Determinants of economic growth in Ghana are analysed using restricted vector autoregressive (VAR) model for the period 1975-2013. The empirical results reveal that GDP per capita in long-run is driven by export, oil and mineral rents while government consumption retard economic growth....

This paper addresses parameter estimation of spatial regression models incorporating spatial lag. These models are very important in spatial econometrics, where spatial interaction and structure are introduced into regression analysis. Because of spatial interactions, observations are not truly...

Following the Mediterranean Region trend, the Portuguese peripheral NUTS III regions are simultaneously affected by a human desertification and population ageing. In order to analyse the requirements to revert this process, DEMOSPIN project - Economically Sustainable DEMOgraphy - ReverSing...

Many regression models are used to provide some recommendations in private sectors or government public policy. Data are usually obtained from several districts which may varies from one to the others. Assuming there is no significant variation among local data, a single global model may provide...

We propose theory-based Monte Carlo simulations to quantify the extent to which the estimated speed of convergence depends on the underlying econometric techniques. Based on a theoretical growth model as the data generating process, we find that, given a true speed of convergence of around 5%,...

Nonparametric efficiency analysis has become a widely applied technique to support industrial benchmarking as well as a variety of incentive-based regulation policies. In practice such exercises are often plagued by incomplete knowledge about the correct specifications of inputs and outputs....

This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects. The estimation procedure is based on the observational equivalence between distribution free models with a conditional median restriction and...

This paper focuses on the estimation of fiscal response functions for advanced economies and on the performance of alternative specifications of the Generalized Method of Moments (GMM) estimator for the rule's parameters. We first estimate the parameters on simulated data through Monte Carlo...

This study introduces a multivariate extension to the class of stochastic volatility models, employing integrated nested Laplace approximations (INLA) for estimation. Bayesian methods for estimating stochastic volatility models through Markov Chain Monte Carlo (MCMC) can become computationally...