pwc-archive/papers-with-abstracts huggingface dataset:
The Effect of the Gotthard Base Tunnel on Road Traffic: A Synthetic Control Approach
Authors: Hannes Wallimann, Widar von Arx, Ann Hesse
Date: 2025-05-27 00:00:00

The opening of the Gotthard Base Tunnel in 2017, the longest railway tunnel in the world, marked a milestone in Swiss transport policy. The tunnel, a part of the New Rail Link through the Alps, serves as a key instrument of the so-called "modal shift policy," which aims to transfer transalpine freight traffic from road to rail. The reduction in travel time by train between northern and southern Switzerland raised expectations that a substantial share of tourist-oriented passenger traffic would also shift from car to rail. In this paper, we conduct a causal analysis of the impact of the Gotthard Base Tunnel's opening at the end of 2016 on the number of cars using the parallel Gotthard motorway section in the subsequent years. To this end, we apply the synthetic control and the synthetic difference-in-differences methods to construct a synthetic Gotthard motorway section based on a weighted combination of other alpine road crossings (a so-called donor pool) that did not experience the construction of a competing rail infrastructure. Our results reveal only a modest but statistically significant decline in the number of cars between the actual and the synthetic Gotthard motorway in the short run. Given the consistently strong and increasing demand for the new rail connection through the Gotthard Base Tunnel, we infer a substantial induced short-run demand effect resulting from the rail travel time savings.
Prestige in Numbers: How Test Scores and Choices Reveal School Rankings
Authors: Federico Echenique, Michael Olabisi
Date: 2025-05-27 00:00:00

This paper introduces a novel revealed-preference approach to ranking colleges and professional schools based on applicants' choices and standardized test scores. Unlike traditional rankings that rely on data supplied by institutions or expert opinions, our methodology leverages the decentralized beliefs of potential students, as revealed through their application decisions. We develop a theoretical model where students with higher test scores apply to more selective institutions, allowing us to establish a clear relationship between test score distributions and school prestige. Using comprehensive data from over 490,000 GMAT test-takers applying to U.S. full-time MBA programs, we implement two ranking methods: one based on monotone functions of test scores across schools, and another using score-adjusted tournaments between school pairs. Our approach has distinct advantages over traditional rankings: it reflects the collective judgment of the entire applicant pool rather than a small group of experts, and it utilizes data from an independent testing organization, making it resistant to manipulation by institutions. The resulting rankings correlate strongly with leading published MBA rankings ($\rho = 0.72$) while offering the additional benefit of being customizable for different student subgroups. This method provides a transparent alternative to existing ranking systems that have been subject to well-documented manipulation.
Manufacturing Revolutions: Industrial Policy and Industrialization in South Korea
Authors: Nathan Lane
Date: 2025-05-26 00:00:00

I study the impact of industrial policies on industrial development by considering an important episode during the East Asian miracle: South Korea's heavy and chemical industry (HCI) drive, 1973--1979. Based on newly assembled data, I use the introduction and termination of industrial policies to study their impacts during and after the intervention period. (1) I reveal that heavy-chemical industrial policies promoted the expansion and dynamic comparative advantage of directly targeted industries. (2) Using variation in exposure to policies through the input-output network, I demonstrate that the policy indirectly benefited downstream users of targeted intermediates. (3) The benefits of HCI persisted even after the policy ended, as some results were slower to appear. The findings suggest that the temporary drive shifted Korean manufacturing into more advanced markets and supported durable change. This study helps clarify the lessons drawn from the East Asian growth miracle. JEL Codes: L5, O14, O25, N6. Keywords: industrial policy, East Asian miracle, economic history, industrial development, Heavy-Chemical Industry Drive, Heavy and Chemical Industry Drive.
Financial literacy, robo-advising, and the demand for human financial advice: Evidence from Italy
Authors: David Aristei, Manuela Gallo
Date: 2025-05-26 00:00:00

