MétaCan
Menu
Back to cohort
Record W4287626514 · doi:10.5281/zenodo.5161247

Assessment of price formation and market power along the food chains

2020· report· en· W4287626514 on OpenAlexaboutno aff
Miranda Svanidze, Lukáš Čechura, Ivan Đurić, Tinoush Jamali Jaghdani, G. Ólafsdóttir, Maitri Thakur, Antonella Samoggia, Gianandrea Esposito, Margherita Del Prete

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
FundersLeibniz-GemeinschaftEuropean Commission
KeywordsMarket powerPower (physics)BusinessAgricultural economicsCommerceEconomicsIndustrial organizationFood scienceMicroeconomicsChemistryThermodynamics

Abstract

fetched live from OpenAlex

The aim of this report is to provide insights into price dynamics and power relationships between actors of selected Food Value Chains (FVC). Following the main focus of the VALUMICS project, provided analysis refers to salmon, tomato, dairy and wheat case studies in selected EU and non-EU countries. The analysis presented in this deliverable greatly rely on the previous deliverables (e.g. BARLING and GRESHAM, 2019, Deliverable D5.1) and work conducted in the project, and will further be used as an input for proceeding work packages that focus on quantitative modelling and foresight exercises. Thus, results presented in this report should be considered as a piece of a large puzzle that aims to provide an in-depth understanding of food value chains and network dynamics under the VALUMICS project (www.valumics.eu). <br> 2. The report is structured in a way to cover both price transmission and market power analysis for each case study separately. Thus, the results are presented under four main sections referring to a specific case study. The section on methodology is kept separately as the same price transmission, and market power methodology has been used for each case study. <br> 3. For the salmon case study, the aim was to analyse the transmission of price changes along the FVC, which in this case presents a global value chain, from Norway towards most important EU importing countries, i.e. France and Poland. France is one of the biggest consumers of salmon in Europe, while Poland is the largest secondary salmon processing country in the EU. Both countries have significantly different structures of their domestic salmon FVCs which was also in the focus of the analysis. The price transmission results indicate that the salmon export price in Norway influences price formation in both France and Poland. Within the French salmon fillet market, the retail sector dominates price formation. It has a strong influence on the prices at the secondary processing level, which sometimes might result in squeezed margins for the processing companies. In contrast, the retail market is disintegrated with the domestic wholesale market in Poland as the latter is exclusively focused on the re-export of processed salmon, where most of the processing companies are directly owned by Norwegian salmon producing companies. Concerning the market power analysis, the results indicate a certain level of market imperfectness. Nevertheless, identified results significantly vary depending on the current economic/political or natural events (e.g. distribution of licenses, Russian import ban, different diseases affecting salmon production, etc.). <br> 4. For the processed tomato case study, the main focus is on price relationships and market imperfections along the processed tomato value chain. As Italy is the largest processed tomato producer in Europe, as well as the largest exporter of processed tomato products, the analysis is primarily conducted for the north Italian processed tomato value chain. The results indicate that the upstream actors of the chain, i.e. producers and processors aim at strengthening market concentration and social collaboration through Inter-Branch Organisation (IBO), ensuring higher competitiveness and sustainability through a mutual agreement that is beneficial for all. This was confirmed by both price developments and margins obtained by producers and processors after 2011 and establishment of the IBO, and in the reduction of market power imbalances between them. The results further indicate that price dynamics present at the producer and processing levels are not reflected on the retail level. This fact was confirmed again by identifying the price margin that is three times higher for the wholesale-retail level compared to wholesale-producer level. One of the reasons might be that retailers are not part of the IBO, and the price-setting mechanism is entirely different. Most of the retail purchases go through auctions where processors usually need to squeeze their margins during the negotiation process. Overall, the tomato processing case analysed in the present research shows that the sustainability, integrity and resilience of the chain are related to the managerial governance of the chain. Thus, chain actors can contribute to finding a balance between competition and collaboration, so to aim for all chain actors’ higher level of competitiveness. <br> 5. For the dairy case study, the main focus is on getting the in-dept understanding of price dynamics and market imperfections for the three largest milk producers in the EU. Thus, the analysis considers dairy value chains in Germany, France and the UK. Understanding developments in these markets would greatly reflect the EU dairy sector in general. The obtained results indicate that milk producers face a negative price/cost ratio in the long-run, indicating that they don’t have strong bargaining power towards processors. One of the reasons could be that producer could act as shareholders of the cooperatives involved in milk processing, and thus have completely different incentives when it comes to the purchased milk price level. Concerning price dynamics along the value chain, the results indicate that changes in raw milk producer prices are almost completely transmitted towards wholesale butter and cheese prices. The short-run price dynamics show that raw milk prices are faster in adjusting the disequilibrium with the wholesale skim milk powder (SMP) prices compared to other dairy products. The results of market imperfection analysis indicate a certain level of oligopsony and oligopoly at different levels of the dairy value chains in all three countries, especially between producers and processor. <br> 6. For the wheat case study, the analysis refers to the integration of the French wheat market with the world market, primarily focusing on integration with the Black Sea countries that are emerging as global leaders in wheat export. The results confirm that, when it comes to price formation, the French market is the leading wheat market transmitting price signals to other markets in Russia, Ukraine, Canada, the USA and Argentina. Furthermore, despite being leaders in wheat export volumes, the Black Sea wheat prices in Russia and Ukraine are adjusting to price changes in France, the USA and Canada. One of the main assumptions is that creation of the futures exchange in the Black Sea region might significantly change the current situation on the global wheat market where consequently France might lose its dominant price formation role. Concerning the analysis of market power along the French and UK wheat value chains, the results indicate a certain degree of market imperfections for milling and bakery industries in both countries. Higher market imbalances are identified for the French milling industry compared to the UK case. Similar results are obtained for the baking industry in both countries. <br> 7. Overall, it is difficult to draw some general conclusions as each case study refers to the specific commodity, with considerably different underlying governance structures of the respective value chains. There is some evidence that producers tend to have better bargaining power in the value chains characterised with strong cooperation (coordination) on the upstream level (e.g. processed tomato and salmon case studies). On the other side, strong integration of the value chains on the upstream level, inevitably lead towards some sort of market imperfections that usually result in an unfavourable position for producers (e.g. dairy and wheat case studies).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.248
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicGlobal Trade and CompetitivenessFrench-language works237,207