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Performance Scorecards and Government Service Delivery: Experimental Evidence from Land Record Changes in Bangladesh

Last registered on January 04, 2021
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Pre-Trial

Trial Information

General Information

Title
Performance Scorecards and Government Service Delivery: Experimental Evidence from Land Record Changes in Bangladesh
RCT ID
AEARCTR-0003232
Initial registration date
August 13, 2018

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 13, 2018, 3:34 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
January 04, 2021, 11:25 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
Bangladesh
Region

Primary Investigator

Name
Martin Mattsson
Affiliation
National University of Singapore
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2018-09-01
End date
2019-08-01
Keywords
Governance
Additional Keywords
Organisational Economics, Corruption, Price Discrimination
JEL code(s)
D73, O12, H83, D82
Secondary IDs
Abstract
Slow government service delivery and low accountability among government bureaucrats are common problems in many low- and middle-income countries. As eGovernance systems are becoming common practice in government service delivery in Bangladesh, more and more data is generated regarding about how bureaucrats are providing government services but so far very little of data is used by the government to improve service delivery. In this project we will use the data generated by one eGovernance system to generate a monthly Performance Scorecard for government bureaucrats in terms of the timeliness of their service provision. The service for which we will implement this intervention is land record changes, also know as “mutations”. We will be sending out performance scorecards displaying how many applications for mutations were processed within the government mandated time limit of 45 working days as well as how many applications that are still pending beyond this limit. By sending these performance scorecards to both the bureaucrats doing the land record changes, as well as the superiors of these bureaucrats we hope to improve accountability within the bureaucracy and thereby increasing the number of government services provided within the time limit.
External Link(s)

Registration Citation

Citation
Mattsson, Martin. 2021. "Performance Scorecards and Government Service Delivery: Experimental Evidence from Land Record Changes in Bangladesh." AEA RCT Registry. January 04. https://doi.org/10.1257/rct.3232-3.2
Former Citation
Mattsson, Martin. 2021. "Performance Scorecards and Government Service Delivery: Experimental Evidence from Land Record Changes in Bangladesh." AEA RCT Registry. January 04. https://www.socialscienceregistry.org/trials/3232/history/200828
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The intervention of our experiment is to generate a monthly “Performance scorecard” for bureaucrats in charge of making changes to land records in Bangladesh. We will share these scorecards with the bureaucrats and their superiors. The scorecard will contain information on the number of applications processed within 45 working days (the limit for how long a processing time can be according to current regulation) in the past month as well as the number of applications pending for more than 45 working days at the end of each month. In addition to these figures, a percentile ranking among the bureaucrats will be generated so anyone receiving the scorecard can assess the relative performance of the bureaucrat.
Intervention (Hidden)
Intervention Start Date
2018-09-01
Intervention End Date
2019-03-01

Primary Outcomes

Primary Outcomes (end points)
1. Effect of Performance Scorecard on bureaucrat performance as measured by the scorecards
2. Benefits of Performance Scorecard to applicants
3. Testing predictions of the model outlined in Pre-Analysis Plan
4. Spillover effect on applications not entering the scorecards

All of these outcomes are described in detail in the Pre-Analysis Plan.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The main identification strategy of the study will be the randomization of which offices the scorecard system is implemented in. Out of 114 Upazila Land Offices currently connected to the eMutation system, 57 will have scorecards generated for them. There are currently 18 offices that have fully implemented the eMutation system so that all applications are processed using the digital system. The randomization will be done separately for the group with the 100% implementation and for the group with partial implementation. After these two groups have been separated the randomization will be stratified using the following strata:

1. Having processed above/below the median number of applications within 45 working days in the months of June and July, 2018 in full implementation group
2. Having processed within the first, second or third tertile number of applications within 45 working days in the months of June and July, 2018 in partial implementation group
3. Having above/below the median number of applications pending for more than 45 working days in full implementation group
4. Having a number within the first, second or third tertile of applications pending for more than 45 working days in partial implementation group

This gives me 13 strata. Within each strata half of the ULOs are assigned to treatment.
Experimental Design Details
Randomization Method
Stratified (Block) randomization using Stata.
Randomization Unit
Upazila Land Office
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
114 Upazila Land Offices
Sample size: planned number of observations
Approximately 40,000 applications
Sample size (or number of clusters) by treatment arms
57 Treatment Upazila Land Offices, 57 Control Upazila Land Offices
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Human Subjects Committee - Yale University
IRB Approval Date
2018-06-20
IRB Approval Number
2000021565
Analysis Plan

Analysis Plan Documents

Pre-Analysis_Plan.pdf

MD5: ee93b463e48ef893a6709d1ea68bb040

SHA1: c696aebfc7119cd27c5d06a7a24eeb1c36abee7f

Uploaded At: August 18, 2018

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
March 01, 2020, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
December 30, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
311 sub-district land offices
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
1,034,688 applications and 2,869 phone interviews
Final Sample Size (or Number of Clusters) by Treatment Arms
155 treated sub-district land offices, 156 control sub-district land offices
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
Slow public service delivery and corruption are common problems in low- and middle-income countries. Can better management information systems improve delivery speed? Does improving the delivery speed reduce corruption? In a large-scale experiment with the Bangladesh Civil Service, I send monthly scorecards measuring delays in service delivery to government officials and their supervisors. The scorecards increase on-time service delivery by 11% but do not reduce bribes. Instead, the scorecards increase bribes for high-performing bureaucrats. A model where bureaucrats' reputational concerns constrain bribes can explain the results. When positive performance feedback improves bureaucrats' reputations, the constraint is relaxed, and bribes increase.
Citation
Mattsson, Martin, Information Systems, Service Delivery, and Corruption: Evidence from the Bangladesh Civil Service. Working Paper. (2023). Available at SSRN: https://ssrn.com/abstract=3986989
URL
https://ssrn.com/abstract=3986989

Reports & Other Materials