This paper investigates the impact of objective financial knowledge, confidence in one's financial skills, and digital financial literacy on individuals' decisions to seek financial advice from robo-advice platforms. Using microdata from the Bank of Italy's 2023 survey on Italian adults' financial literacy, we find that individuals with greater financial knowledge are less inclined to rely on online services for automated financial advice. Conversely, confidence in one's financial abilities and digital financial literacy enhance the likelihood of utilising robo-advice services. Trust in financial innovation, the use of digital financial services, and the propensity to take risks and save also emerge as significant predictors of an individual's use of robo-advice. We also provide evidence of a significant complementary relationship between the adoption of robo-advisory services and the demand for independent professional human advice. By contrast, a substitution effect is found for non-independent human advice. These findings highlight the importance of hybrid solutions in professional financial consulting, where robo-advisory services complement human financial advice.
Academic Research Output Derivatives: Structuring Futures and Options on Research Output Index
Authors: Amarendra Sharma
Date: 2025-05-26 00:00:00

This paper explores an innovative financial concept--Academic Research Output Futures (AROFs)--which aim to bring the tools of market-based finance into the realm of academic research. At the heart of this idea lies a cash-settled futures contract tethered to a composite Research Output Index (ROI), a metric designed to quantify the research productivity of universities and research institutions. By allowing investors to take positions--speculative or hedging--on the projected trajectory of academic performance, AROFs open the door to a fundamentally new funding model. For universities, this could mean access to capital markets without relying solely on grants, donations, or government subsidies. Accompanying these futures are Academic Research Output Options (AROOs), providing a layer of strategic nuance and risk control, much like options in traditional financial markets. The paper delves into the architecture of the ROI, the mechanics of the derivative instruments, regulatory and legal challenges, and the broader strategic consequences of such a framework. If realized, this model could represent a significant departure from conventional research funding approaches--one that aligns scholarly output with financial incentives in ways both promising and provocative.
Private MEV Protection RPCs: Benchmark Stud
Authors: Paul Janicot, Alex Vinyas
Date: 2025-05-26 00:00:00
Tasks: POS

Decentralized Finance (DeFi) on Ethereum has undergone significant transformations since its emergence during the DeFi summer of 2020. With the introduction of Proof of Stake (PoS) and Proposer-Builder Separation (PBS), the transaction supply chain on Ethereum has shifted from relying entirely on the public mempool for DeFi interactions to an astonishing 80% usage of private RPCs. These private RPCs submit transactions directly to builders, skipping the public mempool, while conducting Order Flow Auctions (OFAs) to capture MEV backrun rebates and gas rebates. Our findings reveal that not all RPCs OFAs produce the same outcomes. These insights underscore the significant implications of OFA design choices on transaction efficiency and execution quality, and thus why an order flow originators should pay close attention to which OFA they use.
A General Theory of Growth, Employment, and Technological Change: Experiential Matrix Theory and the Transition from GDP to Humanist Experiential Growth in the Age of Artificial Intelligence
Authors: Christian Callaghan
Date: 2025-05-25 00:00:00

This paper introduces Experiential Matrix Theory (EMT), a general theory of growth, employment, and technological change for the age of artificial intelligence (AI). EMT redefines utility as the alignment between production and an evolving, infinite-dimensional matrix of human experiential needs, thereby extending classical utility frameworks and integrating ideas from the capabilities approach of Sen and Nussbaum into formal economic optimisation modelling. We model the economy as a dynamic control system in which AI collapses ideation and coordination costs, transforming production into a real-time vector of experience-aligned outputs. Under this structure, the production function becomes a continuously learning map from goods to experiential utility, and economic success is redefined as convergence toward an asymptotic utility frontier. Using Pontryagin's Maximum Principle in an infinite-dimensional setting, we derive conditions under which AI-aligned output paths are asymptotically optimal, and prove that unemployment is Pareto-inefficient wherever unmet needs and idle human capacities persist. On this foundation, we establish Alignment Economics as a new research field dedicated to understanding and designing economic systems in which technological, institutional, and ethical architectures co-evolve. EMT thereby reframes policy, welfare, and coordination as problems of dynamic alignment, not static allocation, and provides a mathematically defensible framework for realigning economic production with human flourishing. As ideation costs collapse and new experiential needs become addressable, EMT shows that economic growth can evolve into an inclusive, meaning-centred process -- formally grounded, ethically structured, and AI-enabled.
A representation theorem for events within lattice structures of state-spaces
Authors: Alex A. T. Rathke
Date: 2025-05-24 00:00:00

