American Journal of Economics and Sociology最新文献

We introduce two categories, meta goods and dynamic goods, that extend the standard taxonomy of economic goods. A meta good generates downstream outputs (e.g., text, code, images), expanding the feasible consumption set; a dynamic good improves endogenously with use, feedback, and retraining. We develop a welfare-theoretic model in which artificial intelligence (AI) exhibits both properties. The main result shows underprovision of adoption in decentralized equilibrium when learning-by-using and data externalities are present, relative to a social planner. Formal propositions establish the taxonomy and the welfare ranking, and a stylized calibration illustrates diffusion and quality dynamics consistent with theory. The framework generalizes beyond AI to other general-purpose technologies. These findings speak directly to ongoing global debates on AI governance, open versus closed access, and the role of international institutions in shaping equitable and socially inclusive diffusion.

This study presents a new framework for analyzing how employment is influenced by both the demand and supply sides of the labor market. We employ principal component analysis (PCA) to synthesize the two sets of factors into a demand index and a supply index, thus creating a dual-index model. Each side is represented by five proxies, which are supported and realized by utility and profit maximization theories. A logistic regression model applied to assess their impact on the employment of individuals. The results indicate that both supply and demand indices significantly affect individual employment, with heterogeneous effects across different subpopulations. The female group tends to be influenced by the demand index (a phenomenon most likely caused by workplace bias), while the male group tends to be influenced by the supply index, probably due to their own personal choices. In this way, the dual-index approach overcomes the limitation of a single-variable model focusing only on the causality of a single factor. It is also able to fully distinguish the influences of the demand and supply aspects on both the total population and specific subpopulations, making it suitable for providing group-specific information to policymakers.

This paper develops a duopoly model to examine firms' optimal R&D risk choices under cooperative and non-cooperative R&D with cross-ownership. We find that firms adopt higher R&D risks in cooperative settings than in non-cooperative ones. Moreover, equilibrium R&D risks increase with cross-ownership, and a firm assumes higher risk when it holds a smaller equity stake in its competitor. Our results also reveal that the socially optimal R&D risk exceeds the private optimum. Under cooperative R&D, this risk gap widens as cross-ownership rises, whereas in non-cooperative R&D, its trend depends on product substitutability. Extending the model to unilateral ownership, we show that the firm partially owned by its competitor takes on higher R&D risk than the owning firm, though both assume lower risk compared to cross-ownership. Finally, we demonstrate that R&D risk is higher under Bertrand competition than under Cournot competition. This study contributes to the literature by highlighting the role of ownership structure in shaping firms' risk-taking behaviors in R&D and offering new insights into the trade-off between cooperation and competition in innovation.

Promoting green innovation in resource-based industries is crucial for sustainable socio-economic development. However, existing research has yet to fully elucidate the mechanisms through which market demand incentivizes green innovation within China's resource-based industries. Grounded in the Resource-Based View and Stakeholder Theory, this study constructs a systematic framework for analyzing the antecedents of green innovation in resource-based industries. This paper examines how market demand incentivizes green innovation in China's resource-based industries from a configurational perspective, by integrating three methodologies: Network DEA, NCA, and QCA. The findings reveal that market demand is a key determinant of green innovation in China's resource-based industries. However, high market demand alone is insufficient for these industries to achieve high green innovation. To exert a synergistic effect, market demand must be configured in combination with other antecedent conditions. The analysis identifies three distinct configurational paths leading to high green innovation within resource-based industries. Conversely, two configurational paths result in non-high green innovation. Critically, the absence of market demand emerges as a critical prerequisite for low green innovation in resource-based industries. This research provides a theoretical framework for clarifying the mechanism by which market demand influences green innovation in resource-based industries. Furthermore, it offers a decision-making basis for diverse subsectors within these industries to achieve green innovation.

Transparent, stable, and open trade policies are essential for fostering economic growth, resilience, and addressing critical global issues such as climate change, food security, and underdevelopment. This study examines the impact of the rule of law, financial inclusion, economic growth, and inflation on trade within the Organization for Security and Co-operation in Europe and European countries. The results show that a strong positive relationship between the rule of law and trade in both groups of countries is maintained across nearly all quantiles. Additionally, economic growth has a consistently positive association with trade in both regions. However, financial inclusion negatively affects trade from the second to the sixth quantiles according to the Method of Moments Quantile Regression econometric method. Inflation, on the other hand, does not exhibit a significant relationship with trade. Consequently, both the Organization for Security and Co-operation in Europe and European countries should make the rule of law, economic growth, and financial inclusion focal points of their trade policies. This study provides important insights that can inform policy decisions in these regions.

This paper develops a duopoly model to examine firms' environmental R&D cooperation strategy under managerial delegation, where firms can choose between sales or environmental delegation. The results show that under sales delegation, firms choose non-cooperative environmental R&D when the efficiency of environmental R&D is low; otherwise, cooperative environmental R&D occurs. Under environmental delegation, firms choose non-cooperative environmental R&D when the degree of technology spillover is relatively high and the efficiency of environmental R&D is relatively low, whereas cooperative environmental R&D is optimal when the efficiency of environmental R&D is relatively high. We also find that regardless of the environmental R&D cooperation strategy, sales delegation leads to higher social welfare compared to environmental delegation. Moreover, we show that both symmetric and asymmetric sales (environmental) delegation can be an equilibrium in an endogenous delegation choice game, depending on the technology spillover effect and the efficiency of environmental R&D. Finally, we extend the model to examine the robustness of the baseline results.

This research analyses the effects of trade integration on foreign direct investment (FDI) in a dynamic panel of 30 sub-Saharan African countries over the period 2002–2022. It uses the Pull and Push factors model, which is estimated by the two-step system generalized method of moments. The results show that trade integration fosters FDI. However, this positive effect becomes negative when trade integration exceeds the 103% threshold. The results imply that policymakers in Sub-Saharan Africa should control trade integration to attract FDI to their countries.

Amid growing global commitments to carbon neutrality and sustainable development, heavy-polluting enterprises worldwide are undergoing a critical transition toward low-carbon operations, highlighting the essential role of environmental information disclosure systems in monitoring and guiding corporate environmental performance. This study investigates how environmental regulation, market development, and corporate governance structures interact to shape EID quality among listed chemical and pharmaceutical enterprises in Shanghai, Shenzhen, and Beijing Stock Exchanges. Drawing from institutional and configurational theories, we construct an analytical framework “Environmental Regulation–Market Cultivation–Governance Structure” and apply fuzzy-set qualitative comparative analysis (fsQCA) and Necessary Condition Analysis (NCA) to assess causal complexity. Our findings identify multiple configurations through which state-owned and private enterprises achieve high EID performance, including patterns driven by strong certification, profitability, and ownership structure. These results illustrate how governance models reflect deeper institutional tensions between state intervention, market evolution, and corporate autonomy. By advancing a multipath understanding of environmental governance, the study contributes to ongoing debates about climate accountability, regulatory legitimacy, and the political economy of sustainability in emerging economies. Policy implications highlight the need for differentiated, equity-sensitive governance reforms.