pwc-archive/papers-with-abstracts huggingface dataset:
In and out of lockdown: Propagation of supply and demand shocks in a dynamic input-output model
Authors: Anton Pichler, Marco Pangallo, R. Maria del Rio-Chanona, François Lafond, J. Doyne Farmer
Date: 2021-02-18 00:00:00

Economic shocks due to Covid-19 were exceptional in their severity, suddenness and heterogeneity across industries. To study the upstream and downstream propagation of these industry-specific demand and supply shocks, we build a dynamic input-output model inspired by previous work on the economic response to natural disasters. We argue that standard production functions, at least in their most parsimonious parametrizations, are not adequate to model input substitutability in the context of Covid-19 shocks. We use a survey of industry analysts to evaluate, for each industry, which inputs were absolutely necessary for production over a short time period. We calibrate our model on the UK economy and study the economic effects of the lockdown that was imposed at the end of March and gradually released in May. Looking back at predictions that we released in May, we show that the model predicted aggregate dynamics very well, and sectoral dynamics to a large extent. We discuss the relative extent to which the model's dynamics and performance was due to the choice of the production function or the choice of an exogenous shock scenario. To further explore the behavior of the model, we use simpler scenarios with only demand or supply shocks, and find that popular metrics used to predict a priori the impact of shocks, such as output multipliers, are only mildly useful.
Sustainable and Resilient Systems for Intergenerational Justice
Authors: Sahar Zandi
Date: 2021-02-18 00:00:00
Tasks: Fairness

Rawls' theory of justice aims at fairness. He does not only think of justice between exiting parties in existing society, but he also thinks of it between generations intergenerational justice problem. Rawls' solution to this problem is the saving principle, and he says that we are responsible for being just with the next generations. Wolf thinks of our responsibility for future generations as a kind of financial debt that we have to pay. He also develops the meaning of "saving" and says that it is not restricted to the monetary one. Wolf extends the definition of "saving" such that it includes investment on behalf of the next generations as well. In this paper, I want to extend the meaning of "saving" to "using the resources for sustainable and resilient systems." By referring to the problem of time, I show that our decision on behalf of the next generations will be rational only if we entirely use the natural resources and wealth to produce sustainable and resilient systems.
The Expediting Effect of Monitoring on Infrastructural Works. A Regression-Discontinuity Approach with Multiple Assignment Variables
Authors: Giuseppe Francesco Gori, Patrizia Lattarulo, Marco Mariani
Date: 2021-02-16 00:00:00
Tasks: Management, regression, Survival Analysis

Decentralised government levels are often entrusted with the management of public works and required to ensure well-timed infrastructure delivery to their communities. We investigate whether monitoring the activity of local procuring authorities during the execution phase of the works they manage may expedite the infrastructure delivery process. Focussing on an Italian regional law which imposes monitoring by the regional government on "strategic" works carried out by local buyers, we draw causal claims using a regression-discontinuity approach, made unusual by the presence of multiple assignment variables. Estimation is performed through discrete-time survival analysis techniques. Results show that monitoring does expedite infrastructure delivery.
The economic dependency of the Bitcoin security
Authors: Pavel Ciaian, d'Artis Kancs, Miroslava Rajcaniova
Date: 2021-02-16 00:00:00

We study to what extent the Bitcoin blockchain security permanently depends on the underlying distribution of cryptocurrency market outcomes. We use daily blockchain and Bitcoin data for 2014-2019 and employ the ARDL approach. We test three equilibrium hypotheses: (i) sensitivity of the Bitcoin blockchain to mining reward; (ii) security outcomes of the Bitcoin blockchain and the proof-of-work cost; and (iii) the speed of adjustment of the Bitcoin blockchain security to deviations from the equilibrium path. Our results suggest that the Bitcoin price and mining rewards are intrinsically linked to Bitcoin security outcomes. The Bitcoin blockchain security's dependency on mining costs is geographically differenced - it is more significant for the global mining leader China than for other world regions. After input or output price shocks, the Bitcoin blockchain security reverts to its equilibrium security level.
Interdependencies between Mining Costs, Mining Rewards and Blockchain Security
Authors: Pavel Ciaian, d'Artis Kancs, Miroslava Rajcaniova
Date: 2021-02-16 00:00:00

