An analysis of the worldwide response to the COVID-19 pandemic: What and how much?
Abstract
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
Full text
Felipe, Jesus et al. Working Paper An analysis of the worldwide response to the COVID-19 pandemic: What and how much? ADB Economics Working Paper Series, No. 626 Provided in Cooperation with: Asian Development Bank (ADB), Manila Suggested Citation: Felipe, Jesus et al. (2020) : An analysis of the worldwide response to the COVID-19 pandemic: What and how much?, ADB Economics Working Paper Series, No. 626, Asian Development Bank (ADB), Manila, https://doi.org/10.22617/WPS200353-2 This Version is available at: https://hdl.handle.net/10419/246703 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/3.0/igo/
ASIAN DEVELOPMENT BANK ADB ECONOMICS WORKING PAPER SERIES NO. 626 December 2020 AN ANALYSIS OF THE WORLDWIDE RESPONSE TO THE COVID-19 PANDEMIC WHAT AND HOW MUCH? Jesus Felipe, Scott Fullwiler, Donna Faye Bajaro, Al-Habbyel Yusoph, Simon Alec Askin, and Martin Alexander Cruz
ASIAN DEVELOPMENT BANK ADB Economics Working Paper Series An Analysis of the Worldwide Response to the COVID-19 Pandemic: What and How Much? Jesus Felipe, Scott Fullwiler, Donna Faye Bajaro, Al-Habbyel Yusoph, Simon Alec Askin, and Martin Alexander Cruz No. 626 | December 2020 Jesus Felipe ([email protected]) is an advisor at the Economic Research and Regional CooperationDepartment of the Asian Development Bank (ADB). Scott Fullwiler ([email protected]) is an assistant professor at the University of Missouri-KansasCity. Donna Faye Bajaro ([email protected]) is a consultant at ADB. Al-Habbyel Yusoph([email protected]), SimonAlec Askin ([email protected]), and MartinAlexander Cruz ([email protected]) are also consultants from the University of the Philippines.
Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) © 2020 Asian Development Bank 6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, Philippines Tel +63 2 8632 4444; Fax +63 2 8636 2444 www.adb.org Some rights reserved. Published in 2020. ISSN 2313-5867 (print), 2313-5875 (electronic) Publication Stock No. WPS200354-2 DOI: http://dx.doi.org/10.22617/WPS200354-2 The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies ofthe 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. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned. By making any designation of or reference to a particular territory or geographic area, or by using the term “country” inthis document, ADB does not intend to make any judgments as to the legal or other status of any territory or area. This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) https://creativecommons.org/licenses/by/3.0/igo/. By using the content of this publication, you agree to be bound bytheterms of this license. For attribution, translations, adaptations, and permissions, please read the provisions andterms of use at https://www.adb.org/terms-use#openaccess. This CC license does not apply to non-ADB copyright materials in this publication. If the material is attributed toanother source, please contact the copyright owner or publisher of that source for permission to reproduce it. ADB cannot be held liable for any claims that arise as a result of your use of the material. Please contact [email protected] if you have questions or comments with respect to content, or if you wish toobtain copyright permission for your intended use that does not fall within these terms, or for permission to use theADB logo. Corrigenda to ADB publications may be found at http://www.adb.org/publications/corrigenda. Note: In this publication, “$” refers to United States dollars. The ADB Economics Working Paper Series presents data, information, and/or findings from ongoing research and studies to encourage exchange of ideas and to elicit comment and feedback about development issues in Asia and the Pacific. Since papers in this series are intended for quick and easy dissemination, the content may or may not be fully edited and may later be modified for final publication. ISSN 2313-5867 (print), 2313-5875 (electronic) Publication Stock No. WPS200353-2 DOI: http://dx.doi.org/10.22617/WPS200353-2
CONTENTS TABLES AND FIGURES iv ABSTRACT v I. INTRODUCTION 1 II. THE ADB COVID-19 POLICY DATABASE 2 III. SIZE AND COMPOSITION OF THE PACKAGES 4 A. How Large Are the Country Packages? 5 B. What Measures Have Economies Implemented? 7 C. How Are the Measures Being Funded? 12 IV. COMPARING COUNTRIES—A SHORT CASE STUDY OF PACKAGES AND 13 WHAT IS OR IS NOT REPORTED V. WHAT DETERMINES THE SIZE OF A PACKAGE? IS A PACKAGE “ADEQUATE”? 15 VI. CONCLUSION 25 APPENDIX 27 REFERENCES 37
TABLES AND FIGURES TABLES 1 Categorization of Measures according to Operational Details and Financial Position Effects 2 2 Packages, 20 April and 15 June 2020 Versions 5 3 Top 10 Countries with the Largest Packages, 20 April and 15 June 2020 Versions 6 4 Top Five Economies with the Largest Package as Percent of Gross Domestic Product 6 and per Capita 5 Share of Each Measure in Total Packages, 15 June 2020 Version 9 6 Comparison of Measures 01 to 05 and 10 for the Philippines, Indonesia, Thailand, 13 Malaysia, and the Republic of Korea, 15 June 2020 Version 7 Descriptive Statistics, 15 June 2020 Version 18 8 Package per Capita (log) and Correlates, 15 June 2020 Version 21 9 Actual and Expected Packages per Capita 23 A1 Total Package as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version 27 A2 Measure 05 per Capita and Correlates, 15 June 2020 Version 28 A3 Measure 05 as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version 29 A4 Sum of Measures 01 to 04 per Capita and Correlates, 15 June 2020 Version 30 A5 Sum of Measures 01 to 04 as Percent of Gross Domestic Product and Correlates, 31 15 June 2020 Version FIGURES 1 ADB’s Developing Members’ Packages from 20 April to 15 June 2020 7 2 Other ADB Members’ Packages from 20 April to 15 June 2020 8 3 Package per Capita and Correlates, 15 June 2020 Version 16 4 Number of Countries by Total Package per Capita, 15 June 2020 Version 17 5 Package per Capita and Gross Domestic Product per Capita: Regression Line 20 A1 Total Package as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version 32 A2 Measure 05 per Capita and Correlates, 15 June 2020 Version 33 A3 Measure 05 as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version 34 A4 Sum of Measures 01 to 04 per Capita and Correlates, 15 June 2020 Version 35 A5 Sum of Measures 01 to 04 as Percent of Gross Domestic Product and Correlates, 36 15 June 2020 Version
