This overview chapter discusses the evolution of and outlook for global external positions and summarizes the IMF staff’s external assessments for a globally representative set of economies in 2019, which are also detailed in Chapter 3, “2019 Individual Economy Assessments. “ These assessments are multilaterally consistent and draw on the latest vintage of the External Balance Assessment (EBA) methodology and consider a full set of external indicators, including current accounts, exchange rates, external balance sheets, capital flows, and international reserves. The assessments’ objectives and concepts are summarized in Box 1.1. The chapter is organized as follows: the first section, “Global Imbalances before the COVID-19 Crisis,” documents the evolution of current accounts, exchange rates, and international trade in 2019. It also presents IMF staff external sector assessments for 2019, providing a benchmark for assessing external positions as they were before the onset of the COVID-19 pandemic. The second section, “External Developments during the COVID-19 Crisis,” discusses the evolution of exchange rates, international trade in goods and services, capital flows, and current account balances in 2020, drawing on both recent data and IMF staff forecasts. The third section, “Significant Risks to the External Outlook,” discusses the elevated uncertainties and risks currently pertaining to the outlook. The final section, “Policy Priorities,” discusses policy responses for addressing these risks and responding to the crisis as well as reforms to reduce excess imbalances over the medium term in a manner supportive of global growth.
Global Imbalances before the COVID-19 Crisis
Current account surpluses and deficits narrowed modestly in the years preceding the coronavirus (COVID-19) crisis. In 2019 the global current account balance (the absolute sum of all surpluses and deficits) declined by 0.2 percentage point of world GDP, to 2.9 percent of world GDP (Figure 1.1; Table 1.1). Oil-exporting economies saw their current account surpluses decline, reflecting, on average, lower oil prices. The euro area surplus declined by 0.4 percentage point of GDP, to 2.7 percent of GDP, reflecting weaknesses in services and investment income balances. Chinas current account surplus rose by 0.8 percentage point of GDP to 1.0 percent of GDP, reflecting the economic slowdown, lower commodity and semiconductor import prices, and the import response to expected and realized tariff hikes, which lowered the trade balances in 2018, with an unwinding in 2019. Current account balances also rose toward surplus in some emerging market and developing economies (Argentina, South Africa, Turkey) in 2019 as a result of tighter financial conditions, lower domestic demand, or currency depreciation. Other systemic economies’ external balances moved little. The US current account deficit decreased by 0.1 percentage point of GDP to 2.3 percent of GDP, and Japans surplus remained at 3.6 percent of GDP.
Selected Economies: Current Account Balance, 2017–20
For India, data are presented on a fiscal year basis.
Overall surpluses and deficits (and the of which advanced economies) include non-External Sector Report countries.
Selected Economies: Current Account Balance, 2017–20
Billions of USD | Percent of World GDP | Percent of GDP | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2017 | 2018 | 2019 | 2020 Projection | 2017 | 2018 | 2019 | 2020 Projection | 2017 | 2018 | 2019 | 2020 Projection | |||||
Advanced Economies | ||||||||||||||||
Australia | -35 | -29 | 8 | 15 | 0.0 | 0.0 | 0.0 | 0.0 | -2.6 | -2.0 | 0.6 | 1.2 | ||||
Belgium | 6 | -8 | -7 | -3 | 0.0 | 0.0 | 0.0 | 0.0 | 1.2 | -1.4 | -1.2 | -0.6 | ||||
Canada | -46 | -43 | -35 | -57 | -0.1 | -0.1 | 0.0 | -0.1 | -2.8 | -2.5 | -2.0 | -3.7 | ||||
France | -20 | -16 | -18 | -12 | 0.0 | 0.0 | 0.0 | 0.0 | -0.8 | -0.6 | -0.7 | -0.5 | ||||
Germany | 287 | 292 | 275 | 199 | 0.4 | 0.3 | 0.3 | 0.2 | 7.8 | 7.4 | 7.1 | 5.6 | ||||
Hong Kong SAR | 16 | 14 | 23 | 21 | 0.0 | 0.0 | 0.0 | 0.0 | 4.6 | 3.7 | 6.2 | 5.9 | ||||
Italy | 50 | 52 | 59 | 61 | 0.1 | 0.1 | 0.1 | 0.1 | 2.6 | 2.5 | 3.0 | 3.6 | ||||
Japan | 203 | 177 | 184 | 157 | 0.3 | 0.2 | 0.2 | 0.2 | 4.2 | 3.6 | 3.6 | 3.2 | ||||
Korea | 75 | 77 | 60 | 51 | 0.1 | 0.1 | 0.1 | 0.1 | 4.6 | 4.5 | 3.6 | 3.4 | ||||
Netherlands | 90 | 99 | 93 | 66 | 0.1 | 0.1 | 0.1 | 0.1 | 10.8 | 10.9 | 10.2 | 8.0 | ||||
Singapore | 56 | 64 | 63 | 44 | 0.1 | 0.1 | 0.1 | 0.1 | 16.3 | 17.2 | 17.0 | 13.0 | ||||
Spain | 35 | 28 | 28 | 22 | 0.0 | 0.0 | 0.0 | 0.0 | 2.7 | 1.9 | 2.0 | 1.8 | ||||
Sweden | 17 | 14 | 22 | 14 | 0.0 | 0.0 | 0.0 | 0.0 | 3.1 | 2.5 | 4.2 | 2.8 | ||||
Switzerland | 44 | 58 | 81 | 57 | 0.1 | 0.1 | 0.1 | 0.1 | 9.8 | 9.8 | 11.5 | 8.5 | ||||
United Kingdom | -93 | -111 | -107 | –88 | -0.1 | -0.1 | -0.1 | -0.1 | -3.5 | -3.9 | -3.8 | -3.5 | ||||
United States | -440 | -491 | -498 | -402 | -0.5 | -0.6 | -0.6 | -0.5 | -2.3 | -2.4 | -2.3 | -2.0 | ||||
Emerging Market and Developing Economies | ||||||||||||||||
Argentina | -31 | -27 | -3 | … | 0.0 | 0.0 | 0.0 | … | -4.8 | -5.2 | -0.8 | … | ||||
Brazil | -15 | -42 | -49 | –22 | 0.0 | 0.0 | -0.1 | 0.0 | -0.7 | -2.2 | -2.7 | -1.7 | ||||
China | 195 | 25 | 141 | 195 | 0.2 | 0.0 | 0.2 | 0.2 | 1.6 | 0.2 | 1.0 | 1.3 | ||||
India1 | -49 | -57 | -27 | -9 | -0.1 | -0.1 | 0.0 | 0.0 | -1.8 | -2.1 | -0.9 | -0.3 | ||||
Indonesia | -16 | -31 | -30 | -18 | 0.0 | 0.0 | 0.0 | 0.0 | -1.6 | -2.9 | -2.7 | -1.6 | ||||
Malaysia | 9 | 8 | 12 | 2 | 0.0 | 0.0 | 0.0 | 0.0 | 2.8 | 2.2 | 3.4 | 0.5 | ||||
Mexico | -20 | -25 | -4 | -2 | 0.0 | 0.0 | 0.0 | 0.0 | -1.8 | -2.1 | -0.3 | -0.2 | ||||
Poland | 0 | -6 | 3 | 9 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.5 | 1.5 | ||||
Russia | 32 | 114 | 65 | -2 | 0.0 | 0.1 | 0.1 | 0.0 | 2.1 | 6.8 | 3.8 | -0.1 | ||||
Saudi Arabia | 10 | 72 | 47 | -32 | 0.0 | 0.1 | 0.1 | 0.0 | 1.5 | 9.2 | 5.9 | -4.9 | ||||
South Africa | -9 | -13 | -11 | -5 | 0.0 | 0.0 | 0.0 | 0.0 | -2.5 | -3.5 | -3.0 | -1.8 | ||||
Thailand | 44 | 28 | 38 | 25 | 0.1 | 0.0 | 0.0 | 0.0 | 9.6 | 5.6 | 7.0 | 4.9 | ||||
Turkey | -41 | -21 | 9 | 0.1 | -0.1 | 0.0 | 0.0 | 0.0 | -4.8 | -2.7 | 1.2 | 0.0 | ||||
Memorandum item:2 | ||||||||||||||||
Euro Area | 393 | 426 | 359 | 274 | 0.5 | 0.5 | 0.4 | 0.3 | 3.1 | 3.1 | 2.7 | 2.3 | ||||
Statistical Discrepancy | 394 | 315 | 387 | 39 | 0.5 | 0.4 | 0.4 | 0.0 | … | … | … | … | ||||
Overall Surpluses | 1,439 | 1,495 | 1,465 | 1,078 | 1.8 | 1.7 | 1.7 | 1.3 | … | … | … | … | ||||
Of which: Advanced Economies | 1,038 | 1,074 | 1,042 | 824 | 1.3 | 1.3 | 1.2 | 1.0 | … | … | … | … | ||||
Overall Deficits | -1,045 | -1,180 | -1,078 | -1,039 | -1.3 | -1.4 | -1.2 | -1.3 | … | … | … | … | ||||
Of which: Advanced Economies | -650 | -721 | -721 | -607 | -0.8 | -0.8 | -0.8 | -0.7 | … | … | … | … |
For India, data are presented on a fiscal year basis.
Overall surpluses and deficits (and the of which advanced economies) include non-External Sector Report countries.
