Humanities and Social Sciences

Central European Journal of Economic Modelling and Econometrics

Content

Central European Journal of Economic Modelling and Econometrics | 2020 | No 3 |

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Abstract

Recently, in most developed economies, the average age of the workforce has been growing rapidly. Therefore, the questions arise how will it affect the level of wages and the shape of age-productivity and age-wage profiles. The aim of the paper is to analyse the relationship between changes in the age structure of the employment and wages of individuals in minor occupational groups. Using individual data from the Structure of Earnings Survey in Poland in 2006-2014 we created an unique database of individual wages and the characteristics of employed in occupational groups at 3-digit level of classification. In our analysis we used an extended version of Mincerian wage model where both the characteristics of employees (education, work tenure, age, gender, and type of employment contract) and employers (size and ownership sector) were taken into account. The results for the whole sample indicate a significant and negative relationship between the proportion of older workers in employment in a given occupational group and individual wages. However, when the analyses were performed separately for each of the 1-digit occupational groups, the results varied significantly. In those groups where knowledge and qualifications of employees are more important than physical strength had to be updated permanently, an increase in the number of the older workers raises the average wages.

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Authors and Affiliations

Paulina Broniatowska
Aleksandra Majchrowska
Maciej Nasiński
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Abstract

The paper makes a comparison of the results of the application of two-sided and one-sided versions of the Hodrick-Prescott filter on GDP data concerning 27 EU Member States. Based on the results, the overall finding is that, contrary to its assumed advantages, the one-sided filter does not help overcome endpoint unbiasedness. Quite the opposite, it rather spreads and consolidates the endpoint bias that plagues the two-sided version over the entire filtered data. In addition, regression-based results on the influence of the second, third, and fourth moments of the GDP acceleration rates on the differences between onesided and two-sided HP trends are presented.

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Authors and Affiliations

Kaloyan Ganev
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Abstract

The purpose of this empirical study is to find the relationship between economic growth and foreign direct investment (FDI) in the Commonwealth of Independent States (CIS) and Central and Eastern European Countries (CEECs) using endogenous technological change model. First, we combine the CIS and CEECs into one group to test our hypothesis, and then we test each group separately to account for heterogeneity and draw a conclusion whether FDI is indeed a driving force of the economy. Panel data have been used from 2003 to 2014 and different panel estimation methods have been applied. Additionally, we use the Generalized Method of Moments (GMM) panel estimator to control for endogeneity problem. The present study finds that FDI is an important factor explaining economic growth in the pooled group and CEECs, although it is not significant in the case of CIS.

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Authors and Affiliations

Latif Khalilov
Chae-Deug Yi
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Abstract

The paper presents two algorithms as a solution to the problem of identifying fraud intentions of a customer. Their purpose is to generate variables that contribute to fraud models’ predictive power improvement. In this article, a novel approach to the feature engineering, based on anomaly detection, is presented. As the choice of statistical model used in the research improves predictive capabilities of a solution to some extent, most of the attention should be paid to the choice of proper predictors. The main finding of the research is that model enrichment with additional predictors leads to the further improvement of predictive power and better interpretability of anti-fraud model. The paper is a contribution to the fraud prediction problem but the method presented may generate variable input to every tool equipped with variableselection algorithm. The cost is the increased complexity of the models obtained. The approach is illustrated on a dataset from one of the European banks.

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Authors and Affiliations

Damian Przekop

Editorial office

Editors
JACEK OSIEWALSKI, Cracow University of Economics, Poland
ALEKSANDER WELFE, University of Lodz, Poland

Co-Editors

KATARZYNA BIEŃ-BARKOWSKA, SGH Warsaw School of Economics, Poland
MIKOŁAJ CZAJKOWSKI, University of Warsaw, Poland
JAKUB GROWIEC, SGH Warsaw School of Economics, Poland
MAREK GRUSZCZYŃSKI, SGH Warsaw School of Economics, Poland
BOGUMIŁ KAMIŃSKI, SGH Warsaw School of Economics, Poland
MARCIN KOLASA, SGH Warsaw School of Economics, Poland
ANNA PAJOR, Cracow University of Economics, Poland

Associate Editors
KARIM ABADIR, The American University in Cairo, Cairo, Egypt
ANINDYA BANERJEE, University of Birmingham, UK
STEPHEN HALL, University of Leicester, UK
GARY KOOP, University of Strathclyde, Glasgow, UK
MARK STEEL, University of Warwick, UK
MARTIN WAGNER, Technical University of Dortmund, Germany
JAN WERNER, University of Minnesota, USA
PETER WINKER, University of Giessen, Germany

Editorial Board

HERMAN van DIJK, Erasmus University Rotterdam and VU University Amsterdam, The Netherlands
LAWRENCE R. KLEIN, University of Pennsylvania, Benjamin Franklin Professor of Economics, USA
TIMO TERASVIRTA, University of Aarhus, Denmark
HELMUT LUETKEPOHL, Freie Universität Berlin, Germany

Publishing Editor

ANNA STASZEWSKA-BYSTROVA, University of Lodz, Poland

Editorial Assistant

AGNIESZKA RYGIEL, Cracow University of Economics, Poland

Contact

CEJEME Editorial Office - Ms. Karolina Jaszczyk, Polish Academy of Sciencies - Lodz Branch
Piotrkowska Str. 137/139, 90-434 Lodz, Poland
e-mail: cejeme@pan.pl

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Submission Guidelines and Instructions for Authors of accepted papers please visit: http://cejeme.org/submissionguidelines.aspx

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