ABSTRACT We use the information compiled as of 15 June 2020 by the Asian Development Bank (ADB) in the ADB COVID-19 Policy Database to analyze the measures taken by its 68 members, plus the European Central Bank, and the European Union, to combat the coronavirus disease (COVID-19) pandemic. Measures associated with monetary policy amount to $14.9 trillion ($1.4 trillion by ADB’s developing members), while the measures associated with fiscal policy amount to $7.1 trillion ($1.5 trillion by ADB’s developing members). We discuss the specifics of five countries—identifying similarities and differences. Analysis shows that some countries implemented actions which do not translate easily into monetary amounts for reporting. We show that the total package per capita is directly related to gross domestic product per capita with a high elasticity of 1.61; and so is the package on government support to income and revenue (a subset of the total package), with an elasticity of 1.49. We develop a series of models to understand why rich economies spend significantly more per capita. Results indicate that the package per capita is positively related to the COVID-19 deaths per 100,000 population as of 15 June 2020, population of at least 65 years old as percent of total population, and wage and salaried workers as percent of total employment; and inversely related to self-employed as percent of total employment, and vulnerable employment as percent of total employment. We use this information to compare actual to expected packages. Keywords: ADB COVID-19 Policy Database, COVID-19 JEL codes: A10, C82
An Analysis of the Worldwide Response to the COVID-19 Pandemic 1 I. INTRODUCTION The coronavirus disease (COVID-19) pandemic that shocked the world economy in 2020 has already infected over 18 million people worldwide, caused over 700 thousand deaths (as of mid-August 2020), and affected the lives of countless others. This paper uses the COVID-19 Policy Database of the Asian Development Bank (ADB) to study the measures that its 68 members, as well as the European Central Bank (ECB), and the European Union (EU), have implemented to combat the effects of the COVID-19 pandemic. Database work commenced in March 2020, and has been released five times, in 2-week intervals from 20 April to 15 June. The specific objectives of this paper are to: (i) take stock of how packages have changed since April 2020; (ii) understand the measures that ADB members have implemented; (iii) analyze whether the measures were adequate to deal with the shock phase; and (iv) understand differences in the size of the packages, when measured in per capita terms or as percentage of gross domestic product (GDP). The paper is structured as follows. Section II explains the taxonomy used to classify the different measures as well as the estimated country and aggregate packages. Section III summarizes and discusses the measures taken by ADB members as well as the packages (amounts) deployed to combat COVID-19. Section IV discusses the extent to which the measures taken were adequate to deal with the shock phase. Section V presents a statistical analysis to understand the determinants of the size of the packages. Section VI concludes. II. THE ADB COVID-19 POLICY DATABASE The ADB COVID-19 Policy Database collects information on the key economic measures that authorities are taking to combat the COVID-19 pandemic. 1 The primary information comes from both national sources and data collected by international organizations. The database covers the 68 members of ADB, the ECB, the EU, and 9 other economies in Africa, Latin America, and Europe. 2 They represent 92.0% of global GDP and 80.0% of the world's population. To understand the different policy actions in response to COVID-19, the policy database categorizes these actions according to their differences in operational details and/or financial statement effects. Operational details define the path a given measure takes to affect the financial system, spending, production, and so forth. For the COVID-19 policy responses, these fall into the following categories: 1 Felipe and Fullwiler (2020) provide a detailed guide on the ADB COVID-19 Policy Database. The database can be accessed at https://covid19policy.adb.org/. 2 Other economies included are: Arab Republic of Egypt, Argentina, Brazil, Islamic Republic of Iran, Mexico, Nigeria, the Russian Federation, Saudi Arabia, and South Africa. These economies are not discussed in the analysis. We focus on ADB members.
2 ADB Economics Working Paper Series No. 626 Provide liquidity to financial and nonfinancial businesses and/or state, local, or regional governments Encourage credit creation by the financial sector Directly fund households, businesses, and/or state, local, or regional governments Financial statement effects of a given measure answer one of the following questions: Who, if anyone, bears the financial burden of the measure and what kind? Does the measure create more debt or more income (e.g., net worth or equity, other things being equal) for the recipients? These are shown in Table 1. Table 1: Categorization of Measures According to Operational Details and Financial Position Effects Operational Details Financial Positions Provide liquidity Measure 01 Loans from the central bank or government to the private sector and state, regional, or local sector Government or central bank purchases of short-term assets from the private sector Regulatory or other changes that do not directly alter private sector financial statements Encourage credit creation by the financial sector Measure 02 Increases in liabilities of the private sector and state, regional, or local sector to the government or central bank through loans to the financial sector (to enable further lending to the financial and nonfinancial sectors) or secondary market purchases of securities issued by the financial sector, businesses, or state, regional, or local governments Interest rate changes, loan guarantees, forbearances, and regulatory changes to encourage private credit creation Directly fund Measure 03 Increases in recipients’ liabilities through long-term direct loans from the government or central bank Measure 04 Increases in ownership claims of the government or central bank through equity investments in the business and/or financial sectors Measure 05 Increases in income or reductions in costs or obligations through government transfer payments, loan cancellation, tax cuts, forbearances, and so forth Source: Felipe, Jesus, and Scott Fullwiler. 2020. “The ADB Covid-19 Database: A Guide.” Asian Development Review 37 (2): 1–20. The left column repeats the three bulleted categories for operational details. The respective potential financial statement outcomes of a given measure are to the right of the corresponding operational detail categories. In order to provide liquidity, for instance, governments or central banks can (i) lend (expanding the borrowers’ liabilities in order to obtain central bank liabilities) via existing or expanded standing facilities; (ii) purchase financial assets (exchanging the sellers’ financial assets for central bank liabilities); or (iii) undertake actions which do not directly alter private sector financial statements in the sense that there are no accompanying transactions (though they may encourage or enable financial institutions’ subsequent actions and thereby lead to changes in their financial statements indirectly, of course), such as relaxing regulations (e.g., lowering required minimum
