Seminarios de Negocios 2019

El propósito del seminario es convertirse en el lugar donde presentar nuevas investigaciones así como también ser un foro para aumentar el conocimiento mutuo entre los miembros del profesorado. Planeamos 1 hora de exposición, seguido por 30 minutos de preguntas y de una discusión más informal.

                  Tel.: (+54 9 11) 5169 7301

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Viernes 8 de noviembre | Lounge 5, 4° piso
Santiago Gallino

Customer Supercharging in Experience-Centric Channels

Abstract
We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and test our thesis using data from a digital-first men’s apparel retailer and a pioneer of the so-called “Zero Inventory Store” (ZIS) format — a small footprint, experience-centric retail location which carries no inventory for immediate fulfillment, but fullfils orders via e-commerce. Using a risk-set matching approach, we calibrate our estimates on customers who are “treated”, i.e., have a ZIS experience, and matched with identical customers who shop online only. We find that post the ZIS experience, customers spend more, shop at a higher velocity, and are less likely to return items. Implications for retailing practice, including for legacy, offline-first retailers, are discussed.

Santiago Gallino
Assistant Professor at OID Departament, Wharton Business School. He is interested in operations management challenges in the retail industry. He studies both omni-channel integration and store execution issues in retail. In his research, he uses field data and econometric tools to study existing operational practices as well as potential operational improvements. Santiago holds a PhD in Operations and Information Management and a Master’s in Statistics from the University of Pennsylvania where he was a Fulbright Scholar, an MBA from IAE Business School, and a degree in Electrical Engineering from Universidad de Buenos Aires.


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Viernes 18 de octubre | Sala principal 3° piso
Rodrigo Soares

Down the River: Glyphosate Use in Agriculture and Birth Outcomes of Surrounding Populations

Abstract
This paper documents an externality from the agricultural use of the most popular herbicide in the world — glyphosate — on birth outcomes of surrounding populations. Our empirical strategy explores the initial regulation of genetically modified seeds in Brazil, the potential gains in productivity from adoption of genetically modified soybean, and the fact that glyphosate was strongly complementary to the first generation of genetically modified soybean seeds introduced in the country. We focus on the identification of the subclinical effects through contamination of water for populations distant from the original locations of use. Our strategy relies heavily on the direction of water flow within water basins to achieve identification. We detect a statistically significant deterioration in birth outcomes for populations receiving water from locations that expanded glyphosate use. Despite ongoing controversy, little is known about the externalities of herbicides in general on human populations at large. We provide evidence on this type of externality for the case of glyphosate contamination through water.

Rodrigo Soares
Ph.D. in Economics, University of Chicago. Lemann Professor of Brazilian Public Policy and International and Public Affairs and Affiliated Professor of Economics at Columbia University. His research centers on development economics, ranging from health and demographic economics, to crime, labor economics, and history and institutions. His work has appeared in various scientific journals, including American Economic Review, Journal of Political Economy, American Economic Journal: Applied Economics, Journal of Public Economics, and Journal of Development Economics, among various others.


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Viernes 29 de agosto | Sala principal 3° piso
Ricardo Montoya

A hidden Markov model to detect on-shelf out-of-stocks

Abstract
We propose a hidden Markov model (HMM) approach to identifying on-shelf out-of-stock (OOS) by detecting changes in sales patterns resulting from unobserved states of the shelf. We calibrate our model using point-of-sale (POS) data from a big-box retailer. We validate our approach using visual inspections that monitor the state of the shelf and compare them to the HMM’s predictions. We test the proposed approach on 14 products and 10 stores. We specify our model using a hierarchical Bayes approach and use a Monte Carlo–Markov chain methodology to estimate the model parameters. We identify three latent states in which one of them characterizes an OOS state. The results show that the proposed approach performs well in predicting out-of-stocks, combining high detection power (63.48%) and low false alerts (15.52%). Interestingly, the highest power of detection is obtained for medium-incidence products (77.42%), whereas the lowest false alarm rate is obtained for lower-incidence products (7.32%). Our HMM approach outperforms several benchmarks, particularly for lower-incidence products, which are not typically monitored using visual inspections. Using only POS data, our method uncovers useful information that provides actionable metrics that managers can use to evaluate the quality of demand forecasting and product replenishment at the store–product level.

