{'fraction_non_alphanumeric': 0.022672064777327937, 'fraction_numerical': 0.016194331983805668, 'mean_word_length': 5.505263157894737, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Research on China’s Inter-Provincial Total Factor Productivity Under the Resources and Environment Constraints: Analysis Based on GML Index Method*

Based on the theory of total factor productivity, the directional distance function and the GML index were used to study the changes of total factor productivity in China's 30 provinces and cities from 2004 to 2016 under the constraints of resources and environment. The study found that after incorporating resources and environmental factors into the TFP research framework, the TFP in various regions was reduced to varied degrees. TFP growth in the eastern, central, and western regions decreased by 0.02, 0.29, and 0.1 per cent, respectively, and the national average decreased by 0.1 per cent; panel data regression results show that the level of economic development, endowment structure, resource factors, and foreign investment factors have a significant negative impact on total factor productivity, while industrial structure and technological factors have significant positive effects during the selected sample period. Among them, the largest effect on total factor productivity is the industrial structure and resource factors, and the smallest is the endowment structure.