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Bu çalışmada, Türkiye’de kadınların işgücüne katılımını etkileyen faktörlerin belirlenmesi ve işgücüne katılım oranının farklı istatistiksel metodlar ile modellenmesi hedeflenmiştir. Bu amaçla, 2015-2020 periyodu için İstatistiki Bölge Birimleri Sınıflaması (İBBS) Düzey 1’ de yer alan 12 bölge dikkate alınarak, işgücüne katılım oranı, istihdam oranı, işsizlik oranı ve kadınların işgücüne katılımını etkileyen en önemli faktörler arasında olan eğitim düzeyi değişkenleri dikkate alınarak, tek yönlü rassal etki panel veri modeli kurulmuştur. Ardından, söz konusu belirleyicilerinin aynı zamanda doğrusal olmayan etkilerini de ortaya koymak için 1988-2019 periyodu dikkate alınarak pürüzlülük ceza yaklaşımı ile her bir belirleyicinin işgücüne katılımı oranı üzerindeki etkisi için doğal kübik splayn kullanılarak toplamsal ve kısmi toplamsal modeller kurulmuştur. Kurulan modeller, düzeltilmiş R2, sapma, genelleştirilmiş çaprak geçerlilik ve Akaike bilgi kriteri kullanılarak karşılaştırılmış ve en uygun model seçilmiştir. Yapılan analizler göstermiştir ki, kadınların işgücüne katılım oranını üzerinde işsizlik, istihdam ve nüfus değişkenlerinin aynı zamanda doğrusal olmayan etkileri de söz konusudur.
This study aimed at determining the factors affecting women’s participation in labour in Turkey and modeling their participation in labour by different statistical methods. For this purpose, taking into account the 12 regions listed in Statistical Regional Units Classification (IBBS) Level 1 for the period 2015-2020, taking into account the levels of education variables, which are among the most important factors affecting the participation in labour, the employment rate, the unemployment rate and the participation of women in labour, a one-way racial impact panel data model has been established. Then, to reveal the non-linear effects of those determiners, the 1988-2019 period was taken into account by the flexibility penalty approach and the use of natural cubic splayn for the impact on the participation rate of each determiner in the workforce, the collective and partial collective models were established. Established models, corrected R2, deviation, generalized cross validity and Akaike information criteria are compared and the most suitable model is selected. The analysis has shown that the incidence of unemployment, employment and population variations on women’s participation in labour is also not linear.
In this study, it is aimed to determine the factors affecting the participation of women in the labor force in Turkey and to model the labor force participation rate with different statistical methods. For this purpose, 12 regions included in Statistical Region Units Classification (NUTS) Level 1 for the period of 2015-2020 were taken into consideration. Then, a one-way random effect panel data model was constructed by taking into account the variables of the labor force participation rate, employment rate, unemployment rate and education level, which are among the most important factors affecting women's labor force participation. Then, it is aimed to reveal the nonlinear effects of these determinants. For this purpose, considering the period of 1988-2019, additive and semiparametrik additive models were constructed by using the natural cubic spline for the effect of each determinant on the labor force participation rate with the roughness penalty approach. The constructed models were compared using adjusted R-square, deviation, generalized cross validity and Akaike information criterion, and the most suitable model was selected. These analyzes show that the unemployment rate, employment rate and population variables also have non-linear effects on the female labor force participation rate.
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