1. Parc Mediterrani de la Tecnologia Edifici ESAB Carrer Esteve Terradas, 8 08860 Castelldefels, Barcelona CONSUMERS’ WINE PREFERENCES IN A CHANGING SCENARIO: A GENERALIZED MULTINOMIAL LOGIT APPROACH Cristina ESCOBAR, Zein KALLAS & José María GIL X CONGRESO NACIONAL DE ECONOMÍA AGRARIA “Alimentación y territorios sostenibles desde el sur de Europa”. September 9 th to 11 th, 2015. Córdoba, Spain. CREDA – UPC – IRTA Centre for Agro-food Economy and Development Castelldefels, Barcelona (SPAIN).

2. 1.INTRODUCTION AND OBJECTIVES 1.1. Catalonia as a wine region 1.2. Socio-economic context in Catalonia 1.INTRODUCTION AND OBJECTIVES 1.1. Catalonia as a wine region 1.2. Socio-economic context in Catalonia 3. METHODOLOGY Table of contents 2. CONSUMERS’ PREFERENCES TOWARDS WINE 4. EMPIRICAL APPLICATION 4.1. Sample 4.2. Attributes and levels 4. EMPIRICAL APPLICATION 4.1. Sample 4.2. Attributes and levels 5. RESULTS AND DISCUSSION 6. CONCLUSIONS

3. 1. INTRODUCTION: Catalonia as a wine region Wine production in Spain > 42 millions Hectoliters Catalonia 3,7 millions Hectoliters Source: OIV, 2014 Source: OIV & DAAM, 2014

4. 1. INTRODUCTION: Catalonia as a wine region WINE SECTOR KEY FACTORS (1): CONSUMPTION DECREASE Source: MAGRAMA 2014

5. 1. INTRODUCTION: Catalonia as a wine region % in volume201120122013 Catalan quality wines Market share (11 DO) 28,5%28,9%29,6% Source: Nielsen panel, 2014 WINE SECTOR KEY FACTORS (2): LOW MARKET SHARE OF CATALAN DO WINES IN CATALONIA respecto al vino con DO

6. 1. INTRODUCTION: Catalonia as a wine region WINE SECTOR KEY FACTORS (3): EXPORTATION INCREASE Source: DATACOMEX 2014

7. 1. INTRODUCTION: Socio economic context in Catalonia  Market INSTABILITY (since 2007) and CRISIS (Ortega & Peñalosa, 2012)  DEVASTATING IMPACT on the EMPLOYMENT IN SPAIN: 6.2 million people unemployed in 2011 (INE, 2014)  SHARP DROP in consumption and in fixed capital investment (Carballo-Cruz, 2011)  Also consequences for the AGRO FOOD MARKET (Nielsen market trends)  Market INSTABILITY (since 2007) and CRISIS (Ortega & Peñalosa, 2012)  DEVASTATING IMPACT on the EMPLOYMENT IN SPAIN: 6.2 million people unemployed in 2011 (INE, 2014)  SHARP DROP in consumption and in fixed capital investment (Carballo-Cruz, 2011)  Also consequences for the AGRO FOOD MARKET (Nielsen market trends)

8. 1. INTRODUCTION: Socio economic context in Catalonia  POLITICAL CHANGES have also occurred in Catalonia  Members of Parliament strongly in favor of an INDEPENDENT CATALONIA increased 7,4% (elections of 2012)  Massive POPULAR MOBILIZATIONS in Catalonia after the long awaited decision of the Constitutional Court about the new Statute of Autonomy  Plus, the MAIN NATIONALIST PARTY in Catalonia (CIU), has SHIFTED from nationalism to Catalan independentism (Guibernau, M., 2013, amongst others)  POLITICAL CHANGES have also occurred in Catalonia  Members of Parliament strongly in favor of an INDEPENDENT CATALONIA increased 7,4% (elections of 2012)  Massive POPULAR MOBILIZATIONS in Catalonia after the long awaited decision of the Constitutional Court about the new Statute of Autonomy  Plus, the MAIN NATIONALIST PARTY in Catalonia (CIU), has SHIFTED from nationalism to Catalan independentism (Guibernau, M., 2013, amongst others)

