Mediocre Cyclical United States Economic Growth with GDP Three Trillion Dollars Below Trend in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Probable Global Recession in the Lockdown of Economic Activity in the COVID-19 Event with United States GDP Contracting Sharply at 4.8 Percent SA Annual Equivalent Rate in First Quarter 2020, Contraction of Real Private Fixed Investment, United States Terms of International Trade, IMF View of World Economy and Finance, Probable Global Recession, World Cyclical Slow Growth, and Government Intervention in Globalization
Carlos M. Pelaez
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
I Mediocre Cyclical United States Economic Growth with GDP Three Trillion Dollars Below Trend in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide
IA Mediocre Cyclical United States Economic Growth
IA1 Stagnating Real Private Fixed Investment
IID United States Terms of International Trade
II IMF View of World Economy and Finance
III World Financial Turbulence
IV Global Inflation
V World Economic Slowdown
VA United States
VB Japan
VC China
VD Euro Area
VE Germany
VF France
VG Italy
VH United Kingdom
VI Valuation of Risk Financial Assets
VII Economic Indicators
VIII Interest Rates
IX Conclusion
References
Appendixes
Appendix I The Great Inflation
IIIB Appendix on Safe Haven Currencies
IIIC Appendix on Fiscal Compact
IIID Appendix on European Central Bank Large Scale Lender of Last Resort
IIIG Appendix on Deficit Financing of Growth and the Debt Crisis
Foreword A. IMF View of World Economy and Finance. Table I-1 is constructed with the database of the IMF (https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx) to show GDP in dollars in 2018 and the growth rate of real GDP of the world and selected regional countries from 2018 to 2021. The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession of 2007 to 2009. There is a major change in the sharp contraction of world real GDP of 3.1 percent in 2020 in the probable global recession originating in the lockdown of economic activity in the COVID-19 event. The IMF has changed its measurement of growth of the world economy to 3.6 percent in 2018 and reducing the forecast rate of growth to 2.9 percent in 2019, minus 3.1 percent in 2020 and 5.8 percent in 2021. Slow-speed recovery occurs in the “major advanced economies” of the G7 that are projected to grow at much lower rates than world output, 0.4 percent on average from 2018 to 2021, in contrast with 2.2 percent for the world as a whole. While the world would grow 9.3 percent in the four years from 2018 to 2021, the G7 as a whole would grow 1.6 percent. The “two speed” concept is in reference to the growth of the 150 countries labeled as emerging and developing economies (EMDE). The EMDEs would grow cumulatively 14.2 percent or at the average yearly rate of 3.4 percent.
Table I-1, IMF World Economic Outlook Database Projections of Real GDP Growth
GDP USD Billions 2018 | Real GDP ∆% | Real GDP ∆% | Real GDP ∆% | Real GDP ∆% | |
World | 135,762 | 3.6 | 2.9 | -3.1 | 5.8 |
G7 | 40,783 | 2.0 | 1.6 | -6.2 | 4.5 |
Canada | 1,842 | 2.0 | 1.6 | -6.2 | 4.3 |
France | 2,970 | 1.7 | 1.3 | -7.2 | 4.5 |
DE | 4,343 | 1.5 | 0.6 | -7.0 | 5.2 |
Italy | 2,406 | 0.8 | 0.3 | -9.1 | 4.8 |
Japan | 5,578 | 0.3 | 0.7 | -5.2 | 3.0 |
UK | 3,065 | 1.3 | 1.4 | -6.5 | 4.0 |
US | 20,580 | 2.9 | 2.3 | -5.9 | 4.7 |
Euro Area | NA | 1.9 | 1.2 | -7.5 | 4.7 |
DE | 4,343 | 1.5 | 0.6 | -7.0 | 5.2 |
France | 2,970 | 1.7 | 1.3 | 7.2 | 4.5 |
Italy | 2,406 | 0.8 | 0.3 | -9.1 | 4.8 |
POT | 334 | 2.6 | 2.2 | -8.0 | 5.0 |
Ireland | 389 | 8.3 | 5.5 | -6.8 | 6.3 |
Greece | 312 | 1.9 | 1.9 | -10.0 | 5.1 |
Spain | 1,854 | 2.4 | 2.0 | -8.0 | 4.3 |
EMDE | 80,401 | 4.5 | 3.7 | -1.1 | 6.6 |
Brazil | 3,383 | 1.3 | 1.1 | -5.3 | 2.9 |
Russia | 4,258 | 2.5 | 1.3 | -5.5 | 3.5 |
India | 10,413 | 6.1 | 4.2 | 1.9 | 7.4 |
China | 25,294 | 6.8 | 6.1 | 1.2 | 9.2 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries); POT: Portugal
Source: IMF World Economic Outlook databank
https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx
Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/index.aspx). Table I-2 is constructed with the WEO database to provide rates of unemployment from 2017 to 2021 for major countries and regions. In fact, unemployment rates for 2017 in Table I-2 are high for all countries: unusually high for countries with high rates most of the time and unusually high for countries with low rates most of the time. The rates of unemployment are particularly high in 2017 for the countries with sovereign debt difficulties in Europe: 8.9 percent for Portugal (POT), 6.7 percent for Ireland, 21.5 percent for Greece, 17.2 percent for Spain and 11.3 percent for Italy, which is lower but still high. The G7 rate of unemployment is 5.0 percent. Unemployment rates are not likely to decrease substantially if relative slow cyclical growth persists in advanced economies. There are sharp increases in the rates of unemployment in 2020 in the probable global recession originating in the lockdown of economy activity in the COVID-19 event. The rate of unemployment increases to 7.8 percent for the G7 countries and 10.4 percent for the euro area.
