The substance and style of modern microeconometrics is shaped by its role in analyses of public policy issues. Computational considerations have proved to be an important influence on the methodology and scope of empirical analyses that address these issues. To be convincing to a wide readership the empirical analyses need to be based on representative data and flexible modeling approaches. In this chapter we illustrate, through a variety of empirical examples, how modelers handle the complexities that arise from the richness of survey data and the heterogeneity in behavior of market participants. After introductory sections on data and programming languages, the remainder of the chapter covers many leading computationally intensive econometric techniques. These are illustrated by means of specific numerical examples. An algorithmic format is used to describe the computational features.