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Merit-Based Transfers and Postings: A Field Experiment in Pakistan
Last registered on February 23, 2018

Pre-Trial

Trial Information
General Information
Title
Merit-Based Transfers and Postings: A Field Experiment in Pakistan
RCT ID
AEARCTR-0002753
Initial registration date
February 23, 2018
Last updated
February 23, 2018 2:14 PM EST
Location(s)
Region
Primary Investigator
Affiliation
MIT
Other Primary Investigator(s)
PI Affiliation
LSE
PI Affiliation
Harvard Kennedy School
Additional Trial Information
Status
Completed
Start date
2013-07-01
End date
2015-08-01
Secondary IDs
Abstract
Bureaucracies often post staff to better or worse locations, ostensibly to provide incentives. Yet we know little about whether this works, with heterogeneity in preferences over postings impacting effectiveness. We propose a performance-ranked serial dictatorship mechanism, whereby bureaucrats sequentially choose desired locations in order of performance. We evaluate this using a two-year field experiment with 525 property tax inspectors in Pakistan. The mechanism increases annual tax revenue growth by 30-41 percent. Inspectors that our model predicts face high equilibrium incentives under the scheme indeed increase performance more. Our results highlight the potential of periodic merit-based postings in enhancing bureaucratic performance.
External Link(s)
Registration Citation
Citation
Khan, Adnan, Asim Khwaja and Benjamin Olken. 2018. "Merit-Based Transfers and Postings: A Field Experiment in Pakistan." AEA RCT Registry. February 23. https://doi.org/10.1257/rct.2753-1.0.
Former Citation
Khan, Adnan, Asim Khwaja and Benjamin Olken. 2018. "Merit-Based Transfers and Postings: A Field Experiment in Pakistan." AEA RCT Registry. February 23. https://www.socialscienceregistry.org/trials/2753/history/26072.
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Experimental Details
Interventions
Intervention(s)
Within each of the ten major metropolitan areas in Punjab, we randomly allocated circles into groups of approximately ten circles each. At the beginning of the tax year (i.e. in July), groups were randomly selected to either participate in the MBTP scheme or to remain in the status quo. For groups selected to be in the MBTP scheme, all inspectors were told that they would be ranked based on their performance, and then based on this ranking, would be given a choice of circles within their group. Specifically, inspectors were told that if they were the top-ranked inspectors in a group they would be posted in their first-choice circle, the next ranked inspectors would be posted in their top preference from the remaining circles, and so on. Performance was calculated in two ways (randomized by group): for one sub-treatment (the “recovery” group), inspectors' performance was calculated as the year-on-year percent increase in their current circles’ tax collected collected during a fiscal year; for the other sub-treatment (the “demand” group), inspectors’ performance was calculated as the year-on-year percent increase in their current circles’ assessed tax base.
Intervention Start Date
2013-07-01
Intervention End Date
2015-08-01
Primary Outcomes
Primary Outcomes (end points)
log tax revenue, controlling for baseline log tax revenue
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
At the start of the first year circles were randomly assigned to be groups of 9-11 circles each, within metropolitan area. This results in 41 groups. After soliciting baseline preferences of all inspectors for circles in their assigned group, groups were randomized into treatment and control areas, stratified by metropolitan area. Within treatment areas, half the groups were randomly assigned to have performance judged by year-on-year change in tax recovery, and half were randomly assigned to have performance judged by year-on-year change in tax assessments.

In the second year, groups were randomized again into treatment and control, stratified based on their treatment in the first year.
Experimental Design Details
Randomization Method
public lottery conducted by computer
Randomization Unit
tax circle
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
410 circles in year 1; 525 tax circles in year 2
Sample size: planned number of observations
525 tax circles
Sample size (or number of clusters) by treatment arms
Year 1: 153 treatment; 257 control
Year 2: 150 treatment; 375 control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
MIT Committee on the Use of Humans as Experimental Subjects
IRB Approval Date
2013-06-14
IRB Approval Number
1004003834
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers