Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...

This article evaluates the performance of structural equation models in validating measurement models for hypothetical constructs and deals with specific issues following from the way this methodology is typically applied in scale construction. In particular, controlling for various types of...

The paper considers a SUTSE model embedded in a dynamic framework to estimate an energy cost share model for the Italian economy in an evolutionary environment. This is achieved by allowing stochastic seasonal and trend components in the long-run specification and constructing an error...

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

Following recent work of Franses, Hylleberg and Lee (FHL), this paper analyses the consequences of fitting a deterministic seasonal model to a quarterly time series which can be (at least approximately) described by a seasonal unit root(s) model. Besides the distribution of the coefficient of...

This paper reviews basic notions of return variation in the context of a continuous-time arbitrage-free asset pricing model and discusses some of their applications. We first define return variation in the infeasible continuous-sampling case. Then we introduce realized measures obtained from...

A family of threshold nonlinear generalised autoregressive conditionally heteroscedastic models is considered, that allows smooth transitions between regimes, capturing size asymmetry via an exponential smooth transition function. A Bayesian approach is taken and an efficient adaptive sampling...

We study the impact of individual and temporal aggregation in linear static and dynamic models for panel data in terms of model specification and efficiency of the estimated parameters. Model wise we find that i) individual aggregation does not affect the model structure but temporal aggregation...