1. Discuss how the full (random-coefficients) model conceptually differs from the (IV) logit demand model. What do the random coefficients tell us?2. The author estimates covariances between tastes for store brands, tastes for national brands, and the outside option. What do these estimates suggest? 3. Explain how the author estimates the supply-side model and specifically how this relates to the estimated demand model.4. Discuss the difference between the results of the two cases presented in the first counterfactual exercise.
Instructions ECON7012/8012 – Topic 6a Retail grocery markets A/Prof Jordi McKenzie, Department of Economics Paper Details • Luo R. (2018), ‘Store brands and retail grocery competition’, Journal of Economics & Management Strategy, 27, 653–668. Abstract Grocery retailers rank store brands as the most important factor that differentiates them from their competitors. Retailer competition should have a stronger impact on the more substitutable national brands than the more differentiated store brands. However, the literature has not studied the impacts empirically. In this paper, I quantify the different impacts of retailer competition on national brands and store brands using the scanner data of a U.S. chain retailer. I estimate a structural demand and supply model that incorporates the differentiation effect and retailer competition. The results show that national brand consumers are more likely to switch stores than store brands consumers. By analyzing two counterfactual cases, I find that 1) if the retailer did not sell store brands, its profit would decrease, and the loss would be greater in markets with more competitors; and 2) if the retailer competition had increased, then the national brands' retail prices would decrease more than the store brands' prices. Introduction • Grocery store brands are imperfect (cheap) substitutes to national brands ― Growth of store brands has drawn attention to retailers‘ strategic incentives to sell store brands ― One important incentive is to create differentiation from competing retailers • Unlike a national brand sold by different retailers, store brand exclusively sold by its retailer ― Thus, as competition increases, a retailer will drop the prices of the national brands more than those of the store brands • Retailer differentiation becomes more important as face more competitors Introduction • This paper studies these impacts using scanner data of a U.S. retailer chain, Dominick's in the ready-to-eat cereal category ― Competition is intense, with hundreds of national brands and store brands • To incorporate brand differentiation and retailer competition, set up a random coefficient discrete-choice demand model with two modifications: 1. Assume utility of outside option depends on number of competing retailers, which is different from standard zero mean assumption 2. Allow random coefficients for brand tastes to be correlated • In supply model, Dominick's chooses profit-maximizing prices for all brands • With demand estimates, compute unit costs and estimate supply model Counterfactual Analysis • Study two counterfactual cases: ― First shows Dominick's would reduce national brands’ prices if didn’t sell store brands and national brands’ wholesale prices were fixed ― Implies selling store brands creates brand differentiation and increases national brand prices ―Store brands become more important as competition increases ― In second case, assume each store faces 10% more competitors and solve for the new profit maximizing prices ―Results show Dominick's would drop both national and store brands' prices, but decreases in national brands would be larger Data • Data come from three sources: 1. Dominick's weekly scanner data 2. Economic Census, from which collect data on the number of food retailing stores and population for each zip code 3. Product characteristics collected from the Mr. Breakfast website • Dominick's is a chain grocery store in Chicago area ― Use data on ready-to-eat cereal products from January to July 1997 ― Data set records the product UPC, prices, average acquisition cost (AAC), quantity sold, and size by store every week • A market in this paper is a (store, week) pair ― Use 52 stores in cities near Chicago ― Only use observations from first week of each of 7 months ― In total have 364 store-week markets Data • The leading national brand manufacturers in 1997 were Kellogg, General Mills, Post, Quaker, Ralston, and Kashi ― Combine products that have same shape by company into one brand ― Four different shapes: ring, flake, shredded, and puff ― 23 brands in the data, with 19 national brands and 4 store brands • Product characteristics include dummies for grain, fruits, and nuts ― Take sales weighted average characteristics over products as the characteristics for the brand • To calculate market shares, assume that potential demand for ready-to-eat cereal is one pound per week per person ― Implies outside option's market shares between 33% and 99% ― Outside option means don’t buy cereals from a Dominick's store Summary Statistics Summary Statistics • Use number of retailers at zip code level to measure competition ― Underlying assumption is consumers shop within a zip code area • To see whether reasonable, collect data on the land area size of the zip codes and compare with the average shopping distance ― According to USDA, “the distance to the nearest supermarket or supercenter for the average U.S. household was 2.14 miles.” ― Because average area of zip codes is 11.71 square miles, the assumption of competition being within a market is not very strong Reduced-form Regressions • First column implies store brands have higher markups than national brands • Second column shows retailer competition