Selected Economies: Current Account Balance, 2017–20
Billions of USD | Percent of World GDP | Percent of GDP | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2017 | 2018 | 2019 | 2020 Projection | 2017 | 2018 | 2019 | 2020 Projection | 2017 | 2018 | 2019 | 2020 Projection | |||||
Advanced Economies | ||||||||||||||||
Australia | -35 | -29 | 8 | 15 | 0.0 | 0.0 | 0.0 | 0.0 | -2.6 | -2.0 | 0.6 | 1.2 | ||||
Belgium | 6 | -8 | -7 | -3 | 0.0 | 0.0 | 0.0 | 0.0 | 1.2 | -1.4 | -1.2 | -0.6 | ||||
Canada | -46 | -43 | -35 | -57 | -0.1 | -0.1 | 0.0 | -0.1 | -2.8 | -2.5 | -2.0 | -3.7 | ||||
France | -20 | -16 | -18 | -12 | 0.0 | 0.0 | 0.0 | 0.0 | -0.8 | -0.6 | -0.7 | -0.5 | ||||
Germany | 287 | 292 | 275 | 199 | 0.4 | 0.3 | 0.3 | 0.2 | 7.8 | 7.4 | 7.1 | 5.6 | ||||
Hong Kong SAR | 16 | 14 | 23 | 21 | 0.0 | 0.0 | 0.0 | 0.0 | 4.6 | 3.7 | 6.2 | 5.9 | ||||
Italy | 50 | 52 | 59 | 61 | 0.1 | 0.1 | 0.1 | 0.1 | 2.6 | 2.5 | 3.0 | 3.6 | ||||
Japan | 203 | 177 | 184 | 157 | 0.3 | 0.2 | 0.2 | 0.2 | 4.2 | 3.6 | 3.6 | 3.2 | ||||
Korea | 75 | 77 | 60 | 51 | 0.1 | 0.1 | 0.1 | 0.1 | 4.6 | 4.5 | 3.6 | 3.4 | ||||
Netherlands | 90 | 99 | 93 | 66 | 0.1 | 0.1 | 0.1 | 0.1 | 10.8 | 10.9 | 10.2 | 8.0 | ||||
Singapore | 56 | 64 | 63 | 44 | 0.1 | 0.1 | 0.1 | 0.1 | 16.3 | 17.2 | 17.0 | 13.0 | ||||
Spain | 35 | 28 | 28 | 22 | 0.0 | 0.0 | 0.0 | 0.0 | 2.7 | 1.9 | 2.0 | 1.8 | ||||
Sweden | 17 | 14 | 22 | 14 | 0.0 | 0.0 | 0.0 | 0.0 | 3.1 | 2.5 | 4.2 | 2.8 | ||||
Switzerland | 44 | 58 | 81 | 57 | 0.1 | 0.1 | 0.1 | 0.1 | 9.8 | 9.8 | 11.5 | 8.5 | ||||
United Kingdom | -93 | -111 | -107 | –88 | -0.1 | -0.1 | -0.1 | -0.1 | -3.5 | -3.9 | -3.8 | -3.5 | ||||
United States | -440 | -491 | -498 | -402 | -0.5 | -0.6 | -0.6 | -0.5 | -2.3 | -2.4 | -2.3 | -2.0 | ||||
Emerging Market and Developing Economies | ||||||||||||||||
Argentina | -31 | -27 | -3 | … | 0.0 | 0.0 | 0.0 | … | -4.8 | -5.2 | -0.8 | … | ||||
Brazil | -15 | -42 | -49 | –22 | 0.0 | 0.0 | -0.1 | 0.0 | -0.7 | -2.2 | -2.7 | -1.7 | ||||
China | 195 | 25 | 141 | 195 | 0.2 | 0.0 | 0.2 | 0.2 | 1.6 | 0.2 | 1.0 | 1.3 | ||||
India1 | -49 | -57 | -27 | -9 | -0.1 | -0.1 | 0.0 | 0.0 | -1.8 | -2.1 | -0.9 | -0.3 | ||||
Indonesia | -16 | -31 | -30 | -18 | 0.0 | 0.0 | 0.0 | 0.0 | -1.6 | -2.9 | -2.7 | -1.6 | ||||
Malaysia | 9 | 8 | 12 | 2 | 0.0 | 0.0 | 0.0 | 0.0 | 2.8 | 2.2 | 3.4 | 0.5 | ||||
Mexico | -20 | -25 | -4 | -2 | 0.0 | 0.0 | 0.0 | 0.0 | -1.8 | -2.1 | -0.3 | -0.2 | ||||
Poland | 0 | -6 | 3 | 9 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.5 | 1.5 | ||||
Russia | 32 | 114 | 65 | -2 | 0.0 | 0.1 | 0.1 | 0.0 | 2.1 | 6.8 | 3.8 | -0.1 | ||||
Saudi Arabia | 10 | 72 | 47 | -32 | 0.0 | 0.1 | 0.1 | 0.0 | 1.5 | 9.2 | 5.9 | -4.9 | ||||
South Africa | -9 | -13 | -11 | -5 | 0.0 | 0.0 | 0.0 | 0.0 | -2.5 | -3.5 | -3.0 | -1.8 | ||||
Thailand | 44 | 28 | 38 | 25 | 0.1 | 0.0 | 0.0 | 0.0 | 9.6 | 5.6 | 7.0 | 4.9 | ||||
Turkey | -41 | -21 | 9 | 0.1 | -0.1 | 0.0 | 0.0 | 0.0 | -4.8 | -2.7 | 1.2 | 0.0 | ||||
Memorandum item:2 | ||||||||||||||||
Euro Area | 393 | 426 | 359 | 274 | 0.5 | 0.5 | 0.4 | 0.3 | 3.1 | 3.1 | 2.7 | 2.3 | ||||
Statistical Discrepancy | 394 | 315 | 387 | 39 | 0.5 | 0.4 | 0.4 | 0.0 | … | … | … | … | ||||
Overall Surpluses | 1,439 | 1,495 | 1,465 | 1,078 | 1.8 | 1.7 | 1.7 | 1.3 | … | … | … | … | ||||
Of which: Advanced Economies | 1,038 | 1,074 | 1,042 | 824 | 1.3 | 1.3 | 1.2 | 1.0 | … | … | … | … | ||||
Overall Deficits | -1,045 | -1,180 | -1,078 | -1,039 | -1.3 | -1.4 | -1.2 | -1.3 | … | … | … | … | ||||
Of which: Advanced Economies | -650 | -721 | -721 | -607 | -0.8 | -0.8 | -0.8 | -0.7 | … | … | … | … |
For India, data are presented on a fiscal year basis.
Overall surpluses and deficits (and the of which advanced economies) include non-External Sector Report countries.
Currency movements were generally modest, with a number of exceptions. The US dollar and the Japanese yen appreciated about 3 percent in 2019 in real effective terms, while the euro and the renminbi depreciated by 3 percent and 0.8 percent, respectively. Some emerging market and developing economies (India, Indonesia, Mexico, Thailand) saw their currencies appreciate by 3 percent to 6 percent in real effective terms, reflecting a partial rebound from sharp depreciations in 2018. A number of emerging market and developing economies with preexisting vulnerabilities experienced large currency depreciations. In Argentina, the peso depreciated almost 42 percent vis-à-vis the US dollar, although relatively high inflation limited the real effective depreciation to 11 percent. The currencies of Brazil, South Africa, and Turkey depreciated vis-à-vis the US dollar by 8 percent to 14 percent, also with smaller real effective depreciations.
Trade tensions contributed to currency and financial market fluctuations. US–China trade tensions escalated for much of 2019, with the average US tariff on Chinese imports increasing from 12.0 percent to 21.0 percent, and Chinas average tariff on US imports rising from 16.5 percent to 21.1 percent. The announcement and implementation of these trade policy changes during 2018 and 2019 triggered significant declines in equity prices and offsetting currency movements, with much of the depreciation in the renminbi during this period driven by trade policy announcements (Box 1.2). In early 2020 the United States and China agreed to a “Phase One” economic and trade agreement, with a partial rollback of previously implemented tariffs and a truce on new tariffs. Trade tensions also deescalated on other fronts in late 2019 with the signing of the United States-Mexico-Canada Agreement, which went into effect on July 1, 2020.
Furthermore, the stocks of external assets and liabilities have reached historic highs, with attendant risks to both debtor and creditor economies. External assets and liabilities as a share of GDP more than tripled from the early 1990s to the years preceding the COVID-19 crisis (Figure 1.2). This sharp increase, both in gross and net terms, has raised questions regarding its sustainability, as well as the associated macroeconomic vulnerabilities. The widening stock positions reflect the persistence of the associated current account surpluses and deficits of the world’s systemic economies. The United States has the largest net debtor position as a share of world GDP. The largest net creditor economies in percent of world GDP are China, Germany, and Japan (Table 1.2). In terms of currency exposures, most emerging market and developing economies went from having short positions in foreign currency in 1990 to long positions in 2017, reflecting a shift in foreign liabilities from foreign currency debt to equity financing and, in general, sustained accumulation of foreign exchange reserves. Most advanced economies were already long in foreign currency in 1990, and their net positions have continued to grow.
External Assets and Liabilities, 1990–2019
Sources: Bénétrix and others (2019); External Wealth of Nations database; IMF, World Economic Outlook (WEO); and IMF staff estimates.Note: AEs = advanced economies; DC = domestic currency; EA = euro area; EMs = emerging markets; FC = foreign currency; FX = foreign exchange; IIP = international investment position. Data labels use International Organization for Standardization (ISO) country codes.1 Creditor AEs comprise Hong Kong SAR, Korea, Singapore, Sweden, Switzerland, Taiwan Province of China; AE commodity exporters comprise Australia, Canada, New Zealand; deficit EMs comprise Brazil, India, Indonesia, Mexico, South Africa, Turkey; oil exporters comprise WEO definition plus Norway.2 Comprises 50 countries which are part of the IMF External Balance Assessment model and/or External Sector Report, except Costa Rica and Saudi Arabia.3 Aggregate foreign currency exposure is defined as net foreign assets denominated in foreign currency as a share of total assets and total liabilities.External Assets and Liabilities, 1990–2019
Sources: Bénétrix and others (2019); External Wealth of Nations database; IMF, World Economic Outlook (WEO); and IMF staff estimates.Note: AEs = advanced economies; DC = domestic currency; EA = euro area; EMs = emerging markets; FC = foreign currency; FX = foreign exchange; IIP = international investment position. Data labels use International Organization for Standardization (ISO) country codes.1 Creditor AEs comprise Hong Kong SAR, Korea, Singapore, Sweden, Switzerland, Taiwan Province of China; AE commodity exporters comprise Australia, Canada, New Zealand; deficit EMs comprise Brazil, India, Indonesia, Mexico, South Africa, Turkey; oil exporters comprise WEO definition plus Norway.2 Comprises 50 countries which are part of the IMF External Balance Assessment model and/or External Sector Report, except Costa Rica and Saudi Arabia.3 Aggregate foreign currency exposure is defined as net foreign assets denominated in foreign currency as a share of total assets and total liabilities.External Assets and Liabilities, 1990–2019
Sources: Bénétrix and others (2019); External Wealth of Nations database; IMF, World Economic Outlook (WEO); and IMF staff estimates.Note: AEs = advanced economies; DC = domestic currency; EA = euro area; EMs = emerging markets; FC = foreign currency; FX = foreign exchange; IIP = international investment position. Data labels use International Organization for Standardization (ISO) country codes.1 Creditor AEs comprise Hong Kong SAR, Korea, Singapore, Sweden, Switzerland, Taiwan Province of China; AE commodity exporters comprise Australia, Canada, New Zealand; deficit EMs comprise Brazil, India, Indonesia, Mexico, South Africa, Turkey; oil exporters comprise WEO definition plus Norway.2 Comprises 50 countries which are part of the IMF External Balance Assessment model and/or External Sector Report, except Costa Rica and Saudi Arabia.3 Aggregate foreign currency exposure is defined as net foreign assets denominated in foreign currency as a share of total assets and total liabilities.Selected Economies: Net International Investment Position, 2016–19
