orchestrating impartiality: the impact of blind auditions

Orchestrating Impartiality: The Impact of "Blind" Auditionson Female Musicians

By CLAUDIA GOLDIN AND CECILIA ROUSE*

A change in the audition procedures of symphony orchestras—adoption of "blind"auditions with a "screen" to conceal the candidate's identity from the jury—provides a test for sex-hiased hiring. Using data from actual auditions, in anindividual fixed-effects framework, we find that the screen increases the probabilitya woman will be advanced and hired. Although some of our estimates have largestandard errors and there is one persistent effect in the opposite direction, theweight of the evidence suggests that the blind audition procedure fostered im-partiality in hiring and increased the proportion women in symphony orchestras.(JEL n'

Sex-biased hiring has been alleged for manyoccupations but is extremely difficult to prove.The empirical literature on discrimination, de-

* Goldin; Depanment of Economics, Harvard University,Cambridge, MA 02183; Rouse: Woodrow Wilson School,Princeton University, Princeton, NJ 08544. Rouse acknowl-edges The National Academy of Education, the NAE SpencerPostdoctoral Fellowship Program, and the Mellon Eoundationfor financial support. We are indebted to the staff members ofthe orchestras thai gave us access to their audition records andwho provided other assistance, and to the musicians whoresponded to our questionnaire. We are particularly grateful toJoanne Berry, Brigit Carr, Ruth DeSamo. Stefanie Dyson, JoshFeidman, Barbara Haws, Oren Howard, Cindy Hubbard, CarolJacobs, Lynn Larsen, Bennett McClellan, Stephen Molina, BillMoyer, Jeffrey Neville, Stephen Novak, Deborah Oberschalp,Stacey Pelinka, Carl Schiebler, Alison Scott-Williams, RobertSirineck, Harold Steiman, and Brenda Nelson Strauss. We alsothank Gretchen Jackson of the University of Michigan Schoolof Music. Rashid Alvi. Brigit Chen. Eric Hilfers, Serena May-eri, LaShawn Richburg, Melissa Schettini, Thomas Tucker,Linda Tuch, and Lavelle (Yvette) Winfield served as ourextremely able research assistants. David Howel! of the Prince-ton University Department of East Asian Studies and Jin HeumPark kindly helped to determine the gender of Japanese andKorean names. We thank them all. We are grateful to ourcolleagues David Card, Anne Case, David Cutler, AngusDeaton, Hank Fart>er, Lany Kalz, Alan Krueger, David Lee,and Aaron Yelowitz for helpful conversations, and to seminarparticipants al the School of Industrial and Labor Relations atCornell University, University of Illinois at Champaign-Urbana, Princeton University, Utiiversity of Toronto, HarvardUniversity, and Vanderbilt University. We also thank twoanonymous referees for comments that have made this a betterpaper. Any remaining errors are ours. Unfortunately the dataused in this article are conlidential and may not be madeavailable to other researchers.

riving from the seminal contributions of GaryBecker (1971) and Kenneth Arrow (1973), hasfocused mainly on disparities in earnings be-tween groups (e.g., males and females), givendifferences in observable productivity-alteringcharacteristics. With the exception of variousaudit studies (e.g., Genevieve Kenney andDouglas A. Wissoker, 1994; David Neumark etal., 1996) and others, few researchers have beenable to address directly the issue of bias inhiring practices.' A change in the way sym-phony orchestras recruit musicians provides anunusual way to test for sex-biased hiring.

Until recently, the great symphony orches-tras in the United States consisted of tnemberswho were largely handpicked by the musicdirector. Although virtually all had auditionedfor the position, most of the contenders wouldhave been the (male) students of a select

' An extensive literature exists on occupational segrega-tion by sex and the possible reasons for the large differencesin occupations between men and women today and in thepast. The debate is ongoing. On the one hand are those whobelieve that discrimination, either individual or societal innature, is the driving force, and on the other hand are thosewho claim the evidence shows women and men sort amongoccupations on the basis of different tastes for work char-acteristics. In the former category see Paula England (1982)and England et al. (1988); in the latter group see SolomonW. Polachek (1979) and Randall K. Filer (1989). It shouldbe noted that many other studies (e.g., Ian Ayres and JoelWaldfogel, 1994) have also attempted to measure discrim-ination in atypical ways.

