Carolina Caetano

Assistant Professor of Economics

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I am an assistant professor of economics at the University of Rochester. I specialize in microeconometrics, mainly in problems involving endogeneity in non-parametric models, with a focus on techniques that are readily applicable for applied research. I am also interested in health economics, particularly in endogeneity in behavioral health models. Examples of my health research include the effects of maternal smoking and the effects of breastfeeding.
Contact
Address:
238 Harkness Hall
P.O. Box: 270156
Rochester, NY 14627-0156

Phone:
Office: (585) 275-3895
Fax: (585) 256-2309

Email:
carol.caetano *at* rochester.edu
If you are an ECO 231W student, click
here.

CV: CarolinaCaetano_CV.pdf
Research
Publications
A discontinuity test for identification in triangular nonseparable models, with Christoph Rothe and Nese Yildiz, Journal of Econometrics, v. 193(1), 2016, Pages 113-122. Paper, informal summary, slides.

A test of exogeneity without instrumental variables in models with bunching, Econometrica, v. 83(4), 2015, Pages 1581-1600. Paper, online appendix (details about the estimator and the simulations), code, replication files, informal summary, slides.


Working Papers
Identifying multiple marginal effects with a single instrument, with Juan Carlos Escanciano. (Submitted) Paper, slides.

Identifying multiple marginal effects with the RDD, with Gregorio Caetano and Juan Carlos Escanciano. An early version of the paper above has the setup, estimator and proofs.

The Role of Dynamic Complementarities on Child Development: A Corner Solution Approach, with Gregorio Caetano and Eric Nielsen. Coming soon.

Smoking Across Pregnancy and Birth Outcomes, with Kenneth Chay and Umair Khalil. Coming soon.

Dummy Discontinuity Test of Exogeneity. Coming soon.
Teaching
Undergraduate econometrics (ECO 231W). T​his course prepares undergraduate students equipped​ with a basic knowledge of statistics to do independent applied research using OLS regression techniques. ​​The course lays sufficient groundwork for the students to be able to explore more advanced topics, such as panel data, instrumental variables and GMM, independently in their future work. Course website, detailed curriculum, class notes, Stata homeworks and other downloads, YouTube Stata tutorial channel, class forum (open).


Graduate Nonparametric Econometrics for Applied Researchers (ECO 523). This course covers kernel-based (including local polynomial) and series-based (including splines and wavelets) techniques of nonparametric estimation. It also covers semi-parametric models, such as partially-linear, single-index, additive, and varying coefficient models. Other covered topics include RDD, inverse probability-weighted propensity score, and nonparametric IV. Course website (find the detailed curriculum, notes and homeworks).