Selected Economies: Net International Investment Position, 2016–19
Billions of USD | Percent of World GDP | Percent of GDP | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2016 | 2017 | 2018 | 2019 | 2016 | 2017 | 2018 | 2019 | 2016 | 2017 | 2018 | 2019 | |||||
Advanced Economies | ||||||||||||||||
Australia | -712 | -752 | -731 | -632 | -0.9 | -0.9 | -0.9 | -0.7 | -56.2 | -54.2 | -51.4 | -45.6 | ||||
Belgium | 249 | 293 | 199 | 199 | 0.3 | 0.4 | 0.2 | 0.2 | 52.4 | 58.1 | 36.7 | 37.6 | ||||
Canada | 306 | 576 | 575 | 767 | 0.4 | 0.7 | 0.7 | 0.9 | 20.0 | 34.9 | 33.5 | 44.2 | ||||
France | -306 | -547 | -506 | -507 | -0.4 | -0.7 | -0.6 | -0.6 | -12.4 | -21.1 | -18.1 | -18.7 | ||||
Germany | 1,697 | 2,162 | 2,381 | 2,718 | 2.2 | 2.7 | 2.8 | 3.1 | 48.9 | 59.0 | 60.3 | 70.7 | ||||
Hong Kong SAR | 1,154 | 1,421 | 1,283 | 1,563 | 1.5 | 1.8 | 1.5 | 1.8 | 359.6 | 416.5 | 354.6 | 427.4 | ||||
Italy | -213 | -158 | -100 | –33 | -0.3 | -0.2 | -0.1 | 0.0 | -11.4 | -8.1 | -4.8 | -1.6 | ||||
Japan | 2,902 | 2,915 | 3,033 | 3,393 | 3.8 | 3.6 | 3.5 | 3.9 | 58.9 | 59.9 | 61.2 | 66.8 | ||||
Korea | 281 | 262 | 436 | 501 | 0.4 | 0.3 | 0.5 | 0.6 | 18.7 | 16.1 | 25.3 | 30.4 | ||||
Netherlands | 458 | 519 | 623 | 809 | 0.6 | 0.6 | 0.7 | 0.9 | 58.5 | 62.3 | 68.1 | 89.0 | ||||
Singapore | 754 | 867 | 770 | 896 | 1.0 | 1.1 | 0.9 | 1.0 | 236.7 | 253.7 | 206.3 | 240.8 | ||||
Spain | -1,004 | -1,176 | -1,098 | -1,024 | -1.3 | -1.5 | -1.3 | -1.2 | -81.5 | -89.6 | -77.3 | -73.5 | ||||
Sweden | -9 | 8 | 43 | 112 | 0.0 | 0.0 | 0.1 | 0.1 | -1.7 | 1.4 | 7.8 | 21.0 | ||||
Switzerland | 811 | 857 | 883 | 826 | 1.1 | 1.1 | 1.0 | 0.9 | 120.7 | 126.0 | 125.2 | 117.4 | ||||
United Kingdom | 9 | -268 | -368 | -713 | 0.0 | -0.3 | -0.4 | -0.8 | 0.3 | -10.0 | -12.8 | -25.2 | ||||
United States | -8,192 | -7,743 | -9,555 | -10,991 | -10.8 | -9.6 | -11.2 | -12.6 | -43.8 | -39.7 | -46.4 | -51.3 | ||||
Emerging Market and Developing Economies | ||||||||||||||||
Argentina | 48 | 17 | 65 | 118 | 0.1 | 0.0 | 0.1 | 0.1 | 8.6 | 2.7 | 12.6 | 26.2 | ||||
Brazil | -567 | -645 | -594 | -732 | -0.7 | -0.8 | -0.7 | -0.8 | -31.6 | -31.3 | -31.5 | -39.8 | ||||
China | 1,950 | 2,101 | 2,146 | 2,124 | 2.6 | 2.6 | 2.5 | 2.4 | 17.4 | 17.1 | 15.5 | 14.4 | ||||
India | -394 | -424 | -437 | -455 | -0.5 | -0.5 | -0.5 | -0.5 | -17.2 | -16.0 | -16.1 | -15.0 | ||||
Indonesia | -334 | -323 | -318 | -350 | -0.4 | -0.4 | -0.4 | -0.4 | -35.8 | -31.8 | -30.5 | -31.2 | ||||
Malaysia | 16 | -8 | -18 | -5 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2 | -2.4 | -4.9 | -1.5 | ||||
Mexico | -532 | -556 | -591 | -655 | -0.7 | -0.7 | -0.7 | -0.7 | -49.4 | -48.0 | -48.4 | -52.1 | ||||
Poland | -274 | -350 | -314 | -298 | -0.4 | -0.4 | -0.4 | -0.3 | -58.1 | -66.4 | -53.4 | -50.3 | ||||
Russia | 220 | 281 | 374 | 357 | 0.3 | 0.3 | 0.4 | 0.4 | 17.2 | 17.8 | 22.4 | 21.0 | ||||
Saudi Arabia | 597 | 624 | 632 | 683 | 0.8 | 0.8 | 0.7 | 0.8 | 92.6 | 90.6 | 80.3 | 86.1 | ||||
South Africa | 22 | 35 | 45 | 29 | 0.0 | 0.0 | 0.1 | 0.0 | 7.5 | 9.9 | 12.3 | 8.0 | ||||
Thailand | –33 | -36 | -11 | -10 | 0.0 | 0.0 | 0.0 | 0.0 | -7.9 | -8.0 | -2.2 | -1.8 | ||||
Turkey | -368 | -463 | -371 | -345 | -0.5 | -0.6 | -0.4 | -0.4 | -42.6 | -54.2 | -48.2 | -45.8 | ||||
Memorandum item: | ||||||||||||||||
Euro Area | -984 | -1,044 | -607 | -70 | -1.3 | -1.3 | -0.7 | -0.1 | -8.2 | -8.3 | -4.4 | -0.5 | ||||
Statistical Discrepancy | -1,733 | -912 | -2,020 | -1,979 | -2.3 | -1.1 | -2.4 | -2.3 | … | … | … | … | ||||
Overall Creditors | 14,085 | 15,817 | 16,432 | 18,316 | 18.6 | 19.6 | 19.2 | 20.9 | … | … | … | … | ||||
Of which: | 10,797 | 12,325 | 12,732 | 14,568 | 14.2 | 15.3 | 14.9 | 16.7 | … | … | … | … | ||||
Advanced | ||||||||||||||||
Economies | ||||||||||||||||
Overall Debtors | -15,818 | -16,729 | -18,453 | -20,295 | -20.9 | -20.8 | -21.6 | -23.2 | … | … | … | … | ||||
Of which: | -11,715 | -12,102 | -13,870 | -15,426 | -15.5 | -15.0 | -16.2 | -17.6 | … | … | … | … | ||||
Advanced | ||||||||||||||||
Economies |
Selected Economies: Net International Investment Position, 2016–19
Billions of USD | Percent of World GDP | Percent of GDP | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2016 | 2017 | 2018 | 2019 | 2016 | 2017 | 2018 | 2019 | 2016 | 2017 | 2018 | 2019 | |||||
Advanced Economies | ||||||||||||||||
Australia | -712 | -752 | -731 | -632 | -0.9 | -0.9 | -0.9 | -0.7 | -56.2 | -54.2 | -51.4 | -45.6 | ||||
Belgium | 249 | 293 | 199 | 199 | 0.3 | 0.4 | 0.2 | 0.2 | 52.4 | 58.1 | 36.7 | 37.6 | ||||
Canada | 306 | 576 | 575 | 767 | 0.4 | 0.7 | 0.7 | 0.9 | 20.0 | 34.9 | 33.5 | 44.2 | ||||
France | -306 | -547 | -506 | -507 | -0.4 | -0.7 | -0.6 | -0.6 | -12.4 | -21.1 | -18.1 | -18.7 | ||||
Germany | 1,697 | 2,162 | 2,381 | 2,718 | 2.2 | 2.7 | 2.8 | 3.1 | 48.9 | 59.0 | 60.3 | 70.7 | ||||
Hong Kong SAR | 1,154 | 1,421 | 1,283 | 1,563 | 1.5 | 1.8 | 1.5 | 1.8 | 359.6 | 416.5 | 354.6 | 427.4 | ||||
Italy | -213 | -158 | -100 | –33 | -0.3 | -0.2 | -0.1 | 0.0 | -11.4 | -8.1 | -4.8 | -1.6 | ||||
Japan | 2,902 | 2,915 | 3,033 | 3,393 | 3.8 | 3.6 | 3.5 | 3.9 | 58.9 | 59.9 | 61.2 | 66.8 | ||||
Korea | 281 | 262 | 436 | 501 | 0.4 | 0.3 | 0.5 | 0.6 | 18.7 | 16.1 | 25.3 | 30.4 | ||||
Netherlands | 458 | 519 | 623 | 809 | 0.6 | 0.6 | 0.7 | 0.9 | 58.5 | 62.3 | 68.1 | 89.0 | ||||
Singapore | 754 | 867 | 770 | 896 | 1.0 | 1.1 | 0.9 | 1.0 | 236.7 | 253.7 | 206.3 | 240.8 | ||||
Spain | -1,004 | -1,176 | -1,098 | -1,024 | -1.3 | -1.5 | -1.3 | -1.2 | -81.5 | -89.6 | -77.3 | -73.5 | ||||
Sweden | -9 | 8 | 43 | 112 | 0.0 | 0.0 | 0.1 | 0.1 | -1.7 | 1.4 | 7.8 | 21.0 | ||||
Switzerland | 811 | 857 | 883 | 826 | 1.1 | 1.1 | 1.0 | 0.9 | 120.7 | 126.0 | 125.2 | 117.4 | ||||
United Kingdom | 9 | -268 | -368 | -713 | 0.0 | -0.3 | -0.4 | -0.8 | 0.3 | -10.0 | -12.8 | -25.2 | ||||
United States | -8,192 | -7,743 | -9,555 | -10,991 | -10.8 | -9.6 | -11.2 | -12.6 | -43.8 | -39.7 | -46.4 | -51.3 | ||||
Emerging Market and Developing Economies | ||||||||||||||||
Argentina | 48 | 17 | 65 | 118 | 0.1 | 0.0 | 0.1 | 0.1 | 8.6 | 2.7 | 12.6 | 26.2 | ||||
Brazil | -567 | -645 | -594 | -732 | -0.7 | -0.8 | -0.7 | -0.8 | -31.6 | -31.3 | -31.5 | -39.8 | ||||
China | 1,950 | 2,101 | 2,146 | 2,124 | 2.6 | 2.6 | 2.5 | 2.4 | 17.4 | 17.1 | 15.5 | 14.4 | ||||
India | -394 | -424 | -437 | -455 | -0.5 | -0.5 | -0.5 | -0.5 | -17.2 | -16.0 | -16.1 | -15.0 | ||||
Indonesia | -334 | -323 | -318 | -350 | -0.4 | -0.4 | -0.4 | -0.4 | -35.8 | -31.8 | -30.5 | -31.2 | ||||
Malaysia | 16 | -8 | -18 | -5 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2 | -2.4 | -4.9 | -1.5 | ||||
Mexico | -532 | -556 | -591 | -655 | -0.7 | -0.7 | -0.7 | -0.7 | -49.4 | -48.0 | -48.4 | -52.1 | ||||
Poland | -274 | -350 | -314 | -298 | -0.4 | -0.4 | -0.4 | -0.3 | -58.1 | -66.4 | -53.4 | -50.3 | ||||
Russia | 220 | 281 | 374 | 357 | 0.3 | 0.3 | 0.4 | 0.4 | 17.2 | 17.8 | 22.4 | 21.0 | ||||
Saudi Arabia | 597 | 624 | 632 | 683 | 0.8 | 0.8 | 0.7 | 0.8 | 92.6 | 90.6 | 80.3 | 86.1 | ||||
South Africa | 22 | 35 | 45 | 29 | 0.0 | 0.0 | 0.1 | 0.0 | 7.5 | 9.9 | 12.3 | 8.0 | ||||
Thailand | –33 | -36 | -11 | -10 | 0.0 | 0.0 | 0.0 | 0.0 | -7.9 | -8.0 | -2.2 | -1.8 | ||||
Turkey | -368 | -463 | -371 | -345 | -0.5 | -0.6 | -0.4 | -0.4 | -42.6 | -54.2 | -48.2 | -45.8 | ||||
Memorandum item: | ||||||||||||||||
Euro Area | -984 | -1,044 | -607 | -70 | -1.3 | -1.3 | -0.7 | -0.1 | -8.2 | -8.3 | -4.4 | -0.5 | ||||
Statistical Discrepancy | -1,733 | -912 | -2,020 | -1,979 | -2.3 | -1.1 | -2.4 | -2.3 | … | … | … | … | ||||
Overall Creditors | 14,085 | 15,817 | 16,432 | 18,316 | 18.6 | 19.6 | 19.2 | 20.9 | … | … | … | … | ||||
Of which: | 10,797 | 12,325 | 12,732 | 14,568 | 14.2 | 15.3 | 14.9 | 16.7 | … | … | … | … | ||||
Advanced | ||||||||||||||||
Economies | ||||||||||||||||
Overall Debtors | -15,818 | -16,729 | -18,453 | -20,295 | -20.9 | -20.8 | -21.6 | -23.2 | … | … | … | … | ||||
Of which: | -11,715 | -12,102 | -13,870 | -15,426 | -15.5 | -15.0 | -16.2 | -17.6 | … | … | … | … | ||||
Advanced | ||||||||||||||||
Economies |
Normative Assessment of External Positions in 2019
IMF staff external sector assessments for 2019 provide a benchmark for assessing external positions as they were before the onset of the COVID-19 crisis. The assessment of external positions requires a multilateral approach that matches positive and negative excess external imbalances. The IMF’s external assessment framework combines numerical inputs from the latest vintage of the EBA methodology with a series of external indicators and country-specific judgment (see Box 1.2 and Chapter 3). The EBA methodology produces multilaterally consistent estimates for current account and real exchange rate norms (or benchmarks), which depend on country fundamentals and desired policies.1 The IMF staff estimates current account and real effective exchange rate gaps by comparing actual current accounts (stripped of temporary components) and real effective exchange rates with their staff-assessed norms, using judgment and country-specific insights where appropriate. The IMF staff arrives at a holistic overall external sector assessment for the world’s 30 largest economies based on the estimated gaps as well as consideration of other external sector indicators, such as the net international investment position, capital flows, and foreign exchange reserves.
