The Marginal Productivity Theory Of The Price Of Capital: An Historical Perspective On The Origins Of The Codswallop

Although it might have been expected that, by this point in time, the unacceptability of the marginal productivity theory of the return on capital would be universally agreed, that is evidently not the case. Popular textbooks still propound the dogma to the innocent. This note is presented in the hope that a succinct indication of the origins of the theory it will contribute to a more general appreciation of the unrealistic and illogical nature of this doctrine.

Still More On Why We Should Bury The Marginal Productivity Theory Of The Price Of Capital: A Supplementary Note

The purpose of this note is to supplement the author’s earlier remarks on the unsatisfactory nature of the neoclassical account of how the return on capital is determined. (See Strathclyde Discussion Paper 12-03: “The Marginal Productivity Theory of the Price of Capital: An Historical Perspective on the Origins of the Codswallop”). The point is made via a simple illustration that certain matters which are problematical in neoclassical terms are perfectly straightforward when viewed from a classical perspective. Basically, the marginalist model of the nature of an economic system is not fit for purpose in that it fails to comprehend the essential features of a surplus-producing economic system as distinct from one merely of exchange.

Asset Prices, Business Cycles, and Markov-Perfect Fiscal Policy when Agents are Risk-Sensitive

We study a business cycle model in which a benevolent fiscal authority must determine the optimal provision of government services, while lacking credibility, lump-sum taxes, and the ability to bond finance deficits. Households and the fiscal authority have risk sensitive preferences. We find that outcomes are affected importantly by the household's risk sensitivity, but not by the fiscal authority's. Further, while household risk-sensitivity induces a strong precautionary saving motive, which raises capital and lowers the return on assets, its effects on fluctuations and the business cycle are generally small, although more pronounced for negative shocks. Holding the stochastic steady state constant, increases in household risk-sensitivity lower the risk-free rate and raise the return on equity, increasing the equity premium. Finally, although risk-sensitivity has little effect on the provision of government services, it does cause the fiscal authority to lower the income tax rate. An additional contribution of this paper is to present a method for computing Markov-perfect equilibria in models where private agents and the government are risk-sensitive decisionmakers.

On the Relationship between Market Power and Bank Risk Taking

We analyse risk-taking behaviour of banks in the context of spatial competition. Banks mobilise unsecured deposits by offering deposit rates, which they invest either in a prudent or a gambling asset. Limited liability along with high return of a successful gamble induce moral hazard at the bank level. We show that when the market power is low, banks invest in the gambling asset. On the other hand, for sufficiently high levels of market power, all banks choose the prudent asset to invest in. We further show that a merger of two neighboring banks increases the likelihood of prudent behaviour. Finally, introduction of a deposit insurance scheme exacerbates banks’ moral hazard problem.

Learning about Risk and Return: A Simple Model of Bubbles and Crashes

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.