This paper examines the issue of measuring logistics costs from an applied trade policy research perspective, as well as identifying logistics-intensive sectors. It focuses on currently available data at the macro-and firm-levels. This paper has two main aims. First, it provides a first overview of currently available data relevant to logistics, and suggests some preliminary applications. The second objective of this paper is to frame the issue of logistics cost measurement and data collection in terms of the types of inputs needed for applied trade policy research. The paper is organized as follows. The next section presents an overview of possible directions in applied trade policy research using logistics data. Section three examines existing data sources that can be used to measure domestic logistics costs, focusing on the national accounts, input-output tables, price comparisons, and firm-level data. Section four presents a new methodology for measuring international trade costs, and identifies the proportion of those costs due to logistics. Section five uses input-output data to identify logistics-intensive sectors in a range of countries. Section six concludes. This paper has explored a number of different data sources and methodologies in an effort to move forward on the analysis of logistics costs from a trade policy research perspective. In the future, it will be important to distinguish between data collection efforts that are industry-driven-such as estimates of total logistics costs in Gross Domestic Product (GDP)-and those that are research-driven. Moving further in this direction will help fuel research that identifies sectors in particular countries that are most sensitive to improvements in logistics performance, and which therefore will tend to expand relative to other sectors in the face of logistics sector reforms. From a policy and political economy point of view, it will be important to identify such sectors and make them aware of the potential role logistics can play in facilitating their growth.