Structural transformation has been an important driving force of economic development over the last decades. According to the theory of structural transformation (Kuznets, 1957; Chenery, 1960; and Fourastié, 1963) development is driven by a shift from the extraction of raw materials and primary sector activities to increasingly complex technical transformation processes, commonly referred to as manufacturing. On the supply side, the sources of that transition include, the development of know-how, increase in high-skilled labour and technological advancement, and enabling the application of new production methods. On the demand side, the rising standard of living induces a shift from the consumption of food and other primary commodities towards consumer goods, that are usually manufactured. This transformation leads to higher value added and greater economic welfare. In line with this thinking, Sustainable Development Goal target 9.2 promotes inclusive and sustainable industrialization and aims to significantly raise industry's share of employment and Gross domestic product by 2030.
During the later phases of economic development, a sectoral shift from manufacturing to services has typically been observed. Once a certain standard of living is reached, the demand for services increases relative to the demand for physically produced goods. According to Haraguchi and Rezonja (2010) this level is reached when GDP per capita amounts to around US$13,000 at 2005 prices. At that stage, manufacturing usually accounts for around one fifth of value added. Based on these estimates, UNIDO (2017) considers countries to be industrialized when their Manufacturing value added (MVA) is the net-output of all resident manufacturing activity units. It is obtained by adding up their outputs and subtracting intermediate inputs . Manufacturing can broadly be understood as "the physical or chemical transformation of materials, substances, or components into new products" , consisting of sector C in the International Standard Industrial Classification of all Economic Activities (ISIC) revision 4 ., adjusted to purchasing power parities, exceeds US$2,500 per capita.
In 2018, manufacturing value added per capita amounted to US$5,922 at constant 2015 prices in developed economies (see figure 1). It was around four times higher than in developing Asia and Oceania (US$1,388), five times higher than in developing Latin America and the Caribbean (US$1,136) and six and a half times higher than in transition economies (US$906). It exceeded the value in Africa (US$207) by almost 30 times.
Over the last 20 years, manufacturing value added per capita in developing Asia and Oceania has steadily increased – by three and a half times since 1998 – with the result that the region overtook the transition economies in 2009 and Latin America and the Caribbean in 2015. In Africa, Latin America and the Caribbean and in the transition economies, the indicator has remained constant since 2014. Developed economies have recorded modest steady growth over the last 20 years, disrupted only by the economic downswings from 2000 to 2002 and from 2007 to 2010.
Dropping industrial output after the outbreak of COVID-19
The outbreak of Infectious disease caused by the strain of coronavirus SARS-CoV-2 discovered in December 2019. Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19 . led to considerable disruptions in manufacturing all over the world. According to ILO (2020a) manufacturing was among the economic sectors worst hit by the Commonly described by the WHO as ‘the worldwide spread of a new disease’, no strict definition is provided. In 2009, they set out the basic requirements for a pandemic: • New virus emerges in humans
• Minimal or no population immunity
• Causes serious illness; high morbidity/mortality
• Spreads easily from person to person
• Global outbreak of disease.
The US Centre for Disease Control uses a similar approach, but with a reduced set of criteria. It is very difficult to gauge whether the spread of a disease should be termed an outbreak, epidemic or pandemic. In other words, when to declare a pandemic isn’t a black and white decision ., alongside retail trade, accommodation, food services and other sectors. The impact by industry depends on the effects of the containment measures introduced on supply and demand. Some sectors were hit mainly from the demand side, for example due to restrictions concerning modes of consumption and the distribution of goods, and others more from the supply side, for example due to disrupted supply chains. It seems that certain sectors have also benefited from an increased demand for their products as a direct or indirect consequence of the pandemic. Some businesses have managed to make a digital leap to recover some lost revenue, enable new ways of working, such as telework and digital trade, and apply new methods to quickly adjust production according to rapidly changing demand and supply conditions.
In spring 2020, manufacturing was hit by the COVID-19 pandemic at different times across the world (see figure 2). China came first, experiencing a sharp drop of manufacturing output in January, down 26 per cent on the previous month (seasonally adjusted), as Wuhan and other regions were locked down (CCSA, 2020). Already in February-April, Chinese manufacturing started to recover with 8 to 11 per cent monthly growth and had partially bounced back by March 2020 and reached the pre-crisis level by April 2020.
