Fisheries management must manage people in order to manage fish. In this sense, understanding fishing behavior is the cornerstone of effective fisheries policy. However, the latency of fish stocks is a major obstacle in empirical studies. This paper addresses this challenge by deriving a stock...

Structural models can assess the effectiveness of fishery management prospectively and retrospectively. However, when only fishery-dependent data are available, structural econometric models are highly nonlinear in the parameters, and maximum likelihood and other extremum-based estimators can...

This paper considers the first order large sample properties of the GEL class of estimators for models specified by non-smooth indicators. The GEL class includes a number of estimators recently introduced as alternatives to the efficient GMM estimator which may suffer from substantial biases in...

We suggest a way to perform parsimonious instrumental variables estimation in the presence of many, and potentially weak, instruments. In contrast to standard methods, our approach yields consistent estimates when the set of instrumental variables complies with a factor structure. In this sense,...

We give an overview over smooth back tting type estimators in additive models. Moreover we illustrate their wide applicability in models closely related to additive models such as nonparametric regression with dependent error variables where the errors can be transformed to white noise by a...

We propose two simple bias reduction procedures that apply to estimators in a general static simultaneous equation model and which are valid under reatively weak distributional assumptions for the errors. Standard jackknife estimators, as applied to 2SLS, may not reduce the bias of the exogenous...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

In practice structural equations are often estimated by least-squares, thus neglecting any simultaneity. This paper reveals why this may often be justifiable and when. Assuming data stationarity and existence of the first four moments of the disturbances we find the limiting distribution of the...

We show that the Anderson-Rubin (AR) statistic is the sum of two independent piv-otal statistics. One statistic is a score statistic that tests location and the other statistictests misspecification. The chi-squared distribution of the location statistic has a degreesof freedom parameter that is...

Cognitive diagnosis models (CDMs) are an increasingly popular method to assess mastery or nonmastery of a set of fine-grained abilities in educational or psychological assessments. Several inference techniques are available to quantify the uncertainty of model parameter estimates, to compare...