Özet:

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.

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