Ricardo Montoya
Associate Professor of Industrial Engineering at the Universidad de Chile. He received his Ph.D. in Marketing from Columbia University and his Master in Operations Management and Industrial Engineering degrees from Universidad de Chile. His research focuses on modeling and estimating consumer preferences, dynamic choice models, and optimal product design. His work has been published in top management science journals, such as Marketing Science, Management Science, Operations Research, Quantitative Marketing and Economics, Manufacturing and Service Operations Management, and the European Journal of Operational Research, and his research supported with grants from Conicyt and Institute Millennium in Chile and Columbia University in USA.


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Viernes 8 de agosto | Lounge 4, 4° piso
Rocío Titiunik

Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs

Abstract
Regression discontinuity (RD) designs are viewed as one of the most credible identification strategies for program evaluation and causal inference. However, RD treatment effect estimands are necessarily local, making statistical methods for the extrapolation of these effects a key area for development. We introduce a new method for extrapolation of RD effects that relies on the presence of multiple cutoffs, and is therefore design-based. Our approach relies on an easy-to-interpret identifying assumption that mimics the idea of “common trends” in differences-in-differences designs. We use our methods to study the effect of a subsidized loan program on post-education attendance in Colombia, and offer new empirical evidence on the program effects for students with test scores away from the cutoff that determined program eligibility.

Rocío Titiunik
Professor of Politics at Princeton University. She specializes in quantitative methodology for the social sciences, with emphasis on quasi-experimental methods for causal inference and political methodology. Her research interests lie at the intersection of political science, political economy, and applied statistics, particularly on the development and application of quantitative methods to the study of political institutions. Her recent methodological research includes the development of statistical methods for causal inference and program evaluation, with emphasis on regression discontinuity (RD) designs. Her recent substantive research centers on democratic accountability and the role of party systems in developing democracies. Rocio’s work appeared in various journals in the social sciences and statistics, including the American Political Science Review, the American Journal of Political Science, the Journal of Politics, Econometrica, the Journal of the American Statistical Association, and the Journal of the Royal Statistical Society.


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Viernes 2 de agosto | Sala principal 3° piso
Matías Cattaneo

On Binscatter

Abstract
Binscatter is very popular in applied microeconomics. It provides a flexible, yet parsimonious way of visualizing and summarizing large data sets in regression settings, and it is often used for informal evaluation of substantive hypotheses such as linearity or monotonicity of the regression function. This paper presents a foundational, thorough analysis of binscatter: we give an array of theoretical and practical results that aid both in understanding current practices (i.e., their validity or lack thereof) and in offering theory-based guidance for future applications. Our main results include principled number of bins selection, confidence intervals and bands, hypothesis tests for parametric and shape restrictions of the regression function, and several other new methods, applicable to canonical binscatter as well as higher-order polynomial, covariate-adjusted and smoothness-restricted extensions thereof. In particular, we highlight important methodological problems related to covariate adjustment methods used in current practice. We also discuss extensions to clustered data. Our results are illustrated with simulated and real data throughout. Companion general-purpose software packages for Stata and R are provided. Finally, from a technical perspective, new theoretical results for partitioning-based series estimation are obtained that may be of independent interest.

Matías D. Cattaneo 
Professor of Operations Research and Financial Engineering (ORFE) at Princeton University. His research spans over mathematical statistics, econometrics, data science, and quantitative methods in the social, behavioral and biomedical sciences, with particular interest in program evaluation and causal inference. He currently serves in the editorial boards of the Journal of the American Statistical Association, Econometrica, Operations Research, the Review of Economics and Statistics, Journal of Business & Economic Statistics, Econometric Theory, the Econometrics Journal, and the Journal of Causal Inference.


