Summary:
In the context of China's “dual carbon” strategy, firms increasingly face forward-looking transition risks arising from potential asset stranding and earnings uncertainty during the low-carbon transition. Existing studies typically measure transition risk using historical carbon emissions or emission intensity. However, such backward-looking indicators fail to capture the dynamic alignment between firms' future decarbonization paths and policy targets. Meanwhile, investors have begun to incorporate firms' low-carbon transition performance into asset allocation decisions, and net-zero portfolios have emerged as an important tool for managing transition risk. Against this background, this study develops a forward-looking measure of corporate transition risk and examines the impact on firms' implied cost of capital. Specifically, we construct the Duration of Retention (DOR), defined as the number of years a firm is expected to remain in a dynamically constructed net-zero portfolio from a base year to 2060. A shorter DOR indicates higher forward-looking transition risk. To construct this measure, we first establish a carbon budget path consistent with China's “dual carbon” targets. We then estimate firms' future emissions based on historical emission trends and scenario projections consistent with the Paris Agreement. Based on these forecasts, firms are ranked according to predicted emissions and selected into the net-zero portfolio subject to the carbon budget constraint. The cumulative number of years a firm remains in the portfolio constitutes its DOR. This approach captures the deviation between firms' projected emission paths and policy-consistent trajectories, thereby providing a forward-looking assessment of transition risk. Using a sample of Chinese A-share listed firms from 2020 to 2024, we examine the relationship between DOR and firms' implied cost of capital (ICC), which serves as a proxy for investors' expected returns. Carbon emissions data are obtained from the S&P Trucost database, financial data from the CSMAR database, and analyst forecasts from the Wind database. ICC is estimated using multiple valuation models, including PEG, MPEG, Gordon, OJ model, and a composite indicator called CICC. The empirical results reveal a significant negative association between DOR and ICC. Firms with shorter DOR, indicating higher transition risk, face higher costs of equity, suggesting that investors require higher risk premia for firms with weaker decarbonization prospects. This finding remains robust across alternative specifications, including the use of analyst forecasts and additional robustness checks. Further analysis reveals that DOR affects ICC through three channels: asset impairment losses, greenwashing behavior, and agency conflicts. Firms with higher transition risk are more likely to experience asset impairments, engage in greenwashing, and exhibit more severe agency conflicts, all of which increase perceived risk and raise the cost of equity. Heterogeneity analyses indicate that the impact of DOR on ICC varies across institutional environments and firm characteristics. The effect is more pronounced for state-owned enterprises, firms that do not disclose carbon-related information, and firms located in regions with weaker environmental governance. These findings highlight the roles of ownership structure and information transparency in shaping the pricing of transition risk. This study contributes to the literature in several ways. First, it develops a forward-looking measure of transition risk based on the net-zero portfolio framework, addressing the limitations of traditional static indicators. Second, it aligns the construction of net-zero portfolios with China's “dual carbon” targets, enhancing policy relevance. Third, it provides empirical evidence on the pricing of forward-looking transition risk in the cost of equity. Fourth, it identifies the channels through which transition risk affects capital costs, offering new insights into the mechanisms of climate risk pricing. Based on these findings, we propose several policy implications. Improving carbon information disclosure can reduce information asymmetry and enhance pricing efficiency. Strengthening regional environmental governance can mitigate institutional disparities and improve the effectiveness of climate risk pricing. In addition, promoting green financial instruments can facilitate capital allocation toward low-carbon sectors. This study has several limitations. Carbon emissions data rely on third-party databases and may be subject to measurement constraints. The assumed decarbonization pathways may deviate from actual policy implementation, and the prediction of future emissions may not fully capture technological progress. Future research could incorporate more granular data, such as green patents, to construct more refined models of emission trajectories.
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