Reducing the replication time for structural estimations: A successful replication of "An Anatomy of International Trade" using GPU computing.

Eaton, Kortum, and Kramarz (2011) (EKK) discovered empirical patterns from French manufacturing firms that a baseline firm heterogeneity model could not explain. The authors proposed and estimated a model that closely matches the patterns observed in French data. This paper successfully replicates t...

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Publicado en:Economic Inquiry Vol. 63; no. 2; pp. 424 - 441
Autor principal: Zhong, Jiatong
Formato: Artículo
Publicado: Wiley-Blackwell Apr2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Reducing the replication time for structural estimations: A successful replication of "An Anatomy of International Trade" using GPU computing.
      aug:
        au: Zhong, Jiatong
        affil: Department of Economics, University of Alberta, Edmonton Alberta, , Canada
      su:
        International trade
        Heterogeneity
        Graphics processing units
        Algorithms
        Anatomy
      sug:
        subj:
          International trade
          Heterogeneity
          International Trade Financing
          Graphics processing units
          Algorithms
          Anatomy
      keyword:
        economic methodology
        international trade
        replication
        economic methodology
        international trade
        replication
      ab: Eaton, Kortum, and Kramarz (2011) (EKK) discovered empirical patterns from French manufacturing firms that a baseline firm heterogeneity model could not explain. The authors proposed and estimated a model that closely matches the patterns observed in French data. This paper successfully replicates their findings using author‐provided data, re‐implementing their algorithms in Python and leveraging graphics processing unit computing to significantly boost computational speed. Applying the model to Chinese manufacturing data, despite differences in context, showed that the model explains most observed patterns well.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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