The industry selection effect arising from the impact of environmental regulation on Foreign Direct Investment (FDI) in China is heterogeneous. Based on an extension of the principal-agent Game Theory, this paper constructs a system of simultaneous equations to study the dynamic effect of environmental regulation on Chinese FDI in terms of industry selection decisions, by utilizing panel data from 2005 to 2014 in China. Results of this study show that environmental regulation promotes the technological innovation within the Chinese industry and attract greater foreign capital investment. While the influx of capital will furthermore boost technological progress, a benign interaction effect may be observed between technological innovation and foreign capital. The implementation of the new environmental policy will intensify game strategies between managers and enterprises. Enhanced co-ordination activity within industrial organizations will generate more effective organizational and technological innovation, thereby attracting a large flow of FDI, Phase analysis suggests that the policy of market borrowing technologies is more effective. In addition, industry sample results highlight a compensation effect of technological innovation in the raw materials and manufacturing industry, though environmental regulation of high-tech industries will generate an offset effect with respect to technological innovation. Industries that show the strongest technological and innovative prospects will prove the most attractive for foreign capital investment.

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Purpose Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations. Design/methodology/approach The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches. Findings The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect. Practical implications The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity. Originality/value The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.