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Social and Behavioral Sciences Commons™
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Articles 91 - 120 of 2930
Full-Text Articles in Social and Behavioral Sciences
Pipeline Vs. Choice: The Global Gender Gap In Stem Applications, Isaac Ahimbisibwe, Adam Altjmed, Georgy Artemov, Andres Barrios-Fernandez, Aspasia Bizopoulou, Martti Kaila, Jin-Tan Liu, Rigissa Megalokonomou, José Montalban, Christopher Neilson, Jintao Sun, Sebastian Otero, Xiaoyang Ye
Pipeline Vs. Choice: The Global Gender Gap In Stem Applications, Isaac Ahimbisibwe, Adam Altjmed, Georgy Artemov, Andres Barrios-Fernandez, Aspasia Bizopoulou, Martti Kaila, Jin-Tan Liu, Rigissa Megalokonomou, José Montalban, Christopher Neilson, Jintao Sun, Sebastian Otero, Xiaoyang Ye
Cowles Foundation Discussion Papers
Women account for only 35% of global STEM graduates, a share unchanged for a decade. We use administrative microdata from centralized university admissions in ten systems to deliver the first crossnational decomposition of the STEM gender gap into a pipeline gap (academic preparedness) and a choice gap (first-choice field conditional on eligibility). In deferred-acceptance platforms where eligibility is score-based, we isolate preferences from access. The pipeline gap varies widely, from -19 to +31 percentage points across education systems. By contrast, the choice gap is remarkably stable: high-scoring women are 25 percentage points less likely than men to rank STEM first.
Multidimensional Monotonicity And Economic Applications, Frank Yang, Kai Hao Yang
Multidimensional Monotonicity And Economic Applications, Frank Yang, Kai Hao Yang
Cowles Foundation Discussion Papers
We characterize the extreme points of multidimensional monotone functions from [0,1]n to [0,1], as well as the extreme points of the set of one-dimensional marginals of these functions. These characterizations lead to new results in various mechanism design and information design problems, including public good provision with interdependent values; interim efficient bilateral trade mechanisms; asymmetric reduced form auctions; and optimal private private information structure. As another application, we also present a mechanism anti-equivalence theorem for two-agent, two-alternative social choice problems: A mechanism is payoff-equivalent to a deterministic DIC mechanism if and only if they are ex-post equivalent.
Tariffs And Trade Deficits, Lorenzo Caliendo, Samuel Kortum, Fernando Parro
Tariffs And Trade Deficits, Lorenzo Caliendo, Samuel Kortum, Fernando Parro
Cowles Foundation Discussion Papers
We develop a dynamic multi-country Ricardian trade model with aggregate uncertainty, where trade imbalances emerge as countries exchange goods and assets. We introduce a method for computing counterfactuals in this setting, which doesn't require specifying the stochastic process of shocks or solving for asset prices. Applying the model to tariff shocks, we quantify their effects on prices, income, spending, and trade imbalances. We find that higher U.S. tariffs reduce the U.S. trade deficit through general equilibrium adjustments, but raise domestic prices and lower real consumption. Our findings highlight that movements in trade imbalances are shaped by the structure of global …
The Effect Of Education Policy On Crime: An Intergenerational Perspective, Ulrika Ahrsjö, Costas Meghir, Mårten Palme, Marieke Schnabel
The Effect Of Education Policy On Crime: An Intergenerational Perspective, Ulrika Ahrsjö, Costas Meghir, Mårten Palme, Marieke Schnabel
Cowles Foundation Discussion Papers
We examine the intergenerational effect of education policy on crime. Using administrative data that links outcomes across generations with crime records, we show that the Swedish comprehensive school reform, gradually implemented between 1949 and 1962, reduced conviction rates for both the generation directly affected by the reform and their sons. The reduction in conviction rates occurred in several types of crime. Mediation analysis suggests that key channels include increased parental educational attainment and household income, as well as reduced criminal behavior among fathers.
