In the traditional view of corporate debt, when a company wants to borrow $1 million, creditors ask for something they can seize and keep in case of default—such as equipment, real estate, inventory, or receivables. But this doesn’t work for all businesses: a company that builds code, for example, doesn’t have much to pledge to creditors. Recognizing this, lenders also allow companies to borrow against the cash flows from their operations.

While less traditional, this method of corporate borrowing has actually become dominant, according to an analysis by University of California at Berkeley’s Chen Lian and Chicago Booth’s Yueran Ma. They estimate that 80 percent of US business borrowing by value is made on the basis of cash flows from operations, while only 20 percent is tied to physical and other separable assets, the kind that can be seized by lenders.

Lian and Ma created a database of corporate debt, excluding financial companies. They gathered information from a wide variety of sources on the aggregate value of debt, and they homed in on the debt of individual companies using 2002–18 data from S&P Capital IQ, Thomson Reuters’s DealScan, and other databases.

The researchers observed variation in borrowing patterns across industries. Airlines, for example, largely borrowed against physical assets, as did small companies.

Meanwhile, for companies that borrowed against their cash flows, their total debt was typically limited not by the number of assets, say, but by a multiple of recent operating earnings. “Among large, nonfinancial firms, around 60 percent have earnings-based covenants explicitly written in their debt contracts,” the researchers write.

For companies that used cash flow–based credit, every one dollar increase in operating earnings as measured by EBITDA (earnings before interest, taxes, depreciation, and amortization) was associated with an additional 28 cents in the net issuance of debt. This link was strongest at companies with borrowing amounts that were limited by contracts, and it was also strongest when the economy was weak and lenders were therefore likely to be checking in on borrowers more often.

The researchers also collected real-estate values but observed only a weak connection between real-estate prices and debt levels. At large nonfinancial companies, for every additional dollar value of property, borrowing went up only 2–3 cents.

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“The good news from this research is that, in the United States, we’ve established a good institutional environment that allows firms to pledge their business value,” says Ma. Even if a company doesn’t have machinery to put up as collateral, it can usually borrow money if it can show its business is profitable. Legal structures including Chapter 11 bankruptcy laws facilitate cash flow–based lending in the US, and similar institutions can do the same in other countries.

The flip side, she notes, is that businesses in countries with legal systems that are more oriented to liquidating companies in bankruptcy, or that have less robust and reliable accounting and auditing systems, are at a disadvantage.

The research points to an example of this: pre-2000 Japan, where companies typically offered assets, and especially real estate, as collateral. In the 1990s, Japan had a real-estate boom and bust, and when prices collapsed, a lot of corporate debt turned sour, hurting companies’ ability to borrow. The US had a similar boom and bust in the 2000s, the researchers write, but its companies weren’t hurt as badly. Because large US companies weren’t relying on real estate to borrow, their debt capacity was less affected by the crash in real-estate values. This is in contrast to US households, who relied significantly on borrowing against real estate, and whose debt contributed to the Great Recession.

The study has implications for economic models, and Ma says that the observations could be particularly noteworthy in the coronavirus era, where asset-heavy industries such as airlines, hotels, and oil and gas have been hit hardest. To ensure that policies effectively support an economic recovery, older macroeconomic models may need to be reconsidered.

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