This paper introduces metrics for welfare analysis in dynamic models. We develop estimation and inference for these parameters even in the presence of a high-dimensional state space. Examples of welfare metrics include average welfare, average marginal welfare effects, and welfare decompositions into direct and indirec…
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48 results for “welfare”
Current methodologies in machine learning analyze the effects of various statistical parity notions of fairness primarily in light of their impacts on predictive accuracy and vendor utility loss. In this paper, we propose a new framework for interpreting the effects of fairness criteria by converting the constrained lo…
The paper addresses how to complete incomplete risk markets by iteratively enhancing welfare.
problem How to complete incomplete risk markets to enhance welfare.
method Iterative mechanism to complete the market while monotonically enhancing welfare.
result Iterative completion of incomplete risk markets can enhance welfare.
New framework tackles submodular welfare with multi-agent combinatorial bandits.
problem Maximizing total welfare among agents with shared constraints and submodular utilities under bandit feedback.
method Proposes an explore-then-commit strategy with randomized assignments for multi-agent combinatorial bandits.
result Achieves regret, first for partition-based submodular welfare problem under bandit feedback.
The paper tackles adaptive policy selection to maximize social welfare, achieving optimal regret bounds.
problem Maximizing social welfare through adaptive policy selection, considering both private utility and public revenue.
method The approach involves learning response functions through experimentation, deriving lower and upper bounds for regret, and using algorithms like Exp3.
result The algorithm achieves optimal regret bounds, showing that welfare maximization is harder than multi-armed bandit problems.
The paper automates policy learning for nonlinear welfare criteria using machine learning and debiasing techniques.
problem Learning optimal policies from observational data with nonlinear welfare criteria.
method Modeling a nonlinear welfare criterion with a utility function, estimating propensity scores with machine learning, and using sieve approximations and cross-validation for model selection.
result The proposed policy learning method satisfies oracle inequalities, providing theoretical guarantees on performance.
New job recommendation system improves job seekers' welfare through field experiments.
problem Current job recommendation systems focus on clicks and applications, not job seekers' welfare.
method Developed a job-search model with two dimensions: utility and success probability. Conducted field experiments to validate model predictions.
result Welfare-optimal job recommendation algorithms outperform existing approaches and perform close to the benchmark.
Investors suffer welfare loss despite having better information.
problem Welfare loss among investors with absolute information advantages.
method Examined financial markets with heterogenous investors and objective measures of welfare.
result Investors incur welfare loss even with better information, revealing a double loss phenomenon.
The paper develops an economic foundation for multi-agent learning in markets.
problem Learning dynamics in markets with strategic externalities.
method A two-phase incentive mechanism that estimates and uses implementable transfers to steer long-run dynamics.
result The mechanism achieves sublinear social-welfare regret and asymptotically optimal welfare under mild rationality and exploration conditions.
New framework improves cost-benefit analysis of policies.
problem Limitations of MVPF in welfare analysis.
method Developed an axiomatic framework to create RPV.
result RPV provides better equity-efficiency trade-off quantification.
Now that machine learning algorithms lie at the center of many resource allocation pipelines, computer scientists have been unwittingly cast as partial social planners. Given this state of affairs, important questions follow. What is the relationship between fairness as defined by computer scientists and notions of soc…
Although both systems analyzed are described through two theories apparently different (quantum mechanics and game theory) it is shown that both are analogous and thus exactly equivalents. The quantum analogue of the replicator dynamics is the von Neumann equation. Quantum mechanics could be used to explain more correc…
The so called "globalization" process (i.e. the inexorable integration of markets, currencies, nation-states, technologies and the intensification of consciousness of the world as a whole) has a behavior exactly equivalent to a system that is tending to a maximum entropy state. This globalization process obeys a collec…
Study bridges welfare maximization and CATE estimation in policy learning.
problem Tackles the gap between empirical welfare maximization and conditional average treatment effect estimation in policy learning.
method Shows equivalence between EWM and least squares over reparameterized policy class, proposes regularization method.
result Both approaches are interchangeable under common conditions and share theoretical guarantees.
Existence of incomplete Radner equilibrium with endogenous noise tracker.
problem Existence of incomplete Radner equilibrium in a model with endogenous noise tracker.
method Proved existence through a coupled system of ODEs, reduced to two coupled ODEs.
result Endogenous noise tracker leads to higher aggregate welfare for large stock supply.
The paper proposes a new policy for optimal treatment allocation based on quantile treatment effects.
problem Optimal treatment allocation policies that target distributional welfare, especially when individuals are heterogeneous.
method The approach involves allocating treatments based on the conditional quantile of individual treatment effects (QoTE), considering both prudent and negligent policymakers.
result The proposed minimax policies are robust to model uncertainty and can be generalized to various settings.
