Incentives

  • 详情 "Influencing Factors and Incentive Strategies of Individual Participation Mechanism in Carbon Trading: A Carbon Inclusion System Perspective Based on Subject Heterogeneity"
    Against the backdrop of escalating global carbon emission reduction urgency and China’s "dual carbon" goals, individual carbon trading (ICT) has emerged as a key measure to tap into consumer-side emission reduction potential. However, the current ICT mechanism remains in the exploratory stage, plagued by limited access to formal trading channels, strict entry barriers, and low public penetration, only 5 carbon exchanges in China allow individual participation, with fewer than 10,000 total participants. Focusing on mechanism integrity and integrating the carbon inclusive system, this study explores the influencing factors of ICT operation and constructs targeted optimization strategies. Based on Mechanism Design Theory, the Theory of Planned Behavior, and Value-Belief-Norm Theory, a theoretical model covering five core ICT components was established. Using data from 1,200 questionnaires across 15 Chinese cities, multiple linear regression and hierarchical regression were employed to analyze the impacts of institutional fairness, technical usability, social atmosphere, and individual cognition. Results show: (1) Institutional fairness increases quota compliance by 38% through transparent rules; (2) User-friendly technical tools boost engagement by 1.8x, enhancing accounting accuracy and platform efficiency; (3) Social atmosphere moderates the effect of individual cognition on incentive conversion, particularly strongly in rural areas; (4) Individual cognition mediates the relationship between social atmosphere and trading platform efficiency. Additionally, optimizing mechanism components is more critical for long-term operation than single incentives. This study proposes a multi-dimensional optimization framework, providing theoretical and policy references for improving ICT integrity and advancing "dual carbon" goals.
  • 详情 "Forged in stringency: Environmental regulatory diversity and green innovation in emerging market MNEs"
    This study examines how emerging market multinational enterprises (EMNEs) respond to cross-national diversity in environmental regulation. Prior research suggests that internationalization exposes EMNEs to diverse environmental standards and may facilitate regulatory learning, yet offers a limited understanding of the mechanisms through which such exposure translates into green innovation. Drawing on institutional theory, we argue that green innovation is particularly fostered when EMNEs operate across host countries whose environmental regulatory regimes are more stringent than those in the home country, and when such exposure varies across multiple host locations. We theorize that this form of environmental regulatory diversity creates learning pressures and legitimacy incentives that motivate EMNEs to upgrade their environmental capabilities through green innovation. Using panel data comprising 9,362 firm-year observations from 1,088 Chinese MNEs over the period 2008–2021, we find support for our arguments. We further show that these effects are contingent on organizational and institutional conditions, specifically top management teams’ technological expertise and the strength of intellectual property enforcement in home-country locations. These findings advance research on EMNE learning and sustainable innovation under complex global environmental governance.
  • 详情 Less Informative Advice, More Informative Prices
    Less informative strategic advice can produce more informative prices. We study an informed adviser who both trades on his own account and receives compensation linked to the post-report price. Holding private information fixed, we show how promotion can restrain manipulation motivated by trading profits. At sufficiently high reputation, raising compensation enough to eliminate false bad news used to buy cheaply improves market price informativeness in every equilibrium, even though the strategic adviser’s report becomes uninformative. Under further sufficient conditions, always-favourable strategic reporting yields the most informative current prices among equilibria at every interior reputation. We also derive analytical sufficient conditions under which higher reputation lowers the adviser’s expected payoff and worsens prices within the same equilibrium. Financial influencers motivate the joint incentives: a reward for higher prices can counteract the incentive to depress prices before buying, while greater credibility need not benefit its holder.
  • 详情 Delegation under Risk in IPO Pricing: Evidence from China’s Subscription Reform
    This paper develops a delegation-based framework to explain how institutional design shapes pricing incentives under risk. Using China’s 2016 IPO reform—which abolished prefunding requirements and transferred payment obligations from investors to underwriters—as a natural experiment, we show that introducing subscription-payment risk (SPR) renders underwriter’s partial residual claimants with respect to unpaid allocations. Building on Baron’s (1982) delegation model, we argue that the reform amplifies information asymmetry and induces underwriters to adopt more conservative pricing strategies to manage perceived payment risk. Empirically, IPOs exposed to SPR exhibit greater underpricing and lower offer prices, particularly when investor bids reflect stronger valuation pessimism. The effect tends to be less pronounced for reputable underwriters and when foreign institutional investors participate. Overall, the evidence demonstrates how risk redistribution and institutional frictions jointly shape underwriter behavior and pricing efficiency in primary equity markets.
  • 详情 Political Accountability and Local Government Debt: Evidence from China *
    This study investigates how the interaction of political accountability and local officials’ career incentives shapes the market for Municipal Corporate Bonds (MCBs) in China, taking the 2017 local government debt personal responsibility rule as a quasinatural experiment. We develop a stylized incomplete-information bargaining model to analyze how the rule reshapes the bargaining equilibrium by rendering officials’ observable characteristics credible signals of bailout incentives. Using a dataset of prefecture-level MCBs from 2008 to 2020, we empirically test the model’s predictions and focus on separating officials’ incentive effects from their inherent ability. Our core findings show that post-announcement of the rule, each additional year of a local party secretary’s remaining time to retirement, a proxy for bailout incentives, reduces MCB spreads by approximately 2.5 basis points and increases issuance volume by about 2.0%. These effects are significantly amplified in fiscally stressed cities. Notably, under the 2017 rule, cities led by party secretaries with stronger bailout incentives can expand MCB issuance, which is contrary to the rule’s original intent to rein in local borrowing.