715

716 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 2000

group of teachers. In an attempt to overcomethis seeming bias in the hiring of tnusicians,most major U.S. orchestras changed their au-dition policies in the 197O's and l980's mak-itig them more open and routinized. Openingsbecame widely advertised in the union papers,and many positions attracted more than 100applicants where fewer than 20 would havebeen considered before. Audition committeeswere restructured to consist of members ofthe orchestra, not just the conductor and sec-tion principal. The audition procedure becamedemocratized at a time when many other in-stitutions in America did as well.

But democratization did not guarantee impar-tiality, because favorites could still be identifiedby sight and through resumes. Another set ofprocedures was adopted to ensure, or at least givethe impression of, impartiality. These proceduresinvolve hiding the identity of the player from thejury. Although they take several forms, we use theterms "blind" and "screen" to describe the group."The question we pose is whether the hiring pro-cess became more impartial through the use ofbhnd auditions, Because we are able to identifysex, but no other chiiracteri sties for a large sample,we focus on the impact of the screen on theemployment of women."

Screens were not adopted by all orchestras atonce. Among the major orchestras, one stilldoes not have any blind round to their auditionprocedure (Cleveland) and one adopted thescreen in 1952 for the preliminary round (Bos-ton Symphony Orchestra), decades before theothers. Most other orchestras shifted to blindpreliminaries from the early 197O's to the late198O's. The variation in screen adoption at var-ious rounds in the audition process allows us toassess its use as a treatment.''

The change in audition procedures withthe adoption of the screen allows us to testwhether bias exists in its absence. In both our

' For an article about the blind audition process see TheEconomht 0996).

' The screen may also have opened opprortunities forindividuals from less-welNknown orchestras, those trainedoutside mainstream institutions, and those from minoritygroups,

"" The blind audition procedures bear some resemblanceto "double-blind" refereeing in academic journals. See Re-becca Blank (1991) for an assessment of the treatment effectof such refereeing in the American Economic Review.

Study and studies using audits, the issue iswhether sex (or race or ethnicity), apart fromobjective criteria (e.g., the sound of a musicalperfonnance, the content of a resume), is con-sidered in the hiring process. Why sex mightmake a difference is another matter.

Our data come from two sources; rosters andaudition records. Rosters are simply lists oforchestra personnel, together with instrumentand position (e.g., principal), found in orchestraprograms. The audition records are the actualaccounts of the hiring process kept by the per-sonnel manager of the orchestra. Both are de-scribed in more detail below.

The audition records we have collected form anuncommon data set. Our sample includes whowas advanced and hired from an initial group ofcontestants and also what happened to approxi-mately two-thirds of the individuals in our data setwho competed in other auditions in the sample.There are, to be certain, various data sets contain-ing information on applicant pools and hiringpractices (see, e.g., Harry Holzer and David Neu-mark, 1996). But our data set is unique because ithas the complete applicant pool for each of theauditions and links individuals across auditions.Most important for our study is that audition pro-cedures differed across orchestras in known waysand that the majority of the orchestras in oursample changed audition procedure during the pe-riod of study."''

We find, using our audition sample in an indi-vidual fixed-effects framework, that the screenincreases the probability a woman will be ad-vanced out of a preliminary round when there isno semifinal round. The screen also greatly en-hances the likelihood a female contestant will bethe winner in a final round. Using both the rosterand auditions samples, and rea.sonable assump-tions, the switch to blind auditions can explainabout one-third of the increase in the proportionfemale among new hires (whereas another one-third is the result of the increased pool of femalecandidates). Estimates based on the roster sampleindicate that blind auditions may accotint for 25percent of the increase in the percentage of or-chestra musicians who are female.

^ This statement is true for the roster sample. There areonly a few orchestras that changed audition proceduresduring the years of our audition data.

VOL 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIAUTY 717

I. Sex Composition of Orchestras

Symphony orchestras consist of about 100musicians and, although the number has var-ied between 90 to 105, it is rarely lower orhigher. The positions, moreover, are nearlyidentical between orchestras and over time.As opposed to firms, symphony orchestras donot vary much in size and have virtually iden-tical numbers and types of jobs. Thus we caneasily look at the proportion women in anorchestra without being concerned aboutchanges in the composition of occupationsand the number of workers. An increase in thenumber of women from, say, 1 to 10, cannotarise because the number of harpists(a female-dominated instrument), has greatlyexpanded. It must be because the proportionfemale within many groups has increased.

