Taking China’s environmental “fee-to-tax” reform as a quasi-natural experiment, this paper employs a difference-in-differences (DID) approach to examine the impact of the green tax reform on firms’ cost of equity on a sample of A-share listed firms from 2012 to 2023. The results show that the implementation of the Environmental Protection Tax Law significantly reduced the cost of equity for heavily polluting firms. This finding remains robust after a series of robustness checks. Analyses of the underlying mechanisms reveal that the green tax reform lowered the cost of equity primarily through the channel of “Porter effect.” Moreover, the effect is more pronounced among firms located in the eastern China, those with stronger internal governance, and those operating in a stricter external monitoring environment.

China’s green-finance expansion shifts attention from how much firms disclose to whether transition claims remain credible when verification tightens. Using a 2007–2022 panel of Chinese A-share listed firms (crash-risk measures available through 2021), we measure transition credibility by decomposing firms’ transition signals into verifiable actions, narrative disclosure, and realized environmental outcomes, and we propose a transparent narrative–action gap measure (WordsMinusActions = WordsIndex − ActionIndex) to capture ‘words without deeds.’ Exploiting the staggered rollout of China’s Central Environmental Protection Inspections (CEPI) as a plausibly exogenous increase in verification and enforcement intensity, we find that firms with high pre-CEPI narrative–action gaps experience a sharp increase in stock price crash risk around inspections: NCSKEW rises by about 0.09 in the inspection year and 0.20 in the following year (≈0.24 SD), and DUVOL rises by about 0.04 and 0.10 (≈0.27 SD) relative to low-gap firms. Consistent with enforcement discipline, these high-gap firms subsequently reduce disclosure intensity and increase verifiable green actions, narrowing the narrative–action gap after CEPI. The evidence supports governance that rewards verifiable action and consistency over disclosure volume in markets.

We study whether commodity risk is efficiently priced in the cross-section of US equities. We first provide novel evidence on firm-level risk exposure to up to 42 individual commodities. We then construct a mispricing measure as the realized return less the commodity-risk-implied return, and find that it strongly predicts next-month return reversal beyond the traditional short-term reversal. This commodity-risk-mispricing reversal is substantially stronger among small, less analyst- or media-covered stocks, is weakly associated with investor sentiment, and is less prevalent among firms that engage in commodity hedging. In particular, underpricing among these hedgers often remains persistent and even intensifies after the 2004 financialization of commodity markets. This implies that despite the overall decline in mispricing, financialization has likely introduced more costs than benefits for corporate risk management.

Exploiting China’s 300 billion RMB Special Central Bank Lending Facility for the Clean and Efficient Use of Coal as a quasi-natural experiment across 12,816 firm-year observations from 2018 to 2023, we show that subsidized transition credit increased targeted coal and thermal power firms’ aggregate carbon emissions by 14.18 log points. We establish this backfire as a Financial Jevons Paradox, whereby credit-induced scale expansion overwhelms unit efficiency gains. Although the facility raised total factor productivity and stabilized emission in-tensity, it lowered debt costs, expanded bank loans, and induced production-biased patenting, proving that transition finance requires binding aggregate emission caps.

This paper examines how major artificial intelligence (AI) breakthroughs affect the market pricing of firms’ pre-existing AI capabilities. Using Chinese listed firms’ 2023–2024 AI patents classified with a large language model, we estimate dynamic stock return and volatility responses to the DeepSeek-R1 release. Stronger pre-event AI capabilities are associated with higher post-release returns and greater short-term volatility, with volatility effects persisting longer. Positive return responses concentrate in algorithms and models, not computing infrastructure, while industry applications show later volatility increases without comparable return gains. These findings highlight technology-specific differences between return and volatility responses to AI breakthroughs.

We examine whether and how the cultural background of corporate chairpersons, specifically clan culture, influences firm-to-firm lending decisions. Using hand-collected data on Chinese entrusted loans, a major segment of the country’s shadow banking sector, we find that firms led by chairpersons from prefectures with stronger clan culture are more likely to originate entrusted loans and charge lower spreads. We identify distinct mechanisms governing affiliated versus nonaffiliated transactions. In affiliated lending, our evidence suggests an in-group favoritism channel: culturally embedded chairpersons support affiliated parties despite higher ex-post default risk. Conversely, non-affiliated lending operates via an informational channel, where the positive impact of clan culture is more pronounced when geographic barriers are low, and manifests in larger size dispersion. Overall, our findings highlight the dual role of cultural norms in shadow banking, demonstrating that clan culture facilitates credit allocation while generating sharply different efficiency implications across relationship-based and arm’s-length markets.

