CES VE TRANSLOG ÜRETİM FONKSİYONLARI KULLANILARAK ÜRETİM FAKTÖRLERİNİN GDP ÜZERİNDEKİ ETKİSİNİN KESTİRİMİ: ÇİN EKONOMİSİ İÇİN BİR UYGULAMA

Öz

Bu çalışmada, CES üretim fonksiyonu ve Translog üretim fonksiyonunu yardımıyla Çin ekonomisine ait sermaye, emek ve enerji girdi faktörlerinin ekonomik büyüme (GSYİH) üzerindeki etkisi araştırılmaktadır. Çalışmanın ampirik bulgularına göre, CES üretim fonksiyonu kullanılarak elde edilen GSYİH verilerinin Translog üretim fonksiyonu kullanılarak elde edilen kestirimlerden daha az verimli olduğu söylenebilir. Modelde yer alan değişkenler arasında çoklu doğrusal bağıntı problemi mevcut olduğu için parametre kestiriminde Ridge regresyon tekniği kullanılmıştır. Daha sonra sermaye, emek ve enerji girdi faktörlerini içeren uygun Translog üretim modeline dayalı olarak, faktörlerin her biri için çıktı esnekliklerinin sonuçları ve girdi faktörleri arasındaki ikame esnekliklerinin sonuçları dinamik olarak tahmin edilmiştir. Ayrıca, Çin ekonomisinin gelecekteki ekonomik büyümesini tahmin etmek için Translog üretim modelinin girdileri Holt-Winter’s yöntemi kullanılarak tahmin edilmiştir. Tüm girdi faktörlerinin çıktı esneklikleri pozitif olup, girdi faktörlerini GSYİH üzerindeki etki derecelerine göre, sırasıyla, emek, sermaye ve enerji olarak sıralayabiliriz. Bu durum Çin ekonomisinin emek ve sermaye yoğun olduğunu göstermektedir.

Anahtar Kelimeler

• Gayri Safi Yurtiçi Hasıla
• CES Üretim Fonksiyonu
• Translog Üretim Fonksiyonu
• Holt-Winter’s yöntemi
• Ridge regresyon

ESTIMATION OF EFFECT ON GROSS DOMESTIC PRODUCT OF PRODUCTION FACTORS USING CES AND TRANSLOG PRODUCTION FUNCTIONS: AN APPLICATION TO CHINA ECONOMY

Öz

In this study, the effects on the economic growth (GDP) of capital, labor and energy input factors for the Chinese economy are investigated with the help of the CES and Translog production functions. According to the empirical findings of the study, it can be said that the GDP data obtained using the CES production function are less efficient than the estimates obtained using the Translog production function. The Ridge regression technique was used for parameter estimation of Translog production model since there is multicollinearity between the variables in the model. The output elasticities and the substitution elasticities between each input factor are then dynamically estimated, based on the appropriate Translog production model that includes the capital, labor and energy input factors. In addition, the inputs of the Translog production model were estimated using the Holt-Winter's method to predict the future economic growth of the Chinese economy. Consequently, output elasticities of all input factors are positive, and we can rank the input factors as labor, capital and energy according to their degree of impact on GDP, respectively. This shows that the Chinese economy is labor and capital intensive.

Anahtar Kelimeler

• Gross Domestic Product
• CES production function
• Translog production function
• Holt-Winter’s method
• Ridge Regression

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