Assessing the bioeconomy's contribution to evidence-based policy: A comparative analysis of value added measurements

Ronzon, Tévécia et al. Article Assessing the bioeconomy's contribution to evidencebased policy: A comparative analysis of value added measurements Bio-based and Applied Economics (BAE) Provided in Cooperation with: Firenze University Press Suggested Citation: Ronzon, Tévécia et al. (2024) : Assessing the bioeconomy's contribution to evidence-based policy: A comparative analysis of value added measurements, Bio-based and Applied Economics (BAE), ISSN 2280-6172, Firenze University Press, Florence, Vol. 13, Iss. 4, pp. 317-331, https://doi.org/10.36253/bae-14563 This Version is available at: https://hdl.handle.net/10419/321802 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Firenze University Press | www.fupress.com/bae Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 Citation: Ronzon, T., Gurria, P., Carus, M., Cingiz, K., El-Meligi, A., Hark, N., Iost, S., M’Barek, R., Philippidis, G., van Leeuwen, M., & Wesseler, J. (2024). Assessing the bioeconomy’s contribution to evidence-based policy: A comparative analysis of value added measurements. Bio-based and Applied Economics 13(4): 317-331. doi: 10.36253/bae-14563 Received: March 30, 2023 Accepted: June 11, 2024 Published: December 31, 2024 Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. Editor: Silvia Coderoni ORCID TR: 0000-0001-8554-627X PG: 0000-0002-0420-3273 KC: 0000-0002-8440-2677 AE-M: 0000-0001-7814-9954 SI: 0000-0001-5123-3822 RM: 0000-0002-3205-3938 GP: 0000-0003-1727-2240 MVN: 0000-0003-1902-4531 JW: 0000-0002-6009-8543 Short Communications Assessing the bioeconomy’s contribution to evidence-based policy: A comparative analysis of value added measurements Tévécia Ronzon1,2,*, Patricia Gurria2, Michael Carus3, Kutay Cingiz2, Andrea El-Meligi1, Nicolas Hark3, Susanne Iost4, Robert M’Barek1, George Philippidis5, Myrna van Leeuwen6, Justus Wesseler2 1 European Commission, Joint Research Centre (JRC), Seville, Spain 2 Agricultural Economics and Rural Policy Group, Wageningen University, The Netherlands 3 Nova-Institut GmbH, 50354 Hürth, Germany 4 Thünen Institute of International Forestry and Forest Economics, Hamburg, Germany 5 Agrifood and Technology Research Centre (CITA), Zaragoza, Spain 6 Wageningen Economic Research, International Policy, The Hague, The Netherlands *Corresponding author. E-mail: T[email protected]m Abstract. This paper reviews the main approaches found in the literature to measure the size of the European bioeconomy. The various estimations published might be confusing at first sight, reporting a value added of the European bioeconomy within the large range of EUR 881 billion to EUR 2.3 trillion. However, each approach is best suited to measuring a different aspect of the bioeconomy. Using the different approaches, we estimate that markets of bio-based products and energy generate EUR 730-790 billion of value added, the use of biomass within the European economy generates EUR 670 billion of value added, and the sourcing of core bioeconomy industries with goods and services generates EUR 270 billion of value added. There is no evidence of an increased use of biomass inputs in EU industries in substitution of fossil resources, nor of a decreasing dependence of traditional bioeconomy industries towards fossil resources over the period 2005-2015. Keywords: bioeconomy, value added, Europe, input-output tables, bio-based industries, methodologies. JEL code: Q57. 1. INTRODUCTION As defined in the European Commission’s bioeconomy strategy, the bioeconomy covers all sectors and systems that rely on biological resources, their functions and principles (European Commission, 2012, 2018). The bioeconomy promotes the transition to a sustainable economic model derived from the use of biomass and the application of natural sciences, knowledge, and technologies. Its relevance is well acknowledged by international organi- 318 Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 Tévécia Ronzon et al. zations such as the FAO (FAO, 2021; Gomez San Juan, Harnett, & Albinelli, 2022) and the OECD (OECD, 2018). The European Union (EU) has also stated its importance for the European economy in its bioeconomy strategy and action plan (European Commission, 2012, 2018), recently followed by Council conclusions on the opportunities of the bioeconomy in the light of current challenges with special emphasis on rural areas (Council of the European Union, 2023). Together with the development of bioeconomy strategies around the world, the need of tools for quantifying the bioeconomy and monitoring its development has become crucial. However, the bioeconomy is a complex concept, encompassing a broad range of economic