An Analysis of the Worldwide Response to the COVID-19 Pandemic 9 Table 5: Share of Each Measure in Total Packages, 15 June 2020 Version (%) Functioning Money Markets Credit Creation Lending to the Nonfinancial Sector Equity Claims (private sector) Direct Income Support No Breakdown All ADB members 11.8 47.6 5.2 1.3 31.8 2.4 ADB's developing members 25.8 11.9 7.7 0.5 50.8 3.2 Central and West Asia 13.2 3.9 2.5 – 76.8 3.6 East Asia 26.1 10.7 6.8 0.5 52.5 3.4 South Asia 41.0 17.4 – – 41.1 0.5 Southeast Asia 8.1 15.6 23.1 1.2 47.8 4.3 Pacific – 1.1 9.5 – 35.9 53.5 Other ADB members 9.7 53.0 4.8 1.4 28.9 2.2 United States 8.6 55.9 9.8 – 25.7 – Japan 19.6 3.2 – 3.7 73.5 – Note: The percentages shown for each aggregate (i.e., rows for all members, developing members and regions, and other members) are computed by summing up the measures (numerator) and total packages (denominator) of all countries belonging in the aggregation. For the United States and Japan, Measure 09 is excluded in their total packages. Source: Authors’ calculations based on data from the ADB COVID-19 Policy Database. https://covid19policy.adb.org/. Developing members allocate the largest share of their packages to direct income support. In Central and West Asia, the share is 76.8%. The second largest measure varies across the regions. In Central and West Asia, East Asia, and South Asia, the next largest measure is functioning money markets, while in Southeast Asia and the Pacific, it is lending to the nonfinancial sector. The smallest shares in both developing members and other members are lending to the nonfinancial sector and equity claims on the private sector: combined, they only make up for 8.2% of the developing members’ total package, and 6.2% of the other members’. Southeast Asia is the only region that allocated a noticeably larger share to lending to the nonfinancial sector—23.1% of the total package. The share of equity claims on the private sector is very small in both developing members and other members. We now make some remarks on each measure: 01. Functioning money markets. This measure aims to provide short-term liquidity to ensure the normal functioning of money markets. Actions include short-term lending to the private sector, regulatory adjustments to liquidity requirements, and foreign exchange operations. Among ADB’s developing members, India and Hong Kong, China have allocated significant shares of the total package to this measure, 41.5% and 68.1%, respectively. India’s actions included increased short-term repurchase agreements (0.1% of GDP); variable term repurchase agreements (0.5% of GDP);
10 ADB Economics Working Paper Series No. 626 and special refinance facilities for rural banks, housing finance companies, and small enterprises (0.2% of GDP). Hong Kong, China’s actions relied more heavily on relaxing liquidity requirements with an estimated total of $128.8 billion in lending capacity released through the reduction in regulatory reserves. 7 These two members plus the PRC account for most of the size difference for Measure 01’s relative size in the packages of ADB developing members relative to the other ADB members. Among the other ADB members, Switzerland has the highest allocation to this measure, 51.1% of its total package, although the vast majority of its actions for Measure 01 were in foreign exchange operations totaling more than $100 billion in order to keep the Swiss franc from appreciating. At the other end of the spectrum, Canada’s actions in Measure 01, which total $187 billion and are 31.0% of the total package as of 27 July, include no foreign exchange operations due to Canada’s freely floating exchange rate. Instead, it includes Bank of Canada purchases of banker’s acceptances, short-term debt of the provinces, and commercial paper; multiple repurchase agreement facilities at the Bank of Canada; and short-term loans from government agencies to small business, nonprofit organizations, and farms. 02. Credit creation. This measure aims to encourage the financial sector to increase provision of credit to the nonfinancial private sector and to subnational governments. Actions under this measure include loans to the financial sector, secondary market purchases, provision of loan guarantees, interest rate reductions, and other regulatory adjustments. Among the developing members, Thailand and Bangladesh allocated 31.5% and 52.1% of their total packages to this measure, respectively. The Bank of Thailand offered $15.6 billion in loans to financial institutions to finance the latters’ lending to small and medium-sized enterprises (SMEs). Bangladesh will subsidize interest payments of up to $5.9 billion in working capital loans by scheduled banks to businesses. Among the other ADB members, the ECB, Italy, and Belgium have the highest allocations to this measure. Both Italy and Belgium implemented state guarantee programs for bank loans, as well as reinsurance schemes, accounting for nearly 84.0% of their total packages. The ECB’s entire package is in Measure 02; to date it has offered “Targeted Longer-Term Refinancing Operations” to financial institutions at negative interest rates, estimating that this could enable the equivalent of €3 trillion in private credit creation. Another program, the ECB’s Pandemic Emergency Purchase Programme, was authorized for another €1.35 trillion in security purchases. The US has the highest monetary value for this measure, which is $3.2 trillion as of 27 July. It includes several of the Federal Reserve’s new standing facilities including the Paycheck Protection Program Lending Facility, the Secondary Market Credit Facility, the Main Street New Loan Facility, and the reestablished Term Asset-Backed Securities Loan Facility, as well as its increased purchases of mortgage-backed securities. 8 It also includes nearly $1.1 trillion in guarantees provided by the government to banks and to the Federal Reserve. 03. Lending to the nonfinancial sector. This measure consists of long-term loans to the nonfinancial private sector as well as forbearances. The Republic of Korea (ROK) leads ADB’s developing members in absolute amount at $101.9 billion, comprising 50.8% of its total package. Some of the specific 7 This is an example of how some countries have reported monetary values on regulatory items in Measures 01B and 02B. For Measure 01B, the estimation appears to be similar to a money multiplier view of how much relaxed reserve requirements might increase excess reserves available for deposit creation. For Measure 02B, the calculations are linked to how much additional balance sheet space becomes available when capital requirements are relaxed. The vast majority of countries relaxed regulatory measures related to both Measures 01B and 02B, but only a small minority reported estimates for potential credit creation that might result. 8 The $3.2 trillion figure uses the authorized amounts for the Secondary Market Credit Facility (included with the Primary Market Credit Facility, since the Federal Reserve uses the same Special Purpose Vehicle (SPV) to lend to both facilities and then reports at the level of this vehicle rather than the individual facilities), the Main Street New Loan Facility, and the Term Asset Backed Securities Lending Facility, which total $1.45 trillion.
