<p>This study examines the impact of Non-Tariff Measures (NTMs) on agricultural Global Value Chain (GVC) trade using a quasi-experimental approach. The objective is twofold. First, it seeks to test and identify the presence of self-selection and non-linearities in the relationship between NTMs and GVC trade and to address these issues methodologically. Second, it aims to demonstrate that NTMs influence agricultural GVC trade not only through a direct effect on the affected country but also via an indirect impact, both on the imposing country and on all partners involved in GVC linkages, creating a "chain effect". Using a panel dataset on distinct types of NTMs and trade in value-added rather than gross trade across 172 countries, with a focus on agriculture, the analysis reveals that NTMs significantly affect GVC trade. Most NTMs generally hinder agricultural trade, particularly at both low and high levels of intensity, as observed with technical barriers and sanitary measures. Other NTMs have a positive impact at low intensity, which becomes negative as intensity increases. The study further underscores the non-linear nature of this relationship, emphasizing the need to account for self-selection, heterogeneity, and intensity of NTMs to refine estimates of their effects. These findings also inform policy discussions on the suitability of adopting such measures and their potential unintended consequences.</p>

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Evaluating the causal impact of non-tariff measures on agricultural global value chain trade using matching econometrics

  • Silvia Nenci,
  • Davide Vurchio

摘要

This study examines the impact of Non-Tariff Measures (NTMs) on agricultural Global Value Chain (GVC) trade using a quasi-experimental approach. The objective is twofold. First, it seeks to test and identify the presence of self-selection and non-linearities in the relationship between NTMs and GVC trade and to address these issues methodologically. Second, it aims to demonstrate that NTMs influence agricultural GVC trade not only through a direct effect on the affected country but also via an indirect impact, both on the imposing country and on all partners involved in GVC linkages, creating a "chain effect". Using a panel dataset on distinct types of NTMs and trade in value-added rather than gross trade across 172 countries, with a focus on agriculture, the analysis reveals that NTMs significantly affect GVC trade. Most NTMs generally hinder agricultural trade, particularly at both low and high levels of intensity, as observed with technical barriers and sanitary measures. Other NTMs have a positive impact at low intensity, which becomes negative as intensity increases. The study further underscores the non-linear nature of this relationship, emphasizing the need to account for self-selection, heterogeneity, and intensity of NTMs to refine estimates of their effects. These findings also inform policy discussions on the suitability of adopting such measures and their potential unintended consequences.