q-fin.EC papers | Gist.Science

Adaptive Robust Optimization for European Electricity System Planning Considering Regional Dunkelflaute Events

This study employs an adaptive robust optimization framework to demonstrate that incorporating worst-case regional "Dunkelflaute" events into European electricity planning reveals nonlinear cost increases and a shift toward long-duration hydrogen storage and load shedding as event severity grows, highlighting the critical need for coordinated cross-border infrastructure and geographically balanced renewable deployment to ensure system resilience.

Maximilian Bernecker, Smaranda Sgarciu, Xiaoming Kan, Mehrnaz Anvari, Iegor Riepin, Felix MüsgensWed, 11 Ma📈 econ

The Data-Dollars Tradeoff: Privacy Harms vs. Economic Risk in Personalized AI Adoption

This study reveals that ambiguity regarding data leak probabilities, rather than known risks, significantly reduces user adoption of personalized AI, highlighting a critical demand for transparency institutions to mitigate privacy concerns.

Alexander Erlei, Tahir Abbas, Kilian Bizer, Ujwal GadirajuWed, 11 Ma📈 econ

Perceptions and worldviews of Transgender individuals

Using a panel dataset of over 19,000 observations, this study reveals that transgender individuals report lower subjective well-being and health, exhibit less support for women's empowerment and gender-related statements, rely more on parental and teacher opinions for career decisions, and display higher levels of distrust compared to non-transgender people, with findings on gender attitudes and decision-making diverging from progressive expectations.

Eiji YamamuraWed, 11 Ma💰 q-fin

Has the COVID-19 Pandemic Altered the Traditional View about Women's Active Work?

Using individual-level panel data from 2016 to 2024, this study reveals that the COVID-19 pandemic significantly shifted societal attitudes toward women's active work, resulting in a general increase in positive views across genders, a reversal where women became more supportive than men, and a notable change in perspective among older individuals and married men.

Eiji Yamamura, Fumio OhtakeWed, 11 Ma💰 q-fin

How bad is time variability for users in mobility services?

This paper establishes theoretical upper bounds on the ratio of the cost of time variability to the cost of time within an expected utility framework, demonstrating that for quadratic utility the ratio is at most half the squared coefficient of variation, thereby providing a data-light benchmark for assessing the economic significance of reliability improvements in mobility services.

Zhaoqi Zang, David Z. W. Wang, Xiangdong Xu, Shaojun LiuWed, 11 Ma📈 econ

Conscription and its exemption in 19th Century Japan: Incentivized family head in educational market

Using individual-level data from Keio Gijuku, this paper demonstrates that while 19th-century Japanese conscription exemptions incentivized family heads to increase their educational attendance, this surge in enrollment did not translate into a qualitative improvement in academic performance.

Eiji YamamuraWed, 11 Ma💰 q-fin

LLM-Agent Interactions on Markets with Information Asymmetries

This paper simulates GPT-5.1 agents in credence goods markets to demonstrate that, unlike human actors, LLM-driven markets exhibit distinct behaviors such as higher participation and lower prices but entrenched fraud, suggesting that effective institutional design for AI economies must prioritize aligning agents' social preferences rather than relying on traditional mechanisms like verifiability or reputation.

Alexander Erlei, Lukas MeubWed, 11 Ma💰 q-fin

A Survey of Reinforcement Learning For Economics

This survey introduces reinforcement learning to economists as a flexible, sample-based extension of dynamic programming capable of solving high-dimensional economic models, while critically examining its practical limitations such as sample inefficiency, sensitivity to hyperparameters, and reliance on accurate simulators.

Pranjal RawatWed, 11 Ma🤖 cs.LG

The Illusion of Collusion

This paper demonstrates that competing algorithmic agents using multi-armed bandit learning can spontaneously develop "naive collusion" through action synchronicity, even without knowledge of competitors, with the likelihood of such outcomes depending critically on whether the agents employ deterministic, greedy-in-the-limit, or persistently random policies.

Connor Douglas, Foster Provost, Arun SundararajanTue, 10 Ma💻 cs

Think, Speak, Decide: Language-Augmented Multi-Agent Reinforcement Learning for Economic Decision-Making

The paper proposes LAMP, a language-augmented multi-agent reinforcement learning framework that employs a "Think-Speak-Decide" pipeline to integrate unstructured language with numerical data, significantly outperforming existing baselines in economic decision-making through improved cumulative returns, robustness, and interpretability.

