National Academies Press: OpenBook

Safeguarding the Bioeconomy (2020)

Chapter: Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture)

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Suggested Citation:"Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture)." National Academies of Sciences, Engineering, and Medicine. 2020. Safeguarding the Bioeconomy. Washington, DC: The National Academies Press. doi: 10.17226/25525.
Page 93
Suggested Citation:"Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture)." National Academies of Sciences, Engineering, and Medicine. 2020. Safeguarding the Bioeconomy. Washington, DC: The National Academies Press. doi: 10.17226/25525.
Page 94
Suggested Citation:"Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture)." National Academies of Sciences, Engineering, and Medicine. 2020. Safeguarding the Bioeconomy. Washington, DC: The National Academies Press. doi: 10.17226/25525.
Page 95
Suggested Citation:"Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture)." National Academies of Sciences, Engineering, and Medicine. 2020. Safeguarding the Bioeconomy. Washington, DC: The National Academies Press. doi: 10.17226/25525.
Page 96
Suggested Citation:"Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture)." National Academies of Sciences, Engineering, and Medicine. 2020. Safeguarding the Bioeconomy. Washington, DC: The National Academies Press. doi: 10.17226/25525.
Page 97

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Annex 3-1 Studies of the Industrial Bioeconomy (Including Agriculture) OVERVIEW OF THE LITERATURE Several studies have taken a sector-based approach to defining and measuring the contribution of the industrial bioeconomy to a country’s or region’s overall economy. In these studies, economic activity within the bioeconomy is defined in terms of a country’s system of national accounts. This may be in terms of North American Industry Classification System (NAICS) codes in the United States and Canada, the European Union’s (EU’s) NACE (Nomenclature générale des Activités économiques dans les Communautés Européennes) codes, or United Nations (UN) input-output tables. One goal of these studies is often to measure the size of the bioeconomy in terms of the section’s employment or gross value added relative to the larger economy. Another is to apply input-output modeling techniques to assess how sectors included in the bioeconomy interact with other sectors in the broader economy. However, a challenge is that “bioeconomy cuts across sectors and therefore cannot be treated as a traditional sector in economics” (Wesseler and von Braun, 2017). Applied practitioners follow a two-step process. First, certain sectors are considered wholly within the bioeconomy (this approach may encode entire sectors within NAICS or NACE codes). Next, for remaining sectors, researchers assume either that all activities are considered outside the bioeconomy or that some are considered to have some subactivities within the bioeconomy, while others are designated as outside. For example, steel manufacturing would lie completely outside the bioeconomy, while electricity generation comprises biomass-generated electricity (within) and other generation (without). A key problem is that NAICS and NACE codes often do not make a fine enough distinction within industries to separate components considered inside and outside of the bioeconomy definition. A common approach to addressing this limitation is to conduct industry surveys to determine which type of production within a sector may be “bio-based.” For example, plastics manufacturers may be surveyed to determine how much of their employment and production is devoted to bioplastics. This subset of bioplastic production would then be included as part of the bioeconomy. EU economic policies are increasingly focused on a “circular economy,” in which use of resources is maximized and waste is minimized, instead of a “linear economy,” in which “take,” “make,” and “dispose” are primary elements. A circular economy employs a regenerative approach, including design for longevity, reuse, repair, and recycling as foundational elements. Not surprisingly, the term “circular bioeconomy” has gained traction in the European Union, and policies are being developed to maximize the use of bio-based resources regarded as wastes (such as agricultural and forestry residues), with the long-term objective of gradually replacing fossil-based with bio-based production (Philp, 2018). Studies vary greatly in what sectors and activities within sectors are considered part of the bioeconomy, with distinct differences in particular between studies on North America and those on EU countries and Japan. EU studies tend to use relatively broad definitions, including sectors in their entirety that produce or fundamentally rely on biologically produced materials. For example, not only are primary sectors (agriculture, forestry, fisheries) included, but also food, beverage, tobacco, and wood products manufacturing. For other sectors, such as chemical manufacturing, researchers frequently conduct surveys to divide sectoral activity into bio-based and other categories. In the United States and Canada, there has been a greater emphasis on applications of biotechnology, biological research and development (R&D), and substitution of bio-based for fossil fuel–based products in manufacturing. Primary sectors Prepublication Copy 93

