pwc-archive/papers-with-abstracts huggingface dataset:
A Nonparametric Test of Slutsky Symmetry
Authors: Florian Gunsilius, Lonjezo Sithole
Date: 2025-05-08 00:00:00

Economic theory implies strong limitations on what types of consumption behavior are considered rational. Rationality implies that the Slutsky matrix, which captures the substitution effects of compensated price changes on demand for different goods, is symmetric and negative semi-definite. While negative semi-definiteness has been shown to be nonparametrically testable, a fully nonparametric test of symmetry has remained elusive due to the inherent multidimensionality of the problem. Recently, it has even been shown that the symmetry condition is not testable via the average Slutsky matrix, prompting conjectures about its non-testability. We settle this question by deriving nonparametric conditional quantile restrictions on observable data that permit construction of a fully nonparametric test for the symmetry condition. The theoretical contribution is a multivariate extension of identification results for partial effects in nonseparable models without monotonicity, which is of independent interest. The derived conditional restrictions induce challenges related to generated regressors and multiple hypothesis testing, which can be addressed using recent statistical methods. Our results provide researchers with the missing tool in many econometric models that rely on Slutsky matrices: from welfare analysis with individual heterogeneity to testing an empirical version of rationality in consumption behavior.
Measuring the Euro Area Output Gap
Authors: Matteo Barigozzi, Claudio Lissona, Matteo Luciani
Date: 2025-05-08 00:00:00

We measure the Euro Area (EA) output gap and potential output using a non-stationary dynamic factor model estimated on a large dataset of macroeconomic and financial variables. From 2012 to 2024, we estimate that the EA economy was tighter than policy institutions estimate, suggesting that the slow EA growth results from a potential output issue, not a business cycle issue. Moreover, we find that a decline in trend inflation, not slack in the economy, kept core inflation below 2% before the pandemic and that demand forces account for at least 30% of the post-pandemic increase in core inflation.
The "strength" of patent systems
Authors: Gaetan de Rassenfosse
Date: 2025-05-11 00:00:00

Patent systems vary widely in how rigorously they define and enforce inventors' rights. On one hand, formal statutes ("law on the books") set the scope of what can be patented and outline procedural safeguards. On the other hand, actual enforcement ("law in practice") determines whether those rights hold up in practice. To capture these dimensions, researchers have developed simple indices of legal provisions and more nuanced proxies for enforcement effectiveness, along with metrics of how applicant-friendly each office's procedures are. Comparative studies of "twin patents" -- identical inventions filed in multiple jurisdictions -- reveal systematic differences in grant rates and bar heights across major offices. By combining these approaches, we gain a multifaceted view of patent-system strength that balances statutory design, administrative practice, and actual enforcement. This perspective is crucial for understanding how different regimes support innovation and shape global knowledge flows.
Sustainability of cities under declining population and decreasing distance frictions: The case of Japan
Authors: Tomoya Mori, Daisuke Murakami
Date: 2025-05-13 00:00:00

This study develops a statistical model that integrates economic agglomeration theory and power-law distributions of city sizes to project future population distribution on 1-km grid cells. We focus on Japan -- a country at the forefront of rapid population decline. Drawing on official population projections and empirical patterns from past urban evolution in response to the development of high-speed rail and highway networks, we examine how ongoing demographic contraction and expected reductions in distance frictions may reshape urban geography. Our analysis suggests that urban economies will consolidate around fewer and larger cities, each of which will experience a flattening of population density as the decentralization of urban populations accelerates, while rural areas are expected to experience further depopulation as a result of these spatial and economic shifts. By identifying sustainable urban cores capable of anchoring regional economies, our model provides a framework for policymakers to manage population decline while maintaining resilience through optimized infrastructure and resource allocation focused on these key urban centers.
When Incentives and Nudges Meet: Promoting Budget Allocations for Undervalued Policies
Authors: Makoto Kuroki, Shusaku Sasaki
Date: 2025-05-13 00:00:00

Budget officers often assess public project proposals based on available financial support and expected outcomes. However, behavioral factors such as time discounting and psychological hesitation may lead to underinvestment in programs with delayed but significant benefits. This study investigates whether financial incentives and non-financial nudges can influence budgetary decisions in local governments. We conducted a nationwide mail-based survey experiment targeting budget officers in Japanese municipalities and received 490 valid responses. Using a 2*2 randomized design, we tested the independent and combined effects of a financial incentive (a 50% national subsidy) and a non-financial nudge (loss framing and peer information). All three treatments significantly increased assessed budget amounts compared to the control group. The largest effect appeared in the combination group (approximately 1.1 million JPY higher, p < .01). Both the financial incentive and the nudge independently increased assessments by approximately 650,000-670,000 JPY (p < .01). Notably, only the nudge raised the self-financed portion of the budget. These findings demonstrate how low-cost behavioral interventions can improve budget assessments for undervalued projects. As an application, we embedded the experiment in a case involving HPV vaccine promotion in Japan, but the approach can be broadly relevant to other public policy domains requiring forward-looking budget decisions.
A conditional match rate anomaly and ranking pressure in residency matching programs
Authors: Munetomo Ando, Minoru Kitahara
Date: 2025-05-13 00:00:00

In the medical residency matching markets of the U.S. and Japan, we observe that an applicant's probability of matching with their first-listed program is disproportionately higher than that of matching with their second-listed program, given that they were rejected by the first. In contrast, the conditional probabilities of matching with lower-ranked programs are markedly lower and remain relatively stable. Furthermore, several experts have noted that participating programs sometimes exert pressure on applicants to manipulate the order of their rank-order lists. In this study, we show that this pressure can account for the observed probability pattern, considering the verifiability of being ranked first on the list. Using empirical data, we identify the prevalence of ranking pressure and quantify its impact on rank-order list changes and welfare under a simplified acceptance and pressure process. Additionally, we explore the implementation of a random permutation of the submitted rank-order list as a measure to counteract list reordering due to pressure. Our analysis shows that the benefits of this intervention outweigh the associated efficiency losses.
Strategic ESG-Driven Human Resource Practices: Transforming Employee Management for Sustainable Organizational Growth
Authors: Darul Wiyono, Deshinta Arrova Dewi, Ema Ambiapuri, Nur Aini Parwitasari, Deni Supardi Hambali
Date: 2025-05-13 00:00:00
Tasks: Management

Purpose: This research explores the impact of Environmental, Social, and Governance (ESG) practices on employee performance and well-being in private higher education institutions in Bandung, West Java. It seeks to provide insights into how effective ESG integration can enhance organizational performance and employee satisfaction. Methodology: A quantitative approach employing Partial Least Squares Structural Equation Modeling (PLS-SEM) analyzed the relationships among constructs: environmental practices, social practices, governance practices, and the dependent variable, employee performance and well-being. Data were collected from 270 respondents through stratified random sampling across various administrative roles in 138 private higher education institutions. Findings: The results showed that environmental practices positively impact employee performance and well-being, with social practices also contributing. Governance practices mediate and amplify these effects. These findings emphasize the importance of integrating sustainable practices into organizational strategies to improve employee outcomes and overall institutional performance. Originality: This study explores the impact of ESG practices on employee performance in private higher education institutions, focusing on sustainability to enhance engagement and productivity. Unlike previous research, which focused primarily on corporate sectors or public universities, it emphasizes the unique challenges of private institutions, particularly in Bandung, offering new insights into governance practices as mediators.
Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model
Authors: Jutta G. Kurth, Adam A. Majewski, Jean-Philippe Bouchaud
Date: 2025-05-12 00:00:00
Tasks: Time Series

We amend and extend the Chiarella model of financial markets to deal with arbitrary long-term value drifts in a consistent way. This allows us to improve upon existing calibration schemes, opening the possibility of calibrating individual monthly time series instead of classes of time series. The technique is employed on spot prices of four asset classes from ca. 1800 onward (stock indices, bonds, commodities, currencies). The so-called fundamental value is a direct output of the calibration, which allows us to (a) quantify the amount of excess volatility in these markets, which we find to be large (e.g. a factor $\approx$ 4 for stock indices) and consistent with previous estimates; and (b) determine the distribution of mispricings (i.e. the difference between market price and value), which we find in many cases to be bimodal. Both findings are strongly at odds with the Efficient Market Hypothesis. We also study in detail the 'sloppiness' of the calibration, that is, the directions in parameter space that are weakly constrained by data. The main conclusions of our study are remarkably consistent across different asset classes, and reinforce the hypothesis that the medium-term fate of financial markets is determined by a tug-of-war between trend followers and fundamentalists.
2ACT: AI-Accentuated Career Transitions via Skill Bridges
Authors: Drake Mullens, Stella Shen
Date: 2025-05-12 00:00:00

This study introduces the AI-Accentuated Career Transitions framework, advancing beyond binary automation narratives to examine how distinct AI usage patterns reshape occupational mobility. Analyzing 545 occupations through multivariate modeling, we identify six qualitatively distinct human-AI usage patterns that differentially predict placement across job preparation zones. Our findings empirically validate the "missing middle" hypothesis: automation-focused usage strongly predicts lower job zone placement while augmentative usage predicts higher zones. Most significantly, we identify specific Knowledge, Skill, and Abilities combinations with AI usage patterns that function as "skill bridges" facilitating upward mobility. The interaction between task iteration AI usage and cognitive skills emerges as the strongest advancement predictor, creating pathways across traditionally disconnected occupational categories. Counterintuitively, despite directive AI's negative main effect, its interaction with technical knowledge positively predicts advancement in specialized domains. Comparative model testing confirms that AI usage patterns represent a distinct dimension of occupational classification that adds significant explanatory power beyond traditional skill measures. These findings reveal AI as a skill amplifier that widens capability gaps rather than an equalizing force. The 2ACT framework provides strategic guidance for workers, curriculum designers, policymakers, and organizations navigating increasingly AI-mediated career pathways.
Unequal Journeys to Food Markets: Continental-Scale Evidence from Open Data in Africa
Authors: Robert Benassai-Dalmau, Vasiliki Voukelatou, Rossano Schifanella, Stefania Fiandrino, Daniela Paolotti, Kyriaki Kalimeri
Date: 2025-05-12 00:00:00

Food market accessibility is a critical yet underexplored dimension of food systems, particularly in low- and middle-income countries. Here, we present a continent-wide assessment of spatial food market accessibility in Africa, integrating open geospatial data from OpenStreetMap and the World Food Programme. We compare three complementary metrics: travel time to the nearest market, market availability within a 30-minute threshold, and an entropy-based measure of spatial distribution, to quantify accessibility across diverse settings. Our analysis reveals pronounced disparities: rural and economically disadvantaged populations face substantially higher travel times, limited market reach, and less spatial redundancy. These accessibility patterns align with socioeconomic stratification, as measured by the Relative Wealth Index, and moderately correlate with food insecurity levels, assessed using the Integrated Food Security Phase Classification. Overall, results suggest that access to food markets plays a relevant role in shaping food security outcomes and reflects broader geographic and economic inequalities. This framework provides a scalable, data-driven approach for identifying underserved regions and supporting equitable infrastructure planning and policy design across diverse African contexts.
How Does Monetary Policy Influence the U.S. Treasury Bond Yields, and What are the Implications for Portfolio Managers?
Authors: Minnie Zhu, YuHan Liu, Simon Gong
Date: 2025-05-12 00:00:00

This paper investigates the impact of monetary policy surprises on U.S. Treasury bond yields and the implications for portfolio managers. Based on the supply and demand model, traditional economic theories suggest that Federal Reserve bond purchases should increase bond prices and decrease yields. However, New Keynesian models challenge this view, proposing that bond prices should not necessarily rise due to future expectations influencing investor behavior. By analyzing the effects of monetary policy surprises within narrow windows around Federal Open Market Committee (FOMC) announcements, this study aims to isolate the true impact of these surprises on bond yields. The research covers Treasury bonds of various maturities--3 months, 1 year, 10 years, and 30 years--and utilizes cross-sectional regression analysis. The findings reveal that financial crises significantly decrease short-term yields, while no obvious evidence of factors that might affect long-term yields. This paper provides insights into how monetary policy influences bond yields and offers practical implications for portfolio management, particularly during quantitative easing and financial crises.
The Impact of COVID-19 on FinTech Lending in Indonesia: Evidence From Interrupted Time Series Analysis
Authors: Abdul Khaliq
Date: 2025-05-10 00:00:00
Tasks: Time Series, Time Series Analysis

This study measures the impact of COVID-19 outbreaks on financial technology (FinTech) lending in Indonesia. Using monthly FinTech data published by Financial Services Authority (OJK) over the period 2018M02-2021M04, the article examines the impact of COVID-19 started on March 2020 on FinTech by adopting an interrupted time series (ITS) experiment. The estimation shows that the COVID-19 outbreaks negatively affect changes in FinTech lending level in Indonesia, but the changes in the trend are positive. Moreover, the COVID-19 has been found to have a negative and statistically significant effect on the 90-day success loan settlement rate level. However, COVID-19 has positive and statistically significant effects on the 90-day default rate of loan repayment level. These estimation results recommend that the financial services authority of Indonesia should intensively promote various innovative financial technology (FinTech) lending post-COVID-19 to increase digital financial inclusion by providing peer to peer lending (P2P) to unbanked populations.
Too Sick for Working, or Sick of Working? Impact of Acute Health Shocks on Early Labour Market Exits
Authors: Luis Vieira
Date: 2025-05-10 00:00:00
Tasks: Survival Analysis

