Indicators & Measurement
Identifying and measuring NTMs
NTMs are described by the detailed measure (according to the MAST classification), the country imposing the measure and the country affected as well as the products that are subject to the measure. In some case the time dimension is provided, especially if measures are temporarily imposed, but usually the date of issuing the regulation that contains the provision of the respective NTM is given. Thus, even if a measure is identified the NTM data usually do not convey information about the implementation and enforcement of the measure.
Information on NTM can take different forms. Usually they are the following:
- Binary variables that indicate whether a measure is there or not. These can be simply in the form of 1/0, or yes/no;
- Numerical variables reflecting quantitative attributes of an NTM, e.g. percentage of foreign equity ownership, maximum residual limits, or maximum weight;
- Text that can be a plain description of a regulation (required info on a label, container clearance procedures, etc.), usually the link to the regulatory text is provided. Sometimes also the date of entry into force is provided, which adds important information in particular for ad hoc emergency or temporary measures;
- Categorical variables are used to classify measures, e.g. whether a measure is discriminatory or not;
- Ordinal variables indicating a ranking along a chosen dimension, e.g. a five-point scale of openness from “open without restrictions” to “completely closed” or to signal the status of implementation (not/partially/fully implemented), as well as the perceived restrictiveness of a measures in business surveys;
- Computed indicators combining different information contents, e.g. restrictiveness indexes, count or frequency ratios.
In inventories of regulations, the available NTM data point out if a measure is in place or not. This information thus comprises a dummy (0/1) while usually details on the regulatory text and references are also provided. If possible, the number of measures imposed is provided in frequency indicators. Note that such frequency indicators is prone to double counting, depending on the level of aggregation of products and measures, and does not imply the effect of measures. For example, one measure could entirely hamper trade if prohibitive. Thus the number of measures does not necessarily lead to a more pronounced effect, although there may be an accumulative effect if several measure are in place.
In addition, surveys, questionnaires or complaint registers for business are used to identify NTMs and the issues that firms face when selling on foreign markets. Surveys provide information about which measures matter for businesses and can also be used to gauge information about the perceived restrictiveness from the respective firm’s perspective. In surveys, the issues associated with specific measures are identified, and they are often procedural obstacles that relate to the implementation of measures rather than the measure itself.
Assessing the NTM impact
The analysis of NTMs aims to provide insights about the impact of measures. Such analyses impact crucially rely on NTM data that are used and transformed in order to measure the respective measures or groups of measures. They are indicators of NTMs, such as counts and frequency measures, restrictiveness indices.
The NTM impact concerns the quantity and price effect of measures. First of all, the quantity of products exported/imported subject to NTMs can be compared to the situation of no NTM being in place. Quantity effects are empirically determined by econometric models, usually gravity-type models.
Similarly, the price of a product subject to a NTM is compared to the price of the product without an NTM in order to ascertain the trade cost or compliance costs due to the respective NTM under review. Price comparisons are usually referred to as the handy-craft price gap method, if econometric models are not applied.
Price effects can be expressed as estimates of ad-valorem equivalents of NTMs that are commonly used in simulation models, both partial and general equilibrium models. In the simulation of trade agreements, the reduction of certain barriers due to “actionable” NTMs is depicted as reduced iceberg tariffs that describe the relation between the price of a product exported and the price of the same product as import of the country imposing the NTM.
Such simulation models generate estimates of the outcomes from proposed policy changes to provide guidance on whether they ought to be implemented, given the insights about who actually pays and benefits from the measures in place.