What is it about?
This study introduces a groundbreaking methodological framework to analyze employment dynamics within public agencies, focusing on two key dimensions: turnover and longevity. Using advanced statistical tools such as linear mixed models, Cox survival models with shared frailty, and Propensity Score Matching (PSM), the research provides new insights into how government transitions and workforce composition shape employment stability across different state agencies. A core innovation of this work is the development of two novel indices—Service Hazard Rate (SHR) and Relative Turnover Difference (RTD)—that map agency heterogeneity by quantifying both long-term structural stability and short-term politically induced volatility. These tools enable the identification of key patterns across agencies, revealing how structural and political factors drive differences in public sector dynamics. Importantly, all R code used for this study is openly available for full reproducibility at [GitHub](https://github.com/mauricio-herrera/Mapping_Employment_Dynamics_in_Public_Agencies_with_Payroll_Data), making it a highly accessible and transparent resource for researchers and practitioners alike. This research offers actionable insights for policymakers and comparative researchers interested in enhancing state capacity and public sector governance.
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Why is it important?
This research addresses a critical gap in understanding how public sector agencies respond to political transitions and what drives workforce stability. By introducing innovative indices—Service Hazard Rate (SHR) and Relative Turnover Difference (RTD)—the study provides a nuanced approach to mapping agency heterogeneity, highlighting differences in long-term stability and politically driven volatility. These insights are vital for policymakers and scholars interested in improving governance, as they reveal how structural factors and political dynamics shape the effectiveness of public administration. The methodological framework developed in this study is not only robust but also highly replicable, enabling its application in diverse national contexts and fostering a deeper, comparative understanding of state capacity and workforce management. This makes the research a valuable resource for advancing both theoretical knowledge and practical reforms in public sector governance.
Perspectives
As a researcher, I find this study particularly meaningful because it bridges the gap between theory and practice. Mapping employment dynamics in state agencies has long been a challenge due to the lack of replicable, data-driven methodologies. This publication not only addresses that challenge but also introduces tools and metrics that are both innovative and actionable. For me, the most exciting aspect is how the findings reveal the intricate ways in which political transitions impact agency stability, a topic that is often discussed anecdotally but rarely quantified with such rigor. I believe this work has the potential to inspire future research and policy discussions, particularly in contexts where improving state capacity is a pressing issue. It’s rewarding to contribute to a study that pushes the boundaries of how we analyze and understand public sector stability and its implications for effective governance.
Mauricio Herrera
Universidad del Desarrollo
Read the Original
This page is a summary of: Mapping employment dynamics in public agencies with payroll data: A methodological framework with an application to Chile, PLOS One, December 2024, PLOS,
DOI: 10.1371/journal.pone.0316386.
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