Nick Bloom, Labor Topics 247, 2011 1 LABOR TOPICS Nick Bloom Discrimination.

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Nick Bloom, Labor Topics 247, 2011 1 LABOR TOPICS Nick Bloom Discrimination
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Transcript of Nick Bloom, Labor Topics 247, 2011 1 LABOR TOPICS Nick Bloom Discrimination.

Page 1: Nick Bloom, Labor Topics 247, 2011 1 LABOR TOPICS Nick Bloom Discrimination.

Nick Bloom, Labor Topics 247, 2011 1

LABOR TOPICS

Nick Bloom

Discrimination

Page 2: Nick Bloom, Labor Topics 247, 2011 1 LABOR TOPICS Nick Bloom Discrimination.

Nick Bloom, Labor Topics 247, 2011 2

Thoughts on Bertrand and Mullainathan

Other papers

A research idea

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Nick Bloom, Labor Topics 247, 2011 3

Comments on Bertrand and Mullainathan (1/2)

• I love this kind of paper – ingenious, informative & well executed. It took a lot of effort but was clearly well worth it.

• Developed the idea far beyond just black/white names:• Always need to push multiple angles • Takes time and feedback (seminars)

• Think big – raising funds for good studies is not impossible (at least not at Stanford). Best way is step-by-step: pilot, raise small sum, bigger pilot, raise a larger sum etc…

• Collect data on everything – they recorded lots of information, and kept all the adverts during the period

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Nick Bloom, Labor Topics 247, 2011 4

Comments on Bertrand and Mullainathan (2/2)

• Table 7 is a good example of a well explained table – in particular the full footnotes!• Tables & figures should be self contained

• I assume much of section “IV Interpretation” derived from seminar and referees feedback. When writing a paper always acknowledge problems and try to address them

• Also to note: papers accrue footnotes in response to comments and feedback – e.g. footnote 43. Better to keep these in and drop in the refereeing process

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Nick Bloom, Labor Topics 247, 2011 5

Thoughts on Bertrand and Mullainathan

Other papers

A research idea

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Nick Bloom, Labor Topics 247, 2011 6

The Nature and Extent of Discrimination in the Marketplace: Evidence from the Field

Quarterly Journal of Economics, 2004

by John List (Chicago)

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Nick Bloom, Labor Topics 247, 2011 7

Shows evidence of statistical discrimination in buying and selling of baseball cards

• Paper uses four different experiments employing subjects at baseball card conventions to test between:• Animus discrimination• Statistical discrimination• Bargaining ability differences (not an issue in B&M)

• Finds evidence of discrimination against women, minorities and old people (those aged above 30!)

• Effects mostly initial offer price, to a lesser extent final acceptance price, and also bargaining time

• Strongest effect for least experienced minorities

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Nick Bloom, Labor Topics 247, 2011 8

Innovative methodology of multiple tests and direct recruitment of the public (1/4)

The paper is very well thought out in terms of running four different experiments to distinguish between hypothesis

Experiment A: Recruit subjects to randomly approach dealers to buy/sell cards. Select mix of subjects by demographics

- Also collect information on subjects- Different subjects approach same dealer

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Nick Bloom, Labor Topics 247, 2011 9

Evidence for discrimination (1/3)

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Nick Bloom, Labor Topics 247, 2011 10

Evidence for discrimination (2/3)

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Nick Bloom, Labor Topics 247, 2011 11

Evidence for discrimination (3/3)

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Nick Bloom, Labor Topics 247, 2011 12

Innovative methodology of multiple tests and direct recruitment of the public (2/4)

Experiment B: Also asks subjects to play a $5 dictator game, telling them in advance demographics of their partner

Finds no evidence of differential treatment (i.e. no animus)

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Nick Bloom, Labor Topics 247, 2011 13

Innovative methodology of multiple tests and direct recruitment of the public (3/4)

Experiment C: Also asks subjects to play two Chamberlain games – in one people are given random reservation prices, in the other they are not