9.  Thus, the OBJECTIVE of this paper is: To determine CONSUMERS’ RED WINE PREFERENCES for a special occasion and, More specifically, their CHANGES regarding the newer economic and political scenario  We applied 2 DISCRETE CHOICE EXPERIMENTS (DCE), BEFORE and DURING the economic crisis (1TBefore vs.3TDuring)  Thus, the OBJECTIVE of this paper is: To determine CONSUMERS’ RED WINE PREFERENCES for a special occasion and, More specifically, their CHANGES regarding the newer economic and political scenario  We applied 2 DISCRETE CHOICE EXPERIMENTS (DCE), BEFORE and DURING the economic crisis (1TBefore vs.3TDuring) 1. INTRODUCTION

10. 2. CONSUMERS- PREFERENCES TOWARDS WINE  Wine is a DIFFICULT AND CONFUSING product for consumers to choose  IMMENSE NUMBER OF CUES TYPE Red White Rosé Sparkling Liquored Others... COO ROO DO ROO DO BRAND PRICE PACKAGING AWARDS TASTE VINTAGE GRAPES ALCOHOL CONTENT

11. BRAND  Are capable of acting as a SURROGATE for a number of attributes (including quality) and might help address RISK while providing product cues  Consumers may use a SMALL REPERTOIRE, which may well be a collection of true brands and GENERIC TYPES GRAPE VARIETY ROO DO ROO DO 2. CONSUMERS- PREFERENCES TOWARDS WINE GENERIC TYPES

12. COUNTRY OF ORIGIN  Plays a KEY ROLE in the consumers’ decision making process, specially in wine producing countries 2. CONSUMERS- PREFERENCES TOWARDS WINE PRICE When consumers do not have information about the product, it generally performs as a PROXY to infer the quality of the product when: The product cannot be evaluated The RISK of making a wrong choice is high When consumers do not have information about the product, it generally performs as a PROXY to infer the quality of the product when: The product cannot be evaluated The RISK of making a wrong choice is high

13. RISK REDUCTION STRATEGIES Compilation of the main RRS in wine choice (Rawbone-Viljoen, 2012)  INFORMATION SEARCH [assistants, waiters, wine editorials, tasting notes, packaging, word-of-mouth, family and friends and opinion leaders]  SEEKING REASSURANCE [mainly through tastings, information seeking behaviour and prior experience]  BRAND loyalty and Well-known brands  PRICE  STORE IMAGE  INFORMATION SEARCH [assistants, waiters, wine editorials, tasting notes, packaging, word-of-mouth, family and friends and opinion leaders]  SEEKING REASSURANCE [mainly through tastings, information seeking behaviour and prior experience]  BRAND loyalty and Well-known brands  PRICE  STORE IMAGE 2. CONSUMERS- PREFERENCES TOWARDS WINE

14. 3. METHODOLOGY: The DCE: Econometric model  The basic model is THE MULTINOMIAL LOGIT MODEL (MNL).  It imposes homogeneity in preferences for observed attribute  The IIA property seldom hold.  It imposes homogeneity in preferences for observed attribute  The IIA property seldom hold.

15. 3. METHODOLOGY: The DCE: Econometric model  The Mixed Logit Model (MIXL)  Extend the MNL introducing for unobserved heterogeneity by allowing random coefficients on attributes.  Recent studies argued that much of the PREFERENCE HETEROGENEITY captured by random parameters in MIXL can be better captured by the scale term; and thus known as “SCALE HETEROGENEITY”.  The MIXL turns to be likely a POOR APPROXIMATION to stated data if scale heterogeneity is not accounted for  Extend the MNL introducing for unobserved heterogeneity by allowing random coefficients on attributes.  Recent studies argued that much of the PREFERENCE HETEROGENEITY captured by random parameters in MIXL can be better captured by the scale term; and thus known as “SCALE HETEROGENEITY”.  The MIXL turns to be likely a POOR APPROXIMATION to stated data if scale heterogeneity is not accounted for

16. 3. METHODOLOGY: The DCE: Econometric model  The Generalized Multinomial Logit Model (GMNL)  Known also as Generalized Mixed Logit Model (G-MXL).   n is a scaling factor that proportionately scales the  up or down for each individual n.   is a mixing parameter, and its value determines the level of mixing or interaction between the scale heterogeneity coefficient and the parameter heterogeneity coefficient.  Known also as Generalized Mixed Logit Model (G-MXL).   n is a scaling factor that proportionately scales the  up or down for each individual n.   is a mixing parameter, and its value determines the level of mixing or interaction between the scale heterogeneity coefficient and the parameter heterogeneity coefficient.