An Analysis of the Worldwide Response to the COVID-19 Pandemic 11 measures it has implemented include expanded lending and new bond purchasing facilities. Among the other ADB members, the US and the EU allocate the largest absolute amounts, accounting for 8.3% and 46.5% of their total packages, respectively. For the US, the Federal Reserve established the Municipal Liquidity Facility that will offer up to $500 billion in lending to states and municipalities to manage cash flow stresses caused by the COVID-19 pandemic, while the US government offered loans to businesses critical to national security and also for emergency disaster relief. The EU established the Pandemic Crisis Support credit lines, with access granted for up to 2.0% of the respective country's GDP as of end-2019. 04. Equity claims on the private sector. At just over 1.0% of all ADB members’ total package, this measure is the smallest of Measures 01–05, especially for ADB’s developing members. Germany has allocated $123.9 billion to directly acquire equity of affected companies (e.g., Lufthansa). Japan, on the other hand, increased the purchases of exchange-traded funds and Japan-Real Estate Investment Trusts up to $111.8 billion (2.2% of GDP) and $1.7 billion (0.03% of GDP), respectively. Interestingly, the US has not yet allocated anything to this measure, in contrast with its Troubled Asset Relief Program that purchased private equity positions in large financial institutions during the 2008–2009 global financial crisis. 05. Direct support to income. This measure reflects both health and nonhealth government expenditure designed to increase income and improve the financial positions (net worth) of the private sector. This also includes transfer payments, tax cuts, and other forms of government subsidies. Among ADB developing members, the PRC and India allocated the largest amounts to this measure, $1.1 trillion (60.5% of total package) and $148 billion (42.2% of total package), respectively. Major spending for the PRC includes local government infrastructure projects, COVID-19 control and prevention, tax relief and waived social security contribution, interest concessions, and price reductions. India’s actions include support for businesses and poor households, investments in health institutions, and programs for the agriculture sector. Japan and the US allocated the largest amounts to this measure, $2.3 trillion (73.5% of the total package) and $1.7 trillion (25.6% of the total package), respectively. Japan launched the Emergency Economic Package Against COVID-19, which now represents over 43.4% of its GDP. Some of the measures it has implemented include health-related initiatives, support to businesses and households, and transfers to the local governments. Meanwhile, the US has enacted four major laws to implement its fiscal packages: Coronavirus Preparedness and Response Supplemental Appropriations Act; Families First Coronavirus Response Act; Coronavirus Aid, Relief, and Economic Security (CARES) Act; and Paycheck Protection Program and Healthcare Enhancement Act (PPPHCEA). Relatedly, the multiple US acts are good examples of how Measure 05 can differ from the headline monetary values of government legislation. The CARES Act has a total value of $2.2 trillion but includes nearly $1 trillion in guarantees (Measure 02C) to banks (in the PPPHCEA) and to the Federal Reserve, as well as smaller allocations for loans to private businesses (Measures 01A and 03A). Similarly, the PPPHCEA is nearly $500 billion but includes $321 billion for loan guarantees and another $50 billion in emergency disaster relief loans to small businesses. The four legislative acts combine for $2.9 trillion, but as above, the portion of this that applies to Measure 05 is $1.7 trillion. 09. International assistance. This measure includes the provision of currency swaps and loans among central banks, as well as donations and grants. The US Federal Reserve is by far the largest provider of central bank currency swaps given its contractual agreements with 14 other central banks. Central bank currency swap lines were also provided by the central banks of the EU, India, Japan, the ROK, and
12 ADB Economics Working Paper Series No. 626 Singapore. The Federal Reserve and ECB also provided lines of credit secured by government securities in the respective currencies in some instances, in lieu of loans secured by the borrowing nations’ currencies. Meanwhile, other ADB members, along with the PRC and the ROK, also engaged in direct international assistance, either through direct transfers to intended beneficiaries or increased contributions to multilateral organizations. C. How Are the Measures Being Funded? As countries implement their packages, they have also sought ways to finance them. These are: (i) central bank financing, (ii) international assistance as the borrower or recipient, and (iii) reallocation of previously budgeted government spending. First, any lending or purchasing actions of the central banks in Measure 01–04 in the domestic currency are inherently self-funded, since these actions simply involve a central bank crediting the account of the bank that is the counterparty, or, if the counterparty is not a bank, then it credits the account of the counterparty’s bank, who then credits the counterparty’s account. For government deficit positions, central banks are the major funding sources in Singapore, the United Kingdom, and the US, where this source is equivalent to about 10.4%, 9.4%, and 8.2% of their respective GDPs. Most of this comes from secondary market purchases of government bonds. Direct lending to governments is much more uncommon, only used by the US and a few Southeast Asian countries. 9 In the case of the Philippines, this was accomplished through a $5.9 billion repurchase agreement from the central bank to the government, while the Indonesian central bank opted to purchase sharia sovereign bonds through a government auction in the primary market. As in the previous section’s discussion of Measure 09, the international assistance comes mostly from the network of central bank bilateral swap agreements and via temporary repo facilities (the latter provided independently by the US Federal Reserve and the ECB to central banks in emerging market economies against the risk-free collateral in the lender’s currency). Among ADB’s developing members, those securing swap lines and/or liquidity facilities from multiple central banks are Indonesia, the ROK, Singapore, and Sri Lanka. Other forms of international assistance come from ADB and other multilateral organizations such as the World Bank, the International Monetary Fund, and the Asian Infrastructure Investment Bank, but these make up for a small percentage overall. Nevertheless, international assistance remains an important source of funds for small economies such as those in the Pacific, where it amounts to about 1.7% of the region’s total GDP, compared to 0.03% for the rest of ADB’s developing members. Meanwhile, in absolute amounts, India received the most assistance, $4.0 billion, followed by the Philippines, $3.6 billion. Lastly, reallocating previously budgeted government spending was the least used of these financing measures. Among all ADB members, only Indonesia and the European Union have used this measure. 9 The US case here is unique, involving the government’s backstop of Federal Reserve lending programs, as authorized in the CARES Act. As of 27 July, $114 billion has been moved from the Treasury’s account on the Federal Reserve’s balance sheet into ‘special’ accounts that are effectively equity investments in the Federal Reserve’s SPVs. Of this amount, $96 billion is invested directly in nonmarketable domestic series US government debt. In other words, $96 billion of the government’s current $114 billion equity position in the Federal Reserve’s SPVs is invested directly in newly issued, nonmarketable US government securities. To be more precise, $1.5 billion of the $114 billion is allocated to the Federal Reserves Money Market Liquidity Facility, which is not among the Federal Reserve’s SPVs.
