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Dealer Price Discrimination in New Car Purchases: Evidence from the

Consumer Expenditure Survey

Pinelopi Goldberg (JPE, 1996)

Presented by Jake Gramlich October 12, 2004

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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

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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)

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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

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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)

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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

ijttjtitijt XD ZH

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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

ii

jij

djjkj

k

kjj

ijjij

TRDS

EXiEXPTij

CDPFDFPOOLBL

TLD

)(

*

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Measurement Error:Measurement error of LHS vars

Variables: model info, smaller options, trade-in allowance, sales tax, financing, fees.

Solutions:1. Imputation2. Lack of correlation with RHS variables (so we still have

consistent results)3. Tests for above

Measurement error of RHSVariable: Race, Gender of bargainerSolution: Race correlated, Gender biased towards

finding discrimination

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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

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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 predictable2. There is variation in prices paid: optimal for seller to bargain

• How to explain Ayres & Siegelman?1. Minorities choose stores with systematically lower prices2. Sample Selection Bias: Discriminated drop out of market3. Second Moments: Wider spread of reservation prices for

minorities

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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

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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 higher2. 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…

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i. Variances in Discounts Paid

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ii. Empirical Discount Distributions

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iii. Quantile Regression:

• Dependent Variable = D• R-Square = .18, Obs = 1,279

OLS Median 10% Quant 90% Quant

Minority -248

(-1.04)

-49

(-.27)

-784

(-2.87)**

453

(1.81)*

Female -130

(1-.10)

-115

(-1.39)

190

(1.52)

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(.08)

MinFem -22

(-.05)

-98

(-.34)

446

(1.06)

-380

(-.86)

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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

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Summary

• Ayres & Siegelman, Audit, price discrimination

• Goldberg, microdata, no price discrimination

• Reconciliation: Second moments

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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