Introduction

In this chapter we depart from earlier chapters in that we model technology and measure efficiency relative to what we call price sets. In contrast, Chapters 3 through 6 judged efficiency and modeled technology relative to what might be called quantity sets. These earlier chapters also had in common the assumption that input and output prices are taken as given, i.e. the individual unit is assumed to be a price taker. In this chapter we model the case in which prices are the choice variables and input and output vectors are taken as given.

In evaluating performance relative to price sets rather than quantity sets we are departing from the usual economic approach, which generally takes quantity data as “primal”. In fact, one possible interpretation of the measurement of efficiency in price space is to assume that this is an accounting model, rather than an economic model. Another interpretation is related to what has come to be known as a nonminimal cost function approach. In that approach it is assumed that firms' observed costs and observed or market prices are “distorted” – due to regulation, for example, price controls, imperfect competition, etc. Or firm managers may be utility maximizers rather than cost minimizers. In these cases, firm behavior may be consistent with shadow cost minimization with respect to shadow prices (which may deviate from observed prices). The goal of the nonminimal cost literature is to identify those shadow prices and use their deviation from observed prices as a measure of allocative efficiency.