An Analysis of the Worldwide Response to the COVID-19 Pandemic 13 IV. COMPARING COUNTRIES—A SHORT CASE STUDY OF PACKAGES AND WHAT IS OR IS NOT REPORTED This section provides analyses of qualitative and quantitative differences in packages of the Philippines, Indonesia, Thailand, Malaysia, and the ROK. Table 6 shows the estimated or authorized monetary values as a percent of GDP for the five countries for Measures 01–05 and 10 that the respective countries reported. Cells in the rows for Measures 02 and 03 parenthetically highlight similarities or differences across countries. Cells for Malaysia and the ROK for Measure 10 note that Malaysia’s entry was not clear enough to say which combination of measures within Measures 01–05 the actions most likely fit, whereas for the ROK it appears the actions fit Measures 02, 03, and 04 but with no clear delineation of how much for each. The final two rows list the respective packages as a percent of GDP and in US dollar per capita. Table 6: Comparison of Measures 01 to 05 and 10 for the Philippines, Indonesia, Thailand, Malaysia, and the Republic of Korea, 15 June 2020 Version (% of GDP) Measure Philippines Indonesia Thailand Malaysia Republic of Korea a 1 Liquidity 1.2 1.4 (Actions, but no amounts provided) 1.3 1.1 2 Private credit creation 0.6 (Guarantees) 0.9 (Guarantees) 5.0 (Guarantees; finance bank lending to SMEs) 3.3 (Guarantees) (Guarantees, but no amounts provided 3 Direct lending 0.1 0 2.7 (Corporate bonds) 7.1 (Forbearances) 6.5 (SME loans, corporate bonds) 4 Equity investment 0 0 0 0.1 0.6 5 Direct income support 2.8 3.5 8.3 6.2 2.1 10 No breakdown 0.8 0 0 2.1 (Unclear) 2.1 (Measures 02, 03, 04) Total package (% of GDP) 5.5 5.8 16.0 20.4 12.3 Package per capita ($) 188 229 1,211 2,296 3,730 a GDP = gross domestic product, SMEs = small and medium-sized enterprises. a The Republic of Korea’s package inclusive of Measure 09 (bilateral swaps extended to Bank Indonesia [$7.6 billion] and international aid [$400 million]) is $3,885 per capita. Source: Authors’ calculations based on data from the ADB COVID-19 Policy Database. https://covid19policy.adb.org/.
14 ADB Economics Working Paper Series No. 626 Regarding Measures 01, 02, and 03, it is important to note that all five countries did the following: (i) relaxed liquidity (01B) and capital requirements (02B); (ii) relaxed regulatory oversight to enable banks to restructure customers’ loans (02B, 03B); and (iii) reduced central bank interest rate targets. These are important actions that unfortunately do not translate easily into monetary amounts for reporting. A relatively small minority of countries did report monetary amounts for one or more of these, including, coincidentally, a majority of this sample (Philippines, Indonesia, and Malaysia). 10 On the other hand, Thailand and the ROK reported actions but no accompanying monetary amounts for Measures 01B and 02C, respectively. The packages for the Philippines and Indonesia are substantially smaller as a percent of GDP and in per capita terms than the other three countries. Both have comparatively small amounts for Measures 02 and 03, and similar values for Measures 01 and 05. Looking a bit deeper, Indonesia’s Measure 01B includes almost 0.5% of GDP for reduced liquidity requirements that provide “additional liquidity” available (about 0.1% of GDP) and fewer “demand deposit obligations” (about 0.4% of GDP); the former refers to traditional bank reserve requirements, while the latter refers to more recent macroprudential liquidity regulations. Further, Bank Indonesia also raised a separate liquidity requirement for banks—the “liquidity buffer ratio”—that could only be fulfilled via government bond purchases in the primary market, for which no monetary amounts were reported. The Philippines’ Bangko Sentral ng Pilipinas (BSP) reported the entire amount for its Measure 01 entry also as an increase in liquidity available due to reduced requirements in Measure 01B; on the other hand, BSP was also doing increased open market operation in March (the most severe period of liquidity difficulties) that were later reversed of nearly equal amount to that in Measure 01B. By the same token, Indonesia’s entry for Measure 02 does not include an amount for an additional round of loan guarantees announced on 19 May. Taken altogether, this deeper look appears to net to an amount roughly around the original amounts in the bottom two rows of Table 6 from the ADB database, with perhaps a modest reduction in Measure 01 and a similar increase in Measure 02 for Indonesia. For Thailand and Malaysia, at first sight the two packages seem quite different with nearly $1,100 per capita of separation, but a deeper look suggests their sizes are probably more similar. Recall that Thailand reported actions but not monetary amounts for Measure 01; if we assume these actions amounted to 1.0% of GDP—slightly smaller than the next smallest entry for Measure 01 in the Table (1.1% of GDP for the ROK)—then Thailand’s package is nearly $1,300 per capita. Malaysia’s Bank Negara Malaysia (BNM), like the BSP, and Bank Indonesia, incorporates monetary amounts for Measure 01B that equal 86.0% of the total. Further, Malaysia’s entry for Measure 03 (7.1% of GDP) is mostly due to its inclusion of a monetary estimate in Measure 03B (forbearances) for the impact of a 6-month moratorium and restructuring for SMEs. Thailand likewise reports a “loan payment holiday of 6 months for SMEs and suspension of principal” for Measure 03 but does not report a monetary value like most countries. Overall, to compare “likes to likes,” raising Thailand’s package to account for not reporting monetary values for Measure 01, and reducing Malaysia’s entries for Measures 01 and 03, the two countries’ packages become less than $200 per capita apart (Malaysia’s is still larger), rather than nearly $1,100 apart. 11 10 See also footnote 7 for more information. 11 If Malaysia’s package is actually closer in size in per capita terms to Thailand’s, this is consistent with the results in Table 9 that suggest Malaysia’s reported package is significantly larger than the models predict. The same does not hold for Thailand, for which the regressions also predict much lower values; as a potential explanation for this, the entries for Measure 05 for Thailand in the ADB database report a deliberate attempt by Thailand’s government to pass a fiscal package of 10.0% of GDP, which is a clear anomaly in the database, especially for ADB member economies. The database reports a value less than 10.0% of GDP for Thailand’s Measure 05 because some parts do not fit the database’s definition of “income support” and instead appear in Measures 02 and 03.
