Ekonomik karmaşıklık endeksi (EKE) ile gelir eşitsizliği arasındaki ilişki: OECD ülkeleri üzerine bir uygulama
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Dosyalar
Tarih
2023
Yazarlar
Dergi Başlığı
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Yayıncı
Bursa Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Gelir, bir ekonomide belirli bir dönemde üretilen mal ve hizmetten elde edilen kazancı ifade etmektedir. Ekonomide var olan toplumlar ve bireyler arasında kazancın dağılımını etkileyen birçok unsur bulunmaktadır ve günümüzde ihtiyaçlara ulaşma yollarının kolaylaşması gelir dağılımında eşitsizlik sorununu ortadan kaldırmada etkili olmamaktadır. Gelir dağılımını etkileyen birçok faktör ve gelir dağılımı türleri iktisat tarihinin başlangıcından itibaren iktisadi düşünce okulları ve iktisadi düşünürler için inceleme konusu olmuştur. Bir ekonomide bireylerin bir arada yaşayıp kazanç elde edebilmeleri ve ekonomideki refah seviyesinin azalmaması için gelir eşitsizliği sorununun en aza indirilmesi gerekmektedir. Ekonomilerin dünya pazarında geniş hacimli yer edinebilmeleri önemlidir. Dünya pazarında yer edinebilmek için rekabet üstünlüğü sağlayan, yoğun teknoloji ve bilgi içeren çeşitlendirilebilir mal üretimini gerçekleştirmek gerekmektedir. Üretilen malın içerisinde yer alan bilgi, teknoloji ve kaliteyi ekonomik karmaşıklık endeksi ile ölçmek mümkündür. Bu doğrultuda, çalışmada, ekonomik karmaşıklık endeksi (EKE) ile gelir eşitsizliği arasındaki ilişki OECD ülkelerinde 2000-2020 yılları arasındaki veriler dikkate alınarak incelenmiştir. Modelde araştırma değişkeni ekonomik karmaşıklık endeksi olarak seçilmiştir. Bağımlı değişken OECD ülkelerine ait gini katsayısı olarak; bağımsız değişkenler gayri safi yurtiçi hasıla, ticari açıklık oranı ve OECD ülkelerine giren doğrudan yabancı yatırımların gayri safi yurtiçi hasıla içerisindeki oranı olarak seçilmiş, analiz ve testler uygulamıştır. Kullanılan analiz ve testler sırasıyla; yatay kesit bağımlılık testi, homojenlik testi, panel birim kök analizi, panel zaman serisi analizleri (uzun dönem homojenlik –Hausman- testi), havuzlanmış ortalama grup (PMG) tahmincisi ve Dumitrescu – Hurlin (2012) panel nedensellik testleridir. Yatay kesit bağımlılık ve homojenlik testi sonuçlarına göre modelde değişkenler arasında bağımlılık bulunamamış, panel birim kök analizine göre ise değişkenlerin durağan yapıda oldukları sonucuna ulaşılmıştır. Panel zaman serisi analizlerine göre ise OECD ülkeleri çerçevesinde uzun dönemde ekonomik karmaşıklık endeksinde, ticari açıklık oranında ve doğrudan yabancı yatırımların gayri safi yurtiçi hasıla içerisindeki payında görülen her 1 puanlık artış gini katsayısını sırasıyla; %0,029, %0,043,ve %0,027 oranında azalttığı görülmüştür. Gayri safi yurtiçi hasılada uzun dönemde meydana gelen %1'lik artışın sonucunda ise gini katsayısının %0,021 oranında arttığı gözlemlenmiştir. Panel zaman serisi analizi sonuçlarına göre uzun dönemde parametreler homojen bir yapıda olup birimden birime değişiklik göstermemektedir. Panel nedensellik analizi sonuçlarına göre OECD ülkelerinde ekonomik karmaşıklık endeksi, gayri safi yurtiçi hasıla ve ticari açıklık oranı ile gini katsayısı arasında iki yönlü nedensellik ilişkisinin var olduğu sonucu ortaya çıkmıştır. Doğrudan yabancı yatırımların gayri safi yurtiçi hasıla içerisindeki payı ile gini katsayısı arasında herhangi bir nedensellik ilişkisinin bulunmadığı görülmüştür.
