If interest rates are low, that means capital is cheap, right? And if capital is cheap, that means more edgy, entrepreneurial projects get funded, right? In an era of low interest rates, shouldn’t we see a lot of experimentation in creating businesses with high long-term potential but uncertain short-term return? Chris Dillow asks these questions in a specific case (about which I know little and care less). But as a general proposition, I think the chain of reasoning above is less reliable than you might think. For an explanation, and a suggestive empirical result, read on.
Economics is founded on the notion of opportunity costs. But opportunity costs are frequently overlooked when discussing the “cost of capital”. Suppose real interest rates are at 0%, or even negative. Does that mean capital is “cheap” for an entrepreneur with a project expected to earn a positive real return? At first blush, one might shout “Yes!” After all, anyone with money in the bank would be better off investing in the project than earning interest that fails even to keep up with inflation.
But this reasoning is flawed, because earning quoted interest is not an investor’s only alternative to the proposed project. Suppose there exist many alternative investments that, for a similar level of risk, offer twice the real return of the proposed project. Then the real financing cost faced by entrepreneurs pushing the project is not a quoted interest rate, but the rate of return offered to investors by the alternatives. If the project cannot match those returns, it will not be financed.
In an idealized world, with no stickiness in prices or information, no non-market intervention in interest rates, and objective appraisals of project risk and return, the scenario described could not occur. The “quoted interest rate” for projects at the relevant risk level would quickly rise to approach the returns of the most profitable available investments, and interest rate benchmarks would accurately approximate the cost of capital.
But we don’t live in that idealized world. Interest rate metrics can and do vary in ways that don’t obviously track the expected returns of investable projects in the economy. The risk and expected return of projects cannot be accurately measured, and market participants must rely on a variety of strategies from hyperrational modeling to recent-past extrapolation to make investment decisions. I’d suggest that recent past extrapolation is a common approach.
Suppose an exogenous shock reduces benchmark interest rates beneath equilibrium levels. Financial assets should revalue very quickly in response to interest rate changes. But suppose that, because of stickiness, momentum or other effects, an asset price boom of some duration, rather than an instantaneous price change, results. How does this affect the cost of capital of a small entrepreneur with a speculative project?
Benchmark interest rates are low, so the headline cost of capital is cheap. But if investors, extrapolating from recent experience, expect high returns at low risk from asset appreciation, our entrepreneur has to compete with those expected returns. Her real “hurdle rate” is defined not by the headline interest rate, but by asset-boom inflated expectations.
For some entrepreneurs, this distinction between asset markets and available financing would be fictional, as it ought to be in theory. An entrepreneur within a large firm, for example, could take advantage of an asset market boom by persuading the firm to issue bonds, commercial paper, or shares to finance her project, achieving financing costs at or even beneath levels what headline interest rates would suggest.
But for many entrepreneurs, rasing capital by issuing securities in the broad market is not an option. Their projects must instead rely on bank financing or “angel investors”, who would require higher returns when broad market expectations are high. If I’m right, during asset price booms this category of entrepreneurs should face an unusually high spread between quoted benchmark interest rates and the rates of return demanded by banks or angels. This is a testable proposition.
Unfortunately, I’m unaware of good data on the average returns required of small entrepreneurs by banks and angel investors. But until the late 1980s, there was a published interest rate reflecting the borrowing cost of businesses that rely on bank financing, the US Prime Rate. Presumably, the cost of bank loans for small entrepreneurs included the (observable) prime rate plus some (unobservable) spread. Though not conclusive, it would be suggestive if the spread of the Prime Rate over a low credit-risk benchmark tends to increase when asset markets boom. Naively, one would expect credit speads and asset prices to be negatively related, as higher credit spreads mean higher financing costs, and usually a risky business environment. So a positive association between a high spread for bank-financed loans and asset prices would be both surprising, and consistent with the hypothesis that asset price booms increase financing costs for firms unable to sell securities into the boom.
Regressing the spread between the US Federal Funds Rate and the Prime Rate against monthly percentage changes in the Dow Jones Industrial Average shows a significant positive relationship, with a coefficient of 0.04 (p < 0.001). In other words, a 1% monthly gain in the DJIA was associated with a 4 basis point increase in the spread, consistent with the opportunity cost of capital hypothesis. 34 years of monthly data were regressed form September 1955 though August, 1989. R2 of the regression is small, at 0.04, as would be expected since DJIA returns are much more volatile than the Prime Rate/Fed Funds spread. (The data is truncated in 1989 because, starting in the early nineties, the Prime Rate was altered to a near fixed 3% spread above Federal Funds. It now has little relevance as a specific measure of the cost of bank loans to business. DJIA was chosen as a proxy for asset prices simply because it is the most famous measure, and therefore intuitively likely to influence capital market expectations. I’ve not tried a similar test against other potential asset market price or borrowing cost spread measures.)
This was a butt-simple, univariate regression on data taken from FRED and Yahoo, and is very preliminary. Correlation ain’t causation, and there could be a variety of other factors accounting for the observed relationship. It’d be nice to come up with a more complete model of the Prime/FF spread, and see whether it seems consistent with the high-opportunity-cost-of-capital in an asset boom hypothesis. But this very simple test provides at least a little evidence that asset booms increase the cost of capital to bank-dependent small entrepreneurs relative to what benchmark interest rates would suggest.
If you’ve read this far, thank you.
- 11-Oct-2006, 4:00 a.m. EET: Removed an unnecessary “indeed”.