This statistic depicts the year-on-year growth rate of the gross domestic product of Xinjiang Uygur Autonomous Region in China from 2000 to 2023. In 2023, Xinjiang's GDP value grew by 6.8 percent from the previous year.

Population: Natural Growth Rate: Xinjiang data was reported at 0.093 % in 2023. This records an increase from the previous number of 0.077 % for 2022. Population: Natural Growth Rate: Xinjiang data is updated yearly, averaging 1.086 % from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 1.217 % in 2000 and a record low of 0.056 % in 2021. Population: Natural Growth Rate: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Natural Growth Rate: By Region.

Energy-based economic development brings about some environmental problems, and as China’s economy shifts from rapid growth to high-quality development, the implementation of environmental regulation is crucial to achieving environmental protection and high-quality economic development. Based on the panel data of 14 prefectures and cities from 2000 to 2018 in Xinjiang, this study explored the impact of environmental regulation on high-quality economic development by constructing a comprehensive evaluation index system and using entropy method and Tobit regression model. The results show that 1) overall, each 1% increase in environmental regulation is associated with a 0.037% rise in high-quality economic development level; 2) regionally, each 1% increase in environmental regulation is associated with a 0.119% rise in high-quality economic development level in northern Xinjiang, but the effect on the southern Xinjiang is not significant; 3) each 1% increase in environmental regulation, the level of high-quality economic development decreased by 0.034% from 2000 to 2010 and increased by 0.061% from 2011 to 2018. In general, this study adds to the theoretical and empirical study on the influence of environmental regulation on high-quality economic development while providing a methodology for other economies to assess the relationship between the two.

Land Area Developed: Year to Date: Xinjiang data was reported at 4,997.128 sq m th in Dec 2010. This records an increase from the previous number of 4,465.285 sq m th for Nov 2010. Land Area Developed: Year to Date: Xinjiang data is updated monthly, averaging 1,615.600 sq m th from Apr 1999 (Median) to Dec 2010, with 127 observations. The data reached an all-time high of 7,136.500 sq m th in Dec 2005 and a record low of 0.000 sq m th in Feb 2010. Land Area Developed: Year to Date: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKD: Land Purchase and Development.

Since the implementation of China’s Western Development Policy, Xinjiang has experienced rapid socio-economic development and significant changes in its land use patterns. As an important factor in agricultural production, farmland is of crucial for realizing the rural revitalization strategy. Based the theoretical mechanisms of farmland use transformation, this study selected five periods of land use and socioeconomic data from 2000, 2005, 2010, 2015, and 2018 to study the spatial and temporal evolutionary characteristics of farmland use transformation in Xinjiang since China’s Western Development Policy. We then explored the driving mechanisms using an optimal geographic detector model based on parameters. The results showed that (1) Xinjiang’s farmland use transitioned toward large scale and multifunctionality, and the transition characteristics are mainly of fluctuating growth type. The spatial transformation and functional transformation characteristics were generally consistent in spatial distribution. (2) There was a spatial agglomeration in the transformation, which was concentrated in the economic zone of the northern slope of Tianshan Mountain, the Yili River Valley and Kashgar region. The concentration of functional transformation of farmland has increased, but the spatial transformation of farmland has weakened. (3) The role of influencing factors on the transformation of farmland use differed with periods. Finally, the study concluded that the functional transformation of farmland in Xinjiang since China’s Western Development Policy is still at the stage of mainly production function. We suggest that the protection of farmland in Xinjiang in the New Western Development period should be achieved by promoting the transformation of the function of farmland. The findings of this study provide decision-making assistance for the management of farmland use in Xinjiang during the New Western Development period and are an effective tool for achieving the goals of sustainable farmland use and agricultural and rural modernization.

Population: Household Registration: Death Rate: Xinjiang: Urumqi data was reported at 8.630 ‰ in 2018. This records a decrease from the previous number of 15.360 ‰ for 2017. Population: Household Registration: Death Rate: Xinjiang: Urumqi data is updated yearly, averaging 3.430 ‰ from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 15.360 ‰ in 2017 and a record low of 2.660 ‰ in 2011. Population: Household Registration: Death Rate: Xinjiang: Urumqi data remains active status in CEIC and is reported by Urumqi Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

Xinjiang: FAI: excl Rural Household: TI: SG: Research and Experimental Development data was reported at 418.090 RMB mn in 2017. This records an increase from the previous number of 117.030 RMB mn for 2016. Xinjiang: FAI: excl Rural Household: TI: SG: Research and Experimental Development data is updated yearly, averaging 120.530 RMB mn from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 418.090 RMB mn in 2017 and a record low of 0.750 RMB mn in 2011. Xinjiang: FAI: excl Rural Household: TI: SG: Research and Experimental Development data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Investment – Table CN.OD: Fixed Asset Investment: Annual: Xinjiang.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Characteristic indicators of star-rated hotel operational efficiency network.

Real Estate Investment: Land Development: Xinjiang data was reported at 1,129.500 RMB mn in 2009. This records a decrease from the previous number of 1,786.790 RMB mn for 2008. Real Estate Investment: Land Development: Xinjiang data is updated yearly, averaging 432.730 RMB mn from Dec 1995 (Median) to 2009, with 13 observations. The data reached an all-time high of 1,786.790 RMB mn in 2008 and a record low of 92.080 RMB mn in 1996. Real Estate Investment: Land Development: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKA: Real Estate Investment: Land Development.

