With an increased use of modern ICT methodologies in teaching econometrics, additional research is needed to evaluate their effects on students' learning of econometrics. The purpose of this paper is to empirically investigate how the Internet-based computer laboratory at Ss. Cyril and Methodius...

The Bayesian Estimation, Analysis and Regression toolbox (BEAR) is a comprehensive (Bayesian) (Panel) VAR toolbox for forecasting and policy analysis. BEAR is a MATLAB based toolbox which is easy for non-technical users to understand, augment and adapt. In particular, BEAR includes a...

This beginners’ guide to MATLAB for economics and econometrics is an updated and extended version of Frain (2010). The examples and illustrations here are based on Matlab version 8.3 (R2014a). It describes the new MATLAB Desktop, contains an introductory MATLAB session showing elementary...

This note is a companion to the Lilien (lilien) and Modified Lilien (mlilien) commands for computing the relative indices in STATA. The note illustrates the main features of the commands with an application to the structural determinants of regional unemployment.

This note is a companion to the Lilien (lilien) and Modified Lilien (mlilien) commands for computing the relative indices in STATA. The note illustrates the main features of the commands with an application to the structural determinants of regional unemployment.

This paper is an introduction to Stata with econometrics in mind. One aim of the proposed methodology is the keeping of appropriate records so that results can be easily replicated. These records should meet the requirements of management and internal audit functions in policy making bodies and...

This paper is an introduction to MATLAB for econometrics. It describes the MATLAB Desktop, contains a sample MATLAB session showing elementary MATLAB operations, gives details of data input/output, decision and loop structures, elementary plots, describes the LeSage econometrics toolbox and...

Despite attempts to get around the Jacobian in fitting spatial econometric models by using GMM and other approximations, it remains a central problem for maximum likelihood estimation. In principle, and for smaller data sets, the use of the eigenvalues of the spatial weights matrix provides a...

Recent advances in spatial econometrics model fitting techniques have made it more desirable to be able to compare results and timings. Results should correspond between implementations using different applications, while timings are more readily compared within a single application. A broad...