Interaction effects have been consistently found important in explaining the variation in outcomes in many scientific research fields. Yet, in practice, variable selection including interactions is complicated due to the limited sample size, conflicting philosophies regarding model...

Hierarchical model such as Fay–Herriot (FH) model is often used in small area estimation. The method might perform well overall but is vulnerable to outliers. We propose a robust extension of the FH model by assuming the area random effects follow a t distribution with an unknown...

We build up from the plant level an “aggregate(d)” Solow residual by estimating every U.S. manufacturing plant's contribution to the change in aggregate final demand between 1976 and 1996. Our framework uses the Petrin and Levinsohn (2010) definition of aggregate productivity growth, which...