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Governance Indicators and the Level of Analysis Problem: Empirical Findings from South America

Published online by Cambridge University Press:  25 September 2012

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Abstract

Studies of the link between state capacity and development often utilize national-level governance indicators to explain fine-grained development outcomes. As capacity in some bureaucratic agencies matters more for these outcomes than capacity in others, this work proxies for capacity within the set of relevant agencies by using a measure of ‘mean’ capacity across all agencies in a polity. This practice is problematic for two reasons: (1) within-country, cross-agency diversity in capacity often overwhelms the variation encountered across public sectors considered in their entireties; (2) national-level reputations for capacity are not particularly informative about differences in capacity in functionally equivalent agencies in different countries. The article draws on the author's survey of public employees in Bolivia, Brazil and Chile to establish these points.

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Articles
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Copyright © Cambridge University Press 2012 
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Table 1Partial List of Studies Using Perception-based Governance Indicators to Examine the Relationship between Bureaucratic Capacity and Narrowly Defined Development Outcomes*

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Table 2Ranking and Percentile of the Three Cases on Cross-national Measures of Bureaucratic Effectiveness and Corruption

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Table 3Two-way Analysis of Variance for Questions on Politicization, the Institutionalization of Bureaucratic Career Paths, and Corruption Control

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Fig. 1Agency-level diversity in each polity in perceptions of politicization of personnel matters

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Fig. 2T-statistics from pairwise regressions of agency-level response rates on agency-level average responses to questions about bureaucratic capacity Note: Black circles denote t-statistics corresponding to the coefficient on (the average value of) responses for a given question about bureaucratic capacity. Vertical gray lines denote the 95% threshold for statistical significance.

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Table 4Sister Agencies (as Determined by Administrative Function)

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Fig. 3Q–Q plots of perceptions of Weberianism in sister institutions (as determined by administrative functions). Note: See Table 4 for the list of agencies being compared in each plot: p-val K–S test refers to the probability of the null hypothesis that the distributions of the factor scores being compared are equal (according to the two-sample Kolmogorov–Smirnov test).

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Table 5Logit Models of Relationship between Public Examinations and Authority over Public Contracts, Licences and Loans

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Fig. 4Estimated average predictive comparisons for the probability of having authority over public contracts (upper panel) and the allocation of licences and loans (lower panel) as a function of having one's job through a public examination (Brazilian agencies only). Note: Impact of having obtained one's post via a public examination on authority over contracts, licences and loans is allowed to vary in the logistic regression models across two agency types: agencies with low Weberian perception scores (DNIT, INSS) and agencies with high perception scores (BCdoB, RF, ANTT, CODEVASF, INCRA, MDA, MDS). Displayed in the figure are the estimated average predictive comparisons associated with having taken a public examination, broken down according to agency type.

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Table 6Logit Models of Bureaucratic Quality and Systematic Banking Crises in the 1990s (Bank Regulator-specific Measure Compared to Omnibus Measure)

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