This paper examines how the trade war affected the intensity and direction of innovation in China. Using textual analysis of patent abstracts, we compare innovation directions between Chinese and US firms based on term similarity. We find that higher exposure to US import tariffs decreases similarity—especially with recent US patents—and lowers Chinese patent filings. A quantitative model in which firms allocate innovation effort across product features and choose export markets shows that by 2021, changes in innovation quantity and direction reduced Chinese exports to the US by 3.3%, with shifts in direction accounting for 14% of the decline.

We develop a dynamic quantitative trade model featuring endogenous innovation and trade-driven technology diffusion. In the model, tariffs shape global technological progress by (i) altering knowledge flows embodied in trade and (ii) changing market sizes and thus innovation incentives. We estimate the model’s key parameter—the elasticity of international knowledge diffusion, proxied by patent citations, with respect to trade flows—using quasi-experimental shocks to global trade patterns. With the estimated model in hand, we quantify the effects of recent trade wars and show that endogenous innovation and trade-driven technology diffusion substantially amplify the technological and welfare losses from rising trade barriers. Finally, we characterize the unilaterally optimal U.S. tariffs on China, highlighting a trade-off between limiting China’s technological advance and fostering U.S. innovation.

Sequentially coming agents may adopt a new technology. Early adoption can generate information about its value, which is either high or low, and an intermediary decides how such information will be dynamically published. Because individuals tend to wait and free-ride on information generated by others, efficient social learning is hard to achieve. Facing this challenge, we study how the intermediary can improve social welfare by designing its information publishing policy. To incentivize early adoption, we show it is optimal to restrain future information flow via inducing individually sub-optimal adoption but not via excessive waiting. The optimal design features a simple threshold stopping structure: in every period, recommend adoption if the intermediary’s current belief is more optimistic than a threshold; otherwise, recommend waiting forever.

ESG engagement allows firms to achieve sustainable development, but greenwashing through selective disclosure creates a "bad money drives out good" dilemma in ESG dissemination. This paper demonstrates that ESG greenwashing exerts a dual effect on firm value among Chinese Ashare listed firms, with a short-term positive impact followed by a long-term adverse effect. Using dynamic panel models, we find a positive effect of greenwashing on firm value by alleviating firms’financing constraints. However, the relation reverses in the subsequent two years, which is due to weakened innovation capacity via reduced R&D and reputation discounts. These findings enrich signaling and stakeholder theories with time-varying insights. It offers practical guidance for identifying greenwashing, enhancing regulatory frameworks, and promoting true ESG practices.

Based on the insight that declaring an anomaly not spanned presumes knowledge of the true SDF, we reverse conventional testing: discovery now corresponds to returns being spanned by a given factor set. We develop a Bayesian procedure that, for single anomalies and sequentially for pairs, triplets, and larger sets, computes posterior spanning probabilities and selects discoveries while controlling the expected false discovery rate (EFDR) at each stage. Applied to the U.S. dataset of Jensen et al. (2023) comprising 153 anomalies, our method classifies 132 as spanned. The evidence tempers claims of new factors and highlights redundancy and masking in the anomaly zoo.

We study how cannibalization concerns shape firms’ product launch decisions. In the pharmaceutical industry, the threat of generic competitor entering a branded product’s market reduces cannibalization concerns for pipeline launches, while having limited impact on the standalone value of pipeline product. We find that such competitive threats accelerate pipeline launches, which in turn decrease sales of the threatened product in a period before the competitor's actual market entry. Our findings underscore how competitive pressure accelerates the commercialization of new products by reducing cannibalization costs, fostering creative destruction and strengthening the link between innovation and growth.

Priority-based allocation often requires eliminating justified envy, making serial dictatorship (SD) the only non-wasteful direct mechanism with that property. However, SD’s outcomes can conflict with the policymaker’s objectives. We introduce visible fairness, a framework where fairness is evaluated using coarser information. This is achieved by designing message spaces that strategically conceal information that could render desired allocations unfair. We characterize these mechanisms as generalizations of SD, establish conditions for strategy-proofness, and show how to implement distributional constraints. This creates a new trade-off: achieving distributional goals may require limiting preference elicitation, forgoing efficiency gains even when compatible with the constraints.

We document large inequality in life expectancy at age sixty across cities and sectors of employment in China using the regression discontinuity approach. The life expectancy is higher in larger cities and among public sector retirees, with a gap of over ten years between rural residents and tier-one city public sector retirees. To understand the inequality, we develop a dynamic optimization model of health investment and housing choice for retirees. We show that the inequality is largely attributable to the heterogeneity in income, in the coverage of publicly funded health insurance, and in the housing investment market. Counterfactual experiments indicate that equalizing publicly funded medical coverage will significantly reduce life expectancy inequality. A decline in house prices will reduce life expectancy more in tier-two and tier-three cities.

The innovation of new financial products, processes, and services is a key driver of economic development and technological progress. Yet, the issue of how new technology itself affects financial innovation activity is not well understood. We argue that, although new technologies can spur financial innovation via knowledge spillovers, they can also lead to the “crowding out” of financial innovation by increasing the relative profitability of competing investment opportunities. To test our hypotheses, we use time-series data during 2005-2019 on the occurrence of major waves of non-financial innovation and their impact on firms’ financial patenting and the hiring of financial inventors. We find evidence of aggregate-level crowding-out in the earlier part of the sample: firms tend to shift from financial to non-financial patenting following the onset of an innovation wave.

Overconservatism has long been recognized as a major issue of robust optimization, despite its major advantages of tractability, performance guarantee, and limited information. A new criterion based on adjustable regret is proposed to address this issue by adapting the level of conservatism to the environment, while maintaining all the aforementioned advantages. The level of conservatism can be fine-tuned by maximizing the reward guarantee for scenarios representative of opportunities provided by experts as most likely values, leading to a simple heuristic to best catch opportunities. This criterion also supports a new approach to competitive ratio analysis that is applicable even to multistage problems. The new criterion is then applied to the one-way trading problem with analytical solutions, from which the competitive ratio is easily derived by the new approach.