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Licensed Unlicensed Requires Authentication Published by De Gruyter November 13, 2020

Economic Spill-Over of Food Quality Schemes on Their Territory

Michele Donati ORCID logo, Adam Wilkinson, Mario Veneziani, Federico Antonioli, Filippo Arfini, Antonio Bodini ORCID logo, Virginie Amilien, Peter Csillag, Hugo Ferrer-Pérez, Alexandros Gkatsikos, Lisa Gauvrit, Chema Gil, Việt Hoàng, Kamilla Knutsen Steinnes, Apichaya Lilavanichakul, Konstadinos Mattas, Orachos Napasintuwong, An Nguyễn ORCID logo, Mai Nguyen, Ioannis Papadopoulos, Bojan Ristic, Zaklina Stojanovic, Marina Tomić Maksan, Áron Török, Efthimia Tsakiridou and Valentin Bellassen ORCID logo

Abstract

We study the effect of a set of food quality scheme (FQS) products within the local economy using a local multiplier approach based on LM3 methodology. To evaluate the effective contribution within the local area, we compare each FQS product with its equivalent standard/conventional counterpart. Local multiplier allows us to track the financial flows converging within the local area at the different levels of the supply chain so that we can measure the FQS product role in local economic activation. Overall, the FQS products exhibit a higher positive contribution to the local economy than the standard references. However, there is significant heterogeneity in the impact according to the product categories. In the case of vegetal products, the local economic advantage due to FQS is 7% higher than the reference products, but the statistical tests reject the null hypothesis that the medians are significantly different from zero. On the contrary, animal products exhibit a larger contribution of FQS than the standard counterparts (+24%). The PGI products (+25%) produce the major effect, while PDO products show a median difference lower (+6%). The organic and non-organic products seem to be substantially equivalent in terms of contribution to the local economy, due to the similarity in the downstream processing phase.

JEL code: Q12; Q18; E12; F61

Corresponding author: Michele Donati, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy, E-mail:

Funding source: Horizon 2020 Framework Programme

Award Identifier / Grant number: 678024

Acknowledgement

This study was conducted in the framework of the "Strength2Food" project, which received funding from the European Union’s Horizon 2020 research and innovation programme under the GA 678024. The authors would like to thank all the people and institutions who collected or provided raw data for this publication.

Appendix List of variables

Variable nameVariable relevanceUnitBrief description
R1_turnoverkey€ year-1Total annual turnover at level R1.
R1_wageskey% turnoverSum of wages paid for family workers and employees at level R1 of the value chain, including if necessary an approximated fixed hourly remuneration for (unpaid) family labour
R1_NCIkey% turnoverTotal Cost of Non-Core Input at level R1 (e.g. for Parmigiano-Reggiano, all the input costs excluding labour and milk).
R1_CIkey% turnoverTotal cost of Core Input at level R1 (e.g. for Parmigiano-Reggiano, the cost of milk)
R1_Tot_staff_lakey%Share of staff at level R1 living in the local area
R1_CI_LAkey%Share of core input suppliers (level R2) whose headquarter is located in the local area (e.g. for Parmigiano-Reggiano, the number of milk producers located in the local area)
R1_NCI_LAkey%% of NCI suppliers (level R2) whose headquarter is located in the local area
food&Bcomplementary%% of the total household income spent for food and beverage
home&Rcomplementary%% of the total household income spent for home rent
fuel&Ecomplementary%% of the total household income spent for fuel and energy
home_forniturecomplementary%% of the total household income spent for home furniture
transportcomplementary%% of the total household income spent for transport
dressingcomplementary%% of the total household income spent for dressing
free_timecomplementary%% of the total household income spent for free times
others_expendcomplementary%% of the total household income spent for others
food&B_LAkey%% of the total household income spent IN local area for food and beverage
home&R_LAkey%% of the total household income spent IN local area for home rent
fuel&E_LAkey%% of the total household income spent IN local area for fuel and energy
home_forniture_LAkey%% of the total household income spent IN local area for home furniture
transport_LAkey%% of the total household income spent IN local area for transport
dressing_LAkey%% of the total household income spent IN local area for dressing
free_time_LAkey%% of the total household income spent IN local area for free times
others_expend_LAkey%% of the total household income spent IN local area for others
R2_1_NCinputXcomplementary%% of the non-core input R2.X suppliers (level R2) located IN local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_2_NCinputXkey%% of the non-core input R2.X to level R1 cost on the total cost of the non-core inputs (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_3_NCinputXkey%% of the non-core input R2.X to level R1 cost due to labour sustained by suppliers R2 (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_4_NCinputXcomplementary%% of the non-core input R2.X to level R1 cost due to other inputs (labour excluded) sustained by suppliers R2 (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_5_NCinputXkey%% of labour costs related to R2 suppliers of the input R2.X with HQ IN the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_6_NCinputXkey%% of labour costs related to R2 suppliers of the input R2.X spent IN local area by suppliers R2 located IN the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_7_NCinputXkey%% of other inputs costs (labour excluded) related to suppliers of the input R2.X with HQ IN the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_8_NCinputXkey% % of other inputs costs (labour excluded) for the input R2.X spent IN local area by suppliers located IN the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_9_NCinputXcomplementary%% of labour costs related to suppliers of the input R2.X with HQ OUTSIDE the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_10_NCinputXkey%% of labour costs for the input R2.X spent IN local area by suppliers located OUTSIDE the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_11_NCinputXcomplementary%% of other inputs costs (labour excluded) related to suppliers of the input R2.X with HQ OUTSIDE the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_12_NCinputXkey%% of other inputs costs (labour excluded) for the input R2.X spent IN local area by suppliers located OUTSIDE the local area (where “X” stands for each non-core input, e.g. electric power, fuel, transport, storage, etc.)
R2_inputXkey%% of input R3.X on the total cost sustained by the core input supplier (where “X” stands for each input, e.g. for producing milk farmers sustain costs for feed, veterinary, electricity, etc.)
R2_1_inputXkey%% of input R3.X cost spent IN local area by the core input supplier (where “X” stands for each input, e.g. for producing milk farmers sustain costs for workers (family labour included), feed, veterinary, electricity, etc.)

