Information Disclosure and Performance: The Moderating Role of Incentives

• In Event: Information, Performance Outcomes, and Change in the Public Sector

Abstract

A growing literature on behavioral public administration has devoted to study core questions in the public administration/public management discipline. Some examples include performance information use (Olsen, 2015; Baekgaard and Serritzlew, 2016), trust of civil servants (Van Ryzin, 2011), representative bureaucracy (Riccucci, Van Ryzin and Li, 2016), chief executive decision making (Avellaneda 2013), and transparency (de Fine Licht, 2014). This research has provided important insights on the empirical legitimacy of traditional public administration theories, including the effect of transparency on trust in government and perception of legitimacy (Porumbescu et al, 2017). However, we little know how transparency can shape civil servants’ perceptions and behaviors during implementation, and, through this, improve performance. This study aims to address this gap in the public administration literature. We argue civil servants’ knowledge about the kind and extent of performance information disclosed to citizens should shape civil servants’ behaviors and perception toward program implementation, thus affecting performance. We also argue this relationship is moderated by the type of incentive mechanisms employers use to boost performance: rewards or sanctions.
To test the direct and effect propositions, we will rely on data generated through a survey-experiment that will be applied to street-level bureaucrats implementing a program called Doctor at Your Home (DH) in Mexico City. DH’s goal is to reach underserved patients by providing care in their homes rather than expecting them to come to health centers. Originally, the program targeted only pregnant women in order to address increasing maternal death rates in Mexico City. To explore the reasons behind this high maternity mortality rate, in September 2014 the Mexico City’s Ministry of Health (SEDESA) started to visit each home to identify pregnant women.
In each county of Mexico City, SEDESA’s health centers are in charge of the program implementation. SEDESA has 210 health centers. Each health center has under its responsibility a certain number of neighborhoods, and the advance of the program happens from the most to the less populated neighborhoods, till all of them are covered. Each health center has one DH’s social worker dedicated to visit households looking for pregnant women. During the home visits, social workers advise the mother-to-be to adopt a healthy diet, recommend prenatal care, and explain how identify signs of common pregnancy complications. If the mother-to-be is not receiving prenatal care, the social worker provides her a 48-hour pass to go to her nearest health center for treatment. If unable to attend within that period of time, a physician will visit her to evaluate the overall health of the pregnancy. Based on the evaluation, she is referred to a health center for follow-up prenatal care consults.
DH social worker will be invited to participated in a seminar about transparency and accountability. During the seminar, through a survey, we will assess participants’ knowledge regarding the kind of performance information mandated to be disclosed by the program. In addition, a survey on their perceptions of program’s implementation will be applied to all participants. Afterwards, all subjects will be presented with the same general material about a hypothetical transparency request implemented by the DH program. This requirement will entail posting weekly DH’s performance information by each health center on SEDESA’s web page: number of households visited by each social worker. Subjects will be randomly assigned to one of the following three groups. Control group will receive no additional information regarding the details of the transparency requirement. Treatment group one will receive additional information explaining that the transparency requirement will be complemented with a “pay for performance” policy that will retain 10% of implementer’s salary when performance goals are not achieved. Treatment group two will receive additional information explaining that the transparency requirement will be complemented with a “pay for performance” policy that will increase 10% of implementer’s salary when performance goals are achieved. Finally, participants will receive another survey asking about their perceptions on the implementation of the program.
Using data generated from this survey-experiment and administrative data on performance measures, we will estimate a differences-in-difference (DiD) model comparing outcomes of street-level bureaucrats (both program implementation perceptions and performance measures) in the treatment group to outcomes of street-level bureaucrats in the control group, before and after the experiment. To test the moderating effect of performance incentives on implementers’ perceptions and performance, an interaction term will be added to the DiD specification for each of the treatments.

Authors

• Johabed Georgina Olvera Esquivel, Indiana University

• Claudia N. Avellaneda, Indiana University