There is a sizable and swiftly growing literature that makes use of non-tariff measures (NTMs) in numerous ways. In order to appreciate the available data, it is useful to put it into the context in which it is used. This is the purpose of the called the Methodology INnventory Database on NTMs (MIND). The OECD defines NTMs as “measures other than normal tariffs which have the effect of restricting trade between nations,” however, we adopt an even broader definition that also includes policies that promote trade as well as those that can have both effects (such as a safety standard which is costly to meet but allays consumer concerns over the product’s quality). With this broad definition the volume of existing research is not surprising. The MIND then serves as an entry point for researchers working on NTMs by classifying relevant existing work which may be of use in their own studies which then points the way towards recognizing the existing relevant literature, best practice, common difficulties and ways to overcome them, and innovative techniques.

As the basis for this classification, three overarching descriptions of the research prove useful. First, there is the purpose of the study, that is, the goal the researcher had in mind when carrying out the analysis. Second, there is the perspective of the study which describes whether it is “backwards looking” and using data on what has already happened or predictive and trying to provide an estimate of future NTMs and their relationship to the economic environment. Third, there is the scope, which boils down to whether the study looks at a partial equilibrium setting that focuses on a small number of sectors or whether it considers broader, general equilibrium-type effects. Given the broad notions of these categories, some papers can fit multiple categories, nevertheless to maintain a streamlined categorization, users should be cognizant of such matters.

In setting up the classification, the key determinant of the way in which an NTM is used in a study was the purpose of the study, that is, the goal the researcher had in mind. Here, the classification identifies four purposes: 1) construct an alternative measure of an NTM (e.g. the construction of ad valorem equivalencies), 2) consider the outcome from NTM use (e.g. their impact on trade flows), 3) examine the determinants of NTM use (e.g. the political economy of NTM use), and 4) provide a literature review.

The second key descriptor of a particular study is its perspective. Here, we use two categories: retrospective and predictive. A retrospective study is one that considers past events. Some methods of analysis, such as regressions, are by their nature retrospective because they require data on events and variable realizations that have already happened in order to carry out the method. Others, such as CGE modelling, are usually predictive as they seek to provide estimates of potential outcomes for events that have yet to occur, such as a proposed reduction in NTMs. Note that predictive studies include both simulations and out-of-sample predictions.

The third overarching description captures the scope of a study. We classify papers into two groups: partial equilibrium and general equilibrium studies. The key distinction between the two is whether or not spillovers between sectors, firms, or countries play a role. When a given paper focuses on one industry, such as when it estimates the impact of SPS NTMs on beef trade, this clearly falls into the partial equilibrium category. Sometimes a study may include several sectors by, for example, considering how NTMs affect a variety of agricultural products but it nevertheless does not consider interactions between the products (as might occur due to impacts on intermediate goods prices or via input-output tables). This too would be a partial equilibrium study. In contrast, a general equilibrium study has interactions between observations at its heart. This is most obvious in a CGE study where sectors are linked via an input-output table.

For a fuller discussion of the classification system, including further sub-classifications and numerous illustrative examples, see Davies, Rau, and Vogt (2015), "A Methodology Inventory for Studies Using NTM Data" . The MIND itself can be found here.