For most of the 30 economies, overall external position assessments for 2019 remained broadly similar to those for 2018. About one-third of economy assessments changed categories in 2019 (Tables 1.4 and 1.5). Economies with estimated excess current account surpluses (deficits) generally also had an undervalued (overvalued) real effective exchange rate, according to IMF staff estimates (Figures 1.3 and 1.4).2 The configuration of overall external positions compared with their estimated desirable levels was as follows.
Stronger than the level consistent with medium-term fundamentals and desirable policies: The 10 economies with such positions were the euro area, Germany, Malaysia, the Netherlands, Singapore, and Thailand, as well as Poland, Sweden, Switzerland, and Turkey, which entered this category in 2019, driven by increases in their current account balances.3
Weaker than the level consistent with medium-term fundamentals and desirable policies: The nine economies with such positions were Belgium, Canada, the United Kingdom, the United States, and a number of emerging market and developing economies (Argentina, South Africa), as well as commodity exporters (Brazil, Saudi Arabia) and France, which entered this category in 2019.4 • Broadly in line with the level consistent with medium-term fundamentals and desirable policies: The 11 economies with such positions were, as in the previous year, Australia, China, Hong Kong SAR, India, Italy, Japan, and Mexico, as well as Indonesia, Korea, Russia, and Spain, which entered this category in 2019.
IMF Staff-Assessed and External Balance Assessment Estimated Current Account and Real Effective Exchange Rate Gaps, 2019
Source: IMF staff assessments.Note: CA = current account; EBA = IMF External Balance Assessment model; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.1 Hong Kong SAR, Saudi Arabia, and Singapore do not have EBA estimates.2 EBA REER gap is defined as the average gap from REER-index, REER-level, and REER gap implied from staff CA gap using estimated elasticities (see details in Cubeddu and others 2019).IMF Staff-Assessed and External Balance Assessment Estimated Current Account and Real Effective Exchange Rate Gaps, 2019
Source: IMF staff assessments.Note: CA = current account; EBA = IMF External Balance Assessment model; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.1 Hong Kong SAR, Saudi Arabia, and Singapore do not have EBA estimates.2 EBA REER gap is defined as the average gap from REER-index, REER-level, and REER gap implied from staff CA gap using estimated elasticities (see details in Cubeddu and others 2019).IMF Staff-Assessed and External Balance Assessment Estimated Current Account and Real Effective Exchange Rate Gaps, 2019
Source: IMF staff assessments.Note: CA = current account; EBA = IMF External Balance Assessment model; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.1 Hong Kong SAR, Saudi Arabia, and Singapore do not have EBA estimates.2 EBA REER gap is defined as the average gap from REER-index, REER-level, and REER gap implied from staff CA gap using estimated elasticities (see details in Cubeddu and others 2019).IMF Staff-Assessed Current Account and Real Effective Exchange Rate Gaps, 2019
Source: IMF staff calculations.Note: REER gap is based on 2019 average REER. CA = current account; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.IMF Staff-Assessed Current Account and Real Effective Exchange Rate Gaps, 2019
Source: IMF staff calculations.Note: REER gap is based on 2019 average REER. CA = current account; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.IMF Staff-Assessed Current Account and Real Effective Exchange Rate Gaps, 2019
Source: IMF staff calculations.Note: REER gap is based on 2019 average REER. CA = current account; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.Selected Economies: Foreign Reserves, 2017–191
Sample includes External Sector Report economies excluding individual euro area economies. Euro area is reported as aggregate.
Total reserves from IFS, includes gold reserves valued at market prices.
This item is not necessarily equal to actual FXI, but it is used as an FXI proxy in External Balance Assessment model estimates. The estimated change in official reserves is equivalent to the change in reserve assets in the financial account series from the WEO (which excludes valuation effects, but includes interest income on official reserves) plus the change in off-balance-sheet holdings (short and long FX derivative positions, and other memorandum items) from IRFCL minus net credit and loans from the IMF.
The ARA metric reflects potential balance of payments FX liquidity needs in adverse circumstances and is used to assess the adequacy of FX reserves against potential FX liquidity drains (see IMF 2015). The ARA metric is estimated only for selected EMDEs and Korea, and includes adjustments for capital controls for China. Additional adjusted figures are available in the Individual Country Pages in Chapter 3.
The aggregate is calculated as the sum of External Sector Report economies only. The percent of GDP is calculated relative to total world GDP.
Selected Economies: Foreign Reserves, 2017–191
Gross Official Reservess2 | IMF Staff Estimated Change in Official Reserves3 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Billions of USD | Percent of World GDP | Percent of GDP | Gross Official Reserves in Percent of ARA metric (2019)4 | FXI Data Publication | |||||||||
2017 | 2018 | 2019 | 2017 | 2018 | 2019 | 2017 | 2018 | 2019 | |||||
Advanced Economies | |||||||||||||
Australia | 67 | 54 | 59 | 4.8 | 3.8 | 4.2 | -0.1 | 0.1 | 0.5 | . . . | Yes/Daily | ||
Canada | 87 | 84 | 85 | 5.3 | 4.9 | 4.9 | 0.0 | -0.1 | -0.1 | . . . | Yes/Monthly | ||
Euro Area | 803 | 823 | 914 | 6.3 | 6.0 | 6.9 | 0.0 | 0.2 | 0.0 | . . . | Yes/Quarterly | ||
Hong Kong SAR | 431 | 425 | 441 | 126.4 | 117.4 | 120.7 | 9.3 | 0.6 | -0.7 | . . . | Yes/Daily | ||
Japan | 1,264 | 1,270 | 1,322 | 26.0 | 25.7 | 26.0 | 0.3 | 0.5 | 0.3 | . . . | Yes/Monthly | ||
Korea | 389 | 403 | 409 | 23.9 | 23.4 | 24.8 | 0.7 | 0.1 | 0.0 | 110 | Yes/Quarterly | ||
Singapore | 285 | 293 | 285 | 83.4 | 78.4 | 79.0 | 14.7 | 5.0 | -1.7 | . . . | Yes/Semiannually | ||
Sweden | 62 | 61 | 56 | 11.5 | 10.9 | 10.5 | 0.0 | -0.1 | -1.2 | . . . | No | ||
Switzerland | 811 | 787 | 855 | 119.3 | 111.6 | 114.0 | 9.1 | 2.0 | 2.5 | . . . | Yes/Annually | ||
United Kingdom | 151 | 173 | 174 | 5.7 | 6.0 | 6.1 | 0.4 | 0.8 | -0.1 | . . . | Yes/Monthly | ||
United States | 451 | 450 | 517 | 2.3 | 2.2 | 2.4 | 0.0 | 0.1 | 0.0 | . . . | Yes/Quarterly | ||
Emerging Market and Developing Economies | |||||||||||||
Argentina | 55 | 66 | 45 | 8.6 | 12.7 | 10.0 | 2.3 | -3.3 | -8.4 | 45 | Yes/Daily | ||
Brazil | 374 | 375 | 357 | 18.1 | 19.9 | 19.4 | 0.3 | -2.2 | -0.6 | 154 | Yes/Daily | ||
China | 3,236 | 3,168 | 3,223 | 26.4 | 22.9 | 21.9 | 1.1 | 0.1 | 0.1 | 133 | No | ||
India | 413 | 399 | 492 | 15.6 | 14.7 | 16.2 | 2.6 | -1.3 | 2.3 | 163 | Yes/Monthly | ||
Indonesia | 130 | 121 | 129 | 12.8 | 11.6 | 11.5 | 1.7 | -1.4 | 0.7 | 119 | No | ||
Malaysia | 102 | 101 | 104 | 32.1 | 28.3 | 28.4 | 0.7 | -2.5 | 2.9 | 116 | No | ||
Mexico | 175 | 176 | 183 | 15.1 | 14.4 | 14.5 | -0.4 | 0.0 | 0.2 | 117 | Yes/Monthly | ||
Poland | 113 | 117 | 128 | 21.5 | 19.9 | 21.7 | -1.4 | 1.2 | 1.7 | 144 | No | ||
Russia | 433 | 469 | 555 | 27.5 | 28.1 | 32.6 | 1.7 | 2.0 | 3.9 | 310 | Yes/Daily | ||
Saudi Arabia | 509 | 509 | 500 | 74.0 | 64.8 | 63.0 | -5.8 | 0.1 | 0.5 | 375 | No | ||
South Africa | 51 | 52 | 55 | 14.5 | 14.0 | 15.7 | 0.4 | -0.1 | 0.4 | 76 | No | ||
Thailand | 203 | 206 | 224 | 44.4 | 40.6 | 41.3 | 8.1 | 0.8 | 2.4 | 221 | No | ||
Turkey | 108 | 93 | 106 | 12.6 | 12.1 | 14.0 | -1.1 | -1.5 | -1.3 | 85 | Yes/Daily | ||
Memorandum item: | |||||||||||||
Aggregate5 | 10,703 | 10,674 | 11,216 | 13.3 | 12.5 | 12.8 | 0.5 | 0.1 | 0.2 | . . . | . . . | ||
AEs | 4,801 | 4,821 | 5,117 | 6.0 | 5.6 | 5.8 | 0.2 | 0.2 | 0.0 | . . . | . . . | ||
EMDEs | 5,902 | 5,852 | 6,099 | 7.3 | 6.8 | 7.0 | 0.3 | -0.1 | 0.2 | . . . | . . . |
Sample includes External Sector Report economies excluding individual euro area economies. Euro area is reported as aggregate.
Total reserves from IFS, includes gold reserves valued at market prices.
This item is not necessarily equal to actual FXI, but it is used as an FXI proxy in External Balance Assessment model estimates. The estimated change in official reserves is equivalent to the change in reserve assets in the financial account series from the WEO (which excludes valuation effects, but includes interest income on official reserves) plus the change in off-balance-sheet holdings (short and long FX derivative positions, and other memorandum items) from IRFCL minus net credit and loans from the IMF.
The ARA metric reflects potential balance of payments FX liquidity needs in adverse circumstances and is used to assess the adequacy of FX reserves against potential FX liquidity drains (see IMF 2015). The ARA metric is estimated only for selected EMDEs and Korea, and includes adjustments for capital controls for China. Additional adjusted figures are available in the Individual Country Pages in Chapter 3.
The aggregate is calculated as the sum of External Sector Report economies only. The percent of GDP is calculated relative to total world GDP.
