pwc-archive/papers-with-abstracts huggingface dataset:
Computing Prices for Target Profits in Contracts
Authors: Ghurumuruhan Ganesan
Date: 2021-03-01 00:00:00
Tasks: TAG

Price discrimination for maximizing expected profit is a well-studied concept in economics and there are various methods that achieve the maximum given the user type distribution and the budget constraints. In many applications, particularly with regards to engineering and computing, it is often the case than the user type distribution is unknown or not accurately known. In this paper, we therefore propose and study a mathematical framework for price discrimination with \emph{target} profits under the contract-theoretic model. We first consider service providers with a given user type profile and determine sufficient conditions for achieving a target profit. Our proof is constructive in that it also provides a method to compute the quality-price tag menu. Next we consider a dual scenario where the offered service qualities are predetermined and describe an iterative method to obtain nominal demand values that best match the qualities offered by the service provider while achieving a target profit-user satisfaction margin. We also illustrate our methods with design examples in both cases.
Consequential LCA for territorial and multimodal transportation policies: method and application to the free-floating e-scooter disruption in Paris
Authors: Anne de Bortoli, Zoi Christoforou
Date: 2021-03-01 00:00:00

The indirect environmental impacts of transport disruptions in urban mobility are frequently overlooked due to a lack of appropriate assessment methods. Consequential Life Cycle Assessment (CLCA) is a method to capture the environmental consequences of the entire cause and effect chain of these disruptions but has never been adapted to transportat disruption at the city scale. This paper proposes a mathematical formalization of CLCA applied to a territorial mobility change. The method is applied to quantify the impact on climate change of the breakthrough of free-floating e-scooters (FFES) in Paris. A FFES user survey is conducted to estimate the modal shifts due to FFES. Trip substitutions from all the Parisian modes concerned are considered - personal or shared bicycles and motor scooters, private car, taxi and ride-hailing, bus, streetcar, metro and RER (the Paris metropolitan area mass rapid transit system). All these Parisian modes are assessed for the first time using LCA. Final results estimate that over one year, the FFES generated an extra thirteen thousand tons of CO2eq under an assumption of one million users, mainly due to major shifts coming from lower-emitting modes (60% from the metro and the RER, 22% from active modes). Recommendations are given to enhance their carbon footprint. A scenario analysis shows that increasing the lifetime mileage is insufficient to get a positive balance: reducing drastically servicing emissions is also required. A sensitivity analysis switching the French electricity mix for eleven other country mixes suggests a better climate change effect of the FFES in similar metropolitan areas with higher electricity carbon intensity, such as in Germany and China. Finally, the novelty and the limits of the method are discussed, as well as the results and the role of e-scooters, micromobility, and shared vehicles towards a sustainable mobility.
Epidemics with Behavior
Authors: Satoshi Fukuda, Nenad Kos, Christoph Wolf
Date: 2021-02-28 00:00:00

We study equilibrium distancing during epidemics. Distancing reduces the individual's probability of getting infected but comes at a cost. It creates a single-peaked epidemic, flattens the curve and decreases the size of the epidemic. We examine more closely the effects of distancing on the outset, the peak and the final size of the epidemic. First, we define a behavioral basic reproduction number and show that it is concave in the transmission rate. The infection, therefore, spreads only if the transmission rate is in the intermediate region. Second, the peak of the epidemic is non-monotonic in the transmission rate. A reduction in the transmission rate can lead to an increase of the peak. On the other hand, a decrease in the cost of distancing always flattens the curve. Third, both an increase in the infection rate as well as an increase in the cost of distancing increase the size of the epidemic. Our results have important implications on the modeling of interventions. Imposing restrictions on the infection rate has qualitatively different effects on the trajectory of the epidemics than imposing assumptions on the cost of distancing. The interventions that affect interactions rather than the transmission rate should, therefore, be modeled as changes in the cost of distancing.
Modelling Optimal Policies of Demand Responsive Transport and Interrelationships between Occupancy Rate and Costs
Authors: Jani-Pekka Jokinen
Date: 2021-02-28 00:00:00

This paper presents a model addressing welfare optimal policies of demand responsive transportation service, where passengers cause external travel time costs for other passengers due to the route changes. Optimal pricing and trip production policies are modelled both on the aggregate level and on the network level. The aggregate model is an extension from Jokinen (2016) with flat pricing model, but occupancy rate is now modelled as an endogenous variable depending on demand and capacity levels. The network model enables to describe differences between routes from the viewpoint of occupancy rate and efficient trip combining. Moreover, the model defines the optimal differentiated pricing for routes.
How to Issue a Central Bank Digital Currency
Authors: David Chaum, Christian Grothoff, Thomas Moser
Date: 2021-02-27 00:00:00

