Clay weekly context brief for the Economics category (ISO week 2026-W32).

Clay tracks publications from the Economics feed list. Below are recent items from this category, each with its source and a short description of what the publication covers when one is available in the source feed.

Recent publications:
1. The Turing Valley: How AI Capabilities Shape Labor Income
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2408.16443
   There is concern that progress toward AI systems with strong capabilities across domains will reduce the importance of human input in production and thus wages.
2. Reference Dependence and the Structure of the WTA/WTP Gap
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2607.27239
   This paper studies the willingness-to-accept/willingness-to-pay (WTA-WTP) gap under objective probabilities.
3. Single-Network Finite-Sample Inference in Strategic Network Formation Models
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2607.27505
   We develop a finite-sample valid inference procedure for strategic network formation models in which linking decisions depend on endogenous network statistics (say, the number of common friends).
4. When Do AI Gains Become Broadly Shareable? A Policy Threshold for AI-Driven Automation
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2505.18687
   AI-driven automation generates broad-based social benefit only if technical gains become visible, durable, and publicly claimable.
5. Racing to Ruin
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2607.27638
   We study R&D competition in the shadow of disaster: advancing the technology frontier raises the risk of permanently ending all firms' payoffs.
6. Nonfundamentalness or missing information ? Evidence from causal-noncausal VARs in macro-finance
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2607.28131
   This paper studies the presence of noncausal dynamics in standard macro-finance VAR models and asks whether they reflect genuine nonfundamentalness or omitted information available to economic agents but unobserved by the econometrician.
7. Links between population growth, age demographics, and socio-economic performance among countries
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2508.16872
   Concerns about declining or ageing populations often centre on the concern that fewer people will translate to a weaker economy and lower living standards.
8. Reversing Reserve Logic: Optimal Holdback in Local Allocation under Scalable Entry
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2607.27817
   Scarce opportunities such as concert tickets and accelerator time may be contested by automated participants that can create accounts and sustain commitments beyond the reach of commitment-limited intended users.
9. Asymptotic Uniform False Discovery Rate Control for Inference of Time-varying Correlations
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2512.10467
   Inference for locally stationary time series is challenging because the associated hypotheses form an uncountable collection over a continuous time interval, making pointwise false discovery rate (FDR) control inadequate for simultaneous statistical guarantees.
10. Women Worry, Men Adopt? Gendered Risk Perceptions and Generative AI Adoption
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2601.03880
   Generative artificial intelligence (GenAI) is spreading rapidly across work and daily life, yet adoption remains uneven.
11. Scaling, Lock-In, and Proxy Compliance: A Political Economy of Responsible AI
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2607.28023
   AI accountability at scale is an institutional problem: who can observe, verify, and change deployed systems.
12. Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2501.02672
   Granger causality (GC) is widely used to infer directed relationships in time-series data.
13. What Capital After Labor? Forecasting the Talent ROI Transition in the Human-AI Era
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2606.19846
   AI augmentation breaks the accounting link between labor time and productive contribution, yet firms continue to evaluate talent through time-based overhead bundles.
14. Battery Operations in Electricity Markets: Strategic Behavior and Distortions
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2406.18685
   Battery storage can reduce electricity generation costs by shifting energy across time, but as privately owned batteries become large, they may also be able to exert market power.
15. Unified Inference on Moment Restrictions with Nuisance Parameters
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2202.11031
   This paper proposes a simple unified inference approach on moment restrictions in the presence of nuisance parameters.
16. Wrong and More Confident: A Field Experiment on Large Language Models Taking a Graduate Economics Exam
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2607.23424
   A red herring, an irrelevant passage added to a problem, corrupts a language model's reasoning and, through it, its final answer, while the form of the response survives untouched.
17. Uncharted Waters: Selling a New Product Robustly
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2508.04134
   New products often involve uncertainty about product fit, while sellers may also be unsure about what alternatives buyers face.
18. Debiased Machine Learning: Identification, Estimation, and Shape Constraints
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2607.24472
   We develop a general framework of identification and estimation for automatic debiased machine learning (DML) where the parameter of interest $\theta_0$ is identified by a moment condition involving a nuisance $\gamma_0$ that may be high dimensional.
19. Social Networks and Spatial Mobility: Evidence from Facebook in India
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2203.05595
   This paper studies the role of social networks in spatial mobility across India.
20. Diagnostic Feedback under Hidden Task Difficulty
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2508.20540
   An assessment is meant to tell an agent about herself, but its purchase can reveal the task.
21. Optimizing Regret
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2607.18866
   Building on the identity that expected regret equals the covariance between costs and decisions, this paper develops a derivative theory of the covariance regret functional.
22. Downsian Competition for the Myerson Value
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2607.27996
   This paper studies an electoral competition model in which parties maximize legislative power rather than vote shares.
23. Optimal Taxation under Imperfect Trust
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2509.03085
   We study optimal taxation when citizens are not fully confident that the government will transform tax revenue into useful public goods.
24. Learning Dependence Structures for Econometric Inference: Identification, Ambiguity, and Adaptive Inference
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2606.22555
   Econometric inference usually conditions on a dependence structure chosen in advance, even though the data may support clustering, latent factors, sparse interactions, or mixtures of these mechanisms.
25. Using Large Language Models for Idea Generation in Innovation
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2607.27553
   This research evaluates the efficacy of large language models (LLMs) in generating new product ideas.
26. Government Reputation and Fiscal Capacity
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2509.03087
   How does a state allocate fiscal resources to an executive whose willingness to implement public spending is privately known?
27. Intraday Gas Fee Heterogeneity on Ethereum: Evidence from Operational Firms
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2604.19956
   Ethereum's EIP-1559 fee mechanism was designed under the assumption of homogeneous, myopic agents responding to a single congestion signal.
28. Emission-Forecasting-Based Spatial-Temporal Carbon Response: A Multi-Agent Attention-Enhanced Deep Learning Framework
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2607.26560
   As a major contributor to carbon emissions, the decarbonization of power systems has garnered significant societal attention.
29. The Last Costly Signal: How Generative AI Collapses Competence Signaling and Why Liability Sustains Markets for Expert Services
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2607.26327
   Generative artificial intelligence has reduced the cost of producing convincing artifacts of expertise-reports, analyses, proposals-to nearly zero.
30. Low-Rank Estimation of Nonlinear Panel Data Models
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2511.21948
   This paper investigates nonlinear panel models with interactive fixed effects and introduces a general framework for parameter estimation under potentially nonconvex objective functions.
31. Do Crises Increase Parochial Behavior? Evidence from Donations During Covid
   Source: econ.GN (General Economics)
   Link: https://arxiv.org/abs/2607.28378
   Do people behave more favorably towards their in-group during a crisis?
32. The Complexity of Sparse Win-Lose Bimatrix Games
   Source: econ.TH (Theoretical Economics)
   Link: https://arxiv.org/abs/2602.18380
   We prove that computing an $\epsilon$-approximate Nash equilibrium of a win-lose bimatrix game with constant sparsity is PPAD-hard for inverse-polynomial $\epsilon$.
33. Linear Estimation of Structural and Causal Effects for Nonseparable Panel Data
   Source: econ.EM (Econometrics)
   Link: https://arxiv.org/abs/2607.28291
   This paper develops linear estimators for structural and causal parameters of nonseparable models using panel data.

Sources in this brief: econ.EM (Econometrics); econ.GN (General Economics); econ.TH (Theoretical Economics).
Selected 33 of 450 available items for this weekly brief.