Among the five highest-ranked orchestrasin the nation (known as the "Big Five")—theBoston Symphony Orchestra (BSO), the Chi-cago Symphony Orchestra, the ClevelandSymphony Orchestra, the New York Philhar-monic (NYPhil), and the Philadelphia Or-chestra—none contained more than 12percent women until about 1980.^ As can beseen in Figure lA, each of the five lines(giving the proportion female) greatly in-creases after some point. For the NYPhil, theline steeply ascends in the early 1970"s. Forthe BSO, the turning point appears to be a bitearlier. The percentage female in the NYPhilis currently 35 percent, the highest among all11 orchestras in our sample after being thelowest (generally at zero) for decades. Thusthe increase of women in the nation's finestorchestras has been extraordinary. The in-crease is even more remarkable because, aswe discuss below, turnover in these orchestrasis exceedingly low. The proportion of newplayers who were women must have been,and indeed was, exceedingly high.

Similar trends can be discerned for fourother orchestras—the Los Angeles SymphonyOrchestra (LA), the San Francisco Philhar-monic (SF), the Detroit Symphony Orchestra,and the Pittsburgh Symphony Orchestra

^The data referred to, and used in Figures I to 3, arefrom orchestral rosters, described in more detail below.

(PSO)—given in Figure lB.^ The upwardtrend in the proportion female is also obviousin Figure IB, although initial levels are higherthan in Figure lA. There is somewhat morechoppiness to the graph, particularly duringthe 194O's. Although we have tried to elimi-nate all substitute, temporary, and guest mu-sicians, especially during World War II andthe Korean War, this was not always possible.

The only way to increase the proportionwomen is to hire more female musicians andturnover during most periods was low. Thenumber of new hires is graphed in Figure

2 for five orchestras. Because "new hires" is avolatile construct, we use a centered five-yearmoving average. In most years after the latel950's, the top-ranked orchestras in the group(Chicago and NYPhil) hired about four mu-sicians a year, whereas the other three hiredabout six. Prior to 1960 the numbers are ex-tremely high for LA and the PSO, because, ithas been claimed, their music directors exer-cised their power to terminate, at will, theemployment of musicians. Also of interest isthat the number of new hires trends down,even excluding years prior to 1960. The im-portant points to take from Figure 2 are thatthe number of new hires was small after 1960and that it declined over time.

The proportion female among the new hiresmust have been sizable to increase the pro-portion female in the orchestras. Figure3 shows the trend in the share of womenamong new hires for four of the "Big Five"(Figure 3A) and four other orchestras (Figure3B).^ In both groups the female .share of newhires rose over time, at a somewhat steeperrate for the more prestigious orchestras. Sincethe early l980's the share female among newhires has been about 35 percent for the BSOand Chicago, and about 50 percent for theNYPhil, whereas before 1970 less than 10percent of new hires were women.

Even though the fraction of new hires whoare female rises at somewhat different times

' Our roster sample also includes the Metropolitan OperaOrchestra and the St. Louis Symphony.

^ A centered five-year moving average is also used forthis variable.

^ In virtually all cases the share of women among newhires has decreased in the 1990" s.


A 0.4

BSOPhiladelphiaChicagoNYPhilCleveland

1940 1950 1960 1970 1980 1990

FIGURE 1. PROPORTION FEMALE IN NINE ORCHESTRAS, 1940 TO 1990"S

A: THE "BtG FIVE"; B: FOUR OTHERS

Source: Roster sample. See text.

across the orchestras, there is a discernibleincrease for the group as a whole in the late197O's to early 198O's, a time when the laborforce participation of women increased gen-erally and when their participation in variousprofessions greatly expanded. The question,therefore, is whether the screen mattered in adirect manner or whether the increase wasthe result of a host of other factors, includingthe appearance of impartiality or an increased

pool of female contestants coming out ofmusic schools. Because the majority of newhires are in their late twenties and earlythirties, the question is whether the most se-lective music schools were producing consid-erably more female students in the early1970"s. We currently have information byinstrument for only the Juilliard School ofMusic. With the exception of the brass sec-tion, the data, given in Figure 4, do not reveal

VOL. 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIALITY 719

22

20

18

16(A

% 14

120)

t 10^ ^

NYPhil—•— Chicago

LA^ ^ SF^ ^ PSO

1950 1960 1970 1980 1990

FIGURE 2. NUMBER OF NEW HIRES IN FIVF, ORCHESTRAS, 1950 TO 199O'S


Notes: A five-year centered moving average is used. New hires are musicians who were not with ihe orchestra the previousyear, who remain for at least one additional year, and who were not substitute musicians in the current year.

any sharp breaks in the fraction of all gradu-ates who are female.'" Thus, it is not imme-diately obvious that an expansion in thesupply of qualified female musicians explainsthe marked increase in female symphonyorchestra members; it could, therefore, be be-cause of changes in the hiring procedures oforchestras.

