pwc-archive/papers-with-abstracts huggingface dataset:
Estimation of Tempered Stable Lévy Models of Infinite Variation
Authors: José E. Figueroa-López, Ruoting Gong, Yuchen Han
Date: 2021-01-03 00:00:00

We propose a new method for the estimation of a semiparametric tempered stable L\'{e}vy model. The estimation procedure combines iteratively an approximate semiparametric method of moment estimator, Truncated Realized Quadratic Variations (TRQV), and a newly found small-time high-order approximation for the optimal threshold of the TRQV of tempered stable processes. The method is tested via simulations to estimate the volatility and the Blumenthal-Getoor index of the generalized CGMY model as well as the integrated volatility of a Heston-type model with CGMY jumps. The method outperforms other efficient alternatives proposed in the literature when working with a L\'evy process (i.e., the volatility is constant), or when the index of jump intensity $Y$ is larger than $3/2$ in the presence of stochastic volatility.
COVID-19 spreading in financial networks: A semiparametric matrix regression model
Authors: Billio Monica, Casarin Roberto, Costola Michele, Iacopini Matteo
Date: 2021-01-02 00:00:00
Tasks: regression

Network models represent a useful tool to describe the complex set of financial relationships among heterogeneous firms in the system. In this paper, we propose a new semiparametric model for temporal multilayer causal networks with both intra- and inter-layer connectivity. A Bayesian model with a hierarchical mixture prior distribution is assumed to capture heterogeneity in the response of the network edges to a set of risk factors including the European COVID-19 cases. We measure the financial connectedness arising from the interactions between two layers defined by stock returns and volatilities. In the empirical analysis, we study the topology of the network before and after the spreading of the COVID-19 disease.
The Law of Large Numbers for Large Stable Matchings
Authors: Jacob Schwartz, Kyungchul Song
Date: 2021-01-02 00:00:00

In many empirical studies of a large two-sided matching market (such as in a college admissions problem), the researcher performs statistical inference under the assumption that they observe a random sample from a large matching market. In this paper, we consider a setting in which the researcher observes either all or a nontrivial fraction of outcomes from a stable matching. We establish a concentration inequality for empirical matching probabilities assuming strong correlation among the colleges' preferences while allowing students' preferences to be fully heterogeneous. Our concentration inequality yields laws of large numbers for the empirical matching probabilities and other statistics commonly used in empirical analyses of a large matching market. To illustrate the usefulness of our concentration inequality, we prove consistency for estimators of conditional matching probabilities and measures of positive assortative matching.
Breaking Ties: Regression Discontinuity Design Meets Market Design
Authors: Atila Abdulkadiroglu, Joshua D. Angrist, Yusuke Narita, Parag Pathak
Date: 2020-12-31 00:00:00
Tasks: Math, regression, Selection bias

Many schools in large urban districts have more applicants than seats. Centralized school assignment algorithms ration seats at over-subscribed schools using randomly assigned lottery numbers, non-lottery tie-breakers like test scores, or both. The New York City public high school match illustrates the latter, using test scores and other criteria to rank applicants at ``screened'' schools, combined with lottery tie-breaking at unscreened ``lottery'' schools. We show how to identify causal effects of school attendance in such settings. Our approach generalizes regression discontinuity methods to allow for multiple treatments and multiple running variables, some of which are randomly assigned. The key to this generalization is a local propensity score that quantifies the school assignment probabilities induced by lottery and non-lottery tie-breakers. The local propensity score is applied in an empirical assessment of the predictive value of New York City's school report cards. Schools that receive a high grade indeed improve SAT math scores and increase graduation rates, though by much less than OLS estimates suggest. Selection bias in OLS estimates is egregious for screened schools.
Bias correction for quantile regression estimators
Authors: Grigory Franguridi, Bulat Gafarov, Kaspar Wuthrich
Date: 2020-11-05 00:00:00
Tasks: quantile regression, regression

We study the bias of classical quantile regression and instrumental variable quantile regression estimators. While being asymptotically first-order unbiased, these estimators can have non-negligible second-order biases. We derive a higher-order stochastic expansion of these estimators using empirical process theory. Based on this expansion, we derive an explicit formula for the second-order bias and propose a feasible bias correction procedure that uses finite-difference estimators of the bias components. The proposed bias correction method performs well in simulations. We provide an empirical illustration using Engel's classical data on household food expenditure.
Bias-Aware Inference in Regularized Regression Models
Authors: Timothy B. Armstrong, Michal Kolesár, Soonwoo Kwon
Date: 2020-12-29 00:00:00
Tasks: regression