Selected Economies: Foreign Reserves, 2017–191
Gross Official Reservess2 | IMF Staff Estimated Change in Official Reserves3 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Billions of USD | Percent of World GDP | Percent of GDP | Gross Official Reserves in Percent of ARA metric (2019)4 | FXI Data Publication | |||||||||
2017 | 2018 | 2019 | 2017 | 2018 | 2019 | 2017 | 2018 | 2019 | |||||
Advanced Economies | |||||||||||||
Australia | 67 | 54 | 59 | 4.8 | 3.8 | 4.2 | -0.1 | 0.1 | 0.5 | . . . | Yes/Daily | ||
Canada | 87 | 84 | 85 | 5.3 | 4.9 | 4.9 | 0.0 | -0.1 | -0.1 | . . . | Yes/Monthly | ||
Euro Area | 803 | 823 | 914 | 6.3 | 6.0 | 6.9 | 0.0 | 0.2 | 0.0 | . . . | Yes/Quarterly | ||
Hong Kong SAR | 431 | 425 | 441 | 126.4 | 117.4 | 120.7 | 9.3 | 0.6 | -0.7 | . . . | Yes/Daily | ||
Japan | 1,264 | 1,270 | 1,322 | 26.0 | 25.7 | 26.0 | 0.3 | 0.5 | 0.3 | . . . | Yes/Monthly | ||
Korea | 389 | 403 | 409 | 23.9 | 23.4 | 24.8 | 0.7 | 0.1 | 0.0 | 110 | Yes/Quarterly | ||
Singapore | 285 | 293 | 285 | 83.4 | 78.4 | 79.0 | 14.7 | 5.0 | -1.7 | . . . | Yes/Semiannually | ||
Sweden | 62 | 61 | 56 | 11.5 | 10.9 | 10.5 | 0.0 | -0.1 | -1.2 | . . . | No | ||
Switzerland | 811 | 787 | 855 | 119.3 | 111.6 | 114.0 | 9.1 | 2.0 | 2.5 | . . . | Yes/Annually | ||
United Kingdom | 151 | 173 | 174 | 5.7 | 6.0 | 6.1 | 0.4 | 0.8 | -0.1 | . . . | Yes/Monthly | ||
United States | 451 | 450 | 517 | 2.3 | 2.2 | 2.4 | 0.0 | 0.1 | 0.0 | . . . | Yes/Quarterly | ||
Emerging Market and Developing Economies | |||||||||||||
Argentina | 55 | 66 | 45 | 8.6 | 12.7 | 10.0 | 2.3 | -3.3 | -8.4 | 45 | Yes/Daily | ||
Brazil | 374 | 375 | 357 | 18.1 | 19.9 | 19.4 | 0.3 | -2.2 | -0.6 | 154 | Yes/Daily | ||
China | 3,236 | 3,168 | 3,223 | 26.4 | 22.9 | 21.9 | 1.1 | 0.1 | 0.1 | 133 | No | ||
India | 413 | 399 | 492 | 15.6 | 14.7 | 16.2 | 2.6 | -1.3 | 2.3 | 163 | Yes/Monthly | ||
Indonesia | 130 | 121 | 129 | 12.8 | 11.6 | 11.5 | 1.7 | -1.4 | 0.7 | 119 | No | ||
Malaysia | 102 | 101 | 104 | 32.1 | 28.3 | 28.4 | 0.7 | -2.5 | 2.9 | 116 | No | ||
Mexico | 175 | 176 | 183 | 15.1 | 14.4 | 14.5 | -0.4 | 0.0 | 0.2 | 117 | Yes/Monthly | ||
Poland | 113 | 117 | 128 | 21.5 | 19.9 | 21.7 | -1.4 | 1.2 | 1.7 | 144 | No | ||
Russia | 433 | 469 | 555 | 27.5 | 28.1 | 32.6 | 1.7 | 2.0 | 3.9 | 310 | Yes/Daily | ||
Saudi Arabia | 509 | 509 | 500 | 74.0 | 64.8 | 63.0 | -5.8 | 0.1 | 0.5 | 375 | No | ||
South Africa | 51 | 52 | 55 | 14.5 | 14.0 | 15.7 | 0.4 | -0.1 | 0.4 | 76 | No | ||
Thailand | 203 | 206 | 224 | 44.4 | 40.6 | 41.3 | 8.1 | 0.8 | 2.4 | 221 | No | ||
Turkey | 108 | 93 | 106 | 12.6 | 12.1 | 14.0 | -1.1 | -1.5 | -1.3 | 85 | Yes/Daily | ||
Memorandum item: | |||||||||||||
Aggregate5 | 10,703 | 10,674 | 11,216 | 13.3 | 12.5 | 12.8 | 0.5 | 0.1 | 0.2 | . . . | . . . | ||
AEs | 4,801 | 4,821 | 5,117 | 6.0 | 5.6 | 5.8 | 0.2 | 0.2 | 0.0 | . . . | . . . | ||
EMDEs | 5,902 | 5,852 | 6,099 | 7.3 | 6.8 | 7.0 | 0.3 | -0.1 | 0.2 | . . . | . . . |
Sample includes External Sector Report economies excluding individual euro area economies. Euro area is reported as aggregate.
Total reserves from IFS, includes gold reserves valued at market prices.
This item is not necessarily equal to actual FXI, but it is used as an FXI proxy in External Balance Assessment model estimates. The estimated change in official reserves is equivalent to the change in reserve assets in the financial account series from the WEO (which excludes valuation effects, but includes interest income on official reserves) plus the change in off-balance-sheet holdings (short and long FX derivative positions, and other memorandum items) from IRFCL minus net credit and loans from the IMF.
The ARA metric reflects potential balance of payments FX liquidity needs in adverse circumstances and is used to assess the adequacy of FX reserves against potential FX liquidity drains (see IMF 2015). The ARA metric is estimated only for selected EMDEs and Korea, and includes adjustments for capital controls for China. Additional adjusted figures are available in the Individual Country Pages in Chapter 3.
The aggregate is calculated as the sum of External Sector Report economies only. The percent of GDP is calculated relative to total world GDP.
External Sector Report Economies: Summary of External Assessment Indicators, 2019
The NIIP estimates come from the WEO and the Bureau of Economic Analysis.
The current account balance that would stabilize the ratio of NFA to GDP at the benchmark NFA/GDP level.
The standard error of the 2019 estimated current account norms.
The staff-assessed euro area CA gap is calculated as the GDP-weighted averages of IMF staff-assessed CA gaps for the 11 largest euro area economies.
External Sector Report Economies: Summary of External Assessment Indicators, 2019
Current Account (Percent of GDP) | Staff CA Gap (Percent of GDP) | Staff REER Gap (Percent | International Investment Position (Percent of GDP)1 | CA NFA Stabilizing (Percent of GDP)2 | SE of CA Norm (Percent)3 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Economy | Overall Assessment | Actual | Cycl. Adj. | Midpoint | Range | Midpoint | Range | Net | Liabilities | Assets | ||
Argentina | Weaker | -0.8 | -1.7 | -2.0 | +/-1 | -1.5 | +/-5 | 26 | 63 | 89 | 0.6 | 0.8 |
Australia | Broadly in line | 0.6 | 0.3 | 0.8 | +/-0.5 | -4.0 | +/-2.5 | -46 | 197 | 151 | -2.3 | 1.0 |
Belgium | Weaker | -1.2 | -1.1 | -3.5 | +/-1 | 8.5 | +/-2.5 | 38 | 387 | 425 | 1.3 | 0.5 |
Brazil | Moderately weaker | -2.7 | -3.7 | -1.2 | +/-0.5 | 3.5 | +/-7.5 | -40 | 88 | 49 | -1.4 | 0.9 |
Canada | Moderately weaker | -2.0 | -1.9 | -1.8 | +/-1.5 | 7.1 | +/-5.6 | 44 | 209 | 253 | 1.7 | 0.9 |
China | Broadly in line | 1.0 | 0.8 | 1.0 | +/-1.5 | -2.0 | +/-10 | 14 | 38 | 52 | 1.1 | 1.5 |
Euro Area4 | Moderately stronger | 2.7 | 2.7 | 1.2 | +/-0.8 | -2.8 | +/-2.9 | -1 | 244 | 243 | -0.3 | 0.8 |
France | Moderately weaker | -0.7 | -0.5 | -1.1 | +/-0.5 | 4.1 | +/-1.9 | -19 | 318 | 299 | -0.7 | 0.5 |
Germany | Substantially stronger | 7.1 | 7.3 | 4.3 | +/-1 | -11.0 | +/-5 | 71 | 203 | 273 | 2.1 | 0.8 |
Hong Kong SAR | Broadly in line | 6.2 | . . . | 0.8 | +/-1.5 | -2.5 | +/-5 | 427 | 1,109 | 1,537 | . . . | . . . |
India | Broadly in line | -0.9 | -1.4 | 1.0 | +/-1 | -5.6 | +/-5.5 | -15 | 40 | 25 | -2.4 | 1.3 |
Indonesia | Broadly in line | -2.7 | -2.7 | -1.0 | +/-1.5 | 3.9 | +/-5.1 | -31 | 64 | 33 | -2.2 | 1.3 |
Italy | Broadly in line | 3.0 | 2.7 | 0.0 | +/-1 | 4.0 | +/-4 | -2 | 165 | 163 | -0.3 | 0.8 |
Japan | Broadly in line | 3.6 | 3.5 | 0.0 | +/-1.2 | 0.0 | +/-9 | 67 | 132 | 198 | 3.6 | 1.2 |
Korea | Broadly in line | 3.6 | 3.3 | 0.0 | +/-1 | 0.0 | +/-3 | 30 | 73 | 103 | 1.2 | 0.8 |
Malaysia | Stronger | 3.4 | 3.5 | 3.3 | +/-1 | -7.2 | +/–2 | -1 | 113 | 111 | -0.4 | 0.7 |
Mexico | Broadly in line | -0.3 | -0.7 | 0.9 | +/-1.1 | -7.0 | +/-8 | -52 | 100 | 48 | -1.9 | 1.1 |
Netherlands | Substantially stronger | 10.2 | 10.5 | 4.9 | +/–2 | -7.0 | +/-2.9 | 89 | 1,037 | 1,126 | 2.5 | 0.9 |
Poland | Stronger | 0.5 | 0.6 | 2.7 | +/-1 | -6.0 | +/–2 | -50 | 99 | 49 | -2.8 | 0.6 |
Russia | Broadly in line | 3.8 | 3.8 | 0.1 | +/-1 | -0.4 | +/-5 | 21 | 68 | 89 | 0.9 | 1.6 |
Saudi Arabia | Weaker | 5.9 | . . . | -3.0 | +/-1.2 | 13.0 | +/-3 | 86 | 60 | 146 | . . . | . . . |
Singapore | Substantially stronger | 17.0 | . . . | 4.0 | +/-3 | -8.0 | +/-6 | 241 | 894 | 1,135 | . . . | . . . |
South Africa | Moderately weaker | -3.0 | -3.2 | -1.5 | +/-1.1 | 5.7 | +/-4 | 8 | 129 | 137 | 0.4 | 1.2 |
Spain | Broadly in line | 2.0 | 2.2 | 0.2 | +/-1 | -0.9 | +/-4 | -73 | 250 | 176 | -3.0 | 0.8 |
Sweden | Stronger | 4.2 | 4.5 | 3.2 | +/-1.5 | -10.0 | +/-5 | 21 | 263 | 284 | 0.3 | 1.1 |
Switzerland | Moderately stronger | 11.5 | 11.5 | 1.8 | +/–2 | -3.5 | +/-3.9 | 117 | 644 | 761 | 8.7 | 1.3 |
Thailand | Substantially stronger | 7.0 | 6.6 | 6.1 | +/-1.5 | -9.5 | +/-2.5 | -2 | 99 | 98 | -0.2 | 1.6 |
Turkey | Moderately stronger | 1.2 | 0.8 | 1.6 | +/-1.8 | -15.0 | +/-8 | -46 | 79 | 34 | -3.1 | 1.8 |
United Kingdom | Weaker | -3.8 | -3.8 | -2.9 | +/–2 | 7.5 | +/-7.5 | -25 | 534 | 509 | -0.5 | 0.7 |
United States | Moderately weaker | -2.3 | -2.0 | -1.3 | +/-0.5 | 11.0 | +/-3 | -51 | 188 | 137 | -0.8 | 1.0 |
The NIIP estimates come from the WEO and the Bureau of Economic Analysis.
