intra- and inter-format competition in grocery retailing catherine ball esrc centre for competition...

Intra- and Inter-Format Competition in Grocery Retailing

Catherine Ball

ESRC Centre for Competition Policy

University of East Anglia

20/02/09

Introduction– Research questions– Literature

Econometric model– Methodology– Data

Results Conclusions Further work

Outline of Presentation

Research Questions/Literature

How effective are small supermarkets and specialist stores at providing a competitive constraint to large supermarkets?

– Several CC/OFT studies make the assumption that ‘larger’ supermarkets constrain ‘smaller’ supermarkets but not vice versa.

• Cleeren et al (2008) show that discounters can constrain supermarkets in Germany.

Which type of supermarkets (small, urban or large,out-of-town) are the most ‘harmful’ to the existence of specialist stores?

– Smaller, town-centre supermarkets might be less ‘harmful’ to specialist stores – increase footfall.

Is it useful to measure variation in product range, both in terms of range of product categories and range within categories, in a two dimensional product space?

– Increased scope for product differentiation decreases competitive pressure in a market Seim (2006) – could this extend to differentiation in product range carried?

Market Summary

Large supermarkets– 4 major players

• Tesco (supermarket and Extra formats) (27.6% all formats)• ASDA (14.1%)• Sainsbury (supermarket format) (13.8% all formats)• Morrisons (9.9%)

Market Summary

Large supermarkets– 4 major players

• Tesco (44,000)• ASDA (65,000)• Sainsbury (26,000)• Morrisons

Market Summary

Smaller supermarkets/convenience stores– Main players

• CGL/Somerfield (3.8 and 3.9% respectively 2007)• Waitrose (3.3%)• M&S (3.8%)• Tesco (Express and Metro formats) (27.6% all formats)• Sainsbury (Local and Central formats) (13.8% all formats)• Budgens• Iceland (1.5%)• Aldi/Lidl (2.8% combined)• Others (15.5%)

Market Summary

Smaller supermarkets/convenience stores– Main players

• CGL/Somerfield (15,201 – CGL only)• Waitrose (24,500)• M&S (5,000 – food only)• Tesco (Express and Metro formats) • Sainsbury (Local and Central formats) • Budgens (6,600)• Iceland (3,420)• Aldi/Lidl• Others

Market Summary

Specialist stores– Main types:

• Fishmongers • Greengrocers• Butchers• Bakers• Off-licences

Multiproduct Firms

Most retailers are multiproduct firms:

Two issues-– Internalisation of agglomeration effects (Shaked and

Sutton, 1990)• Expansion effect• Lower for specialist stores

– Product differentiation in range?• Reduces competitive pressure

Large vs. Small Supermarkets

One-stop vs. Top-up shopping

Out-of-town vs. Town centre location

Large supermarkets have a wider range both within and across(?) categories than a smaller supermarket.

Parking, other facilities

Price flexing and “PQRS”

Supermarkets vs. Specialists

Supermarkets internalise agglomeration effects of providing a range of products, a group of independent specialists does not (Hay and Smith, 2005)

Specialists offer expert advice Specialists have a wider within category range(?) Supermarkets have more categories Perceived higher quality

Methodology

Multiple-entrant qualitative response model

Cross-sectional data

Limited to pairwise comparisons– At present limited to comparisons where dependency

between firms is only in one direction• Eg small supermarkets profits depend on number of large

supermarkets but not vice-versa

Methodology

The profits of a particular type of supermarket, k where k = 1, 2 are given by:

– Where S is market size (population and nearby population), X is a vector of demand/cost variables that affect firm profitability within a market.

),,,,(

),,,(

212

11

NNsspecialistSf

NsspecialistSf

iii

iii

ki

ki

ki

X

X

Methodology

Assuming that large supermarkets constrain small supermarkets (but not vice versa). The latent profits are given by:

A firm of a particular type will enter market i when:

SiLiSiSiSSSiSiSSi

LiLiLiLLLiLiLLi

NsspecialistgXS

NsspecialistgXS

)(

)(

kikiki 0

Methodology

Latent profits are unobserved, but if ε are i.i.d. bivariate normal, the observed number of stores of each type, Nk (k=L,S) can be estimated using a simultaneous equation bivariate ordered probit model.

NL and NS are observed such that:

LiJ

Li

Li

Li

cifJ

ccif

cif

N

11

1211

11

2

1

SiSK

SSiS

SSi

Si

cifK

ccif

cif

N

1

21

1

2

1

Methodology

Therefore the probability of observing NL=j and NS=k in market i is:

Assuming ε are bivariate standard normal with correlation parameter ρ, this corresponds to a simultaneous equation bivariate probit model with one endogenous regressor.

),Pr(),Pr( ,1,,1, kSSkSjLLjLSL cccckNjN

Note:

There are several special cases nested within this model:

γ=0 (coefficient on endogenous regressor) – seemingly unrelated model

ρ=0, univariate probit model

Sample Markets Aggregate postcode districts (e.g. NR1, NR2) into postal towns (e.g. Norwich).

Vary in population from 142 (St. Martin’s, Isle of Scilly) to 1,015,043 (Birmingham).

Each London borough is classified as a separate postal town.

1239 postal town markets

Sample Markets - filtering Why filter?

– Isolated markets– Partial and sub-markets– Categorisation of number of firms

Cleeren et al (2007) filtering rule:– Exclude markets where pop<3,000 or pop>25,000

Bresnahan and Reiss (1991) filtering rule:– Exclude markets within 20miles of a town with pop>1,000 – Exclude markets within 100miles of a town/city with pop>100,000

My filtering rule:– Exclude markets within 20miles of a town/city with pop>150,000– Exclude markets where pop<3,000 or pop>75,000

Sample Markets - filtering

Variables All markets Sample markets

Mean S.D. Min Max Mean S.D. Min Max

POP (1000) 42.149 72.089 0.142 1,015.043 14.890 13.305 3.014 73.776

%EMPLOY 0.442 0.053 0 0.739 0.426 0.043 0.267 0.594

OVER64 0.176 0.050 0 0.404 0.208 0.049 0.045 0.384

BUTCHERS 4.385 0.224 0 138 2.746 2.438 0 14

BAKERS 4.422 8.247 0 90 2.498 2.643 0 18

GREEN 1.390 2.801 0 37 0.878 1.112 0 6

FISH 0.641 1.294 0 13 0.722 1.308 0 9

OFFLICENCE 4.431 399 0 133 0.946 4.706 0 26

LARGE - - - - 1.448 1.541 0 6

SMALL 10.213 20.802 0 338 3.373 2.965 0 13

Large supermarkets

Defined as the following fascias of the “big four”– Tesco (Supermarket and Extra formats)– ASDA (All stores)– Sainsbury (Supermarket format)– Morrisons (All stores)

Counted in a postal town if it is within 15mins drive of the centre.

Small supermarkets

Defined as:– All non-”big four” supermarkets

• I.e. Somerfield/Co-op, M&S, Waitrose, Budgens

– All non-”big four” convenience stores

– Tesco (Express and Metro formats), Sainsbury (Local and Central formats)

Counted in a postal town if in one of the postcode districts that comprise the postal town.

Specialists

Specialist stores included:– Butchers (5449)– Bakers (5505)– Offlicences (5539)– Greengrocers (1733)– Fishmongers (790)

Counted in a postal town if in one of the postcode districts that comprise the postal town.

Other Data

Market size given by population

Control variables – percentage employed, age

Instruments– For “large” supermarkets – percentage of car owners

Final specification

Profits of a large supermarket are given by:

Profits of a small supermarket are given by:

LLDLLLLLLi NSPECAGEEMPLOYPOP 321)ln(

SLSSDSSSSSS NNSPECAGEEMPLOYPOP 321)ln(

LARGE SMALL

Variable Coefficient Variable Coefficient

lnPOP 0.739 lnPOP 0.557

Employ 2.582 Employ -2.743

Over64 -0.498 Over64 -2.505

Spec1 -0.197 Spec1 -0.340

Spec2 -0.669 Spec2 -0.532

Spec3 -0.705 Spec3 -0.814

Spec4 -0.575 Spec4 -0.444

pcarowner 3.339 large -0.585

Cut1 -1.138 Cut1 -2.212

Cut2 -0.223 Cut2 -1.730

Cut3 0.456 Cut3 -1.487

Cut4 0.892 Cut4 -1.265

Cut5 1.254 Cut5 -1.132

Cut6 1.837 Cut6 -0.995

Cut7 -0.846

Cut8 -0.733

Cut9 -0.628

Cut10 -0.516

Wald test of independent equations (rho=0)

2.73

Wald test 139.73

Red, orange and yellow indicate significance at the 1%,5% and 10% level respectively.

Red indicates significant difference to the preceding cut-point at 1% level.

Conclusions

Evidence that large and small supermarket’s entry decisions are strategically linked and jointly determined.

Some weak evidence that, for large supermarket, competitive pressure increases with additional entry.

Some weak evidence that an agglomeration of three different types of specialists has an impact on the profitability of small supermarkets but no effect on large supermarkets.

Extensions

Jointly determine whether small and large supermarkets are strategically dependent (two endogenous regressors)

Endogenise specialist entry

Analyse affect of barriers to entry affecting large supermarkets

Model product range as two-dimensional product differentiation. Change order of game.

Extensions

Model product range as two-dimensional product differentiation.

Small supermarkets

Specialists

Large supermarkets

Range w

ithin categories

Range across categories