pwc-archive/papers-with-abstracts huggingface dataset:
On the use of artificial intelligence in financial regulations and the impact on financial stability
Authors: Jon Danielsson, Andreas Uthemann
Date: 2023-10-17 00:00:00
Tasks: Decision Making, Misinformation

Artificial intelligence (AI) can undermine financial stability because of malicious use, misinformation, misalignment, and the AI analytics market structure. The low frequency and uniqueness of financial crises, coupled with mutable and unclear objectives, frustrate machine learning. Even if the authorities prefer a conservative approach to AI adoption, it will likely become widely used by stealth, taking over increasingly high-level functions driven by significant cost efficiencies and superior performance. We propose six criteria for judging the suitability of AI.
Life-Cycle Effects of Comprehensive Sex Education
Authors: Volha Lazuka, Annika Elwert
Date: 2023-10-17 00:00:00

Sex education can impact pupils sexual activity and convey the social norms regarding family formation and responsibility, which can have significant consequences to their future. To investigate the life-cycle effects of social norm transmission, this study draws on the introduction of comprehensive sex education in the curriculum of Swedish primary schools during the 1940s to the 1950s. Inspired by social-democratic values, sex education during this period taught students about abstinence, rational family planning choices, and the importance of taking social responsibility for their personal decisions. The study applies a state-of-the-art estimator of the difference-in-differences method to various outcomes of men and women throughout the life cycle. The results show that the reform affected most intended outcomes for men and women, ultimately decreasing gender inequality in earnings. The effects of the reform also extended to the succeeding generation of girls. Both generations created a critical mass that altered social norms in favor of collective engagement and democracy. The findings suggest that social norms, internalized through school-based sex education, persistently affect peoples outcomes in significant ways.
Digital interventions and habit formation in educational technology
Authors: Keshav Agrawal, Susan Athey, Ayush Kanodia, Emil Palikot
Date: 2023-10-16 00:00:00

As online educational technology products have become increasingly prevalent, rich evidence indicates that learners often find it challenging to establish regular learning habits and complete their programs. Concurrently, online products geared towards entertainment and social interactions are sometimes so effective in increasing user engagement and creating frequent usage habits that they inadvertently lead to digital addiction, especially among youth. In this project, we carry out a contest-based intervention, common in the entertainment context, on an educational app for Indian children learning English. Approximately ten thousand randomly selected learners entered a 100-day reading contest. They would win a set of physical books if they ranked sufficiently high on a leaderboard based on the amount of educational content consumed. Twelve weeks after the end of the contest, when the treatment group had no additional incentives to use the app, they continued their engagement with it at a rate 75\% higher than the control group, indicating a successful formation of a reading habit. In addition, we observed a 6\% increase in retention within the treatment group. These results underscore the potential of digital interventions in fostering positive engagement habits with educational technology products, ultimately enhancing users' long-term learning outcomes.
The Sponge Cake Dilemma over the Nile: Achieving Fairness in Resource Allocation with Cake Cutting Algorithms
Authors: Dwayne Woods
Date: 2023-10-16 00:00:00
Tasks: Fairness

This article explores the intricate dynamics of the Nile Basin dispute, a complex conflict involving Egypt, Ethiopia, and Sudan. Our central argument is that we can gain unique insights into this dispute by employing the principles of game theory and the Steinhaus cake-cutting problem - a mathematical model of fair division. These theoretical frameworks offer a novel perspective to understand the motivations and potential actions of the involved nations. More importantly, these concepts can illuminate potential pathways toward a resolution that ensures equitable resource allocation and maintains regional stability. We will analyze the conflict and explore potential solutions to this enduring dispute through this lens.
A SEM-NCA approach towards the impact of participative budgeting on budgetary slack and managerial performance: The mediating role of leadership style and leader-member exchange
Authors: Khalid Hasan Al Jasimee, Francisco Javier Blanco-Encomienda
Date: 2023-10-16 00:00:00
Tasks: Management

This study re-examines the impact of participative budgeting on managerial performance and budgetary slack, addressing gaps in current research. A revised conceptual model is developed, considering the conditioning roles of leadership style and leader-member exchange. The sample includes 408 employees with managerial experience in manufacturing companies. Hypotheses are tested using a combination of PLS-SEM and Necessary Condition Analysis (NCA). The results demonstrate that participative budgeting negatively affects budgetary slack and directly influences managerial performance, leadership style, and leader-member exchange. Moreover, leadership style and leader-member exchange moderate these relationships. The integration of NCA in management accounting research provides valuable insights for decision-makers, allowing for more effective measures. This study contributes by encouraging a complementary PLS-SEM and NCA approach to examine conditional effects. It also enhances understanding of budgetary control by highlighting the importance of leadership in influencing participative budgeting outcomes.
Unified Merger List in the Container Shipping Industry from 1966 to 2022: A Structural Estimation of M&A Matching
Authors: Suguru Otani, Takuma Matsuda
Date: 2023-10-15 00:00:00
Tasks: counterfactual