Safeguarding the Bioeconomy (agriculture, forestry, and fisheries) are treated largely as outside the bioeconomy. Major exceptions are genetically modified (GM) crops and crops or trees grown specifically for energy production. Lier and colleagues (2018) conducted a survey of EU government ministries tasked with monitoring bioeconomy performance or developing bioeconomy strategies. The survey asked respondents which NACE code activities were completely, partly, or not included in the bioeconomy sector. European ministries included primary sectors along with food, paper, and wood product manufacturing entirely. Only one study (by Ehrenfeld and Kropfhäußer, 2017) followed the approach of North American analyses, examining biological science R&D as part of the bioeconomy. In general, North American studies do not include entire NAICS sectors in their definitions of bioeconomy sectors. They often rely on survey-based data collection within traditional sectors, focusing on novel technology applications to traditional sectors (e.g., GM crops), substitution of bio-based for fossil fuel–based production (e.g., bioplastics), and biological R&D. In response, Carlson (2016) proposes three key additions to the NAICS system to improve its utility in delineating the size of the biotechnology sector (see Box 3-3 in the chapter text). Another approach input-output modelers have taken is to impute the contribution of the bioeconomy to other sectors. Researchers assume that the contribution of the bioeconomy to value added in a sector is proportional to the share of biologically produced inputs in that sector’s production costs. So, for example, there would be virtually no bioeconomy value added derived from the steel sector, but a relatively large contribution from sectors using crop, fiber, and timber products. Efken and colleagues (2016) thus have a definition of the bioeconomy that extends to the retail grocery and restaurant sectors, arguing that “these industries only exist due to the fact that they process (picking and packing, preparing, offering) biological resources.” The imputation approach avoids the need to conduct surveys of industries within NAICS or NACE codes. Instead, it relies on basic data from national input-output tables, with sectoral data reported similarly across countries. Using such an all-encompassing definition, however, means that quite traditional primary sectors, processing sectors, and service sectors that repackage and serve biologically derived goods account for the bulk of employment and value added attributable to the bioeconomy. This definition is far removed from one that focuses on novel biological technologies or even bio-based substitution for fossil fuel–based production. The estimates of the bioeconomy reported in Chapter 3 rely heavily on the studies of Carlson (2016, 2019) and Daystar et al. (2018). Therefore, those studies are reviewed in detail below. CARLSON (2016, 2019) Carlson (2016, 2019) collected data on gross sales revenues from industrial bio-based activities. While his approach has the advantage of relying on data that “are publicly available at no cost or obtainable with minimal registration from sources on the Internet,” some problems are entailed in comparing gross sales with the gross domestic product (GDP). 42 That said, Carlson’s work, within its circumscribed boundary, is the most definitive to date. According to Carlson’s estimates, U.S. GM organisms revenues were 2 percent of U.S. GDP in 2017 (see Annex Figure 3-1), about the same as 5 years earlier but up substantially since 2000, when the sector accounted for just 0.6 percent of GDP (Carlson 2019; 2016, Table S1). Industrial biotechnology was the fastest-growing subcomponent of these estimates prior to 2012, and despite an unchanged ratio to 42 Gross sales are not the same as value added. Value added is the difference between gross output (sales) and intermediate inputs and represents the value of labor and capital used in producing gross output. The sum of value added across all industries is equal to GDP for the economy. In the United States, total gross sales are 1.7 times GDP. Carlson (2016) acknowledges the limitations of using gross sales, noting this approach “may include some double counting.” In later work, Carlson (2019) attempts to correct this limitation; for example, corn used to produce biofuels is not double-counted. However, double-counting elsewhere in his estimates is still a problem. On the other hand, as noted in the main text of Chapter 3, studies that infer total economy effects via interindustry linkages produce larger impacts relative to isolating value added alone, and though imprecise, estimates based on gross output are closer to these broader-based estimates. 94 Prepublication Copy

Frameworks for Measuring the Value of the U.S. Bioeconomy GDP since then, within industrial biotechnology, revenues from biopharma ingredients have gained ground in relative terms (see Annex Figure 3-2). ANNEX FIGURE 3-1 Biotechnology revenues, 2017. NOTE: The cost of corn was removed from the biofuels revenues to avoid double-count in the crops segment. SOURCE: Bioeconomy Dashboard, available at (accessed April 10, 2019). ANNEX FIGURE 3-2 Industrial biotechnology revenues by component. NOTE: The cost of corn was removed from the biofuels revenues to avoid double-count in the crops segment. SOURCE: Bioeconomy Dashboard, available at (accessed April 10, 2019). Prepublication Copy 95