This paper studies to what extent the cost of operating a proof-of-work blockchain is intrinsically linked to the cost of preventing attacks, and to what extent the underlying digital ledger security budgets are correlated with the cryptocurrency market outcomes. We theoretically derive an equilibrium relationship between the cryptocurrency price, mining rewards and mining costs, and blockchain security outcomes. Using daily crypto market data for 2014-2021 and employing the autoregressive distributed lag approach - that allows treating all the relevant moments of the blockchain series as potentially endogenous - we provide empirical evidence of cryptocurrency price and mining rewards indeed being intrinsically linked to blockchain security outcomes.
Canonical Correlation and Assortative Matching: A Remark
Authors: Arnaud Dupuy, Alfred Galichon
Date: 2021-02-15 00:00:00

In the context of the Beckerian theory of marriage, when men and women match on a single-dimensional index that is the weighted sum of their respective multivariate attributes, many papers in the literature have used linear canonical correlation, and related techniques, in order to estimate these weights. We argue that this estimation technique is inconsistent and suggest some solutions.
Personality Traits and the Marriage Market
Authors: Arnaud Dupuy, Alfred Galichon
Date: 2021-02-15 00:00:00
Tasks: Survey

Which and how many attributes are relevant for the sorting of agents in a matching market? This paper addresses these questions by constructing indices of mutual attractiveness that aggregate information about agents' attributes. The first k indices for agents on each side of the market provide the best approximation of the matching surplus by a k-dimensional model. The methodology is applied on a unique Dutch households survey containing information about education, height, BMI, health, attitude toward risk and personality traits of spouses.
How Misuse of Statistics Can Spread Misinformation: A Study of Misrepresentation of COVID-19 Data
Authors: Shailesh Bharati, Rahul Batra
Date: 2021-02-14 00:00:00
Tasks: Misinformation

This paper investigates various ways in which a pandemic such as the novel coronavirus, could be predicted using different mathematical models. It also studies the various ways in which these models could be depicted using various visualization techniques. This paper aims to present various statistical techniques suggested by the Centres for Disease Control and Prevention in order to represent the epidemiological data. The main focus of this paper is to analyse how epidemiological data or contagious diseases are theorized using any available information and later may be presented wrongly by not following the guidelines, leading to inaccurate representation and interpretations of the current scenario of the pandemic; with a special reference to the Indian Subcontinent.
Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles
Authors: Xiaoyan Wang, Xi Lin, Meng Li
Date: 2021-02-14 00:00:00
Tasks: Autonomous Vehicles

Autonomous vehicles (AVs) have the potential of reshaping the human mobility in a wide variety of aspects. This paper focuses on a new possibility that the AV owners have the option of "renting" their AVs to a company, which can use these collected AVs to provide on-demand ride services without any drivers. We call such a mobility market with AV renting options the "AV crowdsourcing market". This paper establishes an aggregate equilibrium model with multiple transport modes to analyze the AV crowdsourcing market. The modeling framework can capture the customers' mode choices and AV owners' rental decisions with the presence of traffic congestion. Then, we explore different scenarios that either maximize the crowdsourcing platform's profit or maximize social welfare. Gradient-based optimization algorithms are designed for solving the problems. The results obtained by numerical examples reveal the welfare enhancement and the strong profitability of the AV crowdsourcing service. However, when the crowdsourcing scale is small, the crowdsourcing platform might not be profitable. A second-best pricing scheme is able to avoid such undesirable cases. The insights generated from the analyses provide guidance for regulators, service providers and citizens to make future decisions regarding the utilization of the AV crowdsourcing markets for serving the good of the society.
On Human Capital and Team Stability
Authors: Pierre-André Chiappori, Alfred Galichon, Bernard Salanié
Date: 2021-02-12 00:00:00