An Analysis of the Worldwide Response to the COVID-19 Pandemic 15 The ROK’s package is by far the largest in Table 6 in per capita terms. Two things stand out—the smaller entry for Measure 05 and the lack of a monetary amount for Measure 02. Regarding the latter, the ADB database notes that there are loan guarantees, but their value is a portion of an entry in Measure 05. The database also reports loan guarantees within the collection of actions in the entry for Measure 10. Of course, this does not increase the size of the ROK’s total package, and the loan guarantees inside part of Measure 05 mean the ROK is devoting even less to direct income support than the already small amount shown in the cell (2.1% of GDP). Overall, and given that the ROK’s entry for Measure 10 is most likely not adding to Measure 05, the ROK’s response to COVID-19 puts the most emphasis of the five countries on loan guarantees, lending to and refinancing the private sector, corporate bond purchases, and (to a lesser extent) increasing equity claims of the government and central bank on the private sector and the least emphasis on direct income support to the private sector. To conclude, more in-depth consideration and comparison of packages across these five countries show interesting differences and similarities. The packages of the Philippines and Indonesia look similar in Table 6, and a deeper look confirms this. The packages of Thailand and Malaysia, on the other hand, are far more similar than they appear in Table 6, at least as a percent of GDP and on a per capita basis. As the highest per capita income country of the five, the ROK’s package is perhaps expectedly much larger than the others, but reverses the larger share of direct income support within the total package compared to Thailand and Malaysia. Finally, the analysis here suggests that there may be no “correct” way to report actions that do not have obvious monetary values such as liquidity requirements, capital requirements, and forbearances. However, it is done, the database’s taxonomy recognizes inherently that governments and central banks nevertheless take onto their own financial statements the costs and/or the financial and macroeconomic risks of loosened financial regulations and requirements that creditors and others provide deferred payments and restructuring options. V. WHAT DETERMINES THE SIZE OF A PACKAGE? IS A PACKAGE “ADEQUATE”? In this section, we undertake a preliminary statistical analysis to understand why packages differ in size. We use six proxies of the size: (i) total amount of package per capita, (ii) sum of Measures 01–04 per capita, (iii) Measure 05 per capita, (iv) total amount of package as a share of 2019 GDP, (v) sum of Measures 01–04 as a share of 2019 GDP, and (vi) Measure 05 as a share of 2019 GDP. Figure 3 and Appendix Figures A.1–A.5 graph these six variables against a number of possible correlates (description is provided in Table 7).
16 ADB Economics Working Paper Series No. 626 Figure 3: Package per Capita and Correlates, 15 June 2020 Version COVID-19 = coronavirus disease, GDP = gross domestic product. Note: ADB’s developing members are in red. Other ADB members are in blue. Source: Authors’ calculations. See data sources in Table 7.
An Analysis of the Worldwide Response to the COVID-19 Pandemic 17 Table 7 provides descriptive statistics of the variables (dependent and correlates) used in the analysis using 15 June data. Eighteen economies have package per capita above the mean. The largest package per capita is that of Luxembourg ($29,409), while the smallest is that of Uzbekistan. Twentyseven ADB members have a package per capita that is at most $500; and 50 ADB members have a package per capita that is at most $10,000. Additionally, six ADB members have a package per capita of at least $23,000. Hong Kong, China is the only ADB developing member in the top six. Figure 4 graphs the distribution of the total package per capita. Figure 4: Number of Countries by Total Package per Capita, 15 June 2020 Version Source: Authors’ calculations. See data sources in Table 7. The largest package as percent of GDP is that of Japan, while the smallest is that of the Lao People’s Democratic Republic (Lao PDR). The highest amounts per capita and as percent of GDP of Measure 05 are also those of Japan. Thirty-two ADB members have packages that are at most 10.0% of their GDP; 48 ADB members have package that are at most 20.0% of their GDP. Finally, four ADB members have packages that are at least 50.0% of their GDP. The highest amounts per capita and as percent of GDP of Measures 01–04 are those of Finland. Hong Kong, China ranks second and is the only ADB developing member in the top 10.
18 ADB Economics Working Paper Series No. 626 Table 7: Descriptive Statistics, 15 June 2020 Version Data Sources Mean Std Dev Min Max Total package per capita ($) a ADB COVID-19 Policy Database, World Bank, ADB ADO Database, National Statistics 5,136 8,016 0.98 29,409 Total package as % of GDP a ADB, IMF, ADB ADO Database 13.9 13.6 0.06 59.5 Measure 05 per capita ($) a ADB COVID-19 Policy Database, World Bank, ADB ADO Database, National Statistics 2,004 3,542 0 17,833 Measure 05 as % of GDP a ADB, IMF, ADB ADO Database 6.4 6.8 0 43.4 Sum of Measures 01–04 per capita ($) a ADB COVID-19 Policy Database, World Bank, ADB ADO Database, National Statistics 2,852 5,137 0 20,064 Sum of Measures 01–04 as % of GDP a ADB, IMF, ADB ADO Database 6.5 9.7 0 41.8 Correlates GDP per capita ($) a IMF, World Bank, ADB ADO Database, National Statistics GDP in 2019, population in 2018 22,778 26,023 504 114,283 Difference in estimated 2020 growth rates, before and during COVID-19 pandemic (percentage points) IMF 6.6 2.6 1.16 14.1 COVID-19 cases per 100,000 population as of 15 June 2020 a European Centre for Disease Prevention and Control, Center for Systems Science and Engineering at Johns Hopkins University, Worldometer, World Bank, and National Statistics Cases and deaths in 2020, population in 2018 136 200 0 713 COVID-19 deaths per 100,000 population as of 15 June 2020 a 9 19 0 85 Population of at least 65 years old as % of total population in 2018 World Bank 10.8 6.8 2.58 27.6 Wage and salaried workers as % of total employment in 2019 World Bank 64.2 23.8 17.67 93.8 Self-employed as % of total employment in 2019 World Bank 35.8 23.8 6.22 82.3 Vulnerable employment as % of total employment in 2019 World Bank 32.8 24.5 3.84 80.1 Total stock of debt liabilities issued by the central government as % of GDP in 2018 IMF 50.8 36.6 2.6 198.4 ADO = Asian Development Outlook, COVID-19 = coronavirus disease, GDP = gross domestic product, IMF = International Monetary Fund. a Data calculated based on the listed sources. Source: Authors' compilation and calculation.