For the standard lattice model of information structures, we derive a reduced poset representation which provides the same informational content as the complete lattice structure which derives it. Rational agents can recover the complete lattice of events by means of the reduced poset alone. We find that both structures provide isomorphic models under mild conditions.
Down to the Last Strike: The Effect of the Jury Lottery on Criminal Convictions
Authors: Scott Kostyshak, Neel U. Sukhatme
Date: 2025-05-23 00:00:00
Tasks: counterfactual

How much does luck matter to a criminal defendant in a jury trial? We use rich data on jury selection to causally estimate how parties who are randomly assigned a less favorable jury (as proxied by whether their attorneys exhaust their peremptory strikes) fare at trial. Our novel identification strategy is unique in that it captures variation in juror predisposition coming from variables unobserved by the econometrician but observed by attorneys. We find that criminal defendants who lose the "jury lottery" are more likely to be convicted than their similarly-situated counterparts, with a significant increase (~19 percentage points) for Black defendants. Our results suggest that a considerable number of cases would result in different verdicts if retried with new (counterfactual) random draws of the jury pool, raising concerns about the variance of justice in the criminal legal system.
How do managers' non-responses during earnings calls affect analyst forecasts
Authors: Qingwen Liang, Matias Carrasco Kind
Date: 2025-05-23 00:00:00

This paper examines the impact of managers' non-responses (NORs) during quarterly earnings calls on analyst forecast behavior by developing a novel measure of NORs using two large language models: ChatGPT-4 and LLaMA 3.3. We adopt a three step prompting approach including identification, classification, and evaluation, to extract NORs from earnings call transcripts of S&P 500 firms. We find that a higher incidence of NORs is significantly associated with greater analyst forecast errors, dispersion, and uncertainty. These effects are more pronounced among firms with high institutional ownership, greater R&D expenditures, operations across multiple industries, and earnings calls held during the COVID-19 period. Further analysis shows that NORs are followed by greater post-earnings announcement drift, higher return volatility, increased trading volume, and wider bid-ask spreads, suggesting that NORs raise information processing costs and exacerbate uncertainty. Overall, our findings indicate that managers' non-responses during earnings calls impair the information environment for analysts and investors.
The Effects of Climate and Weather on Economic Output: Evidence from Global Subnational Data
Authors: Jinchi Dong, Richard S. J. Tol, Jinnan Wang
Date: 2025-05-23 00:00:00

Estimating the effects of climate on economic output is crucial for formulating climate policy, but current empirical findings remain ambiguous. Using annual panel model and panel long-difference model with global subnational data from nearly all countries, we find robust evidence that weather shocks have a transient effect on output. The impact on economic growth is large and significant in the short-run but statistically insignificant in the long-run, except in the coldest and hottest places.
Trade Networks and the Rise of a Global Currency
Authors: Tomoo Kikuchi, Lien Pham
Date: 2025-05-28 00:00:00

