This paper exposits and relates two distinct approaches to bounding the average treatment effect. One approach, based on instrumental variables, is due to Manski (1990, 1994), who derives tight bounds on the average treatment effect under a mean independence form of the instrumental variables...

This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with...

This paper considers the use of instrumental variables to estimate the mean effect of treatment on the treated. It reviews previous work on this topic by Heckman and Robb (1985, 1986) and demonstrates that (a) unless the effect of treatment is the same for everyone (conditional on observables),...

This paper discusses how randomized social experiments operate as an instrumental variable. For two types of randomization schemes, the fundamental experimental estimation equations are derived from the principle that experiments equate bias in control and experimental samples. Using...

This paper considers the recent case for randomized social experimentation and contrasts it with older cases for social experimentation. The recent case eschews behavioral models, assumes that certain mean differences in outcomes are the parameters of interest to evaluators and assumes that...

This chapter studies the microeconometric treatment-effect and structural approaches to dynamic policy evaluation. First, we discuss a reduced-form approach based on a sequential randomization or dynamic matching assumption that is popular in biostatistics. We then discuss two complementary...

This paper considers the identification and estimation of hedonic models. We establish that technology and preferences in a separable version of the hedonic model are generically identified up to affine transformations from data on demand and supply in a single hedonic market. For a very general...