An empirical study of supermarket demand and equilibrium pricing
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1 An empirical study of supermarket demand and equilibrium pricing Martin O Connell Institute for Fiscal Studies and University College London December 2012 O Connell (IFS/UCL) Toulouse Workshop 1 / 27 December / 27
2 Outline Outline of presentation 1 Background/motivation From Griffith, O Connell and Smith (2011) 2 Outline a model of grocery demand and supermarket pricing 3 Show some very preliminary results O Connell (IFS/UCL) Toulouse Workshop 2 / 27 December / 27
3 Background Recent large increase in UK food price O Connell (IFS/UCL) Toulouse Workshop 3 / 27 December / 27
4 Background Recent large increase in UK food price O Connell (IFS/UCL) Toulouse Workshop 3 / 27 December / 27
5 Background Large change in relative prices of different foods Change in price of food types relative to change in price of all food: O Connell (IFS/UCL) Toulouse Workshop 4 / 27 December / 27
6 Background Possible drives of changes in retail food prices Changes in costs? Large depreciation of sterling and global food commodity price boom Would expect an increase in retailer costs Changes in demand? Concurrently there s been large shocks to consumers incomes Crossley et al (2011) report 6.6% decline in consumer expenditure on food over recession Would expect resultant reallocation of expenditures across different foods O Connell (IFS/UCL) Toulouse Workshop 5 / 27 December / 27
7 Objective of this work Background Specify and estimate a model that allows for separation of impact of changes in costs and changes in demand conditions on equilibrium food prices In common with many empirical IO papers: Estimate demand facing firms Use equilibrium pricing condition to pin down marginal costs But in contrast to much of this literature: Model demand for a large class of goods Allow for complementarities between goods Allow for income effects Use model to simulate counterfactual market equilibria e.g. Path of retail prices in absence of increases in costs O Connell (IFS/UCL) Toulouse Workshop 6 / 27 December / 27
8 Demand model Overview of demand model Focus on modelling the consumer s main weekly supermarket trip Which supermarket they choose How they allocate their main trip grocery expenditure across 9 grocery goods Assume one stop shop model - purchase decisions made on main trip are independent of purchase decisions on smaller top up trips Consumer makes discrete decision over which retailer to shop with based on: Anticipated utility from optimal shopping within retailer Their valuation of other retailer characteristics And a continuous decision over how to allocate expenditure across grocery goods available in chosen retailer Model allows for estimation of demand faced by retailers; e.g. demand for meat in retailer Tesco O Connell (IFS/UCL) Toulouse Workshop 7 / 27 December / 27
9 Demand model Utility conditional on retailer choice Consumer i in week t gets utility from shopping with retailer s given by: where: V ist = ζ i φ(p st, x it, ξ it ) + κ i z is + λ i µ s + ε ist p st = (p s1t,..., p sjt ) are prices for J goods within the retailer x it is weekly main shop budget ξ it = (ξ i1t,..., ξ ijt ) captures household specific and time specific factors influencing within retailer demand z is are observable consumer-retailer characteristics µ s are retailer fixed effects (ζ i, κ i, λ i ) are consumer specific (random) coefficients ε ist is an idiosyncratic shock O Connell (IFS/UCL) Toulouse Workshop 8 / 27 December / 27
10 Demand model Within retailer behaviour Assume within retailer preferences can be represented by AIDS with consumer specific heterogeneity Portion of indirect utility realised from within retailer behaviour is: where φ(p st, x it, ξ it ) = 1 B(p st ) [ln x it ln A(p st, ξ it )] ln A(p st, ξ it ) =α o + α j (ξ ijt ) ln p sjt j j ln B(p st ) = β j ln p sjt j k γ jk ln p sjt ln p skt O Connell (IFS/UCL) Toulouse Workshop 9 / 27 December / 27