In the Eurozone and the United States of America manufacturing output started falling in March 2020. This fall was most pronounced in the Eurozone, where many countries introduced full or partial lockdowns by the middle of the month. Production in manufacturing dropped by 12 per cent in March 2020 after a longer period of stability. Italy, the first country in the Eurozone hit by the pandemic, saw manufacturing output decrease by 31 per cent in March. The Purchasing Managers’ Index (PMI) is a monthly indicator of expected economic activity, collected by surveying senior executives at private sector companies. The PMI is a weighted average of five sub-indices measuring new orders, output, employment, suppliers’ delivery times and stocks of purchases. It is calculated for the total economy as well as for specific sectors, such as manufacturing, construction, services, etc. A figure of 50 indicates that no change in economic production is expected; a value above 50 means that the economy is expected to grow, a value below 50 that it is expected to contract . of the manufacturing sector for the Eurozone indicates an acceleration of decline, dropping from 44.5 in March to 33.4 in April. The further the PMI is below 50, the faster the decline anticipated by managers. In the United States of America, where the virus started spreading later than in Europe, manufacturing output dropped in March 2020 by 5.5 per cent and in April at an accelerated rate of 13.7 per cent.
In Brazil, manufacturing started contracting before the pandemic, with the decline speeding up in March (-10 per cent) and April (-14 per cent). By contrast, manufacturing in South Africa and the Russian Federation appeared only slightly affected by COVID-19 until March. In the Russian Federation, the Index of Industrial Production (IIP) is a measure of the change in the volume of goods or services produced over time. Its main purpose is to provide a measure of the short-term changes in value added over a given reference period, usually a month or a quarter. The index covers the industrial sector, including mining, manufacturing, electricity and gas, and water and waste . for manufacturing retained zero growth until March, but declined by 12 per cent in April. In South Africa, where IIP data for manufacturing were not available after February, the PMI indicates a slightly accelerated decline from February (48) to March (45) and further to April (35).
According to the PMI for May 2020, business managers anticipate a continued contraction in manufacturing, albeit at slower pace than before, in all these countries, except for China where manufacturing is expected to continue to grow slightly (PMI 50.6).
Intermittent catching up of LDCs
In 2018, LDCs’ manufacturing sector produced on average US$128 per head, at 2015 prices, almost 50 times less than the average produced in the developed world. However, LDCs’ manufacturing value added per capita has steadily increased over the last 20 years, at a higher rate than in developing countries in general. The level in 2018 was already three times higher than the level of 1998.
The manufacturing share in value added, the focus of SDG target 9.2 for Least developed country, increased from 10.3 per cent in 1998 to 12.4 per cent in 2018. Most of that progress was made in the last eight years; until 2010, the share had remained constant at just below 11 per cent (see figure 3). Extrapolating this trend into the future, the growth achieved after 2005 on average appears to be too slow to achieve the SDG target of doubling the manufacturing share in value added by 2030.1 From 2005 onwards, an average annual increase of 0.41 percentage points would have been required to reach the target. The actual annual average increase until 2018 was 0.17 percentage points. Between 2014 and 2016, accruals comparable to the target path were indeed recorded, of between 0.41 and 0.48 percentage points each year, but in recent years the pace has slowed to less than 0.3 percentage points annually. The findings above − in particular, the modest growth of manufacturing in value added compared to employment − suggest that new industrial innovations and policies are needed in LDCs to accelerate structural transformation.
How has structural transformation changed the sectoral distribution of employment and value added? Between 2000 and 2018, the share of manufacturing in employment increased only in developing Asia and Oceania (from 8.9 to 13.6 per cent) and in Africa (from 6.7 to 7.4 per cent) (see figure 4). In developing Asia and Oceania, in contrast to Africa, this increase was combined with an increase of the manufacturing share in value added (from 19.9 to 24.2 per cent). This highlights a growing disparity in productivity growth between the regions, in line with the above diverging trends in manufacturing value added per capita (see figure 1). In LDCs, increases in manufacturing value added per capita, discussed above, were strongly employment driven. The share of manufacturing in employment increased from 3.3 to 9.1 per cent between 2000 and 2018.