We consider inference on a scalar regression coefficient under a constraint on the magnitude of the control coefficients. A class of estimators based on a regularized propensity score regression is shown to exactly solve a tradeoff between worst-case bias and variance. We derive confidence intervals (CIs) based on these estimators that are bias-aware: they account for the possible bias of the estimator. Under homoskedastic Gaussian errors, these estimators and CIs are near-optimal in finite samples for MSE and CI length. We also provide conditions for asymptotic validity of the CI with unknown and possibly heteroskedastic error distribution, and derive novel optimal rates of convergence under high-dimensional asymptotics that allow the number of regressors to increase more quickly than the number of observations. Extensive simulations and an empirical application illustrate the performance of our methods.
Bayesian analysis of seasonally cointegrated VAR model
Authors: Justyna Wróblewska
Date: 2020-12-29 00:00:00
Tasks: model

The paper aims at developing the Bayesian seasonally cointegrated model for quarterly data. We propose the prior structure, derive the set of full conditional posterior distributions, and propose the sampling scheme. The identification of cointegrating spaces is obtained \emph{via} orthonormality restrictions imposed on vectors spanning them. In the case of annual frequency, the cointegrating vectors are complex, which should be taken into account when identifying them. The point estimation of the cointegrating spaces is also discussed. The presented methods are illustrated by a simulation experiment and are employed in the analysis of money and prices in the Polish economy.
How has labour market power evolved? Comparing labour market monopsony in Peru and the United States
Authors: Jorge Davalos, Ekkehard Ernst
Date: 2021-03-28 00:00:00

We document the evolution of labour market power by employers on the US and Peruvian labour markets during the 2010s. Making use of a structural estimation model of labour market dynamics, we estimate differences in market power that workers face depending on their sector of activity, their age, sex, location and educational level. In particular, we show that differences in cross-sectional market power are significant and higher than variations over the ten-year time span of our data. In contrast to findings of labour market power in developed countries such as the US, we document significant market power of employers in Peru vis-\`a-vis the tertiary educated workforce, regardless of age and sector. In contrast, for the primary educated workforce, market power seems to be high in (private) services and manufacturing. For secondary educated workers, only the mining sector stands out as moderately more monopsonistic than the rest of the labour market. We also show that at least for the 2010s, labour market power declined in Peru. We contrast these findings with similar estimates obtained for the United States where we are able to show that increases in labour market power are particularly acute in certain sectors, such as agriculture and entertainment and recreational services, as well as in specific geographic areas where these sectors are dominant. Moreover, we show that for the US, the labour market power has gradually increased over the past ten years, in line with the general rise in inequality. Importantly, we show that the pervasive gender pay gap cannot be linked to differential market power as men face higher labour market power than women. We also discuss possible reasons for these findings, including for the differences of labour market power across skill levels. Especially, we discuss the reasons for polarization of market power that are specific to sectors and locations.
Drivers of academic engagement in public-private research collaboration: an empirical study
Authors: Giovanni Abramo, Ciriaco Andrea D'Angelo
Date: 2021-03-27 00:00:00

University-industry research collaboration is one of the major research policy priorities of advanced economies. In this study, we try to identify the main drivers that could influence the propensity of academics to engage in research collaborations with the private sector, in order to better inform policies and initiatives to foster such collaborations. At this purpose, we apply an inferential model to a dataset of 32,792 Italian professors in order to analyze the relative impact of individual and contextual factors affecting the propensity of academics to engage in collaboration with industry, at overall level and across disciplines. The outcomes reveal that the typical profile of the professor collaborating with industry is a male under age 40, full professor, very high performer, with highly diversified research, and who has a certain tradition in collaborating with industry. This professor is likely to be part of a staff used to collaborating with industry, in a small university, typically a polytechnic, located in the north of the country.
Public-private research collaborations: longitudinal field-level analysis of determinants, frequency and impact
Authors: Giovanni Abramo, Francesca Apponi, Ciriaco Andrea D'Angelo
Date: 2021-03-27 00:00:00

This study on public-private research collaboration measures the variation over time of the propensity of academics to collaborate with colleagues from private companies. It also investigates the change in weights of the main drivers underlying the academics' propensity to collaborate, and whether the type profile of the collaborating academics changes. To do this, the study applies an inferential model on a dataset of professors working in Italian universities in consecutive periods, 2010-2013 and 2014-2017. The results, obtained at overall and field levels, support the formulation of policies aimed at fostering public-private research collaborations, and should be taken into account in post-assessment of their effectiveness.
Public transport users versus private vehicle users: differences about quality of service, satisfaction and attitudes toward public transport in Madrid (Spain)
Authors: Juan de Oña, Esperanza Estévez, Rocio de Oña
Date: 2021-03-26 00:00:00