The current account balance that would stabilize the ratio of NFA to GDP at the benchmark NFA/GDP level.
The standard error of the 2019 estimated current account norms.
The staff-assessed euro area CA gap is calculated as the GDP-weighted averages of IMF staff-assessed CA gaps for the 11 largest euro area economies.
External Sector Report Economies: Summary of External Assessment Indicators, 2019
Current Account (Percent of GDP) | Staff CA Gap (Percent of GDP) | Staff REER Gap (Percent | International Investment Position (Percent of GDP)1 | CA NFA Stabilizing (Percent of GDP)2 | SE of CA Norm (Percent)3 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Economy | Overall Assessment | Actual | Cycl. Adj. | Midpoint | Range | Midpoint | Range | Net | Liabilities | Assets | ||
Argentina | Weaker | -0.8 | -1.7 | -2.0 | +/-1 | -1.5 | +/-5 | 26 | 63 | 89 | 0.6 | 0.8 |
Australia | Broadly in line | 0.6 | 0.3 | 0.8 | +/-0.5 | -4.0 | +/-2.5 | -46 | 197 | 151 | -2.3 | 1.0 |
Belgium | Weaker | -1.2 | -1.1 | -3.5 | +/-1 | 8.5 | +/-2.5 | 38 | 387 | 425 | 1.3 | 0.5 |
Brazil | Moderately weaker | -2.7 | -3.7 | -1.2 | +/-0.5 | 3.5 | +/-7.5 | -40 | 88 | 49 | -1.4 | 0.9 |
Canada | Moderately weaker | -2.0 | -1.9 | -1.8 | +/-1.5 | 7.1 | +/-5.6 | 44 | 209 | 253 | 1.7 | 0.9 |
China | Broadly in line | 1.0 | 0.8 | 1.0 | +/-1.5 | -2.0 | +/-10 | 14 | 38 | 52 | 1.1 | 1.5 |
Euro Area4 | Moderately stronger | 2.7 | 2.7 | 1.2 | +/-0.8 | -2.8 | +/-2.9 | -1 | 244 | 243 | -0.3 | 0.8 |
France | Moderately weaker | -0.7 | -0.5 | -1.1 | +/-0.5 | 4.1 | +/-1.9 | -19 | 318 | 299 | -0.7 | 0.5 |
Germany | Substantially stronger | 7.1 | 7.3 | 4.3 | +/-1 | -11.0 | +/-5 | 71 | 203 | 273 | 2.1 | 0.8 |
Hong Kong SAR | Broadly in line | 6.2 | . . . | 0.8 | +/-1.5 | -2.5 | +/-5 | 427 | 1,109 | 1,537 | . . . | . . . |
India | Broadly in line | -0.9 | -1.4 | 1.0 | +/-1 | -5.6 | +/-5.5 | -15 | 40 | 25 | -2.4 | 1.3 |
Indonesia | Broadly in line | -2.7 | -2.7 | -1.0 | +/-1.5 | 3.9 | +/-5.1 | -31 | 64 | 33 | -2.2 | 1.3 |
Italy | Broadly in line | 3.0 | 2.7 | 0.0 | +/-1 | 4.0 | +/-4 | -2 | 165 | 163 | -0.3 | 0.8 |
Japan | Broadly in line | 3.6 | 3.5 | 0.0 | +/-1.2 | 0.0 | +/-9 | 67 | 132 | 198 | 3.6 | 1.2 |
Korea | Broadly in line | 3.6 | 3.3 | 0.0 | +/-1 | 0.0 | +/-3 | 30 | 73 | 103 | 1.2 | 0.8 |
Malaysia | Stronger | 3.4 | 3.5 | 3.3 | +/-1 | -7.2 | +/–2 | -1 | 113 | 111 | -0.4 | 0.7 |
Mexico | Broadly in line | -0.3 | -0.7 | 0.9 | +/-1.1 | -7.0 | +/-8 | -52 | 100 | 48 | -1.9 | 1.1 |
Netherlands | Substantially stronger | 10.2 | 10.5 | 4.9 | +/–2 | -7.0 | +/-2.9 | 89 | 1,037 | 1,126 | 2.5 | 0.9 |
Poland | Stronger | 0.5 | 0.6 | 2.7 | +/-1 | -6.0 | +/–2 | -50 | 99 | 49 | -2.8 | 0.6 |
Russia | Broadly in line | 3.8 | 3.8 | 0.1 | +/-1 | -0.4 | +/-5 | 21 | 68 | 89 | 0.9 | 1.6 |
Saudi Arabia | Weaker | 5.9 | . . . | -3.0 | +/-1.2 | 13.0 | +/-3 | 86 | 60 | 146 | . . . | . . . |
Singapore | Substantially stronger | 17.0 | . . . | 4.0 | +/-3 | -8.0 | +/-6 | 241 | 894 | 1,135 | . . . | . . . |
South Africa | Moderately weaker | -3.0 | -3.2 | -1.5 | +/-1.1 | 5.7 | +/-4 | 8 | 129 | 137 | 0.4 | 1.2 |
Spain | Broadly in line | 2.0 | 2.2 | 0.2 | +/-1 | -0.9 | +/-4 | -73 | 250 | 176 | -3.0 | 0.8 |
Sweden | Stronger | 4.2 | 4.5 | 3.2 | +/-1.5 | -10.0 | +/-5 | 21 | 263 | 284 | 0.3 | 1.1 |
Switzerland | Moderately stronger | 11.5 | 11.5 | 1.8 | +/–2 | -3.5 | +/-3.9 | 117 | 644 | 761 | 8.7 | 1.3 |
Thailand | Substantially stronger | 7.0 | 6.6 | 6.1 | +/-1.5 | -9.5 | +/-2.5 | -2 | 99 | 98 | -0.2 | 1.6 |
Turkey | Moderately stronger | 1.2 | 0.8 | 1.6 | +/-1.8 | -15.0 | +/-8 | -46 | 79 | 34 | -3.1 | 1.8 |
United Kingdom | Weaker | -3.8 | -3.8 | -2.9 | +/–2 | 7.5 | +/-7.5 | -25 | 534 | 509 | -0.5 | 0.7 |
United States | Moderately weaker | -2.3 | -2.0 | -1.3 | +/-0.5 | 11.0 | +/-3 | -51 | 188 | 137 | -0.8 | 1.0 |
The NIIP estimates come from the WEO and the Bureau of Economic Analysis.
The current account balance that would stabilize the ratio of NFA to GDP at the benchmark NFA/GDP level.
The standard error of the 2019 estimated current account norms.
The staff-assessed euro area CA gap is calculated as the GDP-weighted averages of IMF staff-assessed CA gaps for the 11 largest euro area economies.
External Sector Report Economies: Summary of IMF Staff-Assessed Current Account Gaps and Staff Adjustments, 2019
(Percent of GDP)
Figures may not add up due to rounding effects.
Refers to the midpoint of the staff-assessed CA gap.
Total staff adjustments include rounding in some cases. The breakdown between the norm and other factors (which affect the underlying CA) is tentative.
The EBA euro area current account norm is calculated as the GDP-weighted average of norms for the 11 largest euro area economies, adjusted for reporting discrepancies in infra-area transactions (which were equivalent to 0.43 percent of GDP in 2019). The staff-assessed CA gap is calculated as the GDP-weighted average of staff-assessed gaps for the 11 largest euro area economies.
GDP-weighted average sum of staff-assessed CA gaps in percent of world GDP.
External Sector Report Economies: Summary of IMF Staff-Assessed Current Account Gaps and Staff Adjustments, 2019
(Percent of GDP)
Economy | Assessment 2019 | Actual CA Balance [A] | Cycl. Adj. CA Balance [B] | EBACA Norm [C] | EBACA Gap1 [D=B-C] | Staff-Assessed CA Gap2 [E] | Staff Adjustments3 | |||
---|---|---|---|---|---|---|---|---|---|---|
Total [F=G-H] | CA [G] | Norm [H] | Comments | |||||||
Argentina | Weaker | -0.8 | -1.7 | -1.2 | -0.5 | -2.0 | -1.5 | 0.0 | 1.5 | NllP/financing risks considerations |
Australia | Broadly in line | 0.6 | 0.3 | -0.1 | 0.5 | 0.8 | 0.3 | -0.7 | -1.0 | Terms of trade (CA); large investment needs (Norm) |
Belgium | Weaker | -1.2 | -1.1 | 2.3 | -3.5 | -3.5 | 0.0 | 0.0 | 0.0 | |
Brazil | Moderately weaker | -2.7 | -3.7 | -2.5 | -1.2 | -1.2 | 0.0 | 0.0 | 0.0 | |
Canada | Moderately weaker | -2.0 | -1.9 | 2.2 | -4.1 | -1.8 | 2.3 | 2.0 | -0.3 | Measurement biases and terms of trade (CA); demographics (Norm) |
China | Broadly in line | 1.0 | 0.8 | -0.4 | 1.2 | 1.0 | -0.2 | -0.2 | 0.0 | Impact of trade tensions |
Euro Area4 | Moderately stronger | 2.7 | 2.7 | 1.4 | 1.3 | 1.2 | -0.1 | 0.1 | 0.3 | Country-specific adjustments |
France | Moderately weaker | -0.7 | -0.5 | 0.6 | -1.1 | -1.1 | 0.0 | 0.0 | 0.0 | |
Germany | Substantially stronger | 7.1 | 7.3 | 2.5 | 4.7 | 4.3 | -0.4 | 0.0 | 0.4 | Demographics (uncertainty related to large and sudden immigration) |
India | Broadly in line | -0.9 | -1.4 | -3.0 | 1.6 | 1.0 | -0.6 | 0.0 | 0.6 | NllP/financing risks considerations |
Indonesia | Broadly in line | -2.7 | -2.7 | -0.8 | -1.9 | -1.0 | 0.9 | 0.0 | -0.9 | Demographics (high mortality risk) |
Italy | Broadly in line | 3.0 | 2.7 | 2.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
Japan | Broadly in line | 3.6 | 3.5 | 3.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
Korea | Broadly in line | 3.6 | 3.3 | 3.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
Malaysia | Stronger | 3.4 | 3.5 | -0.2 | 3.7 | 3.3 | -0.4 | -0.4 | 0.0 | Postponement of large infrastructure projects with high import content |
Mexico | Broadly in line | -0.3 | -0.7 | -2.2 | 1.5 | 0.9 | 0.6 | 0.6 | 0.0 | Effects of trade diversion |
Netherlands | Substantially stronger | 10.2 | 10.5 | 3.3 | 7.2 | 4.9 | -2.3 | -2.3 | 0.0 | Measurement biases |
Poland | Stronger | 0.5 | 0.6 | -2.1 | 2.7 | 2.7 | 0.0 | 0.0 | 0.0 | |
Russia | Broadly in line | 3.8 | 3.8 | 3.7 | 0.1 | 0.1 | 0.0 | 0.0 | 0.0 | |
South Africa | Moderately weaker | -3.0 | -3.2 | 0.9 | -4.0 | -1.5 | 2.5 | 1.5 | -1.0 | SACU transfers and measurement biases (CA); demographics (high mortality risk, Norm) |
Spain | Broadly in line | 2.0 | 2.2 | 1.1 | 1.1 | 0.2 | -0.9 | 0.0 | 0.9 | NllP/financing risks considerations |
Sweden | Stronger | 4.2 | 4.5 | 1.2 | 3.2 | 3.2 | 0.0 | 0.0 | 0.0 | |
Switzerland | Moderately stronger | 11.5 | 11.5 | 6.3 | 5.3 | 1.8 | -3.5 | -3.5 | 0.0 | Measurement biases |
Thailand | Substantially stronger | 7.0 | 6.6 | 0.4 | 6.1 | 6.1 | 0.0 | 0.0 | 0.0 | |
Turkey | Moderately stronger | 1.2 | 0.8 | -1.7 | 2.5 | 1.6 | 0.9 | 0.9 | 0.0 | Temporarily large receipts from travel services |
United Kingdom | Weaker | -3.8 | -3.8 | 0.4 | -4.2 | -2.9 | 1.3 | 1.3 | 0.0 | Measurement biases |
United States | Moderately weaker | -2.3 | -2.0 | -0.7 | -1.3 | -1.3 | 0.0 | 0.0 | 0.0 | |
Hong Kong SAR | Broadly in line | 6.2 | ... | ... | ... | 0.8 | ... | ... | ... | ... |
Singapore | Substantially stronger | 17.0 | ... | ... | ... | 4.0 | ... | ... | ... | ... |
Saudi Arabia | Weaker | 5.9 | ... | ... | ... | -3.0 | ... | ... | ... | ... |
Absolute sum of excess surpluses and deficits5 | 1.2 | |||||||||
Discrepancy5 | ... | ... | ... | ... | ... | 0.02 | ... | ... | ... | ... |
Figures may not add up due to rounding effects.
Refers to the midpoint of the staff-assessed CA gap.
Total staff adjustments include rounding in some cases. The breakdown between the norm and other factors (which affect the underlying CA) is tentative.
The EBA euro area current account norm is calculated as the GDP-weighted average of norms for the 11 largest euro area economies, adjusted for reporting discrepancies in infra-area transactions (which were equivalent to 0.43 percent of GDP in 2019). The staff-assessed CA gap is calculated as the GDP-weighted average of staff-assessed gaps for the 11 largest euro area economies.
GDP-weighted average sum of staff-assessed CA gaps in percent of world GDP.
External Sector Report Economies: Summary of IMF Staff-Assessed Current Account Gaps and Staff Adjustments, 2019
(Percent of GDP)
Economy | Assessment 2019 | Actual CA Balance [A] | Cycl. Adj. CA Balance [B] | EBACA Norm [C] | EBACA Gap1 [D=B-C] | Staff-Assessed CA Gap2 [E] | Staff Adjustments3 | |||
---|---|---|---|---|---|---|---|---|---|---|
Total [F=G-H] | CA [G] | Norm [H] | Comments | |||||||
Argentina | Weaker | -0.8 | -1.7 | -1.2 | -0.5 | -2.0 | -1.5 | 0.0 | 1.5 | NllP/financing risks considerations |
Australia | Broadly in line | 0.6 | 0.3 | -0.1 | 0.5 | 0.8 | 0.3 | -0.7 | -1.0 | Terms of trade (CA); large investment needs (Norm) |
Belgium | Weaker | -1.2 | -1.1 | 2.3 | -3.5 | -3.5 | 0.0 | 0.0 | 0.0 | |
Brazil | Moderately weaker | -2.7 | -3.7 | -2.5 | -1.2 | -1.2 | 0.0 | 0.0 | 0.0 | |
Canada | Moderately weaker | -2.0 | -1.9 | 2.2 | -4.1 | -1.8 | 2.3 | 2.0 | -0.3 | Measurement biases and terms of trade (CA); demographics (Norm) |
China | Broadly in line | 1.0 | 0.8 | -0.4 | 1.2 | 1.0 | -0.2 | -0.2 | 0.0 | Impact of trade tensions |
Euro Area4 | Moderately stronger | 2.7 | 2.7 | 1.4 | 1.3 | 1.2 | -0.1 | 0.1 | 0.3 | Country-specific adjustments |
France | Moderately weaker | -0.7 | -0.5 | 0.6 | -1.1 | -1.1 | 0.0 | 0.0 | 0.0 | |
Germany | Substantially stronger | 7.1 | 7.3 | 2.5 | 4.7 | 4.3 | -0.4 | 0.0 | 0.4 | Demographics (uncertainty related to large and sudden immigration) |
India | Broadly in line | -0.9 | -1.4 | -3.0 | 1.6 | 1.0 | -0.6 | 0.0 | 0.6 | NllP/financing risks considerations |
Indonesia | Broadly in line | -2.7 | -2.7 | -0.8 | -1.9 | -1.0 | 0.9 | 0.0 | -0.9 | Demographics (high mortality risk) |
Italy | Broadly in line | 3.0 | 2.7 | 2.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
Japan | Broadly in line | 3.6 | 3.5 | 3.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
Korea | Broadly in line | 3.6 | 3.3 | 3.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
Malaysia | Stronger | 3.4 | 3.5 | -0.2 | 3.7 | 3.3 | -0.4 | -0.4 | 0.0 | Postponement of large infrastructure projects with high import content |
Mexico | Broadly in line | -0.3 | -0.7 | -2.2 | 1.5 | 0.9 | 0.6 | 0.6 | 0.0 | Effects of trade diversion |
Netherlands | Substantially stronger | 10.2 | 10.5 | 3.3 | 7.2 | 4.9 | -2.3 | -2.3 | 0.0 | Measurement biases |
Poland | Stronger | 0.5 | 0.6 | -2.1 | 2.7 | 2.7 | 0.0 | 0.0 | 0.0 | |
Russia | Broadly in line | 3.8 | 3.8 | 3.7 | 0.1 | 0.1 | 0.0 | 0.0 | 0.0 | |
South Africa | Moderately weaker | -3.0 | -3.2 | 0.9 | -4.0 | -1.5 | 2.5 | 1.5 | -1.0 | SACU transfers and measurement biases (CA); demographics (high mortality risk, Norm) |
Spain | Broadly in line | 2.0 | 2.2 | 1.1 | 1.1 | 0.2 | -0.9 | 0.0 | 0.9 | NllP/financing risks considerations |
Sweden | Stronger | 4.2 | 4.5 | 1.2 | 3.2 | 3.2 | 0.0 | 0.0 | 0.0 | |
Switzerland | Moderately stronger | 11.5 | 11.5 | 6.3 | 5.3 | 1.8 | -3.5 | -3.5 | 0.0 | Measurement biases |
Thailand | Substantially stronger | 7.0 | 6.6 | 0.4 | 6.1 | 6.1 | 0.0 | 0.0 | 0.0 | |
Turkey | Moderately stronger | 1.2 | 0.8 | -1.7 | 2.5 | 1.6 | 0.9 | 0.9 | 0.0 | Temporarily large receipts from travel services |
United Kingdom | Weaker | -3.8 | -3.8 | 0.4 | -4.2 | -2.9 | 1.3 | 1.3 | 0.0 | Measurement biases |
United States | Moderately weaker | -2.3 | -2.0 | -0.7 | -1.3 | -1.3 | 0.0 | 0.0 | 0.0 | |
Hong Kong SAR | Broadly in line | 6.2 | ... | ... | ... | 0.8 | ... | ... | ... | ... |
Singapore | Substantially stronger | 17.0 | ... | ... | ... | 4.0 | ... | ... | ... | ... |
Saudi Arabia | Weaker | 5.9 | ... | ... | ... | -3.0 | ... | ... | ... | ... |
Absolute sum of excess surpluses and deficits5 | 1.2 | |||||||||
Discrepancy5 | ... | ... | ... | ... | ... | 0.02 | ... | ... | ... | ... |
Figures may not add up due to rounding effects.
Refers to the midpoint of the staff-assessed CA gap.
Total staff adjustments include rounding in some cases. The breakdown between the norm and other factors (which affect the underlying CA) is tentative.
The EBA euro area current account norm is calculated as the GDP-weighted average of norms for the 11 largest euro area economies, adjusted for reporting discrepancies in infra-area transactions (which were equivalent to 0.43 percent of GDP in 2019). The staff-assessed CA gap is calculated as the GDP-weighted average of staff-assessed gaps for the 11 largest euro area economies.
GDP-weighted average sum of staff-assessed CA gaps in percent of world GDP.
Global excess imbalances (the sum of absolute excess surpluses and deficits) represented about 1.2 percent of world GDP in 2019, about 40 percent of overall current account surpluses and deficits, only slightly less than in 2018. Addressing underlying structural distortions has been challenging, resulting in persistent excess global imbalances. IMF staff–assessed current account gaps moved down (smaller excess surpluses or larger deficits) for commodity exporters, such as Brazil, Russia, and Saudi Arabia, as well as for euro area economies, such as the Netherlands (Figure 1.5). These changes largely mirrored increased current account gaps for emerging market and developing economies, such as Argentina and Turkey, and, to a lesser extent, emerging market and developing economies in Asia. IMF staff–assessed real effective exchange rate gaps generally moved consistently with current account gaps (Figure 1.5, panel 2).
Evolution of IMF Staff-Assessed Current Account and Real Effective Exchange Rate Gaps, 2018–19
Source: IMF staff estimates.Note: Bubble sizes are proportional to US dollar GDP. A positive (negative) REER gap denotes overvaluation (undervaluation). CA = current account; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.Evolution of IMF Staff-Assessed Current Account and Real Effective Exchange Rate Gaps, 2018–19
Source: IMF staff estimates.Note: Bubble sizes are proportional to US dollar GDP. A positive (negative) REER gap denotes overvaluation (undervaluation). CA = current account; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.Evolution of IMF Staff-Assessed Current Account and Real Effective Exchange Rate Gaps, 2018–19
Source: IMF staff estimates.Note: Bubble sizes are proportional to US dollar GDP. A positive (negative) REER gap denotes overvaluation (undervaluation). CA = current account; REER = real effective exchange rate. Data labels use International Organization for Standardization (ISO) country codes.Overall, the combination of persistent excess global imbalances and stocks of assets and liabilities at historically high levels implied vulnerabilities and remaining policy challenges on the eve of the pandemic.
External Developments during the COVID-19 Crisis
The crisis constitutes an intense shock, with a sharp decline in global trade, lower commodity prices, tighter external financing conditions, and with implications for current account balances and currencies varying widely. With limited available balance of payments data for 2020, only a partial assessment of external sector developments is feasible, and significant uncertainty surrounds the outlook. In addition, changes in macroeconomic fundamentals compared with 2019 may affect not only observed current account balances and real effective exchange rates but also their equilibrium values. For instance, worse commodity terms of trade may come with a depreciated equilibrium exchange rate. Overall, the path of excess imbalances in 2020 cannot be inferred from recent developments and more data are needed for a holistic assessment.