These figures suggest that during the last two decades, only Asian and Oceanian developing economies have gone through a process of structural transformation as described in the literature. The LDCs as a group have also followed that path. Latin America and the Caribbean as well as transition and developed economies recorded shrinking proportions of manufacturing in both employment and value added. This development is not what is aspired to by the SDG target, which aims at significantly raising industry's share of employment and value added. Many of these counties may nevertheless have changed their economic structure towards higher value-added activities, by raising the share of services, in particular telecommunication and Information and communications technology (ICT) is a diverse set of technological tools and resources used to transmit, store, create, share or exchange information. These resources include computers, the Internet, live broadcasting technologies, recorded broadcasting technologies and telephony . services or by a structural transformation within manufacturing from lower-tech to higher-tech production. Below, the analysis is extended to investigate to what extent such digitalization and transformation to higher technologies is happening.
The 2030 Agenda promotes technological development through research and innovation, especially in developing economies. Progress towards the achievement of that target is measured by the proportion of Medium and high-tech industry is an industry in which producers of goods incur relatively high expenditure on research and development (R&D) per unit of output. The distinction between low, medium, and high-tech industries is based on R&D intensity, i.e. the ratio of R&D expenditure to an output measure, usually gross value added. For a list of the particular economic activities, considered to be medium and high-tech . value added in total manufacturing value added (SDG indicator 9.b.1). This indicator shows a shift from lower to higher technology value added, raising the average value added per worker. Research and development (R&D) comprise creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind, culture and society – and to devise new applications of available knowledge . and innovation play a crucial role in this transformation by providing the grounds for the use of new and more efficient technologies.
In the developed world, medium and high-tech industry accounts for higher shares of manufacturing value added than in developing and transition economies (see figure 5). When looking at weighted regional averages, half of developed economies' manufacturing output is obtained in medium and high-tech industries. Among developing countries, the weighted rate varies considerably across regions. In developing Asia and Oceania, it is 43 per cent, almost as high as in developed economies, while the rate reaches 33 per cent in developing America and only 21 per cent in Africa. For transition economies the rate is slightly above that of Africa with 28 per cent.
Over the last 10 years, the gap between developing and developed economies has narrowed only slightly. While developed economies managed to maintain the share of medium and high-tech manufacturing at around 50 per cent, the rate fell slightly in developing Africa (from 22 to 21 per cent) and rose little in developing America (from 32 to 33 per cent). The proportion of medium and high-tech manufacturing has increased by more than 5 per centage points in transition economies from 2007 (22.9 per cent) to 2017 (28.5 per cent) but remains below the level in 2000. Only in the developing economies of Asia and Oceania has the share of medium and high-tech manufacturing remained constant, at around 44 or 43 per cent. Developed countries have cemented their lead, while developing economies have not managed to increase the share of higher technologies in manufacturing in the last 10 to 15 years, and some are shifting towards lower-technology sectors.
Figure 5 highlights the considerable variation across individual economies, especially in Asia. This region encompasses, on one hand, the two economies with the world's most innovative manufacturing sectors, namely, Singapore (78 per cent) and Taiwan, Province of China (70 per cent); on the other hand, it includes several countries, primarily LDCs and Small island developing States, in which the share of medium and high-tech industries in value added has persistently remained below three per cent, such as Cambodia (0.3 per cent), Tajikistan (2.1 per cent) and the State of Palestine (2.5 per cent).
Notes: A violin plot shows the distribution of individual countries’ medium and high-tech industry shares in manufacturing value added within each country group and year. The coloured areas depict the distribution of countries’ rates smoothed by kernel density estimation, a non-parametric way to estimate the probability density function of a variable. The wider the violin shape, the higher the possibility to find an observation, in this case a country, in that location. The dots within the shapes represent the weighted average of countries’ medium and high-tech industry shares in manufacturing value added.
Considerable spread in the medium and high-tech industry share of manufacturing value added is also found among developed economies. Some of them reach less than one third of the rates recorded by the developed countries at the highest ranks, such as, Switzerland (65 per cent) and Germany (62 per cent).
