ALT Population aging and fertility decline are occurring simultaneously worldwide, straining labor supply and pension systems. China began a gradual delayed-retirement (GDR) reform in 2025, raising statutory retirement ages on different schedules for men, female cadres, and female workers across birth cohorts. To evaluate its effects on older individuals and within the family, we develop a model of older adults' retirement, intergenerational transfers, and adult children's fertility decisions, with parameters estimated via fuzzy regression discontinuity at the pre-2025 statutory retirement ages. Counterfactual simulations show that, for mature reform cohorts, the GDR reform increases older employment and monetary transfers to adult children but reduces grandparental childcare. Because the reduction in childcare outweighs the increase in monetary transfers, fertility and older adults' welfare decline, with particularly large losses among lower-income women. Fully flexible retirement, mandat

ALT We study a model in which artificial intelligence lowers the cost of writing faster than the cost of reading. Authors differ in reputation, and time-constrained readers, such as referees, choose between ignoring, verifying, and trusting papers. As writing costs fall, the band of verified papers shrinks: outsiders are no longer read, and established authors are no longer checked. In the “costless writing limit,” the share of verified papers vanishes, and a paper's impact depends on its author's reputation alone. Readers can escape the flood by asking AI to summarize the literature. These summaries aggregate papers reliably only if their errors are sufficiently independent. Once the share of papers written with the same AI exceeds a threshold, summaries inherit the AI's errors, and AI review filters out the original research that could correct them.

ALT We provide the first systematic evidence on whether financial markets price political pressure on the Federal Reserve as a signal of future monetary policy. Using approximately four decades of Reuters newswire articles from 1988 to 2025, classified by an open-weight large language model ensemble into dovish and hawkish pressure, we estimate the daily response of interest rate expectations across the term structure, the US dollar, inflation compensation, and market volatility. Dovish pressure lowers near-term rate expectations by roughly one basis point per pressure event—equivalent to a four-percent increase in the implied probability of a rate cut at the next FOMC meeting—with the effect decaying monotonically and vanishing beyond the three-month horizon. Hawkish pressure has no detectable effect. Furthermore, excluding the Trump presidencies does not weaken the estimate, ruling out the possibility that the result is confined to an idiosyncratic recent episode. The response is accompa

ALT We examine whether lower costs of running AI models lead to lower prices, and whether delays in observing competitors' prices and limits on price changes affect how much consumers benefit. We study a simulated market with two differentiated sellers, logit demand, and tabular Q learning. A factorial experiment varies the age of rival price information, how often sellers can revise prices, whether production costs fall, and differences in firm quality and costs. We evaluate policies trained on 60 paired market seeds in each of 16 conditions, for 960 training runs, and measure expected consumer surplus after learning ends. In the main setting with identical firms and falling costs, the estimated interaction between information delay and repricing frequency on consumer surplus is -0.00025 normalized units, with a 95% paired seed bootstrap interval of [-0.0402, 0.0393]. The interval includes zero, as do intervals for tests of whether the interaction changes with the cost regime or differenc

ALT This paper compares financial-market reactions to the releases of DeepSeek R1 in January 2025 and Kimi K3 in July 2026. Both AI models were presented as credible Chinese competitors near the capability frontier, but their releases conveyed different economic information. DeepSeek R1 combined open weights with unusually low reported training and inference costs, prompting investors to reassess expected demand for computing infrastructure and producing large stock-price decreases among semiconductor and data-centre-related firms. Kimi K3 instead entered at broadly frontier prices and generated a market reaction concentrated more heavily among rival Chinese AI laboratories. Drawing on descriptive event-window evidence, model capability and cost comparisons, subsequent industry developments, and the historical diffusion of open-source software, the paper argues that open-weight models redistribute rents across the AI value chain rather than eliminating them. Incumbents remain protected by

ALT 35.2% of task time in world employment is at least partly delegable to AI agents in 2026, and only 2.5% can be handed over in full. Existing measures score exposure to generative AI, mostly for the United States. We build the Agent Delegability Index (ADI): two language models rate all 18,796 O*NET 30.2 task statements on a frozen, preregistered rubric of delegation levels and barriers; tasks are mapped to 433 ISCO-08 unit groups and weighted by ILOSTAT employment in 146 countries. Four findings. First, delegable employment rises with income, from 22.5% in low-income to 48.7% in high-income countries, a slope of 7.23 percentage points per log point of GDP per capita. This delegation divide is compositional: the physical barrier dominates the jobs poorer countries employ most. Second, at the occupation level ADI tracks exposure closely (r = 0.93 with Eloundou et al. and 0.89 with Felten et al.), above the preregistered bound of 0.80; ADI adds delegation levels and barriers on top of exp

ALT This paper studies whether fiscal consolidation is associated with deeper multidimensional deprivation among older women than among older men, and through which channel. Using six waves of SHARE across eleven European countries, it builds a multidimensional deprivation index spanning functional health, economic insecurity, and social exclusion, and relates it to the cyclically adjusted primary balance (CAPB) at the country-wave level in a two-way fixed-effects model. Consolidation raises deprivation on average with a null average gender gap, which is later found to conceal regional heterogeneity where the gender gap is positive and significant in Southern and Eastern Europe, and absent in Continental/Nordic Europe. This regional pattern holds under individual clustering but does not survive clustering at the country level. Further, the economic insecurity channel the literature would predict runs in the opposite direction, with men's measured insecurity rising more steeply than women's

