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국제통상학회
2018-07-17 19:22:18

This study explores approaches to estimate trade effects of non-tariff measures; as such, it is
intended for a technical audience and, in particular, to inform future efforts to improve the trade
policy database for the OECD METRO model.
The term “non-tariff measures” (NTMs) comprise all policy measures other than tariffs and tariffrate
quotas that have a more or less direct incidence on international trade as they affect the price
of traded products, the quantity traded, or both.
A novel method to estimate trade effects of non-tariff measures is presented. It explicitly
distinguishes several types of measures and ascertains their distinct effects on trade volumes and
prices. The latter feature is particularly important as it allows disentangling trade-cost effects
associated with NTMs from possible demand-enhancing effects that come from reducing
information asymmetries and strengthening consumer confidence in imported products.
The price-based estimations yield a large set of ad valorem equivalents (AVEs) that are specific
for bilateral trade between more than 80 countries and roughly 5 000 products. The volume-based
estimates yield information on how NTMs ultimately affect trade: the trade cost associated with
NTMs, as captured by the AVEs, often reduces trade volumes, as expected, but not always. In a
number of cases, in particular in the sanitary and phytosanitary (SPS) area, trade is found to
expand even though trade costs rise. This is likely explained by closer regulatory environments
between those countries, but the trade-enhancing features of such measures merit further study.
While the estimations as such provide a rich source of information on the cost- and volumeeffects
of NTMs they are also intended to be incorporated into the repository of trade policy
information that underpins the OECD METRO model. The precise way to absorb both the trade
costs (as AVEs) and the volume effects in a consistent manner warrants further attention.

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This paper was written by Yvan Guillemette and David Turner. It draws on the previous work on long-term
scenarios referenced below, and on statistical work by Thomas Chalaux and Sylvie Toly. An earlier version of this
paper was discussed at meetings of Working Party No.1 (WP1) of the OECD Economic Policy Committee and the
OECD Economic Policy Committee. The authors would like to thank the meeting participants, as well as Sebastian
Barnes, Luiz de Mello, Åsa Johansson and Zuzana Smidova for comments on earlier versions of the paper.

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