Many LDCs and SIDS are characterized by low shares of medium and high-tech manufacturing. However, this is changing. Noteworthy developments among SIDS include Trinidad and Tobago, where the medium and high-tech share in manufacturing value added increased from 29 per cent in 2001 to 40 per cent in 2017, as well as Barbados, where the rate has remained high, at 38 per cent, over the last 15 years (see UNIDO, 2020).
Developing economies’ medium and high-tech exports increasing
Looking at international trade, the share of medium and high-tech products in manufacturing exports has been increasing in developing countries recently, while it has remained almost constant in the developed world (see figure 6). In developing America and developing Asia and Oceania, the share of medium and high-tech exports reached almost 60 per cent in 2017, whereas in developed economies it stood at 64 per cent. Africa has increased its medium and high-tech export share from 31 to 39 per cent from 2007 to 2017. As a result, the region has been catching up in the structural transformation of manufactured exports, and the overall gap between the developing and developed world has narrowed. Transition economies lag, despite some progress. They were overtaken by Africa in 2013.
Governments are encouraged to increase spending on R&D in the context of the 2030 Agenda. In 2017, the latest year with globally comparable innovation statistics, the world invested US$2.2 trillion in R&D, PPP-adjusted. Over the five-year period from 2012 to 2017, overall R&D spending increased by 5.8 per cent each year on average. Not surprisingly, investment was highly concentrated in a few economies. In 2017, over 75 per cent of R&D investment was made by only 10 countries.
In PPP-adjusted value terms, the leaders in R&D spending were the United States of America (US$543 billion), China (US$499 billion), Japan (US$171 billion) and Germany (US$131 billion). Remarkably, the United States and China accounted for almost half of global R&D investment (see figure 7 and table 1). Among developing economies, high annual growth rates in R&D spending were recorded for Thailand (29 per cent), Turkey (11.5 per cent), China (11.1 per cent) and Egypt (11 per cent) since 2012. India, Iran and Malaysia also reported significant increases in innovation expenditure.2
Despite the substantial growth of world R&D investment in absolute terms, R&D intensity – SDG indicator 9.5.1 – recorded a rather weak progress from 2012 to 2017. In 2017, global gross expenditure on R&D stood at 1.7 per cent of GDP (see figure 8). The Republic of Korea (4.6 per cent) and Israel (4.5 per cent) were the most prominent R&D investors relative to GDP, followed by Switzerland (3.4 per cent) and Sweden (3.3 per cent). The United States of America invested 2.8 per cent of its GDP in innovation, and China 2.1 per cent. Only a few developing economies have managed to develop into ‘R&D powerhouses’, such as, China and the Republic of Korea. For some of these countries, that process took around two decades. Today, it appears as if a ‘glass ceiling’ separates the R&D leaders from the rest of the world. Participation in global value chains and R&D networks is essential for moving-up the innovation ladder (Cornell University et al., 2019).
Looking at regional averages, Northern America invests most in R&D in proportion to GDP. However, it was Eastern and South-Eastern Asia where R&D spending relative to GDP grew fastest from 2012 to 2017. Europe recorded only a slight increase. At 1.9 per cent of GDP in 2017, R&D intensity remained well below the three-per-cent goal set by the European Union (European Commission, 2010). Only Austria, Denmark, Germany and Sweden surpassed this target. The African Union has also established an R&D intensity target for its member states, set at one per cent (UNECA, 2018). According to available statistics, among AU member countries, only South Africa was close to that target, recording an R&D intensity of 0.9 per cent. Rwanda and Senegal recorded notable rises in innovation expenditures, but the one-percent target is not yet within reach. In Sub-Saharan Africa, R&D intensity stood at 0.4 per cent, while Northern Africa and Western Asia recorded 0.8 per cent.
|Investors||PPP US$ billions|| Annual average growth percentage|
|Percentage of GDP||Percentage of world total|
|Republic of Korea||91||6.6||4.6||4.1|
|Top 10 developing countries, excl. China and the Republic of Korea|
|Iran (Islamic Republic of)||14||...||0.8||0.6|
a refers to 2016.
b refers to 2018.
The developing economies of America spent on average 0.7 per cent of their GDP on innovation in 2017. At 1.3 per cent, Brazil’s R&D intensity is defined as the ratio of gross domestic expenditure on research and development (GERD) to GDP . was more than two times higher than that of any other country from the region. In Oceania, R&D spending stood at 1.8 per cent of GDP, dropping from two per cent observed five years earlier. SIDS3 allocated on average one per cent and LDCs some 0.2 per cent of GDP to R&D.