Decomposing Trends In The Gender Gap For Highly Educated Workers, Joseph G. Altonji, John Eric Humphries, Yagmur Yuksel, Ling Zhong
Decomposing Trends In The Gender Gap For Highly Educated Workers, Joseph G. Altonji, John Eric Humphries, Yagmur Yuksel, Ling Zhong
Cowles Foundation Discussion Papers
This paper examines the gender gap in log earnings among full-time, college-educated workers born between 1931 and 1984. Using data from the National Survey of College Graduates and other sources, we decompose the gender earnings gap across birth cohorts into three components: (i) gender differences in the relative returns to undergraduate and graduate fields, (ii) gender-specific trends in undergraduate field, graduate degree attainment, and graduate field, and (iii) a cohortspecific “residual component” that shifts the gender gap uniformly across all college graduates. We have three main findings. First, when holding the relative returns to fields constant, changes in fields of …
Offline Contextual Bandits In The Presence Of New Actions, Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura, Takanori Muroi, Yusuke Narita, Yuki Sasamoto, Kei Tateno, Takuma Udagawa, Yuta Saito
Offline Contextual Bandits In The Presence Of New Actions, Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura, Takanori Muroi, Yusuke Narita, Yuki Sasamoto, Kei Tateno, Takuma Udagawa, Yuta Saito
Cowles Foundation Discussion Papers
Automated decision-making algorithms drive applications in domains such as recommendation systems and search engines. These algorithms often rely on off-policy contextual bandits or off-policy learning (OPL). Conventionally, OPL selects actions that maximize the expected reward within an existing action set. However, in many real-world scenarios, actions—such as news articles or video content—change continuously, and the action space evolves over time compared to when the logged data was collected. We define actions introduced after deploying the logging policy as new actions and focus on the problem of OPL with new actions. Existing OPL methods cannot learn and select new actions because …
Order Statistics As Finite Mixtures, José-Antonio Espín-Sánchez, Charles Hodgson, Kevin O’Neill
Order Statistics As Finite Mixtures, José-Antonio Espín-Sánchez, Charles Hodgson, Kevin O’Neill
Cowles Foundation Discussion Papers
We propose a new way to obtain identification results using order statistics as finite mixtures with two key properties: i) the weights are known integer numbers; and ii) the elements of the mixture are the distributions of the maximum over a subset of the original random variables. We leverage Exponentiated Distributions (ED), which extend extreme value theory results. ED are max-stable, and we show that finite mixtures of ED are linearly independent. This enables us to derive non-parametric identification results and extend commonly known results using Gumbel and Fréchet distributions, both examples of ED. The results have broad applications in …
Cross Section Curve Autoregression: The Unit Root Case, Peter C.B. Phillips, Liang Jiang
Cross Section Curve Autoregression: The Unit Root Case, Peter C.B. Phillips, Liang Jiang
Cowles Foundation Discussion Papers
This paper is part of a joint study of parametric autoregression with cross section curve time series, focussing on unit root (UR) nonstationary curve data autoregression. The Hilbert space setting extends scalar UR and local UR models to accommodate high dimensional cross section dependent data under very general conditions. New limit theory is introduced that involves two parameter Gaussian processes that generalize the standard UR and local UR asymptotics. Bias expansions provide extensions of the well-known results in scalar autoregression and fixed effect dynamic panels to functional dynamic regressions. Semiparametric and ADF-type UR tests are developed with corresponding limit theory …
Selective Turnout, Voting Policy, And Partisan Bias: Evidence From Multi-Level Data, Steven T. Berry, Christian Cox, Philip A. Haile
Selective Turnout, Voting Policy, And Partisan Bias: Evidence From Multi-Level Data, Steven T. Berry, Christian Cox, Philip A. Haile
Cowles Foundation Discussion Papers
We study voting in general elections for the U.S. House of Representatives. Our data set includes demographics and turnout of all registered voters for the years 2016–2020, as well as vote shares at the precinct and contest level. We estimate a Downsian voting model incorporating rich observed and unobserved heterogeneity at the voter and contest level. We find that voters with high perceived voting costs tend to favor Democrats, as do marginal voters in most districts. Variation in state voting policies accounts for a modest share of overall estimated voting costs but is sufficient to determine the majority party in …
Outsourcing, Labor Market Frictions, And Employment, Mayara Felix, Michael B. Wong
Outsourcing, Labor Market Frictions, And Employment, Mayara Felix, Michael B. Wong
Cowles Foundation Discussion Papers
We estimate the labor market impacts of Brazil’s 1993 outsourcing legalization us-ing North-South variation in pre-legalization court permissiveness, and comparing security guards to less-affected occupations. We find that outsourcing legalization persistently reallocated jobs from older incumbent guards to younger entrants. Total employ-ment of guards and their entry from informality persistently increased, while average demographic-adjusted wages remained constant. Meanwhile, a wave of occupational layoffs displaced some incumbent guards from high-wage firms. The evidence suggests that the rise of non-core activity outsourcing reduced labor market frictions, facilitated by firm-level economies of scale in human resources and spillovers to non-adopting firms.