An Analysis of the Worldwide Response to the COVID-19 Pandemic 25 VI. CONCLUSIONS This paper has used the ADB COVID-19 Policy Database to analyze the packages implemented by ADB’s 68 members, plus the ECB, and the EU, to combat the COVID-19 pandemic. It has (i) provided a detailed account of the measures taken and the amounts announced between 20 April and 15 June; (ii) discussed the specifics of five Asian countries by comparing their packages qualitatively and quantitatively; and (iii) provided a statistical analysis to understand what determines the size of a package, which allowed comparison between actual and estimated packages, given the correlates. The data we used categorized the measures taken by their effects on financial statements and differences in operations. We captured measures and amounts that may have not been included in other databases and analyses which follow the typical fiscal and monetary policy definitions. As of 15 June 2020, the total package announced amounted to $22.5 trillion, an increase of 36.0% from April. This is broken down into $3.0 for ADB’s developing members, $14 trillion for ADB’s other members, and $5.5 trillion for the ECB and the EU. Credit creation and direct income support make up for much of the total package of all 68 ADB members (including ECB and EU), 47.6% and 31.8%, respectively. Developing members allotted the highest to direct income support, 50.8%, while other members’ priority was credit creation, 53.0%. The packages of the Philippines, Indonesia, Thailand, Malaysia, and the ROK reveal interesting similarities and differences. The packages of the Philippines and Indonesia are similar in terms of percent of GDP and in per capita, substantially lower than those of the three other countries. The packages of Thailand and Malaysia, after adjusting for actions with no monetary amounts, are far more similar than they initially appear, at least as a percent of GDP and on a per capita basis. The package of the ROK is the largest, as expected, but has a lower share of direct income support within the total package than those of Thailand and Malaysia. The statistical analysis shows that the key explanatory variable of the package per capita is income per capita. This variable alone can explain why rich countries dedicated significantly more resources to combat COVID-19 than developing economies. Other variables related to infection severity, population age, and employment are also good predictors. Package per capita is positively related to the COVID-19 deaths per 100,000 population, population of at least 65 years old as percent of total population, and wage and salaried workers as percent of total employment; and inversely related to self-employed as percent of total employment, and vulnerable employment as percent of total employment. Our study used information on the measures announced up until 15 June, a period which can still be considered in the shock phase of the pandemic response. However, the global health crisis and economic downturn is not yet over. It is likely that countries will announce more measures to counter medium- and long-term effects brought about by the pandemic. Moreover, many countries covered in our analysis have actual packages lower than expected packages and may have yet to catch up. A new set of explanatory variables may emerge to explain these future packages.
26 ADB Economics Working Paper Series No. 626
APPENDIX Table A.1: Total Package as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version Total Package as % of GDP (log) on: (1) (2) (3) (4) (5) (6) (7) (8) (9) GDP per capita (log) 0.61*** Difference in estimated 2020 growth rates, before and during COVID-19 pandemic 0.11 COVID-19 cases per 100,000 population as of 15 June 2020 (log) 0.20*** COVID-19 deaths per 100,000 population as of 15 June 2020 (log) 0.21* 0.18 0.18 Population of at least 65 years old as % of total population (log) 1.02*** 0.99*** 0.98*** Wage and salaried workers as % of total employment (log) 1.33** 0.63 Self-employed as % of total employment (log) –0.79*** –0.39 Vulnerable employment as % of total employment (log) –0.66*** –0.33 R 2 0.3590 0.0368 0.1201 0.3500 0.3372 0.3370 0.3677 0.3677 0.3673 No. of observations 63 62 63 56 56 56 56 56 56 COVID-19 = coronavirus disease, GDP = gross domestic product, OLS = ordinary least squares. Notes: (i) We tested for the presence of heteroskedasticity using the Breusch-Pagan test and rejected the null hypothesis (no heteroskedasticity) in models (1), and (3)-(9). Estimation method: OLS with robust standard errors; (ii) Model 1: All regional fixed effects (FE) are insignificant. Model 2: East Asia is the only insignificant regional FE. Model 3: Central and West Asia is the only significant regional FE. Model 4: All regional FE are insignificant. Models 5-9: East Asia is the only significant regional FE. *** means significant at 1%, ** at 5%, and * at 10%. Source: Authors' calculations. See data sources in Table 7.
28 Appendixes Table A.2: Measure 05 per Capita and Correlates, 15 June 2020 Version Measure 05 per capita (log) on: (1) (2) (3) (4) (5) (6) (7) (8) (9) GDP per capita (log) 1.49*** Difference in estimated 2020 growth rates, before and during COVID-19 pandemic 0.37*** COVID-19 cases per 100,000 population as of 15 June 2020 (log) 0.43*** COVID-19 deaths per 100,000 population as of 15 June 2020 (log) 0.39** 0.29 0.27 Population of at least 65 years old as % of total population (log) 2.42*** 2.16** 2.12** Wage and salaried workers as % of total employment (log) 3.14*** 1.25 Self-employed as % of total employment (log) –2.03*** –1.00 Vulnerable employment as % of total employment (log) –1.72*** –0.86 R 2 0.6435 0.1334 0.1781 0.4911 0.5082 0.5133 0.5722 0.5854 0.5866 No. of observations 63 62 63 56 56 56 56 56 56 COVID-19 = coronavirus disease, GDP = gross domestic product, OLS = ordinary least squares. Notes: (i) We tested for the presence of heteroskedasticity using the Breusch-Pagan test and rejected the null hypothesis (no heteroskedasticity) in models (7)-(9). Estimation method: OLS with robust standard errors; (ii) Model 1: All regional fixed effects (FE) are insignificant. Model 2: East Asia is the only insignificant regional FE. Model 3: East Asia and the Pacific are insignificant regional FE. Model 4: Southeast Asia and Central and West Asia are the only significant regional FE. Models 5-7: Central and West Asia is the only significant regional FE. Models 8-9: All regional FE are insignificant. *** means significant at 1%, ** at 5%, and * at 10%. Source: Authors' calculations. See data sources in Table 7.