Note: Based on United Nations Educational, Scientific and Cultural Organization country classification
SDG indicator 9.5.2 looks at the number of persons directly Employed in R&D in FTE is the ratio of working hours spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group ., as Full Time Equivalent (FTE) unit of labour is the hours worked by one employee on a full-time basis. The concept is used to convert the hours worked by several part-time employees into the hours worked by an equivalent full-time employee (ideally the comparison is standardized for gender and industry sector)., per million inhabitants. According to this measure, the highest performers come from Europe, led by Denmark and followed by Switzerland, Iceland and Sweden. Among the other regions, Israel and the Republic of Korea rank at the top. In 2017, Denmark and Israel reported over 10,000 per million employed on R&D, while Switzerland, Iceland, Sweden and the Republic of Korea recorded figures surpassing 9,000. These statistics include not only researchers, but also R&D technical and supporting staff. The strongest rise in R&D employment was observed in developing economies, such as China, India, Brazil and Turkey. According to figures available for 50 countries, on average 40 per cent of the R&D workforce were women. Interestingly, developing economies registered higher percentages of female R&D staff than developed economies (UNESCO Institute for Statistics, 2020).
R&D services in international trade
Innovation is increasingly traded internationally. Global R&D services cover services associated with basic and applied research and experimental development, including activities in the physical and social sciences and the humanities , section 11.5). The definition used for international trade includes also testing and product development that may give rise to patents . exports expanded by an estimated 6.3 per cent annually, between 2012 and 2017, outpacing the average growth of total trade in services (2.8 per cent). In 2017, countries exported about US$170 billion worth of R&D services. Again, innovation exports and imports were concentrated on a small group of economies. The top-ten R&D exporters accounted for 75 per cent of the total. The United States of America was the main R&D services supplier on the international markets, followed by Germany and France (see table 2). Seven out of ten leading R&D services exporters also belonged to the top-ten R&D services importers. They were also part of the world leading recipients of charges for the use of intellectual property. Among developing economies, prominent exporters of R&D services include China, India, the Republic of Korea, Singapore, Brazil and Bahrain.
|Annual average growth of exports, 2012-2017, percentage||Imports |
|Ranking in Gross domestic expenditure on research and development,
Purchasing power parity US$
|United States of America||43||8.8||35||1|
Note: China belongs to leading R&D services exporters, according to estimates available for previous years. 2017 figures were not available.
Governments to keep environmental and social R&D investment afloat
R&D is financed by public and private funds. According to the OECD (2018), public spending on R&D has declined since 2012 in Organization for Economic Cooperation and Development member states, not only as a percentage of GDP, but also in proportion to total government expenditure. Instead, R&D is increasingly financed by corporations with a focus on product and process development. Most corporate R&D takes place in health and ICT sectors.
A study by the Cornell University et al. (2019) shows that R&D investment has lost momentum with each economic slowdown over the last two decades. At 2.9 per cent, growth in global output in 2019 was moderate rather than robust. In the face of the COVID-19 pandemic, obtaining financing for innovation and R&D investment from the corporate and public sector could prove challenging. Probably, R&D expenditure on health and ICT can escape the strong downturn, considering the importance of these sectors under the conditions of the pandemic. Amid expectations of scarcer funding, wide-ranging socially and environmentally beneficial projects would need special support by governments and international organizations.
- In this report, progress in target 9.2 is measured with reference to the base year 2005. This is in line with the practice applied in the monitoring of the Millennium Development Goals, where the baseline was set to the year 1990, thus ten years before the adoption of the Millennium Development Declaration (United Nations, 2005). The 2030 Agenda for Sustainable Development does not specify any base year for target 9.2.
- Official statistics for India, the Islamic Republic of Iran and Malaysia do not enable the calculation of comparable growth rates.
- SIDS based on the UNESCO country classification: http://www.unesco.org/new/en/natural-sciences/priority-areas/sids/resources/sids-list/
- CCSA (2020). How COVID-19 is changing the world: a statistical perspective. Available at https://unstats.un.org/unsd/ccsa/documents/covid19-report-ccsa.pdf (accessed 20 May 2020)
- Chenery HB (1960). Patterns of industrial growth. American Economic Review. 50(4):624–654.
