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The Challenge of Identification and the Value of Descriptive Evidence

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The Palgrave Handbook of Comparative Economics

Abstract

This chapter reviews a number of issues of measurement and methodology that arise in comparative economics. There is a view in economics that the most interesting research in social science is about questions of cause and effect. However, identifying causal relationships poses major difficulties, since the just-identifying restrictions required are non-testable. Given these difficulties, descriptive statistics are not only a pre-requisite for identification of causal relationships but valuable in their own right. The comparative dimension also helps in constructing data-driven counterfactuals such as those produced by the synthetic control method and the panel data approach for evaluating the effect of major systemic changes. This chapter concludes on the benefits of methodological pluralism.

I am grateful to the editors for inviting me to write this piece and for many helpful comments on earlier versions.

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Notes

  1. 1.

    See in this volume Sanfey (Chap. 24) for a review of the literature on the dynamics of life satisfaction in Central and Eastern Europe and the former Soviet Union countries, and Morgan and Wang (Chap. 25) for a discussion of life satisfaction and economic growth in rural and urban China.

  2. 2.

    https://www.amstat.org/asa/files/pdfs/P-ValueStatement.pdf.

  3. 3.

    In a related exercise, Akhmadieva and Smith (2019) look for structural breaks associated with the adoption of the euro.

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Smith, R.P. (2021). The Challenge of Identification and the Value of Descriptive Evidence. In: Douarin, E., Havrylyshyn, O. (eds) The Palgrave Handbook of Comparative Economics. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-50888-3_35

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  • DOI: https://doi.org/10.1007/978-3-030-50888-3_35

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