The Health Impacts of Coal-Fired Power Plants in India and the Co-benefits of Greenhouse Gas Reductions

By Maureen Cropper, Ryna Cui, Sarath Guttikunda, Nate Hultman, Puja Jawahar, Yongjoon Park, Xinlu Yao, and Xiaopeng Song

AEA Papers and Proceedings, May 2021

Under the Paris Agreement, India has pledged that 40 percent of its electricity generating capacity will come from non-fossil-fuel sources by the year 2030; however, this pledge does not limit total coal-fired generating capacity. As of 2019, planned incr...

Inference for Support Vector Regression under ℓ₁ Regularization

By Yuehao Bai, Hung Ho, Guillaume A. Pouliot, and Joshua Shea

AEA Papers and Proceedings, May 2021

We provide large-sample distribution theory for support vector regression (SVR) with ℓ1-norm along with error bars for the SVR regression coefficients. Although a classical Wald confidence interval obtains from our theory, its implementation ...

The Proximal Bootstrap for Finite-Dimensional Regularized Estimators

By Jessie Li

AEA Papers and Proceedings, May 2021

We propose a proximal bootstrap that can consistently estimate the limiting distribution of √n consistent estimators with nonstandard asymptotic distributions in a computationally efficient manner by formulating the proximal bootstrap estimator as the s...

Adversarial Inference Is Efficient

By Tetsuya Kaji, Elena Manresa, and Guillaume A. Pouliot

AEA Papers and Proceedings, May 2021

We study properties of the adversarial framework, introduced in Kaji, Manresa and Pouliot (2020). We show that the adversarial inference with an oracle classifier is statistically efficient. In addition, we study the finite sample properties of the advers...

Estimation and Inference by Stochastic Optimization: Three Examples

By Jean-Jacques Forneron and Serena Ng

AEA Papers and Proceedings, May 2021

This paper illustrates two algorithms designed in Forneron and Ng (2020): the resampled Newton-Raphson (rNR) and resampled quasi-Newton (rQN) algorithms, which speed up estimation and bootstrap inference for structural models. An empirical application to ...

Union Reform, Performance Pay, and New Teacher Supply: Evidence from Wisconsin's Act 10

By E. Jason Baron

AEA Papers and Proceedings, May 2021

This study examines the impact of performance pay on teacher selection. I exploit a shift toward performance pay in Wisconsin induced by the enactment of Act 10, which gave school districts autonomy to redesign their compensation schemes. Following the la...

School Capital Expenditure Rules and Distribution

By Barbara Biasi, Julien Lafortune, and David Schönholzer

AEA Papers and Proceedings, May 2021

We provide descriptive evidence on the level and within-state distribution of school capital expenditures over the past two decades. We relate these to the fiscal institutions governing capital funding across states. Within-state differences in capital ex...

Test-Based Accountability and the Effectiveness of School Finance Reforms

By Christian Buerger, Seung Hyeong Lee, and John D. Singleton

AEA Papers and Proceedings, May 2021

A recent literature provides new evidence that school resources are important for student outcomes. This paper examines whether school accountability systems that incentivize performance (such as No Child Left Behind) raise the efficiency with which addit...

The Common Application and Student Choice

By Brian Knight and Nathan Schiff

AEA Papers and Proceedings, May 2021

We study the effects of the Common Application (CA) platform, which allows students to submit a single application to multiple institutions, on student choice. Using individual-level data from freshman surveys over the period 1982–2014, we develop two p...

Microcommitments: The Effect of Small Commitments on Student Success

By Amanda J. Felkey, Eva Dziadula, Eric P. Chiang, and Jose Vazquez

AEA Papers and Proceedings, May 2021

We conducted a randomized control trial with nearly 1,000 students to test whether using a text-message-based tool that provides small commitments with social accountability helps students procrastinate less and maintain engagement with course material, y...

Identifying Students at Risk Using a New Math Skills Assessment

By George Orlov, Douglas McKee, Irene R. Foster, Daria Bottan, and Stephanie R. Thomas

AEA Papers and Proceedings, May 2021

Math skills are critical for success in economics courses. However, instructors often lack information about the level and extent of their students' underpreparedness in mathematics. In this paper, we describe the development of two new assessments of mat...

Grade Sensitivity and the Economics Major at a Women's College

By Patrick J. McEwan, Sheridan Rogers, and Akila Weerapana

AEA Papers and Proceedings, May 2021

We use a regression discontinuity design to estimate the causal effect of letter grades in introductory courses on the probability of choosing an economics major at Wellesley College, a highly selective women's college. We find that women just above lette...

Minimum Grade Requirements for Economics Majors: Effects on Enrollments and Student Learning

By Stephen J. Schmidt

AEA Papers and Proceedings, May 2021

This paper studies one college's policy requiring minimum grades in core courses for completion of the economics major. The policy reduced majors by approximately 6 percent. Grades of C- and D (requiring students to retake the course) dropped substantiall...

Measuring the Impact of COVID-19 on Businesses and People: Lessons from the Census Bureau's Experience

By Catherine Buffington, Jason Fields, and Lucia Foster

AEA Papers and Proceedings, May 2021

We provide an overview of Census Bureau activities to enhance the consistency, timeliness, and relevance of our data products in response to the COVID-19 pandemic. We highlight new data products designed to provide timely and granular information on the p...

Maintaining and Enhancing Labor Statistics during the COVID-19 Pandemic

By William W. Beach

AEA Papers and Proceedings, May 2021

The US Bureau of Labor Statistics (BLS) continued to produce key employment statistics while reengineering operations as a result of the COVID-19 pandemic. In-person data collection moved to electronic, deadlines were adjusted, and flexibilities were impl...

Measuring Consumer Spending Using Card Transaction Data: Lessons from the COVID-19 Pandemic

By Abe Dunn, Kyle Hood, Andrea Batch, and Alex Driessen

AEA Papers and Proceedings, May 2021

Pandemic-driven economic changes are measurable in days and weeks rather than months and years, underscoring a need for more timely economic data to inform the public. We summarize newly available estimates of spending using card transaction data that are...

High-Frequency Data and a Weekly Economic Index during the Pandemic

By Daniel J. Lewis, Karel Mertens, James H. Stock, and Mihir Trivedi

AEA Papers and Proceedings, May 2021

This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI, with its ten component series, tracks the overal...

Arrow Meets Hotelling: Modeling Spatial Innovation

By Steven Callander, Nicolas Lambert, and Niko Matouschek

AEA Papers and Proceedings, May 2021

We combine a spatial model of innovation with Hotelling's model of competition. Innovations are vertically and also horizontally differentiated. Potential innovators choose not only whether to innovate but also how to innovate. The bolder they are with a ...

Learning and Corruption on Monitoring Chains

By Bruno Strulovici

AEA Papers and Proceedings, May 2021

"But who will guard the guardians?" I revisit this age-old question under the following assumptions: (i) guardians are devoid of ethical motives and have quasilinear preferences, (ii) guardians monitor one another through a monitoring chain, and (iii) any...

Constrained Retrospective Search

By Can Urgun and Leeat Yariv

AEA Papers and Proceedings, May 2021

The search for good outcomes—be it government policies, technological breakthroughs, or lasting purchases—takes time and effort. At times, the decision process is unconstrained: an individual seeking a well-priced product determines her search scope a...