Science and technology (S&T) are used in many industries besides high-technology (HT) manufacturing and knowledge-intensive (KI) services. Service industries not classified as KI services—which include the wholesale and retail, restaurant and hotel, transportation and storage, and real estate industries—may incorporate advanced technology in their services or in the delivery of their services. Manufacturing industries not classified as HT by the Organisation for Economic Co-operation and Development (OECD) may use advanced manufacturing techniques, incorporate technologically advanced inputs in manufacture, and/or perform or rely on R&D. Industries not classified as either manufacturing or services—agriculture, construction, mining, and utility—also may incorporate recent S&T in their products and processes. For example, agriculture relies on breakthroughs in biotechnology, construction uses knowledge from materials science, mining depends on earth sciences, and utilities rely on advances in energy science.
In the non-KI services industries—real estate; restaurants and hotels; transport and storage; and wholesale and retail—patterns and trends of the four largest producers—the United States, the EU, Japan, and China—were similar to those in HT manufacturing and commercial KI services (table
Non-HT manufacturing industries are divided into three categories, as classified by the OECD: medium-high technology, medium-low technology, and low technology.* In these industries, patterns and trends were somewhat divergent from those in HT manufacturing (table
The positions of the United States, the EU, China, and Japan in nonmanufacturing and nonservices industries—agriculture, construction, and mining—are fairly similar to their positions in KTI industries (table
* Medium-high technology includes motor vehicle manufacturing and chemicals production, excluding pharmaceuticals; medium-low technology includes rubber and plastic production and basic metals; and low technology includes paper and food product production.
Topic | Data provider | Variables | Basis of classification | Coverage | Methodology |
---|---|---|---|---|---|
Knowledge-intensive (KI) service and high-technology (HT) manufacturing industries | IHS Global Insight, World Industry Service database (proprietary) | Production, value added | Industry basis using International Standard Industrial Classification | KI services—business, financial, communications, health, and education services HT manufacturing—aircraft and spacecraft, pharmaceuticals, office and computer equipment, communications, and scientific and measuring equipment | Uses data from national statistical offices in developed countries and some developing countries and estimates by IHS Global Insight for some developing countries |
Trade in commercial KI services | World Trade Organization | Exports and imports | Product basis using Extended Balance of Payments Services Classification | KI services—business, financial, communications, and royalties and fees | Uses data from national statistical offices, International Monetary Fund, and other sources |
Trade in HT goods | IHS Global Insight, World Trade Service database (proprietary) | Exports and imports | Product basis using Standard International Trade Classification | Aerospace, pharmaceuticals, office and computing equipment, communications equipment, and scientific and measuring instruments | Uses data from national statistical offices and estimates by IHS Global Insight |
U.S. trade in advanced-technology products | U.S. Census Bureau | Exports and imports | Product basis using Harmonized Commodity Description and Coding System, 10 technology areas classified by U.S. Census | Advanced materials, aerospace, biotechnology, electronics, flexible manufacturing, information and communications, life sciences, nuclear technology, optoelectronics, and weapons | Data collected from automated reporting by U.S. Customs |
Globalization of U.S. multinationals | U.S. Bureau of Economic Analysis (BEA) | Value added, employment, and inward and outward direct investment | Industry basis using North American Industrial Classification System (NAICS) | Commercial KI services—business, financial, communications HT manufacturing—aerospace, pharmaceuticals, office and computer equipment, communications, and scientific and measuring equipment | BEA annual surveys of U.S. multinationals and U.S. subsidiaries of non-U.S. multinationals |
U.S. industry innovation activities | National Science Foundation, Business R&D and Innovation Survey | Innovation activities | U.S. businesses with more than five employees | Industries classified on industry basis using NAICS | Survey of U.S.-located businesses with more than five employees using nationally representative sample |
U.S. Patent and Trademark Office (USPTO) patents | The Patent Board | Patent grants | Inventor country of origin, technology area as classified by The Patent Board | More than 400 U.S. patent classes, inventors classified according to country of origin and technology codes assigned to grant | Source of data is USPTO |
Triadic patent families | Organisation for Economic Co-operation and Development (OECD) | Patent applications | Inventor country of origin and selected technology area as classified by OECD | Broad technology areas as defined by OECD, inventors classified according to country of origin | Sources of data are USPTO, European Patent Office, and Japanese Patent Office |
Venture capital | Dow Jones VentureSource | Investment, technology area, country of investor origin | Technology areas as classified by Dow Jones classification system | Twenty-seven technology areas, investment classified by venture firms' country location | Data collected by analysts from public and private sources, such as public announcements of venture capital investment deals |
The data and indicators reported here permit the tracing and analysis of broad patterns and trends that shed light on the spread and shifting distribution of global knowledge- and technology-intensive (KTI) capabilities. The industry data used in this chapter derive from a proprietary IHS Global Insight database that assembles data from the United Nations (UN) and the Organisation for Economic Co-operation and Development to cover 70 countries in a consistent way. IHS estimates some missing data for some of the developing countries, including China. Data for developing countries may not be available on a timely basis or for specific industries.
