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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

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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.

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Project Objectives

•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

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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 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 are those

produced abroad.

3. The rest of the beers are called

craft beers.

8

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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

Type Share Price Per Bottle

Craft 5.3% 0.80

Mass 86.4% 0.54

Import 8.2% 0.95

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Discrete Choice Model Issues

• Model weekly aggregate sales at each store, by

beer type

• Address dimensionality problem (large number

of underlying products) by projecting the

products onto a characteristics space.

• Market characterized by differentiated products.

• Prices may be correlated with unobserved

demand factors, causing endogeneity problem.

Discrete Choice Model

•

),,,,( dijjj vpxU

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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)

( , , )j j jx p

Discrete Choice Model

ij j j j iju z p

• 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.

j j jz x

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Mean Utility Representation

• Simply using dj to represent the mean utility

for product j , which is defined as

everything other than the error term:

j j j jz pd

ij j iju d

Multinomial Logit

• The market share of product j is then

expressible in term of dj :

N

0k

δ

δ

j

k

j

e

es )(d

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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,

•Prices and unobserved product attributes

are correlated Endogeneity.

0ln( ) ln( )j j j j js s z pd

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.

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Variable \ Method MNL MNL-IV

Price -9.10E-06 *** -0.283 ***

0.000 0.012

Size 9.11E-06 *** 0.054 ***

0.000 0.002

Alcohol -2.63E-06 *** 0.029 ***

0.000 0.010

Craft -1.77E-05 *** -0.319 ***

0.000 0.024

Import -1.74E-05 *** -0.202 ***

0.000 0.026

Ethnic 8.22E-06 0.139 ***

0.000 0.047

Education -2.51E-05 0.217

0.000 0.155

Household Size -7.90E-06 -0.179 ***

0.000 0.030

Incomes 6.85E-08 0.002 ***

0.000 0.000

Observations 12066 12066

R2 0.201 0.438

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.

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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.

• (1-σ) is the average correlation in the

random utility across products of the

same group.

ij j jg iju (1 )d

j j j jz pd

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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.

jg ij(1 )

Nested Logit Model

•We can represent the NL model as:

where σ measures average similarity of

products within each group of beer types.

The new term is the log of the within group

share.

0 /ln( ) ln( ) ln( )j j j j j g js s z p sd

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Variable / Method MNL MNL-IV NL-IV

Price -9.10E-06 *** -0.283 *** -0.229 ***

0.000 0.012 0.011

Size 9.11E-06 *** 0.054 *** 0.006 ***

0.000 0.002 0.001

Alcohol -2.63E-06 *** 0.029 *** 0.060 ***

0.000 0.010 0.008

Craft -1.77E-05 *** -0.319 *** -5.253 ***

0.000 0.024 0.040

Import -1.74E-05 *** -0.202 *** -5.122 ***

0.000 0.026 0.040

Ethnic 8.22E-06 0.139 *** 0.090 ***

0.000 0.047 0.035

Education -2.51E-05 0.217 -0.130

0.000 0.155 0.110

Household Size -7.90E-06 -0.179 *** -0.087 ***

0.000 0.030 0.022

Incomes 6.85E-08 0.002 *** 0.002 ***

0.000 0.000 0.000

σ(Average across g) 0.892 ***

0.000

Observations 12066 12066 12066

R2 0.201 0.438 0.716

Legend: * p<.1; ** p<.05; *** p<.01.

Price Elasticities

Mass Craft Import Over All

Mass -0.1223 0.0004 0.0002

Craft 0.0028 -0.3168 0.0013

Import 0.0004 0.0008 -0.1566

Over All -0.1715

Source: Dominik’s dataset, calculations by the authors.

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Compare with Other Findings

Source: Table 2.2. Tremblay and Tremblay (2005).

Source Price Elasticity

Hogarty and Elzinga 1972 -0.889

Orstein and Hanssens 1985 -0.142

Tegene 1990 -0.768

Lee and Tremblay 1992 -0.583

Gallet and List 1998 -0.730

Nelson 1999 -0.200

Nelson 2003 -0.174

This study -0.172

Income Elasticities

Source: Dominik’s dataset,

calculations by the authors.

Elasticity

Mass 0.257

Craft 0.434

Import 0.460

Over All 0.260

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Price Elasticities: Other Findings

Source: Table 2.2. Tremblay and Tremblay (2005).

Source Income Elasticity

Hogarty and Elzinga 1972 0.430

Orstein and Hanssens 1985 0.011

Tegene 1990 0.731

Lee and Tremblay 1992 0.135

Gallet and List 1998 -0.545

Nelson 1999 0.760

Nelson 2003 -0.032

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.

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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)