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825Given the substantial overlap between overcapacity sectors and heavily-polluting industries, it is essential to integrate their governance into a unified analytical framework to explore new paths for coordinated control and high-quality development. In recent years, beyond industrial and competition policies, growing academic attention has been directed toward the impact of environmental regulation on firms’ capacity utilization. However, most existing studies rely on mean regression methods, which are insufficient to capture the heterogeneous effects across firms with varying emission intensities, and fail to reveal the underlying mechanisms of capacity reallocation.
This paper integrates data from Chinese industrial firms with pollution emission records, using the emissions trading policy as a quasi-natural experiment. Building upon mean regression analysis, it employs quantile DID and duration-based DDD methods to evaluate the policy’s impact on capacity utilization among heavily-polluting firms. The findings indicate that the policy effectively enhances average capacity utilization through capacity reallocation. In the short term, the policy improves capacity utilization among low-emission firms while constraining that of high-emission firms, leading to the emergence of capacity stratification. In the long run, the policy increases the survival risk for firms with low capacity, thereby inducing capacity exit. Raising the benchmark emission allowance within the policy simultaneously boosts capacity utilization across all firms, yet attenuates the effectiveness of capacity reallocation.
This paper makes the following contributions: First, the proposed quantile DID method enables a more detailed examination of capacity changes across different segments of the distribution, facilitating the analysis of capacity reallocation dynamics among firms. By incorporating duration analysis into the DID framework, it offers a novel approach to assess whether emissions trading has triggered the exit of heavily-polluting capacity. Second, it reinterprets the mechanisms through which environmental regulation improves capacity utilization, emphasizing the role of resource reallocation. Unlike prior studies, it finds that improvements result primarily from selective resource shifts rather than uniform gains across all firms. Third, it reveals that both emissions trading and emission quotas improve average utilization. However, emissions trading reallocates capacity and market share across firms with varying emission intensities, fostering survival-based restructuring; while emission quotas enhance utilization uniformly, without triggering inter-firm structural shifts. These findings offer valuable guidance for selecting effective market-oriented environmental policies.