College Application Mistakes And The Design Of Information Policies At Scale, Tomás Larroucau, Ignacio A. Rios, Anaïs Fabre, Christopher Neilson
College Application Mistakes And The Design Of Information Policies At Scale, Tomás Larroucau, Ignacio A. Rios, Anaïs Fabre, Christopher Neilson
Cowles Foundation Discussion Papers
We examine whether large-scale information interventions can improve college application outcomes in a centralized admissions system. Using nationwide surveys from Chile, we document widespread information frictions and frequent application mistakes, such as omitting attainable preferred programs or failing to include safety options. To address these frictions, we partnered with the Ministry of Education to implement a large-scale field experiment that provided applicants with personalized information on admission probabilities and program characteristics through customized online platforms. The intervention increased the probability that previously unmatched students received an assignment by 44% and improved placement into higher-ranked programs by 20%. Building on these …
Optimal Management Of Public Energy Communities: Investment Strategies And Welfare Maximization, Dirk Bergemann, Marina Bertolini, Marta Castellini, Michele Moretto, Sergio Vergalli
Optimal Management Of Public Energy Communities: Investment Strategies And Welfare Maximization, Dirk Bergemann, Marina Bertolini, Marta Castellini, Michele Moretto, Sergio Vergalli
Cowles Foundation Discussion Papers
A municipality (social planner) is seeking to establish a renewable energy community paying the initial investment costs, while also identifying the optimal management framework. In this context, two distinct modes of governance are analyzed: the private and the public one. In the first case, a private (or profit) aggregator oversees the energy community with a monopolistic behavior, while in the other the aggregator is a public owned, or controlled, company following the social approach advocated by the promoter, i.e the municipality. In both scenarios, the effective functioning of the community requires the collection of private data on members’ energy consumption. …
Semiparametric Learning Of Integral Functionals On Submanifolds, Xiaohong Chen, Wayne Yuan Guo
Semiparametric Learning Of Integral Functionals On Submanifolds, Xiaohong Chen, Wayne Yuan Guo
Cowles Foundation Discussion Papers
This paper studies the semiparametric estimation and inference of integral functionals on submanifolds, which arise naturally in a variety of econometric settings. For linear integral functionals on a regular submanifold, we show that the semiparametric plugin estimator attains the minimax-optimal convergence rate n—s2s+d-m, where s is the Hölder smoothness order of the underlying nonparametric function, d is the dimension of the first-stage nonparametric estimation, m is the dimension of the submanifold over which the integral is taken. This rate coincides with the standard minimax-optimal rate for a (d − m)-dimensional nonparametric estimation problem, illustrating that integration over the …
Tariffs And Trade Deficits, Lorenzo Caliendo, Samuel Kortum, Fernando Parro
Tariffs And Trade Deficits, Lorenzo Caliendo, Samuel Kortum, Fernando Parro
Cowles Foundation Discussion Papers
This paper develops a complete-markets model to analyze the determinants of endogenous trade imbalances across countries. We introduce a framework where countries can trade in Arrow-Debreu securities to insure against different states of the world, which enables them to run deficits in some states and surpluses in others. The model allows for counterfactual analysis of various trade policy scenarios, such as unilateral tariff impositions. We derive the conditions under which trade deficits arise endogenously and discuss implications for welfare and trade policy analysis.