References

Balamou, E., and D. Psaltopoulos. 2006. “Nature of Rural-Urban Interdependencies and Their Diffusion Patterns in Southern Greece: An Interregional SAM Model.” Review of Urban & Regional Development Studies 18: 60–83, https://doi.org/10.1111/j.1467-940X.2006.00110.x.Search in Google Scholar

Barczak, A., V. Bellassen, F. Arfini, R. Brečić, G. Giraud, E. Majewski, B. Tocco, A. Tregear, and G. Vittersø. 2016. Selection of Case Study Regions and Cases for Impact Analysis. Strength2Food - Deliverable 3.3. https://www.strength2food.eu/2016/11/29/selection-.Search in Google Scholar

Bellassen, V., M. Drut, F. Antonioli, R. Brečić, A. Diallo, M. Donati, H. Ferrer-López, L. Gauvrit, V. Hoang, K. Knutsen Steinnes, A. Lilavanichakul, E. Majewski, A. Malak-Rawlikowska, K. Mattas, A. Nguyen, I. Papadopoulos, J. Peerlings, B. Ristic, M. Tomić Maksan, A. Török, and G. Vittersø. 2020 Submitted for publication. “The Carbon and Land Footprint of Certified Food Products.” JAFIO.10.1515/jafio-2019-0037Search in Google Scholar

Bellassen, V., G. Giraud, M. Hilal, F. Arfini, A. Barczak, A. Bodini, M. Brennan, M. Drut, M. Gorton, E. Majewski, P. Muller, B. Tocco, A. Tregear, M. Veneziani, and G. Vitterso. 2016. Methods and Indicators for Measuring the Social, Environmental and Economic Impacts of Food Quality Schemes, Short Food Supply Chains and Varying Public Sector Food Procurement Policies on Agri-Food Chain Participants and Rural Territories. Strength2Food - Deliverable 3.2. https://www.strength2food.eu/2016/10/03/methodological-handbook/.Search in Google Scholar

Bengo, I., M. Arena, G. Azzone, and M. Calderini. 2016. “Indicators and Metrics for Social Business: A Review of Current Approaches.” Journal of Social Entrepreneurship 7: 1–24, https://doi.org/10.1080/19420676.2015.1049286.Search in Google Scholar

Bramley, C., and J. F. Kirsten. 2007. “Exploring the Economic Rationale for Protecting Geographical Indicators in Agriculture.” Agrekon 4(1), https://doi.org/10.1080/03031853.2007.9523761.Search in Google Scholar

Březina, D., and P. Hlaváčková. 2016. “Quantification of the Influence of the Training Forest Enterprise Masaryk Forest Křtiny on the Local Economy of the Region.” Journal of Forest Science 62: 245–52, https://doi.org/10.17221/117/2015-JFS.Search in Google Scholar