- Cornell University, INSEAD and WIPO (2019). The Global Innovation Index 2019: Creating Healthy Lives—The Future of Medical Innovation. Available at https://www.wipo.int/edocs/pubdocs/en/wipo_pub_gii_2019.pdf (accessed 4 May 2020).
- European Commission (2010). Europe 2020: A Strategy for Smart, Sustainable and Inclusive Growth. European Commission, No. COM(2010) 2020.
- Eurostat (2020). Eurostat database. Available at https://ec.europa.eu/eurostat/data/database (accessed 25 May 2020).
- Fourastié J (1963). Le Grand Espoir Du XXe Siècle. Gallimard. Paris.
- Haraguchi N and Rezonja G (2010). Search of general patterns of manufacturing development. Development Policy and Strategic Research Branch Working Paper No. 02/2010. UNIDO.
- ILO (2020a). ILO Monitor: COVID-19 and the world of work. Second edition. Updated estimates and analysis. Available at https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/documents/briefingnote/wcms_740877.pdf (accessed 25 May 2020).
- ILO (2020b). ILOStat database. Available at https://www.ilo.org/ilostat (accessed 15 April 2020).
- Kuznets S (1957). Quantitative aspects of the economic growth of nations: II. Industrial distribution of national product and labor force. Economic Development and Cultural Change. 5(4):1–111.
- OECD (2011). Guide to Measuring the Information Society. Available at https://dx.doi.org/10.1787/9789264113541-en (accessed 27 May 2020).
- OECD (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development. The Measurement of Scientific, Technological and Innovation Activities. OECD Publishing. Paris.
- OECD (2018). OECD Science, Technology and Innovation Outlook 2018: Adapting to Technological and Societal Disruption. OECD Publishing. Paris.
- OECD (2020). OECD Statistical Database. Available at https://stats.oecd.org/ (accessed 6 June 2020).
- Refinitiv (2020). Eikon. Available at https://www.refinitiv.com/en/financial-data/economic-data (accessed 31 March 2020).
- UNCTAD (2020). UNCTADStat. See https://unctadstat.unctad.org/ (accessed 20 April 2020).
- UNECA (2018). Towards achieving the African Union’s recommendation of expenditure of 1% of GDP on research and development. ECA Policy Brief. ECA/18/004. Addis Ababa.
- UNESCO (2020). UNESCO List of Small Islands Developing States (SIDS). Available at http://www.unesco.org/new/en/natural-sciences/priority-areas/sids/resources/sids-list/ (accessed 28 April 2020).
- UNESCO Institute for Statistics (2020). UNESCO Institute for Statistics database. Available at http://uis.unesco.org/ (accessed 15 April 2020).
- UNIDO (2017). Industrial Development Report 2018, Demand for Manufacturing: Driving Inclusive and Sustainable Industrial Development. United Nations publication. Sales No. E.18.II.B.48. Vienna.
- UNIDO (2020). UNIDO databases. Available at https://stat.unido.org (accessed 4 May 2020).
- United Nations (2005). Millennium Development Goals. 2005 Progress Chart. Available at https://www.un.org/millenniumgoals/pdf/mdg2005progresschart.pdf (accessed 19 May 2020).
- United Nations (2008). International Standard Industrial Classification of All Economic Activities (ISIC). United Nations publication. Sales No. E.08.XVII.25. New York, NY.
- United Nations (2010). International Recommendations for the Index of Industrial Production 2010. Available at https://unstats.un.org/unsd/industry/Docs/F107_edited.pdf (accessed 26 May 2020).
- United Nations et al. (2012). Manual on Statistics of International Trade in Services 2010. United Nations publication. Sales No. E.10.XVII.14. Geneva.
- United Nations (2020). SDG indicators: Metadata repository. Available at https://unstats.un.org/sdgs/metadata/ (accessed 20 April 2020).
- United Nations, European Commission, IMF, OECD and World Bank (2009). System of National Accounts 2008. United Nations publication. Sales No. E.08.XVII.29. New York.
We are sorry that this post was not useful for you!
Let us improve this post!
Tell us how we can improve this post?