Selection In Surveys: Using Randomized Incentives To Detect And Account For Nonresponse Bias, Deniz Dutz, Ingrid Huitfeldt, Santiago Lacouture, Magne Mogstad, Alexander Torgovitsky, Winnie Van Dijk
Selection In Surveys: Using Randomized Incentives To Detect And Account For Nonresponse Bias, Deniz Dutz, Ingrid Huitfeldt, Santiago Lacouture, Magne Mogstad, Alexander Torgovitsky, Winnie Van Dijk
Cowles Foundation Discussion Papers
We show how to use randomized participation incentives to test and account for nonresponse bias in surveys. We first use data from a survey about labor market conditions, linked to full-population administrative data, to provide evidence of large differences in labor market outcomes between survey participants and nonparticipants, differences which would not be observable to an analyst who only has access to the survey data. These differences persist even after correcting for observable characteristics. We then use the randomized incentives in our survey to directly test for nonresponse bias, and find evidence of substantial bias. Next, we apply a range …
Non-Discriminatory Personalized Pricing, Philipp Strack, Kai Hao Yang
Non-Discriminatory Personalized Pricing, Philipp Strack, Kai Hao Yang
Cowles Foundation Discussion Papers
A monopolist offers personalized prices to consumers with unit demand. Consumers differ in their values, costs, and \emph{protected characteristics}---such as race or gender. The seller is subject to a non-discrimination constraint: consumers with the same cost, but different protected characteristics must face identical price distributions. Such regulations are present in markets like credit or insurance. We characterize the optimal pricing rule. Under this rule, surplus accrues to both protected groups, but only to those with intermediate values. Strengthening the constraint to cover transaction prices redistributes surplus, harming the low-value group and benefiting the high-value group. Meanwhile, prohibiting the use of …
Efficient Difference-In-Differences And Event Study Estimators, Xiaohong Chen, Pedro H. C. Sant’Anna, Haitian Xie
Efficient Difference-In-Differences And Event Study Estimators, Xiaohong Chen, Pedro H. C. Sant’Anna, Haitian Xie
Cowles Foundation Discussion Papers
This paper investigates efficient Difference-in-Differences (DiD) and Event Study (ES) estimation using short panel data sets within the heterogeneous treatment effect framework, free from parametric functional form assumptions and allowing for variation in treatment timing. We provide an equivalent characterization of the DiD potential outcome model using sequential conditional moment restrictions on observables, which shows that the DiD identification assumptions typically imply nonparametric overidentification restrictions. We derive the semiparametric efficient influence function (EIF) in closed form for DiD and ES causal parameters under commonly imposed parallel trends assumptions. The EIF is automatically Neyman orthogonal and yields the smallest variance among …
A Stairway To Success: How Parenting Shapes Culture And Social Stratification, Francesco Agostinelli, Matthias Doepke, Giuseppe Sorrenti, Fabrizio Zilibotti
A Stairway To Success: How Parenting Shapes Culture And Social Stratification, Francesco Agostinelli, Matthias Doepke, Giuseppe Sorrenti, Fabrizio Zilibotti
Cowles Foundation Discussion Papers
This chapter argues that parenting choices are a central force in the joint evolution of culture and economic outcomes. We present a framework in which parents-motivated by both their children’s future success and their own normative beliefs-choose parenting styles and transmit cultural traits responding to economic incentives. Values such as work ethic, patience, and religiosity are more likely to be instilled when their anticipated returns, economic or otherwise, are high. The interaction between parenting and economic conditions gives rise to endogenous cultural and economic stratification. We extend the model to include residential sorting and social interactions, showing how neighborhood choice …
Complementarities In High School And College Investments, John Eric Humphries, Juanna Schrøter Joensen, Gregory Veramendi
Complementarities In High School And College Investments, John Eric Humphries, Juanna Schrøter Joensen, Gregory Veramendi
Cowles Foundation Discussion Papers
This paper examines how high school specialization shapes college investment decisions and their subsequent returns through dynamic complementarities. Using Swedish administrative data, we estimate a dynamic Roy model that accounts for selection on multidimensional skills, family background, prior investments, and unobserved heterogeneity. We identify the model using rich skill measures and quasi-experimental variation in program popularity. For marginal students, STEM specialization in high school increases wages by 9%, with more than half this return attributed to dynamic complementarities that enhance the productivity of subsequent college investments. Consequently, we find that counterfactual policies encouraging high school STEM specialization generate twice the …