Burke, C., and A. King. 2015. “Generating Social Value through Public Sector Construction Procurement.” In Proceedings of the 31st Annual Conference - Association of Researchers in Construction Management (ARCOM), edited by A. Raidén, and E. Aboagye-Nimo, 387–96. Reading: ARCOM, Association of Researchers in Construction Management.Search in Google Scholar

Cei, L., E. Defrancesco, and G. Stefani. 2018. “From Geographical Indications to Rural Development: A Review of the Economic Effects of European Union Policy.” Sustainable Times, https://doi.org/10.3390/su10103745.Search in Google Scholar

Chaddad, F. R., and M. P. Mondelli. 2013. “Sources of Firm Performance Differences in the US Food Economy.” Journal of Agricultural Economics 64: 382–404, https://doi.org/10.1111/j.1477-9552.2012.00369.x.Search in Google Scholar

Courtney, P., and A. Errington. 2000. “The Role of Small Towns in the Local Economy and Some Implications for Development Policy.” Local Economy 15: 280–301, https://doi.org/10.1080/026909400750068013.Search in Google Scholar

Courtney, P., L. Mayfield, R. Tranter, P. Jones, and A. Errington. 2007. “Small Towns as “Sub-poles” in English Rural Development: Investigating Rural-Urban Linkages Using Sub-regional Social Accounting Matrices.” Geoforum 38: 1219–32, https://doi.org/10.1016/j.geoforum.2007.03.006.Search in Google Scholar

Courtney, P., J. Mills, P. Gaskell, and S. Chaplin. 2013. “Investigating the Incidental Benefits of Environmental Stewardship Schemes in England.” Land Use Policy 31: 26–37, https://doi.org/10.1016/j.landusepol.2012.01.013.Search in Google Scholar

Dowler, E., M. Caraher, S. Michaels, N. Diamond, E. Delow, and C. Cousens. 2003. The Value and Potential of Local Food Initiatives in the West Midlands Region A Report to Advantage West Midlands Woodland f3-the Foundation for Local Food Initiatives. https://www.researchgate.net/profile/Elizabeth_Dowler/publication/255653937_The_Value_and_Potential_of_Local_Food_Initiatives_in_the_West_Midlands_Region/links/00b7d53a878c3c316e000000/The-Value-and-Potential-of-Local-Food-Initiatives-in-the-West-Midlands.Search in Google Scholar

European Commission. 2019. Study on Economic Value of EU Quality Schemes, Geographical Indications (GIs) and Traditional Specialities Guaranteed (TSGs). Brussels: Publications Office of the European Union. https://op.europa.eu/en/publication-detail/-/publication/a7281794-7ebe-11ea-aea8-01aa75ed71a1.Search in Google Scholar

Feldmann, C., and U. Hamm. 2015. “Consumers’ Perceptions and Preferences for Local Food: A Review.” Food Quality and Preference 40: 152–64, https://doi.org/10.1016/j.foodqual.2014.09.014.Search in Google Scholar

Goodman, D. 2004. “Rural Europe Redux? Reflections on Alternative Agro-Food Networks and Paradigm Change.” Sociologia Ruralis 44 (1): 3–16, https://doi.org/10.1111/j.1467-9523.2004.00258.x.Search in Google Scholar

Harrison, L. 1993. “The Impact of the Agricultural Industry on the Rural Economy – Tracking the Spatial Distribution of the Farm Inputs and Outputs.” Journal of Rural Studies 9 (1): 81–8, https://doi.org/10.1016/0743-0167(93)90007-7.Search in Google Scholar

Hyytiä, N. 2014. “Rural-Urban Multiplier and Policy Effects in Finish Rural Regions: An Inter-regional Sam Analysis.” European Countryside 6: 179–201, https://doi.org/10.2478/euco-2014-0010.Search in Google Scholar

Johns, P. M., and P. M. K. Leat. 1987. “The Application of Modified GRIT Input‐output Procedures to Rural Development Analysis in Grampian Region.” Journal of Agricultural Economics 38: 242–56, https://doi.org/10.1111/j.1477-9552.1987.tb01044.x.Search in Google Scholar

Kilkenny, M. 1998. “Transport Costs and Rural Development.” Journal of Regional Science 38 (2): 293–312, https://dx.doi.org/10.1111/1467-9787.00093.10.1111/1467-9787.00093Search in Google Scholar