Table I-2, IMF World Economic Outlook Database Projections of Unemployment Rate as Percent of Labor Force
% Labor Force 2017 | % Labor Force 2018 | % Labor Force 2019 | % Labor Force 2020 | % Labor Force 2021 | |
World | NA | NA | NA | NA | NA |
G7 | 5.0 | 4.5 | 4.3 | 7.8 | 6.9 |
Canada | 6.3 | 5.8 | 5.7 | 7.5 | 7.2 |
France | 9.4 | 9.0 | 8.5 | 10.4 | 10.4 |
DE | 3.8 | 3.4 | 3.2 | 3.9 | 3.5 |
Italy | 11.3 | 10.6 | 10.0 | 12.7 | 10.5 |
Japan | 2.8 | 2.4 | 2.4 | 3.0 | 2.3 |
UK | 4.4 | 4.1 | 3.8 | 4.8 | 4.4 |
US | 4.3 | 3.9 | 3.7 | 10.4 | 9.1 |
Euro Area | 9.1 | 8.2 | 7.6 | 10.4 | 8.9 |
DE | 3.8 | 3.4 | 3.2 | 3.9 | 3.5 |
France | 9.4 | 9.0 | 8.5 | 10.4 | 10.4 |
Italy | 11.3 | 10.6 | 10.0 | 12.7 | 10.5 |
POT | 8.9 | 7.0 | 6.5 | 13.9 | 8.7 |
Ireland | 6.7 | 5.8 | 5.0 | 12.1 | 7.9 |
Greece | 21.5 | 19.3 | 17.3 | 22.3 | 19.0 |
Spain | 17.2 | 15.3 | 14.1 | 20.8 | 17.5 |
EMDE | NA | NA | NA | NA | NA |
Brazil | 12.8 | 12.3 | 11.9 | 14.7 | 13.5 |
Russia | 5.2 | 4.8 | 4.6 | 4.9 | 4.8 |
India | NA | NA | NA | NA | NA |
China | 3.9 | 3.8 | 3.6 | 4.3 | 3.8 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)
Source: IMF World Economic Outlook
https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx
Foreword B. There is typically significant difference between initial claims for unemployment insurance adjusted and not adjusted for seasonality provided in Table VII-2. Seasonally adjusted claims decreased 603,000 from 4,442,000 on Apr 18, 2020 to 3,839,000 on Apr 25, 2020 in the COVID-19 event. Claims not adjusted for seasonality decreased 792,387 from 4,281,648 on Apr 18, 2020 to 3,489,261 on Apr 25, 2020.
Table VII-2, US, Initial Claims for Unemployment Insurance
SA | NSA | 4-week MA SA | |
Apr 25, 2020 | 3,839,000 | 3,489,261 | 5,033,250 |
Apr 18, 2020 | 4,442,000 | 4,281,648 | 5,790,250 |
Change | -603,000 | -792,387 | -757,00 |
Apr 11, 2020 | 5,237,000 | 4,965,046 | 5,506,500 |
Prior Year | 230,000 | 204,755 | 215,500 |
Note: SA: seasonally adjusted; NSA: not seasonally adjusted; MA: moving average
Source: https://www.dol.gov/ui/data.pdf
Table VII-2A provides the SA and NSA number of uninsured that jumped 1,498,784 NSA from 16,277,222 on Apr 11, 2020 to 17,776,006 on Apr 18, 2020.
Table VII-2A, US, Insured Unemployment
SA | NSA | 4-week MA SA | |
Apr 18 2020 | 17,992,000 | 17,776,006 | 13,292,500 |
Apr 11, 2020 | 15,818,000 | 16,277,222 | 9,559,250 |
Change | +2,174,000 | +1,498,784 | +3,733,250 |
Apr 04, 2020 | 11,914,000 | 12,461,658 | 6,050,750 |
Prior Year | 1,682,000 | 1,647,874 | 1,678,250 |
Note: SA: seasonally adjusted; NSA: not seasonally adjusted; MA: moving average
Source: https://www.dol.gov/ui/data.pdf
IID. United States International Terms of Trade. Delfim Netto (1959) partly reprinted in Pelaez (1973) conducted two classical nonparametric tests (Mann 1945, Wallis and Moore 1941; see Kendall and Stuart 1968) with coffee-price data in the period of free markets from 1857 to 1906 with the following conclusions (Pelaez, 1976a, 280):
“First, the null hypothesis of no trend was accepted with high confidence; secondly, the null hypothesis of no oscillation was rejected also with high confidence. Consequently, in the nineteenth century international prices of coffee fluctuated but without long-run trend. This statistical fact refutes the extreme argument of structural weakness of the coffee trade.”
In his classic work on the theory of international trade, Jacob Viner (1937, 563) analyzed the “index of total gains from trade,” or “amount of gain per unit of trade,” denoted as T:
T= (∆Pe/∆Pi)∆Q
Where ∆Pe is the change in export prices, ∆Pi is the change in import prices and ∆Q is the change in export volume. Dorrance (1948, 52) restates “Viner’s index of total gain from trade” as:
“What should be done is to calculate an index of the value (quantity multiplied by price) of exports and the price of imports for any country whose foreign accounts are to be analysed. Then the export value index should be divided by the import price index. The result would be an index which would reflect, for the country concerned, changes in the volume of imports obtainable from its export income (i.e. changes in its "real" export income, measured in import terms). The present writer would suggest that this index be referred to as the ‘income terms of trade’ index to differentiate it from the other indexes at present used by economists.”
What really matters for an export activity especially during modernization is the purchasing value of goods that it exports in terms of prices of imports. For a primary producing country, the purchasing power of exports in acquiring new technology from the country providing imports is the critical measurement. The barter terms of trade of Brazil improved from 1857 to 1906 because international coffee prices oscillated without trend (Delfim Netto 1959) while import prices from the United Kingdom declined at the rate of 0.5 percent per year (Imlah 1958). The accurate measurement of the opportunity afforded by the coffee exporting economy was incomparably greater when considering the purchasing power in British prices of the value of coffee exports, or Dorrance’s (1948) income terms of trade.
