Shaikh Shaun
Biography
About Me
I'm a Ph.D. candidate at McMaster University. My fields of specialization are Econometrics and Health Economics.
I am currently employed as a consultant for Charles Manski at Northwestern University.
I am on the academic job market and will be available for interviews at the CEEE meetings in December at Toronto, and the AEA/ASSA meetings in January at Philadelphia.
Job Market Paper
Abstract: Estimating trends over time, including those surrounding policy changes, typically does not address the plausible confounding issue of trends in data quality, leading to a non-classical measurement error problem. This may be a concern with either survey or administrative data, where reporting attitudes may change over time or measurement quality may improve with time. Our application is to administrative health data, which is often used in epidemiological studies to evaluate trends in binary health characteristics and treatments. We address the detection of a trend in a binary outcome – successful resuscitation following cardiac arrest – allowing for trending misclassification error. Employing a mixture model, we compute bounds on the outcome following Horowitz and Manski (1995) under contaminated and corrupt data assumptions. Identification relies on validation information from a non-random subsample of the data allowing us to place upper bounds on measurement error. We also consider how identification is improved with monotonicity assumptions (Manski and Pepper 2000), bounded variation assumptions (Manski & Pepper, 2013, 2017), and subgroup specific verification rates (Dominitz and Sherman 2004, 2006; Kreider and Pepper 2007, 2008). We show evidence of a trend in the successful resuscitation rate for the population of reported cardiac arrests in Ontario under assumptions that are weaker than those in the existing literature.
C.V.
To download PDF click here.
For additional information please visit my personal website at the link below.
Personal Website
Education
Ph.D. Economics, McMaster University, expected July 2018
M.A. Economics, McMaster University, 2013
B.A. Economics, University of Waterloo, 2012
B.Math Mathematics, University of Waterloo, 2005
For additional information please visit my personal website at the link below.
Personal Website
Teaching
Teaching Experience
Teaching Assistant, Graduate Level Courses, McMaster University
Applied Microeconometrics (769) - Winter 2017
Econometrics I (761) - Fall 2017
Microeconomic Theory for Public Policy (727) - Fall 2017
Teaching Assistant, Undergraduate Level Courses, McMaster University
Econometrics I (3U03) - Winter 2017
Applied Econometrics (3WW3) - Winter 2017
Econometrics II (4G03) - Fall 2016
Economics of Labour Market Issues (2A03) - Fall 2015
Health Economics (3Z03) - Winter 2013
Intermediate Microeconomics II (2GG3) - Winter 2013
Introduction to Game Theory (3M03) - Fall 2012
Industrial Organization (3S03) - Fall 2012
Intermediate Microeconomics I (2G03) - Fall 2012
For additional information on my teaching background, interests, and philosophy, please visit my personal website.
Personal Website
Research
Job Market Paper
Abstract: Estimating trends over time, including those surrounding policy changes, typically does not address the plausible confounding issue of trends in data quality, leading to a non-classical measurement error problem. This may be a concern with either survey or administrative data, where reporting attitudes may change over time or measurement quality may improve with time. Our application is to administrative health data, which is often used in epidemiological studies to evaluate trends in binary health characteristics and treatments. We address the detection of a trend in a binary outcome – successful resuscitation following cardiac arrest – allowing for trending misclassification error. Employing a mixture model, we compute bounds on the outcome following Horowitz and Manski (1995) under contaminated and corrupt data assumptions. Identification relies on validation information from a non-random subsample of the data allowing us to place upper bounds on measurement error. We also consider how identification is improved with monotonicity assumptions (Manski and Pepper 2000), bounded variation assumptions (Manski & Pepper, 2013, 2017), and subgroup specific verification rates (Dominitz and Sherman 2004, 2006; Kreider and Pepper 2007, 2008). We show evidence of a trend in the successful resuscitation rate for the population of reported cardiac arrests in Ontario under assumptions that are weaker than those in the existing literature.
Other Thesis Chapters
What Happens after Cardiac Arrest? Patterns of Care with Patient Enrollment, with Arthur Sweetman
Temporal Trends in Survival for Patients with In-hospital Cardiac Arrest in Ontario: 2003-2010, with Ahmad von Schlegell, Mathew Mercuri, Madhu K. Natarajan, and Arthur Sweetman
Living for the Weekend with Cardiac Arrest: Survival and Discharge Location by Day of the Week of Arrest Occurrence
Peer Reviewed Publications
Work in Progress
The Exit Rate of Immigrants in Ontario from Disability Support: A Flexible Parametric Duration Model, with Saeed Kamyana
Research Experience
Research Assistant: Charles Manski, Northwestern University (Summer, Fall 2017)
• Coded user interface and back-end logic in Python for a clinical software tool to predict expected remaining lifetime under user inputted risk factor information to augment public life table data
• Statistical techniques required solving numerical linear programming problems to bound (i.e., partially identify) expected remaining lifetime, given aggregate distribution of demographics and user inputted risk factors and restrictions (i.e., monotonicity and bounded variation conditions)
Research Assistant: Arthur Sweetman, McMaster University (Summer 2013 to Summer 2016)
• Data preparation and analysis using Stata on large linked Ontario administrative health datasets related to topics on Ontario primary care reform
For additional information on research interests and experience, please visit my personal website.