This paper discusses a tool for optimization of econometric models based on genetic algorithms. First, we briefly describe the concept of this optimization technique. Then, we explain the design of a specifically developed algorithm and apply it to a difficult econometric problem, the...

This paper considers the shape invariant modelling approach in semiparametric regression estimation. Nonparametric functions of similar shape are linked by parametric transformations with unknown parameters. A computationally convenient estimation procedure is suggested. √N- consistency of the...

We use a multivariate hazard model for the analysis of data on the timing of ratifications of different conventions. The model accounts for two random effects, one at the country level and the other at the convention level. We use a semi-parametric Bayesian approach, based on the partial...

This paper focuses on finding starting-values for maximum likelihood estimation of Vector STAR models. Based on a Monte Carlo exercise, different procedures are evaluated. Their performance is assessed w.r.t. model fit and computational effort. I employ i) grid search algorithms, and ii)...

We formulate an optimal control capital accumulation model with a Leontief-type production function and an exogenously given time-lag between investment and the accumulation of the capital stock, to analyze the qualitative and quantitative influence of time-lags on the system dynamics. As known...

We present a decomposition approach for integrated assessment modeling of climate policy based on a linear approximation of the climate system. Our objective is to demonstrate the usefulness of decomposition for integrated assessment models posed in a complementarity format. First, the...

Following the ambiguous results in the literature aimed at understanding the empirical link between fiscal federalism and economic growth, this paper revisits the question using a Bayesian Model Averaging approach. The analysis suggests that the failure to appropriately account for model...

This paper estimates the impact of training incidence and duration on employment transitions accounting for the endogeneity of program participation and duration. We specify a very flexible bivariate random effects probit model for employment and training participation and we use Bayesian Markov...

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method is more flexible than the approach proposed by Florax et al. (2003) since it controls for spatial dependence as well as for spatial heterogeneity. In particular, Bayesian and...

This paper analyzes long-run co-movements between international real estate stock markets and between regions based on bivariate and multivariate tests for cointegration. While the topic has been analyzed in previous studies such as Gallo and Zhang (2009) and Yunus (2009) among others, this...