activities and their associated workers and consumers, while being dependent on the planet’s ecological boundaries and biomass availability. Understanding and analysing such a multidisciplinary phenomenon requires implementing several theoretical and conceptual approaches, using a broad range of methodologies. From global (FAO, 2021), macro-regional (European Commission, 2022b), to national (Federal Ministry of Food and Agriculture (BMEL), 2014) and regional level (Junta de Andalucía, 2018), guidelines and monitoring systems are being developed and implemented. In the case of the EU, the indicators to measure the progress of the European bioeconomy are very broad and numerous (European Commission, 2022a; Mubareka et al., 2023). However, a smaller number of headline indicators is used by policymakers and stakeholders to analyse and report on the bioeconomy. Most prominently among those indicators features (gross) value added, which is the focus of the present study. The European Union’s statistical directorate general, EUROSTAT, does not (yet) provide statistics of a specific value-added indicator for the bioeconomy and all its sectors spanning a broad range from primary production (e.g., agriculture), via processing (e.g., wooden products) to services (e.g., restaurants). Here, a key scientific challenge relates to the separation of fossil and bio-based production to correctly delimit the bioeconomy (Ronzon, Piotrowski, M’Barek, & Carus, 2017). Over the last years different methodologies have been developed to fill this gap (for example on the EU: Cingiz, Gonzalez-Hermoso, Heijman, and Wesseler (2021); Iost et al. (2019); Iost and Weimar (2020); Kuosmanen et al. (2020); M’barek et al. (2014); Porc, Hark, Carus, and Carrez (2021); Ronzon, Iost, and Philippidis (2022a, 2022b); Wesseler and von Braun (2017)). However, these methodologies have not been consistently used in bioeconomy policy making for two reasons: (i) the calculation methods are difficult to understand by non-specialists, and (ii) the different methodologies yield very different estimates of the European bioeconomy’s size, which may appear confusing at first sight. The aim of this paper is to bring clarity on the estimates of the bioeconomy’s value added size across different methodologies already published, in order to optimize their use by policy makers and consequently contribute to more evidence-based bioeconomy policies. To do so, the paper clarifies what are the concepts measured by each methodology (section 2) and puts their respective results into perspective (section 3). Emphasis is made on pointing to the different aspects of the bioeconomy measured by the different methodologies and on illustrating how each of them can be mobilised to inform on specific policy questions. Finally, conclusions are remarked in the final section. 2. PRESENTATION OF THE DIFFERENT METHODOLOGIES 2.1. Overview Cingiz, Gonzalez-Hermoso, et al. (2021) give an overview of the different quantitative approaches for estimating the value added generated by bioeconomic activities from which four types of methodologies match monitoring requirements (i.e., methodologies based on statistical databases that are harmonized across EU Member States and updated over time). Each type is illustrated in this study by a particular publication that applies to all Member States of the EU (Cingiz, Gonzalez-Hermoso, et al., 2021; Cingiz, González Hermoso, Heijman, & Wesseler, 2021; Kuosmanen et al., 2020; Ronzon et al., 2022a, 2022b). All four methodologies are based on industry-level statistics for quantifying the contribution of industry p to the bioeconomy in terms of value added (Vp). The bioeconomy being a cross-sectorial concept, the size of its value added is thus the sum of the contribution of all industries represented by NACE1 codes in the European System of National Accounts that are indexed by p = 1,…,n. They comprise the industries that fully fall within the scope of the bioeconomy indexed by q = 1,…,l, the industries that partly fall within the scope of the bioeconomy indexed by r = l+1,…,m, and the industries that do not fall at all within the scope of the bioeconomy indexed by s = m+1,…,n.2 1 NACE is the French acronym for Economic Activities in the European Community. 2 We denote here the industries by letters p, q, r and s to differentiate with the original studies that use the same subscripts i, j, k with diverging definitions. 