This paper aims to further understand the main factors influencing the behavioural intentions (BI) of private vehicle users towards public transport to provide policymakers and public transport operators with the tools they need to attract more private vehicle users. As service quality, satisfaction and attitudes towards public transport are considered the main motivational forces behind the BI of public transport users, this research analyses 26 indicators frequently associated with these constructs for both public transport users and private vehicle users. Non-parametric tests and ordinal logit models have been applied to an online survey asked in Madrid's metropolitan area with a sample size of 1,025 respondents (525 regular public transport users and 500 regular private vehicle users). In order to achieve a comprehensive analysis and to deal with heterogeneity in perceptions, 338 models have been developed for the entire sample and for 12 users' segments. The results led to the identification of indicators with no significant differences between public transport and private vehicle users in any of the segments being considered (punctuality, information and low-income), as well as those that did show significant differences in all the segments (proximity, intermodality, save time and money, and lifestyle). The main differences between public transport and private vehicle users were found in the attitudes towards public transport and for certain user segments (residents in the city centre, males, young, with university qualification and with incomes above 2,700EUR/month). Findings from this study can be used to develop policies and recommendations for persuading more private vehicle users to use the public transport services.
Understanding the Paradox of Primary Health Care Use: Empirical Evidence from India
Authors: Pramod Kumar Sur
Date: 2021-03-25 00:00:00

I study households' primary health care usage in India, which presents a paradox. I examine why most households use fee-charging private health care services even though (1) most providers have no formal medical qualifications and (2) in markets where qualified doctors offer free care through public hospitals. I present evidence that this puzzling practice has deep historical routes. I examine India's coercive forced sterilization policy implemented between 1976 and 1977. Utilizing the unexpected timing of the policy, multiple measures of forced sterilization, including at a granular level, and an instrumental variable approach, I document that places heavily affected by the policy have lower public health care usage today. I also show that the instrument I use is unrelated to a battery of demographic, economic, or political aspects before the forced sterilization period. Finally, I explore the mechanism and document that supply-side factors do not explain these differences. Instead, I demonstrate that places with greater exposure to forced sterilization have higher confidence in private hospitals and doctors to provide good treatment.
Making it normal for new enrollments: Effect of institutional and pandemic influence on selecting an engineering institution under the COVID-19 pandemic situation
Authors: Prashant Mahajan, Vaishali Patil
Date: 2021-03-23 00:00:00

The COVID19 pandemic has forced Indian engineering institutions (EIs) to bring their previous half shut shades completely down. Fetching new admissions to EI campuses during the pandemic has become a now or never situation for EIs. During crisis situations, institutions have struggled to return to the normal track. The pandemic has drastically changed students behavior and family preferences due to mental stress and the emotional life attached to it. Consequently, it becomes a prerequisite, and emergencies need to examine the choice characteristics influencing the selection of EI during the COVID19 pandemic situation. The purpose of this study is to critically examine institutional influence and pandemic influence due to COVID19 that affects students choice about an engineering institution (EI) and consequently to explore relationships between institutional and pandemic influence. The findings of this quantitative research, conducted through a self-reported survey, have revealed that institutional and pandemic influence have governed EI choice under the COVID19 pandemic. Second, pandemic influence is positively affected by institutional influence. The study demonstrated that EIs will have to reposition themselves to normalize pandemic influence by tuning institutional characteristics that regulate situational influence and new enrollments. It can be yardstick for policy makers to attract new enrollments under pandemic situations.
Understanding Factors that Influence Upskilling
Authors: Eduardo Laguna-Muggenburg, Monica Bhole, Michael Meaney
Date: 2021-03-22 00:00:00

We investigate the motivation and means through which individuals expand their skill-set by analyzing a survey of applicants from the Facebook Jobs product. Individuals who report being influenced by their networks or local economy are over 29% more likely to have a postsecondary degree, but peer effects still exist among those who do not acknowledge such influences. Users with postsecondary degrees are more likely to upskill in general, by continuing coursework or applying to higher-skill jobs, though the latter is more common among users across all education backgrounds. These findings indicate that policies aimed at connecting individuals with different educational backgrounds can encourage upskilling. Policies that encourage users to enroll in coursework may not be as effective among individuals with a high school degree or less. Instead, connecting such individuals to opportunities that value skills acquired outside of a formal education, and allow for on-the-job training, may be more effective.
Mental Health and Abortions among Young Women: Time-varying Unobserved Heterogeneity, Health Behaviors, and Risky Decisions
Authors: Lena Janys, Bettina Siflinger
Date: 2021-03-22 00:00:00
Tasks: Attribute, Decision Making

