EconPapers    
Economics at your fingertips  
 

Analyzing Computational Models

David A. Siegel

American Journal of Political Science, 2018, vol. 62, issue 3, 745-759

Abstract: Computational models have been underutilized as tools for formal theory development, closing off theoretical analysis of complex substantive scenarios that they would well serve. I argue that this occurs for two reasons, and provide resolutions for each. First, computational models generally do not employ the language or modes of analysis common to game‐theoretic models, the status quo in the literature. I detail the types of insights typically derived from game‐theoretic models and discuss analogues in computational modeling. Second, there are not widely established procedures for analysis of deductive computational models. I present a regularized method for deriving comparative statics from computational models that provides insights comparable to those arising from game‐theoretic analyses. It also serves as a framework for building theoretically tractable computational models. Together, these contributions should enhance communication between models of social science and open up the tool kit of deductive computational modeling for theory building to a broader audience.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/ajps.12364

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:amposc:v:62:y:2018:i:3:p:745-759

Access Statistics for this article

More articles in American Journal of Political Science from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:amposc:v:62:y:2018:i:3:p:745-759