Bio-based and Applied Economics BAE Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 Copyright: © 2023 Tetere, V., Peerlings, J., Dries, L. Open access, article published by Firenze University Press under CC-BY-4.0 License. Firenze University Press | www.fupress.com/bae Citation: Tetere, V., Peerlings, J., Dries, L. (2023). The forest-based bioec- onomy in Latvia: economic and envi- ronmental importance. Bio-based and Applied Economics 12(4): 323-331. doi: 10.36253/bae-13868 Received: October 18, 2022 Accepted: October 21, 2023 Published: December 31, 2023 Data Availability Statement: All rel- evant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. Editor: Fabio Bartolini ORCID VT: 0000-0002-4821-4855 JP: 0000-0002-8984-6226 LS: 0000-0002-1061-1441 The forest-based bioeconomy in Latvia: economic and environmental importance Vineta Tetere1,2,*, Jack Peerlings1, Liesbeth Dries1 1 Wageningen University, the Netherlands, Hollandseweg 1, Wageningen, 6706 KN 2 Latvia University of Life Sciences and Technologies, Latvia, Svetes 18, Jelgava, LV-3001 *Corresponding author. E-mail: vineta.tetere@wur.nl Abstract. The bioeconomy is considered a means to achieving a climate-neutral econ- omy as aimed for in the EU Green Deal. For Latvia, the forest-based bioeconomy has the potential to contribute to this aim. An operational definition of the forest-based bioeconomy is needed to calculate its size. This research aims to provide such a defi- nition and to determine the contribution of the forest-based bioeconomy to GDP, employment, and greenhouse gas emissions. The direct and indirect contribution of the forest-based bioeconomy to economic indicators and climate change is identified using an input-output model. The results of the model show that the forest-based bio- economy contributes 6.4% to GDP and 6.6% to total employment in Latvia. The con- tribution to greenhouse gas emissions is 4.9%. Furthermore, if CO2 sequestration is included, the forest-based bioeconomy becomes climate neutral. Keywords: forestry, input-output model, value added, employment, greenhouse gas emissions. JEL Codes: C67, E01, Q23. 1. INTRODUCTION A strong bioeconomy is a priority in recent EU policies, such as the Green Deal and the Bioeconomy Strategy, that strive towards a greener and more resource-efficient economy in the long run (EC, 2012, 2010, n.d.b ). The bioeconomy comprises those parts of the economy that use renewa- ble biological resources from the land and sea – such as crops, forests, fish, animals, and microorganisms - to produce food, materials, and energy (EC, n.d.a). Major societal challenges such as climate change call for a sustain- ability transition away from a fossil-based society toward a bioeconomy, in which energy and manufacturing processes are based on sustainable bio- logical resources (Ronzon et al., 2015; Siebert et al., 2018). In this way, the bioeconomy contributes to the goals of the Green Deal to transform the EU into a modern, resource-efficient, and competitive economy, by reducing the emissions of greenhouse gases, and by decoupling economic growth from resource use (EC, n.d.b). Moreover, by promoting circular and sustainable production systems, the bioeconomy has the potential to contribute to all https://doi.org/10.36253/bae-13868 http://www.fupress.com/bae https://doi.org/10.36253/bae-13868 https://orcid.org/0000-0002-4821-4855 https://orcid.org/0000-0002-8984-6226 https://orcid.org/0000-0002-1061-1441 mailto:vineta.tetere@wur.nl 324 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 Vineta Tetere, Jack Peerlings, Liesbeth Dries dimensions and objectives of the European Green Deal (EC, 2020). This focus on the potential of the bioeconomy in EU policy narratives, makes it essential to monitor the bioeconomy and to understand its driving forces. An important step in this is to measure the contribution of the bioeconomy and its dimensions to the total economy of countries. There are ongoing efforts to measure this contribution. However, Bracco et al. (2018) point out that these efforts focus mainly on the economic impor- tance of the bioeconomy in terms of value added and employment, whereas environmental aspects such as climate change mitigation are often ignored. An excep- tion is Lazorcakova et al. (2022) who used input-output analysis to quantify economic as well as environmental indicators to measure the bioeconomy in the Visegrad countries. Despite studies on the economic importance of the bioeconomy, for many countries and subsectors of the bioeconomy, this information is limited or still miss- ing (Wesseler & von Braun, 2017). This is especially true for the forest-based bioeconomy, which encompasses the entire forest value chain, from the management and use of natural resources to the delivery of products and services (Ladu et al., 2020). Lovrić, Lovrić, and Mavsar (2020) observed a high centralization of forest-based bio- economy research in a few countries and organizations from North-Western Europe, while the Baltic countries and the countries in Central-Eastern Europe are not adequately represented. Current research contributes to closing this knowledge gap by measuring the forest- based bioeconomy (FBB) in Latvia. The focus on the for- estry sector is especially relevant for Latvia, where the forest area covers more than 50% of the total territory. This paper aims to determine the economic and environmental contribution of the FBB to the total per- formance of the economy in Latvia. However, measur- ing the FBB is not trivial, as there is no unique defini- tion nor set of indicators, no uniform methodology for the assessment of the bioeconomy, and limited data available, especially for partially biobased sectors (Ron- zon et al. 2017; FAO, 2018). FAO (2018) summarized the methodologies that can be used to assess the bioec- onomy. These methodologies include the value-added/ GDP approach, the input-output model, social account- ing matrix multiplier models, computable general equi- librium (CGE) models, partial equilibrium models and the use of various disaggregated or composite indices. Two of these methods dominate the quantification of the bioeconomy: the value added/GDP approach and input- output (IO) models. In the value added/GDP approach, biobased shares of various products are estimated by experts and then sectorial statistics are adjusted accord- ing to these shares (Ronzon et al. 2017; Piotrowski, Carus, and Carrez, 2018). Input-output models build on the concept of biomass flows, namely, that individu- al industries produce biological resources or use inputs from primary biomass producing sectors, and this deter- mines their contribution to the bioeconomy (Grealis and O’Donoghue, 2015; NordBio, 2017). The IO model has advantages over the value added/GDP approach because it automatically includes value added of all industries, and therefore GDP (sum of value added). Moreover, the IO model includes links between multiple producers and products and allows the integration of economic as well as environmental indicators (Gaftea, 2013). In addition to traditional economic indicators (i.e., share in GDP and total employment), this research uses environmental indicators that are connected to climate change. Besides total greenhouse gas (GHG) emissions of carbon dioxide (CO2), methane (CH4) and nitrous diox- ide (N2O) and fluorinated gases (HFC, PFC, SF6, NF3) (see Appendix A), we also include a separate measure of CO2 emissions as the main greenhouse gas. Further- more, CO2 is not only emitted, but also sequestered in forests and harvested wood products. Latvia’s forestry sector has the potential to contribute greatly to this. Therefore, our research objective is to determine the economic and environmental contribution of the forest- based bioeconomy in Latvia. To achieve this objective, the following approach is taken. Section 2 provides a review of the characteristics of the forest-based bioeconomy in Latvia. The frame- work of the IO model to measure the contribution of the forest-based bioeconomy to GDP, employment, and greenhouse gas emissions, the data used in the IO model and 3 scenarios are described in Section 3. In Section 4, we assess alternative approaches to measure Latvia’s for- est-based bioeconomy by using different combinations of inputs. The paper concludes with a discussion of the IO model results in Section 5. 2. THE FOREST-BASED BIOECONOMY IN LATVIA Latvia is one of the Baltic countries situated between Lithuania and Estonia. It is a country rich in forest resources. In terms of forest area per capita, Latvia ranks 4th in the EU (behind Finland, Sweden, and Slovenia), followed by Estonia (Latvian Bioeconomy Strategy 2030, 2018). Forests occupy on average 33% of the land area in the EU, while in Latvia this is 52%, in Estonia 50%, and in Lithuania 33%. According to the Latvian State Forest Service (2019), the area of forest land was 3.35 million ha in 2018, of which forests occupied 3.04 million ha (91%), https://doi.org/10.36253/bae-13868 325 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 The forest-based bioeconomy in Latvia: economic and environmental importance the rest being swamps and forest infrastructure. State- managed forests covered 1.49 million ha (49%), while 1.55 million ha (51%) were managed by local government and private forest owners in 2018. Compared to 1923, when forest land had a share of 23% of the total area, the forest area in Latvia has more than doubled (Baders et al., 2019). The increase in for- est area is expected to continue as a result of purpose- ful afforestation, as well as through the continued nat- ural growth of forests on abandoned agricultural and non-agricultural lands. Additionally, forest biomass is increasing due to sustainable forest management in recent decades (Lazdiņš et al. 2019). In 2015, for exam- ple, the gross annual increase in biomass was 16.9 mil- lion m3, while 10.6 million m3 was harvested (see Appen- dix B for details). Latvia’s forests are mostly made up of conifers (53%), but a significant part is also occupied by other species such as birch (30%), white alder (7%) and aspen (7%) (Latvian State Forest Service, 2019). These species are common in all Baltic countries. In Latvia we see that in 2015 24.27% of the domes- tically produced forestry products (CPA code A02) are used in the production of wood products (CPA code C16) being the largest user after the production of for- estry products itself (39.30%). Moreover, 14.29% is exported. Although only 21.69% of domestically pro- duced wood products are used by the domestic produc- tion of furniture (CPA code C31/C32), most are export- ed: 65.36%, it is the main variable input for the latter (24.21%). Therefore, we see that the production of these three products is vertically linked. However, each of them is also important on its own. We define the forest-based bioeconomy (FBB) as the direct (i.e. the production of forestry, wood and furni- ture products) and indirect production (i.e. the produc- tion of inputs needed in the direct production, e.g. the production of machinery to process wood) needed to enable the final demand of forestry, wood and furni- ture products. So, we have three ‘sub-complexes’. Final demand in IO models consists of consumer demand, demand by the public sector (i.e., public institutions), investment demand, and exports. Table 1 shows the importance of the forest sector in Latvia and the other Baltic countries. The forest sector in Latvia had a share of 4.8% of GDP in 2017, exports amounted to EUR 2.2 billion, or 20.0% of all exports, and employed 46,000 people (5.3% of total employment). These numbers deviate from those previously mentioned because of a different year (2017 instead of 2015). There are 7,000 enterprises in the forest sector, representing 3.8% of the total number of enterprises in Latvia (ZM, 2019). These companies are often the main pillar of sup- port for rural economies. An important role played by forests is that they sequester CO2. Forest land and harvested wood prod- ucts are net sinks of CO2. In 2015, they sequestered 3.8 million tons of CO2 (Table 2), which represents a share of 60.6% in total CO2 sequestration in Latvia. The rest is sequestered by living biomass in other types of land (Skrebele et al., 2020). The amount of sequestered CO2 by forest land and wood products represents 35% of the 10.8 million tons of total greenhouse gas