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Abstract
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Before
Public sector jobs are highly sought after in developing countries, with candidates spending years unemployed to compete for them. In India, less than one percent of candidates who compete end up successful, which raises questions about the long-term labor market outcomes of those who don’t make the cut. Using a correspondence study with private sector employers on India’s biggest job platform, this study investigates whether exam preparation has costs in terms of private sector job opportunities for unsuccessful candidates. Findings from this study will highlight the differences in interview callbacks for candidates with a history of preparing for government exams, relative to candidates who have remained in the private sector since graduation. The study will also highlight if the scores in the government exam hold any signal value in the private sector, to inform policy recommendations on making the time spent on exam preparation useful outside of public sector recruitment drives.
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After
Public sector jobs are highly sought after in developing countries, with candidates spending years unemployed to compete for them. In India, less than one percent of candidates who compete end up successful, which raises questions about the long-term labor market outcomes of those who don’t make the cut. Using a resume evaluation experiment with recruiters at a large Indian staffing firm, this study quantifies the social deadweight loss (in terms of foregone earnings) associated with prolonged exam preparation. Findings from this study will highlight how private sector employers evaluate the growing cohort of government job aspirants and will inform inform policy recommendations on making the time spent on exam preparation useful outside of public sector recruitment drives.
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Last Published
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June 08, 2025 01:15 PM
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After
December 17, 2025 05:26 AM
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Intervention Start Date
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June 09, 2025
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December 15, 2025
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Intervention End Date
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March 31, 2026
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January 31, 2026
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Primary Outcomes (End Points)
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Before
Interview callback decisions
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Interest in shortlisting the resume (1-10 scale), rating of skills shown in the resume against the job description (1-10 scale), rating of perceived likelihood that the candidate will stay at the firm for at least a year if hired (1-10 scale), and pay conditional on hiring.
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Experimental Design (Public)
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Before
The focus of the experiment is on the differential effects of staying unemployed to prepare for government exams relative to working in the private sector after graduation. The study will comprise a large-scale resume experiment. Resumes will vary in whether a candidate reveals a history of preparing for government exams. Callbacks received by candidates with experience preparing for government exams will be compared to callbacks received by candidates who have never prepared for government exams and have worked in the private sector. All other characteristics including gender, religion, school and college quality, academic grades, and extra-curricular activities will be held constant across all resume variants within a job posting.
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After
The focus of the experiment is on the differential effects of staying unemployed to prepare for government exams relative to working in the private sector after graduation. The study will comprise a large-scale resume experiment conducted as face to face interviews with recruiters in a large staffing firm. Resumes will vary in whether a candidate reveals a history of preparing for government exams. Ratings received by candidates with experience preparing for government exams will be compared to ratings received by candidates who have never prepared for government exams and have worked in the private sector. All other characteristics including gender, religion, school and college quality, academic grades, and extra-curricular activities will be held constant across all resume variants within a job posting.
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Randomization Method
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Before
Resumes will be generated using code that will randomly assign candidate characteristics (government vs private sector choice after graduation, years since graduation, government exam score, etc) to each variant. Resumes are generated using the program developed by Lahey and Beasley (2009).
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After
Resumes will be generated using code that will randomly assign candidate characteristics (government vs private sector choice after graduation, years since graduation, college score, etc) to each variant. Resumes are generated using the program developed by Lahey and Beasley (2009).
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Planned Number of Clusters
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500 job ads
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100 recruiters
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Planned Number of Observations
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9 resumes sent to 500 job ads, resulting in 4500 observations.
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30 resumes shown to each recruiter (total of 3000 observations)
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Sample size (or number of clusters) by treatment arms
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Before
1500 control resumes, 3000 treatment resumes.
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After
About half of resumes shown will belong to the treatment group (government exam preparation after graduation) and half will belong to the control group (private sector work experience after graduation)
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