The conventional theory that the terms of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):
“Moreover, physical exports of coffee by Brazil increased at the high average rate of 3.5 per cent per year. Brazil's exchange receipts from coffee-exporting in sterling increased at the average rate of 3.5 per cent per year and receipts in domestic currency at 4.5 per cent per year. Great Britain supplied nearly all the imports of the coffee economy. In the period of the free coffee market, British export prices declined at the rate of 0.5 per cent per year. Thus, the income terms of trade of the coffee economy improved at the relatively satisfactory average rate of 4.0 per cent per year. This is only a lower bound of the rate of improvement of the terms of trade. While the quality of coffee remained relatively constant, the quality of manufactured products improved significantly during the fifty-year period considered. The trade data and the non-parametric tests refute conclusively the long-run hypothesis. The valid historical fact is that the tropical export economy of Brazil experienced an opportunity of absorbing rapidly increasing quantities of manufactures from the "workshop" countries. Therefore, the coffee trade constituted a golden opportunity for modernization in nineteenth-century Brazil.”
Imlah (1958) provides decline of British export prices at 0.5 percent in the nineteenth century and there were no lost decades, depressions or unconventional monetary policies in the highly dynamic economy of England that drove the world’s growth impulse. Inflation in the United Kingdom between 1857 and 1906 is measured by the composite price index of O’Donoghue and Goulding (2004) at minus 7.0 percent or average rate of decline of 0.2 percent per year.
Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:
“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”
Cameron (1961) analyzes the mechanism by which the Industrial Revolution in Great Britain spread throughout Europe and Cameron (1967) analyzes the financing by banks of the Industrial Revolution in Great Britain. O’Donoghue and Goulding (2004) provide consumer price inflation in England since 1750 and MacFarlane and Mortimer-Lee (1994) analyze inflation in England over 300 years. Lucas (2004) estimates world population and production since the year 1000 with sustained growth of per capita incomes beginning to accelerate for the first time in English-speaking countries and in particular in the Industrial Revolution in Great Britain. The conventional theory is unequal distribution of the gains from trade and technical progress between the industrialized countries and developing economies (Singer 1950, 478):
“Dismissing, then, changes in productivity as a governing factor in changing terms of trade, the following explanation presents itself: the fruits of technical progress may be distributed either to producers (in the form of rising incomes) or to consumers (in the form of lower prices). In the case of manufactured commodities produced in more developed countries, the former method, i.e., distribution to producers through higher incomes, was much more important relatively to the second method, while the second method prevailed more in the case of food and raw material production in the underdeveloped countries. Generalizing, we may say -that technical progress in manufacturing industries showed in a rise in incomes while technical progress in the production of food and raw materials in underdeveloped countries showed in a fall in prices”
Temin (1997, 79) uses a Ricardian trade model to discriminate between two views on the Industrial Revolution with an older view arguing broad-based increases in productivity and a new view concentration of productivity gains in cotton manufactures and iron:
“Productivity advances in British manufacturing should have lowered their prices relative to imports. They did. Albert Imlah [1958] correctly recognized this ‘severe deterioration’ in the net barter terms of trade as a signal of British success, not distress. It is no surprise that the price of cotton manufactures fell rapidly in response to productivity growth. But even the price of woolen manufactures, which were declining as a share of British exports, fell almost as rapidly as the price of exports as a whole. It follows, therefore, that the traditional ‘old-hat’ view of the Industrial Revolution is more accurate than the new, restricted image. Other British manufactures were not inefficient and stagnant, or at least, they were not all so backward. The spirit that motivated cotton manufactures extended also to activities as varied as hardware and haberdashery, arms, and apparel.”
Phyllis Deane (1968, 96) estimates growth of United Kingdom gross national product (GNP) at around 2 percent per year for several decades in the nineteenth century. The facts that the terms of trade of Great Britain deteriorated during the period of epochal innovation and high rates of economic growth while the income terms of trade of the coffee economy of nineteenth-century Brazil improved at the average yearly rate of 4.0 percent from 1857 to 1906 disprove the hypothesis of weakness of trade as an explanation of relatively lower income and wealth. As Temin (1997) concludes, Britain did pass on lower prices and higher quality the benefits of technical innovation. Explanation of late modernization must focus on laborious historical research on institutions and economic regimes together with economic theory, data gathering and measurement instead of grand generalizations of weakness of trade and alleged neocolonial dependence (Stein and Stein 1970, 134-5):
“Great Britain, technologically and industrially advanced, became as important to the Latin American economy as to the cotton-exporting southern United States. [After Independence in the nineteenth century] Latin America fell back upon traditional export activities, utilizing the cheapest available factor of production, the land, and the dependent labor force.”
