An empirical framework to study food labelling fraud: an application to the Italian extra‐virgin olive oil market

The mislabelling of agricultural and food products is one of the most common types of food fraud. Despite the frequency with which labelling fraud occurs, there is no empirical framework to study its welfare implications, the probability that it may occur, and the measures that can limit its occurre...

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Bibliographic Details
Published inThe Australian journal of agricultural and resource economics Vol. 63; no. 4; pp. 701 - 725
Main Authors Bimbo, Francesco, Bonanno, Alessandro, Viscecchia, Rosaria
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.10.2019
Subjects
Computer simulation
counterfactual simulation
Descriptive labeling
Economic models
extra‐virgin olive oil
Fines
firm misconduct
Food
food fraud
Food production
Fraud
Labeling
Labelling
Labels
mislabelling
Oils & fats
Olive oil
Overpayments
Sales
Simulation
Supermarkets
Welfare
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Summary:The mislabelling of agricultural and food products is one of the most common types of food fraud. Despite the frequency with which labelling fraud occurs, there is no empirical framework to study its welfare implications, the probability that it may occur, and the measures that can limit its occurrence. We present an empirical framework to study the economic consequences of food labelling fraud in a differentiated products food market. Such framework requires the availability of sales data and the use of an ‘attribute‐space' demand model. The model is applied to the Italian extra‐virgin olive oil market to simulate the occurrence of fraudulent ‘100 per cent Italian' claims. Our results indicate that potential consumer losses due to overpayments for a false claim are higher than manufacturer gains, suggesting that labelling fraud results in welfare losses and not just in welfare transfers. Simulation results indicate that the level of the current administrative fines is not likely to be effective to discourage ‘100 per cent Italian' labelling fraud. Imposing larger fines or other measures negatively affecting a firm's image could be more effective in deterring labelling fraud.
Bibliography:The authors gratefully acknowledge partial funding from the Agricultural Experiment Station of Colorado State University. The authors would like to thank the participants to the AEM and FAMPS track session on ‘Food Fraud: Economic Analysis of Fraud in Supply Chains and Consumer Behaviour' at the 2017 AAEA Meetings in Chicago, IL, and participants at the 2018 LV SIDEA meeting in Perugia, Italy, for comments received on previous versions of this work. We thank the Guest Editor, Mariah Ehmke, and one anonymous referee for comments that have contributed to improve this manuscript. Any opinions or errors are strictly the authors.
Bimbo and Bonanno share senior authorship of this work.
ISSN:1364-985X
1467-8489
DOI:10.1111/1467-8489.12318