Quantifying the Economic Development Dynamics of a Country Based on the Lorenz Curve

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dc.contributor.author Ginevičius, Romualdas
dc.contributor.author Nazarko, Joanicjusz
dc.contributor.author Gedvilaitė, Dainora
dc.contributor.author Dacko-Pikiewicz, Zdzisława
dc.contributor.other Ekonomická fakulta cs
dc.date.accessioned 2021-03-16T10:51:25Z
dc.date.available 2021-03-16T10:51:25Z
dc.identifier.issn 1212-3609
dc.identifier.uri https://dspace.tul.cz/handle/15240/159929
dc.description.abstract The welfare of a country depends on its economic development. In order to have the impact on it, we should have a possibility to quantitatively assess its situation at the desired point in time. Economic development, as a multifaceted and complex phenomenon, is reflected in two dimensions – intensity and uniformity. These mentioned above can be viewed as partial indicators of dynamics. Two main approaches to measuring development uniformity can be distinguished. In one of the cases, it is measured on the basis of an index that includes the main results of the country's economic development. In the other case, the values of the indicators reflecting all the essential development actions are combined in one appropriate way. From a scientific point of view, the second approach is more accurate as it allows for a better assessment of the complex nature of a country’s economic development. On the other hand, its application today is still problematic due to the fact that the models for this differ in terms of both the number and composition of indicators. For this reason, it is not possible to compare countries. Therefore, in international practice, the economic development of countries is measured by gross domestic product per capita (GDP). Based on GDP indicator, the method for the measurement of uniformity is proposed and the essence of which is the ratio of the length of the ideal trajectory of the development during the period under review to the length of the actual trajectory. Without ruling out the appropriateness of such an approach for assessing development uniformity, it makes sense to look for alternative methods. In this sense, methods that allow assessment of the extent of fluctuations of the phenomenon under consideration as an essential feature of development dynamics are suitable. These include the Gini coefficient, which is determined from the Lorenz curve. en
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dc.language.iso en
dc.publisher Technická Univerzita v Liberci cs
dc.publisher Technical university of Liberec, Czech Republic en
dc.relation.ispartof Ekonomie a Management cs
dc.relation.ispartof Economics and Management en
dc.relation.isbasedon Amin, S. (1996). Economic, social and political distortions in the modern world. Retrieved April 10, 2020, from http://www.ismea.org/INESDEV/Amin.eng.html
dc.relation.isbasedon Atkinson, A. B., Cantilton, B., & Marlier, R. (2002). Social Indicators. The EU and the Social Exclusion. Oxford: Oxford University Press.
dc.relation.isbasedon Babu, S. S., & Datta, S. K. (2015). Revisiting the link between socio-economic development and environmental status indicators focus on panel data. Environment, Development and Sustainability, 17(3), 567–586. https://doi.org/10.1007/s10668-014-9561-6
dc.relation.isbasedon Boggia, A., & Cortina, C. (2010). Measuring sustainable development using a multi-criteria model: A case study. Journal of Environmental Management, 91(11), 2301–2306. https://doi.org/10.1016/j.jenvman.2010.06.009
dc.relation.isbasedon Bolcárová, P., & Kološta, S. (2015). Assessment of sustainable development in the EU 27 using aggregated SD index. Ecological indicators, 48, 699–705. http://dx.doi.org/10.1016/j.ecolind.2014.09.001
dc.relation.isbasedon Bratčikovienė, N., & Deveikytė, R. (2006). Namų ūkių pajamos ir išlaidos. Lietuvos ekonominė ir socialinė raida. Retrieved February 12, 2020, from https://osp.stat.gov.lt/lietuvos-statistikos-metrastis/lsm-2019/gyventojai-ir-socialine-statistika/namu-ukiu-pajamos-ir-gyvenimo-salygos
dc.relation.isbasedon Charsan, S. (2013). Assessing the sustainable development of Thailand. Procedia Environmental Sciences, 17, 611–619. https://doi.org/10.1016/j.proenv.2013.02.077
dc.relation.isbasedon Čiegis, R., Ramanauskienė, J., & Šimanskienė, L. (2010). Lietuvos regionų darnaus vystymosi vertinimas. Klaipėda: Klaipėdos universiteto leidykla.
dc.relation.isbasedon Čiulevičienė, V., Čiulevičius, J., & Šiuliauskienė, D. (2006a). Kaimo namų ūkio pajamų nelygybės statistinio vertinimo tobulinimas. Vagos: LŽŪU mokslo darbai, 73(26), 73–82.
dc.relation.isbasedon Čiulevičienė, V., Čiulevičius, J., & Šiuliauskienė, D. (2006b). Vartojimo išlaidų nelygybės statistinio vertinimo metodologiniai aspektai. Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos, (1), 34–40.
dc.relation.isbasedon Čiulevičius, J., & Čiulevičienė, V. (2008). Lietuvos gyventojų ekonominė nelygybė ir jos įvertinimo tobulinimas. Vadybos mokslas ir studijos-kaimo verslų ir jų infrastruktūros plėtrai, 12(1), 46–53.
