Trade policy uncertainty has become a significant feature of today's global economy. While its impact on free trade is evident, its microeconomic effects remain open to debate. This study explores the influence of trade policy uncertainty on corporate ESG performance and its underlying mechanisms, using data from A-share listed companies in China from 2010 to 2020. The findings reveal that increased trade policy uncertainty significantly and robustly enhances corporate ESG performance. Heterogeneity analysis indicates that high-tech enterprises are better equipped to improve their ESG performance in response to trade policy uncertainty. Furthermore, strengthening internal controls and appointing CEOs with environmental backgrounds also help firms seize the opportunities arising from trade policy uncertainty. In terms of mechanisms, trade policy uncertainty intensifies industry competition, compelling firms to enhance their ESG performance to gain market share. Additionally, it stimulates green technological innovation, further optimizing ESG outcomes. Therefore, efforts should focus on improving the ESG standards system, establishing ESG incentive policies, increasing the transparency and predictability of trade policies, and promoting corporate green development to advance national sustainable development goals.

Microsoft's acquisition of Activision Blizzard valued at $68.7 billion has drastically altered the landscape of the video game industry. At the time of the takeover, the intellectual properties of Activision Blizzard included World of Warcraft, Diablo, Hearthstone, StarCraft, Overwatch, Battle.net, Candy Crush Saga, and Call of Duty. This article aims to explore the patenting activity of Activision Blizzard between 2008 (the original merger) and 2023 (the Microsoft acquisition). Four IPC code co-occurrence networks (co-classification maps) are constructed and analyzed based on the patent data downloaded from the WIPO Patentscope database. International Patent Classification (IPC) codes are a language agnostic system for the classification of patents. When multiple IPC codes co-occur in a patent, it shows that the technologies are connected. These relationships can be used for patent mapping. The analysis identifies the prolific and bridging technologies of Activision Blizzard and explores its synergistic role as a subsidiary of Microsoft Corporation.

We revisit the classic job-market signaling model of \cite{spence1973job}, introducing profit-seeking schools as intermediaries that design the mapping from candidates' efforts to job-market signals. Each school commits to an attendance fee and a monitoring policy. We show that, in equilibrium, a monopolist school captures the entire social surplus by committing to low information signals and charging fees that extract students' surplus from being hired. In contrast, competition shifts surplus to students, with schools vying to attract high-ability students, enabling them to distinguish themselves from their lower-ability peers. However, this increased signal informativeness leads to more wasteful effort in equilibrium, contrasting with the usual argument that competition enhances social efficiency. This result may be reversed if schools face binding fee caps or students are credit-constrained.

Exponential random graph models (ERGMs) are very flexible for modeling network formation but pose difficult estimation challenges due to their intractable normalizing constant. Existing methods, such as MCMC-MLE, rely on sequential simulation at every optimization step. We propose a neural network approach that trains on a single, large set of parameter-simulation pairs to learn the mapping from parameters to average network statistics. Once trained, this map can be inverted, yielding a fast and parallelizable estimation method. The procedure also accommodates extra network statistics to mitigate model misspecification. Some simple illustrative examples show that the method performs well in practice.

We consider fully non-linear stochastic optimal control problems in infinite horizon with measurable coefficients and uniformly elliptic diffusion. Using the theory of $L^p$-viscosity solutions, we show existence of an $L^p$-viscosity solution $v\in W_{\rm loc}^{2,p}$ of the Hamilton-Jacobi-Bellman (HJB) equation, which, in turn, is also a strong solution (i.e. it satisfies the HJB equation pointwise a.e.). We are then led to prove verification theorems, providing necessary and sufficient conditions for optimality. These results allow us to construct optimal feedback controls. We use the theory developed to solve a stochastic optimal control problem arising in economics within the context of optimal advertising.