emissions in Latvia. However, it should be noted that nearly a third of forests in Latvia have exceeded their economic matu- rity age (depending on dominant tree species - 41 - 121 years). The ability of these forests to sequester carbon is lower than that of young and premature forests (Lat- vian State Forest Research Institute Silava, 2017), where young forests sequester less than premature forests. The afforestation implemented over previous decades is expected to sequester increasing CO2 emissions after 2030 (Lazdiņš et al., 2019). Old-growth forests serve especially the EU Biodiversity strategy 2030 goals. How- ever, there are many risks/shortcomings in that, for example, appearance of invasive species (Zute, 2022) and, as mentioned, the intensity of carbon sequestra- tion is lower than that of young forests that grow more Table 1. Economic indicators (in % of total) for the forest sector in the Baltic countries, 2017. Country Employment Exports GDP Estonia 5.3 11.9 4.3 Latvia 5.3 20.0 4.8 Lithuania 4.8 9.9 4.0 Source: Author`s calculations based on Eurostat (2020b); Eurostat (2021a); Eurostat (2021b). Table 2. Net GHG emissions by forest land and harvested wood products, 2015. Source Size Net GHG emissions in kiloton CO2 equivalent* Forest land 3.561 million ha -1,995** Harvested wood products 10.626 million m3 -1,850 *See Appendix B for composition. **includes sequestration by living biomass and emissions by dead woods, litter, organic soils, and wildfires and controlled burning on forest land. The negative signs represent the net sequestering of GHG emissions. Source: Skrebele et al. (2020) and CSB (2020). https://doi.org/10.36253/bae-13868 326 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 Vineta Tetere, Jack Peerlings, Liesbeth Dries rapidly, removing much more CO2 from the atmosphere. A forest management that avoids large emissions from the loss of old trees while rapidly removing CO2 from the atmosphere through young forest growth can pro- vide both storage and sequestration benefits. In addition, well-managed forests produce wood products that store carbon long after the trees are harvested. These products provide an added benefit when they are used in place of more energy-intensive ones that require more fossil fuel emissions, such as several building materials (McKinley et al., 2011). 3. MATERIALS AND METHODS 3.1 Input-Output framework Section 2 discussed the forest-based bioeconomy (FBB) and its three sub-complexes. Next, we quantify the economic and environmental performance of the FBB using an input-output framework that allows the disentanglement of the three sub-complexes. The input- output (IO) model was developed by Leontief in the late 1930s to analyse the economy as a whole and to study the interdependence among the different industries in an economy, since the output of one industry can serve as an input for another industry directly and indirectly (Miller and Blair, 2009). Therefore, a change in the final demand for the products of one industry affects the whole economy via direct and indirect linkages (Sink, 2010). Cingiz et al. (2021) analysed the value added of the bioeconomy in 28 EU member states using an IO model. The input-output model is suitable to track bio- mass inputs and to determine the contribution of differ- ent industries to the FBB and, consequently, the FBB’s contribution to the total economy. The IO model is lin- ear as it assumes fixed ratios between inputs and out- puts (i.e., IO coefficients) and, therefore, is applicable to determine the direct and indirect size of the FBB. The standard IO model calculates the vector of product-level output of the industries that is linked to the final demand of products and is given by the follow- ing (Miller and Blair, 2009): x = (I – A)-1f (1) where x is the vector of total output at basic prices, I is the unity (identity) matrix, A is the matrix of IO coef- ficients (the square technical coefficient matrix), f is the vector of final demand of, for example, forest-based products at basic prices (see Appendix C). IO coefficients give the fixed ratio between the amount of input i used for the production of output j. However, we adjust the model to (e.g. Momigliano & Siniscalco, 1982; Pasinetti, 1973): B = (I – A)-1f ̂ (2) Hence, we take the diagonal matrix of ( f ̂ ) and, instead of the vector x, we get the matrix B that shows in each column the production needed in each industry of the economy to make the final demand of each indus- try’s product possible. Consequently, the elements in column k (vector xk) show the production in each indus- try needed to produce the final demand of products produced by industry k. In this way, we disentangle the three sub-complexes of the FBB. Assuming a fixed ratio between economic indica- tors (i.e., value added and employment) and environ- mental indicators (i.e., CO2 and GHG emissions) with output we get: zkl = b̂l xk (3) where zkl is value added (l=1); employment (l=2); emis- sions of CO2 (l=3) and GHG emissions (l=4) for the sub- complex k of the FBB, b̂l is the diagonal matrix of the fixed ratio of indicator l and the output, and xk is col- umn k of matrix B. 3.2 Data description According to OECD (2019), Input-Output (IO) tables describe the sales and purchase relationships of goods and services (i.e. commodities) between producers and consumers within an economy. The table shows the inter- industry linkages, final demand, and value added cre- ated. Therefore, an IO table is a numerical overview of an economy. Commodities are defined as industry outputs, for example, the product produced by agriculture (indus- try-by-industry table), or as products, for example, milk (product-by-product table) (OECD, 2019). An IO table only includes commodities that have a monetary value, external effects (i.e. non-priced by-products as emissions) or leaves and small branches without economic value are excluded. This research uses the product-by-product IO table of 2015 for Latvia. There are two versions of this table, one where imports constitute a separate row, implying that intermediate demands are commodities domesti- cally produced and used. The second version is where intermediate demands include