In a recent paper Gonzalez Manteiga and Vilar Fernandez (1995) considered the problem of testing linearity of a regression under MA structure of the errors using a weighted L1-distance between a parametric and a nonparametric fit. They established asymptotic normality of the corresponding test...

We address the problem how to estimate default probabilities for sovereign countries based on market data of traded debt. A structural Merton-type model is applied to a sample of emerging market and transition countries. In this context, only few and heterogeneous default probabilities are...

We suggest improved tests for cointegration rank in the vector autoregressive (VAR) model and develop asymptotic distribution theory and local power results. The tests are (quasi-)likelihood ratio tests based on a Gaussian likelihood, but of course the asymptotic results apply more generally....

Count data often exhibit overdispersion and/or require an adjustment for zero outcomes with respect to a Poisson model. Zero-modified Poisson (ZMP) and zeromodified generalized Poisson (ZMGP) regression models are useful classes of models for such data. In the literature so far only score tests...

This paper investigates the effects of inward FDI on per-capita income and growth of the US states since the mid-1970s. Using a Markov chain approach, it shows that both quantitative and qualitative characteristics of FDI affect per-capita income and growth. Employment-intensive FDI,...

The paper studies the degree of homogeneity of innovative behavior in order to determine empirically an industry classification of Dutch manufacturing that can be used for policy purposes. We use a twolimit tobit model with sample selection, which explains the decisions by business enterprises...

In this paper I propose a Likelihood Ratio test for a unit root (LR) with a local-to-unity Autoregressive parameter embedded in ARMA(1,1) models. By dealing explicitly with dependence in a time series through the Moving Average, as opposed to the long Autorregresive lag approximation, the test...

This paper provides a test of convexity of a regression function. This test is based on the least squares splines. The test statistic is shown to be asymptotically of size equal to the nominal level, while diverging to infinity if the convexity is misspecified. Therefore, the test is consistent...

This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing...