pwc-archive/papers-with-abstracts huggingface dataset:
Comparing Electoral Polarization Levels
Authors: Boris Ginzburg
Date: 2024-11-06 00:00:00
Tasks: Position, Survey

This paper introduces a definition of ideological polarization of an electorate around a particular central point. The definition is flexible about the location or boundaries of the center. Using US survey data, the paper shows how this approach can be used to establish whether polarization is occurring, and to find the position around which it is happening. I then show how ideological polarization as defined here is related to other phenomena, such as affective polarization and increased salience of divisive issues.
Hiring as Exploration
Authors: Danielle Li, Lindsey Raymond, Peter Bergman
Date: 2024-11-06 00:00:00
Tasks: Decision Making, Diversity

This paper views hiring as a contextual bandit problem: to find the best workers over time, firms must balance exploitation (selecting from groups with proven track records) with exploration (selecting from under-represented groups to learn about quality). Yet modern hiring algorithms, based on supervised learning approaches, are designed solely for exploitation. Instead, we build a resume screening algorithm that values exploration by evaluating candidates according to their statistical upside potential. Using data from professional services recruiting within a Fortune 500 firm, we show that this approach improves the quality (as measured by eventual hiring rates) of candidates selected for an interview, while also increasing demographic diversity, relative to the firm's existing practices. The same is not true for traditional supervised learning based algorithms, which improve hiring rates but select far fewer Black and Hispanic applicants. Together, our results highlight the importance of incorporating exploration in developing decision-making algorithms that are potentially both more efficient and equitable.
Adaptive Shock Compensation in the Multi-layer Network of Global Food Production and Trade
Authors: Sophia Baum, Moritz Laber, Martin Bruckner, Liuhuaying Yang, Stefan Thurner, Peter Klimek
Date: 2024-11-05 00:00:00

Global food production and trade networks are highly dynamic, especially in response to shortages when countries adjust their supply strategies. In this study, we examine adjustments across 123 agri-food products from 192 countries resulting in 23616 individual scenarios of food shortage, and calibrate a multi-layer network model to understand the propagation of the shocks. We analyze shock mitigation actions, such as increasing imports, boosting production, or substituting food items. Our findings indicate that these lead to spillover effects potentially exacerbating food inequality: an Indian rice shock resulted in a 5.8 % increase in rice losses in countries with a low Human Development Index (HDI) and a 14.2 % decrease in those with a high HDI. Considering multiple interacting shocks leads to super-additive losses of up to 12 % of the total available food volume across the global food production network. This framework allows us to identify combinations of shocks that pose substantial systemic risks and reduce the resilience of the global food supply.
Gender Differences in Comparative Advantage Matches: Evidence from Linked Employer-Employee Data
Authors: Hugo Sant'Anna
Date: 2024-11-05 00:00:00

In this paper, I introduce a novel decomposition method based on Gaussian mixtures and k-Means clustering, applied to a large Brazilian administrative dataset, to analyze the gender wage gap through the lens of worker-firm interactions shaped by comparative advantage. These interactions generate wage levels in logs that exceed the simple sum of worker and firm components, making them challenging for traditional linear models to capture effectively. I find that these ``complementarity effects'' account for approximately 17% of the gender wage gap. Larger firms, high human capital, STEM degrees, and managerial roles are closely related to it. For instance, among managerial occupations, the match effect goes as high as one-third of the total gap. I also find women are less likely to be employed by firms offering higher returns to both human capital and firm-specific premiums, resulting in a significantly larger firm contribution to the gender wage gap than previously estimated. Combined, these factors explain nearly half of the overall gender wage gap, suggesting the importance of understanding firm-worker matches in addressing gender-based pay disparities.
Generative AI and Security Operations Center Productivity: Evidence from Live Operations
Authors: James Bono, Justin Grana, Alec Xu
Date: 2024-11-05 00:00:00
Tasks: Causal Identification

We measure the association between generative AI (GAI) tool adoption and security operations center productivity. We find that GAI adoption is associated with a 30.13% reduction in security incident mean time to resolution. This result is robust to several modeling decisions. While unobserved confounders inhibit causal identification, this result is among the first to use observational data from live operations to investigate the relationship between GAI adoption and security worker productivity.
Global Value Chain Linkages and Carbon Emissions embodied in trade, An Evidence from Emerging Economies: Uncovering Connections
Authors: Sakshi Bhayana, Biswajit Nag
Date: 2024-11-05 00:00:00

This study explores whether the Global Value Chain(GVC) participation of 16 emerging market economies (EMEs) from 1995 to 2018 in the manufacturing sector leads to a rise in carbon emissions embodied in trade. The study covers the ecological dimension of the Global Value Chain and validates the Pollution Haven Hypothesis in developing nations.To address the problem of cross-sectional dependence, autocorrelation, and heteroscedasticity panels, we estimate the above models using the feasible generalized least squares (FGLS) method. Our findings exhibit a continuous growth in carbon emissions of all the EMEs, there exists a positive association between GVC participation and domestic CO2 emissions embodied in gross exports. Also, EMEs' foreign carbon emissions embodied in gross exports directly correlate with backward GVC Participation, suggesting that the cleaner environment in developed countries comes at the expense of a dirtier environment in developing countries.
It Takes Three to Ceilidh: Pension System and Multidimensional Poverty Mitigation in China
Authors: Yansong David Wang, Tao Louie Xu, Cheng Yuan
Date: 2024-11-05 00:00:00

This research, employing the Alkire-Foster approach to uncover multidimensional poverty between 2012 and 2020 in China, models and examines the sustainable effects and mechanisms of the three-pillar pension system in household poverty mitigation with the China Family Panel Studies data. The results evince that more participation in the pension system mitigates the probability of being trapped in multidimensional poverty. The findings reveal the significance of synchronising state social insurance, enterprise annuity, and individual commercial insurance. The mitigation effect of market-oriented pillars is achieved through more investment in and consumption for livelihood assets. Based upon the sustainable livelihoods framework, livelihood assets ameliorate household capabilities in human, natural, financial, and psychological capital against exogenous shocks and uncertainties. Our research contributes to the theory and praxis of the facilitating state in new structural economics illustrated by the multi-pillar pension system in sustainable micro-household poverty mitigation.
Age Normalized Testosterone Peaks at Series B for Male Startup Founders
Authors: Jordan Moradian, Michael Dubrovsky, Megha Sama, Pavel Korecky, Sidarth Kulkarni, Yaniv Goder, Diedrik Vermeulen
Date: 2024-11-05 00:00:00

In a study of 107 male Y Combinator founders, a surprising correlation between age-normalized testosterone and company stage was uncovered. Testosterone, a hormone associated with confidence, dominance, and drive, increased by 55.7% from pre-seed to seed funding, peaking at the Series B stage, where levels were 99.6% higher than pre-seed. After series B funding, testosterone was observed to drop by 42.2%, coinciding with a spike in cortisol levels. This age-normalized biomarker analysis supports the dual-hormone hypothesis, illustrating that early startup success fosters feelings of dominance and confidence, while later-stage pressures and stresses erode these feelings. An alternative interpretation of the data, which suggests the opportunity for a longitudinal study, is that male founders with higher testosterone are more likely to raise larger rounds of funding.
Assessing the regulatory framework of financial institutions in Canada in the context of international climate risk management practices and Canadian net zero emission targets
Authors: Victor Cardenas
Date: 2024-11-04 00:00:00

The document addresses the essential role of financial regulatory frameworks in mitigating climate-related risks within the financial sector. The assessment evaluates Canada's efforts to establish a regulatory framework for financial climate risk disclosure, compares it to international standards, and identifies areas for improvement. The regulatory framework, fiscal impact, and incentives to relinquish investments in fossil fuel projects and transition to renewable energies swiftly and seamlessly are the primary challenges that Canada faces in achieving energy net zero targets.
Seesaw Experimentation: A/B Tests with Spillovers
Authors: Jin Li, Ye Luo, Xiaowei Zhang
Date: 2024-11-04 00:00:00
Tasks: Experimental Design

This paper examines how spillover effects in A/B testing can impede organizational progress and develops strategies for mitigating these challenges. We identify a phenomenon termed ``seesaw experimentation'', where a firm's overall performance paradoxically deteriorates despite achieving continuous improvements in measured A/B testing metrics. Seesaw experimentation arises when successful innovations in primary metrics generate negative externalities in secondary, unmeasured dimensions. To address this problem, we propose implementing a positive hurdle rate for A/B test approval. We derive the optimal hurdle rate, offering a simple solution that preserves decentralized experimentation while mitigating negative spillovers.
Multidimensional Economic Complexity and Fiscal Crises
Authors: Goran Hristovski, Gjorgji Gockov, Viktor Stojkoski
Date: 2024-11-04 00:00:00

Recent studies highlight economic complexity's role in mitigating fiscal crises, often measured via an economy's trade structure. Trade, however, is just one facet of an economy's structure and omits critical innovative activities like research. Here, we investigate how a multidimensional approach to economic complexity-including both trade and research structures-relates to fiscal instability. By using data on over 230 national fiscal crises from 1995 to 2021 and hazard duration analysis, we assess how measures of trade and research complexity combine to explain crisis likelihood. We find that the interaction of complexity dimensions significantly reduces crisis probability, whereas individual indexes alone are not robust predictors. This suggests that economies focusing on a single dimension may be more vulnerable, thus highlighting the importance of balanced development across multiple areas. These findings offer valuable insights for policymakers aiming to enhance economic resilience and mitigate fiscal risks.
Information Aggregation in Markets with Analysts, Experts, and Chatbots
Authors: Wolfgang Kuhle
Date: 2024-11-04 00:00:00
Tasks: Position

The present paper shows that it can be advantageous for traders to publish their information on the true value of an asset even if they (i) cannot build a position in the asset prior to the publication of their information and (ii) cannot charge for the provision of information. The model also shows that the informational content of prices is U-shaped in the number of traders who publish their information. Put differently, information aggregation works best if either no trader, or if every trader publishes his information. Small groups of distinguished experts are, on the contrary, an obstacle to information aggregation. The model's key assumption is that the perception/interpretation of a given piece of published information differs slightly across traders.
Can education correct appearance discrimination in the labor market?
Authors: Hambur Wang
Date: 2024-11-03 00:00:00

This study explores the impact of appearance discrimination in the labor market and whether education can mitigate this issue. A statistical analysis of approximately 1.058 million job advertisements in China from 2008 to 2010 found that about 7.7% and 2.6% of companies had explicit requirements regarding candidates' appearance and height, particularly in positions with lower educational requirements. Literature review indicates that attractive job seekers typically enjoy higher employment opportunities and wages, while unattractive individuals face significant income penalties. Regression analysis of 1,260 participants reveals a significant positive correlation between attractiveness scores and wages, especially in low-education groups. Conversely, in high-education groups, the influence of appearance on income is not significant. The study suggests that enhancing education levels can effectively alleviate income declines associated with appearance, providing policy recommendations to reduce appearance discrimination in the labor market.
Donald Trumps in the Virtual Polls: Simulating and Predicting Public Opinions in Surveys Using Large Language Models
Authors: Shapeng Jiang, Lijia Wei, Chen Zhang
Date: 2024-11-03 00:00:00
Tasks: Survey

In recent years, large language models (LLMs) have attracted attention due to their ability to generate human-like text. As surveys and opinion polls remain key tools for gauging public attitudes, there is increasing interest in assessing whether LLMs can accurately replicate human responses. This study examines the potential of LLMs, specifically ChatGPT-4o, to replicate human responses in large-scale surveys and to predict election outcomes based on demographic data. Employing data from the World Values Survey (WVS) and the American National Election Studies (ANES), we assess the LLM's performance in two key tasks: simulating human responses and forecasting U.S. election results. In simulations, the LLM was tasked with generating synthetic responses for various socio-cultural and trust-related questions, demonstrating notable alignment with human response patterns across U.S.-China samples, though with some limitations on value-sensitive topics. In prediction tasks, the LLM was used to simulate voting behavior in past U.S. elections and predict the 2024 election outcome. Our findings show that the LLM replicates cultural differences effectively, exhibits in-sample predictive validity, and provides plausible out-of-sample forecasts, suggesting potential as a cost-effective supplement for survey-based research.
A mathematical model for cognitive structures and processes underlying innovations
Authors: Jürgen Jost, Massimo Warglien
Date: 2024-11-02 00:00:00

Business innovations are often arising from new combinations of pre-existing systems into new ones, coherently assembling features from their sources. We propose an abstract mathematical concept from category theory, the presheaf, to efficiently represent such coherent feature combinations. Moreover, operations on presheaves will allow us to formally describe and analyze business innovations that arise from novel mergings of systems from different domains. Equipped with such tools we provide an example by analyzing a successful case of such type of recombinant innovation, the digital hub concept proposed by Steve Jobs. The example shows how our framework can be used to bring formal rigor while preserving a fundamentally qualitative reasoning style.
A Numerical Assessment for Predicting Human Development Index (HDI) Trends in the GCC Countries
Authors: Mahdi Goldani
Date: 2024-11-02 00:00:00
Tasks: feature selection

This study focuses on predicting the Human Development Index (HDI) trends for GCC countries Saudi Arabia, Qatar, Kuwait, Bahrain, United Arab Emirates, and Omanusing machine learning techniques, specifically the XGBoost algorithm. HDI is a composite measure of life expectancy, education, and income, reflecting overall human development. Data was gathered from official government sources and international databases, including the World Bank and UNDP, covering the period from 1996 to 2022. Using the Edit Distance on Real sequence (EDR) method for feature selection, the model analyzed key indicators to predict HDI values over the next five years (2023-2027). The model demonstrated strong predictive accuracy for in-sample data, but minor overfitting issues were observed with out-of-sample predictions, particularly in the case of the UAE. The forecast results suggest that Kuwait, Bahrain, and the UAE will see stable or slightly increasing HDI values, while Saudi Arabia, Qatar, and Oman are likely to experience minimal fluctuations or slight decreases. This study highlights the importance of economic, health, and educational indicators in determining HDI trends and emphasizes the need for region-specific predictive models to improve accuracy. Policymakers should focus on targeted interventions in healthcare, education, and economic diversification to enhance human development outcomes.
Can Loyalty to Creators Dilute Loyalty to Promoted Products? Examining the Heterogeneous Effects of Live-Streamed Content on Video Game Usage
Authors: Wooyong Jo, Mike Lewis, Yanwen Wang
Date: 2024-11-02 00:00:00

Social media platforms have led to online consumption communities, or fandoms, that involve complex networks of ancillary creators and consumers focused on some core product or intellectual property. For example, video game communities include networks of players and content creators centered around a specific video game. These networks are complex in that video game publishers often sponsor creators, but creators and publishers may have divergent incentives. Specifically, creators can potentially benefit from content that builds their own following at the expense of the core game. Our research investigates the relationship between consuming live-streamed content and engagement with a specific video game. We examine the causal effect of viewing live-streamed content on subsequent gameplay for a specific game, using an unexpected service interruption of the livestreaming platform and time zone differences among users. We find live-streamed content significantly increases gameplay as a 10% increase in live-streamed viewing minutes results in a 3.08% increase in gameplay minutes. We also explore how this effect varies by user loyalty to different types of streamer channels (firm-owned, mega, and micro). The positive effects of live-streamed content are greatest for micro-streamers and smallest for mega-streamers. These findings are salient for firms allocating sponsorship resources.
Randomized Controlled Trials for Security Copilot for IT Administrators
Authors: James Bono, Alec Xu
Date: 2024-11-01 00:00:00
Tasks: Decision Making

As generative AI (GAI) tools become increasingly integrated into workplace environments, it is essential to measure their impact on productivity across specific domains. This study evaluates the effects of Microsoft's Security Copilot ("Copilot") on information technology administrators ("IT admins") through randomized controlled trials. Participants were divided into treatment and control groups, with the former granted access to Copilot within Microsoft's Entra and Intune admin centers. Across three IT admin scenarios - sign-in troubleshooting, device policy management, and device troubleshooting - Copilot users demonstrated substantial improvements in both accuracy and speed. Across all scenarios and tasks, Copilot subjects experienced a 34.53% improvement in overall accuracy and a 29.79% reduction in task completion time. We also find that the productivity benefits vary by task type, with more complex tasks showing greater improvement. In free response tasks, Copilot users identified 146.07% more relevant facts and reduced task completion time by 61.14%. Subject satisfaction with Copilot was high, with participants reporting reduced effort and a strong preference for using the tool in future tasks. These findings suggest that GAI tools like Copilot can significantly enhance the productivity and efficiency of IT admins, especially in scenarios requiring information synthesis and complex decision-making.
Design and Analysis of Intellectual Property Protection Strategies Based on Differential Equations
Authors: Hambur Wang
Date: 2024-11-01 00:00:00

This paper constructs a novel intellectual property (IP) protection strategy using differential equation theory, aiming to analyze and optimize the effectiveness of IP protection. By developing a mathematical model, it explores the dynamic impact of IP protection intensity on both innovative enterprises and infringement activities. The study finds that a well-designed IP protection strategy can effectively reduce infringement while promoting technological innovation. The paper also discusses the effects of strategies under varying parameter conditions and verifies the model's rationality and effectiveness through numerical simulation. The findings provide theoretical support and references for formulating IP protection policies.
The Impact of Farmers' Borrowing Behavior on Agricultural Production Technical Efficiency
Authors: Hambur Wang
Date: 2024-11-01 00:00:00

The effectiveness of farmer loan policies is crucial for the high-quality development of agriculture and the orderly advancement of the rural revitalization strategy. Exploring the impact of farmers' borrowing behavior on agricultural production technical efficiency holds significant practical value. This paper utilizes data from the 2020 China Family Panel Studies (CFPS) and applies Stochastic Frontier Analysis (SFA) along with the Tobit model for empirical analysis. The study finds that farmers' borrowing behavior positively influences agricultural production technical efficiency, with this effect being especially pronounced among low-income farmers. Additionally, the paper further examines household characteristics, such as household head age, gender, educational level, and the proportion of women in the family, in relation to agricultural production technical efficiency. The findings provide policy recommendations for optimizing rural financial service systems and enhancing agricultural production technical efficiency.
From Design to Disclosure
Authors: S. Nageeb Ali, Andreas Kleiner, Kun Zhang
Date: 2024-11-06 00:00:00

This paper studies games of voluntary disclosure in which a sender discloses evidence to a receiver who then offers an allocation and transfers. We characterize the set of equilibrium payoffs in this setting. Our main result establishes that any payoff profile that can be achieved through information design can also be supported by an equilibrium of the disclosure game. Hence, our analysis suggests an equivalence between disclosure and design in these settings. We apply our results to monopoly pricing, bargaining over policies, and insurance markets.
Troll Farms
Authors: Philipp Denter, Boris Ginzburg
Date: 2024-11-05 00:00:00

Political agents often aim to influence elections through troll farms -- organisations that disseminate messages emulating genuine information. We study the behaviour of a troll farm that faces a heterogeneous electorate of partially informed voters, and aims to achieve a desired political outcome by targeting each type of voter with a specific distribution of messages. We show that such tactics are more effective when voters are otherwise well-informed, for example, when the media is of high quality. At the same time, increased polarisation, as well as deviations from Bayesian rationality, can reduce the negative effect of troll farms and restore efficiency of electoral outcomes.