This chapter consists of 2 parts, which are the literature of Non-Tariff Measures related to frequency ratio and coverage ratio analysis of papers.
3.1. Non-Tariff Measures
The non-tariff measures related articles reviewed in this section that particular technical measures have become a prominent feature in the regulation of international trade in goods. The papers present a review of recent work of both theoretical and the impact of non-tariff measures with a focus on technical regulations.
Fugazza (2013) used a variable data description analysis method to analyze technical regulation, while it was imposed on tariff lines from 1999 to 2010. The bulk of technical regulations are grouped into two major categories, namely sanitary or phytosanitary measures and technical barriers to trade. The former includes regulations and restrictions to protect human, animal or plant life and health, while the latter addresses all other technical regulations, standards, and procedures. SPS measures and TBTs are the objects of two WTO agreements that impose disciplines to trade that go beyond the usual non-discrimination. The objective and legal framework, SPS measures, and TBTs can have important effects on international trade. In terms of incidence, TBTs are by far the most used regulatory measures, with the average country imposing them on about 30 percent of products and trade. Countries also impose SPS measures on an average of approximately 15 percent of trade. The large incidence of TBTs and SPS measures raises concerns for developing country's exports.
Each country involved in trade aim at protecting its economic interests (Anggoro &
Widyastutik, 2016). For example, regarding non-tariff barriers and factors affecting Indonesian cocoa exports in the European Union, problems were discovered when Indonesian commodities entered the European Union region, non-tariff barriers in the form of cocoa quality and quality standards being a factor that became an obstacle, this known as Non-Tariff Measures in the form of Sanitary and Phytosanitary policies and Technical Barriers Trade. The research found that GDP per capita of exporting and importing countries, the economic distance between exporting and importing countries, the exchange rate of exporting countries to importing countries, and
tariffs have a significant effect on Indonesian cocoa export (Anggoro & Widyastutik, 2016). The most influential variable on Indonesian cocoa exports from the estimated gravity model is economic distance with the largest estimated coefficient value. The calculation result of the non-tariff barrier value shows that the highest in Bulgaria.
In addition, Azizah (2015) mentioned that Indonesian crude palm oil exports to the European Union in the 2000-2011 period, had fluctuated for nearly eleven years, therefore the research tried to see what factors influenced the decline in crude palm oil export volume. The export destination countries are Germany, Italy, the Netherlands, Russia, Spain, and Ukraine with the highest number of crude palm oil exports from Indonesia. The commodity of interest in the research was crude palm oil with HS (Harmonized System) code 15111000, the research used panel data secondary data source in the form of the cross-section of six export destination countries in the European Union during the period 2000-2011 (Azizah, 2015). The results showed that the GDP and production variables had a positive and significant effect on the volume of Indonesian crude palm oil exports to the European Union while the price, exchange rate, and RED09 (Renewable Energy Directive 2009) variables did not appear to have a significant effect on the volume of Indonesian crude palm oil exports in the European Union.
The average non-tariff barriers contribute 70% of trade barriers originating from tariffs, while the contribution of non-tariff barriers to trade barriers in general is greater than tariff barriers and protection in the agricultural sector greater than the manufacturing sector. This shows that countries whose export composition depends on agricultural products tend to find greater market access problems when compared to countries that specialize in manufactured products. The study uses the calculation of Trade Restrictiveness Indices as a tool for conducting analysis (Fakhrudin, 2008).
3.2. Frequency Ratio and Coverage Ratio Analysis
The difficulty in analyzing technical regulations essentially originates from the fact that it is measured can have contrasting effects on exports and consumption, and ultimately on welfare.
From the manufacturer's point of view, the big difference between the steps falls into technical regulations types, and other more standard non-tariff measures are the existence of untranslated compliance costs directly becomes changes in production costs and final prices. From a consumer's perspective, however, a technical action is possible to increase import demand if this step is informative (Maskus et al., 2000). A similar analysis applies to non-tariff measures such as variable tax on imports, government procurement regulations or any other activity whose primary purpose is to intentionally limit imports of certain goods through the imposition of world prices according to Baldwin (1991) and Deardorff & Stern (1997).
However, Non-Tariff Measures can generate categories of economic effects that are not prima facing as trade cost effects although they translate into similar impacts on trade prices and quantities (Beghin et al., 2008). This applies to measures as technical barriers to trade and sanitary and phytosanitary measures or anything with technical regulatory content. The rationale or Political reasons or intentions for such measures maybe not necessary protection of local/domestic industries. These categories of Non-Tariff Measures have administrative objectives designed to regulate the domestic market.
The simplest aggregate indicator of Non-Tariff Measures is the frequency ratio and coverage ratio (Fugazza, 2013). The frequency ratio is a share of the total tariff lines containing one or more Non-Tariff Measures. The coverage ratio is the percentage of imports affected by one or more Non-Tariff Measures to total imports. This inventory measure allows summarizing information about Non-Tariff Measures collected at the level of disaggregation in one indicator.
The frequency ratio accounts only for the presence or absence of a Non-Tariff Measures and summarizes the percentage of products to which one or more Non-Tariff Measures is applied. A measure of the importance of Non-Tariff Measures on overall imports is given by the coverage ratio which measures the percentage of trade subject to Non-Tariff Measures for the importing country. The immediate advantage of the instrument is the relative ease that can be collected, in essence not much more difficult than compiling tariff schedules. Inventories of non-tariff measures do represent valuable information that could, if updated regularly, help track of the
evolution of the relative occurrence of various types of non-tariff measures on the flow of trade in goods, and about the evolution of events relative to tariffs.
Disdier et al. (2008) found that non-tariff measures have negative or insignificant impacts of technical barriers to trade and sanitary and phytosanitary measures on agricultural and food aggregate trade amongst the Organization for Economic Cooperation and Development (OECD) countries. However, they also find that trade from developing countries towards OECD countries does see a significant reduction because of non-tariff measures. The originality of their approach lies in the fact that they investigate the impact of non-tariff measures using different proxies for the incidence of the latter. Fontagne et al. (2005) and others further underline that the direction and the significance of trade effects of technical measures appear to differ considerably across product groups and trading partners.
Referring to Fugazza (2013), this study analyzed the change in Indonesian trade cooperation with trading partner countries (European Union, US, Japan, China, and Australia) in order to demonstrate the importance of technical measures in policy using the Frequency Ratio and Coverage Ratio. This study applied trade data for the following year: 2000, 2002, 2003, 2005, 2007, 2010, 2011, 2012, 2013, 2014 and 2015. The years selected are to explore the impact and changes in Indonesian trade cooperation. Their trade cooperation shall be discussed in the later chapter of this study.