Original title: Faktory ovlivňující nerovnost příjmů v Číně
Translated title: Drivers of Income Inequality in China
Authors: Chen, Xiao ; Kolář, Daniel (advisor) ; Semerák, Vilém (referee)
Document type: Master’s theses
Year: 2022
Language: eng
Abstract: This thesis uses an empirical approach to examine the drivers of income inequality in China, assuming income inequality to be a linear function of logarithmic per capita income, the educational inequality as well as the percentage of population below secondary, completing secondary, and completing tertiary education. It suggests that growing income inequality is correlated to rising per capita income and educational inequality, utilizing a micro survey data set of 25 provinces from 2010 to 2016 with a one-year gap using the static fixed effects and random effects estimators, as well as a dynamic generalized method of moments estimator. In contrast, the percentage of population completing secondary education has a negative effect. The weighting factors ensure that the data set is representative, and robust and sensitivity tests are applied. The comparison of the EU and China's results shows the features of developed and emerging economies. Keywords Income inequality, Educational inequality, Educational completion, CFPS, Panel data, Weighting factor, Fixed effects, Random effects, GMM-DIFF, GMM-SYS Title Drivers of Income Inequality in China
Keywords: CFPS; Educational Completion; Educational Inequality; Fixed-effect; GMM-SYS; Income Inequality; Panel data; Random-effect,GMM-DIFF; Weighting factor

Institution: Charles University Faculties (theses) (web)
Document availability information: Available in the Charles University Digital Repository.
Original record: http://hdl.handle.net/20.500.11956/174194

Permalink: http://www.nusl.cz/ntk/nusl-507114


The record appears in these collections:
Universities and colleges > Public universities > Charles University > Charles University Faculties (theses)
Academic theses (ETDs) > Master’s theses
 Record created 2022-07-24, last modified 2023-12-31


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