We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator and an empirical likelihood based one for the mean of the response variable are defined. Both the estimators are proved to be asymptotically normal, with...

We investigate the small sample properties of two types of weak exogeneity tests in cointegrated VAR models that are frequently used in applied work. The first one is the standard Likelihood Ratio (LR) test in the Johansen framework. The second test is based on mapping the cointegrated VAR model...

We provide a framework for the analysis of term structures of credit spreads on corporate bonds in the presence of informational asymmetries. While bond investors observe default incidents, we suppose that they have incomplete information on the firm's assets and/or the threshold asset level at...

We study a new type of representation problem for optional processes with connections to singular control, optimal stopping and dynamic allocation problems. As an application, we show how to solve a variant of Skorohod's obstacle problem in the context of backward stochastic differential...

Unobserved heterogeneity is a serious but often neglected problem in structural equation modelling (SEM) challenging the validity of many empirical results. Recently, a finite mixture approach to SEM has been proposed to resolve this problem but until now only a few studies analyse the...

For the Euro 2000 Soccer Championships an experimental asset market was condueted, with traders buying and selling contracts on the winners of individual matches. Market-generated probabilities are compared to professional bet quotas, and factors that are responsible for the quality of the...

Newspapers and weekly magazines catering to the investing crowd often rank funds according to the returns generated in the past. Aside from satisfying sheer curiosity, these numbers are probably also the basis on which investors pick a fund to invest in. In this article, we fully characterize...