Bayesian model average method: An application on employment rate

Abstract

In this study, Bayesian model averaging method, which is used to decrease the model uncertainty and to determine the importance levels of the independent variables in the model, was explained. In addition, with the help of sectoral capacity utilization rate data between January 2007 and August 2018, the Bayesian model average method was used to determine the manufacturing sectors that affect the employment rate. As a result of the analyzes, it is concluded that the sectors that are the most effective on the employment rate are the manufacture of beverages, the manufacture of textiles, the production of other non-metallic mineral products and the furniture manufacturing sectors.

Keywords

• Bayesian model averaging,employment rate,the capacity utilization rate,model uncertainty

Bayesci model ortalaması yöntemi: İstihdam oranı üzerine bir uygulama

Abstract

Bu çalışmada; Ocak 2007- Ağustos 2018 ayları arasındaki sektörel kapasite kullanım oranı verileri yardımıyla, istihdam oranını etkileyen imalat sektörlerinin belirlenmesi için Bayesci model ortalaması yöntemi kullanılmıştır. Ayrıca model belirsizliğinin giderilmesi ve modelde yer alan bağımsız değişkenlerin, önem düzeylerinin belirlenmesi de amaçlanmıştır. Regresyon analizi, değişken seçimi, belirsizlik kavramlarına değinilmiş, Bayesci model ortalaması yöntemi açıklanmıştır. Yapılan analizler sonucunda istihdam oranı üzerinde en etkili olan sektörlerin; içeceklerin imalatı, tekstil ürünlerinin imalatı, diğer metalik olmayan mineral ürünlerin imalatı ile mobilya imalatı sektörleri olduğu sonucuna ulaşılmıştır.

Keywords

• Bayesci model ortalaması,istihdam oranı,kapasite kullanım oran,model belirsizliği

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