Abstract
We develop a stylized theoretical framework for the problem of dynamically tracking the population in a service system with noisy input and output observations. The motivation for the project is the problem of tracking the population of passengers in the TSA area at an airport in real time using the noisy data from people counters. In the airport, such real-time population tracking can be useful for several operational decisions. For example, when the number of passengers in the TSA area is large, the airport needs to deploy staff to manage the overflow from the designated queueing area. This use suggests an objective that detects when the queue becomes large. Other operational decisions, such as determining the number of security lanes to open or the number of officials to check IDs, rely on having an accurate estimate of the exact number of passengers in the TSA area. Our goal is to devise and analyze policies that use past people counter data to estimate the population in the system over a finite and discrete time horizon. We evaluate the performance of policies in two distinct settings, each involving a different objective.

​Fernando Bernstein is the William and Sue Gross Professor of Business​ ​Administration at the Fuqua School of Business, Duke University. He​ ​obtained a Ph.D. in Operations Management from the Graduate School of​ ​Business at Columbia University and joined Duke University in July 2000.​ ​Prof. Bernstein’s research interests include retail operations, supply chain​ ​management, production planning and inventory control, applications of game​ ​theory for​ ​production and distribution systems, and revenue management.​ He has published papers in leading journals such as Operations​ ​Research, Management Science and​ ​Manufacturing and Service Operations​ ​Management, and also serves as Associate Editor for​ ​these journals.

Abstract
This article relies on a large-scale field experiment in Mexico to measure the effects of two ability-grouping models (tracking and heterogeneous/bimodal groups) on student learning outcomes during middle school. Both strategies yielded an average learning gain of 0.08 of a standard deviation. We find larger and more persistent effects among initially high-achieving students and no significant effects among low achievers. Students in top tracking enjoyed multiple advantages, particularly a concentration of high-performing peers and a very homogeneous classroom, that facilitated the teacher’s work and increased students’ effort levels. Bimodal classes fostered greater effort levels among top students, while teachers induced less competition and allocated more time to practice and feedback activities, to the detriment of lecture time. Our results support the allocation of students to homogeneous classes to maximize performance gains among top students without hurting low achievers. Fostering inclusive learning among weaker students would require complementary investments under both models.

Verónica Frisancho es gerenta de Conocimiento de CAF, el Banco de Desarrollo de América Latina. Antes de unirse a CAF, trabajó por más de 10 años como economista líder en el Departamento de Investigación del Banco Interamericano de Desarrollo (BID). El trabajo de Verónica se puede describir mejor como microeconomía aplicada y su principal campo de especialización es la Economía del Desarrollo. Su investigación en estas áreas incluye un énfasis en educación, mercados laborales en países en desarrollo, género, inclusión y educación financiera. Verónica tiene un doctorado en Economía de la Pennsylvania State University y una licenciatura en Economía de la Universidad del Pacífico en Lima, Perú.

Abstract
This paper investigates the relationship between the incorporation of renewable energies and inflation. Energy price volatility is one of the main causes of inflation. The transmission of international energy price fluctuations to local inflation occurs mainly through electricity and fossil fuel prices. We use data from Latin America and the Caribbean (LAC), which exhibit significant spatial and temporal variations, to estimate the pass-through effects of international oil and natural gas prices on local prices and assess how renewable energy transition helps mitigate these effects. Our findings reveal that countries with a higher proportion of renewable energy in their energy matrix exhibit, on average, a lower pass-through effect from international energy prices to local prices, in contrast to countries with lower renewable energy generation. Therefore, this study proposes that the widespread adoption of renewable energies is an effective way to limit vulnerability to spikes in fossil fuel prices.

Magdalena Cornejo es profesora de la Escuela de Negocios de la UTDT e investigadora del CONICET. Su investigación se focaliza en la econometría de cambio climático, la modelación de precios de commodities, el análisis de series temporales y los métodos de pronóstico. Sus publicaciones recientes incluyen artículos publicados en Econometrics, International Journal of Forecasting, Agricultural Economics, entre otros. Dicta cursos de Estadística y Econometría tanto en grado como en posgrado.

Lunes 3 de abril

Elisabeth Kempf | Harvard Business School

"The Political Polarization of Corporate America"

Abstract
Executive teams in U.S. firms are becoming increasingly partisan. We establish this new fact using political affiliations from voter registration records for top executives of S&P 1500 firms between 2008 and 2020. The new fact is explained by both an increasing share of Republican executives and increased assortative matching by executives on political affiliation. Executives who are politically misaligned with the majority of the team are more likely to depart, especially in recent years, and their departures are more likely to be involuntary. Executives’ political views influence how they view the prospects of their companies as well as how stock prices respond to executive departures, suggesting that politically-motivated turnovers have real consequences.

Elisabeth Kempf is an Associate Professor in the Finance Unit at Harvard Business School. She is also a Faculty Research Fellow at the National Bureau of Economic Research (NBER) and a Research Affiliate at the Centre for Economic Policy and Research (CEPR). Her research interests lie at the intersection of political economy and empirical corporate finance.

Abstract
We show that the quality of police hires varies over the business cycle. Officers hired when the unemployment rate is high have fewer complaints, disciplines, and are less likely to be fired than officers hired when the unemployment rate is low. Effects are larger for younger workers who have weaker outside options in recessions. We find that the size and quality of the applicant pool increases in high unemployment years–more people take entry exams and a smaller fraction fail the exam. Our findings shed light on how outside options affect police hires and speak to policy questions about police recruitment.

Fernando Saltiel es profesor asistente de Economía en McGill University e investigador afiliado al Institute for the Study of Labor (IZA) y Duke University. Tiene un Ph.D. en Economía por la University of Maryland. Su investigación se centra en diversos temas de economía laboral, incluyendo la importancia de habilidades en el mercado laboral, el retorno a inversiones de capital humano y el proceso de desarrollo de habilidades. Sus trabajos han sido publicados en revistas académicas como Economic Journal, American Economic Journal: Economic Policy, Journal of Applied Econometrics, European Economic Review y Economics of Education Review, entre otros.