Does the message matter? Evidence on the role of reciprocity in municipal tax compliance

• Autores: Salinas Ortiz, José, Serrano Arone, Cristian
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Universidad Nacional de Ingeniería
• Repositorio: Revistas - Universidad Nacional de Ingeniería
• Lenguaje: español; inglés
• OAI Identifier: oai:oai:revistas.uni.edu.pe:article/1415
• Enlace del recurso: https://revistas.uni.edu.pe/index.php/iecos/article/view/1415
• Nivel de acceso: acceso abierto
• Materia: Ciencias del comportamiento; cumplimiento tributario; política pública; contribuyente; tributos municipales; amnistía tributaria; Behavioral sciences; tax compliance.; public policy; taxpayer; municipal taxes; tax amnesty

This research project aims to demonstrate the efficiency of behavioral science tools on municipal tax compliance and public policy issues. Specifically, the impact of treatments carried out on taxpayers in the district of Villa María del Triunfo within a tax amnesty campaign is evaluated using the Differences in Differences model. For this, a sample of 10,000 taxpayers was provided, where the treatment group was given informational letters with messages that appealed to reciprocity, and the control group, letters with a standard message. In addition, from the treatment group, a subsample was taken to carry out a survey in which the perceptions of taxpayers about taxes and municipal management were collected to understand their motivations or barriers that influence the payment or not of taxes. their tributes. The latter was arranged with the purpose of providing greater support to the results of the experimentation. The results indicate an increase of 0.72 percentage points in the tax compliance of the treatment group with respect to the control group. Although it turns out to be a reduced impact due to the context of the pandemic and the tax culture of the district, this is equivalent to an increase of 150 percent in the tax compliance ratio, so it is relevant to continue generating evidence to design better policies.