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Viernes 5 de julio | Sala principal 3° piso
Jonah Rockoff

Value-added and the Long-Term Impacts of Teachers

Abstract
Are teachers’ impacts on students’ test scores (“value-added”) a good measure of their quality? This question has sparked debate because of disagreement about (1) whether value-added (VA) provides unbiased estimates of teachers’ impacts on student achievement and (2) whether high-VA teachers improve students’ long-term outcomes. I present the results from published research analyzing school district data from grades 3-8 for 2.5 million children linked to tax records on parent characteristics and adult outcomes. First we test for, and find little evidence of, bias in VA estimates. Then we show that students assigned to high-VA teachers have better outcomes in a variety of ways, such as being more likely to attend college and earning higher salaries. We estimate that replacing a teacher whose VA is in the bottom 5% with an average teacher would increase the present value of students’ lifetime income by more than $250,000 for the average classroom in our sample. Additionally, I discuss recent findings regarding other measures and dimensions of teacher quality and their relationship with students’ long-term outcomes.

Jonah E. Rockoff
Professor of Economics at the Columbia Graduate School of Business and a Research Associate at the National Bureau of Economic Research. Professor Rockoff’s interests center on the finance and management of public schools. He received his Ph.D. in Economics from Harvard University and a B.A. in Economics from Amherst College.


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Viernes 21 de junio | Sala principal 3° piso
Ernesto Schargrodsky

El efecto de la campaña de propaganda durante el balotaje argentino de 2015

Abstract
We study a propaganda campaign sponsored by the government against the main political challenger in the days preceding the 2015 Argentine presidential ballotage. Subjects in the treatment group watched an “ad” initially aired during soccer transmissions that was part of this campaign and were then asked about their political views. Relative to subjects in the control group, their declared preference for the challenger drops by 6.5 percentage points. We find no effects of the three types of defenses employed by the challenger (a positive message unrelated to the “ad”, an answer to the accusations in the “ad”, and a counter-attack). The propaganda effect is mainly driven by women.

Ernesto Schargrodsky
Ph.D. in Economics, Harvard University. Fue rector de UTDT, previamente decano de la Escuela de Negocios, profesor visitante en Stanford e investigador visitante en Harvard. Sus estudios analizan el efecto del otorgamiento de títulos de propiedad de la tierra en áreas marginales, el impacto de la presencia policial sobre el crimen, el efecto de la utilización de sistemas de monitoreo electrónico de detenidos sobre la reincidencia criminal, el efecto de la privatización de las empresas de agua sobre la mortalidad infantil, el análisis del apoyo a las privatizaciones en la opinión pública, el impacto del servicio militar obligatorio sobre el delito y la relación entre salarios de los funcionarios públicos y la corrupción. Sus trabajos han sido publicados en American Economic Review, Journal of Political Economy, Quarterly Journal of Economics, American Economic Journal, Journal of Law and Economics, entre otros.


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Viernes 3 de mayo | Sala principal 3° piso
Lucas J. Pujol-Cols

Factores disposicionales y situacionales en el trabajo: validación de escalas y análisis de sus influencias sobre la satisfacción laboral

Abstract 
Este artículo persigue tres objetivos. En primer lugar, examina las propiedades psicométricas de las versiones en español de la Escala de Autoevaluaciones Esenciales (i.e., Core Self-Evaluations Scale, CSES) y el Índice Breve de Satisfacción Laboral Afectiva (i.e., Brief Index of Affective Job Satisfaction, BIAJS) en términos de consistencia interna, estructura factorial, validez convergente, validez discriminante y validez empírica. En segundo lugar, analiza y compara la influencia relativa de un conjunto de factores disposicionales (i.e., autoevaluaciones esenciales, CSE) y situacionales (i.e., factores psicosociales del trabajo, FPST) sobre la satisfacción laboral. En tercer lugar, examina los efectos indirectos (i.e., mediados) de ambos conjuntos de determinantes sobre la satisfacción laboral a través del contraste de modelos alternativos de ecuaciones estructurales. A tales fines, se recolectan y analizan datos provenientes de dos muestras independientes de profesionales argentinos pertenecientes a ocupaciones altamente demandantes (209 académicos y 116 directivos de nivel medio y alto). Los resultados revelan que ambas escalas presentan propiedades psicométricas satisfactorias y consistentes con las reportadas en contextos laborales no hispano-parlantes, lo que brinda evidencia sobre la universalidad y validez transcultural de los constructos involucrados. Por otro lado, los análisis de regresiones múltiples demuestran que tanto las CSE como dos de los FPST, i.e. la autonomía y la estima, se relacionan significativamente con la satisfacción laboral. Más aún, los resultados de los análisis de ecuaciones estructurales muestran que aquellos empleados con CSE más elevadas tienden a percibir las características de su trabajo de manera más favorable (i.e., menor exposición percibida a riesgos psicosociales), lo que los vuelve más proclives a experimentar mayores niveles de satisfacción laboral. Estos hallazgos aportan evidencia al controversial debate individuo-situación y demuestran que la inclusión simultánea tanto de factores situacionales como disposicionales (i.e., perspectiva interaccionista) resulta fundamental en futuras investigaciones que examinen la satisfacción laboral. Se discuten las implicancias de este estudio para la práctica profesional y se proponen líneas futuras de investigación. 

