Copulas have attracted considerable interest for modelling multivariate observations and for stress testing in quantitative finance. In this paper, a semiparametric method is studied for estimating the copula parameter and the joint distribution of the error term in a class of multivariate time series models when the marginal distributions of the errors are unknown. The proposed method first ob...

A standard approach to analyzing n binary matched pairs being usually represented in n 2× 2 tables is to apply a subject-specific model; for the simplest situation it is the so-called Rasch Model. An alternative population-averaged approach is to apply a marginal model to the single 2 × 2 table formed by n subjects. For the situation of having an additional stratification variable with K levels...

Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem. In this paper I find that the most important component of this incidental parameters bias for probit fixed effects estimators of index coefficients is proportional to the true value of these coefficients, using a large-T expansion of the bias. This result allows me to derive a low...

The superexogeneity of wage equations is tested in four major European countries. This is an important issue because while only weak exogeneity is needed for estimation purposes and for testing, and strong exogeneity for forecasting, superexogeneity is required for policy analysis. The procedure suggested by Engle and Hendry (1993) is adopted to carry out the empirical analysis. In all cases th...

Recurrent event analysis has been a topic that has generated much attention in the last few years. The analysis of recurrent event data can be a complex task, with many different relationships and dependencies that need to be specified. One aspect of recurrent events that is difficult to specify, and even more complex to justify, is the relationship a subject’s rate of failure will have as even...

This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten rapidly as the number of time series observations grows. We also show in numerical calculations that the b...

Abstract The extremal index θ , a measure of the degree of local dependence in the extremes of a stationary process, plays an important role in extreme value analyses. We estimate θ semiparametrically, using the relationship between the distribution of block maxima and the marginal distribution of a process to define a semiparametric model. We show that these semiparametric estimators are simpl...

In medical research logistic regression and Cox proportional hazards regression analysis, in which all the confounders are included as covariates, are often used to estimate an adjusted treatment effect in observational studies. In the last decade the method of propensity scores has been developed as an alternative adjustment method and many examples of applications can be found in the literatu...

This paper applies a large number of models to three previously-analyzed data sets, and compares the point estimates and confidence intervals for technical efficiency levels. Classical procedures include multiple comparisons with the best, based on the fixed effects estimates; a univariate version, marginal comparisons with the best; bootstrapping of the fixed effects estimates; and maximum lik...

Conditional independence models are defined by a set of conditional independence restrictions and play an important role in many statistical applications, especially, but not only, graphical modeling. In this paper we identify a subclass of these models which are hierarchical marginal log-linear, as defined by Bergsma and Rudas (2002a). Such models are smooth, which implies the applicability of...