Gravity Redux: Measuring International Trade Costs with Panel Data

Article excerpt


International trade has grown enormously over the last few decades, and almost every country trades considerably more today than 30 or 40 years ago. One reason for this increase in trade has undoubtedly been the decline in international trade costs, for example, the decline in transportation costs and tariffs. But which countries have experienced the fastest declines in trade costs, and how big are the remaining barriers? These questions are important for understanding what impedes globalization, yet we know surprisingly little about the barriers that prevent international market integration.

This paper sheds light on these issues by developing a way of measuring the barriers to international trade. I derive a microfounded measure of aggregate bilateral trade costs that I obtain from the gravity equation. As a workhorse model of international trade, the gravity equation relates countries' bilateral trade to their economic size and bilateral trade costs, and it has one of the strongest empirical track records in economics. The core idea of the paper is to analytically solve a theoretical gravity equation for the trade cost parameters that capture the barriers to international trade. The resulting solution expresses the trade cost parameters as a function of observable trade data and thus provides a micro-founded measure of bilateral trade costs that can be tracked over time. The measure is useful in practice because it is easy to implement empirically with readily available data.

The advantage of this trade cost measure is that it captures a wide range of trade cost components. These include transportation costs and tariffs but also other components that can be difficult to observe such as language barriers, informational costs, and bureaucratic red tape. (1) While it would be desirable to collect direct data on individual trade cost components at different points in time and add them up to obtain a summary measure of trade costs, this is hardly possible in practice because of severe data limitations. The trade cost measure derived in this paper avoids this problem by providing researchers with a gauge of comprehensive international trade costs that is easy to construct. It can be helpful not only for studying international trade but also for other applications that require a time-varying measure of bilateral market integration.

The approach taken in this paper has a strong theoretical foundation. I show that inferring trade costs indirectly from trade data is consistent with a large variety of leading international trade models. Head and Ries (2001) were the first to derive such a trade cost measure based on an increasing returns model of international trade with home market effects and a constant returns model with national product differentiation. I extend their approach by showing that the trade cost measure can be derived from a broader range of models, in particular the well-known gravity model by Anderson and van Wincoop (2003), the Ricardian model by Eaton and Kortum (2002), as well as the heterogeneous firms models by Chaney (2008) and Melitz and Ottaviano (2008). Although these models make fundamentally different assumptions about the driving forces behind international trade, they have in common that they yield gravity equations in general equilibrium. (2) I exploit this similarity and demonstrate that all these models lead to an isomorphic trade cost measure. The intuition is that gravity equations are basic expenditure equations that indicate how consumers allocate spending across countries under the constraints of trade barriers. The motivation for purchasing foreign goods could be that they are either inherently different from domestic goods as in an Armington world, or they are produced relatively more efficiently as in a Ricardian world. I show formally that for the purpose of measuring international trade costs, it does not matter why consumers choose to spend money on foreign goods. …


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