Summerhill (2015) contributes momentous solid facts and analysis with an ideal method combining economic theory, econometrics, international comparisons, data reconstruction and exhaustive archival research. Summerhill (2015) finds that Brazil committed to service of sovereign foreign and internal debt. Contrary to conventional wisdom, Brazil generated primary fiscal surpluses during most of the Empire until 1889 (Summerhill 2015, 37-8, Figure 2.1). Econometric tests by Summerhill (2015, 19-44) show that Brazil’s sovereign debt was sustainable. Sovereign credibility in the North-Weingast (1989) sense spread to financial development that provided the capital for modernization in England and parts of Europe (see Cameron 1961, 1967). Summerhill (2015, 3, 194-6, Figure 7.1) finds that “Brazil’s annual cost of capital in London fell from a peak of 13.9 percent in 1829 to only 5.12 percent in 1889. Average rates on secured loans in the private sector in Rio, however, remained well above 12 percent through 1850.” Financial development would have financed diversification of economic activities, increasing productivity and wages and ensuring economic growth. Brazil restricted creation of limited liability enterprises (Summerhill 2015, 151-82) that prevented raising capital with issue of stocks and corporate bonds. Cameron (1961) analyzed how the industrial revolution in England spread to France and then to the rest of Europe. The Société Générale de Crédit Mobilier of Émile and Isaac Péreire provided the “mobilization of credit” for the new economic activities (Cameron 1961). Summerhill (2015, 151-9) provides facts and analysis demonstrating that regulation prevented the creation of a similar vehicle for financing modernization by Irineu Evangelista de Souza, the legendary Visconde de Mauá. Regulation also prevented the use of negotiable bearing notes of the Caisse Générale of Jacques Lafitte (Cameron 1961, 118-9). The government also restricted establishment and independent operation of banks (Summerhill 2015, 183-214). Summerhill (2015, 198-9) measures concentration in banking that provided economic rents or a social loss. The facts and analysis of Summerhill (2015) provide convincing evidence in support of the economic theory of regulation, which postulates that regulated entities capture the process of regulation to promote their self-interest. There appears to be a case that excessively centralized government can result in regulation favoring private instead of public interests with adverse effects on economic activity. The contribution of Summerhill (2015) explains why Brazil did not benefit from trade as an engine of growth—as did regions of recent settlement in the vision of nineteenth-century trade and development of Ragnar Nurkse (1959)—partly because of restrictions on financing and incorporation. Professor Rondo E. Cameron, in his memorable A Concise Economic History of the World (Cameron 1989, 307-8), finds that “from a broad spectrum of possible forms of interaction between the financial sector and other sectors of the economy that requires its services, one can isolate three type-cases: (1) that in which the financial sector plays a positive, growth-inducing role; (2) that in which the financial sector is essentially neutral or merely permissive; and (3) that in which inadequate finance restricts or hinders industrial and commercial development.” Summerhill (2015) proves exhaustively that Brazil failed to modernize earlier because of the restrictions of an inadequate institutional financial arrangement plagued by regulatory capture for self-interest.
There is analysis of the origins of current tensions in the world economy (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), Regulation of Banks and Finance (2009b), International Financial Architecture (2005), The Global Recession Risk (2007), Globalization and the State Vol. I (2008a), Globalization and the State Vol. II (2008b), Government Intervention in Globalization (2008c)).
The US Bureau of Economic Analysis (BEA) measures the terms of trade index of the United States quarterly since 1947 and annually since 1929. Chart IID-1 provides the terms of trade of the US quarterly since 1947 with significant long-term deterioration from 150.474 in IQ1947 to 109.177 in IQ2020. Significant part of the deterioration occurred from the 1960s to the 1980s followed by some recovery and then stability.
Chart IID-1, United States Terms of Trade Quarterly Index 1947-2020
Source: Bureau of Economic Analysis
Chart IID-1A provides the annual US terms of trade from 1929 to 2019. The index fell from 142.590 in 1929 to 109.928 in 2019. There is decline from 1971 to a much lower plateau.
Chart IID-1A, United States Terms of Trade Annual Index 1929-2019, Annual
Source: Bureau of Economic Analysis
Chart IID-1B provides the US terms of trade index, index of terms of trade of nonpetroleum goods and index of terms of trade of goods. The terms of trade of nonpetroleum goods dropped sharply from the mid-1980s to 1995, recovering significantly until 2014, dropping and then recovering again into 2019. There is relative stability in the terms of trade of nonpetroleum goods from 1967 to 2019 but sharp deterioration in the overall index and the index of goods.
Chart IID-1B, United States Terms of Trade Annual Indexes 1967-2019, Annual
Source: Bureau of Economic Analysis
The US Bureau of Labor Statistics (BLS) provides measurements of US international terms of trade. The measurement by the BLS is as follows (https://www.bls.gov/mxp/terms-of-trade.htm):
“BLS terms of trade indexes measure the change in the U.S. terms of trade with a specific country, region, or grouping over time. BLS terms of trade indexes cover the goods sector only.
To calculate the U.S. terms of trade index, take the U.S. all-export price index for a country, region, or grouping, divide by the corresponding all-import price index and then multiply the quotient by 100. Both locality indexes are based in U.S. dollars and are rounded to the tenth decimal place for calculation. The locality indexes are normalized to 100.0 at the same starting point.
TTt=(LODt/LOOt)*100,
where
TTt=Terms of Trade Index at time t
LODt=Locality of Destination Price Index at time t
LOOt=Locality of Origin Price Index at time t
The terms of trade index measures whether the U.S. terms of trade are improving or deteriorating over time compared to the country whose price indexes are the basis of the comparison. When the index rises, the terms of trade are said to improve; when the index falls, the terms of trade are said to deteriorate. The level of the index at any point in time provides a long-term comparison; when the index is above 100, the terms of trade have improved compared to the base period, and when the index is below 100, the terms of trade have deteriorated compared to the base period.”
Chart IID-3 provides the BLS terms of trade of the US with Canada. The index increases from 100.0 in Dec 2017 to 117.8 in Dec 2018 and decreases to 103.8 in Feb 2020. The index increases to 111.0 in Mar 2020.
Chart IID-3, US Terms of Trade, Monthly, All Goods, Canada, NSA, Dec 2017=100
Source: Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-4 provides the BLS terms of trade of the US with the European Union. There is improvement from 100.0 in Dec 2017 to 102.1 in Feb 2020 followed by decrease to 100.4 in Mar 2020.
Chart IID-4, US Terms of Trade, Monthly, All Goods, European Union, NSA, Dec 2017=100
Source: Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-4 provides the BLS terms of trade of the US with Mexico. There is improvement from 100.0 in Dec 2017 to 100.8 in Mar 2020.
