Consultation Meeting on Domestic Trade Statistics Strengthening Capacities for the Implementation of the Sustainable Development Goals (SCDG) Executive Summary 2nd August 2019 Royal President Hotel, Naypyitaw 1. The Central Statistics Organization (CSO) has proposed the improvement of domestic Trade Statistics in Myanmar as a pilot area for subject matter statistics in the abovementioned project. According to the CSO Trade Section “While price surveys and index calculations are made possible in ongoing cooperation with the International Monetary Fund (IMF) and the Asian Development Bank (ADB), virtually no data can be offered for domestic trade. Common to all areas is the urgent need to elucidate how major administrative domestic trade data could be obtained.” 2. The Consultation Meeting on Domestic Trade Statistics was organized at Royal President Hotel in Naypyitaw on 2nd August 2019 and witnessed the opening remarks of U San Myint, Director General of the Central Statistical Organization (CSO), Ministry of Planning and Finance and Ms Jasmin Freischlad, Head of Project of the bilateral technical cooperation project “Strengthening Capacities for the Implementation of the SDGs”. The meeting was attended by delegates from government departments, GIZ technical experts, and consultants and delegates from the private sector and private research firms; totaling 61 participants, selected jointly by GIZ and CSO. 3. The consultation meeting provided a unique avenue to discuss and explore initial ideas and feasibility for data collection on domestic trade statistics. Key objectives of the meeting are 1) to obtain inputs for potential data sources and types regarding domestic trade statistics from key stakeholders, 2) to generate ideas on the initial domestic trade statistics development framework including institutional arrangements, and 3) to identify the data categories that can be collected as a pilot project before the end of 2020. GIZ and CSO were able to invite a wide range of relevant stakeholders on domestic trade statistics and feature comprehensive and diverse discussions on potentials and challenges. The meeting involved two main sessions – technical inputs session with interactive panel, and breakout group discussions. 4. The technical input sessions comprised past experiences and the importance of domestic trade statistics in Myanmar, agricultural value chains, as well as international standards for industrial classifications and data collection in Germany (monthly report, yearly census data on sales turnover and number of employees). The data is used to monitor economic developments and the labor market. The interactive panel discussion articulated the legal framework for data collection highlighting the Statistics Law, the relevance of motor vehicles trade as a domestic trade category, policy implications at sub-national level and the need for trust building and coordination with the private sector. The panel also suggested to focus on commodity groups from the consumer price index (CPI) calculation in the initial stage of domestic trade statistics development. 5. Breakout group discussions were conducted to deliberate on three potential data sources for domestic trade statistics, namely 1) statistical business register (SBR), retail/wholesale trade and prices, 2) Logistics and commodity flow, and 3) commodity providers and stateowned enterprises (SOEs). Breakout group discussions explored the current data availability and options for domestic trade statistics development to collect quality statistics for effective dissemination to data users. 6. According to the discussions, SBR, retail/wholesale trade and prices group (Group 1) mainly identified that the list of licensed enterprises from municipal organizations, Directorate of Industrial Supervision and Inspection (DISI) and Small-Scale Industries Department (SSID) are key data sources for retail trade where municipal organizations collect capital data and DISI and SSID collect manpower and horsepower of machines on annual basis. Moreover, the Consumer Affairs Department collects retail price data from 22 cities and wholesale price data from wholesale markets while Cooperative Department collects the data from trading cooperatives. The data from this group were mainly utilized for internal reports and data support to other departments and research institutions on request. For additional data types, municipal organizations would like to collect manpower as well as DISI and SSID would like to expand their datasets for investment, production and income data. The group also identified that local raw material data and its flow could be useful and CSO could also request the audit reports as the central statistical authority. 