ANALYSIS OF DEVELOPMENT OF LOCAL SELF-GOVERNMENT UNITS IN VOJVODINA

Authors

DOI:

https://doi.org/10.5937/ekoPolj2002431T

Keywords:

municipalities, logistic regression, discriminant analysis, prediction

Abstract

Discriminant analysis and logistic regressions were applied in this research for the purpose of analyzing the development of autonomous province (AP) Vojvodina local self-government units, which are classified as developed and underdeveloped. The aim of the study is to identify population economic and social characteristics as the one with the most influence on the existence of differences between the observed categories of local self-government units. Based on the results of the discriminatory analysis, number of employed inhabitants per 1,000 inhabitants and number of highly educated inhabitants per 1000 inhabitants were found to have the greatest influence on the development of the local self-government unit, while based on logistic regression results, number of employed inhabitants per 1000 inhabitants and natural increase are the most influential factors. Both models have good data classification power, the discriminant analysis model successfully classifies 90.9% of all cases, and the logistic regression model successfully classifies 88.6% of cases.

Downloads

Download data is not yet available.

References

1.Ahsan ul Haq M., Irum Sajjad D. & Qura-tul-ain. (2015): Performance comparison of classification techniques, artifical neural network, discriminant analysis & logistic regression, Scienece International, 27(3), 1803-1807.
2. Basu A., Ghosh A., Mandal A., Mart´ın N. & Pardo L. (2017), A Wald-type test statistic for testing linear hypothesis in logistic regression models based on minimum density power divergence estimator, Electronic Journal of Statistics, 11(2), 741-2772. DOI: 10.1214/17-EJS1295
3. Chatterjee S. & Ali S. H. (2006): Regression analysis by example, Fourth edition, John Wiley & Sons, New York.
4. Glavaš-Trbić D., Pejanović R. & Maksimović G. (2008): Rural Development and Local Economic Development of Serbia, Agroeconomics, Department of Agricultural Economics and Rural Sociology, Faculty of Agriculture, Novi Sad, Serbia, 47 (48), 80- 91. [In Serbian: Glavaš-Trbić D., Pejanović R. & Maksimović G. (2008): Ruralni razvoj i lokalni ekonomski razvoj Srbije, Agroekonomika, Departman za ekonomiku poljoprivrede i sociologiju sela, Poljoprivredni fakultet, Novi Sad, Srbija, 47 (48), 80- 91].
5. Hair J., Black W., Babin B., Anderson R., Tatham R. (2006): Multivariate data analysis, Pearson Prentice Hall, New Jersey.
6. Heil K. & Schmidhalter U. (2014): Using discriminant analysis and logistic regression in mapping quaternary sediments, Mathematical Geosciences, 46(3),361-376. DOI: 10.1007/s11004-013-9486-x
7. Kačar B., Curić J. & Ikić S. (2016): Local economic development in theories of regional economies and rural studies, Economics of Agriculture, 63(1), 231-246. DOI:10.5937/ekoPolj1601231K
8. Kovljenić M. & Savić M. (2017): Factors influencing meat and fish consumption in Serbia households: Evidence from SILC database, Economics of Agriculture, 64(3), 945-956. DOI: 10.5937/ekoPolj1703945K
9. Liptáková K. & Rigová Z. (2020): Possibilities of Slovak municipalities to participate in regional development in context of globalization, The 19th International Scientific Conference Globalization and its Socio-Economic Consequences -Sustainability in the Global-Knowledge Economy, Rajecke Teplice,Slovakia, 74 (1),1-8. DOI:10.1051/shsconf/20207405013
10. Pohar M., Balas M. & Turk S. (2004): Comparison of Logistic Regression and Linear Discriminant Analysis: A Simulation Study, Metodološki zvezki, 1(1), 143-161.
11. Sokolovska V., Nikolić- Đorić E. & Žolt L. (2014): Regional differences in the Republic of Serbia, Regions and regionalization, Faculty of Philosophy, University of Novi Sad, Serbia, no. 3, 9-22. [In Serbian: Sokolovska V., Nikolić- Đorić E., Žolt L. (2014): Regionalne razlike u Republici Srbiji, Regioni i regionalizacija, Filozofski fakultet, Univerzitet u Novom Sadu, Srbija, no. 3, 9-22].
12. The Statistical Office of the Republic of Serbia, Municipalities and regions.[in Serbian: Republički zavod za statistiku, Opštine i regioni]. Retrieved from www.stat.gov.rs, (February 16,2020).
13. The Official Gazette Republic of Serbia, Decree on the establishment of a single list of development of the region and local self-governemnt units for 2014, No. 104/2014. [in Sebian: Sl. glasnik RS, Uredba o utvrđivanju jedinstvene liste razvijenosti regionai jedinica lokalne samouprave za 2014. Godinu, No. 104/2014].
14. Walker D. & Smith T. (2016): JMASM Algorithms and code nine pseudo R indices for binary logistic regression models, Journal of Modern Applied Statistical Methods, 15(1), 848-854.

Downloads

Published

2020-06-23

How to Cite

Tekić, D., Mutavdžić, B., Novaković, T., & Pokuševski, M. (2020). ANALYSIS OF DEVELOPMENT OF LOCAL SELF-GOVERNMENT UNITS IN VOJVODINA. Ekonomika Poljoprivrede, 67(2), 431–443. https://doi.org/10.5937/ekoPolj2002431T

Issue

Section

Original scientific papers