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A Framework for Unifying Formal and Empirical Analysis

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  • Jim Granato
  • Melody Lo
  • M. C. Sunny Wong

Abstract

An important disconnect exists between the current use of formal modeling and applied statistical analysis. In general, a lack of linkage between the two can produce statistically significant parameters of ambiguous origin that, in turn, fail to assist in falsifying theories and hypotheses. To address this scientific challenge, a framework for unification is proposed. Methodological unification leverages the mutually reinforcing properties of formal and applied statistical analysis to produce greater transparency in relating theory to test. This framework for methodological unification, or what has been referred to as the empirical implications of theoretical models (EITM), includes (1) connecting behavioral (formal) and applied statistical concepts, (2) developing behavioral (formal) and applied statistical analogues of these concepts, and (3) linking and evaluating the behavioral (formal) and applied statistical analogues. The elements of this EITM framework are illustrated with examples from voting behavior, macroeconomic policy and outcomes, and political turnout.

Suggested Citation

  • Jim Granato & Melody Lo & M. C. Sunny Wong, 2010. "A Framework for Unifying Formal and Empirical Analysis," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 783-797, July.
    • Handle: RePEc:wly:amposc:v:54:y:2010:i:3:p:783-797
    DOI: 10.1111/j.1540-5907.2010.00460.x
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    2. Pei-Tha Gan, 2019. "Economic uncertainty, precautionary motive and the augmented form of money demand function," Evolutionary and Institutional Economics Review, Springer, vol. 16(2), pages 397-423, December.

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