We construct a novel unified merger list in the global container shipping industry between 1966 (the beginning of the industry) and 2022. Combining the list with proprietary data, we construct a structural matching model to describe the historical transition of the importance of a firm's age, size, and geographical proximity on merger decisions. We find that, as a positive factor, a firm's size is more important than a firm's age by 9.858 times as a merger incentive between 1991 and 2005. However, between 2006 and 2022, as a negative factor, a firm's size is more important than a firm's age by 2.013 times, that is, a firm's size works as a disincentive. We also find that the distance between buyer and seller firms works as a disincentive for the whole period, but the importance has dwindled to economic insignificance in recent years. In counterfactual simulations, we observe that the prohibition of mergers between firms in the same country would affect the merger configuration of not only the firms involved in prohibited mergers but also those involved in permitted mergers. Finally, we present interview-based evidence of the consistency between our merger lists, estimations, and counterfactual simulations with the industry experts' historical experiences.
Economics unchained: Investigating the role of cryptocurrency, blockchain and intricacies of Bitcoin price fluctuations
Authors: Ishmeet Matharoo
Date: 2023-10-15 00:00:00
Tasks: Decision Making

This research paper presents a thorough economic analysis of Bitcoin and its impact. We delve into fundamental principles, and technological evolution into a prominent decentralized digital currency. Analysing Bitcoin's economic dynamics, we explore aspects such as transaction volume, market capitalization, mining activities, and macro trends. Moreover, we investigate Bitcoin's role in economy ecosystem, considering its implications on traditional financial systems, monetary policies, and financial inclusivity. We utilize statistical and analytical tools to assess equilibrium , market behaviour, and economic . Insights from this analysis provide a comprehensive understanding of Bitcoin's economic significance and its transformative potential in shaping the future of global finance. This research contributes to informed decision-making for individuals, institutions, and policymakers navigating the evolving landscape of decentralized finance.
How Does Artificial Intelligence Improve Human Decision-Making? Evidence from the AI-Powered Go Program
Authors: Sukwoong Choi, Hyo Kang, Namil Kim, Junsik Kim
Date: 2023-10-12 00:00:00
Tasks: Decision Making

We study how humans learn from AI, leveraging an introduction of an AI-powered Go program (APG) that unexpectedly outperformed the best professional player. We compare the move quality of professional players to APG's superior solutions around its public release. Our analysis of 749,190 moves demonstrates significant improvements in players' move quality, especially in the early stages of the game where uncertainty is highest. This improvement was accompanied by a higher alignment with AI's suggestions and a decreased number and magnitude of errors. Young players show greater improvement, suggesting potential inequality in learning from AI. Further, while players of all skill levels benefit, less skilled players gain higher marginal benefits. These findings have implications for managers seeking to adopt and utilize AI in their organizations.
The Connection Between Political Stability and Inflation: Insights from Four South Asian Nations
Authors: Ummya Salma, Md. Fazlul Huq Khan
Date: 2023-10-12 00:00:00

This study explores the relationship between political stability and inflation in four South Asian countries, employing panel data spanning from 2001 to 2021. To analyze this relationship, the study utilizes the dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) methods, which account for cross-sectional dependence and slope homogeneity in panel data analysis. The findings consistently reveal that increased political stability is associated with lower inflation, while reduced political stability is linked to higher inflation.
There are different shades of green: heterogeneous environmental innovations and their effects on firm performance
Authors: Gianluca Biggi, Andrea Mina, Federico Tamagni
Date: 2023-10-12 00:00:00

Using a firm-level dataset from the Spanish Technological Innovation Panel (2003-2016), this study explores the characteristics of environmentally innovative firms and quantifies the effects of pursuing different types of environmental innovation strategies (resource-saving, pollution-reducing, and regulation-driven innovations) on sales, employment, and productivity dynamics.
Are sanctions for losers? A network study of trade sanctions
Authors: Fabio Ashtar Telarico
Date: 2023-10-12 00:00:00