In this paper, we provide causal evidence on abortions and risky health behaviors as determinants of mental health development among young women. Using administrative in- and outpatient records from Sweden, we apply a novel grouped fixed-effects estimator proposed by Bonhomme and Manresa (2015) to allow for time-varying unobserved heterogeneity. We show that the positive association obtained from standard estimators shrinks to zero once we control for grouped time-varying unobserved heterogeneity. We estimate the group-specific profiles of unobserved heterogeneity, which reflect differences in unobserved risk to be diagnosed with a mental health condition. We then analyze mental health development and risky health behaviors other than unwanted pregnancies across groups. Our results suggest that these are determined by the same type of unobserved heterogeneity, which we attribute to the same unobserved process of decision-making. We develop and estimate a theoretical model of risky choices and mental health, in which mental health disparity across groups is generated by different degrees of self-control problems. Our findings imply that mental health concerns cannot be used to justify restrictive abortion policies. Moreover, potential self-control problems should be targeted as early as possible to combat future mental health consequences.
The Shared Cost of Pursuing Shareholder Value
Authors: Michele Fioretti, Victor Saint-Jean, Simon C. Smith
Date: 2021-03-22 00:00:00

Using quasi-experimental variations from the media coverage of firms' Annual General Meetings (AGMs), we propose a portable framework to infer shareholders' preferences and influences on firms' prosocial decisions and apply it to covid-related donations, recent private sanctions on Russia, and firms' prosocial stances over 2011-21. Image gains drive shareholders synonymous with a firm, like closely-connected individuals, to support costly prosocial changes during AGM periods, while others, like financial corporations, oppose them. Influence supporting these changes lowers earnings by 3%: pursuing the values of (some) shareholders has distributional costs, which the monitoring of large shareholders motivated by heterogeneous preferences could prevent.
The Importance of Funding Space-Based Research
Authors: Devan Taylor
Date: 2021-03-03 00:00:00

When it comes to conversations about funding, the questions of whether the United States should be spending its resources on space-based research often rears its head. Opponents of the idea tend to share the opinion that the resources would be better spent helping citizens on the ground. With an estimated homeless population around 562,000 throughout the country, roughly 39.4 million Americans (12.3% of the population) living below the poverty level, and 63.1 million tons of food waste per year, it's hard to argue that the United States does not have its share of problems that need to be addressed. However, a history of space-based research has proven time and time again to bring forth advances in technology and scientific understanding that benefit humans across the globe and provide crucial protection for life on Earth.
Purchase history and product personalization
Authors: Laura Doval, Vasiliki Skreta
Date: 2021-03-21 00:00:00

Product personalization opens the door to price discrimination. A rich product line allows firms to better tailor products to consumers' tastes, but the mere choice of a product carries valuable information about consumers that can be leveraged for price discrimination. We study this trade-off in an upstream-downstream model, where a consumer buys a good of variable quality upstream, followed by an indivisible good downstream. The downstream firm's use of the consumer's purchase history for price discrimination introduces a novel distortion: The upstream firm offers a subset of the products that it would offer if, instead, it could jointly design its product line and downstream pricing. By controlling the degree of product personalization the upstream firm curbs ratcheting forces that result from the consumer facing downstream price discrimination.
Auctioning Annuities
Authors: Gaurab Aryal, Eduardo Fajnzylber, Maria F. Gabrielli, Manuel Willington
Date: 2020-11-05 00:00:00

We propose and estimate a model of demand and supply of annuities. To this end, we use rich data from Chile, where annuities are bought and sold in a private market via a two-stage process: first-price auctions followed by bargaining. We model firms with private information about costs and retirees with different mortalities and preferences for bequests and firms' risk ratings. We find substantial costs and preference heterogeneity, and because there are many firms, the market performs well. Counterfactuals show that simplifying the current mechanism with English auctions and "shutting down" risk ratings increase pensions, but only for high-savers.
Differentiation in a Two-Dimensional Market with Endogenous Sequential Entry
Authors: Jeffrey D. Michler, Benjamin M. Gramig
Date: 2021-03-19 00:00:00
Tasks: Vocal Bursts Valence Prediction

Previous research on two-dimensional extensions of Hotelling's location game has argued that spatial competition leads to maximum differentiation in one dimensions and minimum differentiation in the other dimension. We expand on existing models to allow for endogenous entry into the market. We find that competition may lead to the min/max finding of previous work but also may lead to maximum differentiation in both dimensions. The critical issue in determining the degree of differentiation is if existing firms are seeking to deter entry of a new firm or to maximizing profits within an existing, stable market.
Risk, Agricultural Production, and Weather Index Insurance in Village India
Authors: Jeffrey D. Michler, Frederi G. Viens, Gerald E. Shively
Date: 2021-03-19 00:00:00

We investigate the sources of variability in agricultural production and their relative importance in the context of weather index insurance for smallholder farmers in India. Using parcel-level panel data, multilevel modeling, and Bayesian methods we measure how large a role seasonal variation in weather plays in explaining yield variance. Seasonal variation in weather accounts for 19-20 percent of total variance in crop yields. Motivated by this result, we derive pricing and payout schedules for actuarially fair index insurance. These calculations shed light on the low uptake rates of index insurance and provide direction for designing more suitable index insurance.