With the emergence of Bitcoin and recently proposed stablecoins from BigTechs, such as Diem (formerly Libra), central banks face growing competition from private actors offering their own digital alternative to physical cash. We do not address the normative question whether a central bank should issue a central bank digital currency (CBDC) or not. Instead, we contribute to the current research debate by showing how a central bank could do so, if desired. We propose a token-based system without distributed ledger technology and show how earlier-deployed, software-only electronic cash can be improved upon to preserve transaction privacy, meet regulatory requirements in a compelling way, and offer a level of quantum-resistant protection against systemic privacy risk. Neither monetary policy nor financial stability would be materially affected because a CBDC with this design would replicate physical cash rather than bank deposits.
A Comparison of Indonesia E-Commerce Sentiment Analysis for Marketing Intelligence Effort
Authors: Andry Alamsyah, Fatma Saviera
Date: 2021-02-27 00:00:00
Tasks: Marketing, Sentiment Analysis

The rapid growth of the e-commerce market in Indonesia, making various e-commerce companies appear and there has been high competition among them. Marketing intelligence is an important activity to measure competitive position. One element of marketing intelligence is to assess customer satisfaction. Many Indonesian customers express their sense of satisfaction or dissatisfaction towards the company through social media. Hence, using social media data provides a new practical way to measure marketing intelligence effort. This research performs sentiment analysis using the naive bayes classifier classification method with TF-IDF weighting. We compare the sentiments towards of top-3 e-commerce sites visited companies, are Bukalapak, Tokopedia, and Elevenia. We use Twitter data for sentiment analysis because it's faster, cheaper, and easier from both the customer and the researcher side. The purpose of this research is to find out how to process the huge customer sentiment Twitter to become useful information for the e-commerce company, and which of those top-3 e-commerce companies has the highest level of customer satisfaction. The experiment results show the method can be used to classify customer sentiments in social media Twitter automatically and Elevenia is the highest e-commerce with customer satisfaction.
The Cost of Pollution in the Upper Atoyac River Basin: A Systematic Review
Authors: Maria Eugenia Ibarraran, Romeo A. Saldana-Vazquez, Tamara Perez-Garcia
Date: 2021-02-27 00:00:00

The Atoyac River is among the two most polluted in Mexico. Water quality in the Upper Atoyac River Basin (UARB) has been devastated by industrial and municipal wastewater, as well as from effluents from local dwellers, that go through little to no treatment, affecting health, production, ecosystems and property value. We did a systematic review and mapping of the costs that pollution imposes on different sectors and localities in the UARB, and initially found 358 studies, of which 17 were of our particular interest. We focus on estimating the cost of pollution through different valuation methods such as averted costs, hedonic pricing, and contingent valuation, and for that we only use 10 studies. Costs range from less than a million to over $16 million dollars a year, depending on the sector, with agriculture, industry and tourism yielding the highest costs. This exercise is the first of its kind in the UARB that maps costs for sectors and localities affected, and sheds light on the need of additional research to estimate the total cost of pollution throughout the basin. This information may help design further research needs in the region.
The use of primary energy factors and CO2 intensities -- reviewing the state of play in academic literature
Authors: Sam Hamels, Eline Himpe, Jelle Laverge, Marc Delghust, Kjartan Van den Brande, Arnold Janssens, Johan Albrecht
Date: 2021-02-26 00:00:00

Reaching the 2030 targets for the EU primary energy use (PE) and CO2eq emissions (CE) requires an accurate assessment of how different technologies perform on these two fronts. In this regard, the focus in academia is increasingly shifting from traditional technologies to electricity consuming alternatives. Calculating and comparing their performance with respect to traditional technologies requires conversion factors (CFs) like a primary energy factor and a CO2eq intensity. These reflect the PE and CE associated with each unit of electricity consumed. Previous work has shown that the calculation and use of CFs is a contentious and multifaceted issue. However, this has mostly remained a theoretical discussion. A stock-taking of how CFs are actually calculated and used in academic literature has so far been missing, impeding insight into what the contemporary trends and challenges are. Therefore, we structurally review 65 publications across six methodological aspects. We find that 72% of the publications consider only a single country, 86% apply a purely retrospective perspective, 54% apply a yearly temporal resolution, 65% apply a purely operational (instead of a life-cycle) perspective, 91% make use of average (rather than marginal) CFs, and 75% ignore electricity imports from surrounding countries. We conclude that there is a strong need in the literature for a publicly available, transparently calculated dataset of CFs, which avoids the shortcomings found in the literature. This would enable more accurate and transparent PE and CE calculations, and support the development of new building energy performance assessment methods and smart grid algorithms.
Priming prosocial behavior and expectations in response to the Covid-19 pandemic -- Evidence from an online experiment
Authors: Valeria Fanghella, Thi-Thanh-Tam Vu, Luigi Mittone
Date: 2021-02-26 00:00:00

