In cases of non-compliance with a prescribed treatment, estimates of causal effects typically rely on instrumental variables. However, when participation is also misreported, this approach can be severely biased. We provide an instrumental variable method that researchers can use to identify the...

Since the late 90s, Regression Discontinuity (RD) designs have been widely used to estimate Local Average Treatment Effects (LATE). When the running variable is observed with continuous measurement error, identification fails. Assuming non-differential measurement error, we propose a consistent...

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model...

A key assumption in regression discontinuity analysis is that units cannot manipulate the value of their running variable in a way that guarantees or avoids assignment to the treatment. Standard identification arguments break down if this condition is violated. This paper shows that treatment...

In empirical research, measuring correctly the benefits of welfare interventions is incredibly relevant for policymakers as well as academic researchers. Unfortunately, the endogenous program participation is often misreported in survey data and standard instrumental variable techniques are not...

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step, but retain a fully nonparametric specification in the first step. Such estimators exist in many economic applications, including a wide range of missing data and...

This survey is devoted to the statistical analysis of duration models and point processes. Thefirst section introduces specific concepts and definitions for single-spell duration models.Section two is devoted to the presentation of conditional duration models which incorporatethe effects of...

This paper considers a multivariate t version of the Gaussian dynamic conditional correlation(DCC) model proposed by Engle (2002), and suggests the use of devolatized returnscomputed as returns standardized by realized volatilities rather than by GARCH type volatilityestimates. The t-DCC...

We develop a structural multi-factor labour demand model which distinguishes between eightlabour categories including non-standard types of employment such as marginalemployment. The model is estimated for both the number of workers and total working hoursusing a new panel data set...

This paper introduces a novel approach for dealing with the curse of dimensionality in thecase of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VARare proposed that are binding only in a limit as the number of endogenous variables tends toinfinity...