17. 4. EMPIRICAL APPLICATION: Sample  2 IDENTICAL SURVEYS performed in 2 DIFFERENT TIMES: BEFORE & DURING the ECONOMIC CRISIS.  2 IDENTICAL SURVEYS performed in 2 DIFFERENT TIMES: BEFORE & DURING the ECONOMIC CRISIS. BeforeDuring Population Consumers over 18 years who purchase regularly food and are residents in the metropolitan area of Barcelona. Sample Design Stratified sample by age and postal districts using proportional affixation to the number of persons by stratum. FieldMetropolitan area of Barcelona Sample Size400401 Confidence interval  4.9 ± 4,9% Confidence level95.5% (k=2) Control measurePilot survey (25 questionnaires)

18.  To reduce wine choice complexity we delimited our wine selection by focusing on a RED WINE purchased for a SPECIAL OCCASION such as Christmas.  Based on the literature and discussion groups we identified the following attributes and levels:  ORIGIN: Catalonia (regional), Spain (national), Imported (international)  WINE REFERENCES: Own Experience, Recommendation, Prestige  GRAPE VARIETY: Cabernet Sauvignon, Grenache, Merlot  PRICE: €6, €10, €14  To reduce wine choice complexity we delimited our wine selection by focusing on a RED WINE purchased for a SPECIAL OCCASION such as Christmas.  Based on the literature and discussion groups we identified the following attributes and levels:  ORIGIN: Catalonia (regional), Spain (national), Imported (international)  WINE REFERENCES: Own Experience, Recommendation, Prestige  GRAPE VARIETY: Cabernet Sauvignon, Grenache, Merlot  PRICE: €6, €10, €14 4. EMPIRICAL APPLICATION: Attributes and levels

19.  We followed the DUAL RESPONSE CHOICE EXPERIMENT design.  From the FULL FACTORIAL DESIGN using the total number of attributes and levels which led to a total of 81 hypothetical products. In a choice set of 2 alternatives we have 6,561 possible combinations.  The orthogonal fractional factorial design with only 9 CHOICE SETS.  We followed the DUAL RESPONSE CHOICE EXPERIMENT design.  From the FULL FACTORIAL DESIGN using the total number of attributes and levels which led to a total of 81 hypothetical products. In a choice set of 2 alternatives we have 6,561 possible combinations.  The orthogonal fractional factorial design with only 9 CHOICE SETS. 4. EMPIRICAL APPLICATION: Attributes and levels

20. 4. EMPIRICAL APPLICATION

21.  All attributes, including the price, were coded with EFFECT CODING as discrete variables  To avoid the base levels being CONFOUNDED WITH THE INTERCEPT  Effects of all levels can be estimated  All models were estimated by using 500 Halton draws.  All attributes, including the price, were coded with EFFECT CODING as discrete variables  To avoid the base levels being CONFOUNDED WITH THE INTERCEPT  Effects of all levels can be estimated  All models were estimated by using 500 Halton draws. 4. EMPIRICAL APPLICATION: Attributes and levels

22. BeforeDuring Random parameter estimates Spanish 2.03293***.27705 Catalan 3.80717***.73884*** Recommended -.80762**-.20509*** Prestigious -1.06844***.09827 Grenache -1.52072***-.25125 Cabernet sauvignon 1.58843***.29349** Price-10€.90290**.01346 Price-14€ -1.96268***-1.19805*** No choice -2.52462***2.86293*** Log-Likelihood (0) -3955.00-3964.89 LL ratio test 947.73 (0.000)3650.00 (.000) Pseudo R2.1198152.4602901 AIC/N 1.9651.217 Variance parameter tau in scale parameter (τ) 2.05073***.05930 Weighting parameter Gamma (γ).02924*.10052 5. RESULTS AND DISCUSSION  Both models are statistically significant and exhibited a good fit with highly significant likelihood ratios.  Consumers’ preferences are higher for the CATALAN ORIGIN of the product, for the grape variety CABERNET SAUVIGNON and, for wines that have been PREVIOUSLY EXPERIENCED Practically all SIGNIFICANT