The industry data follow the International Standard Industrial Classification, a UN system for classifying economic activities. Firms are classified according to their primary activity; a company that primarily manufactures pharmaceuticals, for example, but also operates a retail business would have all of its economic activity counted under pharmaceuticals.
Production is measured as value added. Value added is the amount contributed by an economic entity—country, industry, or firm—to the value of a good or service. It excludes purchases of domestic and imported supplies as well as inputs from other countries, industries, or firms.
Value added is measured in current dollars. For countries outside the United States, value added is recorded in the local currency and converted at the prevailing nominal exchange rate. Industry data are reported in current dollar terms because most KTI industries are globally traded and because the majority of international trade and foreign direct investment is dollar denominated. However, current dollars are an imperfect measure. Economic research has found a weak link between nominal exchange rates of countries' currencies that are globally traded and differences in their economic performance (Balke, Ma, and Wohar 2013). In addition, the exchange rates of some countries' currencies are not market determined.
Value added is also an imperfect measure. It is credited to countries or regions based on the reported location of the activity, but globalization and the fragmentation of supply chains mean that the precise location of an activity is often uncertain. Companies use different reporting and accounting conventions for crediting and allocating production performed by their subsidiaries in foreign countries. Moreover, the value added of a diversified company's activity is assigned to a single industry based on the industry that accounts for the largest share of the company's business. However, a company classified as manufacturing may include services, and a company classified in a service industry may include manufacturing or may directly serve a manufacturing company. For China and other developing countries, industry data may be estimated by IHS Global Insight or may be revised frequently because of rapid economic change or improvements in data collection by national statistical offices. Thus, value-added trends should be interpreted as broad and relatively internally consistent indicators of the changing distribution of where economic value is generated, and small differences and changes should not be overemphasized.
Indonesia's commercial knowledge-intensive services more than doubled between 2007 and 2012, expanding 40% faster than the average for all developing countries (figure
International comparisons of industry, trade, investment, and other global economic activities often use current dollars at market exchange rates. Most global economic activities are dollar denominated, which facilitates comparison. In addition, many economists believe that market exchange rates reflect, at least to some degree, differences in economic performance among various countries (Balke, Ma, and Wohar 2013:2).
However, fluctuations in exchange rates may reflect factors other than economic performance. Governments can and do take action to influence the level of their exchange rates, ranging from intervening in currency exchange markets so as to exercise almost complete control of rates to using macroeconomic policies and other mechanisms so as to exercise more limited and indirect influence on markets. In addition, factors such as political instability or the short-term effects of global financial events on a country's economy can cause currency fluctuations that are unrelated to enduring differences in national economic performance. Factors such as these mean that comparing economic data from different countries in current dollar terms can sometimes provide an inaccurate and misleading measure of a country's relative economic performance.
Between 2007 and 2012, during the global financial crisis, the worldwide recession, and the subsequent economic recovery, the exchange rates of the four largest economies—China, the EU member countries that use the euro (the Eurozone), Japan, and the United States—exhibited considerable fluctuations (figure
The substantial appreciation of the yen and yuan against the dollar from 2007 to 2012 made Japan's and China's positions in economic activities denominated in current U.S. dollars appear progressively stronger during this period. Denominated in local currency terms, however, their economic performance looked weaker. The disparity was particularly large for Japan. For example, the value added of Japan's high-technology manufacturing industries in current dollars exhibited a slight decline (4%) from 2007 to 2012 (figure
Australia's commercial KI services grew four times faster than the average of all developed countries between 2003 and 2012 (figure
Brazil's high-technology (HT) manufacturing industries grew more than twice as fast as the average for all developing countries, excluding China, between 2003 and 2012. Pharmaceuticals and aircraft and spacecraft led the growth of Brazil's HT industries (figure
India's pharmaceuticals industry, a globally competitive industry, has led the growth of its HT manufacturing industries, which quadrupled in value added between 2003 and 2012 (figure
Several signs point to an increase in U.S. manufacturing activity after years of decline. After falling continuously in the previous decade, employment in the U.S. manufacturing sector increased somewhat in 2011–12, coinciding with a rebound in this sector's output following the 2008–09 global recession.* According to press reports, several firms, including Apple, GE, and Lenovo, are building new manufacturing facilities in the United States (Booth 2013:1). Furthermore, some analysts and researchers predict a resurgence in U.S. manufacturing production, pointing to low transportation and energy costs, modest U.S. labor costs, and favorable currency exchange rates as factors conducive to manufacturing growth (PwC 2012:3).
However, other observers doubt that large-scale increases in employment will accompany increased U.S. manufacturing production. Many U.S. manufacturing industries are highly productive, which allows them to increase output substantially without increasing employment much. Although manufacturers in the United States and other high-income economies will continue to hire more high-skilled workers, manufacturing employment is likely to continue to decline over the next several decades due to further advances in productivity and global competitive pressures (McKinsey Global Institute 2012:4).
In interpreting recent trends in manufacturing production and employment, it is helpful to take into account several broader trends and patterns:
* Employment in the U.S. manufacturing sector increased by about 200,000 jobs in both 2011 and 2012, according to the U.S. Bureau of Labor Statistics' Current Employment Survey, http://www.bls.gov/ces/data.htm, accessed 10 June 2013.