11 Demand model Within retailer behaviour Assuming 1 α j (ξ ijt ) = α j + ξ ijt 2 ξ ijt = τ jt + c ij Roy s Identity implies (anticipated) share of trip expenditure allocated to good j is: w isjt = α j + τ jt + c ij + γ jk ln p skt + β j ln k ( ) x it A(p st, ξ it ) τ jt captures unobserved common time factors affecting intercept of budget share demands c ij captures unobserved household specific factors affecting intercept of budget share demands O Connell (IFS/UCL) Toulouse Workshop 10 / 27 December / 27
12 Demand model Within retailer behaviour Assuming 1 α j (ξ ijt ) = α j + ξ ijt 2 ξ ijt = τ jt + c ij Roy s Identity implies (anticipated) share of trip expenditure allocated to good j is: w isjt = α j + τ jt + c ij + γ jk ln p skt + β j ln k ( ) x it A(p st, ξ it ) Consumer makes retailer choice decisions based on expected behaviour captured by w isjt Within retailer realised demand, w isjt, may differ; I assume w isjt = E( w isjt τ jt, c ij, p st, x it ) O Connell (IFS/UCL) Toulouse Workshop 10 / 27 December / 27
13 Choice of supermarket Demand model Consumer chooses retailer that provides her with most utility V it = max[v i0t,..., V ist ] s Assume ε ist is distributed iid extreme value and (ζ i, κ i, λ i ) are drawn from a multivariate normal distribution F Then probability consumer i in week t visits retailer s is: π ist = exp(ζ i φ(p st, x it, ξ it ) + κ i z is + λ i µ s ) exp(ζ i φ(p rt, x it, ξ it ) + κ i z ir + λ i µ r ) df r O Connell (IFS/UCL) Toulouse Workshop 11 / 27 December / 27
14 Substitution patterns Demand model Consumer i s week t expected demand for good j in retailer s is: q isjt = π ist q isjt where q isjt is demand conditional on retailer choice Ignoring i and t subscripts, price elasticities of demand between goods within a retailer are: δ (sj)(sk) = ln π s ln φ s ln φ s ln p sk + ln q sj ln p sk Price elasticities of demand between goods in different retailers are: δ (sj)(rk) = ln π s ln φ r ln φ r ln p rk O Connell (IFS/UCL) Toulouse Workshop 12 / 27 December / 27
15 Demand model Choice of total grocery expenditure Current version of the model conditions on main trip grocery expenditure Consumer chooses supermarket based on utility she will get from optimally spending that budget on grocery goods, given prices she ll face in the retailer But budget is assume to be fixed across retailers Roughly, consistent with demand for aggregate grocery good having unit price elasticity with respect to total grocery price index Means variation in consumer s grocery expenditure through time is driven by changes in her total non-durable expenditure/income Consumer s problem O Connell (IFS/UCL) Toulouse Workshop 13 / 27 December / 27
16 Demand model Choice of total grocery expenditure Aim is to relax this assumption Difficulty is market research data has Very detailed information on consumer s within supermarket expenditures But little information on their non-grocery expenditure or income One idea is to: Assume weak separability between grocery and non-grocery demand Use market research data to estimate preference parameters determining grocery demand Use additional data source to estimate preference parameters determining choice of grocery expenditure O Connell (IFS/UCL) Toulouse Workshop 14 / 27 December / 27
17 Supply side Retailer behaviour Assume retailers compete in a Nash-Bertrand game Retailer s in market t chooses the prices of J goods to maximise profits: max p st j {1,...,J} (p sjt c sjt )Q sjt (p 01,..., p St ) C sjt where: c sjt is market t marginal cost of good j in retailer s C sjt is market t fixed cost of good j in retailer s Q sjt i Ωt q isjt is market t demand for good j in retailer s O Connell (IFS/UCL) Toulouse Workshop 15 / 27 December / 27
18 Supply side Retailer behaviour Assume retailers compete in a Nash-Bertrand game Retailer s in market t chooses the prices of J goods to maximise profits: max p st j {1,...,J} First order condition is: Q sjt + (p sjt c sjt )Q sjt (p 01,..., p St ) C sjt k {1,...,J} (p skt c skt ) Q skt = 0 p sjt Inverting system yields implied marginal cost of each good in each retailer and market O Connell (IFS/UCL) Toulouse Workshop 15 / 27 December / 27
