We introduce a regression-based gravity model for commodity flows between 35 regions in Austria. We incorporate information regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model. We find that our approach produces improved model fit and higher likelihood values. The model accounts for spatial dependence in the origin-destination fl...

This article develops improved calculation techniques for estimating the spatial econometric interaction model of LeSage and Pace (2008) by maximum likelihood (MLE), Bayesian Markov Chain Monte Carlo (MCMC) two-stage least-squares (S2SLS). The refined estimation methods derive parameter estimates their standard errors exclusively from moment matrices with low dimensions. For computation these m...

Andrea Bonaccorsi Dipartimento di Sistemi Elettrici ed Automazione, Facoltà di Ingegneria, Università di Pisa Via Diotisalvi 2 – 56126 Pisa E-mail: [email protected] Lucia Piscitello Dipartimento di Ingegneria Gestionale, Politecnico di Milano Piazza Leonardo da Vinci 32 – 20133 Milano E-mail: [email protected] Cristina Rossi Scuola Superiore Sant’Anna P.za Martiri per la Libertà 33 ...

The main objective of this study is to evaluate the impact of maritime transportation instability on international trade instability based on wavelet smoothing and spatial panel data econometric method during the period 1990-2012. The results showed that the spatial effects have an impact on international trade instability. So that a sudden 100 percent increase in international trade in the nei...

A system of two dynamic spatial panel data model equations is developed in which output growth and the change unemployment rate are interdependent. The parameters estimated by recently maximum likelihood techniques for multivariate econometric models, using twelve provinces Netherlands over period 1974–2018, covering four major economic downturns Dutch economy. By time-cumulative marginal effec...

This paper implements a novel approach to formalizing spatial externalities by employing spatial econometric methods that combine spatial dependence and spatial heterogeneity in the form of spatial regimes. The results confirm earlier findings that academic externalities are not uniform across sectors but also indicate important differences across sectors in terms of agglomeration effects.