CV

CONTACT INFORMATION

Email: JMauro@andrew.cmu.edu

Phone: (415) 810-2897

Address: Carnegie Mellon University Room 3005, Hamburg Hall 5000 Forbes Ave, 15213

 

RESEARCH INTERESTS

SEMI-PARAMETRIC CAUSAL INFERENCE. Instrumental Variables, Doubly Robust Estimators, Adapting Machine Learning tools for Inference, Conformal Analysis. Applications in Economics, Criminology and Security.

 

EDUCATION

CARNEGIE MELLON UNIVERSITY, Pittsburgh, PA

Thesis title: Doubly Robust Causal Inference for the Social Sciences: Extending semi-parametric IV to multi-valued treatments and instruments, with an application to the effects of visitation on recidivism

Current PhD Candidate in Statistics and Public Policy joint program

Master of Sciences May 2016, Statistics

 

COLUMBIA UNIVERSITY, Graduate School of Arts and Sciences, New York, NY

Master of Arts May 2011, Quantitative Methods in the Social Sciences

Thesis title: Foreign Finance and Women in the Developing World: How fluctuations in Foreign Portfolio Investment affect Women’s Employment in Developing Nations

 

COLUMBIA UNIVERSITY, Barnard College, New York, NY

Bachelor of Arts, Economics, May 2010

Graduated Magna Cum Laude

Thesis title: The Rising Tide that Lifts no Boats: The stagnation of American wages during a period of prosperity

 

AWARDS/HONORS

  • Awarded Konda award for best first year paper for my work on “Modeling Endogeneity in hurdle models: Novel Instrumental Variables Hurdle Models”
  • Economics Research Fellowship, ADVANCE Research Center at Lisbon School of Economics & Management by University of Lisbon
  • Dean’s list every semester eligible at Barnard College
  • Sylvia Kopald Selekmen Prize in Economics
  • Economics department nominee for George Welwood Murray Scholarship

 

RESEARCH

PUBLICATIONS

  1. Hardison, C. M., Rhodes, C., Mauro, J. A., Daugherty, L., Gerbec, E. N., Ramsey, C. (2014). Identifying Key Workplace Stressors Affecting Twentieth Air Force: Analyses Conducted from December 2012 Through February 2013. Santa Monica, CA: RAND Corporation, RR-592-AF.
  2. Chaitra M. Hardison, Nelson Lim, Kirsten M. Keller, Jefferson P. Marquis, Leslie Adrienne Payne, Robert Bozick, Louis T. Mariano, Jacqueline A. Mauro, Lisa Miyashiro, Gillian S. Oak, Lisa Saum-Manning. (2015) Recommendations for Improving the Recruiting and Hiring of Los Angeles Firefighters.  Santa Monica, CA: RAND Corporation, RR-687-LAFD.
  3. Xin S, Mauro J, Mauro T, Elias P, Man M (2013). Ten-year publication trends in dermatology in mainland China. Report: International Journal of Dermatology, 1-5.
  4. Non-Academic: Columbia Political Review: “Seeing Through the Fog: San Francisco Provides a Model for Health Care that Works” (http://goo.gl/Fas4t) & Columbia Political Review: “Empowe(red): Ethical Consumerism and the Choices We Make” (http://goo.gl/g7GzF)

MANUSCRIPTS IN PROGRESS

  1. Branstetter, L., Kovak, B., Mauro, J., Venancio, A. If it Can’t Bend, will it Break? The China Shock and Portuguese Manufacturing.
  2. Mauro, J., Cuellar, M., Kennedy, ,E. A Primer on Influence Functions.  
  3. Cuellar, M., Mauro, J., When Additional Information Increases Error: Withholding biasing information from Forensic Scientists
  4. Mauro, J., Kennedy, E. Exploring TMLE: what is it and when is it useful?
  5. Mauro, J., G’Sell, M., Kovak, B. Incorporating Endogeneity in Hurdle Models. Supported by Graduate research fellow for FCT Grant, (2015)

 

