2001Journal of Public Administration Research and TheoryOpen access

Means and Ends: A Comparative Study of Empirical Methods for Investigating Governance and Performance

Carolyn J. Heinrich, L. E. Lynn

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Abstract

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 relationships in government, more information about the amount of variation explained by statistical models at different levels of administration, and increased generalizability of findings across different sites or organizations.

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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 relationships in government, more information about the amount of variation explained by statistical models at different levels of administration, and increased generalizability of findings across different sites or organizations.

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Available abstract

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 relationships in government, more information about the amount of variation explained by statistical models at different levels of administration, and increased generalizability of findings across different sites or organizations.

Key concepts: Generalizability theory, Ordinary least squares, Multilevel model, Econometrics, Government (linguistics), Corporate governance, Statistical model, Empirical research

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