Mailing address:     

 

 

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Email:

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Cell phone: +1 (301) 503 - 8232

Zeeshan Samad

Department of Economics

Vanderbilt University

2301 Vanderbilt Place

Nashville, TN 37235, USA

Ph.D. in Economics, Vanderbilt University,  May 2020 (expected)

     Specialization fields: Behavioral economics, Applied microeconomics

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M.A. in Economics, Vanderbilt University,  May 2016

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Master's in Public Policy, University of Maryland College Park,  May 2014

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B.Sc. in Economics, LUMS, Pakistan,  May 2010

Prof Myrna Wooders  (Primary Advisor) 

myrna.wooders@vanderbilt.edu

615-343-0461

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Profs Andrew Daughety and Jennifer Reinganum

andrew.f.daughety@vanderbilt.edu

jennifer.f.reinganum@vanderbilt.edu 

615-322-3453

 

Prof Gregory Leo

g.leo@vanderbilt.edu

615-875-9697

 

Prof Bradley Malin

b.malin@vumc.org

615-343-9096

Vanderbilt University, Instructor

Principles of Microeconomics,  summer semester 2018 

Methods of Economic Analysis,  summer semester 2018

Principles of Microeconomics,  summer semester 2017

Behavioral Economics,  summer semester 2017

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Vanderbilt University, Graduate Teaching Assistant

Microeconomics Theory II (PhD level),  spring semester 2016

Intermediate Microeconomics, fall semester 2015

Strategic Analysis in Game Theory,  fall semester 2015

 

Johns Hopkins University, Instructor

Macroeconomics,  summer semester 2016

Microeconomics,  summer semester 2016

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Lying to Yourself: A Mechanism of Self-deception [JMP]

People get utility from thinking of themselves more favorably than their true type. For example, people get utility from believing they are altruistic and at the same time get disutility from behaving altruistically (e.g. by donating money). Most interestingly, even people who are not truly altruistic get utility from believing they are altruistic. This paper studies a previously unexplored mechanism for self-deception that allows people to behave selfishly and yet view themselves as altruistic (have their cake and eat it too). They do this by manipulating their belief about something that has neither a positive effect nor negative effect on their image (e.g. how pessimistic they are) but allows them to maintain a favorable self-view (e.g. of being altruistic). Such belief manipulation allows people to rationalize their selfish behavior, which in turn protects their self-image from potential damage from the selfish action. The first part of this paper develops a theoretical model that explains this mechanism. The second part of the paper presents a laboratory experiment that shows that people indeed use this belief manipulation mechanism to deceive themselves into viewing themselves more favorably. 

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Measuring Trust in Genetic Data Privacy

How can people’s value of genetic data privacy be estimated? We address this question using methods of behavioral/experimental economics. Through decision-making tasks in two different frames involving risk of loss of privacy of data, in one case genetic data and in the other case financial data, we elicit people’s risk attitudes towards their genetic data relative to their risk attitudes towards their financial data. We find that people are more willing to risk a loss of genetic data privacy for health benefits than they are willing to risk a loss of financial data privacy for financial benefits. We conduct related experiments to better understand people’s motivations for willingness to share their genetic data and undertake the risk of doing so. The results of these experiments suggest that individuals are primarily motivated by private benefits, whether they are health or monetary and little to none by altruism and trust.

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A Mechanism of False Consensus Bias

This paper explores the mechanism behind the false-consensus bias, which states that people overestimate the commonness of their own responses. I propose a mechanism wherein individuals hold incorrect beliefs about the distribution from which their own type is drawn, believing that the distribution is skewed towards them. That is, they think the mode of the distribution is closer to them than it really is. The first part of the paper develops a theoretical model that explains this idea. The second part of the paper provides empirical evidence for this mechanism through a laboratory experiment. In the experiment, subjects first play a dictator game and then guess the distribution of choices made by others who played the same game. The hypothesis, that this distribution-skewing mechanism is a mechanism that drives the false-consensus bias, will be confirmed if the experiment results show that subjects’ predictions about distribution are skewed, and the skew is systematically biased towards one direction. In particular, subjects predict the mode of the distribution to be closer to their own choice and farther from the true mode.

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Behavioral Impacts of Minimum Wage on Informal Sector Wages

What happens to the wage of informal sector workers when a minimum wage is implemented in the formal sector? I address this question using data from Pakistan, a country whose informal labor force accounts for 40% of the total labor force. This data comes from a country-wide household-level survey and is available for multiple years both before and after the introduction of a minimum wage law. I use a difference-in-differences model to estimate the effect of a minimum wage law on wages of informal sector workers. I find that the minimum wage law has a positive impact on informal sector wages and the most plausible reason for this impact is that informal sector employers raise wages to avoid guilt/shame. Moreover, the impact of the minimum wage law is larger in poorer regions where the minimum wage law has a greater ‘bite’.