Appendixes 29 Table A.3: Measure 05 as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version Measure 05 as % of GDP (log) on: (1) (2) (3) (4) (5) (6) (7) (8) (9) GDP per capita (log) 0.53*** Difference in estimated 2020 growth rates, before and during COVID-19 pandemic 0.09 COVID-19 cases per 100,000 population as of 15 June 2020 (log) 0.10 COVID-19 deaths per 100,000 population as of 15 June 2020 (log) 0.13 0.10 0.09 Population of at least 65 years old as % of total population (log) 0.70* 0.60 0.60 Wage and salaried workers as % of total employment (log) 1.21** 0.71 Self-employed as % of total employment (log) –0.78*** –0.51 Vulnerable employment as % of total employment (log) –0.65*** –0.42 R 2 0.2580 0.0225 0.0319 0.2250 0.2311 0.2295 0.2389 0.2467 0.2452 No. of observations 63 62 63 56 56 56 56 56 56 COVID-19 = coronavirus disease, GDP = gross domestic product, OLS = ordinary least squares. Notes: (i) We tested for the presence of heteroskedasticity using the Breusch-Pagan test and rejected the null hypothesis (no heteroskedasticity) in all models. Estimation method: OLS with robust standard errors; (ii) Model 1: Pacific is the only significant regional fixed effects (FE). Model 2: East Asia and the Pacific are the only insignificant regional FE. Model 3: Central and West Asia is the only significant regional FE. Models 4-9: All regional FEare insignificant. *** means significant at 1%, ** at 5%, and * at 10%. Source: Authors' calculations. See data sources in Table 7.
30 Appendixes Table A.4: Sum of Measures 01 to 04 per Capita and Correlates, 15 June 2020 Version Sum of Measures 01–04 per capita (log) on: (1) (2) (3) (4) (5) (6) (7) (8) (9) GPD per capita (log) 2.05*** Difference in estimated 2020 growth rates, before and during COVID-19 pandemic 0.42* COVID-19 cases per 100,000 population as of 15 June 2020 (log) 0.96*** COVID-19 deaths per 100,000 population as of 15 June 2020 (log) 0.42*** 0.23* 0.19 Population of at least 65 years old as % of total population (log) 3.30*** 2.61*** 2.48*** Wage and salaried workers as % of total employment (log) 4.53*** 1.75* Self-employed as % of total employment (log) –3.17*** –1.76*** Vulnerable employment as % of total employment (log) –2.72*** –1.57*** R 2 0.6489 0.0926 0.4572 0.5708 0.6509 0.6678 0.7013 0.7429 0.7498 No. of observations 63 62 63 56 56 56 56 56 56 COVID-19 = coronavirus disease, GDP = gross domestic product, OLS = ordinary least squares. Notes: (i) We tested for the presence of heteroskedasticity using the Breusch-Pagan test and rejected the null hypothesis (no heteroskedasticity) in models (2) and (5)-(9). Estimation method: OLS with robust standard errors; (ii) Model 1: East Asia is the only insignificant regional fixed effects (FE). Model 2: All regional FE are significant. Models 3-5: East Asia is the only insignificant regional FE. Model 6: Southeast Asia and East Asia are the only insignificant regional FE. Model 7: South Asia and Central and West Asia are the only significant regional FE. Models 8-9: East Asia is the only significant regional FE. *** means significant at 1%, ** at 5%, and * at 10%. Source: Authors' calculations. See data sources in Table 7.
Appendixes 31 Table A.5: Sum of Measures 01 to 04 as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version Sum of Measures 01–04 as % of GDP (log) on: (1) (2) (3) (4) (5) (6) (7) (8) (9) GPD per capita (log) 0.67*** Difference in estimated 2020 growth rates, before and during COVID-19 pandemic 0 .13** COVID-19 cases per 100,000 population as of 15 June 2020 (log) 0.30*** COVID-19 deaths per 100,000 population as of 15 June 2020 (log) 0.13 0.07 0.05 Population of at least 65 years old as % of total population (log) 1.18*** 0.94*** 0.90*** Wage and salaried workers as % of total employment (log) 1.59*** 0.57 Self-employed as % of total employment (log) –1.12*** –0.59** Vulnerable employment as % of total employment (log) –0.96*** –0.52** R 2 0.4684 0.0588 0.2944 0.3970 0.4569 0.4688 0.5033 0.5312 0.5354 No. of observations 63 62 63 56 56 56 56 56 56 COVID-19 = coronavirus disease, GDP = gross domestic product, OLS = ordinary least squares. Notes: (i) We tested the presence of heteroskedasticity using the Breusch-Pagan test and could not reject the null hypothesis (no heteroskedasticity). Estimation method: OLS with robust standard errors; (ii) Model 1: The Pacific is the only significant regional fixed effects (FE). Models 2-3: East Asia is the only insignificant regional FE. Model 4: Central and West Asia and the Pacific are the only significant regional FE. Models 5-7: All regional FE are insignificant. Models 8-9: East Asia is the only significant regional FE. *** means significant at 1%, ** at 5%, and * at 10%. Source: Authors' calculations. See data sources in Table 7.
32 Appendixes Figure A.1: Total Package as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version COVID-19 = coronavirus disease, GDP = gross domestic product. Note: ADB’s developing members are in red. Other ADB members are in blue. Source: Authors’ calculations. See data sources in Table 7.
Appendixes 33 Figure A.2: Measure 05 per Capita and Correlates, 15 June 2020 Version COVID-19 = coronavirus disease, GDP = gross domestic product. Note: ADB’s developing members are in red. Other ADB members are in blue. Source: Authors’ calculations. See data sources in Table 7.
34 Appendixes Figure A.3: Measure 05 as Percent of Gross Domestic Product and Correlates, 15 June 2020 Version COVID-19 = coronavirus disease, GDP = gross domestic product. Note: ADB’s developing members are in red. Other ADB members are in blue. Source: Authors’ calculations. See data sources in Table 7.