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Complexity and the Effectiveness of Public Policy
Last registered on March 04, 2018


Trial Information
General Information
Complexity and the Effectiveness of Public Policy
Initial registration date
March 02, 2018
Last updated
March 04, 2018 2:23 PM EST
Primary Investigator
University of Copenhagen
Other Primary Investigator(s)
PI Affiliation
University of Copenhagen
PI Affiliation
University of Copenhagen
PI Affiliation
University of Copenhagen
Additional Trial Information
In development
Start date
End date
Secondary IDs
Unemployment insurance (UI) systems in modern labor markets are riddled with a multitude of rules and regulations governing job seekers' economic situation and their incentives to search for employment. These include, for instance, detailed regulations specifying individuals' benefit level and potential benefit duration, job search requirements, conditions for avoiding benefit sanctions, possibilities for earning extra income or additional benefit entitlements by working in part-time or short-term jobs, etc. The complexity of UI systems makes it challenging for job seekers to understand the prevailing rules, their build-in incentives, and the resulting consequences for their personal economic situation. This is potentially problematic, as a lack of understanding may distort individuals' job search incentives and employment prospects. We conduct a randomized controlled trial among Danish job seekers to study how reducing complexity affects individuals' understanding of UI benefit rules, their job search behavior, and labor market outcomes. Our intervention rests on an online information tool that provides continuously updated, personalized information on individuals' remaining UI benefit period, their accumulated working time that can be used to prolong the potential benefit duration (PBD), as well as information on essential rules regarding job seekers' benefit duration and benefit sanctions. Earlier evidence has shown that job seekers in Denmark find these aspects of the UI system difficult to understand and that they exhibit limited knowledge of the underlying UI benefit rules. Participants in our experiment are randomly assigned to three equally sized groups: individuals in the treatment group (T) receive messages that direct their attention to the online information tool; (ii) individuals in the placebo group (P) receive generic messages that are unrelated to the information tool; individuals in the control group (C) receive no messages. We evaluate the causal effects of our intervention using administrative data on individuals' labor market outcomes and an online survey that is administered to a subset of participants.
External Link(s)
Registration Citation
Altmann, Steffen et al. 2018. "Complexity and the Effectiveness of Public Policy." AEA RCT Registry. March 04. https://doi.org/10.1257/rct.2666-1.0.
Former Citation
Altmann, Steffen et al. 2018. "Complexity and the Effectiveness of Public Policy." AEA RCT Registry. March 04. http://www.socialscienceregistry.org/trials/2666/history/26278.
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Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
labor market outcomes, measures of job search behavior and knowledge
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The randomized controlled trial focuses on a complexity-reducing intervention among unemployed job seekers in the Danish labor market. The intervention aims at enhancing the understanding of complex labor market rules among treated individuals, by fostering the usage of an online information tool in the treatment group.

We focus on rules governing job seekers' potential benefit duration (PBD) and benefit sanctions related to not making use of short-term work opportunities during the benefit period. In the Danish UI system, job seekers can influence their PBD by working in "non-regular" jobs during the benefit period, e.g., on a temporary or part-time basis. Specifically, job seekers have the possibility to extend the regular PBD from two years up to maximally three years. At the same time, benefit recipients face potential benefit sanctions if they do not work (enough) while receiving UI benefits (specifically, UI benefits will lapse for one day every four months if the benefit recipient has not worked for at least one week per month on average in this period). In a prior survey that we conducted in May 2017, we identified strong knowledge gaps with respect to the rules governing non-regular work during the benefit period and the corresponding possibilities of extending the PBD.

The online information tool on which our intervention is based aims at addressing these knowledge gaps. Specifically, the tool provides benefit recipients with information about their personal benefit situation, a simple visual presentation, and an interactive calculator. The provided information includes individuals' remaining unemployment benefit entitlements, their accumulated working time that can be used to extend the PBD, as well as information on essential rules regarding job seekers' benefit duration and benefit sanctions. The information provided in the online tool is personalized to the individual job seeker's specific situation and continuously updated. The tool is accessible through jobnet.dk, the online portal of the Danish Agency for Labor Market and Recruitment (STAR).

Our intervention aims at fostering the usage among treated individuals by drawing their attention to the tool. Specifically, we randomly divide the stock of UI benefit recipients at the beginning of the intervention into three groups. Individuals in the treatment group (T) receive messages (a somewhat longer initial message and up to three monthly reminders) that inform them about the tool and provide a direct link to access the tool. Individuals in the placebo group (P) receive generic messages at the same points in time, which are unrelated to the online information tool and the corresponding rules. Individuals in the control group (C) receive no messages.
Experimental Design Details
Randomization Method
randomization done in offcie by computer
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
approx 98,600 individuals
Sample size: planned number of observations
approx 98,600 individuals
Sample size (or number of clusters) by treatment arms
approx 32,866 in treatment group, 32,866 in placebo group and 32,866 in control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents
Pre-analysis plan: complexity and public policy

MD5: fe3ab67f4e812eeb63ce031a956c8144

SHA1: 970b270966937f2b55a1f44f19290b321fd21a2a

Uploaded At: March 02, 2018

Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)