319 Assessing the bioeconomy’s contribution to evidence-based policy: A comparative analysis of value added measurements Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 The families of methodologies differ on three main aspects: (i) The set of industries q. All methodologies concur in considering the biomass producing industries fully part of the bioeconomy (i.e., agriculture, forestry and fishing). However, divergences occur on the additional industries that complete the set q within the full scope of industries considered (p), see Table 1. (ii) The level of the contribution of industries r to the total bioeconomy’s value added. Different quantification criteria are considered: the biomass content of products and energy produced or the bioeconomy relevance of the services delivered considering a given policy definition of bioeconomy (see section 2.2.1); the use of biomass; or the provision of inputs to industries q. (iii) The inclusion or exclusion of the industries providing inputs to industries q into the bioeconomy aggregate (p). The different approaches taken regarding points (ii) and (iii) provide distinct measures of the bioeconomy’s value added and inform on a variety of aspects of the bioeconomy. Measurement principles are clarified in sections 2.2 to 2.5 while measured aspects are presented in section 3. 2.2. The “output-based” approach 2.2.1. Approach The “output-based” approach quantifies the value added generated by an industry p in proportion to the biomass content of tangible (i.e., merchandise) outputs or to the bioeconomy relevance of intangible (i.e., services) outputs. The biomass content is calculated in dry matter content (Ronzon et al., 2022a). The ‘bioeconomy relevance’ criterion is derived from a policy definition of the bioeconomy. In the context of the EU Bioeconomy Strategy, it covers the services associated to a bio-based product (e.g., transport, trade, repair), the marketed ecosystem services (e.g., nature tourism), the generation of knowledge in bioeconomy fields (e.g., research and development in life sciences) or support to bio-based markets (e.g., market research, public administration) (Ronzon et al., 2022b). The output-based approach quantifies the value added of the bioeconomy (VBE_O) at a given point in time and space as: VBE_O = ∑q Vq + ∑r δr .Vr (1) with δr = biomass content share or bioeconomy relevance share of industry r (Figure 1). Vq and Vr are the value added of individual industries q and r (see Annex 1). In other terms, the total value added of the bioeconomy is the sum of the value added generated by those industries whose output is biomass (e.g., agriculture, forestry, fisheries, food and beverage manufacturing) or whose output is partially made of biomass (e.g. biobased textile industry, biochemical industry) or whose output is fully or partially bioeconomy relevant (e.g., food services, veterinary activity, research). Industries q=1,…,l comprise the biomass producing industries (A01, A02, A03), the manufacturing of food (C10) and beverage (C11), water supply, sewerage and management3 (E36-E38) for their full biomass content, as well as food and beverage service activities (I56) and veterinary activities (M75) for their bioeconomy relevance. Industries s=m+1,…,n comprise mining industries (B05-B09), the manufacturing of coke and petroleum products (C19), of mineral or metallic products (C23-C25), of electronic or electrical equipment (C26-C27), of machinery and motor vehicles (C28-C30, C33), the wholesale, retail trade and repair of motor vehicles (G45), the industries of information and communication (J59-J63), of financial, insurance and real estate activities (K64-K66, L68) and of management, employment, human health and social work activities (M70, N78, Q86-Q88). Industries r=l+1,…,m comprise all other NACE industries. 2.2.2. Data sources The output-based approach builds on a variety of data sources. Industry-level data on value added (Vq and Vr) are retrieved from the Eurostat Structural Business statistics (Eurostat, 2020a, 2020b, 2020c) and from Eurostat’s national accounts (Eurostat, 2020d) for the industries not represented in the former databases. Other Eurostat databases are mobilised for the computation of the biomass content share or of the bioeconomy relevance share δr (Ronzon et al., 2022a, 2022b). In addition to official data, the output-based approach relies on literature, market reports and expert insights for the estimation of the biomass content of the 875 bio-based products listed in the Eurostat database on the production of manufactured goods (Eurostat, 2021). As δr cannot be quantified with precision with available Eurostat data and expert knowledge for all industries r, a minimum and maximum threshold value of δr is determined that consequently generates a minimum and a maximum value of bio-based amount of Vr. 3 The dry matter content of water is considered 100% biomass (i.e., organic matter and micro-organisms). 320 Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 Tévécia Ronzon et al. Time series data of Vr are available from 2008 (the latest revision of the NACE classification), up to the most recent common year of data sources used, typically released with a time lag of two years. 2.2.3. Data interpretation This approach has been coined “policy-driven” in the sense that the bioeconomy relevance of industries in set p follows the concept of bioeconomy as defined in the EU bioeconomy strategy. Indeed, by focusing on the bioeconomy nature of industries’ outputs, the output-based approach provides lower and upper thresholds of domestic bio-based markets (min VBE_O - max VBE_O). Over time, market developments in the bioeconomy’s valued added, or of an individual bio-based industry’s value added, give insight on progress towards policy objectives of bio-based market uptake. Also, the difference between an industry’s bio-based output share δr attained in one country compared with that of another country, or compared with a 100% δr share, gives an indication of the remaining potential for bio-based market development. 2.3. The “input-based” approach 2.3.1. Approach The “input-based” approach quantifies the value added generated by an industry p in proportion to its bio-based input cost share. Among the different variants of input-based approaches published in the scientific literature (Efken, Dirksmeyer, Kreins, & Knecht, 2016; Heijman, 2016; Iost et al., 2019; Iost & Weimar, 2020; Kuosmanen et al., 2020; Meesters, van Dam, & Bos, 2013; Robert, Jonsson, Chudy, & Camia, 2020), only Kuosmanen et al. (2020) propose quantifications for the EU aggregate. Their methodology, also coined Fundamental Industry Level Model (FILM), is thus proposed here as a benchmark for the families of “input-based” approaches while variations from other input-based approaches are briefly discussed. The FILM input-based approach relies on the use of monetary flows of input-output tables (IOTs) for quantifying the value added of the bioeconomy (VBE_I) at a given point in time and space, such as: VBE_I = ∑q Vq + ∑r γr .Vr (2) with q being the biomass producing industries (agriculture, forestry and fishing) and γr being the biomass input cost share of industry r (Figure 1 and equation 3). γr = (3) Thus, Iqr is the cost of inputs from the set of biomass producing industries q to industry r; Ir’r is the cost of inputs from industry r’ to industry r with r’ = l+1,…,m; γr’ is the bio-based input cost share of industry r’ (equation 4); Mr is the cost of imported inputs to industry r; γMr is the bio-based input cost share of imported inputs to industry r; and Ipr is the cost of inputs from all industries to industry r. Note that intra-industry trade is captured when r’ = r. γr’ = (4) That is, the total value added of the bioeconomy is the value added generated from biomass producing activities, and from the use of biomass in all other activity sectors, including from imported products and services. 2.3.2. Data sources The FILM approach is systematic across all industries. The data source is the Eurostat IOTs (Eurostat, 2020e) released every five years with some Member States also providing annual estimates. This data does not offer a complete coverage of all EU Member States but does provide complete data for the EU28 aggregate. 2.3.3. Data interpretation By focusing on biomass input cost shares, the FILM methodology reports on the value added (VBE_I) generated from the use of biomass across all industries of an economy. The 5-year time step evolution of VBE_I gives insight on the increasing (decreasing) mobilisation of biomass – measured in value terms - by the economic system considered. The bio-based input cost share γr gives an indication of the degree of dependence of industry r towards non-renewable biological resources: the smaller γr is, the higher the dependence. The development of γr over time indicates progress towards the objective of substituting non-renewable resources with bio-based equivalents. 2.3.4. Variation to the FILM approach While the FILM approach is homogeneous across all NACE industries and employs data from a single source, Iost et al. (2019) and Iost and Weimar (2020) adapt the input-based approach to reflect the bioeconomy concept 321 Assessing the bioeconomy’s contribution to evidence-based policy: A comparative analysis of value added measurements Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 as defined in the previous German Bioeconomy Strategy (BMEL, 2014). First, the delineation of the bioeconomy’s industrial scope is restricted to a selection of bio-based industries that includes only a few bio-based services (i.e., joinery installation and erection of frames and constructional timber works, food and beverage service activities and research and experimental development on biotechnology). Second, several sources of German statistics are employed for they offer more precise information than IOTs (AGEB, 2015; DESTATIS, 2018). Third, per policy definition, the bio-based share of research industries (M7219) is not determined according to its biomass input cost share but rather from the share of personnel cost incurred in bioeconomy-related research disciplines on total costs (DESTATIS, 2016). Data on value added are retrieved from EUROSTAT’s structural business statistics. 2.4. The “Weighted Input-Output based” approach The “weighted Input-Output based” approach provides a middle ground quantification of the bioeconomy’s value added, taking into account the parameters δp and γp quantified by the output-based and the inputbased approaches (Figure 1). It quantifies the value added of the bioeconomy (VBE_W) at a given point in time and country as: VBE_W = ∑p θp.Vp (5) where θp is the weighted average of the input-based and output-based coefficients. With that purpose, the output bio-based share δp is weighed with the ratio of value added on gross output, and the input bio-based share γp is weighed with the ratio of total cost of inputs on gross output: θp = (δp.Vp + γp.Ip) / Op (6) The total value added of the bioeconomy is the value generated from the utilization of biomass and bio-based inputs, as well as their conversion into bioeconomy outputs through further processing. The data sources used are the same as those employed in the output-based and input-based approaches (see sections 2.2.2 and 2.3.2). 2.5. The “Upstream & Downstream” approach 2.5.1. Approach The “upstream & downstream” approach quantifies two different aspects of the bioeconomy (Figure 1, Cingiz, Gonzalez-Hermoso, et al. (2021)): – ∑r Dr, the “downstream effect” of the bioeconomy which corresponds to the value added size of the industries r that use bio-based inputs in proportion to their respective bio-based input cost share βr from industries q. q represents the biomass producing industries, the manufacture of food, beverage, tobacco, wood and paper products, and printing. – ∑r Ur, the “upstream effect” of the bioeconomy which corresponds to the value added size of the industries r that source industries q in proportion to their respective output cost share αr. In sum, the “upstream & downstream” approach quantifies the value added of the bioeconomy (VBE_UD) at a given point in time and space as4: VBE_UD = ∑q Vq + ∑r (Dr + Ur) (7) In other words, the total value added of the bioeconomy is the value generated by activities considered core to the bioeconomy (i.e., biomass producing, the manufacturing of food, beverage, tobacco products, wood products, paper and printed products) as well as the value generated by the use of the outputs of the former activities (downstream effect) and the use of inputs by them (upstream effect). Similarly to equation (2), Dr = βr .Vr (8) Ur = αr (1βr) Vr (9) where αr is the output cost share of industry r to industries q. αr is multiplied by (1βr) to avoid double counting with the downstream effect. αr = (10) where Fr denotes the final demand for industry r and Er denotes the exports of industry r. 2.5.2. Data sources Similarly to the FILM approach, the “upstream & downstream” approach is systematic across all industries. The two effects are computed from the OECD’s IOTs with annual data series from 2005 to 2015 for the 28 pre-Brexit EU Member States (OECD, 2021). EU28 data are calculated as the sum of IO matrix entries across the 28 countries. 4 Notations have been changed compared to Cingiz, GonzalezHermoso, et al. (2021) for the sake of harmonization across the various methodologies presented in the paper. 322 Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 Tévécia Ronzon et al. 2.5.3. Data interpretation Compared to the other three approaches, the “upstream & downstream” method adds information on how much the bioeconomy is integrated with the rest of the economy, in particular to non-bioeconomy sourcing industries. The downstream component ∑r Dr provides similar information as the input-based approach (see section 2.3.3). Additionally, the output cost share αr used for the quantification of the upstream component Ur illustrates the interconnection between industry r and the core bioeconomy industries q. The higher αr is, the larger is the sourcing role of industry r. Moreover, the development of the total upstream and downstream effects over time (∑r Ur and ∑r Dr) informs whether an increasing (decreasing) value creation from the use of renewable biological resources (∑r Dr) is concomitant or not with a growth of the economic size of bioeconomy sourcing industries (∑r Ur). Finally, the ratio of bioeconomy value added on GDP (VBE_UD/GDP) describes how much the bioeconomy is integrated into the whole economy. As a summary, Figure 1 graphically illustrates the concepts or flows quantified in the four approaches and their related equations. Table 1 compares the main parameters of the four approaches. 3. RESULTS AND DISCUSSION The four methodologies presented above yield very different estimates of the value added size of the EU bioeconomy in 2015, ranging from EUR 881 billion to EUR 2.3 trillion5 (Figure 2). Such a large range may be puzzling at first sight or may even confuse policy makers. In fact, differences in numbers reflect the different aspects of the bioeconomy captured by each approach. This section summarises the main results and illustrates how the specific aspects of each methodology can be mobilised to answer relevant policy questions. 3.1. Aggregated results and complementary information on differences In order to provide an overview of main results, we focus hereafter on the comparison of the aggregates of pri5 The EU 2015 is the only common scope of the approaches commented at section 3. The output-based approach from Ronzon et al. (2022a and 2022b) provides data at country and EU level from 2008 to 2019, The input based approach published by Kuosmanen et al. (2020) provides data for the EU and the year 2015. The upstream and downstream approach published by Cingiz et al. (2021a) provides country and EU level data from 2005 to 2019. Figure 1. Four methodological approaches for determining the bio-based share of industry p. Note: I stands for Input, O for Output and V for Value added, all three are measured in monetary terms. 323 Assessing the bioeconomy’s contribution to evidence-based policy: A comparative analysis of value added measurements Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 mary, secondary and tertiary economic sectors6 as illustrated by Figure 2. For each of these aggregates, we highlight the reasons leading to differences in value added estimates. The weighted input-output approach is not commented though, as it always provides an intermediate quantification between the input-based and the output-based approaches. All quantifications from the “upstream and downstream” approach are taken from the online database published by Cingiz, González Hermoso, et al. (2021)7. Estimations of value added for the bioeconomy industries of the primary sector are convergent (EUR 207 to 216 billion) in spite of methodological differences and slight variations from the different data sources employed by each approach. The output-based approach only considers those industries that produce biomass (EUR 216 billion) while the other three approaches also consider a proportion of the bioeconomy value added coming from the mining industries. From an inputbased perspective, EUR 1 billion of value added is generated from the use of biological material in mining activities such as for bioleaching. Moreover, the upstream effect Ur calculated in the “upstream and downstream” approach reveals that EUR 1.2 billion of value added are generated from the sourcing of core bioeconomy industries q by mining industries. 6 The primary sector refers to NACE sections A and B (biomass production and mining and carrying), the secondary sector to NACE C to F (manufacturing), and the tertiary sector to NACE G to T (services). 7 Although the methodological comments exposed in section 2.5 were derived from Cingiz, Gonzalez-Hermoso, et al. (2021). The value added of the bioeconomy industries operating in the secondary sector differs more from one approach to the other than in the case of primary sector industries: EUR 299 billion (input-based approach) to EUR 573 billion (output-based approach). The biomass input cost share γr (input-based approach) is systematically smaller than the biomass content δr of the outputs of the manufacturing industries (output-based approach), except for those industries s considered non bio-based in the output-based approach (γr ranging between 0.6% and 2.5%, Table 2). As a matter of example, only 55% of the inputs of the manufacturing of food, beverage and tobacco are bio-based inputs while that Table 1. Summary comparison of the four approaches introduced at sections 2.2 to 2.5. Approach “output-based” “input-based” (FILM) “weighted Input-Output” “upstream & downstream” Quantification criteria Biomass content of tangible outputs, bioeconomy relevance of intangible outputs Biomass inputs (biomass input cost share) See the two previous columns Biomass inputs (biomass input cost share) and sourcing of industries q (output cost share) Equations VBE_O = ∑q Vq + ∑r δr Vr Equation (1) VBE_I = ∑q Vq + ∑r γr Vr Equation (2) VBE_W = ∑p θp Vp with θp = (δp Vp + γp Ip) / Op Equations (5) and (6) VBE_UD = ∑q Vq + ∑r (Dr + Ur) Equation (7) Industries q (NACE codes) A01-A03, C10-C12, E36, I56, M75 