Income refers to the income obtained from the goods and services produced in an economy in a certain period. There are many factors in the economy that affect the distribution of earnings between societies and individuals, and today, facilitating the ways to reach needs is not effective in eliminating the problem of inequality in income distribution. Many factors and types of income distribution that affect income distribution have been the subject of study for schools of economic thought and economic thinkers since the beginning of economic history. In an economy, it is necessary to minimize the problem of income inequality in order for individuals to live together and earn profits and not to decrease the level of welfare in the economy. It is important for economies to gain a large volume in the world market. In order to gain a place in the world market, it is necessary to produce diversified goods that provide competitive advantage and include intensive technology and information. It is possible to measure the knowledge, technology and quality in the produced goods with the economic complexity index.Accordingly, in this study, the relationship between the economic complexity index (ECI) and income inequality was examined by considering the data between 2000 and 2020 in OECD countries. In the model, the research variable was chosen as the economic complexity index. As the dependent variable, the Gini coefficient of OECD countries; The independent variables were selected as gross domestic product, trade openness rate and the ratio of foreign direct investments in OECD countries to gross domestic product, analysis and tests were applied. The analyzes and tests used are respectively; cross-section dependency test, homogeneity test, panel unit root analysis, panel time series analysis (long-term homogeneity –Hausman- test), pooled mean group (PMG) estimator and Dumitrescu – Hurlin (2012) panel causality tests. According to the results of the cross-sectional dependence and homogeneity test, no dependency was found between the variables in the model, and it was concluded that the variables were stationary according to the panel unit root analysis. According to the panel time series analysis, every 1% increase in the long-term economic complexity index, trade openness rate and the share of foreign direct investments in gross domestic product within the framework of OECD countries is the gini coefficient, respectively; It was observed that it decreased by 0.029%, 0.043%, and 0.027%. As a result of the 1% increase in the gross domestic product in the long term, it was observed that the gini coefficient increased by 0.021%. According to panel time series analysis, it has a homogeneous structure in the long term and does not change from unit to unit. According to the results of the panel causality analysis, it was concluded that there is a two-way causality relationship between the economic complexity index, gross domestic product and trade openness ratio and the gini coefficient in OECD countries. It has been observed that there is no causal relationship between the share of foreign direct investments in gross domestic product and the gini coefficient.
Income refers to the income obtained from the goods and services produced in an economy in a certain period. There are many factors in the economy that affect the distribution of earnings between societies and individuals, and today, facilitating the ways to reach needs is not effective in eliminating the problem of inequality in income distribution. Many factors and types of income distribution that affect income distribution have been the subject of study for schools of economic thought and economic thinkers since the beginning of economic history. In an economy, it is necessary to minimize the problem of income inequality in order for individuals to live together and earn profits and not to decrease the level of welfare in the economy. It is important for economies to gain a large volume in the world market. In order to gain a place in the world market, it is necessary to produce diversified goods that provide competitive advantage and include intensive technology and information. It is possible to measure the knowledge, technology and quality in the produced goods with the economic complexity index.Accordingly, in this study, the relationship between the economic complexity index (ECI) and income inequality was examined by considering the data between 2000 and 2020 in OECD countries. In the model, the research variable was chosen as the economic complexity index. As the dependent variable, the Gini coefficient of OECD countries; The independent variables were selected as gross domestic product, trade openness rate and the ratio of foreign direct investments in OECD countries to gross domestic product, analysis and tests were applied. The analyzes and tests used are respectively; cross-section dependency test, homogeneity test, panel unit root analysis, panel time series analysis (long-term homogeneity –Hausman- test), pooled mean group (PMG) estimator and Dumitrescu – Hurlin (2012) panel causality tests. According to the results of the cross-sectional dependence and homogeneity test, no dependency was found between the variables in the model, and it was concluded that the variables were stationary according to the panel unit root analysis. According to the panel time series analysis, every 1% increase in the long-term economic complexity index, trade openness rate and the share of foreign direct investments in gross domestic product within the framework of OECD countries is the gini coefficient, respectively; It was observed that it decreased by 0.029%, 0.043%, and 0.027%. As a result of the 1% increase in the gross domestic product in the long term, it was observed that the gini coefficient increased by 0.021%. According to panel time series analysis, it has a homogeneous structure in the long term and does not change from unit to unit. According to the results of the panel causality analysis, it was concluded that there is a two-way causality relationship between the economic complexity index, gross domestic product and trade openness ratio and the gini coefficient in OECD countries. It has been observed that there is no causal relationship between the share of foreign direct investments in gross domestic product and the gini coefficient.
Açıklama
Anahtar Kelimeler
Ekonomi, Economics
