Cointegration techniques are applied to a model of induced innovation based on the two-stage Constant Elasticity of Substitution (CES) production function. This approach results in direct tests of the inducement hypothesis, which are applied to agricultural data for the United Kingdom from 1953...

Das vorliegende Dissertationsprojekt hatte zwei zentrale Schwerpunkte. Den ersten Schwerpunkt bildete die innovative Insolvenzprognosemodellierung für ukrainische Unternehmen.Dafür wurde im Wesentlichen die moderne internationale Standardmethodik zur Insolvenzprognose auf Basis der...

In many scientific studies, the response variable bears a generalized nonlinear regression relationship with a certain covariate of interest, which may, however, be confounded by other covariates with unknown functional form. We propose a new class of models, the partly parametric generalized...

This dissertation studies the question of nonlinearities in the Phillips curve relationshipin France, Germany and Italy. The implications from the theoretical models are that themechanisms that make the Phillips curve nonlinear can work through different channels.Therefore, this thesis not just...

The field of nonlinear regression is a long way from reaching a consensus. Once a method decides to explore nonlinear combinations of predictors, a number of questions are raised, such as what nonlinear combinations to permit and how best to search the resulting model space. Genetic Association...

Aimed at providing the anticipatory ability for the proactive traffic control systems, a new adaptive online short-term univariate traffic condition forecasting method is presented in this dissertation by assimilating knowledge from previous research. Using 15-minute traffic flow series as a...

The stylized fact of time-varying volatility in financial series is commonly accepted amongst scholars as well as practitioners. The GARCH model has been exceptionally successful in this area. Our approach, the minimally cross-entropic conditional density (MCECD) model, is a generalization of...

Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density...