Land Area Developed: Xinjiang data was reported at 4,997.128 sq m th in 2010. This records a decrease from the previous number of 6,754.020 sq m th for 2009. Land Area Developed: Xinjiang data is updated yearly, averaging 3,823.999 sq m th from Dec 1996 (Median) to 2010, with 15 observations. The data reached an all-time high of 7,644.769 sq m th in 2008 and a record low of 264.198 sq m th in 1996. Land Area Developed: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKD: Land Purchase and Development.

R & D: Expenditure: Xinjiang data was reported at 11,551.775 RMB mn in 2023. This records an increase from the previous number of 9,098.491 RMB mn for 2022. R & D: Expenditure: Xinjiang data is updated yearly, averaging 3,300.310 RMB mn from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 11,551.775 RMB mn in 2023 and a record low of 259.514 RMB mn in 1999. R & D: Expenditure: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OS: Research and Development: Expenditure: Region.

The GCMs dataset used in this dataset is CMIP3 comparison plan data (A1B (Medium Carbon Emissions, Global Common Development Scenarios that Focus on Economic Growth), A2 (High Carbon Emissions, Focus on Regional development scenarios for economic growth) and B1 (low carbon emissions, global common development scenarios that emphasize environmentally sustainable development) from the 24 GCM outputs in IPCC AR4 provided by PCMDI. This dataset uses the Delta method for downscaling, uses the 20C3M dataset from 1961 to 1990 as a reference, and uses the SRES dataset from 2010 to 2099 as the future scenario.

Accurately grasping the spatial network correlation structure of operational efficiency in star-rated hotels and its influencing factors is of great significance for promoting high-quality coordinated development of star-rated hotels and the regional tourism reception industry. Using a comprehensive approach integrating the Super-DEA model, modified gravity model, and social network analysis to explore the evolving characteristics of spatial network structure in operational efficiency of provincial star-rated hotels in China from 2013 to 2022, and their underlying mechanisms. The results indicate that: (1) During the study period, the average operational efficiency of star-rated hotels in China was 0.618, with spatial efficiency values showing a distribution pattern of "Eastern > Central > Western > Northeastern". (2) The spatial correlation network of operational efficiency among provincial star-rated hotels in China overall exhibits characteristics of densification, hierarchical structure, and reinforcement. Provinces such as Beijing, Tianjin, Shanghai, and Jiangsu in the eastern region play central roles as "central actors" in the network, while provinces in the western and northeastern regions such as Heilongjiang, Tibet, and Xinjiang play roles as "passive actors" in the spatial network. (3) Members of the “Net benefit” and “Two-way spillover” are primarily from the eastern and some central provinces, while members of the “Net overflow” are mainly from the northeastern and western provinces. (4) Factors such as economic development level, residents’ consumption level, and distance from provincial capital cities collectively drive the evolution and optimization of the spatial network structure of operational efficiency among provincial star-rated hotels in China. This study not only enriches the research findings on hotel operational efficiency but also provides a reference for constructing a cross-regional collaborative mechanism to enhance the operational efficiency of star-rated hotels.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Scientific Research and Development, Technical Service: Xinjiang: Urumqi data was reported at 106.300 Prev Year=100 in 2018. This records an increase from the previous number of 98.500 Prev Year=100 for 2017. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Scientific Research and Development, Technical Service: Xinjiang: Urumqi data is updated yearly, averaging 110.800 Prev Year=100 from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 122.900 Prev Year=100 in 2011 and a record low of 92.900 Prev Year=100 in 2010. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Scientific Research and Development, Technical Service: Xinjiang: Urumqi data remains active status in CEIC and is reported by Urumqi Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Index: TI: Scientific Research and Development, Technical Service.

The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces.

R & D: Number of Person: Xinjiang data was reported at 29.996 Person th in 2023. This records an increase from the previous number of 21.838 Person th for 2022. R & D: Number of Person: Xinjiang data is updated yearly, averaging 14.109 Person th from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 29.996 Person th in 2023 and a record low of 4.156 Person th in 2000. R & D: Number of Person: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OS: Research and Development: No of Person: Region.

Since the issuance of the "Guiding Opinions on Vigorously Developing Sports Tourism" in 2016, the integration of sports and tourism has become a strategy in regional economic development. It creates new economic growth points, enhances local images, and promotes cultural communication. In the context of the "Tourism Makes Xinjiang Thrive" strategy, quantitatively investigating the integration of the sports and tourism industries helps people to better understand their interaction which can serve as the valuable input in policy-making for the comprehensive development of a region. This paper uses entropy weight method, stochastic frontier analysis and coupling coordination model to quantitatively analyze the effect of sports tourism industry integration in Xinjiang from the perspective of integration path. Meanwhile, the Dagum Gini coefficient and nuclear density estimation were used to analyze the regional differences and dynamic evolution of industrial integration quality. The result shows that (1) The sports and tourism integration quality in Xinjiang has not reached the optimal goal of complete integration. In the process of mutual industrial promotion, tourism promotes a higher degree of integration with the sports industry. (2) The industrial integration quality shows a phenomenon of “imbalance and inadequacy” among the regions. The regions with high quality of industrial integration were Urumqi, Ili, Kashgar, Altay and Changji, which have rich sports tourism resources. (3) The overall spatial difference in the quality of industrial integration presented a fluctuation downtrend. The difference between the tourism industrial belts was very significant.

Adjusted Seroprevalence of HEV antibodies in the Chinese population in the national sample, 2005–2006, by gender, occupation, ethnic origin, geographic area, economic development areas and age groups.