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Article | 20-December-2020

Predicting Polish transport industry equilibrium characteristics as an inverse problem: An Entropy Econometrics Model

The business environment dynamics is governed by a high degree of uncertainty and risk; consequently, in a majority of cases investors face serious difficulties when making business decisions. Additionally, when detailed statistical information relating to industry is missing, any decisions may become a matter of highly risky conjectures. The present article proposes a simultaneous equation model based on the entropy econometrics estimator for recovering some key industrial subsector long-term

Second Bwanakare, Marek Cierpiał-Wolan

Statistics in Transition New Series, Volume 21 , ISSUE 5, 179–191

Article | 22-July-2019

GENERALIZED BAYES ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS

The spatial autoregressive (SAR) models are widely used in spatial econometrics for analyzing spatial data involving spatial autocorrelation structure. The present paper derives a Generalized Bayes estimator for estimating the parameters of a SAR model. The admissibility and minimaxity properties of the estimator have been discussed. For investigating the finite sample behaviour of the estimator, the results of a simulation study have been presented. The results of the paper are applied to

Anoop Chaturvedi, Sandeep Mishra

Statistics in Transition New Series, Volume 20 , ISSUE 2, 15–31

Research paper | 31-October-2017

ANALYSIS OF CONVERGENCE OF EUROPEAN REGIONS WITH THE USE OF COMPOSITE INDEX

, such as: expenditure on R&D, HRST, quantity of patents, employment, participation of people in tertiary education among all employees. This will allow the analysis of conditional β-convergence to be conducted. In the investigation some methods and models offered by the spatial statistics and econometrics will be used. There are empirical proofs that geographical location has a great impact on the processes of economic growth. Consequently, spatial dependencies will be analysed as well.

Joanna Górna, Karolina Górna

Statistics in Transition New Series, Volume 16 , ISSUE 2, 265–278

Research Article | 20-November-2017