A system of multivariate semiparametric nonlinear time series models is studied with possible dependence structures and nonstationarities in the parametric and nonparametric components. The parametric regressors may be endogenous while the nonparametric regressors are assumed to be strictly exogenous. The parametric regressors may be stationary or nonstationary and the nonparametric regressors ...

In the common nonparametric regression model the problem of testing for a specific parametric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process of pseudo residuals. The process converges weakly to a Gaussian process with a complicated covariance kernel depending on the data generating process. In the ...

Glossary Hypothesis A hypothesis is a statement concerning the (joint) distribution underlying the observed data. Nonparametric test In contrast to a parametric test, a nonparametric test does not presume a particular parametric structure concerning the data generating process. Serial dependence Statistical dependence among time series observations.

If a data set suffers from selection bias then, ordinary regression estimators must be adapted in order to achieve consistency. Consequently, it is necessary to modify any goodness of fit tests based on distances between parametric and non-parametric residuals. More particularly, any bootstrap approximation to these tests must be re– designed. Our first approach to this latter task is based on ...

This paper discusses parametric, nonparametric, and semiparametric models of urban growth. To illustrate differences across approaches, we test Gibrat's law in the long run, using three methods different datasets: Spanish capital cities regions (1900–2011, annual data) US MSAs (1900–2000, decennial data). Our results reveal that estimation relationship between growth initial size can significan...

selection of superior varieties of wide adaptability over diverse farming environments is of high importance, prior to any varietal recommendation. in order to study yield stability of alfalfa, 17 ecotypes were evaluated during 2004-2005 and 2005-2006 growing seasons at 10 research stations. each trial was carried out according to a completely randomized block design of 3 replications with fres...

in more recent years, it has become increasingly recognized that r&d; (research and development) is a key driver of economic growth, a source of innovation and change, and as such stimulates improvements in productivity and economic competitiveness. it is closely associated with knowledge and flexibility, two factors that have gained new significance as a source of competitiveness in an increas...

This paper develops a new methodology for estimating and testing conditional factor models in finance. We propose a two-stage procedure that naturally unifies the two existing approaches in the finance literature–the parametric approach and the nonparametric approach. Our combined approach possesses important advantages over both methods. Using our two-stage combined estimator, we derive new te...

Conditional tests like two-sample permutation tests establish valid nite sample tests for large classes of nonparametric composite null hypotheses. In particular, we discuss the quality of various conditional distribution free tests in comparison to a (parametric) benchmark test. It is shown that they are often asymptotically e ective. This means that conditional tests are asymptotically equiva...