ALT Rooftop photovoltaics (PV) can support rapid urban decarbonization, but their contribution is constrained by the imbalance between PV generation and demand, both shaped by local climate. Growing urban electric-vehicle (EV) deployment creates distributed storage near rooftop PV, shifting PV electricity across time. Here we simulate rooftop PV integrated with EVs as batteries across 5,000 grid cells globally, using hourly meteorology and climate-induced demand. We find that PV-EV systems can supply up to 84% of annual building and mobility electricity demand. Self-sufficiency is highest where daytime demand aligns with generation and seasonal variability remains limited. Using PV capacity factor alone to screen PV-EV potential undervalues 21.9% of the world's 1,000 most populous cities because generation-side metrics overlook the temporal coupling of PV generation, electricity demand and EV storage. Substantial PV-EV potential is concentrated in many low-latitude cities, offering a pathw

ALT Research on why people contribute to open source software (OSS) and related open collaboration platforms spans more than two decades, but its findings conflict, and studies often treat the work people contribute and their intention to keep contributing as interchangeable. Drawing on self-determination theory and motivation crowding theory, we meta-analyze 41 studies. The main analysis pools 178 correlations of eight antecedents with contribution effort and continuance intention from 29 independent samples (N = 9,632). Seven antecedents relate positively to effort, all eight relate positively to intention, and each relates at least as strongly to intention as to effort. Contrary to a common assumption, intrinsic motivation is not more strongly related to effort than extrinsic motivation, but its gap between intention and effort is larger. Reputation relates to effort mainly on platforms with a reputation system, and we find no sign that monetary rewards crowd out enjoyment. The findings

ALT Public procurement laws trade rules against discretion with value thresholds: below them, buyers use faster and less competitive procedures. Colombia offers an unusually clean setting to measure how much buyers manipulate estimated values to stay below the line and what it costs. Thresholds are entity-specific (five budget bands set by law) and move every January with the minimum wage, while the round numbers that usually confound bunching estimates stay fixed. Using the universe of Colombian procurement records (SECOP I and II, 2011-2026; 8,569,218 SECOP II processes) and each entity-year's own threshold, we find sharp bunching of estimated values just below both legal cutoffs: 49,631 excess processes below the small-purchase threshold (86% of the mass observed in the last five percent below it) and 3,157 below the tender threshold. The spike tracks the threshold, not the round numbers: it moves with the minimum wage, appears only at each entity's own band, and is an order of magnitud

ALT Changes in occupational task content may have different economic implications depending on whether the tasks gained or lost are occupation-specific or already widespread across the economy. Existing measures of occupational task change largely abstract from this distinction, treating occupations as self-contained task bundles rather than accounting for how tasks are distributed across occupations. We develop a framework to measure a distinct dimension of occupational change, one that goes beyond task expertise or task content: task structure. Using this new framework that tracks tasks across occupations and over time, we separate changes in task quantity from changes in occupational uniqueness, defined as the distinctiveness of an occupation's task bundle relative to other occupations. Using a harmonized dataset of 196563 task statements from the Dictionary of Occupational Titles and O*NET spanning 1977-2018, we measure task diffusion, occupational uniqueness, and distinct dimensions o

ALT In 2024 the Korea Baseball Organization became the first top-tier league to replace the home-plate umpires ball-strike judgment with an automated system. Using over a million pitches from 2021 to 2026, we separate the change into the removal of human discretion and the imposition of a new zone geometry. The machine eliminated count-dependent calls, the value of catcher framing and a small advantage for star batters, rents worth only a few runs per player-season. Because the machines zone scales with height and treats every matchup alike, it redistributed strikes toward tall batters and across matchups, but few pitches are exposed to these changes, and their effects on plate-appearance outcomes are precisely estimated and close to zero. Pitchers re-optimized quickly by throwing higher, with left-handers catching up to an existing trend, whereas we find no evidence that batters adjusted. The results suggest that the incidence of replacing human judgment with a rule depends on its geometr

ALT As AI voice agents get deployed in high-volume contact centers, firms can route low-intent leads to AI and allocate high-intent leads to human workers. Drawing on sequential search theory, we posit that AI-induced task allocation reshapes work, enriching opportunities facing human workers but also raising their reservation value for continuing with the lead in hand, making them less willing to persist. We study the effects of an AI voice-agent deployment at a Chinese online health-insurance brokerage using more than a half million customer outreach records surrounding the rollout. Adopting a regression-discontinuity-in-time design, we trace how worker behavior changes across the workday. Results show that the enrichment of human-facing opportunities concentrates early in the workday, raising the probability that a call is a high-intent lead by about 23 percentage points on the first three calls and fading to zero later. However, customer acquisition by human workers declines precisely