Safeguarding the Bioeconomy Emerging R&D services are small in Carlson’s estimates, about $2 billion. Official statistics from the U.S. Census Bureau for the biotechnology segment of the R&D services industry suggest that revenues in 2012 were much larger ($16.9 billion), but they were similar in that they reflect little evidence of growth. In the U.S. Census Bureau statistics, revenues from R&D biotechnology services in 2012 were down slightly from the level reported in 2007 ($17.4 billion). This decline contrasts with R&D service revenues in other life sciences, which were $40.0 billion in 2012, up from $26.2 billion 5 years earlier. It is possible that genomics companies are in the latter category, or that a company such as Illumina, which sells sequencing machines as well as genomic services, is somewhere else entirely. The figures quoted are details from the 2012 Economic Census; detailed results from the 2017 economic census are not yet available. Annual product-level figures from the Census Bureau’s Services Annual Survey do not report data for R&D services, much less components by type of R&D service. Sales by R&D-performing firms within the R&D services industry are reviewed in the main text of Chapter 3. 43 The patterns in those data compare favorably with the comprehensive figures from the 2007 and 2012 economic censuses and with Carlson’s estimates, suggesting the utility of a broader regular collection of the more timely annual revenue data for bioeconomy firms in the services industries. The National Science Foundation’s (NSF’s) data on sales are of course smaller than the U.S. Census Bureau’s revenue data because not all firms in the R&D services industry conduct scientific R&D; the NSF data are 60 percent of U.S. Census Bureau revenues for biotechnology and 75 percent of revenues for the other life sciences segment in 2012. The downtrend in sales by R&D-performing firms in the biotechnology R&D services industry and increase in the other category of R&D services (which includes other physical sciences along with other life sciences) are evident in both surveys. 44 Carlson’s estimates for “biopharma ingredients,” while at a lower level because of the absence of manufacturers’ markup, exhibit growth similar to that for sales by R&D-performing firms in biopharma. This result underscores the utility of Carlson’s recommendation to segment product revenue data for the pharmaceutical industry along biotechnology/bioproduct lines. Industrial biotechnology revenues in the Carlson system reflect business-to-business transactions and therefore understate the impact of biotechnology, because consumer bio-based products (e.g., replacements for plastic wraps, bio-based ink pens, personal genetic histories) are not necessarily captured. Consumer bio-based products are one of the drivers of the synthetic biology startup business segment of the bioeconomy discussed in the chapter main text. No studies or industry estimates assign a revenue figure to the consumer-driven portion of this activity, despite ample evidence of the importance of doing so. Consumer-oriented genomics companies (e.g., 23andMe), along with bio-based consumer food companies (e.g., Impossible Foods), are becoming household names today. DAYSTAR ET AL. (2018) The U.S. Department of Agriculture (USDA) commissioned the Daystar et al. (2018) report, the fourth in a series of reports tracking the impact of the bio-based product industry on the U.S. economy. The sectors included in this report are • agriculture and forestry, • bio-based chemicals, • bioplastic bottles and packaging, • biorefining (food), • enzymes, 43 Data available for download at 44 Note also that the share of biotech revenues in 2012 by class of customer did not change materially between the two census years; that is, revenue from governments and nonprofits accounted for 10 percent of the total in each year, which suggests that the flagging performance of this segment is market driven. 96 Prepublication Copy

Frameworks for Measuring the Value of the U.S. Bioeconomy • forest products, and • textiles. The report specifically excludes the energy, livestock, feed, and pharmaceutical sectors. Daystar and colleagues (2018) conducted an extensive input-output modeling exercise to trace bio-based spending through the broader U.S. economy, including calculating economic multiplier effects. The report also examines environmental benefits; the economic impacts of bio-based exports; and areas in which the use or manufacturing of bio-based products could be more effective, including identifying technical and economic obstacles and recommending how those obstacles could be overcome. In their analysis of environmental benefits, the authors endeavor to quantify how the production and use of bio-based products reduces greenhouse gas (GHG) emissions via displacement of petroleum- based products. They estimate that the petroleum saved by a 100 percent shift to bio-based products (in the industries considered) would amount to as much as 9.4 million barrels of oil, based on 2016 data. In terms of reductions in GHG emissions, they estimate the reduction attributable to the bio-based products industry to be as much as 12.7 million metric tons of carbon dioxide (CO2) equivalent in 2016. The strength of this study is in its methodology and its detailed coverage of certain bio-based chemicals, enzymes, and biorefining of food. These areas encompass a complex and detailed set of products and processes that are difficult to identify in readily available data. For example, an area unearthed in the report’s data is enzymes, specifically “other enzymes” identified as produced by the NAICS 5 Digit Industry 32519—Other Basic Organic Chemical Manufacturing. This industry comprises establishments engaged primarily in manufacturing basic organic chemicals (except petrochemicals, industrial gases, and synthetic dyes and pigments) and includes enzyme proteins (i.e., basic synthetic chemicals), except those for pharmaceutical use. In Daystar and colleagues’(2018) report, total enzymes also include biologics (NAICS 325414). The report estimates that total value added by the two enzyme subsectors rose dramatically in 2016, and that the combined type II multiplier for these subsectors is very large at 4.4 (see the stacked bar to the far right in Annex Figure 3-3). ANNEX FIGURE 3-3 Enzymes production: contribution to employment and value added, 2013, 2014, and 2016. NOTE: “Direct” is enzyme industry value added; “Spillover” accounts for interindustry linkages (indirect effects), as well as induced effects via linkages to final demand. SOURCE: Daystar et al., 2018, p. 43. Prepublication Copy 97

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Research and innovation in the life sciences is driving rapid growth in agriculture, biomedical science, information science and computing, energy, and other sectors of the U.S. economy. This economic activity, conceptually referred to as the bioeconomy, presents many opportunities to create jobs, improve the quality of life, and continue to drive economic growth. While the United States has been a leader in advancements in the biological sciences, other countries are also actively investing in and expanding their capabilities in this area. Maintaining competitiveness in the bioeconomy is key to maintaining the economic health and security of the United States and other nations.

Safeguarding the Bioeconomy evaluates preexisting and potential approaches for assessing the value of the bioeconomy and identifies intangible assets not sufficiently captured or that are missing from U.S. assessments. This study considers strategies for safeguarding and sustaining the economic activity driven by research and innovation in the life sciences. It also presents ideas for horizon scanning mechanisms to identify new technologies, markets, and data sources that have the potential to drive future development of the bioeconomy.

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