We develop a model of strategic competition between global currencies. Issuers choose their commitment levels for currency internationalization, while users -- interconnected in a trade network -- choose their usage of each currency for trade settlement. Our theoretical findings highlight not only the advantage of the status-quo issuer in maintaining dominance, but also the conditions under which an emerging issuer can attract users, potentially leading to a multi-currency payment system. The network centrality of users plays a key role in shaping both their currency choices and the strategic commitment levels of issuers. Our framework offers testable implications for the share of global currencies for trade settlement by linking the network structure, the strategy of issuers and the currency choice of users.
Trade among moral agents with information asymmetries
Authors: José Ignacio Rivero-Wildemauwe
Date: 2025-05-26 00:00:00

Two agents trade an item in a simultaneous offer setting, where the exchange takes place if and only if the buyer's bid price weakly exceeds the seller's ask price. Each agent is randomly assigned the buyer or seller role. Both agents are characterized by a certain degree of Kantian morality, whereby they pick their bidding strategy behind a Veil of Ignorance, taking into account how the outcome would be affected if their trading partner adopted their strategy. I consider two variants with asymmetric information, respectively allowing buyers to have private information about their valuation or sellers to be privately informed about the item's quality. I show that when all trades are socially desirable, even the slightest degree of morality guarantees that the outcome is fully efficient. In turn, when quality is uncertain and some exchanges are socially undesirable, full efficiency is only achieved with sufficiently high moral standards. Moral concerns also ensure equal ex-ante treatment of the two agents in equilibrium. Finally, I show that if agents are altruistic rather than moral, inefficiencies persist even with a substantial degree of altruism.
Geopolitical Tensions and Financial Networks: Strategic Shifts Toward Alternatives
Authors: Antonis Ballis
Date: 2025-05-27 00:00:00

Global financial systems are undergoing strategic shifts as geopolitical tensions reshape international trade and payments. The United States (US)-China trade war, sanctions regimes, and rising concerns over the weaponization of financial infrastructures like SWIFT have led countries to seek alternative networks, including China's CIPS and emerging cross-border CBDCs. This letter presents a dynamic theoretical framework where sanction risks, investment choices, and network effects drive payment system migration. Empirical evidence from Russia, Saudi Arabia, India, and Argentina supports the model. Policy implications point toward increasing financial fragmentation, with critical roles for international institutions to mitigate systemic risks. The future of finance may be less global and more regionally fragmented, influenced heavily by political considerations.
Repeated Auctions with Speculators: Arbitrage Incentives and Forks in DAOs
Authors: Nicolas Eschenbaum, Nicolas Greber
Date: 2025-05-27 00:00:00

We analyze the vulnerability of decentralized autonomous organizations (DAOs) to speculative exploitation via their redemption mechanisms. Studying a game-theoretic model of repeated auctions for governance shares with speculators, we characterize the conditions under which -- in equilibrium -- an exploitative exit is guaranteed to occur, occurs in expectation, or never occurs. We evaluate four redemption mechanisms and extend our model to include atomic exits, time delays, and DAO spending strategies. Our results highlight an inherent tension in DAO design: mechanisms intended to protect members from majority attacks can inadvertently create opportunities for costly speculative exploitation. We highlight governance mechanisms that can be used to prevent speculation.
Berk-Nash Rationalizability
Authors: Ignacio Esponda, Demian Pouzo
Date: 2025-05-27 00:00:00

Misspecified learning -- where agents rely on simplified or biased models -- offers a unifying framework for analyzing behavioral biases, cognitive constraints, and systematic misperceptions. We introduce Berk--Nash rationalizability, a new solution concept for such settings that parallels rationalizability in games. Our main result shows that, with probability one, every limit action -- any action played or approached infinitely often -- is Berk--Nash rationalizable. This holds regardless of whether behavior converges and offers a tractable way to bound long-run behavior without solving complex learning dynamics. We illustrate this advantage with a known example and identify general classes of environments where the rationalizable set can be easily characterized.
A Characterization of Reny's Weakly Sequentially Rational Equilibrium through $\varepsilon$-Perfect $γ$-Weakly Sequentially Rational Equilibrium
Authors: Yiyin Cao, Chuangyin Dang
Date: 2025-05-26 00:00:00
Tasks: Form

