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Title:Značilnosti premoženjske neenakosti v izbranih državah
Authors:ID Poharc, Luka (Author)
ID Boršič, Darja (Mentor) More about this mentor... New window
ID Fir, Nejc (Comentor)
Files:.pdf UN_Poharc_Luka_2024.pdf (2,91 MB)
MD5: 734FA942F9B9E5704A4F06CA26754CF9
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:EPF - Faculty of Business and Economics
Abstract:Neenakost je pojav neenake in nepravične porazdelitve virov in priložnosti med člani določene družbe. Na neenakost je moč gledati z različnih vidikov: najpogostejša metrika je dohodkovna neenakost, povezani koncepti so še življenska neenakost, neenakost priložnosti in premoženjska neenakost. Premoženjska neenakost se nanaša na način razporeditve premoženja med različne skupine v družbi. V našem diplomskem delu smo predstavili teorijo ekonomske neenakosti s poudarkom na premoženjski neenakosti. Osredotočili smo se na ključne kazalnike premoženjske neenakosti, ki smo jih za nekatere države tudi grafično predstavili in opisali. Rezultati kažejo, da se premoženjska neenakost v večini analiziranih držav povečuje, vendar se ta vrednost znatno razlikuje med regijami in državami. Analiza kazalnikov premoženjske neenakosti v izbranih regijah kaže, da so nekatere države, zlasti v Afriki in Latinski Ameriki, med tistimi z najvišjo stopnjo premoženjske neenakosti. Države z razvitimi gospodarstvi, kot so ZDA in Kitajska, kljub hitri rasti in premoženju kažejo visoko neenakost, kar je primerljivo ali celo nad svetovnim povprečjem. Evropa in Kanada pa ostajajo nekoliko bolj uravnotežene v porazdelitvi premoženja. Afrika in Latinska Amerika se soočata z najvišjimi stopnjami premoženjske neenakosti, kar je predvsem posledica zgodovinskih in strukturnih dejavnikov, kot so kolonializem, rasna segregacija in neenakomeren dostop do izobraževanja ter zaposlitve. S pomočjo programa Eviews smo na podlagi presečnih podatkov za leti 2010 in 2021 ocenili funkciji premoženjske neenakosti. Ocenjene modele smo analizirali ter preverjali ustreznost njihove specifikacije in veljavnost predpostavk metode najmanjših kvadratov. V modelih za leto 2010 in 2021 smo uspeli potrditi vse predpostavke metode najmanjših kvadratov z izjemo homoskedastičnosti. Pri proučevanju dejavnikov premoženjske neenakosti so se v modelu za leto 2010 za statistično značilne spremenljivke izkazale delež premoženja 10 % najpremožnejšega prebivalstva, učinkovitost vlade, odprtost trgovine, sodelovanje in odgovornost in HDI indeks. V modelu za leto 2021 so se za statistično značilne izkazale delež premoženja 10 % najpremožnejšega prebivalstva, učinkovitost vlade, odprtost trgovine in HDI indeks.
Keywords:premoženjska neenakost, Ginijev koeficient, kvintili, metoda najmanjših kvadratov.
Place of publishing:Maribor
Publisher:L. Poharc
Year of publishing:2024
PID:20.500.12556/DKUM-90659 New window
UDC:330.34
COBISS.SI-ID:215974659 New window
Publication date in DKUM:21.11.2024
Views:0
Downloads:26
Metadata:XML DC-XML DC-RDF
Categories:EPF
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:12.09.2024

Secondary language

Language:English
Title:Characteristics of wealth inequality in selected countries
Abstract:Inequality is the phenomenon of unequal and unfair distribution of resources and opportunities among members of a given society. Inequality can be viewed from different perspectives: the most common metric is income inequality, related concepts are life inequality, inequality of opportunity and wealth inequality. Wealth inequality refers to the way wealth is distributed among different groups in society. In our thesis, we presented the theory of economic inequality with an emphasis on wealth inequality. We focused on the key indicators of wealth inequality, which we also graphically presented and described for some countries. The results show that wealth inequality is increasing in most of the analyzed countries, but this value varies significantly between regions and countries. Analysis of wealth inequality indicators in selected regions shows that some countries, especially in Africa and Latin America, are among those with the highest levels of wealth inequality. Countries with developed economies such as the US and China, despite rapid growth and wealth, show high inequality, which is comparable to or even above the global average. Europe and Canada, however, remain somewhat more balanced in wealth distribution. Africa and Latin America face the highest levels of wealth inequality, which is mainly the result of historical and structural factors such as colonialism, racial segregation and unequal access to education and employment. With the help of the Eviews program, we estimated the functions of wealth inequality based on cross-sectional data for the years 2010 and 2021. We analyzed the estimated models and checked the adequacy of their specifications and the validity of the assumptions of the least squares method. In the 2010 and 2021 models, we were able to confirm all assumptions of the least squares method with the exception of homoscedasticity. When studying the factors of wealth inequality, the share of wealth of the wealthiest 10% of the population, government efficiency, trade openness, cooperation and responsibility and the HDI index proved to be statistically significant variables in the 2010 model. In the model for 2021, the wealth share of the wealthiest 10% of the population, government efficiency, trade openness and the HDI index proved to be statistically significant.
Keywords:wealth inequality, Gini coefficient, quintiles, least squares method.


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