Scalable Targeting Of Social Protection: When Do Algorithms Out-Perform Surveys And Community Knowledge?, Emily Aiken, Anik Ashraf, Joshua E. Blumenstock, Raymond Guiteras, Ahmed Mushfiq Mobarak
Scalable Targeting Of Social Protection: When Do Algorithms Out-Perform Surveys And Community Knowledge?, Emily Aiken, Anik Ashraf, Joshua E. Blumenstock, Raymond Guiteras, Ahmed Mushfiq Mobarak
Cowles Foundation Discussion Papers
Innovations in big data and algorithms are enabling new approaches to target interventions at scale. We compare the accuracy of three different systems for identifying the poor to receive benefit transfers — proxy means-testing, nominations from community members, and an algorithmic approach using machine learning to predict poverty using mobile phone usage behavior — and study how their cost-effectiveness varies with the scale and scope of the program. We collect mobile phone records from all major telecom operators in Bangladesh and conduct community-based wealth rankings and detailed consumption surveys of 5,000 households, to select the 22,000 poorest households for $300 …
Quantile-Optimal Policy Learning Under Unmeasured Confounding, Zhongren Chen, Siyu Chen, Zhengling Qi, Xiaohong Chen, Zhuoran Yang
Quantile-Optimal Policy Learning Under Unmeasured Confounding, Zhongren Chen, Siyu Chen, Zhengling Qi, Xiaohong Chen, Zhuoran Yang
Cowles Foundation Discussion Papers
We study quantile-optimal policy learning where the goal is to find a policy whose reward distribution has the largest α-quantile for some α P p0, 1q. We focus on the offline setting whose generating process involves unobserved confounders. Such a problem suffers from three main challenges: (i) nonlinearity of the quantile objective as a functional of the reward distribution, (ii) unobserved confounding issue, and (iii) insufficient coverage of the offline dataset. To address these challenges, we propose a suite of causal-assisted policy learning methods that provably enjoy strong theoretical guarantees under mild conditions. In particular, to address (i) and (ii), …
The Price Of Intelligence: How Should Socially-Minded Firms Price And Deploy Ai?, Nils H. Lehr, Pascual Restrepo
The Price Of Intelligence: How Should Socially-Minded Firms Price And Deploy Ai?, Nils H. Lehr, Pascual Restrepo
Cowles Foundation Discussion Papers
Leading AI firms claim to prioritize social welfare. How should firms with a social mandate price and deploy AI? We derive pricing formulas that depart from profit maximization by incorporating incentives to enhance welfare and reduce labor disruptions. Using US data, we evaluate several scenarios. A welfarist firm that values both profit and welfare should price closer to marginal cost, as efficiency gains outweigh distributional concerns. A conservative firm focused on labormarket stability should price above the profit-maximizing level in the short run, especially when its AI may displace low-income workers. Overall, socially minded firms face a trade-off between expanding …
Trade And Domestic Distortions: The Case Of Informality, Rafael Dix-Carneiro, Pinelopi Goldberg, Costas Meghir, Gabriel Ulyssea
Trade And Domestic Distortions: The Case Of Informality, Rafael Dix-Carneiro, Pinelopi Goldberg, Costas Meghir, Gabriel Ulyssea
Cowles Foundation Discussion Papers
We examine the effects of international trade in the presence of a set of domestic distortions giving rise to informality, a prevalent phenomenon in developing countries. In our quantitative model, the informal sector arises from burdensome taxes and regulations that are imperfectly enforced by the government. In equilibrium, smaller, less productive firms face fewer distortions than larger, more productive ones, potentially leading to substantial misallocation. We show that in settings with a large informal sector, the gains from trade are significantly amplified, as reductions in trade barriers imply a reallocation of resources from initially less distorted to more distorted firms. …
Fatigue, Recovery, And The Economics Of Remote Work, María Sáez Martí
Fatigue, Recovery, And The Economics Of Remote Work, María Sáez Martí
Cowles Foundation Discussion Papers
I propose a model in which workers experience fatigue over time and can restore productivity by taking breaks. Optimal schedules feature evenly spaced, full-recovery breaks; when breaks are costless, they should occur frequently, but switching costs make the optimal number finite. The model is embedded in a principal-agent framework with contractual frictions. When employers control the schedule, workers overwork; when workers self-manage, they overrest. Both lead to inefficiencies. These results shed light on the trade-offs in remote work arrangements, especially following COVID-19. The analysis highlights how control rights, incentive design, and recovery constraints interact—and why neither rigid supervision nor full …
Revisiting The Lasting Impacts Of Incarceration, John Eric Humphries, Cécile Macaire, Aurélie Ouss, Megan Stevenson, Winnie Van Dijk
Revisiting The Lasting Impacts Of Incarceration, John Eric Humphries, Cécile Macaire, Aurélie Ouss, Megan Stevenson, Winnie Van Dijk
Cowles Foundation Discussion Papers
