I. Introduction, 440. — II. Some partial equilibrium results, 442. — III. Model One: Bandom labor supply, 444.—IV. Model Two: Random production parameter, 453.—V. Summary and conclusions, 458.—Appendix, 458.

It has been argued by William Baumol and Richard Quandt (1964) and Day (1967) that rules of thumb can be efficient economic strategies when decision making is costly and when decision makers have imperfect information. The present paper augments this literature and analyzes an industrial growth model in which firms determine production and investment levels by solving a single period optimizing problem. The solution is carried out period after period rather than by making a complete lifetime plan involving forecasts of the future. We portray the firm as myopically groping toward an unknown equilibrium through successive one-period movements made by a simple linear programming allocation of the firm's cash budget.' Cash availability is the channel through which market feedback, operating through the demand function, modifies behavior. Our model can be thought of as a dynamic, rule of thumb, approximation to an intertemporally optimal investment and production path for the firm and industry. It is shown that, under certain conditions of demand and cost, an industry whose firms use our myopic investment rules will converge asymptotically to a perpetually maintainable capital stock. This solution is the long-run equilibrium of the perfectly competitive industry in which price just covers total costs of the marginal firm. In other words, a shortsighted optimization based on complete ignorance of demand can lead to equilibrium in the sense of theories based on perfect knowledge and polyperiodic time horizons. This is only one of several possible outcomes, however, for under somewhat different market conditions fluctuations in investment and production levels will eventually occur, perhaps after a protracted period of growth. The model can also generate S-shaped industry growth paths, simultaneous saving and investment, and investment at less than the maximum possible rate (excess borrowing capacity). All of these are commonly observed patterns of industry behavior. The possibility of industrial instability suggests the need for a risk-avoiding rule at the firm level. The rule introduced is the safety-first principle (see Andrew Roy, Day, Dennis Aigner and Smith), a device that is easily seen to reduce the likelihood of unstable oscillations about industrial equilibrium.

In this paper we explore various criteria for risky decision making and examine the relationship among these rules, full cost pricing, and safety margin maximization. The three rules are alternative versions of the "safety-first" principle; each is concerned with expected profits and with the probability of loss. Since the probability of loss can be identified with the firm's margin of safety, these rules can be viewed as alternative ways of making a compromise between expected profit maximization and high safety margins. They result in various output policies which can be most simply characterized as "full cost" or"safety margin" pricing. Rules of thumb related to recovering full cost are therefore explained by the marginal analysis that was supposed by some to refute them.