2023
DOI: 10.3389/fpubh.2023.1122139
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How does national development zone policy affect carbon emissions in China? New evidence from a quasi-natural experiment

Abstract: The expansion of China's development zones has made great contributions to economic development, as well as provided practical guidance for other developing countries to implement development zone policies. However, in the context of global advocacy of low carbon, literature about how the development zone policy affect carbon emissions is poor, especially in China at the urban level. Therefore, this study takes China's development zone policy as a quasi-natural experiment, using the panel data of 285 cities in… Show more

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Cited by 10 publications
(3 citation statements)
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References 79 publications
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“…Evaluating the effects of development zone policies has been an international hot topic in recent years [8,9]. Empirical studies based on samples from both developed and developing countries have not reached consistent conclusions.…”
Section: Effects Of Development Zone Policiesmentioning
confidence: 99%
“…Evaluating the effects of development zone policies has been an international hot topic in recent years [8,9]. Empirical studies based on samples from both developed and developing countries have not reached consistent conclusions.…”
Section: Effects Of Development Zone Policiesmentioning
confidence: 99%
“…To address the endogeneity problem of the model, the core explanatory variables are with a one-period lag [78], which is commonly used in economics management studies and is effective in addressing reverse causality and endogeneity. The results are shown in column (1) of Table 4, where the cross-product term is still significant, which proves the robustness of the regression results.…”
Section: Lagged Explanatory Variablesmentioning
confidence: 99%
“…An inverse causal link between the growth of digitization of companies and carbon release cannot be excluded. To reduce or even eliminate the possible endogeneity problem in the model and its resulting estimation bias, as shown in Table 5, this paper takes Feng et al's [50] approach of adopting the introduction of digitization level's first order lagged section as an instrumental variable for 2SLS regression. The coefficient of digitization level remains positive, proving the robustness of the above results.…”
Section: Empirical Studies 41 Baseline Model Regressionmentioning
confidence: 99%