As digital technologies and digital industries are advancing, digital economy becomes a new drive to a high-quality economic development. Study on their relation is of strategic importance in promoting provincial high-quality economic development. This paper, by means of China’s 30 provinces/cities’ 2014 to 2020 panel data, uses entropy weighted TOPSIS to comprehensively score digital economy and high-quality economic development, applies spatial auto-correlation test and hotspot to analyze their spatial distribution on the basis of their temporal-spatial instability, and employs GTWR model to discuss their temporal-spatial response law between digital economy and China’s provincial high-quality economic development, and analyzes the path of digital economy to a provincial high-quality economic development. Digital economy has a strong spatial auto-correlation with high-quality economic development, with their hotspots concentrating on central and eastern China, and cold spots on western China. The spatial concentrating intensity of digital economy is diminishing while that of the high-quality development is maintained at a high level. Digital economy can outstandingly promote a high-quality economic development with impacting factor of temporal-spatial heterogeneity, showing a declining trend from south-eastern coastal to northwestern continent spatially, and a diminishing provincial difference to regional coordinated development. Digital economy variably drives the sub indicators of high-quality economic development, weakest on innovative development. This paper presents suggestions on further advancing regional coordinated development of digital economy in western China, promoting high-quality economic development through innovation, and promoting provincial high-quality development through digital economy. 

Study of impacts of technical innovation on green total factor productivity from perspective of industrial agglomeration is of strategic significance to promoting a coordinated development between technical innovation and green economy in China and keeping same pace between industrial development and environmental protection. This paper, based on 2008 to 2019 provincial panel data of Chinese provinces (cities), uses SBM model and GML indicator to estimate the dynamic changes of green total factor productivity in 30 Chinese provinces (cities), and applies threshold regression model and adjusting effect model to discuss the threshold and adjusting effects of financing & manufacturing conglomeration on technical innovative achievements and green total factor productivity. Results show a strikingly positive coefficient of technical innovative achievements on green total factor productivity, a positive adjusting and sole threshold effect of financing conglomeration on technical innovative achievement and green total factor productivity, and a negative adjusting of manufacturing conglomeration, and an outstandingly adjusting of local public budget, residents usable income per capita and foreign investment on green total factor productivity. This paper presents suggestions on focusing on their match between technical innovative achievements and green economic development, enabling digital financing to break the spatial barrier of financing, converting manufacturing to a quality conglomeration, properly allocating financing resources in environmental protection sector, and boosting supervision of foreign investment in environmental protection.

The objectives of this paper are to evaluate industrial structural rationalization and escalation of the Yellow River Basin, study the factors of industrial structural development, and provide suggestions for optimizing industrial structure. According to 2009-2018 three industries production data and employment in the Yellow River Basin, this paper uses Hamming osculation and Moore structural index to estimate industrial rationalization and escalation, and applies improved SIR model to study the optimization factors under unmarked grid. Geographically, Hamming osculation between industrial production structure and employment structure is highest in the down-reach, followed by the middle- and then the upper-reach, average at 0.783 4 in the upper-reach, 0.795 6 in the middle- and 0.817 6 in the down-reach. Temporally, rationalization is gradually rising with an escalating industrial developing trend in general with variance among the three reaches. Industrial structural escalation is highest up to 8.792 0 in the down-reach, 6.296 0 in the middle- and 6.305 5 in the down-reach. Industrial structural changing rate has increased by 14.297 4(from 1.597 7 in 2009 to 15.895 1 in 2018) in the down-reach, by 9.183 4 in the middle- and by 9.536 9 in the upper-reach, displaying a pattern of rising upper-reach, fluctuating middle-reach and leading down-reach. Adjusting industrial influence has little impact on industrial structural optimization, if industrial initial proportion, industrial optimization success ratio and failure ratio keep constant. However, industrial optimization may be largely improved if it is possible to increase industrial optimization success rate and the re-optimization possibility of failed industries. This paper presents suggestions on boosting industrial optimization, upgrading failed industries, using "the Belt and Road" policy to intensity innovation in the middle- and upper-reach, and focusing on information technology and industrial cooperation in the down-reach.

This paper, taking environmental regulation intensity as threshold variable, uses threshold model to study the impact of two-way FDI on China's carbon emission in order to check if there is carbon pollution paradise effect from IFDI（inward foreign direct investment） and OFDI（outward foreign direct investment） under different environmental regulation intensities. The result is no. IFDI plays a key role in carbon emission in China varying with environmental regulation intensities; carbon emission will reduce as environmental regulation intensities tighten. OFDI's impact on carbon emission shows an upside-down U shape that carbon emission will soar if OFDI expands when environmental regulation intensities descend, and that carbon emission will be restrained when environmental regulation intensities tighten. Among carbon emission reduction effects from technical overflow, IFDI exceeds OFDI in that China is at the initial stage of OFDI, but at middle to late stage of actual use of IFDI.

Coal as China's energy security cornerstone plays a key role in economy along with its radiation to correlated industries. This paper uses nations input/output 2002 to 2015 to dynamically analyze the radiation effect between coal industry and its correlated industries. The price model established on input/output table indicates a radiation of coal industry on its correlated industries, with four largely impacted sectors supply and production of electricity and heating, metallurgy and processing, chemicals and industrial minerals on their close economic dependence but a unstable industrial correlation, induction more than influence. The stated-above industries are sensitive to coal price change, especially the electricity and heating production and supply, with sensitiveness up to 0.0029. Diversified suggestions are presented for coal-electricity coalition, coal-steel coalition, coal-chemicals coalition and fossil energy-new energy coalition.

Water, energy and food are three vital resources, their coordinated development provides a basis for the sustainable development of economy and society. This paper establishes an evaluation index system for Water-Energy-Food (WEF), weighted by means of entropy and variation coefficient, and calculates the coordinated development level of WEF system by means of coupling model, which is compared with WEF system by Gray Verhulst model during 2018 to 2027. The result shows a rising comprehensive evaluation index, a high coupling level of WEF system during 2002 to 2017, whose coupling coordination has undergone transition, generally coordinated and highly coordinated, and will keep premium coordination in the period of 2018 to 2027. The energy development level will still be behind water and food. This paper presents suggestions on intensifying energy developing efficiency in order to push a sustainable development of economy.