Public Prediction Bulletin

Abstract

Sierra Leone has maternal and child mortality rates that are among the highest in the world. In order to strengthen the provision of primary health care, Sierra Leone’s Ministry of Health and Sanitation (MoHS) created a national Community Health Worker Program in 2017. The program is organized around Peripheral Health Units (PHUs), small health facilities staffed with doctors, nurses, and midwives. Each village in the catchment area of a PHU is served by one Community Health Worker (CHW). Further, in every PHU, there is a supervisor whose job it is to enable the CHW’s work by training and advising them. We have run an RCT to understand how to best incentivize the community-health workers (CHW) and their supervisors. This study randomly varied whether a performance incentive of SLL 2,000 ($0.23) per household visit conducted by a CHW is (i) paid to the CHW, (ii) paid to the supervisor, or (iii) equally shared between the CHW and their supervisor. We will ask you to forecast how these interventions affect the number of household visits conducted by the CHWs, as well as the structural parameters that lead to these effects.

Study ID sspp-2021-0022-v1
Authors Erika Deserranno, Stefano Caria, Philipp Kastrau, Gianmarco Leon-Ciliotta
Discipline Economics
Field Development Economics
Completion Time 15 Minutes
Close Date Aug. 31, 2021


Citation
Deserranno, Erika, Caria, Stefano, Kastrau, Philipp, and Gianmarco Leon-Ciliotta. 2021. "Predicting the Effect of Financial Incentives on Household Visits by Health Workers." Social Science Prediction Platform. July 10. https://socialscienceprediction.org/s/cb2c0c



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Abstract

Our goal is to collect predictions of experts about the effects of interventions to increase COVID-19 vaccine uptake. We have not yet analyzed the data on vaccination uptake. Your predictions will help us to contextualize the findings of our experiment.

Study ID sspp-2021-0021-v1
Authors Pol Campos-Mercade, Armando Meier, Stephan Meier, Devin Pope, Florian Schneider, Erik Wengström
Discipline Economics
Field Health Economics, Behavioral Economics
Completion Time 5 Minutes
Close Date Aug. 15, 2021


Citation
Campos-Mercade, Pol, Meier, Armando, Meier, Stephan, Pope, Devin, Schneider, Florian, and Erik Wengström. 2021. "Behavioral interventions and vaccination uptake." Social Science Prediction Platform. June 28. https://socialscienceprediction.org/s/de0c42



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Abstract

In this paper, I evaluate customer preferences in the field with an online platform where cash paying consumers can shop and book a provider for medical procedures. I address whether customers discriminate against doctors on the basis of race and to what extent is such discrimination statistical. Literature has suggested two fundamental mechanisms for discrimination: statistical discrimination and taste-based discrimination . Taste-based discrimination theory suggests that customers chooses as if there is a dis-utility of associating with a particular racial group. Even with perfect information, taste- based discrimination cannot be eliminated. Unlike taste-based discrimination, statistical discrimination can be eliminated when enough information is shared to signal quality and therefore the value of a prospective purchase to customers, because they can rely on information other than race to update their beliefs about the doctor. A critical test for whether discrimination is statistical in nature is to see whether the introduction of an economically relevant signal closes the racial gap. I seek to distinguish between these forms of discrimination by comparing the willingness to pay penalty for Black or Asian doctors in the case where no quality signals are provided against the case where quality signals are provided. (J71, I11, L15, L86, M31)

Study ID sspp-2021-0025-v1
Authors Alex Chan
Discipline Economics
Field Health Economics, Labor Economics, Experimental Economics
Completion Time 10 Minutes
Close Date Aug. 14, 2021


Citation
Alex Chan. 2021. "Customer Discrimination and Quality Signals: A Field Experiment with Healthcare Shoppers." Social Science Prediction Platform. July 15. https://socialscienceprediction.org/s/2azzy2

Abstract

Example

Study ID sspp-2021-0005-v1
Authors Example
Discipline Economics
Field Applied Econometrics
Completion Time 10 Minutes
Close Date July 30, 2021


Citation
Example. 2021. "Example #4." Social Science Prediction Platform. January 21. https://socialscienceprediction.org/s/24fc2z

Abstract

In 2009-2012, Blattman, Jamison, and Sheridan, worked with the Liberian NGO Network for Empowerment & Progressive Initiative (NEPI) and the research non-profit Innovations for Poverty Action (IPA) to study the impact of a short, inexpensive, intensive therapy program informed by cognitive behavioral therapy (CBT) on young men’s violent and criminal behavior. Cash alone and therapy alone initially reduced crime and violence, but effects dissipated over time. When cash followed therapy, crime and violence decreased dramatically for at least a year (Blattman et al., 2017). Based on these promising findings, as well as those of a similar program in Chicago (Heller et al., 2016), CBT interventions have been replicated around the globe in efforts to reduce violence and criminal behavior. There is no long term evidence on these programs, however. This study is a ten-year follow-up in order to track long-term effects of the CBT and the cash interventions in Liberia.

Study ID sspp-2021-0020-v1
Authors Christopher Blattman, Sebastian Chaskel, Julian Jamison, Margaret Sheridan
Discipline Economics, Psychology, Political Science
Field Applied Econometrics, Development Economics, Econometrics, Health Economics, Experimental Economics, Social Psychology, Cognitive Psychology, Experimental Psychology, Behavioral Economics
Completion Time 10 Minutes
Close Date July 18, 2021


Citation
Blattman, Christopher, Chaskel, Sebastian, Jamison, Julian, and Margaret Sheridan. 2021. "The Long Run Effects of a Program Aimed At Reducing Crime and Violence: Experimental Evidence from Cognitive Behavioral Therapy in Liberia." Social Science Prediction Platform. May 19. https://socialscienceprediction.org/s/4e4000

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Incentive Details

Incentive Type Based on forecast accuracy
Calculation Method Discrete: Fixed payment if forecast is within bounds
Recipient Pool Everyone receives the incentives


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