7. In the logistics and commodity flow group (Group 2), Myanma Railway, Inland Water Transport and Customs Department collect tons, ton-mile and origin-destination of cargoes. As the private logistics sector is growing, logistics data from Myanmar Highway Freight Transportation Association would be a great use for domestic trade statistics. Myantrade under the Ministry of Commerce also collects daily volumes and prices by commodity types of wholesale market transactions for which CSO can get a copy. Another interesting data source is the livestock health check register in origin before transporting by the Livestock Breeding and Veterinary Department which can provide the volume of livestock trade. The vehicle registration database of the Road Transport Administration Department can also be a potential data source for motor trade. The data from this group were also mainly utilized for internal reports and data support to other departments and research institutions on request. Additional potential data sources for the logistics sector may be the cargo weight data from Road Department and cargo truck registration data from Road Transport Administration Department. The Livestock Breeding and Veterinary Department can also calculate the livestock feed requirement for livestock value chain based on the volume of livestock trade. 8. For the commodity providers (Group 3) and SOEs group, data availability was mainly on production, sales turnover and prices data from state-owned enterprises while the Market Information Section of the Department of Planning from the Ministry of Agriculture, Livestock and Irrigation collects price data of agriculture products and inputs in 23 markets from 22 cities and the Department of Agriculture collects the production, cost and price data from 71 districts. The data from this group were utilized for diverse purposes including dissemination to farmers, policy makers and other statistics users. Moreover, the Fisheries Department has been cooperating with the Food and Agriculture Organization (FAO) for comprehensive fishery statistics development. If the CSO could identify the required data for domestic trade statistics, commodity providers and state-owned enterprises including the Union of Myanmar Federation of Chambers of Commerce and Industry (UMFCCI) could provide the additional data. 9. Based on the breakout group discussions, three main data collection options can be recommended. First, the existing administrative data sources can be used for data extraction. But there are limitations regarding the type of available data and the incomplete datasets which requires extensive coordination between CSO and respective data providers for standard data collection formats to improve data quality. Second, the administrative databases can be expanded to fill the gaps of the first option in the shortterm. However, during the consultation meeting, potential additional data types and sources were not discussed thoroughly due to time limitations for which CSO should further coordinate with respective data providers to add additional data types in standard data collection formats of previous option. The DG of CSO could also exercise his power as Chief Statistician to assign statistical focal points from various departments and stateowned enterprises according to Statistics Law Chapter 7, additional notifications for data collection might be needed to enhance the legal framework for data collection. Third option is to conduct periodic surveys directly by CSO in short-term and by respective departments in medium-term through amendments in data collection regulations which require private enterprises to report regularly in order to bridge the data gaps of previous options. 10. In order to implement these options, CSO and respective data providers should prioritize to coordinate with private sector for trust building. A coordination mechanism should be established with relevant business associations with the support of UMFCCI to strengthen the domestic trade statistics system with private sector data. Domestic trade statistic is primarily built on data from private enterprises and its accuracy depends on the accuracy of the information provided by private entities. The initial framework for domestic trade statistics should emphasize the coherence of data collection option and data types with considerations on possible data gaps in order to develop the data collection system in consistency with data processing and production systems. Moreover, the co-leadership of the Ministry of Commerce is also important with regard to the institutional arrangements for domestic trade statistics and needs to be further explored going forward. Regardless of the choice of initial commodity group for the pilot project, key stakeholders of each potential data source should be prioritized for the coordination mechanism. Based on the breakout group discussions, Municipal Organizations, DISI and SSID for retail trade, Wholesale Markets and Municipal Organizations for wholesale trade, Myanma Railways, Inland Water Transport, Customs Department and Myanmar Highway Freight Transportation Association for logistics sector, and respective SOEs and Business Associations from UMFCCI for commodity providers should be prioritized. 11. GIZ will continue to support the establishment of meaningful cooperation between CSO and German Statistics Office for the development of domestic trade statistics starting with the initial framework for the test commodity group of pilot project based on the successful results from this consultation meeting. The initial framework for development of domestic trade statistics is an important step for implementing the National Strategy for Development of Statistics as well as generating good practices of strengthening National Statistical System towards the emergence of monitoring and review mechanisms for 2030 Agenda.