has a negative impact overall ― Interaction implies competition has smaller impact on store brands Demand Model • Let j = 1, 2,…, J denote a brand of cereals, ?? = 1, 2,…,?? denote a store, and t = 1, 2,…, T denote a week • Consumer i’s utility from buying brand ?? in store ?? in week ?? is ― xj is vector of product characteristics (grain type dummies, fruit dummy, and nut dummy) of product j ― ???????? is price of brand j in store m in week t ― ?????? is store brand dummy, and ?????? is national brand dummy ― ???????? is unobserved (common) demand shock of ?? in ?? in period ?? ― ?????????? is an idiosyncratic random shock on ??'s utility of ?? • Coefficients for product characteristics is ?? • The consumer-specific price coefficient ???? captures heterogeneity in consumer price sensitivity • Consumers have heterogeneous tastes for national and store brands [??????; ??????] Demand Model • The outside option (?? = 0) means consumer either buys from a competing store or does not buy cereals. ― To capture retailer competition, assume mean utility of outside good function of number of competing retailers in zip code area, ???? ― Use median income to control for market-specific taste for the outside option that is related to the market income level ― Logarithm of median income in market ?? is ???????? • Consumer ??'s utility of the outside option in market ?? is: ― ????1 and ??2 are coefficients on ???? and ????????, and ?????? is the individual taste for the outside option ― ????1 is heterogeneous across consumers because competition can have varying impacts on consumers Demand Model • The vector of random coefficients is (????, ????1, ??????, ??????, ??????). ― Assume mean is [??; ??1; ????; ????; 0]. • Let ???? = (?????? ; ?????? ; ??????; ??????; ??????) be random component in the coefficients, which is the individual deviations from the mean ― Random vector ???? follows a correlated normal distributions, ??(??, Σ), with the joint distribution function ???? • Note that (??????, ??????) are independent and with (??????, ??????, ??????), but ??????, ??????, and ?????? can be correlated to measure correlation tastes for different brands ― Covariances between ?????? and ?????? is ??????, between ?????? and ?????? is ??????, and between ?????? and ?????? is ?????? Supply Model • Different stores in same zone sell same product at same price. ― Let Ω?? be the set of stores in zone ?? • Dominick's unit cost of selling product ?? in store ?? in period ?? is ― ???????? is (observed) AAC market-specific wholesale cost ― ???? is unobserved zone-specific management cost that measures labor cost, property leasing cost, electricity cost, and other management costs per pound of cereal ―Varies across zones but same across periods and across brands for the same zone ― ???????? is an unobserved brand-zone level cost shock, which is assumed at zone level to match the zone level prices • Total weekly profits in a zone are sum of weekly profits of all stores in zone • Let ???? be the time invariant market size of store ?? • The profit-maximization problem for zone ?? in week ?? is ― ????????(??????, ????) is share of Dominick's brand ?? in market ?? ― ?????? is the vector of all brands' prices • The first order conditions (FOC) of the profit maximization problem are Supply Model and Profit Maximization Instruments and Estimation • Estimate parameters in demand model using two-stage GMM and use them and FOCs for prices to calculate the costs ― Regress differences between unit costs and AACs on zone dummies to estimate ?? • An endogeneity issue exists in identifying price coefficient ― Unobserved demand shocks may be positively correlated with prices ― Use average characteristics of competing brands and wholesale costs of same brand and of competing brands as IVs for price • The GMM objective function is ??(??)??′(????′ )−1????(??), where ?? is the IV matrix ― To compute the shocks ?? for a given parameter ??, use iterations over ?? to match the model-predicted market shares with the data ― Simulate 200 consumers for each market where a consumer is characterized by his/her individual vector of ???? Estimation Results Discussion of Results • Consumers prefer cereals made from bran, rice, and corn ― Cereals with nuts give higher utility, while fruits are not as preferred • The Logit model underestimates the price coefficient because the unobserved demand shocks are positively correlated with prices ― Price coefficient estimate is −1.34 and significant in the full model • The estimates of ??1 are positive and significant in all specifications ― Consumer's utility of the outside option increases when the number of retailers in the area increases ― More consumers choose outside option as competition increases Discussion of Results • Variance of price coefficient ???? is 0.18, implying a standard deviation of 0.42 • Variance of ????1 close to zero, which means no significant heterogeneity in retailer competition on utility of outside option • Covariances imply consumers' taste for outside option is negatively correlated with taste for store brands, and positively correlated with taste for national brands ― As retailer competition increases, national brands customers switch to the outside option more often than the store brands customers ― Store brands increasingly important as face more competitors Elasticities • The (??, ??)th element is demand elasticity of brand ?? (row) against price of brand ?? (column) ― Diagonal elements show consumers' elasticities of Dominick's store brands are greater than national brands except for Post brands ― Cross-demand elasticities are higher among national brands than between national and store brands • Counterfactual Exercise No. 1 ― Impact of Removing Store Brands •