  • 详情 Multitracking within a Multitasking Tournament: Evidence and Theory from China
    This paper studies how dividing candidates in a tournament into separate tracks with differentiated performance criteria affects incentives and aggregate outcomes. We exploit China’s Major Function Oriented Zoning plan, which assigns counties to devel-opment or conservation tracks, with the latter de-emphasizing growth indicators. Using a staggered Difference-in-Differences design, we find that prefectures introducing a con-servation track achieved higher aggregate economic performance despite relaxing growth-based evaluation for part of their subordinate counties. To explain this counterintuitive ef-fect, we develop a stylized Tullock contest model that highlights two institutional features: promotion opportunities remain open to officials in both tracks, and counties within the same prefecture continue to interact across tracks. The model further predicts an inverted U-shaped relationship between the size of the conservation track and overall performance, which is supported by empirical evidence.
  • 详情 Maintaining Empire: The Examination System and Secessionist Conflict in Imperial China
    The endurance of empire in China over much of the past two millennia contrasts starkly with the political fragmentation in Europe since the fall of Rome. To explain the persistence of China’s empire, we analyze the role of keju, the imperial civil service examination system. We argue that the systematic implementation of keju from the Song dynasty onward tied local elites to the imperial state, sustaining political integration and reducing secessionist conflicts. Exploiting panel data covering 4,243 grid cells and 22 centuries, we find robust evidence that areas producing more jinshi – the top exam passers – experienced significantly fewer secessionist wars. Our study shows how the examination system created the political incentives for imperial durability.
  • 详情 Do Political Connections Reduce Customer Complaints? Evidence from China's Online Complaint Platform
    Research Question/Issue: This study investigates whether and how political connections affect customer complaints in the Chinese market, using a comprehensive dataset from the country’s largest online complaint platform. Research Findings/Insights: Analyzing 22,644 firm-year observations from 2018 to 2023, we find that politically connected firms experience significantly fewer customer complaints. A one-unit increase in political connection strength is associated with a 9% reduction in complaints relative to the sample mean. This effect operates through two primary mechanisms: a reputation-motivation channel and a financial resource channel. The mitigating effect is more pronounced for firms in highly marketized regions, those with higher advertising expenditures, companies facing greater earnings pressure, and those with lower tangible asset ratios. Theoretical/Academic Implications: Our study contributes to the literature on political connections and corporate governance by demonstrating how political capital translates into tangible consumer experience advantages. It also advances research on the determinants of customer complaints by highlighting the role of internal governance mechanisms, particularly managerial political ties. Our findings support the Corporate Reputation and Financial Resource Hypotheses while challenging alternative explanations based on regulatory shielding or managerial complacency. Practitioner/Policy Implications: For corporate leaders, our results underscore the importance of reputation management and quality investment, particularly when political connections are absent. Policymakers should consider strengthening public monitoring institutions to reinforce reputational incentives across markets. Investors may use customer complaints as an indicator of product quality and operational stability in their investment decisions.
  • 详情 Law and Algorithm-Managed Firms
    Recent technological advancements have enabled the emergence of business organizations fully managed by algorithms, such as decentralized autonomous organizations (DAOs) or through artificial intelligence (AI), as observed in China’s online food delivery sector. These organizations are collectively referred to as algorithm-managed firms (AMFs). Given machines’ capabilities in data collection and analysis, human directors are increasingly being replaced by algorithms or AI in specific sectors. This article contends that algorithms can effectively take over human directors’ managerial, monitoring, and mediating roles. The diminishing role of human directors raises certain concerns of stakeholder protection. Unlike human directors, algorithm directors or managers would not consider stakeholders’ interests unless clearly instructed to do so. However, the algorithm supplier and the AMFs may lack the incentives to fully consider stakeholders because they do not always internalize the social costs. To address the challenges of AMFs, policymakers need to consider different regulation strategies. First, they must choose between command-and-control regulations and target-based regulations. Command-and-control regulations often do not work well because regulators lack enough information or control over complex algorithms. Instead of setting detailed technical rules, policymakers should adopt target-based regulations that let the algorithm balance various interests and regulate its own operations. Second, policymakers should decide between entity-based and algorithm-based regulations. Algorithm-based regulation is more suitable because it prevents companies from passing costs onto society. The state could consider regulating the composition of the board of directors of the algorithm supplier to ensure that they incorporate the concerns of stakeholders’ interests in the development of the algorithm. Additionally, corporate law doctrines that protect creditors and other stakeholders, such as piercing the corporate veil and limiting liability for corporate torts, must be revisited and modified because their foundational assumptions no longer align with the realities of AMFs.