imports. Given that we are especially interested in domestic production, we decided to use the first table. The original table contains data for 63 goods and services (i.e., products i). However, some rows or columns showing intermediate demands https://doi.org/10.36253/bae-13868 327 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 The forest-based bioeconomy in Latvia: economic and environmental importance are empty, that is why they are added to other related products. This results in a table containing 60 goods and services. The IO table is developed every five years by the Central Statistics Bureau (CSB) of Latvia. Data are com- piled according to the European Union Statistical Classi- fication of Products by Activity (CPA) and are expressed in basic prices (million euros). Industry-by-industry IO tables are not provided by CSB. IO tables for Latvia are also provided by OECD but, due to the high level of aggregation, they are not applicable for our purpose. To assess the economic and environmental impor- tance of the FBB for Latvia, the following indicators are selected: value added, employment, carbon dioxide (CO2) emissions (excluding CO2 emissions from biomass combustion) and greenhouse gas (GHG) emissions. Val- ue added at basic prices data (see Appendix C) are used from the IO table, employment data are used from the EU labour force survey of Eurostat (2020b), and emis- sions data are obtained from the air emissions accounts of Eurostat (2020a). All data used are from 2015 due to availability of the IO table. Table 3 gives the value add- ed, employment and CO2 and GHG emissions that are directly linked to the production of ‘products of forest- ry, logging and related services’ (CPA code A02, prod- uct i=2), ‘wood and products of wood and cork, except furniture; articles of straw and plaiting materials’ (CPA code C16, i=16) and ‘furniture and other manufactur- ing such as jewellery, musical instruments, household tools, entertainment articles and other miscellaneous goods that are not covered in other parts of the classifi- cation’ (aggregate CPA codes C31 and C32, i=31). In the rest of the paper, we indicate these three product catego- ries as forest products (A02), wood (C16), and furniture (C31/32) products. Note that these data are not for the FBB as a whole because they do not include interdepend- encies with other sectors of the economy. The table shows that the production of the three product categories directly contributes 5% to GDP and 5.8% to total employment in Latvia. The contribution to CO2 emissions is 3.3% and to greenhouse gas emissions 2.6%, excluding CO2 sequestration. 85% of GHG emitted by FBP is CO2 (i.e. CO2 234,009 ton/ GHG 276,656 ton). 4. SCENARIOS AND RESULTS 4.1 Scenarios We defined the FBB as the direct and indirect pro- duction linked to the final demand for forestry prod- ucts (A02), wood products (C16), and furniture (C31/32). We show the results of the FBB as a whole, but also its decomposition in the three sub-complexes linked to the final demand of the three products mentioned. Notice that the calculations imply that if forestry products (A02) are used in the production of wood products (C16) that production, value added, employment and emis- sions are linked to the sub-complex wood products (C16) and not to the sub-complex forestry products (A02). 4.2 Results Table 4 shows the size of the FBB and its sub-com- plexes using 4 indicators. For all four indicators, the sub-complex wood products (C16) is the largest and the sub-complex furniture (C31/32) is the smallest. The over- all share in GDP is 6.44%. However, if we include the value added created in the direct production of forestry Table 3. Value added, employment, and emissions directly related to the production of Forestry (A02), Wood (C16), and Furniture (C31/32) products in Latvia, 2015. Value added Employment CO2 emissions GHG emissions million Euros % of GDP thousand persons % of total ton % of total ton % of total Forestry products (A02)* 356 1.7 18.60 2.2 122,642 1.7 128,945 1.2 Wood products (C16) 546 2.6 23.50 2.7 100,586 1.4 136,785 1.3 Furniture (C31/32) 139 0.7 7.30 0.9 10,781 0.2 10,926 0.1 Total (A02+C16+C31/32) 1,041 5.0 49.4 5.8 234,009 3.3 276,656 2.6 Rest of the economy 20,204 95.0 809.6 94.2 6,882,766 96.7 10,501,761 97.4 Total 21,245 100 859 100 7,116,775 100 10,778,417 100 Note: GHG emissions include CO2, N2O in CO2 equivalent, CH4 in CO2 equivalent, HFC in CO2 equivalent, PFC in CO2 equivalent, SF6 in CO2 equivalent, NF3 in CO2 equivalent. * A02, C16 and C31/32 are CPA codes. Source: Authors’ calculations based on CSB (2016), Eurostat (2020a and 2020b). https://doi.org/10.36253/bae-13868 328 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 Vineta Tetere, Jack Peerlings, Liesbeth Dries (A02), wood (C16) and furniture (C31/32) products that are used as intermediate inputs in the production of the final demand for other products we get a share of 6.88%. We see a similar increase for the other three indicators. This illustrates that forestry products (A02) are important in the production of wood products (C16) which, in turn, are important for the production of furniture (C31/32). 5. DISCUSSION AND CONCLUSIONS We measured the FBB contribution to Latvia’s econ- omy using share in GDP, employment and CO2 and GHG emissions. We did this using an IO model that incorporates the direct and indirect use of intermedi- ate inputs in the production needed to enable the final demand of forestry (A02), wood (C16) and furniture (C31/32) products. These linkages appear to be important, especial- ly forestry products (A02) form an important input in the production of wood products (C16) which, in turn, are important for the production of furniture (C31/32). These linkages determine our definition of the FBB. For another country another definition could apply depend- ing on the linkages present. For example, in other coun- tries like Finland the paper industry, which is not present in Latvia, could be part of the FBB. The FBB had in 2015 a share of 6.44% in GDP and if we include also the val- ue added created with the production of forestry (A02), wood (C16) and furniture (C31/32) products that are used as intermediate