Trade data are based on a classification of goods or services themselves. In the case of product trade, trade is assigned one product code according to the Harmonized Commodity Description and Coding System, or Harmonized System (HS).* The product classification of trade is fundamentally different from the industry classification used in the last section, which is based on the primary activity of the industry that produced a product and not on the characteristics of the product itself. Thus, the two classifications cannot be mapped onto each other. For example, an export classified as a computer service in the product-based system may be classified in the industrial classification as computer manufacturing because it originated from a firm in that industry.
Data on exports and imports represent the market value of products and services in international trade. Exports of products are assigned by the importing country's port of entry to a single country of origin. For goods manufactured in multiple countries, the country of origin is determined by where the product was “substantially transformed” into its final form.
The value of product trade entering or exiting a country's ports may include the value of components, inputs, or services classified in different product categories or originating from countries other than the country of origin. For example, China is credited with the full value (i.e., factory price plus shipping cost) of a smart phone when it is assembled in China, although made with components imported from other countries. In these data, countries whose firms provide high-value services such as design, marketing, and software development are typically not credited for these contributions.
* HS is a system for classifying goods traded internationally that was developed under the auspices of the Customs Cooperation Council. Beginning on 1 January 1989, HS numbers replaced schedules previously adhered to in more than 50 countries, including the United States. For more information, see http://www.census.gov/foreign-trade/guide/sec2.html#htsusa.
Trade in research and development services is part of U.S. trade in business services, a component of commercial KI services. In 2011, companies located in the U.S. exported $24 billion in these services and imported $22 billion, based on Bureau of Economic Analysis (BEA) statistics.* Most of this trade occurs between affiliated parties, that is, within multinational companies (MNCs) (appendix table
Details by regions and countries (available for total trade, not by affiliation) show that Europe is the top destination for U.S. R&D services exports, with a 64.9% share in 2011. For R&D services imports, Europe is also the largest trading partner but with a lower share, at 46.6% in 2011. The Asia-Pacific region was the second-largest destination for R&D services exports, receiving 15.9% of U.S. exports in these services. The region's share as a source of imports was higher, at 29.4% in 2011.
Data for earlier years were collected under the category “research, development, and testing (RDT) services” (appendix table
R&D and testing services imports from the Asia-Pacific region increased most notably from India (from $427 million in 2006 to $1.6 billion in 2010), China (from $92 million to $955 million) and Japan (from $550 million to $1.3 billion). This trend is consistent with increased R&D activities in these countries both overall (gross expenditures in R&D) and by affiliates of U.S. MNCs (see the “International Comparisons of R&D Performance” and “R&D by Multinational Companies” sections in chapter 4).
* Statistics for 2011 are from the Benchmark Survey of Transactions in Selected Services and Intellectual Property with Foreign Persons. See appendix table
The Organisation for Economic Co-operation and Development (OECD)/World Trade Organization (WTO) Trade in Value Added (TiVA) initiative is developing estimates of trade measured in value-added terms to complement conventional measures of trade. In a world where goods and services are often produced through global supply chains, value-added measures of international trade have two substantial advantages over conventional trade measures. First, they record the amount of global trade more accurately; they record value only once, in the country in which it is added. In contrast, conventional trade measures overstate the value of internationally traded goods and services, recording the entire (gross) value of an item every time it crosses a national border. Second, value-added measures produce better estimates of national contributions to the value of goods and services in international trade. In contrast, conventional trade measures attribute the entire (gross) value of the goods and services a country trades to that country, even if a portion of the value was produced by other countries in the supply chain. The OECD's estimate of the U.S. trade balance in iPhones shows that the United States has a much smaller estimated trade deficit with China, the location of final assembly and export of iPhones, and larger trade deficits with countries that supply inputs to the iPhone (table
OECD/WTO estimates of trade in value-added terms are derived from OECD country-level input-output tables. Input-output tables track the interrelationships among domestic industries and also between domestic industries and consumers—households, government, industry, and export customers. OECD/WTO built international input-output tables that link exports in one country to the purchasing industries or final-demand consumers in the importing country. The international input-output tables estimate trade among countries on an industry basis using coefficients derived from bilateral product and services trade data, which are not collected on an industry basis.
OECD/WTO estimates of trade in value-added terms assume that the share of imports in any product consumed directly as intermediate consumption or final demand (except imports) is the same for all users. This assumption is reasonable for developed countries, where there is little product differentiation between what is produced for export and what is produced for the domestic market. This assumption is probably less realistic for developing countries because the import content of exports is usually higher than the import content of products destined for domestic consumption.
The most recent version of the OECD/WTO database, released in May 2013, covers 58 economies (including all OECD countries, Brazil, China, India, Indonesia, Russia, and South Africa) and the years 1995, 2000, 2005, 2008, and 2009. Trade in value-added indicators and additional information are available at http://www.oecd.org/industry/ind/measuringtradeinvalue-addedanoecd-wtojointinitiative.htm.
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Science and Engineering Indicators 2014 Arlington, VA (NSB 14-01) | February 2014