Heyang Ma, Qirui Mi, Qipeng Yang, Zijun Fan, Bo Li, Haifeng ZhangTue, 10 Ma💻 cs

HLER: Human-in-the-Loop Economic Research via Multi-Agent Pipelines for Empirical Discovery

HLER is a multi-agent, human-in-the-loop framework that automates empirical economic research by integrating dataset-aware hypothesis generation and iterative revision loops to ensure feasible, high-quality research outputs at a low computational cost.

Chen Zhu, Xiaolu WangTue, 10 Ma💻 cs

Designing probabilistic AI monsoon forecasts to inform agricultural decision-making

This paper presents a decision-theory framework and a blended AI-statistical forecasting system that successfully delivered skillful, tailored monsoon onset predictions to 38 million Indian farmers in 2025, enabling better agricultural decision-making under uncertainty.

Colin Aitken, Rajat Masiwal, Adam Marchakitus, Katherine Kowal, Mayank Gupta, Tyler Yang, Amir Jina, Pedram Hassanzadeh, William R. Boos, Michael KremerTue, 10 Ma🤖 cs.LG

The coordination gap in frontier AI safety policies

The paper argues that frontier AI safety policies currently suffer from a structural "coordination gap" by overemphasizing prevention while neglecting the institutional capacity needed to coordinate responses when failures occur, and proposes adapting mechanisms from nuclear safety and pandemic preparedness to address this underinvestment in ecosystem robustness.

Isaak MengeshaThu, 12 Ma📈 econ

A Semi-Structural Model with Household Debt for Israel

This paper proposes a semi-structural DSGE model for the Israeli economy incorporating household credit frictions to demonstrate that effective monetary policy should respond to credit spreads, while macroprudential policy can mitigate debt crises and stimulate demand by reducing leverage-induced borrowing costs.

Alex Ilek, Nimrod CohenThu, 12 Ma📈 econ

Towards macroeconomic analysis without microfoundations: measuring the entropy of simulated exchange economies

This paper demonstrates through computer simulations that the entropy of exchange economies can be empirically measured using a calorimetric approach, validating the framework of thermal macroeconomics by confirming that entropy acts as a concave, path-independent state function even in complex systems where traditional microfoundations are infeasible.

Yihang Luo, Robert S. MacKay, Nick ChaterThu, 12 Ma💰 q-fin

Identifying the post-pandemic determinants of low performing students in Latin America through Interpretable Machine Learning methods

Using interpretable machine learning on 2022 PISA data from ten Latin American countries, this study identifies that student underachievement is primarily driven by a combination of individual socioeconomic factors (such as poverty, minority language status, and child labor) and systemic school-level disadvantages (including poor ICT infrastructure and low teacher certification), with repetition and household wealth emerging as consistent predictors across the region.

Marcos DelpratoMon, 09 Ma💰 q-fin

Sleep and redistribution preferences: Considering allowable tax rates

This study utilizes survey data and regression analyses to demonstrate that both sleep duration and quality significantly influence redistribution preferences, revealing an inverted U-shaped relationship where optimal sleep maximizes allowable tax rates, with stronger positive effects observed among high-income earners and those facing hypothetical scenarios of doubled tax redistribution.

Eiji Yamamura, Fumio OhtakeMon, 09 Ma💰 q-fin

Preference for redistribution and institutional trust: Comparison before and after COVID-19

Using a Japanese panel dataset from 2016 to 2024, this study finds that the COVID-19 pandemic reduced redistribution preferences among high-income individuals, a decline that was mitigated by higher trust in government but remained unaffected by generalized trust or reciprocity.

Eiji Yamamura, Fumio OhtakeMon, 09 Ma💰 q-fin

The Widening Gap in Tax Attitudes: Role of Government Trust in the post COVID-19 period

Using Japanese data, this study reveals that the post-pandemic shift from unconditional support for tax-based redistribution to conditional altruism has created a widening gap where income redistribution now critically depends on trust in government, particularly among high-income individuals.

Eiji Yamamura, Fumio OhtakeMon, 09 Ma💰 q-fin

Nonlinear Fiscal Transitions and the Dynamics of Public Expenditure Reform

This paper develops a nonlinear theoretical framework to analyze public expenditure reform in Uruguay, demonstrating that structural adjustments involving institutional frictions and transition costs initially increase total spending before converging to a more efficient long-run allocation, thereby producing a J-shaped expenditure trajectory.

Diego VallarinoMon, 09 Ma💰 q-fin