inputs for the production of final demand of non-FBB products, the share equals 6.88%. Similar percentages apply for employment (6.58% and 7.12%) and CO2 (6.59% and 6.92%). The share of the FBB in total GHG emissions is somewhat lower (4.93% and 5.17%). The outcomes for the FBB are higher than the sum of the value added, employment, CO2 and GHG emissions cre- ated with the production of forestry (A02), wood (C16) and furniture (C31/32) products, since it includes the indirect use of other products in the production of these products. To our knowledge, this is the first research that takes these linkages into account for the FBB of Latvia. The contribution to the emissions of CO2 and GHG excludes CO2 sequestration. Forest land and harvested wood products sequester an estimated 3.8 million tons of GHG emissions. This is 35.2% of total GHG emis- sions in Latvia in 2015. GHG sequestration has increased in recent years due to the expansion of forest land and the annual growth of forest biomass. The EU Green Deal states that the EU has to become climate neutral by 2050. This requires that EU member states reduce net greenhouse gas emissions to zero. Our results show that Latvia already achieves this goal set by the EU if we take into account GHG sequestration. Furthermore, there is a great potential for further sequestration of GHGs from forest biomass. At the moment, sequestration is not included in the EU emissions trading system, including it would provide opportunities for the Latvian economy. Table 4. First four rows: Value added, employment, CO2 and GHG emissions linked to the final demand of Forestry products (A02), Wood products (C16) and Furniture (C30/31) in Latvia, 2015. Next four rows (i.e. Rest): Value added, employment, CO2 and GHG emissions of Forestry products (A02), Wood products (C16) and Furniture (C30/31) that are linked to the final demand of other products in Latvia, 2015. Products Value Added Employment CO2 emissions GHG emissions million EUR % of GDP thousand persons % of the total economy ton % of total CO2 equivalent ton % of total Linked to final demand of: Forestry products A02 211.8 1.00 10.1 1.18 72,854.5 1.02 77,109.9 0.72 Wood products C16 953.0 4.49 37.1 4.31 350,815.8 4.93 402,382.1 3.75 Furniture C30/31 202.8 0.95 9.4 1.09 45,389.6 0.64 49,657.0 0.46 Total 1,367.6 6.44 56.5 6.58 469,059.9 6.59 529,149.0 4.93 Rest Forestry products A02 46.6 0.22 2.4 0.28 16,046.4 0.23 16,871.2 0.16 Wood products C16 34.2 0.06 1.5 0.17 6,296.9 0.09 8,563.0 0.08 Furniture C30/31 13.7 0.16 0.7 0.08 1,056.7 0.01 1,070.9 0.01 Total Rest 94.5 0.44 4.6 0.53 23,400.0 0.33 26,505.1 0.25 Total + Total Rest 1,462.1 6.88 61.1 7.12 492,459.9 6.92 555,654.1 5.17 Source: Authors’ calculations. https://doi.org/10.36253/bae-13868 329 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 The forest-based bioeconomy in Latvia: economic and environmental importance Besides the assumed fixed shares between inputs and outputs (i.e., IO coefficients), other drawbacks of IO mod- els are the absence of a link between income creation and spending, and the assumption of a perfectly elastic sup- ply of factor inputs (i.e., labour and capital) (Guerra & Sancho, 2014; Acemoglu & Azar, 2020). These drawbacks are not relevant in this research, as we use the IO model for descriptive purposes. Moreover, the IO model that we use can be applied to any country by using national or regional data sets, statistics of employment, value added, and emissions. In this way, the FBB becomes country- specific and can form a benchmark and information source for policy formulation to achieve the goals of the Green Deal because it enables monitoring the bioecono- my and understanding its driving forces. We used the Eurostat IO table of 2015 to analyse the importance of the forest-based bioeconomy due to the lack of data in recent years. Notably, outcomes can dif- fer between years. Ideally, we would have information for more years that would enable us to detect and analyse the development of the forest-based bioeconomy over time. A general drawback of the use of the Eurostat IO table is the high level of aggregation, preferable we would like to have more detail on the products produced in the for- est-based bioeconomy. This is especially relevant in case we, for example, would like to formulate product related policies or obtain regional detail. A more specific caveat of the use of the IO table of 2015 is that in the light of the Green Deal and the Russian invasion of Ukraine, it is expected that Latvia will try to increase the use of for- est-based biomass for energy production. This potential increase of the FBB cannot be investigated with the pre- sent model. Despite these drawbacks, this paper gives a first attempt to derive the size of the FBB in Latvia using not only economic but also environmental indicators and by including direct and indirect linkages in the economy. REFERENCES Acemoglu, D., & Azar, P. D. (2020). Endogenous Produc- tion Networks. Econometrica, 88(1), 33–82. https:// doi.org/10.3982/ecta15899 Baders, E., Lukins, M., Zarins, J., Krisans, O., Jansons, A., & Jansons, J. (2019). Recent land cover chang- es in Latvia. 1, 34–39. https://doi.org/10.22616/ rrd.24.2018.005 Bracco, S., Calicioglu, O., SanJuan, M., & Flammini, A. (2018). Assessing the Contribution of Bioeconomy to the Total Economy: A Review of National Frame- works. Sustainability, 10. https://doi.org/10.3390/ su10061698 Cingiz, K., Gonzalez-Hermoso, H., Heijman, W., & Wes- seler, J. H. H. (2021). A Cross-Country Measurement of the EU Bioeconomy: An Input–Output Approach. Sustainability, Vol. 13. https://doi.org/10.3390/ su13063033 CSB - Central Statistics Bureau of Latvia. (2020). MSG010. Latvian forest land and timber stand. Retrieved from http://data1.csb.gov.lv/pxweb/ en/lauks/lauks__mezsaimn__plat_mez/MSG010. px/?rxid=d8284c56-0641-451c-8b70-b6297b58f464 CSB Latvia. (2016). Gross domestic product Supply-Use and Input-Output tables. Retrieved from https://www. csb.gov.lv/en/statistics/statistics-by-theme/economy/ GDP/IOT EC - European Commission. (2010). EUROPE 2020: A Strategy for Smart, Sustainable and Inclusive Growth. Retrieved from https://eur-lex.europa.eu/LexUriServ/ LexUriServ.do?uri= COM:2010:2020:FIN:EN:PDF EC - European Commission. (2012). Innovating for Sus- tainable Growth: A Bioeconomy for Europe. Retrieved from https://publications.europa.eu/sk/publication- detail/-/publication/1f0d8515-8dc0-4435-ba53- 9570e47dbd51 EC - European Commission. (2020). How the bioeconomy contributes to the European Green Deal. Retrieved from https://ec.europa.eu/info/sites/info/files/ research_and_innovation/research_by_area/docu- ments/ec_rtd_greendeal-bioeconomy.pdf EC - European Commission a. (n.d.). Bioeconomy. Retrieved from https://ec.europa.eu/info/research- and-innovation/research-area/environment/bioecon- omy_en EC - European Commission b. (n.d.). Bioeconomy & European Green Deal. Retrieved from https://knowl- edge4policy.ec.europa.eu/bioeconomy/bioeconomy- european-green-deal_en Eurostat. (2021). EU trade since 1988 by CPA 2008, [DS-1060915]. Retrieved from https://appsso. eurostat.ec.europa.eu/nui/show.do?dataset=DS- 1060915&lang=en Eurostat a. (2020). Air emissions accounts by NACE Rev. 2 activity, [env_ac_ainah_r2]. Retrieved from https://appsso.eurostat.ec.europa.eu/nui/show. do?dataset=env_ac_ainah_r2&lang=en Eurostat a. (2021). Employment by sex, age, and detailed economic activity (from 2008 onwards, NACE Rev. 2 two digit level) - 1 000, [lfsa_egan22d]. Retrieved from https://appsso.eurostat.ec.europa.eu/nui/show. do?dataset=lfsa_egan22d&lang=en Eurostat b. (2020). Economic aggregates of forestry, [FOR_ ECO_CP]. Retrieved from https://appsso.eurostat. ec.europa.eu/nui/show.do?dataset=for_eco_cp&lang=en https://doi.org/10.36253/bae-13868 https://doi.org/10.3982/ecta15899 https://doi.org/10.3982/ecta15899 https://doi.org/10.22616/rrd.24.2018.005 https://doi.org/10.22616/rrd.24.2018.005 https://doi.org/10.3390/su10061698 https://doi.org/10.3390/su10061698 https://doi.org/10.3390/su13063033 https://doi.org/10.3390/su13063033 http://data1.csb.gov.lv/pxweb/en/lauks/lauks__mezsaimn__plat_mez/MSG010.px/?rxid=d8284c56-0641-451c-8b70-b6297b58f464 http://data1.csb.gov.lv/pxweb/en/lauks/lauks__mezsaimn__plat_mez/MSG010.px/?rxid=d8284c56-0641-451c-8b70-b6297b58f464 http://data1.csb.gov.lv/pxweb/en/lauks/lauks__mezsaimn__plat_mez/MSG010.px/?rxid=d8284c56-0641-451c-8b70-b6297b58f464 https://www.csb.gov.lv/en/statistics/statistics-by-theme/economy/GDP/IOT https://www.csb.gov.lv/en/statistics/statistics-by-theme/economy/GDP/IOT https://www.csb.gov.lv/en/statistics/statistics-by-theme/economy/GDP/IOT https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri= https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri= https://publications.europa.eu/sk/publication-detail/-/publication/1f0d8515-8dc0-4435-ba53-9570e47dbd51 https://publications.europa.eu/sk/publication-detail/-/publication/1f0d8515-8dc0-4435-ba53-9570e47dbd51 https://publications.europa.eu/sk/publication-detail/-/publication/1f0d8515-8dc0-4435-ba53-9570e47dbd51 https://ec.europa.eu/info/sites/info/files/research_and_innovation/research_by_area/documents/ec_rtd_greendeal-bioeconomy.pdf https://ec.europa.eu/info/sites/info/files/research_and_innovation/research_by_area/documents/ec_rtd_greendeal-bioeconomy.pdf https://ec.europa.eu/info/sites/info/files/research_and_innovation/research_by_area/documents/ec_rtd_greendeal-bioeconomy.pdf https://ec.europa.eu/info/research-and-innovation/research-area/environment/bioeconomy_en https://ec.europa.eu/info/research-and-innovation/research-area/environment/bioeconomy_en https://ec.europa.eu/info/research-and-innovation/research-area/environment/bioeconomy_en https://knowledge4policy.ec.europa.eu/bioeconomy/bioeconomy-european-green-deal_en https://knowledge4policy.ec.europa.eu/bioeconomy/bioeconomy-european-green-deal_en https://knowledge4policy.ec.europa.eu/bioeconomy/bioeconomy-european-green-deal_en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=DS-1060915&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=DS-1060915&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=DS-1060915&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_ac_ainah_r2&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_ac_ainah_r2&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egan22d&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_egan22d&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=for_eco_cp&lang=en https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=for_eco_cp&lang=en 330 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 Vineta Tetere, Jack Peerlings, Liesbeth Dries FAO - Food and Agriculture Organization of United Nations. (2018). Assessing the Contribution of Bio- economy to Countries’ Economy. A Brief Review of National Frameworks. Retrieved from http://www.fao. org/3/I9580EN/i9580en.pdf Gaftea, V. (2013). The input-output modeling approach to the national economy. Romanian Journal of Economic Forecasting, 16, 211–222. Retrieved from https://ide- as.repec.org/a/rjr/romjef/vy2013i2p211-222.html Grealis, E., & O’Donoghue, C. (2015). The Economic Impact of the Irish Bio-Economy: Development and Uses. In Joint report issued by the Teagasc Rural Econ- omy Development Programme and the Socio-Econom- ic Marine Research Unit, NUI Galway. https://doi. org/10.22004/ag.econ.210704 Guerra, A.-I., & Sancho, F. (2014). An operational, nonlinear input–output system. Economic Model- ling, 41, 99–108. https://doi.org/10.1016/j.econ- mod.2014.04.027 Gunning, J. W., & Keyzer, M. (1995). Applied general equilibrium models for policy analysis (H. Chenery & T. N. Srinivasan, Eds.). Retrieved from https://econ- papers.repec.org/RePEc:eee:devchp:3-35 Ladu, L., Imbert, E., Quitzow, R., & Morone, P. (2020). The role of the policy mix in the transition toward a circular forest bioeconomy. Forest Policy and Eco- nomics, 110, 101937. https://doi.org/https://doi. org/10.1016/j.forpol.2019.05.023 Latvian Bioeconomy Strategy 2030. (2018). Retrieved from https://www.zm.gov.lv/public/files/CMS_Static_Page_ Doc/00/00/01/46/58/E2758-LatvianBioeconomyStrat- egy2030.pdf Latvian State Forest Research Institute Silava. (2017). INFORMATION ON LULUCF ACTIONS IN LATVIA Progress report under EU Decision 529/2013/EU Arti- cle 10. Retrieved from https://www.zm.gov.lv/public/ files/CMS_Static_Page_Doc/00/00/01/03/51/LULUC- Factionplan_progress_report_21042017.pdf Latvian State Forest Service. (2019). Public review 2018. Retrieved from https://www.zm.gov.lv/public/files/ CMS_Static_Page_Doc/00/00/01/54/24/VMD_Pub- liskais_parskats_2018_.pdf Lazdiņš, A., Lupiķis, A., Butlers, A., Bārdule, A., Kārkliņa, I., Šņepsts, G., & Donis, J. (2019). Latvia’s national forest accounting plan and proposed forest reference level 2021-2025. Retrieved from https://www.fern.org/ fileadmin/uploads/fern/Documents/NFAP_Latvia.pdf Lazorcakova, E., Dries, L., Peerlings, J., & Pokrivcak, J. (2022). Potential of the bioeconomy in Visegrad countries: An input-output approach. Biomass and Bioenergy, 158, 106366. https://doi.org/https://doi. org/10.1016/j.biombioe.2022.106366 Lovrić, M., Lovrić, N., & Mavsar, R. (2020). Mapping forest-based bioeconomy research in Europe. Forest Policy and Economics, 110. https://doi.org/10.1016/j. forpol.2019.01.019 McKinley, D. C., Ryan, M. G., Birdsey, R. A., Giardina, C. P., Harmon, M. E., Heath, L. S., … Skog, K. E. (2011, September). A synthesis of current knowledge on for- ests and carbon storage in the United States. Ecologi- cal Applications, Vol. 21, pp. 1902–1924. https://doi. org/10.1890/10-0697.1 Miller, R. E., & Blair, P. D. (2009). Input-Output analyses, Foundations and Extentions. Retrieved from https:// books.google.lv/books?id=SmFUl-6X1FUC&lpg=PA 557&ots=lXQFT8SyuF&dq=direct and indirect link- ages input output model&hl=lv&pg=PA557#v=on epage&q=direct and indirect linkages input output model&f=false Momigliano, F., & Siniscalco, D. (1982). The Growth of Service Employment: a reappraisal (pp. 269–306). pp. 269–306. Retrieved from https://rosa.uniroma1. it/rosa04/psl_quarterly_review/article/view/14060/ pdf_17 NordBio. (2017). The Nordic Bioeconomy Initiative. Final Report. Nordic Council of Ministers, 2017. Retrieved from http://norden.diva-portal.org/smash/get/ diva2:1084345/FULLTEXT01.pdf OECD. (2019). Input-Output Tables (IOTs). Retrieved from http://www.oecd.org/sti/ind/input-outputtables. htm Pasinetti, L. L. (1973). the Notion of Vertical Integration in Economic Analysis (). Metroeconomica, 25(1), 1–29. https://doi.org/10.1111/j.1467-999X.1973.tb00539.x Piotrowski, S., Carus, M., & Carrez, D. (2018). European Bioeconomy in Figures 2008 – 2015. Retrieved from https://biconsortium.eu/sites/biconsortium.eu/files/ documents/Bioeconomy_data_2015_20150218.pdf Ronzon, T, Santini, F., & M’Barek, R. (2015). The Bioec- onomy in the European Union in numbers. Facts and figures on biomass, turnover and employment. Euro- pean Commission, Joint Research Centre. Institute for Prospective Technological Studies, Spain, 4. Ronzon, Tévécia, Piotrowski, S., M’Barek, R., & Carus, M. (2017). A systematic approach to understanding and quantifying the EU’s bioeconomy. Bio-Based and Applied Economics Journal, Vol. 06, pp. 1–17. https:// doi.org/10.22004/ag.econ.276283 Siebert, A., Bezama, A., O’Keeffe, S., & Thrän, D. (2018). Social life cycle assessment: in pursuit of a frame- work for assessing wood-based products from bioec- onomy regions in Germany. The International Journal of Life Cycle Assessment, 23(3), 651–662. https://doi. org/10.1007/s11367-016-1066-0 https://doi.org/10.36253/bae-13868 http://www.fao.org/3/I9580EN/i9580en.pdf http://www.fao.org/3/I9580EN/i9580en.pdf https://ideas.repec.org/a/rjr/romjef/vy2013i2p211-222.html https://ideas.repec.org/a/rjr/romjef/vy2013i2p211-222.html https://doi.org/10.22004/ag.econ.210704 https://doi.org/10.22004/ag.econ.210704 https://doi.org/10.1016/j.econmod.2014.04.027 https://doi.org/10.1016/j.econmod.2014.04.027 https://econpapers.repec.org/RePEc https://econpapers.repec.org/RePEc https://doi.org/https http://doi.org/10.1016/j.forpol.2019.05.023 http://doi.org/10.1016/j.forpol.2019.05.023 https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/46/58/E2758-LatvianBioeconomyStrategy2030.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/46/58/E2758-LatvianBioeconomyStrategy2030.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/46/58/E2758-LatvianBioeconomyStrategy2030.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/03/51/LULUCFactionplan_progress_report_21042017.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/03/51/LULUCFactionplan_progress_report_21042017.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/03/51/LULUCFactionplan_progress_report_21042017.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/54/24/VMD_Publiskais_parskats_2018_.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/54/24/VMD_Publiskais_parskats_2018_.pdf https://www.zm.gov.lv/public/files/CMS_Static_Page_Doc/00/00/01/54/24/VMD_Publiskais_parskats_2018_.pdf https://www.fern.org/fileadmin/uploads/fern/Documents/NFAP_Latvia.pdf https://www.fern.org/fileadmin/uploads/fern/Documents/NFAP_Latvia.pdf https://doi.org/https http://doi.org/10.1016/j.biombioe.2022.106366 http://doi.org/10.1016/j.biombioe.2022.106366 https://doi.org/10.1016/j.forpol.2019.01.019 https://doi.org/10.1016/j.forpol.2019.01.019 https://doi.org/10.1890/10-0697.1 https://doi.org/10.1890/10-0697.1 https://books.google.lv/books?id=SmFUl-6X1FUC&lpg=PA557&ots=lXQFT8SyuF&dq=direct https://books.google.lv/books?id=SmFUl-6X1FUC&lpg=PA557&ots=lXQFT8SyuF&dq=direct https://books.google.lv/books?id=SmFUl-6X1FUC&lpg=PA557&ots=lXQFT8SyuF&dq=direct https://rosa.uniroma1.it/rosa04/psl_quarterly_review/article/view/14060/pdf_17 https://rosa.uniroma1.it/rosa04/psl_quarterly_review/article/view/14060/pdf_17 https://rosa.uniroma1.it/rosa04/psl_quarterly_review/article/view/14060/pdf_17 http://norden.diva-portal.org/smash/get/diva2 http://norden.diva-portal.org/smash/get/diva2 http://www.oecd.org/sti/ind/input-outputtables.htm http://www.oecd.org/sti/ind/input-outputtables.htm https://doi.org/10.1111/j.1467-999X.1973.tb00539.x https://biconsortium.eu/sites/biconsortium.eu/files/documents/Bioeconomy_data_2015_20150218.pdf https://biconsortium.eu/sites/biconsortium.eu/files/documents/Bioeconomy_data_2015_20150218.pdf https://doi.org/10.22004/ag.econ.276283 https://doi.org/10.22004/ag.econ.276283 https://doi.org/10.1007/s11367-016-1066-0 https://doi.org/10.1007/s11367-016-1066-0 331 Bio-based and Applied Economics 12(4): 323-331, 2023 | e-ISSN 2280-6172 | DOI: 10.36253/bae-13868 The forest-based bioeconomy in Latvia: economic and environmental importance Sink, T. (2010). Input-Output Models. Retrieved from https://www.researchgate.net/publication/261175197_ Input-Output_Models Skrebele, A., Rubene, L., Lupkina, L., Cakars, I., Siņics, L., LazdāneMihalko, J., … Zustenieks, G. (2020). Latvia’s National Inventory Report 1990 – 2018, Submission under UNFCCC and the Kyoto Protocol. Retrieved from https://unfccc.int/sites/default/files/resource/ lva-2020-nir-11may20.pdf UNFCCC. (2008). Kyoto Protocol Reference manual on Accounting of Emissions and Assigned Amount. Retrieved from https://unfccc.int/resource/docs/pub- lications/08_unfccc_kp_ref_manual.pdf Wesseler, J., & von Braun, J. (2017). Measuring the Bio- economy: Economics and Policies. Annual Review of Resource Economics, 9(1), 275–298. https://doi. org/10.1146/annurev-resource-100516-053701 World Bank. (2020). What is the difference between pur- chaser prices, producer prices (VAP), and basic prices (VAB)? Retrieved from https://datahelpdesk.world- bank.org/knowledgebase/articles/114947-what-is-the- difference-between-purchaser-prices-p ZM - Ministry of Agriculture. (2019). Latvian Forest Sec- tor in Facts and Figures 2018. Retrieved from https:// www.zm.gov.lv/mezi/statiskas-lapas/buklets-meza- nozare-skaitlos-un-faktos-2019-?id=16973#jump. APPENDIX A CO2 AND GHG EMISSIONS Information from the national inventory reported to the United Nations Framework Convention on Climate Change (UNFCCC) and the Convention on Long-range Transboundary Air Pollution, as well as data from the Central Statistical Bureau (CSB), is used for the calcula- tion of CO2 emissions. The GHG emission indicator measures the total national emissions of the so-called ‘Kyoto basket’ of greenhouse gases, including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and the so-called F-gases (hydrofluorocarbons, perfluorocarbons, nitro- gen trifluoride (NF3) and sulphur hexafluoride (SF6)). For each gas’ individual global warming potential (GWP), they are integrated into a single indicator expressed in units of CO2 equivalents. Emissions data are submitted annually by the EU Member States as part of the reporting under the UNF- CCC (UNFCCC, 2008). APPENDIX B SEQUESTRATION Table B.1. Forest land, gross annual increment, potential harvest, and harvested wood products in Latvia, 2015-2018. Year Forest land, 1,000 ha Gross annual increment, 1,000 m3 Potential harvest, 1,000 m3 Harvested wood products, 1,000 m3 2015 3,561 23,637.10 16,927.00 10,626.50 2016 3,561 25,166.92 17,276.44 10,555.81 2017 3,576 26,312.66 17,235.59 11,443.42 2018 3,585 26,480.09 17,584.81 12,861.65 Source: Latvian State Forest Service (2019), Skrebele et al. (2020), and CSB (2020). Table B.2. Net GHG emissions by forest land and harvested wood products, 2015-2018 (thousand ton CO2 equivalents). Source 2015 2016 2017 2018 Forest land -1,995.01 -3,179.63 -4,905.08 -3,213.87 Harvested wood products -1,850.36 -2,129.34 -2,251.33 -2,064.57 Total -3,845.46 -5,308.97 -7,156.41 -5,278.44 Source: Skrebele et al. (2020). APPENDIX C PRICES The World Bank (World Bank, 2020) provides the following price definitions: · The basic price is the amount receivable by the pro- ducer, exclusive of taxes payable on products, and inclusive of subsidies receivable on products. The equivalent for imported products is the c.i.f. (cost, insurance, and freight) value, that is, the value at the border of the importing country. · The producer price is the amount receivable by the producer inclusive of taxes on products except deductible value added tax and exclusive of subsidies on products. The equivalent for imported products is the c.i.f. value plus any import duties or other taxes on imports (minus any subsidies on imports). Producer prices = Basic prices + taxes on products (excluding VAT) - subsidies on products · The purchaser price is the amount payable by the purchaser. This includes trade margins realized by wholesalers and retailers (by definition, their output) as well as transport margins (that is, any transport charges paid separately by the purchaser) and non- deductible VAT. Purchaser prices = Producer prices + trade and trans- port margins + non-deductible VAT https://doi.org/10.36253/bae-13868 https://www.researchgate.net/publication/261175197_Input-Output_Models https://www.researchgate.net/publication/261175197_Input-Output_Models https://unfccc.int/sites/default/files/resource/lva-2020-nir-11may20.pdf https://unfccc.int/sites/default/files/resource/lva-2020-nir-11may20.pdf https://unfccc.int/resource/docs/publications/08_unfccc_kp_ref_manual.pdf https://unfccc.int/resource/docs/publications/08_unfccc_kp_ref_manual.pdf https://doi.org/10.1146/annurev-resource-100516-053701 https://doi.org/10.1146/annurev-resource-100516-053701 https://datahelpdesk.worldbank.org/knowledgebase/articles/114947-what-is-the-difference-between-purchaser-prices-p https://datahelpdesk.worldbank.org/knowledgebase/articles/114947-what-is-the-difference-between-purchaser-prices-p https://datahelpdesk.worldbank.org/knowledgebase/articles/114947-what-is-the-difference-between-purchaser-prices-p https://www.zm.gov.lv/mezi/statiskas-lapas/buklets-meza-nozare-skaitlos-un-faktos-2019-?id=16973#jump https://www.zm.gov.lv/mezi/statiskas-lapas/buklets-meza-nozare-skaitlos-un-faktos-2019-?id=16973#jump https://www.zm.gov.lv/mezi/statiskas-lapas/buklets-meza-nozare-skaitlos-un-faktos-2019-?id=16973#jump Modeling conversion to organic agriculture with an EU-wide farm model Dimitrios Kremmydas*, Pavel Ciaian, Edoardo Baldoni A systematic literature review on the rural-urban economic well-being gap in Europe Cesare Meloni1,*, Benedetto Rocchi2, Simone Severini1 The forest-based bioeconomy in Latvia: economic and environmental importance Vineta Tetere1,2,*, Jack Peerlings1, Liesbeth Dries1 The impact of COVID-19 on household income and participation in the agri-food value chain: Evidence from Ethiopia Margherita Squarcina1,2,*, Donato Romano1 Bioeconomy and resilience to economic shocks: insights from the COVID-19 pandemic in 2020 Jesús Lasarte-López1,*, Nicola Grassano2, Robert M’barek1, Tévécia Ronzon1 Acknowledgements