A weakening of sequential rationality of sequential equilibrium yields Reny's (1992) weakly sequentially rational equilibrium (WSRE) in extensive-form games. WSRE requires Kreps and Wilson's (1982) consistent assessment to satisfy global rationality of nonconvex payoff functions at every information set reachable by a player's own strategy. The consistent assessment demands a convergent sequence of totally mixed behavioral strategy profiles and associated Bayesian beliefs. Nonetheless, due to the nonconvexity, proving the existence of WSRE required invoking the existence of a normal-form perfect equilibrium, which is sufficient but not necessary. Furthermore, Reny's WSRE definition does not fully specify how to construct the convergent sequence. To overcome these challenges, this paper develops a characterization of WSRE through $\varepsilon$-perfect $\gamma$-WSRE with local sequential rationality, which is accomplished by incorporating an extra behavioral strategy profile. For any given $\gamma>0$, we generate a perfect $\gamma$-WSRE as a limit point of a sequence of $\varepsilon_k$-perfect $\gamma$-WSRE with $\varepsilon_k\to 0$. A WSRE is then acquired from a limit point of a sequence of perfect $\gamma_q$-WSRE with $\gamma_q\to 0$. This characterization enables analytical identification of all WSREs in small extensive-form games and a direct proof of the existence of WSRE. An application of the characterization yields a polynomial system that serves as a necessary and sufficient condition for verifying whether a totally mixed assessment is an $\varepsilon$-perfect $\gamma$-WSRE. Exploiting the system, we devise differentiable path-following methods to compute WSREs by establishing the existence of smooth paths, which are secured from the equilibrium systems of barrier and penalty extensive-form games. Comprehensive numerical results further confirm the efficiency of the methods.
A General Theory of Risk Sharing
Authors: Vasily Melnikov
Date: 2025-05-25 00:00:00

We introduce a new paradigm for risk sharing that generalizes earlier models based on discrete agents and extends them to allow for sharing risk within a continuum of agents. Agents are represented by points of a measure space and have potentially heterogeneous risk preferences modeled by risk measures. The existence of risk minimizing allocations is proved when constrained to satisfy economically convincing conditions. In the unconstrained case, we derive the dual representation of the value function using a Strassen-type theorem for the weak-star topology. These results are illustrated by explicit formulas when risk preferences are within the family of entropic and expected shortfall risk measures.
Cognitive Biases at Play? Insights from a Bayesian Game Framework
Authors: Samiha Tariq
Date: 2025-05-24 00:00:00
Tasks: Decision Making

This paper examines the impact of cognitive biases on financial decision-making through a static Bayesian game framework. While traditional economic theory assumes fully rational investors, real-world choices are often shaped by loss aversion, overconfidence, and herd behavior. Integrating psychological insights with economic game theory, the model studies strategic interactions among investors who allocate wealth between risky and risk-free assets. Solving for the Bayesian Nash Equilibrium reveals that each bias distorts optimal portfolios and alters aggregate market dynamics. The results echo Herbert Simon's notion of bounded rationality, showing how biases can generate market inefficiencies, price bubbles, and crashes. The findings highlight the importance of incorporating psychological factors into economic models to guide policies that foster market stability and more informed financial decision-making.
Accuracy Is (Generically) Bad For Compliance
Authors: John W. Patty, Elizabeth Maggie Penn
Date: 2025-05-23 00:00:00

We demonstrate that the set of cost distributions under which the optimal strategy for maximizing compliance (or more generally, effort) in a binary choice environment is identical to the optimal strategy for maximizing the accuracy of the reward (minimizing Type-I and Type-II errors) is finitely shy (Anderson and Zame (2001) in the space of all smooth parameterized real-valued distributions possessing full support on the real line. In words, this implies that maximizing compliance and maximizing accuracy "almost always" call for different incentive schemes.