Substitution between Mass-Produced and High-End Beers Daniel Toro-Gonzalez Ph.D. candidate, School of Economic Sciences (SES) Jill J. McCluskey Visiting Professor, Cornell University and Professor, SES, Washington State University and Ron C. Mittelhammer Regents Professor, SES & Dept. of Statistics Presented at Beeronomics Symposium UC Davis November 3, 2011

2 Macro Brews Dominate many U.S. Markets

However, This is Changing Mass producers’ market share still represents the vast majority of sales, but their sales are flat or declining. Trend of consumers switching from mass to craft beers. Consistent with general shift in food preferences:  Increasing desire for variety, taste, and local products.

We know that consumers shift from macro to craft brews. Does it go the other way? “…consumers are very loyal to craft beers and not shifting to macro from craft. In economics terms the cross-price elasticity of craft and macro brews appears to be very inelastic, or that beer drinker do not think of macro lagers as a good substitute for micro brews.” - “Beeronomics: Is Craft Beer Recession Proof After All ?”, The Oregon Economics Blog, Thursday, May 7, 2009.

Project Objectives beer, differentiated product Estimate demand for beer, which is a differentiated product. Estimate the own-price, cross-price and income elasticities.

Data Scanner data from 60 Dominick's supermarkets in Chicago. Seven years of store-level weekly sales data (1991 to 1997) 483UPCs for 343 brands. Product info and store area sociodemographics

Market and Product Definition Oligopolistic differentiated product market. Each store is treated as an independent market. Each brand of beer is considered as a product.

Types of Beer 1.Mass produced beers 1.Mass produced beers are defined as those with similar characteristics of lightness, same fermentation method (bottom fermenting yeast) and the use of adjuncts such as corn or rice. 2.Import beers 2.Import beers are those produced abroad. craft beers 3.The rest of the beers are called craft beers. 8

Number of Firms Long term secular decline in traditional breweries Rapid expansion in specialty breweries since 1980

Market Shares by Beer Type Sample Averages for Dominick Stores

Discrete Choice Model Issues aggregate Model weekly aggregate sales at each store, by beer type dimensionality Address dimensionality problem (large number of underlying products) by projecting the products onto a characteristics space. differentiated products Market characterized by differentiated products. correlated Prices may be correlated with unobserved demand factors, causing endogeneity problem.

Discrete Choice Model

Observable Variables  Observed product characteristics: –Size of the bottle –Alcohol content –Type (Mass, Craft, Import) –Style (Ale, Fruit, Low Alcohol, Oktoberfest, Seasonal, Smoked, Steam, Stout, Wheat)  Price  Observed consumer characteristics: –Household income, home value, household size, education (% college graduates), ethnicity (% blacks+hispanics)

Discrete Choice Model Linear specification of utility where  j is interpreted as the mean of consumers’ valuations of unobserved product characteristics (product quality). Error term encompasses the distribution of consumer preferences around  j. Errors are i.i.d. with “extreme value” distribution, resulting in a multinomial logit formulation.

Mean Utility Representation Simply using  j to represent the mean utility for product j, which is defined as everything other than the error term:

Multinomial Logit The market share of product j is then expressible in term of  j :

Multinomial Logit Assuming the relationship between observed and predicted market shares is invertible, with the mean utility of the outside good (all other than beers) normalized to zero, Endogeneity Prices and unobserved product attributes are correlated  Endogeneity.

Instrument for Prices Prices in other markets? (Hausman, 1996).  Prices of brand j in two markets will be correlated due to the common marginal cost.  But prices in other markets uncorrelated with the market-specific unobserved product characteristics.

Variable \ MethodMNLMNL-IV Price-9.10E-06***-0.283*** Size9.11E-06***0.054*** Alcohol-2.63E-06***0.029*** Craft-1.77E-05***-0.319*** Import-1.74E-05***-0.202*** Ethnic8.22E *** Education-2.51E Household Size-7.90E *** Incomes6.85E *** Observations12066 R2R Legend: * p<.1; ** p<.05; *** p<.01. MNL: Ignores endogeneity of prices. MNL-IV: Prices in other markets as IV for Price.

Problem with MNL Independence of Irrelevant Alternatives (IIA).  Example, if a consumer wants to try a beer that is an American lager, he/she may consider alternatives like Coors light or Bud Light, but he will not consider any Stout type of beer.

Nested Logit Model The NL preserves the assumption that consumer tastes are extreme value distributed. Allows consumer tastes to be correlated across products. More reasonable substitution patterns than in the previous model ( a priori ).

Nested Logit Model We divide the products into g different exhaustive and mutually exclusive groups.  is common to all products in group g. averagecorrelation in the random utility across products of the same group (1- σ ) is the average correlation in the random utility across products of the same group.

Nested Logit Model Berry (1994) shows that if the errors are i.i.d. extreme value then: it is also distributed as a extreme value.

Nested Logit Model We can represent the NL model as: where σ measures average similarity of products within each group of beer types. within group share The new term is the log of the within group share.

Variable / MethodMNLMNL-IVNL-IV Price-9.10E-06***-0.283***-0.229*** Size9.11E-06***0.054***0.006*** Alcohol-2.63E-06***0.029***0.060*** Craft-1.77E-05***-0.319***-5.253*** Import-1.74E-05***-0.202***-5.122*** Ethnic8.22E ***0.090*** Education-2.51E Household Size-7.90E ***-0.087*** Incomes6.85E ***0.002*** σ(Average across g) 0.892*** Observations12066 R2R Legend: * p<.1; ** p<.05; *** p<.01.

Price Elasticities MassCraftImportOver All Mass Craft Import Over All Source: Dominik’s dataset, calculations by the authors.

Compare with Other Findings Source: Table 2.2. Tremblay and Tremblay (2005). SourcePrice Elasticity Hogarty and Elzinga Orstein and Hanssens Tegene Lee and Tremblay Gallet and List Nelson Nelson This study

Income Elasticities Source: Dominik’s dataset, calculations by the authors. Elasticity Mass0.257 Craft0.434 Import0.460 Over All0.260

Price Elasticities: Other Findings Source: Table 2.2. Tremblay and Tremblay (2005). SourceIncome Elasticity Hogarty and Elzinga Orstein and Hanssens Tegene Lee and Tremblay Gallet and List Nelson Nelson This study 0.260

Conclusions Demand for beer is inelastic with respect to prices. Cross-price elasticities are very close to zero.  Mass and craft beers are not close substitutes! From the income elasticities, all of the types of beer (mass, craft, and import) are normal goods.

Next Steps Estimate the model using a random coefficients specification for utility. Allow for consumer heterogeneity. Consumer characteristics can interact with product attributes. Examine other formulations/instruments to tackle endogeneity between price and unobserved product characteristics.

Thank you and Cheers! Questions? (pictures from the Beeronomics Conference, Belgium May 2009)