New welfare-based fairness notions align with existing error rate balance and predictive parity.
problem Aligning fairness notions with welfare-based criteria.
method Discussing and establishing conditions for envy freeness and prejudice freeness.
result Envy freeness and prejudice freeness are equivalent to error rate balance and predictive parity.
Adopting a zonal structure of electricity market requires specification of zones' borders. In this paper we use social welfare as the measure to assess quality of various zonal divisions. The social welfare is calculated by Market Coupling algorithm. The analyzed divisions are found by the usage of extended Locational …
Our work extends Coase's theorem to settings with uncertainty, showing how to maximize social welfare through property rights and learning.
problem Theoretical models of externality often assume perfect knowledge, limiting practical solutions.
method We extend Coase's theorem to a two-player bandit setting with uncertainty, designing a learning policy to maximize social welfare.
result We show that property rights and learning can recover Coase's theorem in settings with uncertainty.
Framework for online resource allocation using social welfare functions.
problem Optimal allocation of resources over time steps in a population.
method Confidence sequence framework for SWF-based online learning and inference, valid for any monotonic, concave, and Lipschitz-continuous SWF.
result Achieves near-optimal regret of for SWF-agnostic algorithm SWF-UCB.
The paper explores fairness, welfare, and equity in personalized pricing across various applications.
problem Interplay of fairness, welfare, and equity in personalized pricing based on customer features.
method Comprehensive literature review and observational metrics without underlying valuation distribution assumptions.
result Personalized pricing can expand access, improve welfare, and increase revenue or budget utilization.
This paper studies the problem of optimally allocating treatments in the presence of spillover effects, using information from a (quasi-)experiment. I introduce a method that maximizes the sample analog of average social welfare when spillovers occur. I construct semi-parametric welfare estimators with known and unknow…
Privacy subsidy found in market trading with noisy direction signals.
problem Analyzing welfare and bid-ask spread in a market with privacy mechanisms.
method Closed-form derivation of bid-ask spread and welfare under flip-noise direction observation.
result Privacy subsidy of from liquidity pool to traders, robust across models.
This paper tackles no-regret learning for fair multi-agent social welfare optimization.
problem Maximizing social welfare in a fair manner for multiple agents.
method Developed algorithms for stochastic and adversarial multi-agent settings, proving regret bounds and tightness.
result Achieved no-regret learning for fair multi-agent social welfare optimization in various settings.
Homeownership boosts wealth and welfare compared to renting, according to new research.
problem The conventional wisdom that renting is better than owning a home.
method Block-bootstrap lifecycle simulation to compare homeownership and renting strategies.
result Homeownership generates more wealth and welfare gains than renting, especially for households with high labor income.
Examines optimal risk sharing with realistic risk attitudes, finding risk seeking in certain subdomains.
problem Optimal risk sharing with empirically realistic risk attitudes.
method Allows for risk-seeking agents, generalizes expected utility, and uses counter-monotonic improvement theorem.
result First empirical results on optimal risk sharing with realistic risk attitudes.
The study evaluates how prediction helps identify the worst-off in welfare programs.
problem Identifying the most vulnerable individuals for support.
method Mathematical models and real-world case study on long-term unemployment.
result Prediction is more effective than other policy levers in surfacing the worst-off.
Algorithm learns fair division from noisy feedback in uncertain markets.
problem Learning fair division in uncertain markets with noisy feedback.
method Wrapper algorithms using dual averaging to learn item and agent values from bandit feedback.
result Asymptotically achieves optimal Nash social welfare in linear Fisher markets.
The paper explores fair machine learning policies for balancing competing objectives in noisy data.
problem Balancing competing objectives in noisy data.
method Analyzes a class of policies that trace an empirical Pareto frontier based on learned scores.
result Characterizes optimal strategies and bounds Pareto errors due to score inaccuracies.
Laser Welfare: First Steps in Econodynamic Engineeringcond-mat.other
The paper starts with a brief review of present understanding of income distributions; especially with regard to recent work in the field of econophysics that draws parallels between income, wealth and energy distributions. Examples of alternative energy distributions found in physical systems are discussed, and how th…
Bayesian framework for policy learning in decision problems.
problem Maximizing expected welfare in decision-making problems.
method Loss-based Bayesian updating and squared-loss surrogate for welfare maximization.
result General Bayes posterior over decision rules with Gaussian pseudo-likelihood interpretation.
Improved model accuracy can reduce overall user accuracy in competitive markets.
problem The impact of model competition on overall user accuracy.
method Defined a model of competition for classification tasks and used data representations to study the effect of scale.
result Improving data representation quality can decrease overall predictive accuracy across users (social welfare) in a competitive market.
Singapore's cooling measures did not increase housing wealth overall.
problem The impact of cooling measures on housing wealth distribution.
method Examined Singapore's cooling measures over ten rounds, analyzing welfare from housing wealth.
result Welfare from housing wealth in the last round might not be higher than before 2009, depending on the deflator.