A Sharp Contraction in Trade
The global volume of goods trade in the first five months of 2020 was about 20 percent lower than in 2019—a more abrupt contraction than in the first five months of the global financial crisis. China’s recent trade growth rebound is an exception that reflects the earlier end of lockdown policies (Figure 1.6). For 2020 as a whole, the June 2020 World Economic Outlook (WEO) Update forecast for goods and services trade volume is a contraction of about 12 percent. Falling output appears to be the main driver of the trade contraction. The historical relationship between trade and the components of GDP fully explains the expected global decline in trade of goods and services, given current forecasts for these GDP components in 2020 (Box 1.3). Part of the impact of lower economic activity on trade is expected to involve transmission through global value chains. By contrast, in the years following the global financial crisis, trade in goods and services was weaker than could be explained by the fall in economic activity alone, with the residual reflecting the role of additional factors, such as rising protectionism (see the October 2016 WEO). For services trade, the expected contraction in 2020 is more severe than could be expected based on the prospective fall in aggregate demand, suggesting a strong role for special factors, such as travel restrictions. Overall, the current and prospective weakness in trade appears to reflect primarily the effects of COVID-19 and associated mitigation measures as well as the effects of production disruptions and lower demand associated with lost jobs and income.
Global Trade
Sources: Shipping volumes from Cerdeiro and others (2020), with AIS data collected by MarineTraffic; CPB World Trade Monitor; national authorities; Haver Analytics; IMF, World Economic Outlook (WEO); and IMF staff estimates.Note: Trade growth based on growth in volume of imports calculated as the weighted average of country-specific import growth, where nominal import shares are the weights used. See Box 1.3 for derivation of trade growth explained by GDP adjusted for import intensity. For aggregate manufacturing purchasing managers’ index (panel 2), nominal manufacturing value-added at market exchange rates are the weights used.Global Trade
Sources: Shipping volumes from Cerdeiro and others (2020), with AIS data collected by MarineTraffic; CPB World Trade Monitor; national authorities; Haver Analytics; IMF, World Economic Outlook (WEO); and IMF staff estimates.Note: Trade growth based on growth in volume of imports calculated as the weighted average of country-specific import growth, where nominal import shares are the weights used. See Box 1.3 for derivation of trade growth explained by GDP adjusted for import intensity. For aggregate manufacturing purchasing managers’ index (panel 2), nominal manufacturing value-added at market exchange rates are the weights used.Global Trade
Sources: Shipping volumes from Cerdeiro and others (2020), with AIS data collected by MarineTraffic; CPB World Trade Monitor; national authorities; Haver Analytics; IMF, World Economic Outlook (WEO); and IMF staff estimates.Note: Trade growth based on growth in volume of imports calculated as the weighted average of country-specific import growth, where nominal import shares are the weights used. See Box 1.3 for derivation of trade growth explained by GDP adjusted for import intensity. For aggregate manufacturing purchasing managers’ index (panel 2), nominal manufacturing value-added at market exchange rates are the weights used.Tighter Financial Conditions
Financial market sentiment deteriorated sharply in mid- to late February and in March as concerns about the global spread of COVID-19 and its economic fallout grew. Equity markets sold off sharply, and expected equity price volatility, as measured by the Chicago Board Options Exchange Volatility Index, reached levels last seen during the peak of the global financial crisis. Amid the general rebalancing of portfolios toward cash and safe assets, corporate and emerging market and developing economy sovereign spreads widened significantly.
Since late March many risky asset prices have rebounded with an overall easing in global financial conditions, on the back of strong policy actions, as discussed in the June 2020 Global Financial Stability Report (GFSR) Update. The swift response of central banks, with policy rate cuts, liquidity support, and asset purchase programs—and swap lines by the US Federal Reserve extended to additional foreign central banks—has, by most measures, been stronger than during the global financial crisis. The expansion in fiscal policy has also, in many cases, been stronger. The policy response has contributed to an easing in global financial conditions since late March. Capital flows and currency movements generally reflected these swings in global risk sentiment.
Capital Flow Reversals
Emerging market and developing economies experienced sudden capital flow reversals in late February and March, followed by a stabilization in flows in most cases and modest inflows in selected economies (June 2020 GFSR Update). Available high-frequency data on portfolio flows indicate outflows that exceed those during the early stages of the global financial crisis in US dollar terms. The outflow is more comparable across the two crisis episodes when expressed in percent of initial stock positions and outflows have varied widely across economies. Following the significant policy easing by central banks, portfolio flows stabilized in April and May, with some emerging market economies able to fully regain access to sovereign debt markets.
Country-specific characteristics have played a role in determining the degree of capital outflow across economies (Box 1.4). Factors include dependence on commodity exports, the strength of reserve buffers, initial current account balances, and access to swap lines from the US Federal Reserve. While some emerging market and developing economies have adjusted inflow capital flow management measures, the use of outflow capital flow management measures has thus far been rare. Following the decline in equity prices since the beginning of the COVID-19 pandemic, however, a few countries have tightened screening and approval procedures for foreign direct investment. While this trend began before the pandemic, motivations broadened to protecting the health care sector and preventing the takeover of undervalued domestic companies.
Currency Movements
Exchange rates experienced large swings as global financial conditions tightened through late March and eased thereafter (Figure 1.7).5 As investor sentiment worsened, global reserve currencies appreciated, reflecting their safe haven role in times of financial stress, as was the case during the global financial crisis. Since late March these initial currency shifts have partly unwound. Emerging market and developing economy currencies generally saw sharp depreciations as investor sentiment worsened and exchange rates worked as shock absorbers, although with substantial variation across economies. The currencies of commodity exporters with flexible exchange rates fell especially sharply in value, reflecting the fall in oil prices (Figure 1.8). Emerging market and developing economies that entered the crisis with stronger economic and financial fundamentals—or stronger perceived institutional quality—have generally experienced smaller depreciations and stronger rebounds in the value of their currencies more recently (Figure 1.8; Box 1.5). In some cases, such as Egypt and Turkey, the significant decline of foreign exchange reserves points to strong underlying depreciation pressures. By contrast, when global investor sentiment worsened, the sharp initial currency depreciations in Colombia, Indonesia, Mexico, South Africa, and Russia occurred with a more limited change in foreign currency reserves and currency movements allowed by the authorities to more fully reflect market pressure (Figure 1.8).
Currency Movements: Nominal Effective Exchange Rate (Percent change)
Sources: IMF, Global Data Source; and IMF staff calculations.Note: Data labels use International Organization for Standardization (ISO) country codes.Currency Movements: Nominal Effective Exchange Rate (Percent change)
Sources: IMF, Global Data Source; and IMF staff calculations.Note: Data labels use International Organization for Standardization (ISO) country codes.Currency Movements: Nominal Effective Exchange Rate (Percent change)
Sources: IMF, Global Data Source; and IMF staff calculations.Note: Data labels use International Organization for Standardization (ISO) country codes.Currency Movements and Country Characteristics
Sources: IMF, Global Data Source; IMF, Information Notice System; IMF, International Financial Statistics; International Country Risk Guide; and IMF staff calculations.Note: EMDE = emerging market and developing economies; ICRG = International Country Risk Guide; NEER = nominal effective exchange rate; rhs = right scale.1 The figure is based on the International Country Risk Guide composite risk score for the year before the crisis based on three subcategories of risk: political, financial, and economic. The indicator is based in part on expert opinions. “High (low) ICRG score” denotes average NEER change for economies with a precrisis composite score above (below) the EMDE sample median, where a higher score indicates a more favorable risk rating.2 The change in foreign exchange reserves is based on the change in the stock of reserves, adjusted for valuation changes and reserve income flows, and operations with foreign exchange derivatives.Currency Movements and Country Characteristics
Sources: IMF, Global Data Source; IMF, Information Notice System; IMF, International Financial Statistics; International Country Risk Guide; and IMF staff calculations.Note: EMDE = emerging market and developing economies; ICRG = International Country Risk Guide; NEER = nominal effective exchange rate; rhs = right scale.1 The figure is based on the International Country Risk Guide composite risk score for the year before the crisis based on three subcategories of risk: political, financial, and economic. The indicator is based in part on expert opinions. “High (low) ICRG score” denotes average NEER change for economies with a precrisis composite score above (below) the EMDE sample median, where a higher score indicates a more favorable risk rating.2 The change in foreign exchange reserves is based on the change in the stock of reserves, adjusted for valuation changes and reserve income flows, and operations with foreign exchange derivatives.Currency Movements and Country Characteristics
Sources: IMF, Global Data Source; IMF, Information Notice System; IMF, International Financial Statistics; International Country Risk Guide; and IMF staff calculations.Note: EMDE = emerging market and developing economies; ICRG = International Country Risk Guide; NEER = nominal effective exchange rate; rhs = right scale.1 The figure is based on the International Country Risk Guide composite risk score for the year before the crisis based on three subcategories of risk: political, financial, and economic. The indicator is based in part on expert opinions. “High (low) ICRG score” denotes average NEER change for economies with a precrisis composite score above (below) the EMDE sample median, where a higher score indicates a more favorable risk rating.2 The change in foreign exchange reserves is based on the change in the stock of reserves, adjusted for valuation changes and reserve income flows, and operations with foreign exchange derivatives.Outlook for Current Account Balances
The outlook for current account balances remains highly uncertain, given the limited balance of payments data currently available for 2020, but recent data and the latest IMF staff forecasts point to a modest narrowing in current account surpluses and deficits on average, although with high uncertainty and substantial cross-country variation. Central channels affecting the evolution of current account balances in 2020 include the aforementioned contraction in economic activity and tightening in global financial conditions as well as lower commodity prices, the contraction in tourism, and the decline in remittances. This section offers a perspective on the latter three factors and reports the latest IMF staff forecasts for 2020–21.
Impact on Commodity Trade Balances
The price of crude oil has fluctuated in recent months and is expected to be 41 percent lower in 2020 than in 2019. The prices of metals, food, and raw materials are also expected to decline, but by significantly less than the price of oil. The decline in the volume of oil imports in economies affected by the pandemic has also been substantial, with global oil demand expected to be about 8 percent lower in 2020 than in 2019. The overall estimated direct impact on oil trade balances ranges widely across economies—from –7 percent to 3 percent of GDP—reflecting differences in dependence on oil exports and imports (Figure 1.9). Estimated trade balance losses are concentrated among economies with significant net oil exports, including Norway, Russia, and Saudi Arabia, where they are expected to exceed 3 percent of GDP. Positive effects on trade balances are spread more evenly across net oil importers, although they are expected to exceed 2 percent of GDP for Thailand and Turkey.
Evolution of Commodity Prices and Oil Trade Balances
Sources: IMF, Global Data Source; IMF, Information Notice System; IMF, World Economic Outlook (WEO); International Country Risk Guide; and IMF staff calculations.Note: The figure reports the impact on the 2020 oil trade balance based on the latest IMF staff forecast compared with the October 2019 WEO forecast for 2020. Data labels use International Organization for Standardization (ISO) country codes.Evolution of Commodity Prices and Oil Trade Balances
Sources: IMF, Global Data Source; IMF, Information Notice System; IMF, World Economic Outlook (WEO); International Country Risk Guide; and IMF staff calculations.Note: The figure reports the impact on the 2020 oil trade balance based on the latest IMF staff forecast compared with the October 2019 WEO forecast for 2020. Data labels use International Organization for Standardization (ISO) country codes.Evolution of Commodity Prices and Oil Trade Balances
Sources: IMF, Global Data Source; IMF, Information Notice System; IMF, World Economic Outlook (WEO); International Country Risk Guide; and IMF staff calculations.Note: The figure reports the impact on the 2020 oil trade balance based on the latest IMF staff forecast compared with the October 2019 WEO forecast for 2020. Data labels use International Organization for Standardization (ISO) country codes.