The paper considers the K-statistic, Kleibergen’s (2000) adaptation ofthe Anderson-Rubin (AR) statistic in instrumental variables regression.Compared to the AR-statistic this K-statistic shows improvedasymptotic efficiency in terms of degrees of freedom in overidentifiedmodels and yet it...

The inequality dataset compiled in the 1990s by the World Bank and extendedby the UN has been both widely used and strongly criticized. The criticisms raisequestions about conclusions drawn from secondary inequality datasets in general. Wedevelop techniques to deal with national and...

We study electoral competition among politicians who are heterogeneous both in competence and in how much they care about (what they perceive as) the public interest relative to the private rents from being in office. We show that politicians may have stronger incentives to behave...

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...

We identify the conditions under which voters can induce political parties to collect information and to select policies which are optimal from the representative voter’s point of view. We show that when parties are office motivated the voting rule should encourage parties to collect...

We develop a simple two period model to study the importance of motivational differences among politicians in describing the role of elections and explaining policy choices. In our model, politicians differ in their motives of running public office. Good politicians care about policies while bad...

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...

This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient procedure named AdMitIS. The methodology automatically constructs a mixture of Student-t distributions as an approximation to the...

We consider the problem of smoothing data on two-dimensional grids with holes or gaps. Such grids are often referred to as difficult regions. Since the data is not observed on these locations, the gap is not part of the domain. We cannot apply standard smoothing methods since they smooth over...

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of...