Kitchen, L., and T. Marsden. 2009. “Creating Sustainable Rural Development through Stimulating the Eco-Economy: Beyond the Eco-Economic Paradox?” Sociologia Ruralis 49 (3): 273–94, https://doi.org/10.1111/j.1467-9523.2009.00489.x.Search in Google Scholar

Leontief, W. 1974. “Structure of the World Economy Outline of a Simple Input-Output Formulation.” The American Economic Review 64 (6): 823–34.10.2307/3439247Search in Google Scholar

Lobley, M., A. Butler, and M. Reed. 2009. “The Contribution of Organic Farming to Rural Development: An Exploration of the Socio-Economic Linkages of Organic and Non-organic Farms in England.” Land Use Policy 26: 723–35, https://doi.org/10.1016/j.landusepol.2008.09.007.Search in Google Scholar

Mancini, M. C., and F. Arfini. 2018. “Short supply Chains and Protected Designations of Origin: The Case of Parmigiano Reggiano (Italy).” Ager 2018(25): 43–64, https://doi.org/10.4422/ager.2018.11.Search in Google Scholar

Marasteanu, I. J., and E. C. Jaenicke. 2018. “Renewable Agriculture and Food Systems Economic Impact of Organic Agriculture Hotspots in the United States.” Renewable Agriculture and Food Systems: 1–22, https://doi.org/10.1017/S1742170518000066.Search in Google Scholar

Marsden, T., J. Banks, and G. Bristow. 2000. “Food Supply Chain Approaches: Exploring Their Role in Rural Development.” Sociologia Ruralis 40: 424–38. https://doi.org/10.1111/1467-9523.00158.Search in Google Scholar

McDonald, A., and P. Boden. 2012. Northern Gas Network: Regional Economic Impact. Leeds: Edge Analytics. https://www.northerngasnetworks.co.uk/wp-content/uploads/2017/04/Appendix20-Regional-Economic-Impacts.pdf.Search in Google Scholar

Mitchell, A. 2017. The Local Economic Multiplier Effect of edibLE16: A Supply Chain Survey. https://sustainableharborough.co.uk/wp-content/uploads/2019/05/SH-project-report-edibLE16-LM3-2017.pdf.Search in Google Scholar

Mitchell, A., and M. Lemon. 2019. “Using the LM3 Method to Evaluate Economic Impacts of an On-line Retailer of Local Food in an English Market Town.” Local Economy 34: 51–67. https://doi.org/10.1177/0269094219826569.Search in Google Scholar

Moretti, E. 2010. “Local Multipliers.” The American Economic Review 100: 1–7. https://doi.org/10.1257/aer.100.2.373.Search in Google Scholar

Morris, C., and H. Buller. 2003. “The Local Food Sector: A Preliminary Assessment of its Form and Impact in Gloucestershire.” British Food Journal 105 (8): 559–66, https://doi.org/10.1108/00070700310497318.Search in Google Scholar

Pangbourne, K., and D. Roberts. 2015. “Small Towns and Agriculture: Understanding the Spatial Pattern of Farm Linkages.” European Planning Studies 23: 494–508. https://doi.org/10.1080/09654313.2013.872231.Search in Google Scholar

Pieters, J. 2010. “Growth and Inequality in India: Analysis of an Extended Social Accounting Matrix.” World Development 38: 270–81. https://doi.org/10.1016/j.worlddev.2009.09.006.Search in Google Scholar

Potts, D. 2008. “Assessing the Impact of Regeneration Spending: Lessons from the United Kingdom and the Wider World.” Education, Knowledge & Economy 2: 213–22. https://doi.org/10.1080/17496890802426238.Search in Google Scholar

Psaltopoulos, D., E. Balamou, and K. J. Thomson. 2006. “Rural-Urban Impacts of CAP Measures in Greece: An Inter-regional SAM Approach.” Journal of Agricultural Economics 57: 441–58. https://doi.org/10.1111/j.1477-9552.2006.00059.x.Search in Google Scholar

Raimondi, V., D. Curzi, F. Arfini, A. Olper, and M. Aghabeygi. 2018. “Evaluating Socio-Economic Impacts of PDO on Rural Areas.” In 7th AIEAA Conference “Evidence-Based Policies to Face New Challenges for Agri-Food Systems.Search in Google Scholar

Renting, H., T. K. Marsden, and J. Banks. 2003. “Understanding Alternative Food Networks: Exploring the Role of Short Food Supply Chains in Rural Development.” Environment & Planning A 35: 393–411. https://doi.org/10.1068/a3510.Search in Google Scholar

