pwc-archive/papers-with-abstracts huggingface dataset:
Beyond the Median Voter Theorem: A New Framework for Ideological Positioning
Authors: Shitong Wang
Date: 2025-02-10 00:00:00

This paper revisits the limitations of the Median Voter Theorem and introduces a novel framework to analyze the optimal economic ideological positions of political parties. By incorporating Nash equilibrium, we examine the mechanisms and elasticity of ideal deviation costs, voter distribution, and policy feasibility. Our findings show that an increase in a party's ideal deviation cost shifts its optimal ideological position closer to its ideal point. Additionally, if a voter distribution can be expressed as a positive linear combination of two other distributions, its equilibrium point must lie within the interval defined by the equilibrium points of the latter two. We also find that decreasing feasibility costs incentivize governments, regardless of political orientation, to increase fiscal expenditures (e.g., welfare) and reduce fiscal revenues (e.g., taxes). This dynamic highlights the fiscal pressures commonly faced by democratic nations under globalization. Moreover, we demonstrate that even with uncertain voter distributions, parties can identify optimal ideological positions to maximize their utility. Lastly, we explain why the proposed framework cannot be applied to community ideologies due to their fundamentally different nature. This study provides new theoretical insights into political strategies and establishes a foundation for future empirical research.
Incorporating Damped Harmonic Oscillator in DSGE Models
Authors: Wei Chun Hsu
Date: 2025-02-10 00:00:00

This paper integrates the damped harmonic oscillator into DSGE models to better capture delayed economic adjustments. By introducing a damping coefficient, I model economic recoveries as under-damped, critically damped, or over-damped processes. Numerical simulations illustrate how different damping levels affect recovery speed and stability. This approach enhances DSGE models' realism, offering insights into historical economic crises and improving macroeconomic forecasting.
Words or Numbers? How Framing Uncertainties Affects Risk Assessment and Decision-Making
Authors: Robin Bodenberger, Kirsten Thommes
Date: 2025-02-10 00:00:00
Tasks: Decision Making, Decision Making Under Uncertainty

The communication of uncertainties needs to be as precise as possible to enable the receiver of risk-messages to adapt their behavior appropriately. However, the communication of uncertainties comes with its own set of challenges as most senders prefer to communicate uncertainty through verbal probability phrases (e.g., likely) - a communication form characterized by its ambiguity and (framed) directionality. While it is well known that receivers often do not translate such phrases into the numerical probability intended by the sender, it is less clear how this discrepancy influences subsequent behavioral actions. By implementing a laboratory experiment, we show that individuals value uncertain options with medium to high likelihoods significantly lower when uncertainty is communicated verbally rather than numerically. This effect may lead to less rational decisions under verbal communication, particularly at high likelihoods. Those results remain consistent even if individuals translate verbal uncertainty correctly into the associate numerical uncertainty, implying that a biased behavioral response is not only induced by mistranslations. Instead, ambiguity about the exact meaning of a verbal phrase interferes with decision-making even beyond mere mistranslations. These findings tie in with previous research on ambiguity aversion, which has predominantly operationalized ambiguity through numerical ranges rather than verbal phrases. We conclude that managers and firms should carefully consider the impact of uncertainty framing on employees' decision-making and customer purchasing behavior, opting for numerical probabilities when possible.
Compounding Effect of Harsh Climate and Societal Disruptions on Food Prices in Early Modern Europe
Authors: Emile Esmaili, Michael J. Puma, Francis Ludlow, Eva Jobbova
Date: 2025-02-10 00:00:00

The complex interplay between famine, warfare, and climate constitutes a multifaceted and context-dependent relationship that has profoundly influenced human history, particularly in early modern Europe. This study advances the literature on climate-economy interactions by leveraging multi-scale statistical techniques to quantify the compounded effects of climate variability and socio-political factors on food prices, offering novel model-based insights into the historical dynamics of climate and economic systems. Using Canonical Correlation Analysis (CCA), we investigate the influence of temperature fluctuations and drought severity on food prices across 14 European cities from 1565 to 1785. Our findings confirm a persistent negative relationship between temperature and food prices over the long term, while the relationship between drought severity and price dynamics appears positive yet inconsistent. Extending our analysis to higher-frequency patterns, we demonstrate that cold anomalies are strongly associated with food price that caused large-scale famines of the 1590s and 1690s. Likewise, we show that the severe and consecutive droughts of 1634 to 1636, coinciding with the Thirty Years' War, significantly amplified food price volatility, illustrating how climatic shocks can compound socio-economic and political crises. Furthermore, we identify years characterized by the simultaneous occurrence of extreme cold and drought as periods of heightened price instability, underscoring the compounded impact of concurrent climatic stressors on food prices during the early modern period.
Rising Marginal Costs, Rising Prices?
Authors: Joel Kariel, Anthony Savagar
Date: 2025-02-09 00:00:00

