A Dynamic Measure of Bureaucratic Reputation: New Data for New Theory

Abstract

Bureaucratic reputation is one of the most important concepts used to understand the behavior of administrative agencies and their interactions with multiple audiences. Despite a rich theoretical literature discussing reputation, we do not have a comparable measure across agencies, between countries, and over time. I present a new strategy to measure bureaucratic reputation from legislative speeches with word‐embedding techniques. I introduce an original dataset on the reputation of 465 bureaucratic bodies over a period of 40 years, and across two countries—the U.S. and the U.K. I perform several validation tests and present an application of this method to investigate whether partisanship and agency politicization matter for reputation. I find that agencies enjoy a better reputation among the members of the party in government, with partisan differences less pronounced for independent bodies. Finally, I discuss how this measurement strategy can contribute to classical and new questions about political–administrative interactions.

Do reputational threats influence the rigidity of US agencies? A dynamic panel data approach

“…For this reason, Bellodi (2022) took several measures to ensure the validity of the data. Multiple quantitative and qualitative tests were performed to confirm that (a) the reputation estimates reflect critical events, (b) correlate with public opinion data, and (c) with reputation estimates derived from newspaper articles (Bellodi, 2022, 8–11). In addition, we know from political‐agenda setting studies that a substantial overlap exists between the parliamentary agenda and the media agenda and public opinion (Burstein, 2003; Vliegenthart et al, 2016).…”

“…This explains why most reputation scholarship has limited itself to non‐comparative and/or non‐longitudinal designs, which poses external validity concerns (Boon et al, 2021). This paper overcomes this limitation by building on the recently developed and validated reputation data from Luca Bellodi (2022), published in the American Journal of Political Science. Exploiting recent advancements in natural language‐processing techniques, word‐embedding techniques were used to estimate the reputation of 465 public organizations from more than 4.5 million parliamentary speeches over a period of almost 40 years.…”

“…This paper would not have been possible without the previous data collection efforts of Luca Belllodi (see Bellodi, 2022) and Anthony Bertelli, Dyana Mason, Jennifer Connolly, and David Gastwirth (see Bertelli et al, 2015). We thank them for their efforts and willingness to make their data publicly available.…”

“…First, scholars have looked at the evolution of reputational sentiment towards the organizations. Reputations have stronger repercussions and hence create organizational unrest, as the aggregated sentiment towards organizations evolves more negatively (Bellodi, 2022; Salomonsen et al, 2021). Second, scholars have complemented the sentiment focus with an interest in the organizational domain that is targeted.…”

The benefits of nonprofit reputation: Government funding, nonprofit performance, and nonprofit reputational gains

“…As such, the IDSM is an excellent proxy of the reputations of different hospital providers among these two audiences. Indeed, reputation has previously been captured using survey data (e.g., Lee and Van Ryzin 2018) or language media analysis (Bellodi, 2022;Peci, 2021).…”