Andrea Canales
Volume 82, 2024, 101358
Andrea Canales
Volume 119, 2024, 102990
Andrea Canales
Volume 100, 2023, 102805
Andrea Canales
Volume 117, 2023, 102138
Luca Flabbi, Mauricio M. Tejada
Volume 231, October 2023, 111278
María Paola Sevilla, Paola Bordón and Fernanda Ramirez-Espinoza.
Volume 95, August 2023, 102428
We study the cyclicality of online posted wages at the job level, using a representative dataset for the Chilean economy. Unlike other datasets, ours has wage and requirements for most job ads. We find clear evidence of posted wage procyclicality, in line with matched employer-employee studies. Our results are robust to cyclical mismatch and job upgrading biases, important issues in the literature. We also show that not controlling for requirements leads to the underestimation of the cyclicality of offered wages. Indeed, using the Gelbach (2016) decomposition, we show that ignoring countercyclical experience and education requirements dampens wage cyclicality estimates.
Damian Clarke, Nicolás Paris, Benjamín Villena-Roldán
We demonstrate that regression models can be estimated by working independently in a row-wise fashion. We document a simple procedure which allows for a wide class of econometric estimators to be implemented cumulatively, where, in the limit, estimators can be produced without ever storing more than a single line of data in a computer’s memory. This result is useful in understanding the mechanics of many common regression models. These procedures can be used to speed up the computation of estimates computed via OLS, IV, Ridge regression, LASSO, Elastic Net, and Non-linear models including probit and logit, with all common modes of inference. This has implications for estimation and inference with `big data’, where memory constraints may imply that working with all data at once is particularly costly. We additionally show that even with moderately sized datasets, this method can reduce computation time compared with traditional estimation routines.
Mauricio Tejada y Luca Flabbi analizan el impacto de la exclusión financiera sobre el trabajador informal.
Andrea Canales y Paola Bordón están estudiando las diferencias de género en graduación/deserción de carreras universitarias STEM (ciencia, tecnología, ingeniería y matemáticas).
Benjamín Villena, junto con el investigador Sekyu Choi de la Universidad de Bristol, están estudiando las diferencias de género en las preferencias sobre trabajos.
Marcela Perticará and Mauricio Tejada. Journal of Economic Inequality.
July, 2021
Mauricio Bucca, Kim A. Weeden, Youngjoo Cha
The Russell Sage Foundation Journal of the Social Sciences, Volume 2, Number 4, August 2016, pp. 71-102 (Article)
Mario D. Molina, Mauricio Bucca, Michael W. Macy
American Association for the Advancement of Science, 2375-2548
July 17, 2019
Lucas Navarro, Mauricio M. Tejada; Review of Economic Dynamics Volume 43
January 2022, Pages 168-196
Felipe Balmaceda; Economics of Education Review
Volume 84, October 2021, 102165
Mauricio Tejada, Claudia Piras, Luca Flabbi, Monserrat Bustelo
February 5, 2021
Felipe Balmaceda; Journal of Economic Theory
Volume 196, September 2021, 105314
Paola Bordón, Catalina Canals, Alejandra Mizala; Economics of Education Review 77
(2020) 102011.
Felipe Balmaceda; International Journal of Game Theory volume 49, pages 601–637 (2020)