We examine whether the characteristics of economically linked firms predict stock returns in the Chinese A-share market. We construct two peer-based signals: a peeraverage (PA) signal that aggregates the characteristics of fundamentally similar firms, and a peer-deviation (PD) signal that summarizes a firm’s characteristic deviations from industry-peer averages. PA captures shared fundamental information, whereas PD benchmarks a firm’s relative position against economically comparable peers. Portfolio sorts, factor-spanning tests, and Fama–MacBeth regressions reveal economically meaningful and statistically significant return predictability for both signals, with generally larger portfolio returns among non-state-owned enterprises. Both signals retain significant incremental predictive power after controlling for the full set of own-firm characteristics and flexible machine-learning forecasts based solely on these characteristics. Changes in both signals also predict future earnings, while return predictability is generally stronger among firms receiving less investor attention, consistent with limited-attention-induced underreaction. These findings highlight the distinct informational and benchmarking roles of economic networks and their predictive value beyond firms’ own characteristics.

We identify choke points in global production networks as industries bridging flows across global value chains. These industries exhibit low substitutability: US firms exposed to Chinese choke points during the 2022 Covid-19 lockdowns experienced large and persistent sales declines. The Red Sea crisis demonstrates how negative shocks to water transport, a single choke point, propagate throughout the global network. This structural fragility is priced in global stock markets: firms in choke point industries earn annualized benchmark-adjusted returns exceeding 6%. The premium compensates for aggregate consumption risk, as downturns in choke point industries predict lower future US and global consumption growth.

This study investigates the relationship between the number of stock concepts and future returns, as well as the economic mechanisms underlying this association. Using novel collected data, we find that stocks with a greater number of concepts earn significantly higher returns in the subsequent month, generating a six-factor adjusted annualized alpha of approximately 9.6% for a long-short portfolio. Although these stocks exhibit higher turnover, return volatility, and investor attention - features commonly associated with speculative concept-driven trading - an analysis of cross-listed AH twin stocks reveals that concept counts do not widen the AH premium. Moreover, the return premium persists for up to 15 months without significant reversal, whereas firms that engage in opportunistic concept-chasing exhibit pronounced long-run reversals, suggesting that the positive concept-return relation is not driven by speculative motives. The higher returns are primarily attributable to strong industrial policy support and sustained above-expectation operating performance. Firms with more concepts are more likely to receive government subsidies and deliver positive earnings surprises, effects that are amplified when their core concepts receive stronger national policy backing. In contrast, firms that pursue concepts lacking substantive business relevance are significantly less likely to obtain government subsidies and fail to achieve above-expectation growth. Regarding investor composition, institutional ownership of high-concept stocks increases modestly, while ownership by government-guided funds rises substantially - particularly for stocks whose core concepts are strongly supported by national industrial policies. Conversely, concept-chasing behavior by listed firms significantly reduces the ownership ratio of government-guided funds. Overall, our findings indicate that concept stocks in China’s capital market are not purely speculative but signal underlying national policies.

Firms frequently overstate digital transformation in public disclosures while committing less in observable investment, a phenomenon known as digital catering. We examine whether digital public financial infrastructure can discipline such symbolic behavior. Using a staggered difference-in-differences design on Chinese A-share listed firms over 2014--2024, we find that exposure to China's e-CNY pilot reduces digital catering by roughly 14% relative to the sample mean. The decline is driven almost entirely by reduced rhetorical digital transformation, while balance-sheet-based digital commitment rises only marginally: the e-CNY pilot is associated with substantially less digital talk, but not with a commensurate increase in digital walk in the short run. The effect operates through lower agency costs and reduced information asymmetry, and follows an amplification--substitution pattern---stronger among digital-sector and accounting-opaque firms, weaker where internal controls and institutional ownership are already strong. The evidence identifies financial-transaction verifiability as a novel source of discipline over corporate cheap talk: CBDC-related infrastructure constrains unsupported symbolic claims without immediately accelerating substantive digital investment.