A01-A03 A01-A03 A01-A03, C10-C12, C16-C18 Industries s (NACE codes) B05-B09, C19, C23-C30, C33, G45, K64-K66, L68, M70, N78, Q86-Q88. None None None Data sources Expert knowledge and many Eurostat sources Eurostat’s IOTs See the two previous columns OECD’s IOTs Interpretation of the results Bio-based market size Use of biomass Middle ground perspective between the previous two columns Use of bio-based inputs and integration to the wider economy - 500 1.000 1.500 2.000 Output Input Up- & Downstream Weighted InputOutput Tertiary sectors (max) Tertiary sectors (min) Secondary sectors (max) Secondary sectors (min) Primary sectors Figure 2. Estimation of the value added size of primary, secondary and tertiary activities of the EU28 bioeconomy according to the four quantitative approaches presented in the study 324 Bio-based and Applied Economics 13(4): 317-331, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14563 Tévécia Ronzon et al. industry generates fully bio-based outputs (Table 2). The proportion (αr (1βr)) of outputs that secondary sector’s industries sell to bioeconomy industries q ranges from 0.3% to 5.3%. The tertiary sector shows a high divergence in terms of value added size estimates from one approach to the other: EUR 370 billion (input-based approach) to EUR 1,488 billion (output-based approach). The four-fold difference is due to relatively small biomass input cost shares (γr = 1-5%, except for accommodation and food services where γr = 35%) compared with high biomass content or bioeconomy relevance of tertiary outputs (maximum δr = 12-100% in eight out of fourteen tertiary industries, Table 2). While the approaches based on IOTs (input and “up and downstream” approaches) are systematic and precise, the output-based approach suffers from both a lack of clarity about the definition of a bioeconomy service and a lack of informative data Table 2. Output bio-based shares (a), biomass input cost shares (b), combined upstream and downstream shares (c) and weighted InputOutput shares (d) at the sectorial level and for the EU28 in 2015. nace (a) min – max (b) (c) (d) min– max A01_A03 Agriculture, forestry, fishing 100% 100% 100% 100.0% 100% 100% B05_B09 Mining and quarrying 0.0% 0.0% 1.4% 3.0% 0.6% 0.6% C10_C12 Food, beverages and tobacco products 100% 100% 54.8% 100.0% 66.4% 66.4% C13_C15 Textiles, wearing apparel and leather products 35.6% 46.5% 40.9% 6.0% 38.4% 42.8% C16 Products of wood and cork 99.7% 99.7% 45.7% 100.0% 61.7% 61.7% C17_C18 Paper products and printing 60.8% 98.9% 30.7% 100.0% 37.3% 53.2% C19 Coke and refined petroleum products 0.0% 0.0% 0.6% 3.7% 0.5% 0.5% C20_C21 Chemicals and pharmaceuticals 25.6% 27.1% 4.3% 8.4% 12.1% 12.6% C22 Rubber and plastics products 3.3% 3.9% 4.6% 9.1% 4.1% 4.4% C23 Other non-metallic mineral products 0.0% 0.8% 2.5% 5.5% 1.6% 1.9% C24 Basic metals 0.0% 0.0% 0.9% 1.5% 0.7% 0.7% C25 Fabricated metal products 0.0% 0.0% 1.5% 4.4% 0.9% 0.9% C26 Computer, electronic and optical equipment 0.0% 0.0% 1.4% 1.7% 0.9% 0.9% C27 Electrical equipment 0.0% 0.0% 1.6% 2.1% 1.0% 1.0% C28 Machinery and equipment, nec 0.0% 0.0% 1.1% 2.7% 0.7% 0.7% C29 Motor vehicles, trailers and semi-trailers 0.0% 0.0% 1.5% 1.2% 1.1% 1.1% C30 Other transport equipment 0.0% 0.0% 1.5% 1.4% 1.1% 1.1% C31_C33 Manufacturing nec; repair and installation of machinery and equipment 8.8% 17.8% 8.3% 9.8% 8.4% 11.3% D35_E39 Electricity, gas, water supply, sewerage, waste and remediation services 24.0% 25.4% 1.3% 5.6% 10.2% 10.6% FConstruction 5.3% 5.6% 3.4% 4.4% 3.9% 4.0% G45_G47 Wholesale and retail trade; repair of motor vehicles 24.8% 39.8% 3.7% 11.0% 15.0% 23.0% H49_H53 Transportation and storage 20.1% 32.2% 0.9% 3.9% 8.9% 14.0% I55_I56 Accommodation and food service activities 76.5% 76.5% 34.7% 34.3% 57.7% 56.4% J58_J60 Publishing, audiovisual and broadcasting activities 0.0% 32.1% 4.6% 12.3% 2.4% 19.1% J61 Telecommunications 0.0% 0.0% 0.9% 2.1% 0.5% 0.5% J62_J63 IT and other information services 0.0% 0.0% 0.9% 2.7% 0.5% 0.5% K64_K66 Financial and insurance activities 0.0% 0.0% 0.6% 3.3% 0.3% 0.3% L68A Real estate activities 0.0% 0.0% 0.9% 2.2% 0.2% 0.2% M69_N82 Professional, scientific and technical activities, administrative and support services 4.0% 11.8% 2.1% 4.9% 2.0% 9.8% O84 Public administration and defence; compulsory social security 10.5% 15.9% 2.6% 4.7% 0.9% 11.5% P85 Education 2.2% 4.9% 4.3% 6.7% 0.9% 3.5% Q86_Q88 Human health and social work activities 0.0% 0.0% 5.4% 5.6% 1.8% 1.8% R90_S96 Arts, entertainment and recreation and other service activities 0.2% 47.1% 3.8% 6.9% 1.6% 27.1% T97_T98 Activities of households as employers 0.0% 100.0%  0.0% 0.0% 0.0% Sources: Cingiz, González Hermoso, et al. 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