As described in the article “The Choice between Formal and Informal Intellectual Property: A Review“, published in the Journal of Economic Literature by Bronwyn Hall (University of California, Berkeley), Christian Helmers (Santa Clara University), Mark Rogers (Oxford University), and Vania Sena (University of Essex), the UK Community Innovation Survey suggests that most UK-based companies consider trade secrets one of the most effective mechanisms to protect their intellectual property. Further, the recent passing of the “Trade Secrets (Enforcement, etc) Regulations 2018” (SI 2018 No. 597) act by Parliament indicates that UK policymakers are also concerned with protecting domestic trade secrets.
Loosely defined, trade secrets are configurations of closely held, confidential information (e.g. devices, formulas, methods, processes, programmes, techniques, etc.), which are used in a firm’s operations, are not easily ascertainable by outside parties, and have commercial value for the holder because it is secret. Common examples include detailed information about a firm’s customer contact and price lists, computer algorithms, cost information, and business plans for future products and services, among others. Although, despite the simplicity and straightforwardness of these examples, the opaque and intangible nature of trade secrets makes it challenging for investors to appropriately assess the risk profiles and fundamental values of companies more reliant on secrecy.
As explained in the legal article “Bankruptcy in the Age of ‘Intangibility’: The Bankruptcies of Knowledge Companies” by Mathieu Kohmann (Harvard Law School), the difficulty in assessing the risk and value of trade secrets is even more alarming for creditors of financially distressed or defaulted firms. For one, trade secrets cannot generally be collateralised in debt contracts. And second, even if the secrets were pledgeable to lenders, they do not have active secondary markets, making their redeployability and liquidation in bankruptcy costly and largely infeasible. Prior theoretical work in the financial economics literature, further suggests that firms composed primarily of intangible assets (e.g. trade secrets) sustain less debt financing because these types of assets decrease the value that can be captured by lenders in the event of default.
Motivated by the increasing importance of secrecy for firms and governments, and the corresponding difficulties borne by creditors of these types of firms, in the article “Keeping Secrets from Creditors: The Uniform Trade Secrets Act and Financial Leverage“, CERF Research Associate Scott Guernsey, and research collaborators Kose John (New York University) and Lubomir Litov (University of Oklahoma), examine the impact of stronger trade secrets protection on firms’ capital structure decision-making.
To empirically analyse the relationship between trade secrets protection and financial leverage, Dr Guernsey focuses his study on the adoption of the Uniform Trade Secrets Act (UTSA) by 46 US states from 1980 to 2013. The UTSA, much like the recent “Trade Secrets (Enforcement, etc) Regulations 2018” in the UK, improves the protection of trade secrets by codifying existing common law, standardising its legal definition, detailing what constitutes illegal misappropriation (e.g. bribery, theft, espionage), and clarifying the rights and remedies of victimised firms (e.g. injunctive relief, damages, reasonable royalties). Using the staggered adoptions of the UTSA by different states in different years, the authors find that firms located in states with enhanced trade secrets protection reduce (increase) their use of debt (equity) financing, compared to firms operating in the same US Census region and sharing similar industry trends but headquartered in states without the laws’ protection.
Next, Dr Guernsey explores a possible economic explanation for the reduction in debt ratios experienced by firms located in states with the UTSA. The authors find evidence for the “asset pledgeability hypothesis” which conjectures that stronger trade secrets protection incentivises firms to increase their reliance on secrecy (and away from patents), which, correspondingly, increases intangibility, leading to enhanced contracting problems with creditors – since such assets are more difficult to redeploy and liquidate in secondary markets – ultimately, leading to less borrowing. For instance, relative to industry rivals operating in similar geographical regions, firms located in UTSA enacting states increase their investments in intangible assets and research and development (R&D), and experience decreases in the liquidation value of their assets and in their reliance on patents.
Overall, Dr Guernsey’s findings provide important
insights into how greater reliance on trade secrets affects corporate leverage
decisions – indicating that companies with stronger protection choose to keep their
secrets from creditors.
Hall, B., Helmers, C., Rogers, M. and Sena, V. (2014) “The choice between formal and informal intellectual property: a review.” Journal of Economic Literature, 52: 375-423
Kohmann, M. (2017) “Bankruptcy in the age of ‘intangibility’: the bankruptcies of knowledge companies.” Unpublished Working Paper, Harvard Law School.
Long, M.S. and Malitz, I.B. (1985) “Investment patterns and financial leverage.” In: Corporate capital structures in the United States. University of Chicago Press, Illinois, pp.325-352
Shleifer, A., and Vishny, R.W. (1992) “Liquidation values and debt capacity: a market equilibrium approach.” Journal of Finance, 47: 1343-1366
Williamson, O.E. (1988) “Corporate finance and corporate governance.” Journal of Finance, 43: 567-591
Kahle, K.M. and Stulz, R.M. (2017) “Is the US public corporation in trouble?” Journal of Economic Perspectives, 31: 67–88
 For instance, the Coca-Cola soft drink recipe, Google’s search algorithm, McDonald’s Big Mac special sauce, and the New York Times Bestseller List are among the most famous examples of trade secrets.
 For example, see, Long and Malitz (1985), Williamson (1988), and Shleifer and Vishny (1992).
 The US Census Bureau groups states into four census regions: Northeast, Midwest, South, and West.