But why would changes in audition proceduresalter the sex mix of those hired? Many of the mostrenowned conductors have, at one time or another,asserted that female musicians are not the equal ofmale musicians. Claims abound in the world ofmusic that "women have smaller techniques thanmen," "are more temperamental and more likelyto demand special attention or treatment," and that"the more women [in an orchestra], the poorer the

'"We also have data on the .sex composition of thegraduates of the University of Michigan School of Musicand Indiana University, but not by instrument. In the Mich-igan data, both for those receiving the Bachelor of Music(BM) degree and for those receiving the Masier of Music(MM) degree, there is no change in ihe percentage femalefrom 1972 to 1996. The Indiana University data, for bothBM and MM degrees and excluding voice, piano, guitar,and early instruments, show an increase in the fractionfemale from 1975 to 1996. The ratio of females to maleswas 0.9 in 1975 but 1.2 in 1996.

sound."'' Zubin Mehta, conductor of the Los An-geles Symphony from 1964 to 1978 and of theNew York Philharmonic from 1978 to 1990, iscredited with saying, "I just don't think womenshould be in an orchestra."'^ Many European or-chestras had, and some continue to have, statedpoUcies not to hire women.'^ The Vienna Philhar-monic has only recently admitted its first femalemember (a harpist). Female musicians, it can beconvincingly argued, have historically faced con-siderable discrimination.'* Thus a blind hiringprocedure, such as a screen that conceals the iden-tity of the musician auditioning, could eliminate

"Seltzer (1989). p. 215.'^ Seltzer (1989), p. 215. According to Seltzer, the fact

that new hires at the NYPbil were about 45 percent femaleduring Mebta's tenure as conductor suggests that Mehta'sviews may have changed.

'•' In comparison with the Llnited Kingdom and the twoGermanys. tbe United States in 1990 had the highest percent-age female among its regional symphony orchestras and was aclose second lo the United Kingdom in the major orchestracategory (Juna J. Allmendinger et al., 1996).

'•* In addition, an African-American cellLst (Earl Madi-son) brought a civil suit against the NYPbil in 1968 allegingtbat their audition procedures were discriminatory becau.sethey did not use a screen. Tbe orche.stra was found not guiltyof discriminating in hiring permanent musicians, hut it wasfound to discriminate in hiring substitutes.


0.6

m 0.5

B

I

04

1950

0-6

« 0.5

0.4

0.301

to® 0.2(0Eto"- 0.1

0.0

1950

NY PhilBSOChicagoCleveland

1960 1970 1980 1990

^ v _ LASF

—0— Detroit—•— PSO

v— — — ' — — ' — • 1 • 1

1960 1970 1980 1990

FIGURE 3. FEMALE SHARE OF NEW HIRES IN EIGHT ORCHESTRAS. 1950 TO 1990'SA: FOUR OF THE "BIG FFVE"; B: FOUR OTHERS


Notes: A five-year centered moving average is used. New hires are musicians who were not with the orchestra the previousyear, who remain for at least one additional year, and who were not substitute musicians in Ibe current year.

the possibility of discrimination and increase thenumber of women in orchestras.

II. Orchestral Auditions

To understand the impact of the democra-tization of the audition procedure and the

screen, we must first explain how orchestraauditions are now conducted. After determin-ing that an audition must be held to fill anopening, the orchestra advertises that it willhold an audition. Each audition attracts mu-sicians from across the country and, often,

VOL. 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIALHY 721

1940 1950 1960 1970 1980 1990 2000

FIGURE 4. PROPORTION FEMALE OF JUILLIARD GRADUATES, TOTAL AND BY SECTION: 1947 TO 1995

Source: Juilliard Music School files.

from around the world.'^ Musicians inter-ested in auditioning are required to submit aresume and often a tape of compulsory music(recorded according to specific guidelines) tobe judged by members of the orchestra. Insome orchestras this prescreening is disposi-tive; in others the musician has the right toaudition live in the preliminary round, even ifthe audition committee rejects the candidateon the basis of the tape.'^ All candidates aregiven, in advance, most of the music they areexpected to perform at the live audition.

