Wine Consumption Across Generations – A Life Cycle Approach Work in Progress Geir W. Gustavsen 1 and Kyrre Rickertsen 1,2 1 Norwegian Institute of Bioeconomy Research, Ås 2 School of Economics and Business, Norwegian University of Life Sciences Norwegian University of Life SciencesAAWA, Bordeaux, France, June , 20161

Wine Consumption in Norway Sales exclude tax-free sales and border trade Sales of beer has declined from 65 – 57 liters per adult Sales of spirits has declined from 3 to 2.6 liters per adult Sales of wines has increased from 8 – 18 liters per adult –A third of France –Half of Denmark –On level with Ireland Our objective is to investigate factors that explain the growth in sales of wine Norwegian University of Life SciencesGustavsen and Rickertsen2

Changes in Real Prices and Income Potentially Important The mean Norwegian own-price and income elasticity of alcohol was and 1.07 (Fogarty 2010) The median world own-price and income elasticity of wine was and 1.10 (Gallet 2007) The price indices for beer, wine, and spirits are shown in Figure 2 They are the sub-indices of the Consumer Price Index (CPI) divided by the CPI Real income is the average annual income divided by the CPI The price index of wine has been between 0.99 – 1.02 since 1993 Real income has grown from 0.9 to 1.5 Income growth seems to be more important than changes in relative prices Norwegian University of Life SciencesGustavsen and Rickertsen3

Availability: The State Monopoly “Vinmonopolet” Controls the Norwegian retail market for alcoholic beverages (content above 4.75%) The existence of Vinmonopolet was controversial when Norway joined the EEA (in the 1990s) To regain popular support Vinmonopolet decided to increase the number of retail outlets and to introduce self service The plan was implanted in 1998 –1997: 114 outlets (not self service) –2015: 306 outlets (self service) –Sells: 5988 red, 3845 white and 1199 sparkling wines on their web pages Norwegian University of Life SciencesGustavsen and Rickertsen4

Age, Period, and Cohort (APC) Effects Wine consumption is likely to differ with age, over periods and across birth cohorts Age effects reflect biological and social processes across the life cycle of an individual (drink less alcohol but more wine?) Period effects reflect changes over time that influence all age groups simultaneously (wine culture, media attention, health effects?) (Birth) cohort effects reflect changes that have a particular effect on all people who were born at the same time (were youths when the alcohol policy was liberalized?) APC variables can be considered to be proxy variables –Non-included socioeconomic and demographic variables –Availability –Attitudes (religion, health consciousness, hedonism, etc.) Many of the attitudinal variables are typically not investigated because of lack of data Norwegian University of Life SciencesGustavsen and Rickertsen5

Norwegian Monitor Survey Nationally representative sample for adults aged 15 to 95 years We include individuals from 18 to 80 years and data for Bi-annual repeated cross-sectional survey that includes many of the same questions –Can not estimate the dynamics of wine consumption for a respondent –We use both the cross-sectional and time-series dimensions to estimate and predict future wine consumption in Norway –3,000 – 4,000 respondents in each round, we use 39,544 obs Includes data about socio-demographics, attitudes and habits (about 150 compact pages with questions) –We used two questions concerning the consumption frequency of red and white wine (every day … less than three times a year, never) to construct the frequency of wine consumption –Used uniform distributions to create frequencies that we draw from (500 bootstraps) to estimate and simulate the model Norwegian University of Life SciencesGustavsen and Rickertsen6

Average Number of Wine Drinking Days per Year in Different Cohorts over Time Cohort defined as individuals born in the same five-year period Substantial (unconditional) time and cohort effects Frequency is increasing over time (except for last survey) Frequency highest in second oldest cohort –Average frequency increased from about 30 days in 1991 to about 60 days in 2015 Norwegian University of Life SciencesGustavsen and Rickertsen7

Average Number of Wine Drinking Days in Different Cohorts and Average Age of Cohort Substantial (unconditional) age and cohort effects The rightmost curve is the oldest cohort (born ) The leftmost curve is the youngest cohort (born ) Frequency increases with age (except for last survey) Younger cohorts have a higher frequency than older cohorts when measured at the same age –When the oldest cohort was 56 years in 1991, the average frequency was 17 per year –When the second oldest cohort was 56 years in 2001, the average frequency was 52 Norwegian University of Life SciencesGustavsen and Rickertsen8

Marginal Effects in Binary Logit Model The outcome variable is 1 if the respondent drinks wine at least once per week (and 0 otherwise) – about 23% Insignificant marginal effects of: Price (excluded due to insignificance), birth cohort, gender, and being a regular beer drinker The probability of drinking wine increases by: –0.7 percentage point for a one year age increase –2.2 percentage points for a new wine store in the county –1.1 percentage points for a 1% increase in income –12.4 percentage points for having university education –5.0 percentage points if you are married –7.0 percentage points if you live in a big city –8.0 percentage points if you are born in 1980 or later –9.9 percentage points for “hedonists” –4.2 percentage points for “health conscious” respondents The probability is reduced by 9 percentage points for “religious” respondents Norwegian University of Life SciencesGustavsen and Rickertsen9

Simulated Probabilities by Estimated Model We simulate the probabilities of drinking wine at least once per week for five different cohorts (1950, 1960, 1970, 1980 and 1990) We let the age sequentially increase from 30 to 80 years in the different cohorts –The 2015 values of the explanatory variables are used in simulations The probabilities are around 0.15 when respondents are around 30 years The probabilities increase with age The probabilities increase more rapidly with age for younger than older cohorts –0.4 in the oldest cohort at 70 years –0.8 in the youngest cohort at 70 years Norwegian University of Life SciencesGustavsen and Rickertsen10

Conclusions –There are substantial age, period, and cohort effects before we control for other variables –When we control for socioeconomic, demographic and attitudinal variables only the age effect remains significant –Significant effects of the number of wine stores; income; demographics; and attitudes related to hedonism, health, and religion –No effects of price (in preliminary models), gender, or being a regular beer drinker –Simulation indicates that more people are likely to consume wine at least once per week in the future because older cohorts are replaced by younger cohorts Norwegian University of Life SciencesGustavsen and Rickertsen11

Thank you for your attention! School of Economics and BusinessGustavsen and Rickertsen12