Using newly-linked administrative and commercial data from Virginia spanning 25 years, we study the consequences of incarceration. While previous research has examined labor market outcomes and recidivism, we focus on two of the primary channels through which low-income households build wealth: asset ownership (homes and cars) and human capital formation. To identify causal effects, we use a matched differencein-differences design. In line with much of the literature on the impact of incarceration in the U.S., we find no evidence of scarring effects on labor market outcomes or changes in recidivism beyond the incapacitation period. However, we find that incarceration leads …
A Dynamic Theory Of Optimal Tariffs, Eduardo Dávila, Andrés Rodríguez-Clare, Andreas Schaab, Stacy Yingqi Tan
A Dynamic Theory Of Optimal Tariffs, Eduardo Dávila, Andrés Rodríguez-Clare, Andreas Schaab, Stacy Yingqi Tan
Cowles Foundation Discussion Papers
The classic tariff formula states that the optimal unilateral tariff equals the inverse of the foreign export supply elasticity. We generalize this result and show that an intertemporal tariff formula characterizes the efficient tariff in a large class of dynamic heterogeneous agent (HA) economies with multiple goods. Intertemporal export supply elasticities and relative tariff revenue weights are sufficient statistics for the optimal tariff that decentralizes the efficient allocation. We also develop a general theory of second-best optimal tariffs. In dynamic HA incomplete markets economies, Ramsey optimal tariffs trade off intertemporal terms of trade manipulation against production efficiency, risk-sharing, and redistribution. …
Personalized Discounts And Consumer Search, Zikun Liu, Jiwoong Shin, Jidong Zhou
Personalized Discounts And Consumer Search, Zikun Liu, Jiwoong Shin, Jidong Zhou
Cowles Foundation Discussion Papers
The growing availability of big data enables firms to predict consumer search outcomes and outside options more accurately than consumers themselves. This paper examines how a firm can utilize such superior information to offer personalized buy-now discounts intended to deter consumer search. However, discounts can also serve as signals of attractive outside options, potentially encouraging rather than discouraging consumer search. We show that, despite the firm’s ability to tailor discounts across a continuum of consumer valuations, the firm-optimal equilibrium features a simple two-tier discount scheme, comprising a uniform positive discount when the consumer outside option is intermediate and no discount …
Cross Section Curve Data Autoregression, Peter C.B. Phillips, Liang Jiang
Cross Section Curve Data Autoregression, Peter C.B. Phillips, Liang Jiang
Cowles Foundation Discussion Papers
This paper develops and applies new asymptotic theory for estimation and inference in parametric autoregression with function valued cross section curve time series. The study provides a new approach to dynamic panel regression with high dimensional dependent cross section data. Here we deal with the stationary case and provide a full set of results extending those of standard Euclidean space autoregression, showing how function space curve cross section data raises efficiency and reduces bias in estimation and shortens confidence intervals in inference. Methods are developed for high-dimensional covariance kernel estimation that are useful for inference. The findings reveal that function …
Soft-Floor Auctions: Harnessing Regret To Improve Efficiency And Revenue, Dirk Bergemann, Kevin Breuer, Peter Cramton, Jack Hirsch, Yero S. Ndiaye, Axel Ockenfels
Soft-Floor Auctions: Harnessing Regret To Improve Efficiency And Revenue, Dirk Bergemann, Kevin Breuer, Peter Cramton, Jack Hirsch, Yero S. Ndiaye, Axel Ockenfels
Cowles Foundation Discussion Papers
A soft-floor auction asks bidders to accept an opening price to participate in an ascending auction. If no bidder accepts, lower bids are considered using first-price rules. Soft floors are common despite being irrelevant with standard assumptions. When bidders regret losing, soft-floor auctions are more efficient and profitable than standard optimal auctions. Revenue increases as bidders are inclined to accept the opening price to compete in a regret-free ascending auction. Efficiency is improved since having a soft floor allows for a lower hard reserve price, reducing the frequency of no sale. Theory and experiment confirm these motivations from practice.
A Geospatial Approach To Measuring Economic Activity, Anton Yang, Jianwei Ai, Costas Arkolakis
A Geospatial Approach To Measuring Economic Activity, Anton Yang, Jianwei Ai, Costas Arkolakis
Cowles Foundation Discussion Papers
We introduce a new methodology to detect and measure economic activity using geospatial data and apply it to steel production, a major industrial pollution source worldwide. Combining plant output data with geospatial data, such as ambient air pollutants, nighttime lights, and temperature, we train machine learning models to predict plant locations and output. We identify about 40% (70%) of plants missing from the training sample within a 1 km (5 km) radius and achieve R2 above 0.8 for output prediction at a 1 km grid and at the plant level, as well as for both regional and time series …