This paper studies whether and how differently projected information about the impact of the Covid-19 pandemic affects individuals' prosocial behavior and expectations on future outcomes. We conducted an online experiment with British participants (N=961) when the UK introduced its first lockdown and the outbreak was on its growing stage. Participants were primed with either the environmental or economic consequences (i.e., negative primes), or the environmental or economic benefits (i.e., positive primes) of the pandemic, or with neutral information. We measured priming effects on an incentivized take-and-give dictator game and on participants' expectations about future environmental quality and economic growth. Our results show that primes affect participants' expectations, but not their prosociality. In particular, participants primed with environmental consequences hold a more pessimistic view on future environmental quality, while those primed with economic benefits are more optimistic about future economic growth. Instead, the positive environmental prime and the negative economic prime do not influence expectations. Our results offer insights into how information affects behavior and expectations during the Covid-19 pandemic.
Does Bankruptcy Protection Affect Asset Prices? Evidence from changes in Homestead Exemptions
Authors: Yildiray Yildirim, Albert Alex Zevelev
Date: 2021-02-25 00:00:00

Does the ability to protect an asset from unsecured creditors affect its price? This paper identifies the impact of bankruptcy protection on house prices using 139 changes in homestead exemptions. Large increases in the homestead exemption raised house prices 3% before 2005. Smaller exemption increases, to adjust for inflation, did not affect house prices. The effect disappeared after BAPCPA, a 2005 federal law designed to prevent bankruptcy abuse. The effect was bigger in inelastic locations.
Granddaughter and voting for a female candidate
Authors: Eiji Yamamura
Date: 2021-02-24 00:00:00

This study examines the influence of grandchildren's gender on grandparents' voting behavior using independently collected individual-level data. The survey was conducted immediately after the House of Councilors election in Japan. I observed that individuals with a granddaughter were more likely to vote for female candidates by around 10 % than those without. However, having a daughter did not affect the parents' voting behavior. Furthermore, having a son or a grandson did not influence grandparents' voting behavior. This implies that grandparents voted for their granddaughter's future benefit because granddaughters may be too young vote in a male-dominated and aging society.
Price Discrimination in International Airline Markets
Authors: Gaurab Aryal, Charles Murry, Jonathan W. Williams
Date: 2021-02-10 00:00:00

We develop a model of inter-temporal and intra-temporal price discrimination by monopoly airlines to study the ability of different discriminatory pricing mechanisms to increase efficiency and the associated distributional implications. To estimate the model, we use unique data from international airline markets with flight-level variation in prices across time, cabins, and markets and information on passengers' reasons for travel and time of purchase. The current pricing practice yields approximately 77% of the first-best welfare. The source of this inefficiency arises primarily from private information about passenger valuations, not dynamic uncertainty about demand. We also find that if airlines could discriminate between business and leisure passengers, total welfare would improve at the expense of business passenger surplus. Also, replacing the current pricing that involves screening passengers across cabin classes with offering a single cabin class has minimal effect on total welfare.
Understanding the Farmers, Environmental Citizenship Behaviors Towards Climate Change. The Moderating Mediating Role of Environmental Knowledge and Ascribed Responsibility
Authors: Immaculate Maumoh, Emmanuel H. Yindi
Date: 2021-02-23 00:00:00

Knowledge is known to be a pre-condition for an individuals behavior. For the most efficient informational strategies for education, it is essential that we identify the types of knowledge that promote behavior effectively and investigate their structure. The purpose of this paper is therefore to examine the factors that affect Kenyan farmers, environmental citizenship behavior (ECB) in the context of Adaptation and mitigation (Climate smart agriculture). To achieve this objective, a theoretical framework has been developed based on value belief norm (VBN) theory. Design/methodology/approach, Data were obtained from 350 farmers using a survey method. Partial lease square structural equation modelling (PLS-SEM) was used to examine the hypothetical model. The results of PLS analysis confirm the direct and mediating effect of the causal sequences of the variables in the VBN model. The moderating role of Environmental knowledge has been seen to be impactful in Climate Smart Agriculture.
The Association of Opening K-12 Schools with the Spread of COVID-19 in the United States: County-Level Panel Data Analysis
Authors: Victor Chernozhukov, Hiroyuki Kasahara, Paul Schrimpf
Date: 2021-02-20 00:00:00

