The Gravity of Intermediate Goods


One of the puzzles of the gravity literature is the persistent effect of distance on trade flows, despite the dramatic fall in trade costs during the last few decades (Disdier and Head in Rev Econ Stat 90(1):37–48, 2008). A possible reason for the “distance puzzle” is that trade in intermediate goods—which has risen dramatically during this period due to the emergence of global value chains—may be more sensitive to distance than trade in final goods. Using a dataset of bilateral import flows that covers 5000 products and more than 200 countries over the 1998–2011 period, we show that intermediate goods are indeed more sensitive to distance than are final goods and that differentiated inputs exhibit the highest distance elasticity. The results are robust to including different sets of controls, and using different samples and econometric methodologies. They suggest that sourcing inputs from nearby countries helps final good producers to coordinate with their suppliers, monitor their production, and ensure the timely delivery of inputs that need to be tailored to their needs.

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  1. 1.

    Our analysis builds on earlier studies that have estimated gravity regressions at the product or sectoral level (e.g., Anderson and Yotov 2010; Imbs and Mejean 2017).

  2. 2.

    Final goods thus comprise both capital and consumption goods. We drop from our analysis those goods that are considered “mixed’ in the BEC classification.

  3. 3.

  4. 4.

    From Eq. (1), the effect of intermediates on imports is \(\frac{\partial ln (\textit{Imports}_{ijk})}{\textit{Intermediate}_k} = \beta _1 \times ln{(Distance)}_{ij} + \beta _2\). It is straightforward to verify that this effect becomes negative when the distance between countries i and j is above a certain threshold. In the specification of column 1 of Table 2, this threshold is around 2500 km, implying that countries that are further apart trade more in final goods than in intermediate goods.

  5. 5.

    Raw materials correspond to 575 HS6 codes in our sample. Of these, 379 are intermediate goods: some are homogeneous (e.g., oil, fertilizers, copper), while others are differentiated (e.g., glass containers, live animals, plants and parts, including seeds and fruits). The remaining products are final goods: some are homogeneous (e.g., frozen fish fillets, frozen shrimps and prawns), while others are differentiated (e.g., fish meat, mackerel).

  6. 6.

    For example, if we included zeros in column 1 of Table 8, they would account for almost 98% of the sample (the number of observations would increase from 4,785,880 to 222,746,370). We have nevertheless tried to reproduce Tables 8, 9 and 10, with the inclusion of zeros in the dependent variable. The results confirm that intermediate goods are more sensitive to distance than are final goods—particularly when eliminating raw materials. However, the role of product differentiation is less clear-cut (intermediate goods are more sensitive to distance than only two of the three other categories of products).


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We are grateful for the comments and suggestions of Peter Egger, Mathieu Parenti, André Sapir, and seminar and conference participants at ECARES, EUI, and Warsaw School of Economics. Paola Conconi gratefully acknowledges financial support from the FNRS and the ERC (Project 834253—TRASC) and the European Union’s Horizon 2020 research and innovation programme (Agreement Grant No. 770680).

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Conconi, P., Magerman, G. & Plaku, A. The Gravity of Intermediate Goods. Rev Ind Organ (2020).

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  • Distance
  • Final goods
  • Intermediate goods
  • Product differentiation

JEL Classification

  • F14
  • F23