24. BeforeDuring Random parameter estimates Spanish 2.03293***.27705 Catalan 3.80717***.73884*** Recommended -.80762**-.20509*** Prestigious -1.06844***.09827 Grenache -1.52072***-.25125 Cabernet sauvignon 1.58843***.29349** Price-10€.90290**.01346 Price-14€ -1.96268***-1.19805*** No choice -2.52462***2.86293*** Log-Likelihood (0) -3955.00-3964.89 LL ratio test 947.73 (0.000)3650.00 (.000) Pseudo R2.1198152.4602901 AIC/N 1.9651.217 Variance parameter tau in scale parameter (τ) 2.05073***.05930 Weighting parameter Gamma (γ).02924*.10052 5. RESULTS AND DISCUSSION Some levels turn into NON- SIGNIFICANT A change into positive utility for the No choice intercept might explain it In During consumers show a greater preference for not taking the product, indicating PERSISTENCE IN THE UNOBSERVED ATTRIBUTES

25. BeforeDuring Random parameter estimates Spanish 2.03293***.27705 Catalan 3.80717***.73884*** Recommended -.80762**-.20509*** Prestigious -1.06844***.09827 Grenache -1.52072***-.25125 Cabernet sauvignon 1.58843***.29349** Price-10€.90290**.01346 Price-14€ -1.96268***-1.19805*** No choice -2.52462***2.86293*** Log-Likelihood (0) -3955.00-3964.89 LL ratio test 947.73 (0.000)3650.00 (.000) Pseudo R2.1198152.4602901 AIC/N 1.9651.217 Variance parameter tau in scale parameter (τ) 2.05073***.05930 Weighting parameter Gamma (γ).02924*.10052 5. RESULTS AND DISCUSSION Common circumstances may have had a HOMOGENISING INFLUENCE  In “During” model it becomes NON-SIGNIFICANT: the VARIATION OF THE DEGREE of RANDOMNESS in their final decision and hence their degree of UNCERTAINTY DECREASED significantly.  Tau parameter (KEY PARAMETER) captures the SCALE HETEROGENEITY

26. BeforeDuring Random parameter estimates Spanish 2.03293***.27705 Catalan 3.80717***.73884*** Recommended -.80762**-.20509*** Prestigious -1.06844***.09827 Grenache -1.52072***-.25125 Cabernet sauvignon 1.58843***.29349** Price-10€.90290**.01346 Price-14€ -1.96268***-1.19805*** No choice -2.52462***2.86293*** Log-Likelihood (0) -3955.00-3964.89 LL ratio test 947.73 (0.000)3650.00 (.000) Pseudo R2.1198152.4602901 AIC/N 1.9651.217 Variance parameter tau in scale parameter (τ) 2.05073***.05930 Weighting parameter Gamma (γ).02924*.10052 5. RESULTS AND DISCUSSION  GAMMA in both models is SIGNIFICANTLY DIFFERENT from ZERO.  TASTE heterogeneity is PARTIALLY CONDITIONED to SCALE heterogeneity.  In “During” model, however, they become more INDEPENDENT (Gamma increases from 0.10 to 0.57)  GAMMA in both models is SIGNIFICANTLY DIFFERENT from ZERO.  TASTE heterogeneity is PARTIALLY CONDITIONED to SCALE heterogeneity.  In “During” model, however, they become more INDEPENDENT (Gamma increases from 0.10 to 0.57)

27. BeforeDuring Standard deviations of parameter distributions Spanish3.12735***.25613 Catalan5.09622***.59020** Recommended.23246.08569 Prestigious1.65080***.11011 Grenache1.81875***.67845 Cabernet sauvignon2.74603***.21026 Price-10€3.05442***.38428 Price-14€4.86483***.97643** No choice7.34722***.52561 5. RESULTS AND DISCUSSION Practically all SIGNIFICANT  Regarding the UNOBSERVED TASTE (PREFERENCE) HETEROGENEITY, it is captured by the standard deviation of the random parameters.

