1. 1 Dealer Price Discrimination in New Car Purchases: Evidence from the Consumer Expenditure Survey Pinelopi Goldberg (JPE, 1996) Presented by Jake Gramlich October 12, 2004

2. 2 Introduction Is there price discrimination in the new car market? Ayres & Siegelman (1995) –Audit Study: yes Goldberg (1996) –Microdata: no How can we reconcile these two findings? –Second moments of reservation prices

3. 3 Two-part paper: 1. Present evidence from the Consumer Expenditure Survey (CES) that contradicts Ayres & Siegelman’s findings of racial and gender discrimination 2. Reconcile the two studies by looking at second moments of discounts (and thus implied reservation prices)

4. 4 Microdata approach Instead of audit method, use microdata (CES) on actual purchases and transaction prices of new cars Advantages relative to audit method: –Data are on actual purchases –Nationwide (not Chicago area) –More car models (not just 9 representative models) Disadvantage relative to audit method –No controlled environment Only household data No dealership data

5. 5 Data CES, 1983-1987, quarterly, pooled Household’s asked: –Household characteristics –Household car purchase activity –Household’s stock of owned vehicles –Disposal of old cars –Trade-in –Financing Representative of U.S. population 32,000 households; 3,000 bought cars; 1,279 bought from dealers for personal use 67 minorities (Black, Hispanic, American Indian)

6. 6 Model Estimation Equation: –D = discount –i = individual –j = model –t = time –H = household characteristics (vector) –Z = model characteristics (vector of dummies) –X = time dummies –ε = iid error term

7. 7

8. 8 Discounts List = base + options + destination fees + dealer prep fees + dealer specific costs Transaction = (Expenditure – Expenses) / Sales Tax + Trade-in value Absolute (not relative) – profit, not power

9. 9 Measurement Error: Measurement error of LHS vars Variables: model info, smaller options, trade- in allowance, sales tax, financing, fees. Solutions: 1. Imputation 2. Lack of correlation with RHS variables (so we still have consistent results) 3. Tests for above Measurement error of RHS Variable: Race, Gender of bargainer Solution: Race correlated, Gender biased towards finding discrimination

10. 10 Regression Results (Table 2) Significant: –Intercept (-) –Rural (-) –Midwest (+) –dealer financing (+) –first time buyer (+) –trade-in (-) –Q3/4p (+), Q4s (-) –CLAO*Minority (-) Not Significant: –minority (-) –female (-) –minority female (-) –Wealth controls (-) Dependent Variable = D R-Square =.18, Obs = 1,279

11. 11 Take-home from CES Regression Conclusion from microdata is no price discrimination due to race or gender Then why bargain? 1. Bargaining power relevant, just not predictable 2. There is variation in prices paid: optimal for seller to bargain How to explain Ayres & Siegelman? 1.Minorities choose stores with systematically lower prices 2.Sample Selection Bias: Discriminated drop out of market 3.Second Moments: Wider spread of reservation prices for minorities

12. 12 Possibility 2: Sample Selection Bias Discriminated household’s don’t purchase, or purchased used cars Arguments against this explaining difference between two studies: –Ayres & Siegelman find same discrimination pattern in 20% of sample reaching agreement –Visiting dealership indicates willingness to pay approximately equal to retail price – you might visit another dealership, but you wouldn’t leave the market –Re-estimate model with Selection Equation (used, drop out) Similar to OLS results The correlation coefficient between the error terms of the selection and regression equations is statistically insignificant => “no selection bias” hypothesis unrejected

13. 13 Possibility 3: Second Moments Blacks’ distribution of reservation prices is spread out Bargaining theory predicts sellers use whole distribution of buyer reservation prices in making offers Example –Reservation prices: $4k, $6k (type A) v. $3k, $7k (B) –Initial offers higher of $6k and $7k (respectively; types costlessly observed) –Final offers depend on parameters, strategies, but likely that $3k will receive lower (using patience to bargain longer) If blacks have higher spread of reservation prices, bargaining theory predicts: 1.First round offers to blacks higher 2.In equilibrium, low-value blacks receive lower final offers than low-value whites (and vice-versa) 3.For some parameters, groups pay same average prices Econometric Evidence i-iii…

14. 14 i. Variances in Discounts Paid

15. 15

16. 16 ii. Empirical Discount Distributions

17. 17

18. 18 iii. Quantile Regression: Dependent Variable = D R-Square =.18, Obs = 1,279 OLSMedian10% Quant90% Quant Minority-248 (-1.04) -49 (-.27) -784 (-2.87)** 453 (1.81)* Female-130 (1-.10) -115 (-1.39) 190 (1.52) 1 (.08) MinFem-22 (-.05) -98 (-.34) 446 (1.06) -380 (-.86)

19. 19 Summary of i - iii Empirical discount distributions for minorities is more spread out than the distribution for white males –Explains initial offer disparity What about final offer disparity? –Ayres & Siegelman “final offers” are poor indicators of transaction prices (since they do not lead to sales) –Ayres & Siegelman imposed uniform bargaining strategy. This indicates from where on the distribution you come Systems analyst at a bank Wealthy suburb of Chicago

20. 20 Summary Ayres & Siegelman, Audit, price discrimination Goldberg, microdata, no price discrimination Reconciliation: Second moments

21. 21 Comments CES Regression? –Signs were headed in right direction (increase N, increase R-square) –Especially few minorities Story of wider spread in minority reservation prices? –Not income (controlled for) –Aggressive v. Unaggressive heterogeneity? –Aggressive v. Uninformed? Link between reservation prices and discounts? –More careful treatment of bargaining theory