EXPLAINER

How National Statistical Systems Provide Timely Data during the Pandemic

 Rapid and effective response and adaptation to the COVID-19 crisis depend on accurate and timely data, such as infection rates, number of deaths, and vaccination rates. Photo credit: ADB.
Rapid and effective response and adaptation to the COVID-19 crisis depend on accurate and timely data, such as infection rates, number of deaths, and vaccination rates. Photo credit: ADB.

Published: 13 September 2021

Statisticians turn to digital solutions and nontraditional methods for faster data collection, processing, and dissemination to inform crisis response.

Introduction

The COVID-19 pandemic has sharply brought into focus the importance and necessity of high-quality and timely data in our lives. Infection rates, number of deaths, and vaccination rates are just some of the information that influence the decisions of governments on such matters as freedom of movement and economic activities during this unprecedented crisis. Accurate and up-to-date data is crucial in navigating a rapidly changing situation to promptly assess impacts on peoples’ lives and livelihoods and develop the best response.

However, lockdowns and other pandemic restrictions have greatly impeded the traditional methods of data collection used by national statistical systems, hindering statistical capacity worldwide and curbing the ability to produce high-quality statistics in a timely manner. This has spurred statisticians to embrace and accelerate the use of alternative methods and digital solutions for faster collection, processing, and dissemination of data.

Technology-Assisted Data Collection

The Asian Development Bank (ADB) conducted a survey on initiatives of national statistics offices in Asia and the Pacific to improve their statistical systems prior to and during the pandemic to assess their ability to deliver needed information. A national statistical system is made up of “statistical organizations and units that jointly collect, process, and disseminate official statistics on behalf of the government.”

The survey shows that majority were able to push through with more than half of their scheduled data collection activities. Comparing the results of the survey with the World Bank’s Statistical Performance Indicators (SPI) index, which assesses the performance of national statistical systems, the results suggest that, although there is a positive association between the two measures, the value of the SPI is not a strong predictor of whether scheduled data collection activities were completed. This could be indicative of the commitment of national statistics offices in the region to provide timely and relevant data despite disruptions caused by the pandemic.

Figure 1: Association between the Statistical Performance Indicator and Scheduled Data Collection Activities

SPI = Statistical Performance Indicator
Source: Asian Development Bank estimates using data from the Survey on National Statistics Systems’ Initiatives to Enhance Timeliness of Data and Statistics and the World Bank’s Statistical Performance Indicators (accessed 27 July 2021).

Initiatives taken included technology-assisted data collection, such as using big data and innovative data capture tools. From traditional pen and paper surveys, national statistics offices also shifted to computer assisted personal interviewing (CAPI), computer assisted telephone interviewing (CATI), or computer assisted web interviewing (CAWI) methods.

Statistics offices that have started exploring such innovations before the pandemic, experienced a smoother transition and fewer delays as they scaled up implementation during the pandemic. However, for others that have just started, it was a bit more challenging.

The survey also shows that statistics offices that advanced digitalization in data collection before COVID-19 are more resilient. For example, early adoption of digital technology by Malaysia and the Philippines increased their ability to provide timely data during the pandemic. Thailand used tablets for faster data consistency checks, shorter processing time of survey responses, and immediate uploading of responses to the cloud. It also planned to use a web application to monitor field operations by tracking enumerators via their tablets. This was to provide the headquarters with real-time information and the ability to immediately respond in cases of delays in the field.

Nontraditional Data Sources

Several statistics offices explored the use of nontraditional data sets to provide richer and more timely insights on economic activities. For example, imputation techniques (e.g., Republic of Korea, Singapore, Thailand), alternative data sources such as firms’ annual reports (Sri Lanka and Hong Kong, China), and web-scraping were used to fill missing data in price surveys.

Some countries used various administrative data to make up for the inability to conduct field work. Malaysia integrated data from the Employees’ Provident Fund and the Inland Revenue Board, which provided quick snapshots of how the pandemic is affecting the labor market, resulting in less cost and delays in data collection. Thailand also recognizes the importance of using administrative data and the need to develop the technical capacity of officials supporting in this area

National statistical systems have explored integrating the use of big data into current national accounting standards. For example, the Reserve Bank of India tracks high-frequency activity indicators in real time to provide up-to-date information on the state of the economy and forecast gross domestic product (GDP) growth ahead of official releases.

Studies have also examined the use of satellite images and spatial data to complement conventional GDP estimation, specifically nighttime lights data as a proxy indicator of economic growth. In Thailand, a study by the statistics office and ADB helped explore the use of satellite population maps to provide detailed population data, which is especially useful when face-to-face data gathering is not feasible.

Conclusion

The COVID-19 pandemic provided the opportunity to accelerate adoption of digital solutions and nontraditional techniques. It underscored the advantages of utilizing technology in capturing information especially in times of crises. It also showed how national statistical systems benefit from evaluating their resources and capacities to enable them to integrate new methods and invest in agile and resilient information systems that will enable them to produce high-quality data and statistics.

Statistical systems need to remain flexible and adaptable, combining traditional and nontraditional sources and techniques. This will allow them to continue providing timely, accurate, and credible statistics, which plays a vital role in our lives now more than ever.

Additional details from the survey are available in the 2021 edition of Key Indicators for Asia and the Pacific.

Resources

Asian Development Bank (ADB). 2021. Key Indicators for Asia and the Pacific 2021. Manila.

ADB. Key Indicators Database.

Ask the Experts

  • Vararat Atisophon
    Consultant, Asian Development Bank

    Vararat is an ADB consultant, working as a Statistical Specialist at the Economic Research and Regional Cooperation Department. Prior to joining ADB, she was a statistician at the OECD Development Centre between 2009 and 2020. She served as an economist at the Bank of Thailand between 2001 and 2003. She holds a Master of Public Policy degree from GRIPS, Japan.

  • Anna Marie Fernando
    Consultant, Asian Development Bank

    Anna Marie Fernando is an Economics and Statistics Specialist at the Asian Development Bank. She provides technical assistance in compiling various indicators for ADB’s Key Indicators for Asia and the Pacific publication.

  • Arturo Martinez, Jr.
    Statistician, Economic Research and Regional Cooperation Department, Asian Development Bank

    Art Martinez works on Sustainable Development Goals indicator compilation, particularly poverty statistics and big data analytics. Prior to joining ADB, he was a research fellow at the University of Queensland where he also got his doctorate in Social Statistics.

  • Domini Velasquez
    Consultant, Asian Development Bank

    Domini is a short-term ADB consultant with the Economic Research and Regional Cooperation Department. Before ADB, she worked as an economist with the Philippine government’s National Economic and Development Authority and Bangko Sentral ng Pilipinas. She holds an MSc in International Migration and Public Policy from London School of Economics and a Master in Public Policy from National University of Singapore.

  • Asian Development Bank (ADB)

    The Asian Development Bank is committed to achieving a prosperous, inclusive, resilient, and sustainable Asia and the Pacific, while sustaining its efforts to eradicate extreme poverty. Established in 1966, it is owned by 68 members—49 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance.

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The views expressed on this website are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.




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