Studies built on dependency and world-system theory using network approaches have shown that international trade is structured into clusters of 'core' and 'peripheral' countries performing distinct functions. However, few have used these methods to investigate how sanctions affect the position of the countries involved in the capitalist world-economy. Yet, this topic has acquired pressing relevance due to the emergence of economic warfare as a key geopolitical weapon since the 1950s. And even more so in light of the preeminent role that sanctions have played in the US and their allies' response to the Russian-Ukrainian war. Applying several clustering techniques designed for complex and temporal networks, this paper shows that a shift in the pattern of commerce away from sanctioning countries and towards neutral or friendly ones. Additionally, there are suggestions that these shifts may lead to the creation of an alternative 'core' that interacts with the world-economy's periphery bypassing traditional 'core' countries such as EU member States and the US.
Empirical Review of Youth-Employment Policies in Nigeria
Authors: Oluwasola E. Omoju, Emily E. Ikhide, Iyabo A. Olanrele, Lucy E. Abeng, Marjan Petreski, Francis O. Adebayo, Itohan Odigie, Amina M. Muhammed
Date: 2023-10-11 00:00:00

Youth unemployment is a major socioeconomic problem in Nigeria, and several youth-employment programs have been initiated and implemented to address the challenge. While detailed analyses of the impacts of some of these programs have been conducted, empirical analysis of implementation challenges and of the influence of limited political inclusivity on distribution of program benefits is rare. Using mixed research methods and primary data collected through focus-group discussion and key-informant interviews, this paper turns to that analysis. We found that, although there are several youth-employment programs in Nigeria, they have not yielded a marked reduction in youth-unemployment rates. The programs are challenged by factors such as lack of framework for proper governance and coordination, inadequate funding, lack of institutional implementation capacity, inadequate oversight of implementation, limited political inclusivity, lack of prioritization of vulnerable and marginalized groups, and focus on stand-alone programs that are not tied to long-term development plans. These issues need to be addressed to ensure that youth-employment programs yield better outcomes and that youth unemployment is significantly reduced.
Incentives for Private Industrial Investment in historical perspective: the case of industrial promotion and investment promotion in Uruguay (1974-2010)
Authors: Diego Vallarino
Date: 2023-10-10 00:00:00

Using as a central instrument a new database, resulting from a compilation of historical administrative records, which covers the period 1974-2010, we can have new evidence on how industrial companies used tax benefits, and claim that these are decisive for the investment decision of the Uruguayan industrial companies during that period. The aforementioned findings served as a raw material to also affirm that the incentives to increase investment are factors that positively influence the level of economic activity and exports, and negatively on the unemployment rate.
Revenue sharing at music streaming platforms
Authors: Gustavo Bergantiños, Juan D. Moreno-Ternero
Date: 2023-10-18 00:00:00

We study the problem of sharing the revenues raised from subscriptions to music streaming platforms among content providers. We provide direct, axiomatic and game-theoretical foundations for two focal (and somewhat polar) methods widely used in practice: pro-rata and user-centric. The former rewards artists proportionally to their number of total streams. With the latter, each user's subscription fee is proportionally divided among the artists streamed by that user. We also provide foundations for a family of methods compromising among the previous two, which addresses the rising concern in the music industry to explore new streaming models that better align the interests of artists, fans and streaming services.
Tractability and Phase Transitions in Endogenous Network Formation
Authors: Jose M. Betancourt
Date: 2023-10-16 00:00:00

The dynamics of network formation are generally very complex, making the study of distributions over the space of networks often intractable. Under a condition called conservativeness, I show that the stationary distribution of a network formation process can be found in closed form, and is given by a Gibbs measure. For conservative processes, the stationary distribution of a certain class of models can be characterized for an arbitrarily large number of players. In this limit, the statistical properties of the model can exhibit phase transitions: discontinuous changes as a response to continuous changes in model parameters.
Coherent Distorted Beliefs
Authors: Christopher P. Chambers, Yusufcan Masatlioglu, Collin Raymond
Date: 2023-10-15 00:00:00

Many models of economics assume that individuals distort objective probabilities. We propose a simple consistency condition on distortion functions, which we term distortion coherence, that ensures that the function commutes with conditioning on an event. We show that distortion coherence restricts belief distortions to have a particular function form: power-weighted distortions, where distorted beliefs are proportional to the original beliefs raised to a power and weighted by a state-specific value. We generalize our findings to allow for distortions of the probabilities assigned to both states and signals, which nests the functional forms widely used in studying probabilistic biases (e.g., Grether, 1980 and Benjamin, 2019). We show how coherent distorted beliefs are tightly related to several extant models of motivated beliefs: they are the outcome of maximizing anticipated expected utility subject to a generalized Kullback-Liebler cost of distortion. Moreover, in the domain of lottery choice, we link coherent distortions to explanations of non-expected utility like the Allais paradox: individuals who maximize subjective expected utility maximizers conditional on coherent distorted beliefs are equivalent to the weighted utility maximizers studied by Chew [1983].
Credibility in Credence Goods Markets
Authors: Xiaoxiao Hu, Haoran Lei
Date: 2023-10-14 00:00:00

