The author would like to express gratitude to the creators of the handbook on indicators for trade facilitation that had collected all the references and the data sources available on all the trade facilitation measures. Seven international organizations collect the data on trade that is publically available and can be used for the research. They are: the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), the Organization for Economic Cooperation and Development (OECD), the Asian Development Bank (ADB), in collaboration with World Bank (WB), International Trade Centre (ITC), World Customs Organization (WCO), United Nations Conference on Trade and Development (UNCTAD). The handbook collected the data sources with all the necessary data on trade related issues. It is a comprehensive source of information on publically available cross-country databases and indicators. All the datasets used fell into one of the three components of the Trade Facilitation: Customs and Other Regulatory Trade Procedures, Trade and Transport Infrastructure, Trade-related services. In the appendices, the author included the table of contents by source to show the full range of datasets available on the matter. The author used five aggregate databases to obtain information. The most valuable is the OECD Trade Facilitation Indicators database ; it covers all the indicators that fall into the category of trade facilitation measures that were included in the WTO Trade Facilitation Agreement (TFA). There are 133 variables that compose 11 trade policy sectors, which are Information availability; Consultations; Advance rulings; Appeal procedures; Fees and charges; Documentation requirements; Automation of border procedures; Streamlining of border processes; Domestic border agency cooperation; Cross-border agency cooperation; Governance and Impartiality. It is updated every two years and was first launched in 2013. The last updated dataset of 2017 covers 163 countries. The author used the dataset to monitor the sample countries in the performance of implementing the measures and having the indexed approach to each TFM. Moreover, the dataset was used to assess the impact of specific trade facilitation measures on the trade flows and trade costs. It can be also used to estimate the effect on the resource allocation or the welfare. The dataset uses information and not perceptions, which is important when conducting quantitative research. One of the highlights of such dataset is the interactive tool that allows comparing each country with each other on different TFI and looking at what measures define such rankings. As it was written in the description of the dataset:
The data on the OECD TFIs are gathered through a questionnaire replied by the relevant administrations and by carriers with worldwide presence, and crosschecked against publicly available sources. They are then verified through each concerned country’s WTO and Customs administrations. Variables follow a scoring from 0 (lowest performance) to 2 (highest performance) (percentile ranking is used where no “natural” thresholds can be identified, i.e. where variables are numerical in nature). The indicators are the simple average of the scores for each variable composing them.
The detailed table on the eleven policy dimensions can be found in the Appendices. This dataset was a major source of data in this research and was used for obtaining the TFI indicators on specific countries and their correlation between the bilateral trade of each country.
The second data was taken from the ESCAP – World Bank Trade Costs database. The United Nations ESCAP and the World Bank joined efforts to develop a common bilateral trade costs database in 2011. It includes all costs involved in trading goods internationally compared to the domestic trade. The last updated version covers the time span from 1995 to 2014 for over 180 countries in agriculture and manufacturing sectors. It is updated on annual basis. The database offers the costs without tariffs as well which is handy in terms of calculating the net trade costs without policy interventions. There trade costs are calculated with the usage of the “inverse gravity framework” that was developed by Novy (2009). The total trade cost there accounts for all direct and indirect costs that are executed between two countries including transport and logistics costs, tariffs, as well as currencies, geographical barriers and export and import procedures. There trade costs are expressed in ad valorem equivalent which implies a percentage of the domestic value of goods. It is useful because there is an extensive country and time coverage that is based on macro data. It also allows calculating sub-regional trade costs and was used to evaluate the importance of TF measures. The author included the example of how the dataset looks like in the Appendices.
The third database used in the research was found in the World Bank Doing Business trading across borders Rank Indicators. Especially in the Border compliance section: Time and cost to export/import. There the data on export and import costs was taken along with the Documentary Compliance: Time and cost to export and import. It was measured in hours and in US dollars. The domestic transport with time and cost was used to account for the transportation hours and costs for each country.
The fourth database used in the research is the United Nations Global Survey on Trade Facilitation and Paperless Trade Implementation. It was conducted by the UN Regional Commissions with global partners. The survey covered 38 TFM’s that were categorized into four groups: General Trade Facilitation measures (WTO TFA), Paperless Trade measures, Cross-border Paperless Trade measures, and Transit Facilitation measures. It was conducted every 2 years and covered the range of 119 countries from 8 global regions, 44 of which are from Asia and the Pacific. The survey is based on facts and not perceptions and issues related to trade facilitation. Full dataset is available for advanced analysis. The full dataset was submitted by each country to the experts, and then the validation of data was conducted through published and unpublished materials. The final step was a verification of the data by the governments of the selected countries. The examples of such datasets are available in the Appendices.
The last dataset used was the World Bank Logistic Performance Index (LPI). It was launched in 2007 and incorporated interactive tool to help countries identify the challenges and obstacles when conducting trade and logistic performances. The index is updated every 2 years and 160 countries are ranked on the efficiency of international supply chains. The LPI is based on a worldwide survey of logistics professionals on the ground and providing proper feedback on International LPI and the Domestic LPI. Its uniqueness lies in combined effect of the quantitative and qualitative research that was done by the logistics experts. The index allows tracking progress and changes in the supply chain. The methodology is as follows:
International LPI: Each survey respondent rates eight overseas markets on six
core components of logistic performance. The index is the weighted average of the country scores on the six key dimensions. Domestic LPI: Respondents provide qualitative and quantitative information on the logistics environment in the country where they work. Country scores are calculated taking a geometric average in levels whereas scores for regions, income groups, and LPI quintiles are simple averages of the relevant country scores.
For the qualitative research within the Central Asian scope the author of the thesis used the OSCE POiB documents that are not publically available during the internship at the office. With the Customs and Trade Officer, the author analyzed the situation in customs of Kyrgyzstan, Kazakhstan, Uzbekistan, and Tajikistan. The report gives insights and recommendations on the ways of assisting the governments in trade facilitation and what an OSCE can do to enhance the process. The vision of the long-term cooperation is also included in the research. Author expresses gratitude to the GIZ office in helping to conduct an interview with the expert on Trade Facilitation (See Acknowledgements) and providing the data on the Time Release Study (TRS) on the borders of the Kyrgyz Republic. The data from the TRS is not yet published by the official authorities of the country and that is why the results of the findings cannot be used or published outside the OSCE Academy. All the relevant figures and tables from the qualitative research are available in the Appendices section of the work. The results of the findings will be discussed in the Conclusion/Recommendations chapter.