Identifying demand and supply factors in democratic governance in Estonia

Last registered on November 20, 2022

Pre-Trial

Trial Information

General Information

Title
Identifying demand and supply factors in democratic governance in Estonia
RCT ID
AEARCTR-0007245
Initial registration date
March 16, 2021

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
March 17, 2021, 10:31 AM EDT

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

Last updated
November 20, 2022, 7:56 PM EST

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

Locations

Region

Primary Investigator

Affiliation
World Bank

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2021-03-01
End date
2022-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study how public officials respond to information on their own outputs and citizen policy preferences across 74 local municipalities in Estonia. Using a citizen survey and Quadratic Voting for Survey Research (QVSR) methods, we capture the policy preferences of citizens in each municipality. We then randomize public officials into one of four treatment arms based on their municipality of work. The treatment arms vary the information provided to municipal public officials on local municipal performance (service-delivery and public-performance indicators) and citizens' policy preferences. Our first treatment arm strengthens awareness and use of a new local government dashboard (19 municipalities). This treatment provides local public officials with a detailed diagnostic assessment of their municipality's performance, highlighting how they are doing and where they might improve, with a focus on outputs (service-delivery indicators) only. The objective is to see whether simply updating public officials with information on outputs is sufficient to change their behavior. Our second treatment arm promotes the dashboard among local citizens via Facebook adverts in order to increase citizens' awareness and usage of the dashboard (17 municipalities). We also contact a representative sample of citizens in each treatment local government and introduce them to the dashboard and its functionality. Our third treatment arm combines the first two arms, allowing us to assess the existence of complementarities (18 municipalities). Our fourth treatment arm is a control group, in which public officials are not provided training nor information on citizens' policy preferences (20 municipalities). We assess the effects of the treatment arms on measures of citizen policy preferences; measures of local municipality efficiency (backlogs, service wait times, fiscal waste); population welfare outcomes (health indicators and education indicators); voter turnout; election outcomes; and budgetary outcomes. Together, these interventions will provide information into how information on publicly available information on public-sector performance and citizen preferences can impact provider behaviors and future performance.
External Link(s)

Registration Citation

Citation
Rogger, Daniel. 2022. "Identifying demand and supply factors in democratic governance in Estonia." AEA RCT Registry. November 20. https://doi.org/10.1257/rct.7245-1.2
Experimental Details

Interventions

Intervention(s)
T1 (19 municipalities): providing a detailed diagnostic assessment of municipality performance to public officials, highlighting how they are doing and where they might improve, with a focus on outputs (indicators of local municipality performance) only. The objective of this treatment arm to see whether simply updating public officials with information on outputs is sufficient to change their behavior, actions, and performance.

T2 (17 municipalities): promoting the dashboard among local citizens via Facebook adverts and introducing a representative survey of citizens to the dashboard and its functionality. The objective of this treatment arm is to substantially increase awareness and usage of the dashboard among local citizens.

T3 (18 municipalities): T1 and T2 Combined

T4 (20 municipalities): Neither (control group)
Intervention Start Date
2021-03-01
Intervention End Date
2022-11-30

Primary Outcomes

Primary Outcomes (end points)
Citizen policy preferences; measures of local municipality efficiency (backlogs, service wait times, fiscal waste); population welfare outcomes (health indicators and education indicators); voter turnout; election outcomes; budgetary outcomes
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomize municipalities into one of four treatment arms. Our experiment includes all 74 local municipalities in Estonia, covering ~2,500 public officials. Our first treatment arm includes providing a detailed diagnostic assessment of municipality performance to public officials, which summarises local-municipality outputs (covering 300 indicators). The diagnostic tool will highlight core aspects of their performance and primary areas for improvement, with a focus on output indicators only. Our second treatment arm promotes the dashboard among local citizens via Facebook adverts in order to increase citizens' awareness and usage of the dashboard. Our third treatment arm is a combination of the first two treatment arms which allows us to assess the extent to which the treatments complement each other. We also contact a representative sample of citizens in each treatment local government and introduce them to the dashboard and its functionality. Our fourth treatment arm is a control group, where public officials in this group receive no training nor data on citizens' policy preferences.

We assess the effect of the treatment arms (T1, T2, and T3, relative to the control) on measures of citizen policy preferences; measures of local municipality efficiency (backlogs, service wait times, fiscal waste); population welfare outcomes (health indicators and education indicators); voter turnout; election outcomes; and budgetary outcomes.
Experimental Design Details
Not available
Randomization Method
Randomization will be done by a computer using statistical software.
Randomization Unit
Municipality level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
79 municipalities
Sample size: planned number of observations
74 municipalities; ~2,500 local government officials; ~300 indicators; undetermined sample of citizens.
Sample size (or number of clusters) by treatment arms
Municipalities will be randomized into the three treatment arms with equal probability (one-quarter): 19 in T1, 17 in T2, 18 in T3, 20 in T4.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Columbia University
IRB Approval Date
2020-12-30
IRB Approval Number
IRB-AAAT3960
IRB Name
Columbia University
IRB Approval Date
2021-01-21
IRB Approval Number
IRB-AAAT5426
IRB Name
Research Ethics Committee of the University of Tartu (UT REC)
IRB Approval Date
2020-12-21
IRB Approval Number
332/T-27
Analysis Plan

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