Live auditions today generally consist ofthree rounds: preliminary, semifinal, and final.But there is considerable variation. Although allorchestras now have a preliminary round, somehave two final rounds and in many there was nosemifinal round until the 198O's. The prelimi-nary is generally considered a screening roundto eliminate unqualified candidates. As a result.

the committee is free to advance as many, or asfew, as they wish. Candidates advanced fromthe semifinal round are generally considered"acceptable for hire" by the audition committee(which does not include the music director,a.k.a. conductor, until the finals). Again, thismeans that the committee can advance as manyas it wishes. The final round generally results ina hire, but sometimes does not.'^

In blind auditions (or audition rounds) ascreen is used to hide the identity of the playerfrom the committee.'^ The screens we haveseen are either large pieces of heavy (but sound-porous) cloth, sometimes suspended from theceiling of the symphony hall, or look like largeroom dividers. Some orchestras also roll out acarpet leading to center stage to muffle footstepsthat could betray the sex of the candidate.'^Each candidate for a blind audition is given anumber, and the jury rates the candidate's

'^ Orchestral auditions, particularly for the nation's mostprestigious orchestras, are national if nol international, inscope. Many contestants, the vast majority of whom receiveno travel reimbursement, travel long distances to audition.The auditions span the fewest number of days possible tominimize hotel charges.

"'The tape, in this case, provides information to thecandidate of his or her likelihood of success, sparing themusician a potentially large travel expense.

"There is one exception to this general rule. In rarecases when ihe committee cannot decide between two orthree candidates, each is invited to play with the orchestrabefore the final deci.sion is made.

"* It may also serve to hide the identity of ihe committeefrom the player, although thai is not ils main function. Weuse the terms "blind" and "screen" interchangeably.

'^ Or, if a carpel is not placed on the stage, the personnelmanager may ask a woman to take off her shoes and heprovides ihe compensating footstep.s.


performance next to the number on a sheet ofpaper. Only the personnel manager knows themapping from number to name and from nameto other personal information.^" The names ofthe candidates are not revealed to the juries untilafter the last blind round.

Almost all preliminary rounds are now blind.The semifinal round, added as the number ofapplicants grew, may be blind. Finals are rarelyblind and almost always involve the attendanceand input ofthe music director.^' Although themusic director still wields considerable power,the self-governance that swept orchestras in the197O's has served to contain the conductor'sauthoritarianism. The music director can ignorethe audition committee's advice, but does so atgreater peril. Once an applicant is chosen to bea member of an orchestra, lifetime tenure isawarded after a brief probationary period. Thebasis for termination is limited and rarely used.The positions we are analyzing are choice jobsin the musical world. In 1995 the minimumstarting base salary for musicians at the BSOwas $1,400 per week (for a 52-week year), notincluding recording contracts, soloist fees, over-time and extra service payments, bonuses, andper diem payments for tours and Tanglewood.^"

Are blind auditions truly blind, or can atrained, accomplished musician identify contes-tants solely from differences in playing style,just as academics can often identify authors ofdouble-blind papers they get to referee? Unlikedouhie-biind refereeing, for which one sees an

^ The personnel manager is generally a musician whoplayed with the orchestra for some time and knows theplayers and the conductor well. The duties involve manag-ing the day-to-day work of the orchestra, getting substitutemusicians, making travel plans, and arranging the hiring ofnew musicians.

^' It is almost always the case that if an orchestra in. say,the spring of 1986 holds a hlind preliminary round for aposition, it will have all its candidates audition blind in thatround and in all other preliminary rounds during that season,should there he any. That is. there is generally no discretionon the part ot" the jury (and certainty not on the part of thecontestant) in temi.s of the audition prcK-edure, particularlyonce an audition i.s underway.

" Most of the orchestra contracts in the group we haveexamined have similar base salatics. Union contracts listonly the minimum or base starting salary and minimumincrements for seniority. We do not know how many mu-sicians have individually negotiated rates above the statedminimum amounts.

entire paper with its distinctive writing style,methodology, sources, and citations, the candi-dates play only predetermined and brief ex-cerpts from the orchestral repertoire. Eachcandidate typically has just 5 to 10 minutes toplay for the audition committee, particularly inthe early rounds. There is little or no room forindividuality to be expressed and not much timefor it to be detected.^ Even when an individualmusician is known in advance to be auditioning,jury members often cannot identify that individ-ual. Only the rare, well-known candidate, withan unusually distinctive musical style couldconceivably be correctly identified.

The many musicians and personnel managerswith whom we have spoken uniformly deny thatidentification is possible for the vast majority ofcontestants. They also observe that, although itis tempting to guess the identity of a contestant,particularly in the later rounds, audition com-mittee members, more often than not, find theyare wrong. To base a hiring decision on specu-lation would not be in the best interests of theorchestra. Further, although an individual com-mittee member may believe that he or sheknows the identity of a player, it would be rarefor the entire committee to be secure in suchknowledge. Thus, even if one committee mem-ber's vote is swayed by such a belief, the com-mittee's vote must correspond to the consensusview of the player's musical ability for it todetermine the outcome. Thus, auditions heldwith a screen, apart from very few exceptions,are truly blind.

The audition procedures of the 11 orches-tras in the roster sample are summarized inTable \.^* Although audition procedures arenow part of union contracts, that was not thecase in the more distant past and the proce-dures were not apparently recorded in anysurviving documents. We gathered informa-tion on these procedures from varioussources, including union contracts, interviewswith personnel managers, archival documentson auditions, and a mail survey we conductedof orchestral musicians concerning the proce-

" Also, there is generally not a standing audition com-mittee that might hecome familiar with the musicians whoaudition frequently.

-•* We identify the orchestras by letter, rather than byname, to preserve confidentiality of the audition sample.

VOL. 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIAUTY 723

TABLE 1—ORCHESTRA AuDmoN PROCEDtiRE SUMMARY TABLE

Orchestra

A

B

C

D

EF

GHIJK

Preliminaries

Blind since 1973

Blind since al leasl 1967

Blind since at least 1979(definitely afler 1972)Blind since 1986

Use of screen varies until 1981Blind since at leasl 1972

Blind since 1986Blind since 1970Blind since 1979Blind since 1952Not blind

Semifinals

Blind (varies) since1973

Use of screen varies

Not blind: 1991-preseniBlind: 1984-1987Blind since 1986; varies

until 1993Use of screen variesBlind since at least

1972Use of screen variesNot blindBlind since 1979Blind since 1952Not hlind

Finals

Nol blind

Blind 1967-1969; sincewinter 1994

Not blind

1st pan blind since 1993;2nd part not bbnd

Not blindBlind since at least 1972

Not blindNot blindBlind since fall 1983Nol blindNot blind

Notes: The 11 orchestras (A dirough K) are ibose in the roster sample described in the text. A subset of eight form the auditionsample (also described in the text). All orchestras in tbe sample are major big-city U.S. symphony orchestras and include the"Big Five."Sources: Orchestra union contracls (from orchestra personnel managers and libraries), personal conversations with orchesUapersonnel managers, and our mail survey of current orchestra members who were hired during the probable period of screenadoption.

dures employed during Ihe audition that wonthem their current position.

An obvious question to ask is whether theadoption of the screen is endogenous. Of par-ticular concern is that more meritocratic orches-tras adopted blind auditions earlier, producingthe spurious result that the screen increased thelikelihood that women were hired."" We esti-mate a probit model of screen adoption by year,conditional on an orchestra's not previouslyhaving adopted the screen {an orchestra exitsthe exercise once it adopts the screen). Twotime-varying covariates are included to assesscommonly held notions about screen adoption:the proportion female (lagged) in the orchestra,and a measure of tenure (lagged) of then-currentorchestra members. Tenure is included becausepersonnel managers maintain the screen wasadvocated more by younger players.

As the proportion female in an orchestra in-creases, so does the likelihood of screen adop-tion in the preliminary round, as can be seen in

^ Note, however, it is unlikely that the orchestras tbatsought to bire more women chose to adopt the screen earliersinee the besl way to increase the number of women in theorchestra is to have not-blind auditions (so that one could besure to bire more women).

columns (1) and (2) in Table 2, although theeffects are very small and far from statisticallysignificant."*' We estimate a similar effect whenwe assess the role of female presence on theadoption of blind finals [see column (3)]. Theimpact of current tenure, measured by the pro-portion with less than six years with the orches-tra, is—contrary to general belief^negativeand the results do not change controlling forwhether the orchestra is one of the "Big Five.""^In all. it appears that orchestra sex compositionhad little influence on screen adoption, althoughthe stability of the personnel may have in-creased its likelihood.^^

~^ An increase in tbe proportion female from 0 to 0.35,the largest for any of the orcbestras (see Figure I), wouldenhance the likelihood of adopting tbe screen in the prelim-inary round by a mere 0.0021 percentage points,

^ Our measure of tenure begins at ihe first date forwhieh we have rosters, but not earlier than 1947. Tenurethen cumulates for each member until the individual exitsthe orchestra. Because tenure will increase for all orchestraswith time, we use the proportion of all members with fewerthan six years of tenure.

