Is no news good news? Corruption enforcement and corruption perceptions in Ukraine

Last registered on March 06, 2024

Pre-Trial

Trial Information

General Information

Title
Is no news good news? Corruption enforcement and corruption perceptions in Ukraine
RCT ID
AEARCTR-0013089
Initial registration date
February 27, 2024

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 06, 2024, 3:35 PM EST

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

Locations

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Primary Investigator

Affiliation
SITE - Stockholm School of Economics

Other Primary Investigator(s)

PI Affiliation
University of San Francisco
PI Affiliation
University of California, Berkeley
PI Affiliation
Kyiv School of Economics
PI Affiliation
University of Rome Tor Vergata

Additional Trial Information

Status
On going
Start date
2024-02-06
End date
2024-05-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study evaluates how individuals update their perceptions of corruption in response to new information about corruption enforcement. Theoretically, information about judicial investigations or convictions may simultaneously provide a negative signal about the extent of corruption and a positive signal about the level of enforcement. Our survey experiment is designed to measure these two effects and the net effect on corruption perceptions. It consists of an online survey of 7000 respondents in Ukraine, in which randomly selected sub-samples are exposed to information about corruption cases.
External Link(s)

Registration Citation

Citation
Fedyk, Yuri et al. 2024. "Is no news good news? Corruption enforcement and corruption perceptions in Ukraine." AEA RCT Registry. March 06. https://doi.org/10.1257/rct.13089-1.0
Experimental Details

Interventions

Intervention(s)
Corruption is – like most illegal transactions – hard to observe and quantify systematically. Given that the ‘true’ level of corruption is unobservable, corruption perceptions are widely used as a substitute in research and policy discussions. Perceptions have been shown to be biased measures of corruption (Olken 2009, Gutmann et al. 2020) but they matter in their own right. Domestic corruption perceptions may sway the outcome of elections while international corruption perceptions may, in the case of Ukraine, affect willingness to supply aid, foreign direct investment, reconstruction funding and the prospects of EU accession.

Over the past decade, Ukraine has implemented a range of reforms intended to combat corruption, including the creation of new, independent agencies tasked with anti-corruption enforcement. One consequence of their activities has been a steady stream of news about the discovery and investigation of corruption cases. The publication of news about prosecutions and convictions is an important component of law enforcement because it is a prerequisite for deterrence. News about corruption cases may, however, also affect corruption perceptions. Individuals who learn about a new corruption case may focus on the details of the crime and their perception of corruption in the country may worsen. Others may focus on the fact that it has been detected and is being prosecuted, causing their perceptions to improve. Our study aims to evaluate these responses empirically and in particular, to measure the net effect of news about enforcement on corruption perceptions.

Information about corruption cases can be delivered in different forms. Individuals may be most frequently exposed to news stories about a single corruption case. Such news reports may have a different effect from aggregate statistical information about the total number of prosecutions or convictions. For example, news stories about individual cases may encourage a focus on the crime while statistical information may be viewed through the lens of enforcement. Our study includes treatment arms that provide both kinds of information in order to evaluate whether the nature of the news affects the response.
Intervention Start Date
2024-02-06
Intervention End Date
2024-03-01

Primary Outcomes

Primary Outcomes (end points)
1. Perceptions about corruption, 2. Perceptions about enforcement
Primary Outcomes (explanation)
1. Perception of corruption in Ukraine
Measured in question B7 of the survey. Respondents are asked how important the problem of corruption is for Ukraine on a scale from 1 (not at all important) to 10 (the most important problem).

2. Perception of corruption enforcement in Ukraine
Measured in question B9 of the survey. Respondents are asked how willing the government is to fight corruption in Ukraine on a scale from 1 (not at all willing) to 10 (determined to fight corruption).
In each case, respondents will have been asked similar questions with different phrasing, and an equivalent 10 point scale prior to treatment.

In the analysis we will report results for (i) variables that use the original 10-point scale and (ii) dummy variables that take the value of 0 for values below 6 and 1 otherwise.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our survey will have a sample of approximately 7000 respondents. It is conducted online, in Ukrainian, by the survey company Info Sapiens. The sample is drawn from a larger panel designed to be representative of the Ukrainian population as of early 2022. Respondents are divided randomly into 5 groups of 1400 respondents each. One of these groups is a control group. The other four groups will receive information about corruption prevalence, corruption enforcement, or both.
Experimental Design Details
Not available
Randomization Method
Randomization done by the survey company using a computer.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
7000
Sample size: planned number of observations
7000 individual respondents
Sample size (or number of clusters) by treatment arms
1400 control, 1400 treatment arm 1 (receives statistical information about corruption prosecutions by anti-corruption court), 1400 treatment arm 2 (receives statistical information about corruption prevalence), 1400 treatment arm 3 (combination of treatment 1 and treatment 2), 1400 treatment 4 (receives information about a specific corruption case).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents

Pre-analysis plan Fedyk, Gorodnichenko, Lehne, Sologoub and Spagnolo

MD5: da48f769527841cc93688bb996fb9c85

SHA1: 86814b552aa17d2aed02b72053e5c6b88fe73149

Uploaded At: February 27, 2024