Chart IID-5, US Terms of Trade, Monthly, All Goods, Mexico, NSA, Dec 2017=100
Source: Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-4 provides the BLS terms of trade of the US with China. There is deterioration from 100.0 in Dec 2017 to 98.0 in Sep 2018, improvement to 100.6 in Apr 2019 with deterioration to 96.4 in Mar 2020.
Chart IID-6, US Terms of Trade, Monthly, All Goods, China, NSA, Dec 2017=100
Source: Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-4 provides the BLS terms of trade of the US with Japan. There is deterioration from 100.0 in Dec 2017 to 99.2 in Dec 2019 and deterioration to 94.5 in Mar 2020.
Chart IID-7, US Terms of Trade, Monthly, All Goods, Japan, NSA, Dec 2017=100
Source: Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Manufacturing is underperforming in the lost cycle of the global recession. Manufacturing (NAICS) in Mar 2020 is lower by 9.6 percent relative to the peak in Jun 2007, as shown in Chart V-3A. Manufacturing (SIC) in Mar 2020 at 98.5511 is lower by 12.3 percent relative to the peak at 112.3113 in Jun 2007. There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Mar 1919 to Mar 2020. Growth at 3.1 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 157.4135 in Mar 2020. The actual index NSA in Mar 2020 is 98.5511 which is 37.4 percent below trend. The deterioration of manufacturing in Mar 2020 originates in the lockdown of economic activity in the COVID-19 event. Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 161.1952 in Mar 2020. The actual index NSA in Mar 2020 is 98.5511, which is 38.9 percent below trend. Manufacturing output grew at average 1.7 percent between Dec 1986 and Mar 2020. Using trend growth of 1.7 percent per year, the index would increase to 133.1389 in Mar 2020. The output of manufacturing at 98.5511 in Mar 2020 is 26.0 percent below trend under this alternative calculation. Using the NAICS (North American Industry Classification System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index increased from 86.3800 in Apr 2009 to 99.9350 in Mar 2020 or 15.7 percent. The NAICS manufacturing index increased at the annual equivalent rate of 3.5 percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the NAICS manufacturing output index from 106.6777 in Dec 2007 to 162.5897 in Mar 2020. The NAICS index at 99.9350 in Mar 2020 is 38.5 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 131.1461 in Mar 2020. The NAICS index at 99.9350 in Mar 2020 is 23.8 percent below trend under this alternative calculation.
Chart V-3A, United States Manufacturing (NAICS) NSA, Jun 2007 to Mar 2020
Board of Governors of the Federal Reserve System
https://www.federalreserve.gov/releases/g17/Current/default.htm
Chart V-3B provides the civilian noninstitutional population of the United States, or those available for work. The civilian noninstitutional population increased from 231.713 million in Jun 2007 to 259.758 million in Mar 2020 or 28.045 million.
Chart V-3B, United States, Civilian Noninstitutional Population, Million, NSA, Jan 2007 to Mar 2020
Source: US Bureau of Labor Statistics
Chart V-3C, United States, Payroll Manufacturing Jobs, NSA, Jan 2007 to Mar 2020, Thousands
Source: US Bureau of Labor Statistics
Chart V-3D provides the index of US manufacturing (NAICS) from Jan 1972 to Mar 2020. The index continued increasing during the decline of manufacturing jobs after the early 1980s. There are likely effects of changes in the composition of manufacturing with also changes in productivity and trade.
Chart V-3D, United States Manufacturing (NAICS) NSA, Jan 1972 to Mar 2020
Source: Board of Governors of the Federal Reserve System
https://www.federalreserve.gov/releases/g17/Current/default.htm
Chart V-3E provides the US noninstitutional civilian population, or those in condition of working, from Jan 1948, when first available, to Mar 2020. The noninstitutional civilian population increased from 170.042 million in Jun 1981 to 259.758 million in Mar 2020, or 89.716 million.
Chart V-3E, United States, Civilian Noninstitutional Population, Million, NSA, Jan 1948 to Mar 2020
Source: US Bureau of Labor Statistics
Chart V-3C, United States, Payroll Manufacturing Jobs, NSA, Jan 1939 to Mar 2020, Thousands
Source: US Bureau of Labor Statistics
Table I-13A provides national income without capital consumption by industry with estimates based on the Standard Industrial Classification (SIC). The share of agriculture declines from 8.7 percent in 1948 to 1.7 percent in 1987 while the share of manufacturing declines from 30.2 percent in 1948 to 19.4 percent in 1987. Colin Clark (1957) pioneered the analysis of these trends over long periods.
Table I-13A, US, National Income without Capital Consumption Adjustment by Industry, Annual Rates, Billions of Dollars, % of Total
1948 | % Total | 1987 | % Total | |
National Income WCCA | 249.1 | 100.0 | 4,029.9 | 100.0 |
Domestic Industries | 247.7 | 99.4 | 4,012.4 | 99.6 |
Private Industries | 225.3 | 90.4 | 3,478.8 | 86.3 |
Agriculture | 21.7 | 8.7 | 66.5 | 1.7 |
Mining | 5.8 | 2.3 | 42.5 | 1.1 |
Construction | 11.1 | 4.5 | 201.0 | 5.0 |
Manufacturing | 75.2 | 30.2 | 780.2 | 19.4 |
Durable Goods | 37.5 | 15.1 | 458.4 | 11.4 |
Nondurable Goods | 37.7 | 15.1 | 321.8 | 8.0 |
Transportation PUT | 21.3 | 8.5 | 317.7 | 7.9 |
Transportation | 13.8 | 5.5 | 127.2 | 3.2 |
Communications | 3.8 | 1.5 | 96.7 | 2.4 |
Electric, Gas, SAN | 3.7 | 1.5 | 93.8 | 2.3 |
Wholesale Trade | 17.1 | 6.9 | 283.1 | 7.0 |
Retail Trade | 28.8 | 11.6 | 400.4 | 9.9 |
Finance, INS, RE | 22.9 | 9.2 | 651.7 | 16.2 |
Services | 21.4 | 8.6 | 735.7 | 18.3 |
Government | 22.4 | 9.0 | 533.6 | 13.2 |
Rest of World | 1.5 | 0.6 | 17.5 | 0.4 |
2003.9 | 11.6 | 2016.3 | 11.5 | |
252.6 | 1.5 | 257.9 | 1.5 |
Notes: Using 1972 Standard Industrial Classification (SIC). Percentages Calculates from Unrounded Data; WCCA: Without Capital Consumption Adjustment by Industry; RE: Real Estate; PUT: Public Utilities; SAN: Sanitation
Source: US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Table I-13B provides national income without capital consumption estimated based on the 2012 North American Industry Classification (NAICS). The share of manufacturing fell from 14.9 percent in 1998 to 9.5 percent in 2018.
Table I-13B, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total
1998 | % Total | 2018 | % Total | |
National Income WCCA | 7,744.4 | 100.0 | 17,136.5 | 100.0 |
Domestic Industries | 7,727.0 | 99.8 | 16,868.6 | 98.4 |
Private Industries | 6,793.3 | 87.7 | 14,889.6 | 86.9 |
Agriculture | 72.7 | 0.9 | 119.7 | 0.7 |
Mining | 74.2 | 1.0 | 202.7 | 1.2 |
Utilities | 134.4 | 1.7 | 157.7 | 0.9 |
Construction | 379.2 | 4.9 | 902.5 | 5.3 |
Manufacturing | 1156.4 | 14.9 | 1635.3 | 9.5 |
Durable Goods | 714.9 | 9.2 | 964.9 | 5.6 |
Nondurable Goods | 441.5 | 5.7 | 670.4 | 3.9 |
Wholesale Trade | 512.8 | 6.6 | 958.2 | 5.6 |
Retail Trade | 610.0 | 7.9 | 1124.1 | 6.6 |
Transportation & WH | 246.1 | 3.2 | 554.4 | 3.2 |
Information | 294.3 | 3.8 | 629.7 | 3.7 |
Finance, Insurance, RE | 1280.9 | 16.5 | 3058.8 | 17.8 |
Professional & Business Services | 889.8 | 11.5 | 2522.6 | 14.7 |
Education, Health Care | 607.1 | 7.8 | 1764.8 | 10.3 |
Arts, Entertainment | 290.5 | 3.8 | 756.6 | 4.4 |
Other Services | 244.9 | 3.3 | 502.5 | 2.9 |
Government | 933.7 | 12.1 | 1979.0 | 11.5 |
Rest of the World | 17.4 | 0.2 | 267.9 | 1.6 |
Notes: Estimates based on 2012 North American Industry Classification System (NAICS). Percentages Calculates from Unrounded Data; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services
Source: US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
II I IMF View of World Economy and Finance. The International Financial Institutions (IFI) consist of the International Monetary Fund, World Bank Group, Bank for International Settlements (BIS) and the multilateral development banks, which are the European Investment Bank, Inter-American Development Bank and the Asian Development Bank (Pelaez and Pelaez, International Financial Architecture (2005), The Global Recession Risk (2007), 8-19, 218-29, Globalization and the State, Vol. II (2008b), 114-48, Government Intervention in Globalization (2008c), 145-54). There are four types of contributions of the IFIs:
1. Safety Net. The IFIs contribute to crisis prevention and crisis resolution.
i. Crisis Prevention. An important form of contributing to crisis prevention is by surveillance of the world economy and finance by regions and individual countries. The IMF and World Bank conduct periodic regional and country evaluations and recommendations in consultations with member countries and jointly with other international organizations. The IMF and the World Bank have been providing the Financial Sector Assessment Program (FSAP) by monitoring financial risks in member countries that can serve to mitigate them before they can become financial crises.
ii. Crisis Resolution. The IMF jointly with other IFIs provides assistance to countries in resolution of those crises that do occur. Recently, the IMF is cooperated with the government of Greece, European Union and European Central Bank in resolving the debt difficulties of Greece as it has done in the past in numerous other circumstances. Programs with other countries involved in the European debt crisis may also be developed.
2. Surveillance. The IMF conducts surveillance of the world economy, finance and public finance with continuous research and analysis. Important documents of this effort are the World Economic Outlook (http://www.imf.org/external/ns/cs.aspx?id=29), Global Financial Stability Report (http://www.imf.org/external/pubs/ft/gfsr/index.htm) and Fiscal Monitor (http://www.imf.org/external/ns/cs.aspx?id=262).
3. Infrastructure and Development. The IFIs also engage in infrastructure and development, in particular, the World Bank Group and the multilateral development banks.
4. Soft Law. Significant activity by IFIs has consisted of developing standards and codes under multiple forums. It is easier and faster to negotiate international agreements under soft law that are not binding but can be very effective (on soft law see Pelaez and Pelaez, Globalization and the State, Vol. II (2008c), 114-25). These norms and standards can solidify world economic and financial arrangements.
The objective of this section is to analyze current projections of the IMF database for the most important indicators.
