Organizational Dynamics and Administrative Data Production

Last registered on January 22, 2023


Trial Information

General Information

Organizational Dynamics and Administrative Data Production
Initial registration date
January 02, 2023

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
January 22, 2023, 10:50 AM EST

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



Primary Investigator

New York University

Other Primary Investigator(s)

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
I study organizational dynamics in bureaucracies associated with the decentralized collection of administrative data. By decentralized data collection, I refer to state data that is solicited from decentralized governments by a central government agency. In collaboration with a national government organization in Colombia, I study organizational dynamics associated with the collection, reporting, and use of data within both decentralized governments and the partner agency itself. I study reporting behavior by bureaucrats in decentralized governments experimentally by embedding an RCT in a nation-wide administrative data collection effort. I the use of data by bureaucrats in the central government (partner) agency using qualitative methods.
External Link(s)

Registration Citation

Slough, Tara. 2023. "Organizational Dynamics and Administrative Data Production." AEA RCT Registry. January 22.
Experimental Details


The experimental interventions are embedded in a new data collection effort by a Colombian government agency. To understand how communication within local bureaucracies influences administrative data submission, we use an encouragement design to increase the level of communication or communication between bureaucrats and politicians or other bureaucrats in their local government when collecting data for submission to the national government agency. Municipal governments assigned to treatment receive communication promoting this type of collaboration or communication. Those assigned to control do not receive this encouragement. To measure bureaucratic uncertainty, we use a within-subjects randomized elicitation of uncertainty.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
I measure the distribution of responses across all questions on the instrument, validate accuracy of responses (where objective data are available), and measure bureaucrats' level of certainty in select responses.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
I use enumerator assessments of bureaucratic performance in the data submission process.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The primary experimental manipulation utilizes an encouragement RCT design. In this design, municipal governments are randomly assigned to a treatment or control condition. The treatment encourages bureaucrats to consult with other individuals in their local government—whether other bureaucrats or the elected mayor—or others in their municipality. I contrast this to a control condition in which bureaucrats are simply asked to prepare responses. In the data collection, enumerators measured levels of collaboration or communication within the institution (the endogenous treatment). In the first stage, this design identifies the effect of the encouragement on levels of collaboration within local governments. I then can use this experimental manipulation to identify the ITT of encouragement or the complier average causal effect (CACE or LATE) of collaboration on attributes of the data submitted to the national government. Additionally, the design permits identification of quantile treatment effects, which measure the effects of encouragement on the distribution of responses.

The secondary experimental manipulation provides novel measurement of bureaucratic uncertainty. This within-subjects design elicits respondents' level of certainty three times, once per each block of two questions. In each block, of two questions, a municipal government is randomly assigned to provide their level of certainty on the first or second question. This design allows for measurement of uncertainty as well as studying the effects of certainty elicitation on subsequent responses. For the latter, this design facilitates the identification the ATE (and quantile treatment effects) of certainty elicitation on subsequent responses.
Experimental Design Details
Randomization Method
Randomization Unit
For the encouragement design: the municipal government. For the secondary manipulation: the municipality-question (a within subjects design)
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
551 per arm for the encouragement design.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For the ITT analysis, a standardized effect of 0.2 control group standard deviations.

Institutional Review Boards (IRBs)

IRB Name
Innovations for Poverty Action
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials