Modern textbook presentations of production economics, from Samuelson's innovative Foundations of Economic Analysis to the present day, treat producers as successful optimizers. They produce maximum outputs allowable by the technology in place and the resources at their disposal. They minimize the cost of producing whatever outputs they choose to produce, given the technology in place and the input prices they face. Cost-minimizing input demands are derived from the resulting minimum cost function by means of Shephard's lemma. They also maximize profit, given the technology in place and the output and input prices they face. Profit-maximizing output supplies and input demands are derived from the resulting profit function by means of Hotelling's lemma.

Conventional econometric practice, beginning with the pioneering work of Cobb and Douglas, has generally followed this theoretical paradigm. Thus least squares–based regression techniques are used to estimate the parameters of production, cost, and profit functions. In such a framework departures from maximum output, from minimum cost and cost-minimizing input demands, and from maximum profit and profit-maximizing output supplies and input demands, are attributed exclusively to random statistical noise.

However casual empiricism and the business press both make persuasive cases for the argument that, although producers may indeed attempt to optimize, they do not always succeed. It is desirable, therefore, to develop a theory of producer behavior in which the motivations are unchanged, but in which success is not guaranteed.