Agrifood Safety Standards, Market Power, and Consumer Misperceptions

Abstract

This article analyzes how the public regulation of food safety influences a firm's strategic behaviour in a food chain. In this context, we provide an original theoretical framework to show how, regardless of the level of standard, food safety regulation may have unexpected harmful effects. Namely, the level of compliance costs alone cannot explain the producer exclusion due to a high level of standard. We highlight how upstream producers' involvement in the market also depends on the strategic interest of the downstream firm to remunerate their compliance process. Finally, we show how the actual level of risk does not necessarily decrease when the standard is reinforced.

KEYWORDS:

• Food safety standards
• market power
• risk misperception

Notes

1. In this sense, our article differs from the above-mentioned literature (Caswell & Kleinschmit, 1997; Antle, 2001, Viscusi, 2006). These contributions mainly examine the effects of public regulation through the concept of compliance costs, which are considered to directly determine the degree of producer exclusion from the market: the more the standard constrains, the higher the risk of the exclusion of producers from the market.

2. Food safety standards often require specific procedures related to field hygiene, worker safety, record keeping, environmental quality and traceability. Furthermore, empirical evidence shows that infrastructure issues and the use of information technology represent the most relevant compliance effort, for small-scale producers (see for example, OCDE, 2007). The equipment level can be interpreted as the value of the initial infrastructure of a producer (or as the cost associated with the equipment's introduction). The assumption of equipment continuity is a mathematical device considered for the sake of simplicity, which does not have any influence on the qualitative results of the model.

3. For an illustration of this heterogeneity in the empirical literature, see Kleinwechter and Grethe (2006).

4. This assumption is justified by empirical evidence in the agrifood sector, where the characteristics of inputs largely affect the quality and safety of the final product. See for example FAO (2007) for an analysis of the sources of contamination in the fruit and vegetable sector. See also Bastianelli and Le Bas (2000) for an analysis of the influence of animal feed as one of the main factors influencing the sanitary quality of the final product.

5. Indeed, consumers are indirectly informed about the risk reduction through a communication concerning the brands or private labels, which are based on the definition of specific production conditions, concerning quality and safety attributes of the inputs. There exist several examples of these “selection brands,” where the downstream processing and/or retailing firm communicates to consumers the product's quality, issued from its selection strategy toward upstream producers and from the quality of the inputs, see for example the high-quality retailers' brands like Engagement Qualité Carrefour or the procedures developed in the meat sector by Sainsbury, Marks, and Spencer or Tesco (Giraud-Héraud, Rouached, & Soler, 2006; Bazoche, Giraud-Héraud, & Soler, 2005; Fearne, 1998).

6. This approach also refers to the contributions by Mitchell and McGoldrick (1996) that use the term “degree of trust” in the information provided on the product attributes. Thus, the higher is the trust the lower is the perceived risk, which may be even underestimated. Moreover, the recent works by Mazzocchi, Lobb, Traill, & Cavicchi (2008) and Lobb, Mazzocchi, & Traill (2007) highlight how the trust in the source of information about food safety may decrease the perceived risk.

7. This first assumption is obtained as follows. The final price given by (3) is positive, for any given level of quantity, if and only if α > (1 − λσl + x). Given that i) x ≤ J, ii) the contamination risk varies from 0 to 1 and iii) the degree of misperception is assumed to vary from −1 to 1, the final price is positive for any given level of quantity and for any degree of misperception considered, if and only if the parameter α is sufficiently high, that is: α > J + 2l.

8. Even if a few contributions consider an endogenous choice of the MQS (see Ecchia & Lambertini, 1997), the choice of the criterion for determining the MQS is a very complex issue. Hence, several criteria exist for the definition of a MQS, especially in the agricultural sector. In addition to the traditional criteria of maximization of social welfare, other criteria could represent the public authority's concerns, such as the minimization of the risk, especially in the case of product safety, or the minimization of upstream producer exclusion.

9. We have voluntarily left out the explicit formalization of the intermediation ensured by the Producers Organization, with which the downstream firm negotiates (as shown by empirical evidence). Indeed, taking into account this intermediary in the model would not change the analysis or the qualitative results.

10. Figures 1–7 represent the mechanisms behind each proposition; simulations have been made according to values of the parameters (J, α, l, λ), which are consistent with (HP1) - (HP3). In Figures 1–5, the Benchmark situation refers to the absence of standard and is thus represented by the case e_s = 0.

11. The possible quality-reducing effect of a standard has been widely illustrated by the literature on MQS. See for example Scarpa (1998), who shows that if a MQS is introduced in a vertically differentiated market with three firms, then the maximum quality level, the average quality consumed as well as the profit levels of all firms decrease. In this spirit, Maxwell (1998) illustrates that a MQS may reduce firm incentives to innovate—when the innovating firm correctly anticipates that a regulator will raise the minimum standard once an innovation has been discovered—leading to a lower level of social welfare under regulation. Furthermore, the introduction of “innocuous” minimum quality standards, namely below the lowest quality level in a market, may reduce the incentive to invest in R&D by the quality-leading firm (Garella, 2006).

12. By calculating the Lerner index, we can verify how the implementation of the standard affects the market power of the downstream firm. Namely, a reinforcement of the standard (switching from moderate to strong regulation) reduces the market power of the downstream firm.

13. Several contributions analyze the substitutability and complementarities of these two regulatory tools as means of controlling externality-creating activities (see for example, Shavell, 1984; Kolstad, Ulen, & Johnson, 1990;Schmitz, 2000; Innes, 2004). Nevertheless, except for a few contributions (see Hiriart, Martimort, & Pouyet, 2004, Boyer & Porrini, 2004), the market dimension and the role of vertical relationships are often neglected.

14. This result departs from an accepted idea, which is generally put forward by the traditional economic literature; see Henson and Heasman, 1998; Henson and Caswell, 1999.