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Shaikh Shaun

photo of Shaun Shaikh

Shaun Shaikh

PhD Students
Department of Economics

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

Evaluating Trends in Successful Resuscitation after Cardiac Arrest under Trending Misclassification Error: Estimating Bounds under Partially Verified Data

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

https://www.shaunshaikh.com/

 

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

https://www.shaunshaikh.com/

 

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

https://www.shaunshaikh.com/

 

Research

Job Market Paper

Evaluating Trends in Successful Resuscitation after Cardiac Arrest under Trending Misclassification Error: Estimating Bounds under Partially Verified Data, with Arthur Sweetman

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

Nigar Sekercioglu, Shaun Shaikh, Gordon H. Guyatt, Jason W. Busse, ‘Derivation and Validation of a Prognostic Model for Workers Disabled by Depression’, Journal of Clinical and Analytical Medicine, 2017, 8(4), Pages 351-356

Nigar Sekercioglu, Jason W. Busse, M. Fatih Sekercioglu, Arnav Agarwal, Shaun Shaikh, Luciane Cruz Lopes, Reem A. Mustafa, Gordon H. Guyatt and Lehana Thabane, ‘Cinacalcet Versus Standard Treatment for Chronic Kidney Disease: A Systematic Review and Meta-analysis’, Renal Failure, 2016, 38(6), Pages 857-874

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.

Personal Website

https://www.shaunshaikh.com/