Study incentive efficiency in monopoly insurance markets with hidden information.
problem Maximizing social welfare in a monopoly insurance market with hidden agent types.
method Maximizes social welfare function subject to incentive compatibility and individual rationality constraints.
result Optimal menus of contracts depend on the level of social welfare weight and agent risk attitudes.
By analyzing the relationships between a socioeconomical system modeled through evolutionary game theory and a physical system modeled through quantum mechanics we show how although both systems are described through two theories apparently different both are analogous and thus exactly equivalents. The extensions of qu…
The study assesses the relative value of prediction in algorithmic decision making.
problem Improving welfare through better predictions versus other policy levers.
method Theoretical analysis of statistical models.
result Simple conditions determining the relative value of prediction.
Study tackles RLHF with diverse human feedback, showing limitations and proposing a meta-learning approach.
problem Traditional RLHF fails to balance diverse human preferences.
method Integrates meta-learning and multiple social welfare functions to optimize diverse preferences.
result Establishes sample complexity bounds for optimizing diverse social welfare functions.
New mechanism designs regulate herding in financial markets.
problem Herding causes irrational market decisions and volatility.
method A trilateral game framework based on optimal control theory.
result Effective mechanisms improve social welfare.
This paper identifies and analyzes biases in risk-adjusted index weighting methods, affecting social welfare and market fairness.
problem Biases in risk-adjusted index weighting methods lead to tracking errors and fraud in indices and ETFs.
method Characterizes and analyzes the biases and adverse effects of risk-adjusted index weighting methods.
result These biases reduce social welfare and can enable harmful arbitrage activities.
The paper develops methods to estimate optimal treatment sequences under policy constraints.
problem Estimating the best sequence of treatments over multiple stages for individuals.
method Empirical welfare maximization approach, solving treatment assignment sequentially or simultaneously.
result Established convergence rates and upper bounds for estimation methods.
Poultry farms are an important contributor to the human food chain. Worldwide, humankind keeps an enormous number of domesticated birds (e.g. chickens) for their eggs and their meat, providing rich sources of low-fat protein. However, around the world, there have been growing concerns about the quality of life for the …
When Indemnity Insurance Fails: Parametric Coverage under Binding Budget and Risk Constraintsecon.GN
Parametric insurance offers better risk-sharing in high-risk settings than traditional indemnity insurance.
problem High-risk environments where traditional indemnity insurance is unaffordable or ineffective.
method Comparison of excess-of-loss indemnity insurance and parametric insurance within a mean-variance framework, considering fixed costs and binding budget constraints.
result Parametric insurance yields higher welfare for risk-averse individuals, especially when indemnity insurance is impractical.
Dynamic pricing improves DeFi lending efficiency by reducing regret to logarithmic levels.
problem Static pricing mechanisms in DeFi lending protocols lead to suboptimal welfare and revenue.
method Online learning model for static and dynamic pricing models in DeFi lending.
result Adaptive supply models achieve logarithmic regret, outperforming static models.
Inequalities of wealth distribution in a conservative economycond-mat.stat-mech
We analyze a conservative market model for the competition among economic agents in a close society. A minimum dynamics ensures that the poorest agent has a chance to improve its economic welfare. After a transient, the system self-organizes into a critical state where the wealth distribution have a minimum threshold, …
Study copyright's impact on creative industries using AI-generated fonts.
problem Estimating supply and demand in creative industries with AI-generated content.
method Neural network embeddings, spatial regression, event-study analyses, structural model of supply and demand.
result Copyright can raise consumer welfare by encouraging product relocation.
Platform uses queries to elicit investor preferences for portfolio trades, improving allocation efficiency.
problem Hidden-information problem in institutional crossing markets where investors value trades as portfolios but liquidity discovery is organized by individual securities.
method Modeling portfolio crossing as preference elicitation, using price-directed demand queries and value queries to verify selected packages.
result Hybrid procedure using demand and value queries recovers 88-95% of full-information welfare with a limited query budget.
Asymmetric Nonlinear Return Extrapolation and Optimal Portfolio Choice under Stochastic Volatilityq-fin.PM
Extends return extrapolation to nonlinear, asymmetric functions under stochastic volatility.
problem Behavioral anomalies in portfolio choice under stochastic volatility.
method Smooth, nonlinear, asymmetric extrapolation function; CRRA investor; Heston stochastic volatility; Hamilton-Jacobi-Bellman equation; Numerical solutions (finite-difference ADI, deep learning-driven iterative).
result Saturation acts as an endogenous correction mechanism, reducing welfare loss.
BRACE addresses noncompliance in bandits, offering methods for recommendation and treatment policies.
problem Noncompliance in bandit problems complicates learning objectives and treatment effects.
method BRACE formalizes objective-choice, identifies direct-control regimes, and proposes a phase-doubling algorithm for IV inversion.
result BRACE delivers valid policy values and structural uncertainty, even under weak identification and homogeneity failure.