Estimating Macro–Relationships Using Micro–Data: A One–Stage Approach

Lauren J. Krivo, Robert L. Kaufman

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Widespread recognition that many sociological processes occur at multiple levels has led researchers to search for valid forms of cross-level modeling such as contextual analysis. In this article, we propose an alternative cross-level method for examining the effects of macro-factors on macro-processes while controlling for processes at a lower-level of aggregation. This method applies existing statistical techniques but in a new fashion. It has the advantages of more precise control for lower-order effects, reduction of problems with degrees of freedom, and more error-free prediction of the higher-level relationships than using alternative estimation strategies. As a result, parameter estimates of the macro-level effects are more efficient. An empirical example studying macro-determinants of unemployment rates in states in the United States demonstrates that estimation of this model leads to more valid conclusions than more commonly used methods.

Original languageEnglish (US)
Pages (from-to)196-224
Number of pages29
JournalSociological Methods & Research
Volume19
Issue number2
DOIs
StatePublished - Jan 1 1990
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Sociology and Political Science

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