19 Data Data Rolling panel of households, containing All grocery shopping trips households make Including the retailer they visit And within retailer expenditures and transaction prices on very disaggregate products Data cover period ; 466 weeks/markets Households in data for 120 weeks on average Weekly main shopping trip is defined as weekly trip on which household spends most Small number of weeks where a household s grocery expenditure is less than 50% of its median are dropped On average 82% of households weekly grocery supermarket expenditure is made on main trips O Connell (IFS/UCL) Toulouse Workshop 16 / 27 December / 27
20 Goods Data Good Expenditure share Main compenents Fruit 8.05% Fresh fruits, canned and dried fruits, frozen fruit and fruit juices Vegetables 5.08% Fresh vegetables, canned vegetables and frozen vegetables Grains 7.95% Flour, cereals, pasta, rice, breads and potatoes Dairy 10.73% Milk, cream, cheese, butter, margarine and yogurt Meats 14.88% Beef, pork, lamb, poultry, bacon, ham, sausages, eggs, seafood, seeds and nuts Drinks 5.52% Non fruit juice, water, tea and coffee Sweet 8.23% Sugar, sweeteners, cakes, biscuit and desserts Savoury 18.24% Ready meals and prepared snacks Non food 21.31% Alcohol, toiletries, pet foods and cleaning produce Prices O Connell (IFS/UCL) Toulouse Workshop 17 / 27 December / 27
21 Retailers Data Retailer Market share Asda 20.1% Morrisons 14.8% Sainsbury s 17.9% Tesco 35.9% Other 11.3% O Connell (IFS/UCL) Toulouse Workshop 18 / 27 December / 27
22 Preliminary results Demand conditional on retailer choice Variables Fruit Vegetables Grain Dairy Meat Expenditure *** *** *** *** *** (0.0001) (0.0001) (0.0001) (0.0001) (0.0002) PriceFruit *** *** *** (0.0007) (0.0004) (0.0006) (0.0007) (0.0009) PriceVegetables *** *** *** *** (0.0004) (0.0006) (0.0006) (0.0007) (0.0008) PriceGrain *** *** *** *** (0.0006) (0.0006) (0.0011) (0.0010) (0.0010) PriceDairy *** *** *** *** *** (0.0007) (0.0007) (0.0010) (0.0016) (0.0013) PriceMeat *** *** *** *** *** (0.0009) (0.0008) (0.0010) (0.0013) (0.0022) PriceDrink *** *** *** *** (0.0005) (0.0004) (0.0005) (0.0007) (0.0008) PriceSweet *** *** *** *** *** (0.0005) (0.0004) (0.0005) (0.0006) (0.0008) PriceSavoury *** *** *** *** *** (0.0008) (0.0006) (0.0008) (0.0010) (0.0014) Time effects Yes Yes Yes Yes Yes Fixed effects Yes Yes Yes Yes Yes No. of observations Notes: *** p<0.01, **p<0.05, * p<0.1 O Connell (IFS/UCL) Toulouse Workshop 19 / 27 December / 27
23 Preliminary results Demand conditional on retailer choice Variables Drink Sweet Savoury Non Food Expenditure *** *** *** *** (0.0001) (0.0001) (0.0002) (0.0002) PriceFruit *** *** *** *** (0.0005) (0.0005) (0.0008) (0.0008) PriceVegetables *** *** *** (0.0004) (0.0004) (0.0006) (0.0007) PriceGrain *** *** *** *** (0.0005) (0.0005) (0.0008) (0.0009) PriceDairy *** *** *** *** (0.0007) (0.0006) (0.0010) (0.0011) PriceMeat *** *** *** *** (0.0008) (0.0008) (0.0014) (0.0015) PriceDrink *** *** * (0.0006) (0.0004) (0.0007) (0.0008) PriceSweet *** *** *** *** (0.0004) (0.0006) (0.0007) (0.0008) PriceSavoury *** *** *** *** (0.0007) (0.0007) (0.0016) (0.0013) Time effects Yes Yes Yes Yes Fixed effects Yes Yes Yes Yes No. of observations Notes: *** p<0.01, **p<0.05, * p<0.1 O Connell (IFS/UCL) Toulouse Workshop 20 / 27 December / 27
24 Preliminary results Demand conditional on retailer choice Conditional elasticities in Tesco Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Expenditure Notes: Number (i, j) gives percent change in demand for product j with respect to a 1 percent increase in price for product i O Connell (IFS/UCL) Toulouse Workshop 21 / 27 December / 27
25 Preliminary results Demand conditional on retailer choice Conditional elasticities in Tesco Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Expenditure Notes: Number (i, j) gives percent change in demand for product j with respect to a 1 percent increase in price for product i O Connell (IFS/UCL) Toulouse Workshop 21 / 27 December / 27
26 Preliminary results Demand conditional on retailer choice Conditional elasticities in Tesco Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Expenditure Notes: Number (i, j) gives percent change in demand for product j with respect to a 1 percent increase in price for product i O Connell (IFS/UCL) Toulouse Workshop 21 / 27 December / 27