We present empirical evidence on the relationship between demand shocks and price changes, conditional on returns to scale. We find that in industries with decreasing returns to scale, demand increases (which raise costs) correspond to price increases. Whereas, in industries with increasing returns to scale, demand increases (which lower costs) correspond to stable prices. We interpret the results with a theory of imperfect competition and returns to scale. For prices to remain stable following a cost decrease, markups necessarily rise. For prices to increase as cost increases, it is not necessary for markups to change but does not preclude their role. From a macroeconomic perspective, our results imply that inflation dynamics and the effectiveness of monetary policy depend on market structures.
Managing Geological Uncertainty in Critical Mineral Supply Chains: A POMDP Approach with Application to U.S. Lithium Resources
Authors: Mansur Arief, Yasmine Alonso, CJ Oshiro, William Xu, Anthony Corso, David Zhen Yin, Jef K. Caers, Mykel J. Kochenderfer
Date: 2025-02-08 00:00:00
Tasks: Decision Making

The world is entering an unprecedented period of critical mineral demand, driven by the global transition to renewable energy technologies and electric vehicles. This transition presents unique challenges in mineral resource development, particularly due to geological uncertainty-a key characteristic that traditional supply chain optimization approaches do not adequately address. To tackle this challenge, we propose a novel application of Partially Observable Markov Decision Processes (POMDPs) that optimizes critical mineral sourcing decisions while explicitly accounting for the dynamic nature of geological uncertainty. Through a case study of the U.S. lithium supply chain, we demonstrate that POMDP-based policies achieve superior outcomes compared to traditional approaches, especially when initial reserve estimates are imperfect. Our framework provides quantitative insights for balancing domestic resource development with international supply diversification, offering policymakers a systematic approach to strategic decision-making in critical mineral supply chains.
Does the financialization of agricultural commodities impact food security? An empirical investigation
Authors: Manogna R. L., Nishil Kulkarni
Date: 2025-02-08 00:00:00
Tasks: regression

The financialization of agricultural commodities and its impact on food security has become an increasing concern. This study empirically investigates the role of financialization in global food markets and its policy implications for a stable and secure food system. Using panel data regression models, moderating effects models, and panel regression with a threshold variable, we analyze wheat, maize, and soybean futures traded on the Chicago Board of Trade. We incorporate data on annual trading volume, open interest contracts, and their ratio. The sample consists of five developed countries (United States, Australia, Canada, France, Germany) and seven developing countries (China, Russia, India, Indonesia, Brazil, Vietnam, Thailand), covering the period 2000 to 2021. The Human Development Index (HDI) serves as a threshold variable to differentiate the impact across countries. Our findings indicate that the financialization of agricultural commodities has negatively affected global food security, with wheat and soybean showing a greater adverse impact than maize. The effects are more pronounced in developing countries. Additionally, we find that monetary policy has the potential to mitigate these negative effects. These results provide insights for policymakers to design strategies that ensure a secure and accessible global food supply.
Robust valuation and optimal harvesting of forestry resources in the presence of catastrophe risk and parameter uncertainty
Authors: Ankush Agarwal, Christian Ewald, Yihan Zou
Date: 2025-02-07 00:00:00

We determine forest lease value and optimal harvesting strategies under model parameter uncertainty within stochastic bio-economic models that account for catastrophe risk. Catastrophic events are modeled as a Poisson point process, with a two-factor stochastic convenience yield model capturing the lumber spot price dynamics. Using lumber futures and US wildfire data, we estimate model parameters through a Kalman filter and maximum likelihood estimation and define the model parameter uncertainty set as the 95% confidence region. We numerically determine the forest lease value under catastrophe risk and parameter uncertainty using reflected backward stochastic differential equations (RBSDEs) and establish conservative and optimistic bounds for lease values and optimal stopping boundaries for harvesting, facilitating Monte Carlo simulations. Numerical experiments further explore how parameter uncertainty, catastrophe intensity, and carbon sequestration impact the lease valuation and harvesting decision. In particular, we explore the costs arising from this form of uncertainty in the form of a reduction of the lease value. These are implicit costs that can be attributed to climate risk and will be emphasized through the importance of forestry resources in the energy transition process. We conclude that in the presence of parameter uncertainty, it is better to lean toward a conservative strategy reflecting, to some extent, the worst case than being overly optimistic. Our results also highlight the critical role of convenience yield in determining optimal harvesting strategies.
The Economics of Large Language Models: Token Allocation, Fine-Tuning, and Optimal Pricing
Authors: Dirk Bergemann, Alessandro Bonatti, Alex Smolin
Date: 2025-02-11 00:00:00

