It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.

This chapter provides an overview of techniques for econometric analysis of technical (production) and economic (cost) efficiency. The stochastic frontier model of Aigner, Lovell, and Schmidt (1977) is now the standard econometric platform for this type of analysis. The underlying models and econometric techniques that have been used in studying technical inefficiency in the stochastic frontier framework are surveyed, and some of the recent developments in econometric methodology are presented. Applications that illustrate some of the computations are presented in the final section.