27 Retailer demand Unconditional elasticities in Tesco Preliminary results Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Fruit Vegetables Grain Dairy Meat Drink Sweet Savoury Non Food Notes: Number (i, j) gives percent change in demand for product j with respect to a 1 percent increase in price for product i O Connell (IFS/UCL) Toulouse Workshop 22 / 27 December / 27
28 Preliminary results Firm own price elasticity There are strong complementarities across goods within a supermarket Increasing price of one good, creates a reduction in demand for most goods sold in supermarket Can measure strength of this effect through firm own price elasticity Percent change in demand for all of a retailer s produce in response to 1% increase in all prices in that retailer O Connell (IFS/UCL) Toulouse Workshop 23 / 27 December / 27
29 Preliminary results Firm own price elasticity There are strong complementarities across goods within a supermarket Increasing price of one good, creates a reduction in demand for most goods sold in supermarket Can measure strength of this effect through firm own price elasticity Percent change in demand for all of a retailer s produce in response to 1% increase in all prices in that retailer Retailer Firm own price elasticity Asda Morrisons Sainsbury s Tesco O Connell (IFS/UCL) Toulouse Workshop 23 / 27 December / 27
30 Retailer demand Unconditional meat elasticities Preliminary results Asda Morrisons Sainsbury s Tesco Asda Morrisons Sainsburys Tesco Notes: Number (i, j) gives percent change in demand for product j with respect to a 1 percent increase in price for product i O Connell (IFS/UCL) Toulouse Workshop 24 / 27 December / 27
31 Retailer-good margins Preliminary results Asda Morrisons Sainsbury s Tesco Fruit Vegetables Grains Dairy Meat Drinks Sweet Savoury Non food Profit O Connell (IFS/UCL) Toulouse Workshop 25 / 27 December / 27
32 Preliminary results Marginal costs and producer prices over time O Connell (IFS/UCL) Toulouse Workshop 26 / 27 December / 27
33 Summary Preliminary results Aim is to model consumer demand and supermarket pricing in UK food market And to use model to gauge relative importance of changes in retailers costs demand conditions faced by retailers on recent large changes in UK food prices Next steps include Modelling choice over total grocery expenditure Possibly using producer price information in estimation Conduct counterfactuals O Connell (IFS/UCL) Toulouse Workshop 27 / 27 December / 27
34 Preliminary results Consumer s problem conditional on retailer choice Conditional on choosing supermarket s, consumer i in week t solves max U i(u i (q ist ), n ist ) (q ist,n ist ) s.t. p st q ist + n ist = X it Where q its = (q is1t,..., q isjt ) are quantities of supermarket goods n its is total quantity of non-supermarket non-durable (numeraire) p st = (p s1t,..., p sjt ) are prices for J goods within the supermarket X it is weekly non-durable expenditure O Connell (IFS/UCL) Toulouse Workshop 27 / 27 December / 27
35 Preliminary results Consumer s problem conditional on retailer choice Conditional on choosing supermarket s, consumer i in week t solves max U i(u i (q ist ), n ist ) (q ist,n ist ) s.t. p st q ist + n ist = X it Which implies Conditional demands for supermarket goods w isjt p sjtq isjt = f ij (p st, x ist ) j x ist where x ist p st q ist is total supermarket expenditure A total supermarket expenditure rule And indirect utility x ist = F i (p st, X it ) φ i (p st, X it ) Back: Expenditure O Connell (IFS/UCL) Toulouse Workshop 27 / 27 December / 27
36 Prices Preliminary results From transaction level prices for 100,000s of different products, need to compute prices for 9 broad goods in each retailer Define 43 sub-goods and define market t retailer s price as volume weighted mean transaction price Where weights are time and retailer varying Captures retailer price of narrowingly defined good - e.g. poultry in Tesco Aggregate up to market t retailer s price for good j by computing an expenditure weighted mean over relevant sub-goods Where weights are constant across markets and retailers Captures price offering for, e.g. meat in Tesco, allowing for weighting of meat components based on long run average behaviour Back: Goods O Connell (IFS/UCL) Toulouse Workshop 27 / 27 December / 27
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