In many economic contexts, agents from a same population team up to better exploit their human capital. In such contexts (often called "roommate matching problems"), stable matchings may fail to exist even when utility is transferable. We show that when each individual has a close substitute, a stable matching can be implemented with minimal policy intervention. Our results shed light on the stability of partnerships on the labor market. Moreover, they imply that the tools crafted in empirical studies of the marriage problem can easily be adapted to many roommate problems.
Uncertainty spill-overs: when policy and financial realms overlap
Authors: Emanuele Bacchiocchi, Catalin Dragomirescu-Gaina
Date: 2021-02-12 00:00:00

No matter its source, financial- or policy-related, uncertainty can feed onto itself, inflicting the real economic sector, altering expectations and behaviours, and leading to identification challenges in empirical applications. The strong intertwining between policy and financial realms prevailing in Europe, and in Euro Area in particular, might complicate the problem and create amplification mechanisms difficult to pin down. To reveal the complex transmission of country-specific uncertainty shocks in a multi-country setting, and to properly account for cross-country interdependencies, we employ a global VAR specification for which we adapt an identification approach based on magnitude restrictions. Once we separate policy uncertainty from financial uncertainty shocks, we find evidence of important cross-border uncertainty spill-overs. We also uncover a new amplification mechanism for domestic uncertainty shocks, whose true nature becomes more blurred once they cross the national boundaries and spill over to other countries. With respect to ECB policy reactions, we reveal stronger but less persistent responses to financial uncertainty shocks compared to policy uncertainty shocks. This points to ECB adopting a more (passive or) accommodative stance towards the former, but a more pro-active stance towards the latter shocks, possibly as an attempt to tame policy uncertainty spill-overs and prevent the fragmentation of the Euro Area financial markets.
Challenges of Equitable Vaccine Distribution in the COVID-19 Pandemic
Authors: Joseph Bae, Darshan Gandhi, Jil Kothari, Sheshank Shankar, Jonah Bae, Parth Patwa, Rohan Sukumaran, Aviral Chharia, Sanjay Adhikesaven, Shloak Rathod, Irene Nandutu, Sethuraman TV, Vanessa Yu, Krutika Misra, Srinidhi Murali, Aishwarya Saxena, Kasia Jakimowicz, Vivek Sharma, Rohan Iyer, Ashley Mehra, Alex Radunsky, Priyanshi Katiyar, Ananthu James, Jyoti Dalal, Sunaina Anand, Shailesh Advani, Jagjit Dhaliwal, Ramesh Raskar
Date: 2020-11-24 00:00:00

The COVID-19 pandemic has led to a need for widespread and rapid vaccine development. As several vaccines have recently been approved for human use or are in different stages of development, governments across the world are preparing comprehensive guidelines for vaccine distribution and monitoring. In this early article, we identify challenges in logistics, health outcomes, user-centric matters, and communication associated with disease-related, individual, societal, economic, and privacy consequences. Primary challenges include difficulty in equitable distribution, vaccine efficacy, duration of immunity, multi-dose adherence, and privacy-focused record-keeping to be HIPAA compliant. While many of these challenges have been previously identified and addressed, some have not been acknowledged from a comprehensive view accounting for unprecedented interactions between challenges and specific populations. The logistics of equitable widespread vaccine distribution in disparate populations and countries of various economic, racial, and cultural constitutions must be thoroughly examined and accounted for. We also describe unique challenges regarding the efficacy of vaccines in specialized populations including children, the elderly, and immunocompromised individuals. Furthermore, we report the potential for understudied drug-vaccine interactions as well as the possibility that certain vaccine platforms may increase susceptibility to HIV. Given these complicated issues, the importance of privacy-focused, user-centric systems for vaccine education and incentivization along with clear communication from governments, organizations, and academic institutions is imperative. These challenges are by no means insurmountable, but require careful attention to avoid consequences spanning a range of disease-related, individual, societal, economic, and security domains.
Approximate Expected Utility Rationalization
Authors: Federico Echenique, Kota Saito, Taisuke Imai
Date: 2021-02-12 00:00:00

