Identification and Significance of Outliers in Models of Income Convergence
DOI:
https://doi.org/10.15678/ZNUEK.2015.0941.0501Keywords:
outliers, income convergence, econometric models, European UnionAbstract
The research of income convergence found remunerative findings in the existing literature and economic practice. The results obtained, however, show comparatively large differentiation. Many authors underline the strong dependence of the results obtained from the time and spatial character of the sample as well as the type of methods applied. Little attentions is placed on the role of non-typical observations (outliers) which can occur as a result of incorrect measurement, random error, non-standard circumstances or intentional impact. The hypothesis verified was that outliers exert an essential influence on estimation results. The main objective of the analyses provided was to determine if the occurrence of such observations significantly changes the quality of the models built and the speed of the process of income convergence.Downloads
References
Acuna E., Rodriguez C.A. [2004], A Meta Analysis Study of Outlier Detection Methods in Classification, Proceedings IPSI 2004, Venice, http://academic.uprm.edu/eacuna/paperout.pdf (dostęp: 26.04.2014).
Barnett V., Lewis T. [1994], Outliers in Statistical Data, John Wiley, Chichester.
Barro R.J., Sala-i-Martin X. [2004], Economic Growth, 2nd ed., MIT Press, Cambridge, Massachusetts.
Batóg J. [2010], Konwergencja dochodowa w krajach Unii Europejskiej. Analiza ekonometryczna, Rozprawy i Studia, t. DCCCLIV (780), Wydawnictwo Naukowe Uniwersytetu Szczecińskiego, Szczecin.
Batóg J. [2013], Analiza krańcowej pionowej konwergencji dochodowej typu β w krajach Unii Europejskiej w latach 1993-2010, Studia i Prace Wydziału Nauk Ekonomicznych i Zarządzania, nr 31, Metody ilościowe w ekonomii, t. 1, Wydawnictwo Naukowe Uniwersytetu Szczecińskiego, Szczecin.
Batóg J., Batóg B. [2006], Income Convergence in the European Countries: Empirical Analysis, „Folia Oeconomica Stetinensia", nr 5(13).
Ben-Gal I. [2005], Outlier Detection[w:] Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers, red. O. Maimon, L. Rokach, Kluwer Academic Publishers, Boston.
The Conference Board Total Economy Database [2014], January, http://www.conference-board.org/data/economydatabase/ (dostęp: 22.04.2014).
Fawcett T., Provost F. [1997], Adaptive Fraud Detection, „Data Mining and Knowledge Discovery", vol. 1, nr 3.
Hawkins D. [1980], Identification of Outliers, Chapman and Hall, London.
Hozer J. [1993], Mikroekonometria, PWE, Warszawa.
Maddala G.S. [2006], Econometrics, Wydawnictwo Naukowe PWN, Warszawa.
Penny K.I., Jolliffe I.T. [2001], A Comparison of Multivariate Outlier Detection Methods for Clinical Laboratory Safety Data, „The Statistician", vol. 50, nr 3, http://dx.doi.org/10.1111/1467-9884.00279. DOI: https://doi.org/10.1111/1467-9884.00279
Ruts I., Rousseeuw P.J. [1996], Computing Depth Contours of Bivariate Point Clouds, „Computational Statistics and Data Analysis", vol. 23, nr 1, http://dx.doi.org/10.1016/s0167-9473(96)00027-8. DOI: https://doi.org/10.1016/S0167-9473(96)00027-8
Walfish S. [2006], A Review of Statistical Outlier Methods, „Pharmaceutical Technology", November 2.
Williams G.J., Baxter R.A., He H.X., Hawkins S., Gu L. [2002], A Comparative Study of RNN for Outlier Detection in Data Mining, Proceedings of the 2ndIEEE International Conference on Data Mining (ICDM'02), Maebashi City, Japan.
Downloads
Published
Issue
Section
License
Copyright (c) 2015 Cracow Review of Economics and Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