Table I-1 is constructed with the database of the IMF (https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx) to show GDP in dollars in 2018 and the growth rate of real GDP of the world and selected regional countries from 2018 to 2021. The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession of 2007 to 2009. There is a major change in the sharp contraction of world real GDP of 3.1 percent in 2020 in the probable global recession originating in the lockdown of economic activity in the COVID-19 event. The IMF has changed its measurement of growth of the world economy to 3.6 percent in 2018 and reducing the forecast rate of growth to 2.9 percent in 2019, minus 3.1 percent in 2020 and 5.8 percent in 2021. Slow-speed recovery occurs in the “major advanced economies” of the G7 that are projected to grow at much lower rates than world output, 0.4 percent on average from 2018 to 2021, in contrast with 2.2 percent for the world as a whole. While the world would grow 9.3 percent in the four years from 2018 to 2021, the G7 as a whole would grow 1.6 percent. The “two speed” concept is in reference to the growth of the 150 countries labeled as emerging and developing economies (EMDE). The EMDEs would grow cumulatively 14.2 percent or at the average yearly rate of 3.4 percent.
Table I-1, IMF World Economic Outlook Database Projections of Real GDP Growth
GDP USD Billions 2018 | Real GDP ∆% | Real GDP ∆% | Real GDP ∆% | Real GDP ∆% | |
World | 135,762 | 3.6 | 2.9 | -3.1 | 5.8 |
G7 | 40,783 | 2.0 | 1.6 | -6.2 | 4.5 |
Canada | 1,842 | 2.0 | 1.6 | -6.2 | 4.3 |
France | 2,970 | 1.7 | 1.3 | -7.2 | 4.5 |
DE | 4,343 | 1.5 | 0.6 | -7.0 | 5.2 |
Italy | 2,406 | 0.8 | 0.3 | -9.1 | 4.8 |
Japan | 5,578 | 0.3 | 0.7 | -5.2 | 3.0 |
UK | 3,065 | 1.3 | 1.4 | -6.5 | 4.0 |
US | 20,580 | 2.9 | 2.3 | -5.9 | 4.7 |
Euro Area | NA | 1.9 | 1.2 | -7.5 | 4.7 |
DE | 4,343 | 1.5 | 0.6 | -7.0 | 5.2 |
France | 2,970 | 1.7 | 1.3 | 7.2 | 4.5 |
Italy | 2,406 | 0.8 | 0.3 | -9.1 | 4.8 |
POT | 334 | 2.6 | 2.2 | -8.0 | 5.0 |
Ireland | 389 | 8.3 | 5.5 | -6.8 | 6.3 |
Greece | 312 | 1.9 | 1.9 | -10.0 | 5.1 |
Spain | 1,854 | 2.4 | 2.0 | -8.0 | 4.3 |
EMDE | 80,401 | 4.5 | 3.7 | -1.1 | 6.6 |
Brazil | 3,383 | 1.3 | 1.1 | -5.3 | 2.9 |
Russia | 4,258 | 2.5 | 1.3 | -5.5 | 3.5 |
India | 10,413 | 6.1 | 4.2 | 1.9 | 7.4 |
China | 25,294 | 6.8 | 6.1 | 1.2 | 9.2 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries); POT: Portugal
Source: IMF World Economic Outlook databank
https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx
Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/index.aspx). Table I-2 is constructed with the WEO database to provide rates of unemployment from 2017 to 2021 for major countries and regions. In fact, unemployment rates for 2017 in Table I-2 are high for all countries: unusually high for countries with high rates most of the time and unusually high for countries with low rates most of the time. The rates of unemployment are particularly high in 2017 for the countries with sovereign debt difficulties in Europe: 8.9 percent for Portugal (POT), 6.7 percent for Ireland, 21.5 percent for Greece, 17.2 percent for Spain and 11.3 percent for Italy, which is lower but still high. The G7 rate of unemployment is 5.0 percent. Unemployment rates are not likely to decrease substantially if relative slow cyclical growth persists in advanced economies. There are sharp increases in the rates of unemployment in 2020 in the probable global recession originating in the lockdown of economy activity in the COVID-19 event. The rate of unemployment increases to 7.8 percent for the G7 countries and 10.4 percent for the euro area.
Table I-2, IMF World Economic Outlook Database Projections of Unemployment Rate as Percent of Labor Force
% Labor Force 2017 | % Labor Force 2018 | % Labor Force 2019 | % Labor Force 2020 | % Labor Force 2021 | |
World | NA | NA | NA | NA | NA |
G7 | 5.0 | 4.5 | 4.3 | 7.8 | 6.9 |
Canada | 6.3 | 5.8 | 5.7 | 7.5 | 7.2 |
France | 9.4 | 9.0 | 8.5 | 10.4 | 10.4 |
DE | 3.8 | 3.4 | 3.2 | 3.9 | 3.5 |
Italy | 11.3 | 10.6 | 10.0 | 12.7 | 10.5 |
Japan | 2.8 | 2.4 | 2.4 | 3.0 | 2.3 |
UK | 4.4 | 4.1 | 3.8 | 4.8 | 4.4 |
US | 4.3 | 3.9 | 3.7 | 10.4 | 9.1 |
Euro Area | 9.1 | 8.2 | 7.6 | 10.4 | 8.9 |
DE | 3.8 | 3.4 | 3.2 | 3.9 | 3.5 |
France | 9.4 | 9.0 | 8.5 | 10.4 | 10.4 |
Italy | 11.3 | 10.6 | 10.0 | 12.7 | 10.5 |
POT | 8.9 | 7.0 | 6.5 | 13.9 | 8.7 |
Ireland | 6.7 | 5.8 | 5.0 | 12.1 | 7.9 |
Greece | 21.5 | 19.3 | 17.3 | 22.3 | 19.0 |
Spain | 17.2 | 15.3 | 14.1 | 20.8 | 17.5 |
EMDE | NA | NA | NA | NA | NA |
Brazil | 12.8 | 12.3 | 11.9 | 14.7 | 13.5 |
Russia | 5.2 | 4.8 | 4.6 | 4.9 | 4.8 |
India | NA | NA | NA | NA | NA |
China | 3.9 | 3.8 | 3.6 | 4.3 | 3.8 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)
Source: IMF World Economic Outlook
https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx
The database of the World Economic Outlook of the IMF (https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx) is used to obtain government net lending/borrowing as percent of GDP in Table I-5. Interest on government debt is added to the primary balance to obtain overall government fiscal balance in Table I-5. For highly indebted countries there is an even tougher challenge of fiscal consolidation. Adverse expectations on the success of fiscal consolidation may drive up yields on government securities that could create hurdles to adjustment, growth and employment. The overall government fiscal balance increases sharply to 12.0 percent for the G7 in 2020, decreasing to 6.2 percent in 2021. The overall fiscal deficit of the US increases to 15.5 percent in 2020, decreasing to 8.6 percent in 2021.
