Conclusion

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 GDP - and those that are research-driven. The former are useful in establishing the size of the sector and in attracting attention from researchers and policy analysts. However, the results presented here suggest that they may be of limited use from a trade research point of view. The reason is that measures of sector size exhibit little systematic relationship with economic outputs and inputs in a cross-country regression framework. Moreover, the relationship between sector size and performance appears to be non-monotonic, which makes it difficult to draw meaningful policy conclusions based on size alone. By contrast, performance measures such as prices generally display a more significant relationship with important economic variables.

The work presented here has three important implications for future research and data collection work in this area. First, the data and analysis presented here has relied on descriptive statistical techniques only. There is clearly major scope to exploit data sources such as national accounts, input-output tables, and firm-level data within the framework of a fully-specific regression problem. Such an approach could properly account for intervening causes, and establish more robust results than those presented here. In tandem with future data collection efforts, it will be important to make better use of existing data sources too.

Second, it is important that future data collection efforts emphasize performance measures rather than size measures. Data on logistics expenditures is important in either case, but the choice of denominator is crucial in terms of making the resulting data most useful for applied trade policy researchers. Ideally, logistics costs should be converted into an ad valorem equivalent - i.e., a percent of the landed price of 45 traded goods - which is the measure trade economists most commonly work with in their models. Alternatively, "pure" performance measures like the LPI can also be used to estimate ad valorem equivalents by applying the Novy methodology.

Third, measures of logistics intensity should also be part of the data and analysis framework moving forward. Some existing work has already focused on logistics costs as a percentage of total costs, which is essentially a measure of intensity. 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.