnings of other employees. Earnings of male employees rise strongly in response to a patent allowance, while earnings of female employees are less responsive. Inventor earnings (defined as the earnings of employees ever listed as inventors on a patent application) are more responsive than are the earnings of non-inventors, although we find substantial wage changes even for non-inventors.




Our paper interprets this set of empirical findings in the context of a simple economic model in which incumbent workers - that is, workers who were present at the firm at the time the patent application was filed - are imperfectly substitutable with new hires. We think this economic model appropriately captures the features of the small, innovative firms we study: the innovative work conducted at these firms is necessarily specialized and proprietary in nature, likely making it costly to replace incumbent employees with new hires. In this model, firms choose to share economic rents with incumbent workers to increase the odds of retaining them. We document empirical results consistent with that prediction: namely, worker retention rises most strongly among groups of workers with the largest earnings increases.


More broadly, our empirical findings provide some of the first evidence that truly idiosyncratic variability in firm performance is an important causal determinant of worker pay. Given that firm productivity is highly variable and persistent, it is plausible that firm-specific shocks contribute substantially to permanent earnings inequality across identically skilled workers.



The preceding is republished on TAP with permission by its author, Professor Heidi Williams, and by the Toulouse Network for Information Technology (TNIT). “Who Profits from Patents?” was originally published in TNIT’s June 2019 newsletter.