China's Optimal Industrial Structure:Theoretical Model and Econometric Estimation

With analysis of producer's and factor supplier's dual optimization motives,this paper developed an optimal nominal output growth rate model that can conduct quantified estimation.Result of estimation of China's optimal industrial structure between1992 and 2009 indicates that optimal nominal output growth rate model has successfully quantified the impact of major events occurring in the process of China's economic operation on the level of deviation between actual industrial structure and optimal industrial structure.Quantitative indicators involved in this model can provide industrial policy instruments for the Chinese government in developing and adjusting industrial structure targets,optimizing resource allocation and advancing industrial structure optimization and upgrade.

Embodied energy consumption and carbon emissions evaluation for urban industrial structure optimization

Cities are the main material processors asso- ciated with industrialization. The development of urban production based on fossil fuels is the major contributor to the rise of greenhouse gas density, and to global warming. The concept of urban industrial structure optimization is considered to be a solution to urban sustainable develop- ment and global climate issues. Enforcing energy con- servation and reducing carbon emissions are playing key roles in addressing these issues. As such, quantitative accounting and the evaluation of energy consumption and corresponding carbon emissions, which are by-products of urban production, are critical, in order to discover potential opportunities to save energy and to reduce emissions. Conventional evaluation indicators, such as ＂energy consumption per unit output value＂ and ＂emissions per unit output value＂, are concerned with immediate consumptions and emissions; while the indirect consump- tions and emissions that occur throughout the supply chain are ignored. This does not support the optimization of the overall urban industrial system. To present a systematic evaluation framework for cities, this study constructs new evaluation indicators, based on the concepts of ＂embodied energy＂ and ＂embodied carbon emissions＂, which take both the immediate and indirect effects of energy consumption and emissions into account. Taking Beijing as a case, conventional evaluation indicators are compared with the newly constructed ones. Results show that the energy consumption and emissions of urban industries are represented better by the new indicators than by conventional indicators, and provide useful information for urban industrial structure optimization.

Does the Digital Economy Optimize Tourism Industry Structure?Effects and Mechanisms Based on Quantile Regression and Threshold Modeling

A comprehensive evaluation index system is constructed,and the entropy weight TOPSIS method isused to measure the optimization level of the digital economy and tourism industry structure of 30 provinces inChina from 2012 to 2021.Moreover,models such as quantile regression and panel threshold are used to explorethe influence of the digital economy(DIG)on the optimization of the tourism industry structure(TIS)as well as itstransmission mechanism.The study reveals that DIG significantly promotes TIS,which remains valid after endogeneity and robustness tests;the impact of DIG on TIS exhibited a“U-shape”effect that first decreases and thenincreases,and its highest significance is at the 90%quartile level.Threshold model tests revealed a nonlinearthreshold effect with DIG and tourism total factor productivity(TTFP)as a single threshold and tourism technological progress index(TECH)as a double threshold,and the second threshold has the largest effect of 0.163.Mechanism analysis found that the mediating impact of the DIG on the TIS was mediated by increasing the TTFP,and the TECH accounted for the highest proportion of 12.15%.Regional analysis revealed that the role of DIG onthe TIS is Central>East>West>Northeast,and the empowering effect is more significant in the high digital economylevel area and the high tourism industry structure optimization area.