1. U. S. Bureau of Labor Statistics Price Differentials Across Outlets in CPI Data, 2002-2007 John Greenlees Robert McClelland May 15, 2008

2. 2 New Outlets Bias New Outlets Bias can arise from the failure of the CPI to adequately reflect the gains to consumers from the appearance of new types of product outlets These welfare gains can arise from: –Greater convenience (e.g., Internet shopping) –Greater product variety (e.g., Tuscan restaurants) –Lower prices (e.g., Wal-Mart, Costco) This paper focuses only on the lower-price effect

3. 3 Price Effects of New Outlets The CPI does not reflect differences in prices between products at different sample outlets –Differences across outlets are implicitly treated as entirely reflecting quality differentials Currently, the most interest concerns the low prices offered at discount department stores like Wal  Mart and warehouses and club stores like Costco

4. 4 Empirical Studies New Outlets Bias is a long-recognized issue Hoover and Stotz (1964) Reinsdorf (1993) White (2000) Hausman and Leibtag (2004, 2005)

5. 5 Empirical Approach Use CPI Research Database for 2002-2007 Select relatively, but not completely, homogeneous CPI food item categories Regress price on item characteristics, with dummies for time and for outlet fixed effects Estimate changes in average outlet premium or discount, and average item quality, over time Decompose outlet effects within and across outlet categories

6. 6 Key Advantages of Our Approach Uses actual CPI microdata Uses regression estimation to incorporate variations in item characteristics Examines outlet differentials in general, not just across pre-specified outlet categories Analyzes item quality change, not just outlet effects Compares hedonic to matched-model approach

7. 7 CPI Sample 14 Food ELIs corresponding to categories used earlier by Reinsdorf and Hausman/Leibtag –Some more homogeneous than others 69 months from January 2002 through September 2007 About 8,000 outlets About 16,000 “quote strings” About 360,000 price quotes

8. 8 Sample Shares by Outlet Type, 2002-2007

9. 9 Hedonic Regression Models We estimate 14 regressions, one for each of our item categories Dependent variable is ln P ijt, the log-price of item i in outlet j in time t. RHS variables include item characteristics, outlet fixed effects, and dummies for month Regressions yield a monthly price index for each item category with January 2002=100.

10. 10 Price Trends with Outlet Fixed Effects

11. 11 Index log-changes by Item Category, 2002-07

12. 12 Overall Results Outlet effect = -0.26 percent/year Item characteristics effect = +0.20 percent/year Difference between hedonic and matched-model index = -0.25 percent/year

13. 13 Weighted Sample Average Outlet Effects by Outlet Category

14. 14 Conclusions (1) We find significant new outlet effects –Averaging -0.26 percent per year –Lowering prices for 10 of 14 items –This result is after adjusting for differences in item characteristics across outlets –Remember, some of these effects may be due to differences in outlet quality

15. 15 Conclusions (2) Most of the outlet effects do not arise from growth in the discount department store category –Warehouse category growth is also important –About 1/3 of total outlet effect comes from changes in average outlet premiums within categories

16. 16 Conclusions (3) We also identify large effects of changes in item characteristics –Even within our relatively homogeneous item categories –Hedonic model estimates average quality increase at 0.20 percent per year –Differences between hedonic and matched model estimates warrant further study of how CPI adjusts for quality