Predicting the capital intensity of the new energy industry in China using a new hybrid grey model
Predicting the capital intensity of the new energy industry in China using a new hybrid grey model
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使用新的混合灰色模型预测中国新能源行业的资本强度
DOI：
10.1016/j.cie.2018.10.012
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发表时间：
2018
影响因子：
7.9
通讯作者：
Zheng Xin Wang
中科院分区：
文献类型：
--
作者：
Hong Hao Zheng;Qin Li;Zheng Xin Wang
资本密集度是反映一个行业生产要素相对变动的重要指标。资本深化的促进作用，即，资本密集度的提高对产业结构转型的积极影响是肯定的。因此，准确预测新能源产业的资本密集度对于促进产业结构转型升级具有重要意义。基于柯布-道格拉斯生产函数，建立了一个描述资本密集度动态特征的产业层面资本-劳动比率（KLR）模型。然后，将非线性灰色伯努利模型（NGBM（1，1））的估计和预测方法与KLR模型相结合，提出了一种新的混合灰色模型，提出了NGBM（1，1）-KLR模型。这样，KLR的经济意义和NGBM（1，1）模型在解决小样本和非线性问题上的优势相互补充，使人们能够更好地预测行业的资本密集度。为了验证该模型的有效性和优越性，采用NGBM（1，1）-KLR模型对我国新能源产业的资本密集度进行了预测，并与GM（1，1）模型和NGBM（1，1）模型的预测性能进行了比较。实证结果表明，NGBM（1，1）-KLR模型比GM（1，1）模型和NGBM（1，1）模型更能准确地预测我国产业的资本密集度。并利用新的混合灰色模型对2017-2020年我国新能源产业资本密集度进行了样本外预测。预测结果表明，中国产业结构将进一步向资本深化方向转型升级。
Capital intensity is an important indicator for reflecting the relative changes of production factors of an industry. The facilitating effect of capital deepening, i.e., the positive impact of the augment of capital intensity, towards the structural transformation of the industry is definite. Therefore, the accurate prediction of capital intensity of the new energy industry is of great significance in facilitating the structural transformation and upgrading of the industry. Based on the Cobb-Douglas production function, an industry-level capital-labour ratio (KLR) model is established to describe the dynamic characteristics of the capital intensity. Then, by combining the estimation and prediction method of the nonlinear grey Bernoulli model (NGBM(1, 1)) with the KLR model, a new hybrid grey model, i.e., NGBM(1, 1)-KLR model is proposed. In this way, the economic meaning of the KLR and the advantage of the NGBM(1, 1) model in solving small-sample and nonlinear problems are complemented with each other, which enables one to more favourably predict the capital intensity of the industry. To verify the effectiveness and superiority of the proposed model, the NGBM (1, 1)-KLR model is used to predict the capital intensity of the new energy industry in China, and the model is compared with the GM(1, 1) and the NGBM(1, 1) models in the prediction performance. The empirical results show that the NGBM(1, 1)-KLR model can more accurately predict the capital intensity of the industry in China than the GM(1, 1) and the NGBM(1, 1) models. Moreover, the new hybrid grey model is used to carry out the out-of-sample prediction for the capital intensity of the new energy industry in China in the period of 2017–2020. The predicted results demonstrate that the structure of the industry in China will further transform and upgrade towards the capital deepening.