The paper introduces a novel approach to ensemble modeling as a weighted model average technique. The proposed idea is prudent, simple to understand, and easy to implement compared to the Bayesian and frequentist approach. The paper provides both theoretical and empirical contributions for...

We consider a set of potentially misspecified structural models, geometrically combine their likelihood functions, and estimate the parameters using composite methods. In a Monte Carlo study, composite estimators dominate likelihood-based estimators in mean squared error and composite models are...

The key purpose of this paper is to present an alternative viewpoint for combining expert opinions based on finite mixture models. Moreover, we consider that the components of the mixture are not necessarily assumed to be from the same parametric family. This approach can enable the agent to...

In many set identified models, it is difficult to obtain a tractable characterization of the identified set, therefore, empirical works often construct confidence region based on an outer set of the identified set. Because an outer set is always a superset of the identified set, this practice is...

Economic theories are often encoded in equilibrium models that cannot be directly estimated because they lack features that, while inessential to the theoretical mechanism that is central to the specific theory, would be essential to fit the data well. We propose an econometric approach that...

In this research report, we present a new version of IT Modeling Language (ITML). It is integrated with the family of Domain-Specific Modeling Languages (DSMLs) that are part of Multi-Perspective Enterprise Modeling (MEMO). The design of the language followed a proven method. It provides for...