- Finds no evidence of differential treatment in first game- Finds evidence of differential treatment in the second

Suggests discrimination related to dealers views over different reservation prices

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Nick Bloom, Labor Topics 247, 2011 14

Innovative methodology of multiple tests and direct recruitment of the public (4/4)

Experiment D: Play Vickrey (second-price) auctions to find out subjects reserve valuations for cards

Evidence minorities, women and older people have more dispersion, so discrimination is profit maximizing

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Nick Bloom, Labor Topics 247, 2011 15

Impressive paper, but rather complex

Neat paper with clear identification and well thought out. But less cited than B&M (100 vs 500 Google scholar hits)

Key reason is probably complexity – B&M has one neat idea and simple execution (and a memorable title).

But complexity matters less in long-run – so should age well

List takes a number of steps to ease presentation – like bullet point result summaries, e.g.

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Nick Bloom, Labor Topics 247, 2011 16

ORCHESTRATING IMPARTIALITY: THE IMPACT OF “BLIND” AUDITIONS ON FEMAL MUSICIANS

American Economic Review, 2000

Claudia Goldin and Cecilia Rouse

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Nick Bloom, Labor Topics 247, 2011 17

Finds evidence in favor of discrimination against females

Evidence that orchestra’s historically had been discriminatory towards women:

“I just don’t think women should be in orchestras”

Zubin Mehta, conductor to the LA and NY Philharmonics from 1964-1978 and 1978-1990 respectively

Orchestras started introducing blind auditions in 1970s and 1980s, but with a wide time spread (Boston had some in the 1950s while Cleveland still had none in 2000)

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Nick Bloom, Labor Topics 247, 2011 18

Uses data from staggered introduction of blind orchestra auditions

In the raw data the success rate of females in auditions after the introduction of blind auditions goes down!

But if you control of quality – i.e. look at people who repeatedly audition – it goes up

Hence, evidence is that:

(A) Blind auditions helped improved female success rates(B) As a result more marginal female candidates applied, pushing down average success rates of women

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Nick Bloom, Labor Topics 247, 2011 19

Women have a lower unconditional success rate in blind auditions

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But a higher success rate conditional on taking part in blind and non-blind auditions (i.e. controlling for selection changes)

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Nick Bloom, Labor Topics 247, 2011 21

Simple neat idea which is well executed

Key idea of using blind-orchestra auditions is great – simple to understand and clean results

Also well written, in that clear on it’s statistical defects (small sample and reversed results) – again, do acknowledge issues

As a result is quite well cited and well known

Also fits the AER shorter-papers format – crisp clean result

Only fly in the ointment is the semi-final results reverse

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Nick Bloom, Labor Topics 247, 2011 22

TESTING THEORIES OF DISCRIMINATION: EVIDENCE FROM THE WEAKEST LINK

Journal of Law & Economics, 2004

Steve Levitt

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Nick Bloom, Labor Topics 247, 2011 23

Uses data from “The Weakest link” game shows & finds limited discrimination evidence

Game show where:(i) The final prize is a function of number of correctly

answered questions(ii)Only one winner that collects this final prize(iii) Start with many contestants and they vote each other out

Strategy is early on to vote out bad contestants and later on to vote out good contestants

Finds some evidence for:• statistical discrimination against hispanics: voted out more

early on and less later then prior performance warrants• animus discrimination against old people (50+): always

voted out more often

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Nick Bloom, Labor Topics 247, 2011 24

The visible hand: race and online market outcomes

Stanford mimeo (2010)

Jennifer Doleac and Luke Stein

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Nick Bloom, Labor Topics 247, 2011 25

Randomizes over the hand color holding an IPod sold on-line to test for discrimination

Find black sellers receive 17% less offers than white sellers

Similar in size to having a wrist tattoo

Black sellers also face lower trust (buyers less willing to use names in an e-mail, provide an address etc.)

Discrimination particularly a problem in thin markets – competition helps drive out discrimination

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Nick Bloom, Labor Topics 247, 2011

Photos (my hand is bottom left)