We develop an economic framework to analyze the optimal pricing and product design of Large Language Models (LLM). Our framework captures several key features of LLMs: variable operational costs of processing input and output tokens; the ability to customize models through fine-tuning; and high-dimensional user heterogeneity in terms of task requirements and error sensitivity. In our model, a monopolistic seller offers multiple versions of LLMs through a menu of products. The optimal pricing structure depends on whether token allocation across tasks is contractible and whether users face scale constraints. Users with similar aggregate value-scale characteristics choose similar levels of fine-tuning and token consumption. The optimal mechanism can be implemented through menus of two-part tariffs, with higher markups for more intensive users. Our results rationalize observed industry practices such as tiered pricing based on model customization and usage levels.
A deterministic electoral system satisfying Arrow's four conditions in an easily approached limit
Authors: Roger F. Sewell
Date: 2025-02-11 00:00:00

In 1950 Arrow famously showed that there is no social welfare function satisfying four basic conditions. In 1976, on the other hand, Gibbard and Sonnenschein showed that there does exist a unique probabilistic social welfare method that satisfies a different set of strictly stronger conditions. In this paper we discuss a deterministic electoral method satisfying those same stronger conditions in an appropriate sense; it is not a counterexample to either of these theorems. We attach a simple reference implementation written in C with executables for Linux and Windows.
Robust pricing for cloud computing
Authors: Dirk Bergemann, Rahul Deb
Date: 2025-02-11 00:00:00
Tasks: Cloud Computing

We study the robust sequential screening problem of a monopolist seller of multiple cloud computing services facing a buyer who has private information about his demand distribution for these services. At the time of contracting, the buyer knows the distribution of his demand of various services and the seller simply knows the mean of the buyer's total demand. We show that a simple "committed spend mechanism" is robustly optimal: it provides the seller with the highest profit guarantee against all demand distributions that have the known total mean demand. This mechanism requires the buyer to commit to a minimum total usage and a corresponding base payment; the buyer can choose the individual quantities of each service and is free to consume additional units (over the committed total usage) at a fixed marginal price. This result provides theoretical support for prevalent cloud computing pricing practices while highlighting the robustness of simple pricing schemes in environments with complex uncertainty.
Decision theory and the "almost implies near" phenomenon
Authors: Christopher P Chambers, Federico Echenique
Date: 2025-02-10 00:00:00

Traditional decision theory establishes equivalence between axioms and the functional forms of utility representations. In this paper, we develop a new framework where axioms need only be approximately satisfied, introducing a principled approach to measuring the degree of axiom violations. Our central finding is that behavior that "almost" satisfies canonical axioms induces utility representations that are "near" the standard utility forms associated with those axioms. Specifically, when agents approximately satisfy axioms like independence or stationarity, their utility functions can be approximated by the corresponding canonical utilities, with quantifiable error bounds directly linked to the magnitude of axiom violations. We apply this phenomenon across three domains: decisions under risk, uncertainty, and intertemporal choice. Our results provide theoretical foundations for approximate optimization in economics and offer a middle ground between rejecting theories and requiring exact axioms, and accommodating small deviations from the theory in empirical work.
Experiments in the Linear Convex Order
Authors: Kailin Chen
Date: 2025-02-10 00:00:00
Tasks: valid

This paper proposes two rankings of statistical experiments using the linear convex order. These rankings hold in a broader set of scenarios where intuition suggests that one experiment is more informative than another, and provide more tractable characterizations than Blackwell order, which relies on the convex order. We apply these rankings to compare statistical experiments in binary-action decision problems and in decision problems that aggregate payoffs over a collection of binary-action decision problems. Furthermore, these rankings enable comparisons of statistical experiments in moral hazard problems without requiring the validity of the first-order approach, thereby complementing the results in Holmstr\"om (1979) and Kim (1995).
Marginal Mechanisms For Balanced Exchange
Authors: Vikram Manjunath, Alexander Westkamp
Date: 2025-02-10 00:00:00

