Quantitative Cross-national Research Methods

Gosta Esping-Andersen, Adam Przeworski

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    Quantitative cross-national comparisons usually are based on smaller N's. This implies that theory needs to be stronger and that counterfactuals need to be made explicit. Bayesian estimation is, in this situation, an attractive possibility. Because dependent variables are often categorical or limited, it is often preferable to use nonlinear models, like logit and probit. Selection bias is potentially acute due to nonrandom sampling. This is a problem of identification that usually cannot be overcome by quasi-experimental designs. It calls, again, for strong counterfactual thinking. Cross-national comparisons often cannot assume independence between observations on a variable (nations form 'families'), and this provokes biased coefficients and likely heteroskadisticity. Finally, the article examines the endogeneity problem (. X is influenced by Y, or both jointly by an unobserved Z) which is potentially serious in cross-national comparisons because the meaning of a variable is embedded in the nation's entire history. The bias can derive from variable omission in which case correction calls for added controls. The article also examines the tradeoffs between large-. N and smaller-. N comparisons in terms of generalization and context, and stresses the need for stronger theory the smaller the number of cases being sampled.

    Original languageEnglish (US)
    Title of host publicationInternational Encyclopedia of the Social & Behavioral Sciences: Second Edition
    PublisherElsevier Inc.
    Pages719-724
    Number of pages6
    ISBN (Electronic)9780080970875
    ISBN (Print)9780080970868
    DOIs
    StatePublished - Mar 26 2015

    Keywords

    • Cross-national research
    • Endogeneity
    • Nonindependent units
    • Quantitative methods
    • Selection bias

    ASJC Scopus subject areas

    • Social Sciences(all)

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