Using bordered matrices for Durbin-Watson d statistic evaluations
Journal Title: Central European Review of Economics and Finance - Year 2014, Vol 5, Issue 2
Abstract
In this paper the usage of bordered matrices for Durbin-Watson d statistic evaluation in linear time series model is presented. It is shown how to obtain this statistic without estimation of structural parameters and vector of residuals. As an example - the model of GDP growth in Poland, basing on empirical data from 1991-2013 - is shown.
Authors and Affiliations
Zbigniew Śleszyński
The stabilizing role of unemployment benefits in Poland
This study examines the impact of unemployment benefit system in stabilizing the economy in Poland in 2008-13. The goal is to answer the question: by how much do the automatic stabilizers in the Polish unemployment benef...
Use of Six Sigma for Quality Assurance in the Arms Industry
The purpose of this paper is to present military applications of the quality assurance method called Six Sigma. This method is applied worldwide to shape the quality. It is used by the biggest global enterprises includin...
Application of an early warning system in the dynamic model for business processes improvement
The goal of the present paper is to depict the application of an early warning system as a part of the dynamic model for business processes improvement. The essence of the system is presented, the stages its building pas...
The Limits of the Freedom of a Commune Council in Determining and Differentiating of Property Tax Rates
The power of communes to impose taxes, which is guaranteed in the Constitution of the Republic of Poland and the European Charter of Local Self-Government, includes the competences of a commune council to determine and d...
Systemic competitiveness - new challenges for enterprises in the 21st century
The presented study notes that in the period of ongoing globalization, it is necessary to look at the new rules of building competitiveness for the enterprises. Consequently, it is reasonable to present the basic assumpt...