Means and ends : a comparative study of empirical methods for investigating governance adn performance
By: HEINRICH, Carolyn J
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Contributor(s): LYNN, Laurance E., Jr.
Material type: 
ArticlePublisher: 2001Journal of Public Administration 11, 1, p. 109-138Abstract: Scholars employ a wide range of empirical approaches to understand how, why, and with what consequences government is organized and managed. We review recent statistical modeling efforts in governance research and assess recent advances in quantitative research designs. We then estimate models of government performance, using three statistical approaches: multilevel (hierarchical linear) models;ordinary least squares (OLS) regression models using individual level data; and OLS models using outcome measures aggregated at the site or administrator level. We show that multilevel approaches produce a fuller and more precise understanding of complex, hierarchical relationship in government, more information about the amount of variation explained by statistical models at different levels of administration, and increased generalization of findings across different sites or organizations
| Item type | Current location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
| Periódico | Biblioteca Graciliano Ramos | Periódico | Not for loan |
Scholars employ a wide range of empirical approaches to understand how, why, and with what consequences government is organized and managed. We review recent statistical modeling efforts in governance research and assess recent advances in quantitative research designs. We then estimate models of government performance, using three statistical approaches: multilevel (hierarchical linear) models;ordinary least squares (OLS) regression models using individual level data; and OLS models using outcome measures aggregated at the site or administrator level. We show that multilevel approaches produce a fuller and more precise understanding of complex, hierarchical relationship in government, more information about the amount of variation explained by statistical models at different levels of administration, and increased generalization of findings across different sites or organizations
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