BRICS-T Ülkelerinde Sağlık Harcamaları ve Ekonomik Büyüme: Panel Veri Analizi

Sağlıklı bir nüfusun daha yüksek verimlilikle çalışacağı ve dolayısıyla daha yüksek katma değer yaratacağı genel kabul görmektedir. Ancak Covid-19 salgınıyla mücadelede de görüldüğü üzere ülkeler sağlık hizmetlerine kolay ve eşit bir şekilde ulaşamamaktadır. Nitekim sağlık harcamalarının ekonomik büyüme üzerindeki etkisinin ülkelerin gelişmişlik seviyelerine göre farklılaştığı ortaya konmaktadır. Bu çalışmada, farklı gelişmişlik seviyelerine sahip BRICS-T ülkeleri ele alınmıştır. Çalışmanın ampirik kısmında değişkenlerin durağanlığını testi etmek amacıyla LLC ve ADF bitim kök testlerinden yararlanılmıştır. Pedroni panel eş bütünleşme testi sonuçlarına göre değişkenler arasında uzun dönem ilişki saptandıktan sonra FMOLS ve DOLS metodları ile uzun dönem katsayı tahmini yapılmıştır. Elde edilen sonuçlar iktisadi beklentiler ile büyük ölçüde örtüşmektedir.

Anahtar Kelimeler:

Sağlık Harcamaları, Ekonomik Büyüme, BRICS-T Ülkeleri, Panel Veri Analizi

Health Expenditures and Economic Growth in BRICS-T Countries: Panel Data Analysis

It is generally accepted that a healthy population will operate at higher productivity and therefore create higher added value. However, as seen in the fight against the Covid-19 epidemic, countries cannot access health services easily and equally. As a matter of fact, it is revealed that the effect of health expenditures on economic growth differs according to the development levels of countries. In this study, BRICS-T countries with different development levels are discussed. In the empirical part of the study, LLC and ADF finite root tests were used to test the stationarity of the variables. After determining the long-term relationship between the variables according to the Pedroni panel cointegration test results, long-term coefficient estimation was made with FMOLS and DOLS methods. The results obtained largely overlap with the economic expectations.

Keywords:

Health Expenditure, Economic Growth, BRICS-T Countries, Panel Data Analysis,

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