Table I-5, IMF World Economic Outlook Database Projections of General Government Net Lending/Borrowing as Percent of GDP
% GDP 2017 | % GDP 2018 | % GDP 2019 | % GDP 2020 | % GDP 2021 | |
World | NA | NA | NA | NA | NA |
G7 | -3.2 | -3.6 | -3.8 | -12.0 | -6.2 |
Canada | -0.1 | -0.4 | -0.4 | -11.8 | -3.8 |
France | -2.8 | -2.3 | -3.0 | -9.2 | -6.2 |
DE | 1.2 | 1.9 | 1.4 | -5.5 | -1.2 |
Italy | -2.4 | -2.2 | -1.6 | -8.3 | -3.5 |
Japan | -3.1 | -2.4 | -2.8 | -7.1 | -2.1 |
UK | -2.5 | -2.2 | -2.1 | -8.3 | -5.5 |
US | -4.5 | -5.7 | -5.8 | -15.5 | -8.6 |
Euro Area | -0.9 | -0.5 | -0.7 | -7.5 | -3.6 |
DE | 1.2 | 1.9 | 1.4 | -5.5 | -1.2 |
France | -2.8 | -2.3 | -3.0 | -9.2 | -6.2 |
Italy | -2.4 | -2.2 | -1.6 | -8.3 | -3.5 |
POT | -3.0 | -0.4 | 0.2 | -7.1 | -1.9 |
Ireland | -0.3 | 0.1 | 0.3 | -5.2 | -0.8 |
Greece | 1.0 | 0.9 | 0.4 | -9.0 | -7.9 |
Spain | -3.0 | -2.5 | -2.6 | -9.5 | -6.7 |
EMDE | -4.1 | -3.7 | -4.7 | -8.9 | -7.2 |
Brazil | -7.9 | -7.2 | -6.0 | -9.3 | -6.1 |
Russia | -1.5 | 2.9 | 1.9 | -4.8 | -3.0 |
India | -6.4 | -6.3 | -7.4 | -7.4 | -7.3 |
China | -3.8 | -4.7 | -6.4 | -11.2 | -9.6 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)
Source: IMF World Economic Outlook databank
https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx
There were some hopes that the sharp contraction of output during the global recession would eliminate current account imbalances. Table I-6 constructed with the database of the WEO (https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx) shows that external imbalances have been maintained in the form of current account deficits and surpluses. China’s current account surplus is 1.6 percent of GDP for 2017 and is projected to stabilize at 1.0 percent of GDP in 2021. At the same time, the current account deficit of the US is 2.3 percent of GDP in 2017 and is projected at 2.8 percent of GDP in 2021. The current account surplus of Germany is 7.8 percent for 2017 and remains at a high 6.6 percent of GDP in 2021. Japan’s current account surplus is 4.2 percent of GDP in 2017 and stabilizes to 1.9 percent of GDP in 2021.
Table I-6, IMF World Economic Outlook Databank Projections, Current Account of Balance of Payments as Percent of GDP
% CA/ | % CA/ | % CA/ | % CA/ | % CA/ | |
World | NA | NA | NA | NA | NA |
G7 | -0.2 | -0.4 | -0.4 | -0.9 | -0.9 |
Canada | -2.8 | -2.5 | -2.0 | -3.7 | -2.3 |
France | -0.7 | -0.6 | -0.8 | -0.7 | -0.6 |
DE | 7.8 | 7.4 | 7.1 | 6.6 | 6.6 |
Italy | 2.6 | 2.5 | 3.0 | 3.1 | 3.1 |
Japan | 4.2 | 3.5 | 3.6 | 1.7 | 1.9 |
UK | -3.5 | -3.9 | -3.8 | -4.4 | -4.5 |
US | -2.3 | -2.4 | -2.3 | -2.6 | -2.8 |
Euro Area | 3.1 | 3.1 | 2.7 | 2.6 | 2.7 |
DE | 7.8 | 7.4 | 7.1 | 6.6 | 6.6 |
France | -0.7 | -0.6 | -0.8 | -0.7 | -0.6 |
Italy | 2.6 | 2.5 | 3.0 | 3.1 | 3.1 |
POT | 1.3 | 0.4 | -0.1 | 0.3 | -0.4 |
Ireland | 0.5 | 10.6 | -9.5 | 6.3 | 5.3 |
Greece | -2.5 | -3.5 | -2.1 | -6.5 | -3.4 |
Spain | 2.7 | 1.9 | 2.0 | 2.2 | 2.4 |
EMDE | 0.0 | -0.1 | 0.1 | -0.9 | -0.6 |
Brazil | -0.7 | -2.2 | -2.7 | -1.8 | -2.3 |
Russia | 2.1 | 6.8 | 3.8 | 0.7 | 0.6 |
India | -1.8 | -2.1 | -1.1 | -0.6 | -1.4 |
China | 1.6 | 0.4 | 1.0 | 0.5 | 1.0 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)
Source: IMF World Economic Outlook databank
https://www.imf.org/external/pubs/ft/weo/2020/01/weodata/index.aspx
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
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