28. 5. RESULTS AND DISCUSSION Some levels turn into NON- SIGNIFICANT BeforeDuring Standard deviations of parameter distributions Spanish3.12735***.25613 Catalan5.09622***.59020** Recommended.23246.08569 Prestigious1.65080***.11011 Grenache1.81875***.67845 Cabernet sauvignon2.74603***.21026 Price-10€3.05442***.38428 Price-14€4.86483***.97643** No choice7.34722***.52561

29. 5. RESULTS AND DISCUSSION In the During model,  Spanish wine’s show a NOT SIGNIFICANT UTILITY but its TASTE HETEROGENEITY TURNS SIGNIFICANT  Catalan wines show again a SIGNIFICANTLY POSITIVE UTILITY and its TASTE HETEROGENEITY TURNS NOT SIGNIFICANT  Furthermore, the SCALE HETEROGENEITY = ZERO  CONSUMERS’ PREFERENCES TOWARDS CATALAN wines have become CLEAR In the During model,  Spanish wine’s show a NOT SIGNIFICANT UTILITY but its TASTE HETEROGENEITY TURNS SIGNIFICANT  Catalan wines show again a SIGNIFICANTLY POSITIVE UTILITY and its TASTE HETEROGENEITY TURNS NOT SIGNIFICANT  Furthermore, the SCALE HETEROGENEITY = ZERO  CONSUMERS’ PREFERENCES TOWARDS CATALAN wines have become CLEAR

30. 6. CONCLUSIONS  Consumers’ preferences are higher for the CATALAN ORIGIN of the product, for the grape variety CABERNET SAUVIGNON and for wines that have been PREVIOUSLY EXPERIENCED  The CATALAN ORIGIN of the wine shows a SIGNIFICANTLY POSITIVE UTILITY IN BOTH SURVEYS, which reveals the importance of the Catalonian identity in the consumer behaviour.  However, During the crisis, this quality is HOMOGENEOUS ACROSS CONSUMERS (does not show any unobservable heterogeneity).  This finding is in ACCORDANCE with the POLITICAL ENVIRONMENT  Consumers’ preferences are higher for the CATALAN ORIGIN of the product, for the grape variety CABERNET SAUVIGNON and for wines that have been PREVIOUSLY EXPERIENCED  The CATALAN ORIGIN of the wine shows a SIGNIFICANTLY POSITIVE UTILITY IN BOTH SURVEYS, which reveals the importance of the Catalonian identity in the consumer behaviour.  However, During the crisis, this quality is HOMOGENEOUS ACROSS CONSUMERS (does not show any unobservable heterogeneity).  This finding is in ACCORDANCE with the POLITICAL ENVIRONMENT

31. 6. CONCLUSIONS  SPANISH WINES shows a NON-SIGNIFICANT UTILITY During the crisis, this occurs in spite of gathering the highest market share in Catalonia, which suggests an influence of the political changes

32. 6. CONCLUSIONS  The GMNL model has shown to be appropriated to DECOUPLE both UNOBSERVED HETEROGENEITIES  Has provided us with more information about the SOURCE OF CONSUMERS’ HETEROGENEITY  In the “During” model: the results for the SCALE HETEROGENEITY indicate that the degree of uncertainty in the decision-making process has DECREASED SIGNIFICANTLY.  This finding might show an IMPACT OF SOCIO ECONOMIC CHANGES in the environment of consumers’ decision-making towards wine. In this sense, external common circumstances may have had a HOMOGENIZING INFLUENCE.  The GMNL model has shown to be appropriated to DECOUPLE both UNOBSERVED HETEROGENEITIES  Has provided us with more information about the SOURCE OF CONSUMERS’ HETEROGENEITY  In the “During” model: the results for the SCALE HETEROGENEITY indicate that the degree of uncertainty in the decision-making process has DECREASED SIGNIFICANTLY.  This finding might show an IMPACT OF SOCIO ECONOMIC CHANGES in the environment of consumers’ decision-making towards wine. In this sense, external common circumstances may have had a HOMOGENIZING INFLUENCE.