Roberts, D. 1998. “Rural-Urban Interdependencies: Analysis Using an Inter-regional SAM Model.” European Review of Agricultural Economics 25: 506–27. https://doi.org/10.1093/erae/25.4.506.Search in Google Scholar

Robison, M. H. 1997. “Community Input-Output Models for Rural Area Analysis with an Example from Central Idaho.” The Annals of Regional Science 31: 325–351. https://doi.org/10.1007/s001680050052.Search in Google Scholar

Round, J. 2003. “Social Accounting Matrices and SAM-based Multiplier Analysis.” In Techniques and Tools for Evaluating the Poverty Impact of Economic Policies, edited by F. Bourguignon, andL.A.P. da Silva, 301–24. Washington, DC.Search in Google Scholar

Sacks, J. 2002. The Money Trail: Measuring Your Impact on the Local Economy Using LM3. London: New Economics Foundation.Search in Google Scholar

Sckokai, P., C. Soregaroli, and D. Moro. 2013. “Estimating Market Power by Retailers in a Dynamic Framework: The Italian PDO Cheese Market.” Journal of Agricultural Economics 64 (1): 33–53, https://doi.org/10.1111/j.1477-9552.2012.00368.x.Search in Google Scholar

Slee, B. 2006. “The Socio-economic Evaluation of the Impact of Forestry on Rural Development: A Regional Level Analysis.” Forest Policy and Economics 8: 542–54. https://doi.org/10.1016/j.forpol.2005.07.006.Search in Google Scholar

Smithers, J., J. Lamarche, and A. E. Joseph. 2008. “Unpacking the Terms of Engagement with Local Food at the Farmers’ Market: Insights from Ontario.” Journal of Rural Studies 24: 337–50. https://doi.org/10.1016/j.jrurstud.2007.12.009.Search in Google Scholar

Stahmer, C. 2004. “Social Accounting Matrices and Extended Input-Output Tables.” In Measuring Sustainable Development: Integrated Economic, Environmental and Social Frameworks, 313–44. Paris: OECD Publishing.10.1787/9789264020139-21-enSearch in Google Scholar

Thatcher, J., and L. Sharp. 2008. “Measuring the Local Economic Impact of National Health Service Procurement in the UK: An Evaluation of the Cornwall Food Programme and LM3.” Local Environment 13: 253–70. https://doi.org/10.1080/13549830701669005.Search in Google Scholar

Tregear, A., F. Arfini, G. Belletti, and A. Marescotti. 2007. “Regional Foods and Rural Development: The Role of Product Qualification.” Journal of Rural Studies 23: 12–22. https://doi.org/10.1016/j.jrurstud.2006.09.010.Search in Google Scholar

USDA. 2008. “Farm and Household Interaction with Local and Regional Economies.” In Agricultural Income and Finance Outlook. USDA Economic Research Service, 68–71. https://downloads.usda.library.cornell.edu/usda-esmis/files/w0892992w/wh246t71n/08612q19q/AIS-12-10-2008.pdf.Search in Google Scholar

van der Ploeg, J. D., H. Renting, G. Brunori, K. Knickei, J. Mannion, T. Marsden, K. de Roest, E. Sevilla-Guzmán, and F. Ventura. 2018. “Rural Development: From Practices and Policies towards Theory.” The Rural Times 40: 201–18. https://doi.org/10.4324/9781315237213-11.Search in Google Scholar

van der Zanden, E. H., P. H. Verburg, C. J. E. Schulp, and P. J. Verkerk. 2017. “Trade-offs of European Agricultural Abandonment.” Land Use Policy 62: 290–301. https://doi.org/10.1016/j.landusepol.2017.01.003.Search in Google Scholar

Vandecandelaere, E. 2014. “Geographical Indication as a Tool for Sustainable Food Systems: Importance of a Territorial Approach.” In Voluntary Standards for Sustainable Food Systems: Challenges and Opportunities, 93–104. Rome: FAO.Search in Google Scholar

Vandecandelaere, E., F. Arfini, G. Belletti, and A. Marescotti. 2010. Linking People, Places and Products. A Guide for Promoting Quality Linked to Geographical Origin and sustainable Geographical Indications. Rome: Quality. FAO.Search in Google Scholar

Wiedmann, T. 2009. “A Review of Recent Multi-Region Input-Output Models Used for Consumption-Based Emission and Resource Accounting.” Ecological Economics 69 (2): 211–22, https://doi.org/10.1016/j.ecolecon.2009.08.026.Search in Google Scholar

Received: 2019-09-30
Accepted: 2020-10-22
Published Online: 2020-11-13

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