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Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Framework Consumers choices and a willingness to pay for Auvergne cheeses under PDO label. An empirical analysis. Umr Territoires,


  1. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Framework Consumer’s choices and a willingness to pay for Auvergne cheeses under PDO label. An empirical analysis. Umr Territoires, IRSTEA-Clermont Jeannot Ngoulma - Doctorant 3e année  Juin  1/16 Jeannot Ngoulma - Doctorant 3e année

  2. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Framework context In 2011, 970 products registered under PDO or PGI (465 PGI and 505 PDO) by the European Commission 45 PDO cheeses, with 5 in the former region of Auvergne Since 2000, Tonnage of French PDO cheeses is stable (190,000 tons, with a turnover of about 1.4 billion euros) Unfortunately, Auvergne PDO cheeses do not have the same stability at the French national level (Baisse des volumes commercialisés de 46 075 à 40 555 tonnes (-12%)) Regional strategy (3 levers) [code of practise, Marketing Effort, Compulsory voluntary contribution] But... 1/16 Jeannot Ngoulma - Doctorant 3e année

  3. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Framework context Auvergne PDO cheeses face many difficulties in terms of price and volumes sold compared to PDO and no-PDO These difficulties, which can be qualified as the “curse of the Auvergne PDO cheeses” Despite these efforts the Auvergne PDO cheeses still has mitigate results It seems that a consumer forsakes these Auvergne PDO cheeses for other PDO or no-PDO cheeses from other regions What are the determinants of choice of consumption and what is the willingness to pay of consumers ? 2/16 Jeannot Ngoulma - Doctorant 3e année

  4. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Empirical studies Krystallis and Ness (2005) "olive oil from Greece". Age, the education and the income Scarpa and Del Giudice (2004) "extra virgin olive oil from Italy". Appearance, price, geographical origin Van der Lans, Van Ittersum et al. (2001) "extra virgin olive oil". Price, the color and the appearance" 3/16 Jeannot Ngoulma - Doctorant 3e année

  5. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Empirical studies Bonnet and Simioni (2001) "Camembert cheeses from France" Cavicchi, Bailetti et al. (2010) "Cheese Pecorino di Fossa from Italy" Hassan, Monier-Dilhan et al. (2011) "21 cheeses from France" Gracia and de-Magistris (2016). "cheese from Spain". Female, older, a university-level education 4/16 Jeannot Ngoulma - Doctorant 3e année

  6. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Data Kantar Worldpanel (2008-2010), about 20 000 French households We merge data 58 199 acts of purchases of Auvergne PDO cheeses Following Bonnet and Simioni (2001) 5/16 Jeannot Ngoulma - Doctorant 3e année

  7. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Destriptive staistics 6/16 Jeannot Ngoulma - Doctorant 3e année

  8. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Models random utility model (RUM) Mixed logit Model (MXL) Does not take into account the Independence of Irrelevant Alternatives (IIA) 1 assumption Authorize a distribution of preferences among the population rather than identifying 2 only the average preference Nested logit Model(NL) Does not take into account the Independence of Irrelevant Alternatives (IIA) 1 assumption It allow us to group the modalities into several nests 2 7/16 Jeannot Ngoulma - Doctorant 3e année

  9. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Econometric specifications Model 1 : Mixed logit equation Choice Mixed = α i + β price Price + β nit X + β nit Z + ε nit We deduce WTP WTP k = − β k β price Model 2 : Nested logit equation Choice Nested = α i + β price Price + β nit X + β nit Z + ε nit X : income, age, nberind, CDI, CDD, gender, Single, Couple, Primary-Educ, Secondary-Educ, Superior-Educ Z : Supermarket, Hypermarket, Hard-Discount, Creamer, MDD, sale-promo, Mat-Grasse, Auvergne 8/16 Jeannot Ngoulma - Doctorant 3e année

  10. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Mixed logit results 9/16 Jeannot Ngoulma - Doctorant 3e année

  11. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Mixed logit results ( continued) 10/16 Jeannot Ngoulma - Doctorant 3e année

  12. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Mixed logit results ( continued) 11/16 Jeannot Ngoulma - Doctorant 3e année

  13. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Willingness to Pay 12/16 Jeannot Ngoulma - Doctorant 3e année

  14. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Comparaison 13/16 Jeannot Ngoulma - Doctorant 3e année

  15. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Nesting structure for the choice of cheese (1 743 896 observations) 14/16 Jeannot Ngoulma - Doctorant 3e année

  16. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Nested logit results 15/16 Jeannot Ngoulma - Doctorant 3e année

  17. Introduction Literature review Descriptive statistics Theoritical Background Empirical Specifications Results Nested logit results ( continued ) 16/16 Jeannot Ngoulma - Doctorant 3e année

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