ALT In previous studies, using agent-based simulations of a model of a capitalist economy proposed by Ian Wright, we showed that inequality in both wealth and income distributions is largely governed by a single key parameter: the ratio between average wealth per capita and the mean salary, denoted by R. This parameter captures the relative importance of accumulated assets compared with labor income. In the model, larger values of R are systematically associated with higher levels of inequality, as measured by the Gini coefficient. In the present work, we investigate whether this relationship is also observed in real-world economies. Using empirical data from the World Inequality Database (WID) and the Organization for Economic Co-operation and Development (OECD), we construct empirical estimates of R and compare them with standard measures of income and wealth inequality. We find a positive relation between R and inequality across several empirical settings, with the strongest relationshi

ALT Artificial intelligence (AI) makes it easier than ever to produce research outputs. The pressing question is how researchers should organize their work with this technology. The question is not new: software engineering and security research have long studied how teams of people and machines keep control of a shared body of work with many contributors. We distil principles from the practices these literatures report and transpose them to AI-assisted research. The principles form TRACE: Track records, Review against sources, Accept independently, Control transitions, and Evaluate corrections. Together, the five principles give researchers a common basis for remaining in control while integrating AI into their workflows. By bounding units of work and attending to how each is shaped, they help researchers pace AI-assisted work to human attention rather than to the speed at which AI produces content. We also introduce TRACE-OS, an open source operating system for AI-assisted research proje

ALT Input-output analysis with linear programming is widely used in the planning of national economies. However, linear programming attains its optimum at a vertex of the feasible set, and a small deviation of the optimal plan in some direction violates a constraint. So far, little attention has been paid to finding sets of production plans which guarantee both the supply-demand balance of an economy and a given level of its gross domestic product (GDP), and the sphere packing approach cannot be applied directly, since the balance equations define a set with an empty interior. In this paper, we introduce the set of (ε,δ)-solutions, in which GDP may be smaller than its optimal value by at most ε and supply may differ from demand by at most δ, and we find a sphere with the maximum radius inscribed into this set by solving a linear programming problem. We prove that the optimal radius is positive for positive tolerances, that it is non-decreasing, concave and piecewise linear with respect to

ALT We provide a theory of optimal trade sanctions with three strategic players: Home (sanctioner), Foreign (target), and Bystander. Bystander may act unilaterally or ally with either party subject to a participation constraint. We derive three novel results. First, members of a coalition generically set different tariffs either under Stackelberg timing or when transfers are imperfect. Second, as sanctions tighten, Home's welfare can improve even beyond the unilateral terms-of-trade optimum due to strategic interactions. Third, we characterize feasible sanctions targets when Home and Foreign compete for Bystander's support. An alternative implementation arises with competition: Home lets Foreign win, but Foreign's transfer to Bystander implements the sanctions target. We apply our model to sanctions against Russian crude. In a calibration exercise, cooperation among India, China, and Russia best matches observed data. Sanctions could have been roughly 70% more effective had China and India

ALT Social scientists routinely convert text into covariates like topic shares, ideal points or sentiment scores, and insert them into statistical models of interest. This two-step design is convenient, but it is rarely guided by theory: little tells the analyst which text-based covariates to construct or include. Each approach embodies contestable measurement choices, and competing operationalizations of the same construct can support different conclusions, so a single research question gives rise to a menu of competing regression models. Which text constructed covariates belong in a model, and in what functional form, is thus a problem of model uncertainty. We propose spike-and-slab generalized additive models (SSGAMs), which jointly select covariates and determine whether their effects are linear or nonlinear. We illustrate the approach with the communication of a powerful unelected institution, asking which of 45 competing text indicators from 224 monthly European Central Bank press co

ALT Pediatric vaccine procurement for low- and lower-middle-income countries (LICs and LMICs) requires long-term coordination across heterogeneous vaccine markets, competing stakeholder objectives, and uncertain demand, yet tenders are currently scheduled as a series of independent renewals. We extend the Hypothetically Coordinated Vaccine Market (HCVM) framework to schedule multi-year tenders with flexible lengths and all-unit quantity discounts, and compare three objectives: a balanced coordinatingentity model (UG), a social-benefit model that minimizes missed doses (SB), and a producer profit-maximizing model (MP). Using UNICEF ten-year demand forecasts and 30 demand replications across six discount scenarios, we find that the procurement objective, not demand variability, drives cost-to-tender and schedule complexity. Quantity discounts favor large producers, concentrating the market and increasing supply chain vulnerability. Discount effectiveness depends on market maturity rather tha

ALT We study two hypotheses for how a human role in production could persist despite growing AI capabilities. Humans might have a durable advantage in taste, designing better products even as AI agents automate routine tasks, or consumers might intrinsically prefer that humans have a hand in production. In our experiment, participants act as producers, designing computer games with an AI coding agent, and as consumers who buy them. Across three studies (N = 1,025), we find no evidence for either hypothesis. Games designed by an AI on its own outperform those of human producers, including both amateurs and professional creatives. Human producers do not anticipate the AI's advantage. Revealing whether a game is human-designed does not raise consumers' willingness to pay for the product.