dc.relation.isbasedon Dagum, C. (1980). The generation and distribution of income, the Lorenz curve and the Gini ratio. Economie Appliquée, 33(2), 327–367.
dc.relation.isbasedon Ginevičius, R., Gedvilaitė, D., Stasiukynas, A., & Šliogerienė, J. (2018). Quantitative assessment of the dynamic of the economics development of socioeconomic systems based on the MDD method. Inzinerine ekonomika – Engineering Economics, 29(3), 531–553. https://doi.org/10.5755/j01.ee.29.3.20444
dc.relation.isbasedon Gursky, D. B. (2001). The past, present and future of social inequality. In Social stratification: class, race and gender in sociological perspective. Boulder, CO: Westview Press.
dc.relation.isbasedon Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making. Methods and applications a state-of-the-art survey. Lecture notes in economics and mathematical systems 186. Berlin, Heidelberg: Springer.
dc.relation.isbasedon Ibragimov, M., Ibragimov, R., Kattuman, P., & Ma, J. (2018). Income inequality and price elasticity of market demand: the case of crossing Lorenz curves. Economic Theory, 65, 729–750. https://doi.org/10.1007/s00199-017-1037-0
dc.relation.isbasedon Jann, B. (2016). Estimating Lorenz and Concentration Curves. The Stata Journal, 16(4), 837–866. https://doi.org/10.1177/1536867X1601600403
dc.relation.isbasedon Kawachi, I., & Kennedy, B. P. (1999). Income inequality and health: pathways and mechanisms. Health Services Research, 34(1 Pt 2), 215–227.
dc.relation.isbasedon Kawachi, J., Kennedy, B. P., & Wilkinson, R. G. (1999). Income inequality and health. New York, NY: New York Press.
dc.relation.isbasedon Kurowska-Pysz, J., Szczepańska-Woszczyna, K., Štverková, H., & Kašík, J. (2018). The catalysts of cross-border cooperation development in Euroregions. Polish Journal of Management Studies, 18(1), 180–193.
dc.relation.isbasedon Lando, T., Staníčková, M., & Franek, J. (2018). Parametric families for the Lorenz Curve: an analysis of income distribution in European countries. Ekonomická revue – Central European Review of Economic Issues, 21, 51–60. https://doi.org/10.7327/cerei.2018.06.03
dc.relation.isbasedon Lazutka, R. (2003). Gyventojų pajamų nelygybė. Filosofija. Sociologija, 2, 53–64.
dc.relation.isbasedon Lyon, M., Cheung, L. C., & Gastwirth, J. L. (2016). The advantages of using group means in estimating the Lorenz Curve and Gini Index from grouped data. The American Statistician, 70(1), 25–32. https://doi.org/10.1080/00031305.2015.1105152
dc.relation.isbasedon Prascevic, N., & Prascevic, Z. (2017). Application of fuzzy AHP for ranking and selection of alternatives in construction project management. Journal of Civil Engineering and Management, 23(8), 1123–1135. https://doi.org/10.3846/13923730.2017.1388278
dc.relation.isbasedon Rudzkienė, V. (2005). Socialinė statistika. Vilnius: MRU Publishing Center.
dc.relation.isbasedon Song, Y., Yao, S., Yu, D., & Schen, Y. (2017). Risky multi-criteria group decision on green capacity investment projects based on supply chain. Journal of Business Economics and Management, 18(3), 355–372. https://doi.org/10.3846/16111699.2017.1331461
dc.relation.isbasedon Turskis, Z. (2018). A comparative study of integrated FMCDM methods for evaluation of organizational strategy development. Journal of Business Economics and Management, 19(2), 360–381. https://doi.org/10.3846/jbem.2018.5683
dc.relation.isbasedon Turskis, Z., Morkūnaitė, Z., & Kutut, V. (2017). A hybrid multiple criteria evaluation method of ranking of caltural heritage strucrues for renovation projects. International Journal of Strategic Property Management, 21(3), 318–329. https://doi.org/10.3846/1648715X.2017.1325782
dc.rights CC BY-NC
dc.subject country economic development en
dc.subject quantification of dynamics of economic development en
dc.subject Gini coefficient en
dc.subject Lorenz curve en
dc.subject.classification O1
dc.subject.classification O11
dc.title Quantifying the Economic Development Dynamics of a Country Based on the Lorenz Curve en
dc.type Article en
dc.publisher.abbreviation TUL
dc.relation.isrefereed true
dc.identifier.doi 10.15240/tul/001/2021-1-004
dc.identifier.eissn 2336-5604
local.relation.volume 24
local.relation.issue 1
local.relation.abbreviation E+M cs
local.relation.abbreviation E&M en
local.faculty Faculty of Economics
local.citation.spage 55
local.citation.epage 65
local.access open
local.fulltext yes
local.filename EM_1_2021_4


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