This study investigates the impact of acute health shocks on early labour market exits among individuals aged 50 and over in Europe. Utilising data from Waves 1-8 of the Survey of Health, Ageing, and Retirement in Europe (SHARE), encompassing over 140,000 individuals, I employ survival analysis techniques, including Kaplan-Meier estimators and Cox proportional hazards models. The analysis explores how sudden, severe health events, alongside self-perceived health, chronic conditions, and socio-demographic factors, influence the probability of exiting the workforce before official retirement age. Results indicate that acute health shocks significantly increase the hazard of early labour market exit, with more pronounced effects observed for males. Poorer self-perceived health and lower educational attainment are also strong predictors of early exit. Gender differences are notable: while poorer health consistently raises exit risk for both genders, income acts as a protective factor for females, and living with a partner reduces exit risk for males but increases it for females. These findings highlight the critical role of health in labour market participation and suggest the need for targeted policies to support older workers, particularly those experiencing adverse health events.
Competition and Collusion in Two-Sided Markets with an Outside Option
Authors: Cristian Chica, Yinglong Guo, Gilad Lerman
Date: 2025-05-09 00:00:00

We introduce pricing formulas for competition and collusion models of two-sided markets with an outside option. For the competition model, we find conditions under which prices and consumer surplus may increase or decrease if the outside option utility increases. Therefore, neglecting the outside option can lead to either overestimation or underestimation of these equilibrium outputs. Comparing collusion to competition, we find that in cases of small cross-side externalities, collusion results in decreased normalized net deterministic utilities, reduced market participation and increased price, on both sides of the market. Additionally, we observe that as the number of platforms increases in the competition model, market participation rises. Profits, however, decrease when the net normalized deterministic utility is sufficiently low but increase when it is high. Furthermore, we identify specific conditions that quantify the change of price and consumer surplus when the competition increases.
Predicting Poverty
Authors: Paolo Verme
Date: 2025-05-09 00:00:00
Tasks: counterfactual

Poverty prediction models are used to address missing data issues in a variety of contexts such as poverty profiling, targeting with proxy-means tests, cross-survey imputations such as poverty mapping, top and bottom incomes studies, or vulnerability analyses. Based on the models used by this literature, this paper conducts a study by artificially corrupting data clear of missing incomes with different patterns and shares of missing incomes. It then compares the capacity of classic econometric and machine learning models to predict poverty under different scenarios with full information on observed and unobserved incomes, and the true counterfactual poverty rate. Random forest provides more consistent and accurate predictions under most but not all scenarios.
Identifying Optimal Market Choices to Increase the Profitability of Coffee Farmers in Sultan Kudarat through Modeling and Scenario Analysis
Authors: Novy Aila B. Rivas, Giovanna Fae R. Oguis, Alex John C. Labanon, El Veena Grace A. Rosero, Jon Henly O. Santillan, Larry N. Digal
Date: 2025-05-09 00:00:00
Tasks: Marketing

This study focuses on the coffee chain of Sultan Kudarat - the coffee capital of the Philippines, where most of the farmers are smallholders. Coffee farmers in this area allocate their harvested cherries as fresh cherries, dried cherries, and green coffee beans to five market outlets: Nestle Philippines, local traders, association, direct selling, and other markets not mentioned (e.g., coffee shops and hotels). Hence, a supply chain network design (SCND) model and simulation are developed to investigate the changes in the profits of coffee farmers as they market their products, whether to be sold as fresh cherries, dried cherries, or processed into green coffee beans before marketing to the market outlets mentioned above, based on the average annual costs affecting the production, primary processing, and market prices of coffee products. Assuming that the annual coffee yield per tree and the average prices of coffee products in different markets are constant, the simulations show that farmers can gain a positive annual profit if they sell all dried cherries. However, results show that if farmers decide to produce and sell all green coffee beans, the farmers gain a negative profit due to the additional annual average dehulling cost and the minimal difference in average selling prices between dried cherries and green coffee beans in different markets. Furthermore, members of the association producing dried cherries can gain by allocating the required 70 percent of their product to the association and 30 percent to the other markets. In contrast, selling 30 percent of green coffee beans to any market generates a negative profit. The developed model can also be modified and used for regular coffee farms and other commodities.
Who's at Risk? Effects of Inflation on Unemployment Risk
Authors: Hie Joo Ahn, Lam Nguyen
Date: 2025-05-09 00:00:00
Tasks: quantile regression

We empirically investigate the distributional effects of inflation on workers' unemployment tail risks using instrumental variable quantile regression. We find that supply-driven inflation disproportionately raises unemployment tail risks for cyclically vulnerable workers in both the short and medium term, while demand-driven inflation has differential effects -- limited to race and reason for unemployment -- only in the medium term. Demand-boosting policies, including monetary policy, can inadvertently widen those disparities through the inflation channel, underscoring the importance of inflation stabilization in promoting equitable growth in the labor market. Our findings could be explained structurally by heterogeneity in experienced inflation and wage inflation expectations.