This paper empirically examines how the opening of K-12 schools and colleges is associated with the spread of COVID-19 using county-level panel data in the United States. Using data on foot traffic and K-12 school opening plans, we analyze how an increase in visits to schools and opening schools with different teaching methods (in-person, hybrid, and remote) is related to the 2-weeks forward growth rate of confirmed COVID-19 cases. Our debiased panel data regression analysis with a set of county dummies, interactions of state and week dummies, and other controls shows that an increase in visits to both K-12 schools and colleges is associated with a subsequent increase in case growth rates. The estimates indicate that fully opening K-12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the positive association of K-12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These results have a causal interpretation in a structural model with unobserved county and time confounders. Sensitivity analysis shows that the baseline results are robust to timing assumptions and alternative specifications.
Métodos Empíricos Aplicados à Análise Econômica do Direito
Authors: Thomas V. Conti
Date: 2021-02-20 00:00:00

Nas \'ultimas d\'ecadas houve forte mudan\c{c}a no perfil das publica\c{c}\~oes em an\'alise econ\^omica do direito e nos m\'etodos emp\'iricos mais utilizados. Por\'em, nos pr\'oximos anos a mudan\c{c}a pode ser maior e mais r\'apida, exigindo adapta\c{c}\~ao dos pesquisadores da \'area. Neste cap\'itulo analiso algumas tend\^encias recentes de mudan\c{c}a e oportunidades futuras que se avizinham a partir avan\c{c}os nas bases de dados, estat\'istica, computa\c{c}\~ao e no arcabou\c{c}o regulat\'orio dos pa\'ises. Avan\c{c}o a hip\'otese de que expans\~ao de objetos e m\'etodos favorecer\'a equipes de pesquisa maiores e interdisciplinares e apresento evid\^encias circunstanciais a partir de dados bibliom\'etricos de que isso j\'a vem acontecendo no Journal of Law and Economics.
Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses
Authors: Alberto Bisin, Andrea Moro
Date: 2021-02-19 00:00:00
Tasks: Epidemiology

We simulate a spatial behavioral model of the diffusion of an infection to understand the role of geographic characteristics: the number and distribution of outbreaks, population size, density, and agents' movements. We show that several invariance properties of the SIR model concerning these variables do not hold when agents interact with neighbors in a (two dimensional) geographical space. Indeed, the spatial model's local interactions generate matching frictions and local herd immunity effects, which play a fundamental role in the infection dynamics. We also show that geographical factors affect how behavioral responses affect the epidemics. We derive relevant implications for estimating the effects of the epidemics and policy interventions that use panel data from several geographical units.
The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?
Authors: Anthony Strittmatter, Conny Wunsch
Date: 2021-02-18 00:00:00

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological improvements made possible by such big data affect estimates of the unexplained gender pay gap. We study the sensitivity of the estimates with regard to i) the availability of observationally comparable men and women, ii) model flexibility when controlling for wage determinants, and iii) the choice of different parametric and semi-parametric estimators, including variants that make use of machine learning methods. We find that these three factors matter greatly. Blinder-Oaxaca estimates of the unexplained gender pay gap decline by up to 39% when we enforce comparability between men and women and use a more flexible specification of the wage equation. Semi-parametric matching yields estimates that when compared with the Blinder-Oaxaca estimates, are up to 50% smaller and also less sensitive to the way wage determinants are included.
The Impact of Corona Populism: Empirical Evidence from Austria and Theory
Authors: Patrick Mellacher
Date: 2020-12-29 00:00:00
Tasks: Selection bias

I study the co-evolution between public opinion and party policy in situations of crises by investigating a policy U-turn of a major Austrian right-wing party (FPOE) during the Covid-19 pandemic. My analysis suggests the existence of both i) a "Downsian" effect, which causes voters to adapt their party preferences based on policy congruence and ii) a "party identification" effect, which causes partisans to realign their policy preferences based on "their" party's platform. Specifically, I use individual-level panel data to show that i) "corona skeptical" voters who did not vote for the FPOE in the pre-Covid-19 elections of 2019 were more likely to vote for the party after it embraced "corona populism", and ii) beliefs of respondents who declared that they voted for the FPOE in 2019 diverged from the rest of the population in three out of four health-dimensions only after the turn, causing them to underestimate the threat posed by Covid-19 compared to the rest of the population. Using aggregate-level panel data, I study whether the turn has produced significant behavioral differences which could be observed in terms of reported cases and deaths per capita. Paradoxically, after the turn the FPOE vote share is significantly positively correlated with deaths per capita, but not with the reported number of infections. I hypothesize that this due to a self-selection bias in testing, which causes a correlation between the number of "corona skeptics" and the share of unreported cases after the turn. I find empirical support for this hypothesis in individual-level data from a Covid-19 prevalence study that involves information about participants' true vs. reported infection status. I finally study a simple heterogeneous mixing epidemiological model and show that a testing bias can indeed explain the apparent paradox of an increase in deaths without an increase in reported cases.