We propose a new measure of deviations from expected utility theory. For any positive number~$e$, we give a characterization of the datasets with a rationalization that is within~$e$ (in beliefs, utility, or perceived prices) of expected utility theory. The number~$e$ can then be used as a measure of how far the data is to expected utility theory. We apply our methodology to data from three large-scale experiments. Many subjects in those experiments are consistent with utility maximization, but not with expected utility maximization. Our measure of distance to expected utility is correlated with subjects' demographic characteristics.
Coordinated Capacity Reductions and Public Communication in the Airline Industry
Authors: Gaurab Aryal, Federico Ciliberto, Benjamin T. Leyden
Date: 2021-02-10 00:00:00

We investigate the allegation that legacy U.S. airlines communicated via earnings calls to coordinate with other legacy airlines in offering fewer seats on competitive routes. To this end, we first use text analytics to build a novel dataset on communication among airlines about their capacity choices. Estimates from our preferred specification show that the number of offered seats is 2% lower when all legacy airlines in a market discuss the concept of "capacity discipline." We verify that this reduction materializes only when legacy airlines communicate concurrently, and that it cannot be explained by other possibilities, including that airlines are simply announcing to investors their unilateral plans to reduce capacity, and then following through on those announcements.
Models, Markets, and the Forecasting of Elections
Authors: Rajiv Sethi, Julie Seager, Emily Cai, Daniel M. Benjamin, Fred Morstatter
Date: 2021-02-06 00:00:00

We examine probabilistic forecasts for battleground states in the 2020 US presidential election, using daily data from two sources over seven months: a model published by The Economist, and prices from the PredictIt exchange. We find systematic differences in accuracy over time, with markets performing better several months before the election, and the model performing better as the election approached. A simple average of the two forecasts performs better than either one of them overall, even though no average can outperform both component forecasts for any given state-date pair. This effect arises because the model and the market make different kinds of errors in different states: the model was confidently wrong in some cases, while the market was excessively uncertain in others. We conclude that there is value in using hybrid forecasting methods, and propose a market design that incorporates model forecasts via a trading bot to generate synthetic predictions. We also propose and conduct a profitability test that can be used as a novel criterion for the evaluation of forecasting performance.
Dynamic Structural Impact of the COVID-19 Outbreak on the Stock Market and the Exchange Rate: A Cross-country Analysis Among BRICS Nations
Authors: Rupam Bhattacharyya, Sheo Rama, Atul Kumar, Indrajit Banerjee
Date: 2021-02-10 00:00:00
Tasks: Causal Inference

COVID-19 has impacted the economy of almost every country in the world. Of particular interest are the responses of the economic indicators of developing nations (such as BRICS) to the COVID-19 shock. As an extension to our earlier work on the dynamic associations of pandemic growth, exchange rate, and stock market indices in the context of India, we look at the same question with respect to the BRICS nations. We use structural variable autoregression (SVAR) to identify the dynamic underlying associations across the normalized growth measurements of the COVID-19 cumulative case, recovery, and death counts, and those of the exchange rate, and stock market indices, using data over 203 days (March 12 - September 30, 2020). Using impulse response analyses, the COVID-19 shock to the growth of exchange rate was seen to persist for around 10+ days, and that for stock exchange was seen to be around 15 days. The models capture the contemporaneous nature of these shocks and the subsequent responses, potentially guiding to inform policy decisions at a national level. Further, causal inference-based analyses would allow us to infer relationships that are stronger than mere associations.
The Role of a Nation's Culture in the Country's Governance: Stochastic Frontier Analysis
Authors: Vladimír Holý, Tomáš Evan
Date: 2021-02-10 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction

What role does culture play in determining institutions in a country? This paper argues that the establishment of institutions is a process originating predominantly in a nation's culture and tries to discern the role of a cultural background in the governance of countries. We use the six Hofstede's Cultural Dimensions and the six Worldwide Governance Indicators to test the strength of the relationship on 94 countries between 1996 and 2019. We find that the strongest cultural characteristics are Power Distance with negative effect on governance and Long-Term Orientation with positive effect. We also determine how well countries transform their cultural characteristics into institutions using stochastic frontier analysis.
The Fake News Effect: Experimentally Identifying Motivated Reasoning Using Trust in News
Authors: Michael Thaler
Date: 2020-12-03 00:00:00
Tasks: Experimental Design

Motivated reasoning posits that people distort how they process information in the direction of beliefs they find attractive. This paper creates a novel experimental design to identify motivated reasoning from Bayesian updating when people have preconceived beliefs. It analyzes how subjects assess the veracity of information sources that tell them the median of their belief distribution is too high or too low. Bayesians infer nothing about the source veracity, but motivated beliefs are evoked. Evidence supports politically-motivated reasoning about immigration, income mobility, crime, racial discrimination, gender, climate change, and gun laws. Motivated reasoning helps explain belief biases, polarization, and overconfidence.
Lowest-cost virus suppression
Authors: Jacob Janssen, Yaneer Bar-Yam
Date: 2021-02-09 00:00:00

Analysis of policies for managing epidemics require simultaneously an economic and epidemiological perspective. We adopt a cost-of-policy framework to model both the virus spread and the cost of handling the pandemic. Because it is harder and more costly to fight the pandemic when the circulation is higher, we find that the optimal policy is to go to zero or near-zero case numbers. Without imported cases, if a region is willing to implement measures to prevent spread at one level in number of cases, it must also be willing to prevent the spread with at a lower level, since it will be cheaper to do so and has only positive other effects. With imported cases, if a region is not coordinating with other regions, we show the cheapest policy is continually low but nonzero cases due to decreasing cost of halting imported cases. When it is coordinating, zero is cost-optimal. Our analysis indicates that within Europe cooperation targeting a reduction of both within country transmission, and between country importation risk, should help achieve lower transmission and reduced costs.
Black-box model risk in finance
Authors: Samuel N. Cohen, Derek Snow, Lukasz Szpruch
Date: 2021-02-09 00:00:00
Tasks: BIG-bench Machine Learning, Management, model

Machine learning models are increasingly used in a wide variety of financial settings. The difficulty of understanding the inner workings of these systems, combined with their wide applicability, has the potential to lead to significant new risks for users; these risks need to be understood and quantified. In this sub-chapter, we will focus on a well studied application of machine learning techniques, to pricing and hedging of financial options. Our aim will be to highlight the various sources of risk that the introduction of machine learning emphasises or de-emphasises, and the possible risk mitigation and management strategies that are available.
View about consumption tax and grandchildren
Authors: Eiji Yamamura
Date: 2021-02-09 00:00:00

In Japan, the increase in the consumption tax rate, a measure of balanced public finance, reduces the inequality of fiscal burden between the present and future generations. This study estimates the effect of grandchildren on an older person's view of consumption tax, using independently collected data. The results show that having grandchildren is positively associated with supporting an increase in consumption tax. Further, this association is observed strongly between granddaughters and grandparents. However, the association between grandsons and grandparents depends on the sub-sample. This implies that people of the old generation are likely to accept the tax burden to reduce the burden on their grandchildren, especially granddaughters. In other words, grandparents show intergenerational altruism.
Trade Union Strategies towards Platform Workers: Exploration Instead of Action (The Case of Hungarian Trade Unions)
Authors: Szilvia Borbely, Csaba Mako, Miklos Illessy, Saeed Nostrabadi
Date: 2021-02-08 00:00:00

Although the share of platform work is very small compared to conventional and traditional employment system, research shows that the use of platform work is increasingly growing all over the world. Trade unions have also paid special attention to the platform work because they know that the transfer of a percentage of human resources to the platforms is undeniable. To this end, the trade unions prepare themselves for the challenges and dynamics of this emerging phenomenon in the field of human resources. Using a qualitative research method and a case study of Hungary, the present study aimed to identify the strategies adopted by Trade Unions to manage the transition to platform works and provide suggestions for both practitioners and future research.