Estimation of Effect on Gross Domestic Product of Production Factors Using CES and Translog Production Functions: An Application to China Economy

Abstract In this paper, we investigate the effect on economic growth (GDP) for China’s economy with capital, labor and energy input factors by using CES production function and Translog production function. The empirical findings of the study showed that CES, consisting of capital and labor factors, is less efficient than the Translog function consisting of capital, labor and energy input factors for GDP estimation.The Ridge regression method is used to the parameter estimation of Translog production function using historical data because there is collinearity between variables. Then, based on the fitted Translog production model including capital, labor and energy input factors, the results of the output elasticities for each of the factors and the substitution elasticities between input factors have been dynamically estimated. To predict the future economic growth of the China economy, the inputs of Translog production model are predicted by using Holt-Winter’s method. The elasticities of the output of all input factors are positive. According to degrees of the effect on GDP, we can list the factors as labor, capital and energy, respectively. This situation represents the China economy is labor and capital intensive.