PRESENTATIONS

  • Atlantic Causal Inference Conference 2017 Poster Presentation: Doubly Robust Causal Inference With Multivalued Instruments
  • Midwest Economics Association Presenter: Incorporating Endogeneity in Censored Data
  • Midwest Economics Association Discussant: Two-Step Estimation and Inference with Possibly Many Included Covariates (Cattaneo, Jannson and Ma, 2017)
  • JSM 2016 Poster Presentation: Analytic Approaches to Labor Force Adjustment in the face of Import Competition

 

PROFESSIONAL EXPERIENCE

Lawrence Livermore National Lab, Livermore, CA

Data Science Intern, May 2016-August 2016

  • Modeled variance in the estimation of hyperspectral images.
  • Developed Approximate Bayesian Computing analysis of atmospheric conditions in hyperspectral image analysis.
  • Presented a poster detailing variance estimation strategy and results

RAND Corporation, Santa Monica, CA

Research Assistant, January 2013-June 2014

  • Ran and participated in interviews and focus groups of LAFD personnel, gathered and analyzed data from LAFD, and wrote memo describing entire selection process of LAFD
  • Coordinated with internal team and panel of experts to develop nationwide survey of crime victim service providers, including cognitive testing and development of a sampling frame
  • Using SAS and R, undertook statistical analyses predicting likelihood of crime victim’s accessing services, researched applicability of APC analyses to crime victimization data
  • Coordinated with team statistician to develop analyses of small sample Equal Employment data with missing data
  • Coordinated and helped run focus groups; coded and analyzed response data; contributed to preparation of presentation materials for upper-level leadership in the Air Force

KEYSTONE STRATEGY, San Francisco, CA

Senior Analyst (Promoted to Senior Analyst July 2012), May 2011-December 2012

  • Used SAS and SQL to undertake statistical analyses to demonstrate anti-competitive behavior and harm for a major technology firm
  • Manipulated and analyzed large datasets to provide evidence to anti-trust authorities
  • Researched and wrote reports on business model and history of search engines
  • Wrote and edited papers and reports for anti-trust authorities outlining economic theory and empirical evidence
  • Advised other teams on appropriate statistical methods

GOLDMAN SACHS, New York, NY

Operational Risk Intern, Jan 2010-May 2010

 

TEACHING

  • Teaching Assistant, Summer 2017: Professional Writing
  • Teaching Assistant, Spring 2016 & Spring 2017: Sampling, Survey and Society
  • Teaching Assistant, Fall 2015 & Fall 2016: Empirical Methods for Public Policy and Management
  • Teaching Assistant, Fall 2014: Introduction to Probability Theory

 

GRADUATE COURSEWORK

  • Statistical Machine Learning (CMU 36-702)
  • Foundations of Statistics (CMU 36-835)
  • Advanced Statistics (CMU 36-755)
  • Network Models (CMU 36-720)
  • Advanced Data Analysis (CMU 36-757)
  • Advanced Probability (CMU 36-752)
  • Intermediate Statistics (CMU 36-705)
  • Regression Analysis (CMU 36-707)
  • Statistical Computing (CMU 36-750)
  • Time Series (CMU 36-728)
  • PhD International Microeconomics (CMU 90-928)
  • Probability Models and Stochastic Processes (CMU 36-733)
  • Multilevel and Hierarchical Models (CMU 36-663)
  • Probability and Mathematical Statistics (CMU 36-700)
  • PhD Microeconomics (CMU 90-908)
  • Non-parametric Statistics (Columbia W4413)
  • Economics of Finance (Columbia U6022)
  • Statistical Inference (Columbia W4107)
  • International Capital Markets (Columbia U6045)

 

ADDITIONAL SKILLS

Software: R, Python, Shiny, SAS, SQL, STATA, LaTeX, Microsoft Office

Languages: Fluent in French, Conversant in Italian and Spanish, Elementary knowledge of Portuguese, Mandarin and Turkish

Additional Interests: Samba, Muay Thai, Faulkner, Crocheting