An expert seller chooses an experiment to influence a client's purchasing decision, but may manipulate the experiment result for personal gain. When credibility surpasses a critical threshold, the expert chooses a fully-revealing experiment and, if possible, manipulates the unfavorable result. In this case, a higher credibility strictly benefits the expert, whereas the client never benefits from the expert's services. We also discuss policies regarding monitoring expert's disclosure and price regulation. When prices are imposed exogenously, monitoring disclosure does not affect the client's highest equilibrium value. A lower price may harm the client when it discourages the expert from disclosing information.
Risk Aversion and Insurance Propensity
Authors: Fabio Maccheroni, Massimo Marinacci, Ruodu Wang, Qinyu Wu
Date: 2023-10-13 00:00:00

We provide a new foundation of risk aversion by showing that this attitude is fully captured by the propensity to seize insurance opportunities. Our foundation, which applies to all probabilistically sophisticated preferences, well accords with the commonly held prudential interpretation of risk aversion that dates back to the seminal works of Arrow (1963) and Pratt (1964). In our main results, we first characterize the Arrow-Pratt risk aversion in terms of propensity to full insurance and the stronger notion of risk aversion of Rothschild and Stiglitz (1970) in terms of propensity to partial insurance. We then extend the analysis to comparative risk aversion by showing that the notion of Yaari (1969) corresponds to comparative propensity to full insurance, while the stronger notion of Ross (1981) corresponds to comparative propensity to partial insurance.
The spatial evolution of economic activities and the emergence of cities
Authors: Davide Fiaschi, Cristiano Ricci
Date: 2023-10-11 00:00:00

This paper examines the spatial agglomeration of workers and income in a continuous space-time framework. Local markets feature spatial spillovers and both exogenous and endogenous amenities. Workers relocate to maximise their instantaneous utility, constrained by mobility costs. In the limit of infinite workers, short-run equilibria are described by a partial differential equation (PDE). The PDE reveals spatial dynamics influenced by initial conditions, path dependence, and metastability (persistence), where prolonged stability is disrupted by sharp transitions to new distributions. We characterise conditions for spatial agglomeration in stationary equilibria and demonstrate that social utility consistently increases over time, suggesting efficient spatial allocations. Numerical results replicate key patterns, such as city formation, dependence on historical spatial patterns, and nonlinear out-of-equilibrium dynamics.
Enhancing Spoofing Speech Detection Using Rhythm Information
Authors: Jingze Lu, Yuxiang Zhang, Wenchao Wang, Zengqiang Shang, Pengyuan Zhang
Date: 2023-10-18 00:00:00
Tasks: Data Augmentation, Rhythm

Current spoofing speech detection systems need more convincing evidence. In this paper, the flaws of rhythm information inherent in the TTS-generated speech are analyzed to increase the reliability of detection systems. TTS models take text as input and utilize acoustic models to predict rhythm information, which introduces artifacts in the rhythm information. By filtering out vocal tract response, the remaining glottal flow with rhythm information retains detection ability for TTS-generated speech. Based on these analyses, a rhythm perturbation module is proposed to enhance the copy-synthesis data augmentation method. Fake utterances generated by the proposed method force the detecting model to pay attention to the artifacts in rhythm information and effectively improve the ability to detect TTS-generated speech of the anti-spoofing countermeasures.
Iterative Shallow Fusion of Backward Language Model for End-to-End Speech Recognition
Authors: Atsunori Ogawa, Takafumi Moriya, Naoyuki Kamo, Naohiro Tawara, Marc Delcroix
Date: 2023-10-17 00:00:00
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Decoder, Language Modeling, Language Modelling, Sentence, speech-recognition, Speech Recognition

We propose a new shallow fusion (SF) method to exploit an external backward language model (BLM) for end-to-end automatic speech recognition (ASR). The BLM has complementary characteristics with a forward language model (FLM), and the effectiveness of their combination has been confirmed by rescoring ASR hypotheses as post-processing. In the proposed SF, we iteratively apply the BLM to partial ASR hypotheses in the backward direction (i.e., from the possible next token to the start symbol) during decoding, substituting the newly calculated BLM scores for the scores calculated at the last iteration. To enhance the effectiveness of this iterative SF (ISF), we train a partial sentence-aware BLM (PBLM) using reversed text data including partial sentences, considering the framework of ISF. In experiments using an attention-based encoder-decoder ASR system, we confirmed that ISF using the PBLM shows comparable performance with SF using the FLM. By performing ISF, early pruning of prospective hypotheses can be prevented during decoding, and we can obtain a performance improvement compared to applying the PBLM as post-processing. Finally, we confirmed that, by combining SF and ISF, further performance improvement can be obtained thanks to the complementarity of the FLM and PBLM.