Resultados de investigación

Governments, political parties and public institutions regularly design and launch communication campaigns emphasising their successes, fostering participation in democratic acts, promoting the use of public services and seeking to boost electoral support. Accordingly, researchers in the fields of politics and public administration have long sought to enhance our understanding of how individuals perceive the performance of services offered by the private and public sectors. In this respect, conflicting findings have been reported: some studies affirm there is an anti-public sector bias, others detect a preference towards public-sector providers, and some have found no evidence of a sector bias, pro or anti. We believe it crucially important to understand the mechanisms underlying sector bias, if it exists. To address the current research gap in this area, we make use of theories and tools drawn from neuropolitics (namely, functional Magnetic Resonance Imaging, fMRI) to elucidate the neurobiological foundations of perceptions regarding the performance of public-sector service providers. The neural findings obtained reveal that brain networks associated with reward and positive values provide a neurobiological explanation for pro-public sector bias, while neural mechanisms linked to aversion, risk, ambiguity and motivated reasoning are associated with an anti-public sector bias. The implications of these findings should be considered by policymakers; for example, to promote acceptance of public-sector service provision, people must be clearly informed about the goals achieved and other positive aspects.

Bases de datos utilizadas en un trabajo de investigación, 6 bases de datos en SPSS

Dataset with quality and quantity labour indicators and the number of refugees in host Middle Eastern countries (Egypt, Iran, Lebanon, Jordan and Turkiye) from 1991 to 2021. Data are collected from World Bank Open data and the statistics on working poverty by ILOSTAT. It includes: Refugee ratio (as a percentage of the total population of each country); Official development assistance. Quantitative labour market indicators: unemployment rate, labour force, number of own-account workers. Qualitative labour market indicators: distribution of employment by income level in developing countries.

Base de datos de la Encuesta de Empleo del Tiempo 2010 y de la Encuesta de Estructura Salarial, En formato Stata. Database of Time Use Survey 2010 (TUS_2010) and Wages Survey (WS_2018). Stata format.

This work was supported by grant CTQ2017–85658-R funded by MCIN/AEI/10.13039/501100011033/ FEDER “Una manera de hacer Europa” and grants PID2019–104366RB-C22 and PID2020–114256RBI00 funded by MCIN/AEI/10.13039/501100011033