We consider the balanced exchange of bundles of indivisible goods. We are interested in mechanisms that only rely on marginal preferences over individual objects even though agents' actual preferences compare bundles. Such mechanisms play an important role in two-sided matching but have not received much attention in exchange settings. We show that individually rational and Pareto-efficient marginal mechanisms exist if and only if no agent ever ranks any of her endowed objects lower than in her second indifference class. We call such marginal preferences trichotomous. In proving sufficiency, we define mechanisms, which are constrained versions of serial dictatorship, that achieve both desiderata based only agents' marginal preferences. We then turn to strategy-proofness. An individually rational, efficient and strategy-proof mechanism-marginal or not-exists if and only if each agent's marginal preference is not only trichotomous, but does not contain a non-endowed object in her second indifference class. We call such marginal preferences strongly trichotomous. For such preferences, our mechanisms reduce to the class of strategy-proof mechanisms introduced in Manjunath and Westkamp (2018). For trichotomous preferences, while our variants of serial dictatorship are not strategy-proof, they are truncation-proof and not obviously manipulable (Troyan and Morrill, 2020).
Weak independence of irrelevant alternatives and generalized Nash bargaining solutions
Authors: Kensei Nakamura
Date: 2025-02-10 00:00:00

In Nash's (1950) seminal result, independence of irrelevant alternatives (IIA) plays a central role, but it has long been a subject of criticism in axiomatic bargaining theory. This paper examines the implication of a weak version of IIA in multi-valued bargaining solutions defined on non-convex bargaining problems. We show that if a solution satisfies weak IIA together with standard axioms, it can be represented, like the Nash solution, using weighted products of normalized utility levels. In this representation, the weight assigned to players for evaluating each agreement is determined endogenously through a two-stage optimization process. These solutions bridge the two dominant solution concepts, the Nash solution and the Kalai-Smorodinsky solution (Kalai and Smorodinsky, 1975). Furthermore, we consider special cases of these solutions in the context of bargaining over linear production technologies.
Full Implementation via Information Design in Nonatomic Games
Authors: Frederic Koessler, Marco Scarsini, Tristan Tomala
Date: 2025-02-09 00:00:00
Tasks: All

This paper studies the implementation of Bayes correlated equilibria in symmetric Bayesian nonatomic games, using direct information structures and obedient strategies. The main results demonstrate full implementation in a class of games with positive cost externalities. Specifically, if the game admits a strictly convex potential in every state, then for every Bayes correlated equilibrium outcome with finite support and rational action distributions, there exists a direct information structure that implements this outcome under all equilibria. When the potential is only weakly convex, we show that all equilibria implement the same expected social cost. Additionally, all Bayes correlated equilibria, including those with infinite support or irrational action distributions, are approximately implemented.
Discounting under inequality and lobbyists disagreement
Authors: Mahdi Mousavi, Mahdi Kohan Sefidi
Date: 2025-02-07 00:00:00
Tasks: Decision Making

The appropriate discount rate for evaluating policies is a critical consideration in economic decision-making. This paper presents a new model for calculating the derived discount rate for a society that includes different groups with varying desirable discount rates. The model takes into account equality in society and is designed to be used by social planners. The derived discount rate is a useful tool for examining the social planner's approach to policies related to the future of society. If the discount rate is determined correctly, it can help determine the amount of growth and equality in society, as well as the level of attention paid to long-term public projects. The model can be customized for different distributions of wealth and discount rates, allowing researchers to extract desired results. Analysis of the model shows that when equality in society is considered, the derived discount rate is lower than the result obtained using Hamilton's method. Social planners must consider that this may increase disagreement in more consuming groups of society at first.
Towards Efficient and Multifaceted Computer-assisted Pronunciation Training Leveraging Hierarchical Selective State Space Model and Decoupled Cross-entropy Loss
Authors: Fu-An Chao, Berlin Chen
Date: 2025-02-11 00:00:00

Prior efforts in building computer-assisted pronunciation training (CAPT) systems often treat automatic pronunciation assessment (APA) and mispronunciation detection and diagnosis (MDD) as separate fronts: the former aims to provide multiple pronunciation aspect scores across diverse linguistic levels, while the latter focuses instead on pinpointing the precise phonetic pronunciation errors made by non-native language learners. However, it is generally expected that a full-fledged CAPT system should perform both functionalities simultaneously and efficiently. In response to this surging demand, we in this work first propose HMamba, a novel CAPT approach that seamlessly integrates APA and MDD tasks in parallel. In addition, we introduce a novel loss function, decoupled cross-entropy loss (deXent), specifically tailored for MDD to facilitate better-supervised learning for detecting mispronounced phones, thereby enhancing overall performance. A comprehensive set of empirical results on the speechocean762 benchmark dataset demonstrates the effectiveness of our approach on APA. Notably, our proposed approach also yields a considerable improvement in MDD performance over a strong baseline, achieving an F1-score of 63.85%. Our codes are made available at https://github.com/Fuann/hmamba