The Nexus Between Financial Globalization and Income Inequality: The Case of Emerging Market Economies

Çelik, Orkun

doi:10.30794/pausbed.789689

Cited by 3 publications

(2 citation statements)

References 62 publications

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“…In general, the Granger causality linkage running from financial globalization to income inequality is seen in Canada, Germany, Japan, Italy, and the UK. The results are line with the studies of many researchers (e.g., Das & Mohapatra, 2003;Lee, 2006;Elmawazini et al, 2013;Jaumotte et al, 2013;Asteriou et al, 2014;Kang-Kook, 2014;Daisaka et al, 2014;Bukhari & Munir, 2016;Cabral et al, 2016;De Haan & Sturm, 2017;Khan et al, 2019;Furceri et al, 2019;Akbakay & Barak, 2020;Çelik, 2021), unlike Agnello et al (2012), Bumann and Lensink (2016), Lee et al (2019). Moreover, the Granger causality linkage running from income inequality to financial globalization is clearly observed in Italy and the UK.…”

Section: Empirical Findingssupporting

confidence: 90%

Causality Linkages Between Income Inequality and Financial Globalization for G7 Countries

Çelik

2021

Finansal Araştırmalar Ve Çalışmalar Dergisi

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The main aim of this study is to evaluate the causality linkages between income inequality and financial globalization for G7 countries over the period 1970-2015. The bootstrap panel Granger causality analysis by Kónya (2006) is used. The empirical results indicate that there is a causality linkage between income inequality and financial globalization in most of the G7 countries. Furthermore, it is shown that income tax has a significant role on the causality linkage. Hence, in order to reduce income inequality, policy makers should apply high taxes on top income, using fiscal policy instruments.

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Section: Empirical Findingssupporting

confidence: 90%

Causality Linkages Between Income Inequality and Financial Globalization for G7 Countries

Çelik

2021

Finansal Araştırmalar Ve Çalışmalar Dergisi

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“…LR DT kNN RF NB SVM Both traditional statistical methods and machine learning methods were used in 13 studies (İçerli, 2005;Aksoy, 2018;Ural, 2020;Çelik, 2009;Torun, 2007;Ergin, 1999;Paket, 2014;Şengören, 2019;Hesarı, 2018;Aktaş, Doğanay & Yıldız, 2003;Yazıcı, 2018;Yakut & Elmas, 2013) examined in the context of Turkey. While the predictive accuracy of these models is compared, it is noticed that machine learning models give 92% more successful result.…”

Section: Methodsmentioning

confidence: 99%

Using Machine Learning Methods in Financial Distress Prediction: Sample of Small and Medium Sized Enterprises Operating in Turkey

AKER¹,

Karavardar

2023

eab

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Financial distress has become one of the main topics on which lots of research has been done in the recent finance literature. This paper aims to predict the financial distress of Turkish small and medium firms using Logistic Regression, Decision Tree, Random Forest, Support Vector Machines, K-Nearest Neighbor and Naive Bayes model. Empirical results indicate that decision tree model is the best classifier with overall accuracy of %90 and %97 respectively for 1 and 2 years prior to financial distress. Three years prior to financial distress, Naive Bayes outperform other models with an overall accuracy of 92.86%. Furthermore, this study finds that distressed firms have more bank loans and lower equity. In the Turkish economy, where cyclical fluctuations are high in the last decade, distressed firms grew rapidly with high bank loans and gained higher operating profits than non-distressed firms. After a while, distressed firms that cannot manage their financial expenses get into financial trouble and go bankrupt. This article can be useful for managers, investors and creditors as well as its contribution to academic research.

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Küreselleşme ve Finansal Gelişmenin Gelir Eşitsizliği Üzerindeki Etkisi: Yükselen Piyasa Ekonomilerinden Yeni Kanıtlar

Pala

2022

Yönetim Ve Ekonomi Dergisi

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The aim of the study is to empirically examine the combined effects of globalization and financial development on income inequality in a unified framework for an emerging economy. Panel data analysis method was used to examine the effect of globalization and financial development on income inequality. First, the existence of correlation between units was examined via the Breusch Pegan ( 2008) LM test and the Pesaran, Ullah and Yamagata ( 2008) NLM test. The stationarities of the variables were examined with the CADF (Crosssectional Augmented Dickey Fuller) Panel Unit Root test. Then, homogeneity test was applied via Swamy (S) test. The long-term relationship between the variables was analyzed via the Gengenbach, Urbain and Westerlund Panel Cointegration test.The causality between the variables was analyzed by the Dumitrescu-Hurlin causality test and the coefficients were analyzed by panel regression analysis. As a result of the panel cointegration test, no long-term relationship was detected between the variables. In a shortterm relationship; It was concluded that there is a bidirectional causality relationship from

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The Nexus Between Financial Globalization and Income Inequality: The Case of Emerging Market Economies

Cited by 3 publications

References 62 publications

Causality Linkages Between Income Inequality and Financial Globalization for G7 Countries

Causality Linkages Between Income Inequality and Financial Globalization for G7 Countries

Using Machine Learning Methods in Financial Distress Prediction: Sample of Small and Medium Sized Enterprises Operating in Turkey

Küreselleşme ve Finansal Gelişmenin Gelir Eşitsizliği Üzerindeki Etkisi: Yükselen Piyasa Ekonomilerinden Yeni Kanıtlar

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