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.