Lucas J. Pujol-Cols 
Es doctor en Administración, MBA, especialista en Docencia Universitaria, investigador de posdoctorado en CONICET, investigador asociado en la Universidad Católica del Maule (Talca, Chile), profesor de Metodología de la Investigación, Métodos Cuantitativos y Taller de Tesis en el MBA de la Facultad de Ciencias Económicas y Sociales de la U. Nacional de Mar del Plata, referato externo en Academia: Revista Latinoamericana de Administración (Colombia), integrante del Grupo de Investigaciones en Administración (Facultad de Ciencias Económicas, U. Nacional de Mar del Plata) y del Grupo de Investigación en Psicología Laboral (Facultad de Psicología, U. Nacional de Mar del Plata), colaborador externo del proyecto Anillos SOC180040 – Conicyt Chile (2019-2021).


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Viernes 8 de marzo | Sala principal, 3er piso
Andrés Gago

Costos de Confrontación en Negociaciones

Abstract
In negotiations the objectives of parties are generally in conflict. Facing this conflict can trigger negative emotions: A sentiment of nervousness, embarrassment or awkwardness. In this paper, by means of a lab experiment, I explore the existence and implications of these confrontation costs. First, I show that a significant proportion of participants avoid bargaining even when it delivers higher payoffs. I find that the avoidance rate is 50% higher in face-to-face negotiations relative to electronic negotiations. This offsets a higher rate of agreements conditional on bargaining, making the unconditional probability of agreement equal across communication channels. Second, after shutting down alternative channels, I attribute the decrease in bargaining propensity to an increase in confrontation costs. Both things together make e-negotiations welfare improving in my design, casting doubts on the general belief that face-to-face communication increases efficiency by fostering transactions. Finally, consistent with previous literature, I observe that women haggle less than men, and I find that confrontation costs are a reason to explain it.

Andrés Gago
Ph.D. Candidate in Economics, CEMFI.


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Jueves 28 de febrero | Sala principal, 3er piso
Franco Esteban Cattaneo

Competencia downstream y comercialización exclusiva

Abstract
I empirically investigate the role of downstream competition in the use of exclusive dealing and quantify its effects in the formation of the car retailing networks. I estimate a model where exclusivity impacts both supply and demand, and dealers choose which brand to offer in a strategic manner. These choices frame product and brand availability in the market and the retail networks for manufacturers. In my model, dealers have incentives to add more brands in order to sell a wider set of products, but their interest to differentiate from local rivals limits this option. Moreover, manufacturers could raise costs anticompetitively to deter dealers from selling products of rival brands. I analyze the potential for this foreclosing channel by estimating fixed cost differences between exclusive and non-exclusive stores using moment inequalities. I find that multi-dealing has an average cost advantage between 10,000 and 620,000 euros. These numbers indicate that downstream competition, instead of anticompetitive motives, explains a more substantial part of the prevalence of exclusive dealing in the market.

Franco Esteban Cattaneo
Ph. D. candidate in Economics, University of Mannheim.