Exploring the Link Between Natural Resource Revenues and Income Inequality

Omarov Hidayat Oglu (2025) Exploring the Link Between Natural Resource Revenues and Income Inequality. Külkereskedelmi Kar.

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Absztrakt (kivonat)

In this thesis, I look at the link between natural resources’ revenues and income inequality of 30 countries – it looks at the years 2000 till 2020. The so-called “resource curse” is often attributed to resource-rich countries as suffering from slow economic growth or governance afflictions. However, its distributional consequence – income inequality is unclear. This research seeks to add empirical evidence to this ongoing debate by assessing whether and how resource dependence influences the level of income inequality and what economic, institutional and policy-related factors mediate this relationship.For that purpose, a fixed effects panel regression model is specified which uses the natural logarithm of the Gini Index as the dependant. The log of natural resource rents lessors’ percentage of GDP is a key independent variable in the model. The model also looks at other things like birth rate, jobless, savings made by the country, revenue from tax, per capita income, registration in junior school, quality of institution, price rise and trade openness. Theoretical literature on the determinants of inequality and the distributional impact of natural resource wealth informed the selection of these variables.We use Gretl, an open-source econometric software, for the analysis and we proceed systematically and step-wise. To normalize the key variables, some data transformation is performed initially with log transformations applied at some places. Following this, we will estimate the model using pooled OLS, random effects and fixed effects regressions. In this project, the author has conducted model diagnostics such as the White test for heteroskedasticity, tests for autocorrelation, and multicollinearity analysis using Variance Inflation Factors (VIFs). According to the Hausman test, the results of the study are interpreted in favor of fixed effects. The model seems to be a good fit as can be seen from the plot between actual with fitted values.We found that nations that went around enacting policies that require resource dependence tend to experience a rise in inequality. At the same instant, greater secondary schooling, higher institutional quality, and trade openness are align with lower inequality, highlighting the importance of structural and governance factors for equitable outcomes. The association of GDP per capita with inequality appears slightly positive, thus suggesting a Kuznets-curve relationship in some countries. According to a theoretical expectation, fertility and unemployment are positively related to inequality.Despite unsuccessful attempts to carry out panel unit root and cointegration tests due to software problems, robustness checks with alternative specifications and a correlation matrix affirm the internal consistency of the results. The findings point to the conclusion that resource wealth can exacerbate inequality unless it is combined with good governance, effective public investment, and economic diversification.The thesis ends with policy suggestions and actions that institutional development, fiscal transparency, and inclusive education systems can lessen the inequality impact of resource wealth. We acknowledge that some limitations associated with data availability and estimation constraints. We also indicate directions for future research that may use dynamic panel models, disaggregated inequality measures, and such others.

Intézmény

Budapesti Gazdasági Egyetem

Kar

Külkereskedelmi Kar

Tanszék

Nemzetközi Gazdaságtan Tanszék

Tudományterület/tudományág

NEM RÉSZLETEZETT

Szak

Nemzetközi gazdaság és gazdálkodás (angol)

Mű típusa:	diplomadolgozat (NEM RÉSZLETEZETT)
Kulcsszavak:	bevételi forrás, bér - bérezés, conservation of natural resources, egyenlőtlenségek, GDP, inequality, political corruption, regression analysis, természeti erőforrások
SWORD Depositor:	User Archive
Felhasználói azonosító szám (ID):	User Archive
Rekord készítés dátuma:	2025. Okt. 27. 14:30
Utolsó módosítás:	2025. Okt. 27. 14:30

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