The knowledge and support technical assistance (TA) will support capacity enhancement of the national statistical data (NSD) systems of selected developing member countries (DMCs) in Asia and the Pacific to produce high-quality statistical information using modern technology, innovative data, advanced methods, and best practices. The Statistics and Data Innovation Unit (EROD-SDI ) of the Economic Research and Regional Cooperation Department (ERCD) has undertaken capacity building initiatives in statistics, and this project, as one of those initiatives, supports the Sustainable Development Goals (SDGs) through technology-focused capacity building, in line with Strategy 2030 of the Asian Development Bank (ADB). The project is aligned with operational priority (OP) 6 of Strategy 2030 (strengthening governance and institutional capacity) as it will enhance the capacity of statistical systems to produce information needed for evidence-based policy making and program monitoring.
|Project Name||Strengthening Digital Information of the National Statistical Data Systems|
|Project Type / Modality of Assistance||Technical Assistance
|Source of Funding / Amount||
|Strategic Agendas||Inclusive economic growth
|Drivers of Change||Gender Equity and Mainstreaming
Governance and capacity development
Private sector development
|Sector / Subsector||
Information and communication technology / ICT strategy and policy, and capacity development
Public sector management / Public administration
|Gender Equity and Mainstreaming||Some gender elements|
|Description||The knowledge and support technical assistance (TA) will support capacity enhancement of the national statistical data (NSD) systems of selected developing member countries (DMCs) in Asia and the Pacific to produce high-quality statistical information using modern technology, innovative data, advanced methods, and best practices. The Statistics and Data Innovation Unit (EROD-SDI ) of the Economic Research and Regional Cooperation Department (ERCD) has undertaken capacity building initiatives in statistics, and this project, as one of those initiatives, supports the Sustainable Development Goals (SDGs) through technology-focused capacity building, in line with Strategy 2030 of the Asian Development Bank (ADB). The project is aligned with operational priority (OP) 6 of Strategy 2030 (strengthening governance and institutional capacity) as it will enhance the capacity of statistical systems to produce information needed for evidence-based policy making and program monitoring. Statistics produced in participating DMCs will enable governments and ADB to track progress in alleviating poverty, in line with Strategy 2030 OP1 (addressing remaining poverty and reducing Inequalities). The project also supports OP7 of the strategy (fostering regional cooperation and integration) in that it will encourage country- and sector-specific participation in global statistical standards and methodologies. The TA is part of the approved workplan of ERCD and will enable ADB to expand its socioeconomic databases used for critical analysis.|
|Project Rationale and Linkage to Country/Regional Strategy||
High-quality data that can be transformed and analyzed are needed to deliver the indicators in Strategy 2030 which can improve policy making, monitoring, and accountability of DMCs. In a globalized and digitalized world, relevant, accurate, timely, cross-cutting, readily accessible, and usable statistical information based on conventional and innovative data are critical to analyzing local and global socioeconomic issues. The use of modern technology, cutting-edge methods, and innovative data can significantly improve the quality and usability of statistics in, for example, formulating policies, and tracking progress toward development goals especially the SDGs, which ADB recommends using to guide recovery from the coronavirus disease (COVID 19).
Although NSD systems in the target DMCs produce key socioeconomic indicators and even compile crucial data relevant to the SDGs, they have failed to adopt technological and technical innovations in the field of statistics and continue to compile statistics through outdated and/or costly means, which adversely affects the quality and timeliness of data. Furthermore, traditional data-release and dissemination methods severely limit the accessibility and usability of data. These shortcomings leave these NSD systems unable to provide critical and timely data. The selection of the DMCs will vary and will be broadly based on the following criteria: the DMCs (i) will be conducting a census, survey, administrative, or nontraditional data; (ii) should have qualified staff who can be trained in statistics; and (iii) should be keen to incorporate modern tools and statistical innovations into their systems.
The TA project will focus on innovative approaches to producing key socioeconomic and SDG-relevant statistics in two domains: (i) data collection, management, and dissemination; and (ii) knowledge sharing on innovations in statistics.
|Impact||DMCs capacity to produce information needed for rigorous evidence-based policy making and program monitoring particularly under the SDGs enhanced.|
|Description of Outcome||The capacity of DMCs' NSDatS in producing high quality, high frequency, and highly granular statistics on selected socioeconomic indicators strengthened.|
|Progress Toward Outcome|
|Description of Project Outputs||
Data collection, management, and dissemination through innovative technology
Knowledge sharing on technological, technical and data innovations in statistics
|Status of Implementation Progress (Outputs, Activities, and Issues)|
|Geographical Location||Fiji - Nation-wide; Timor-Leste - Nation-wide|
|Summary of Environmental and Social Aspects|
|Stakeholder Communication, Participation, and Consultation|
|During Project Design|
|During Project Implementation|
Under the TA, the following experts will be engaged:
(i) International Consultant to develop a customized software application to digitize CAPI/CATI/CAWI
(ii) International Consultant for SDMX
(iii) Economists or Statisticians
(iv) Research Assistants
|Procurement||The TA requires both micro and macro data. The datasets will be procured from DMC agencies as well as other research institutions. Equipment such as laptop computers and software may also be procured for the TA where needed. Procurement of data, equipment, and software will be in accordance with ADB's Procurement Guidelines (2017, as amended from time to time). For the equipment, a certificate of equipment turnover or disposal will be submitted at the end of the TA implementation.|
|Responsible ADB Officer||Mariasingham, Mahinthan Joseph|
|Responsible ADB Department||Economic Research and Regional Cooperation Department|
|Responsible ADB Division||EROD-SDI|
|Concept Clearance||29 Oct 2020|
|Approval||09 Dec 2020|
|Last Review Mission||-|
|Last PDS Update||04 Jan 2021|
|Approval||Signing Date||Effectivity Date||Closing|
|09 Dec 2020||-||09 Dec 2020||31 Dec 2023||-||-|
|Financing Plan/TA Utilization||Cumulative Disbursements|
|1,500,000.00||0.00||0.00||0.00||0.00||0.00||750,000.00||09 Dec 2020||0.00|
Project Data Sheets (PDS) contain summary information on the project or program. Because the PDS is a work in progress, some information may not be included in its initial version but will be added as it becomes available. Information about proposed projects is tentative and indicative.
The Access to Information Policy (AIP) recognizes that transparency and accountability are essential to development effectiveness. It establishes the disclosure requirements for documents and information ADB produces or requires to be produced.
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|Title||Document Type||Document Date|
|Strengthening Digital Information of the National Statistical Data Systems: Technical Assistance Report||Technical Assistance Reports||Dec 2020|
Safeguard Documents See also: Safeguards
Safeguard documents provided at the time of project/facility approval may also be found in the list of linked documents provided with the Report and Recommendation of the President.
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Evaluation Documents See also: Independent Evaluation
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