^ A change in conductor could also have led to a changein the audition policy, but we lind no supporting evidence.For example, current players contend that Charles Munchhad complete authority in hiring at the BSO before 1952.The BSO adopted the screen in 1952, but Munch was


TABLE 2—ESTIMATED PROBIT MODELSFOR THE USE OF A SCREEN

(Proportion female),_,

(Proportion of orchestrapersonnel with <6years tenure),. ,

"Big Five" orchestra

pseudo R^Number of observations

Preliminaries blind

(1)

2.744(3.265)10.006]-26.46(7.314)

1-0.058]

0.178294

(2)

3.120(3.271)[0.004]-28.13(8.459)

[-0.039]0.367

(0.452)[0.001]

0.193294

Finalsblind

(3)

0.490(i.l63)[0.011]-9.467(2.787)

[-0.207]

0.050434

Notes: Tbe dependent variable is 1 if the orchestra adopts ascreen, 0 otherwise. Huber standard errors (with orchestrarandom effects) are in parentheses. All specifications in-clude a constant. Changes in probabilities are in brackets."Proportion female" refers to the entire orchestra. "Tenure"refers lo years of employment in the current orchestra. "BigFive" includes Boston, Chicago. Cleveland, New York Phil-harmonic, and Philadelphia. The data begin in 1947 and anorchestra exits the exercise once it adopts the screen. Theunit of observation is an orchestra-year.Source: Eleven-orchestra rosier .sample. See text.

m . The Role of Blind Auditions on theAudition and Hiring Process

A. Data and Methods

Audition Records.—^We use the actual audi-tion records of eight major symphony orchestrasobtained from orchestra personnel managers andthe orchestra archives. The records are highly con-fidential and occasionally contain remarks (in-cluding those of the conductor) about musicianscurrently with the orchestra. To preserve the fullconfidentiality of the records, we have not re-vealed the names of the orchestras in our sample.

Although availability differs, taken togetherwe obtained information on auditions datingfrom the late l950's through 1995. Typically,the records are lists of the names of individuals

conductor from 1949 to 1962. Our inability to explain thetiming of screen adoption may result from our lack ofintimate knowledge of the musical world, although it is alsodifficult to explain blind refereeing policy among econom-ies journals (see the list in Blank, 1991).

who attended the auditions, with notation nearthe names of those advanced to the next round.For the preliminary round, this would indicateadvancement to either the semifinal or finalround. Another list would contain the names ofthe semifinalists or finalists with an indicationof who won the audition." " From these records,we recorded the instrument and position (e.g,,section, principal, substitute) for which the au-dition was held. We also know whether theindividual had an "automatic" placement in asemifinal or final round. Automatic placementoccurs when a musician is already known to beabove some quality cutoff and is invited tocompete in a semifinal or final round.''^ We alsorecorded whether the individual was advancedto the next round of the current audition.

We rely on the first name of the musicians todetennine sex. For most names establishing sexwas straightforward."*' Sexing the Japanese andKorean names was equally straightforward, atleast for our Japanese and Korean consultants.For more difficult cases, we checked the namesin three haby books (Connie Lockhard Ellefson,1990; Alfred J. Kolatch, 1990; Bruce Lansky,1995). If the name was listed as male- orfemale-only, we considered the sex known. Thegender-neutral names (e.g., Chris, Leslie, andPat) and some Chinese names (for which sex isindeterminate in the absence of Chinese char-acters) remained ambiguous. Using these pro-cedures, we were able to determine the sex of96 percent of our audition sample.^^ We laterassess the impact that sex misclassification mayhave on our results.

In constructing our analysis sample, we ex-clude incomplete auditions, those in which therewere no women (or only women) competing,rounds from which no one was advanced, andthe second final round, if one exists, for which

In rare cases, we have additional information on tbefinalists, such as resumes,

•™ The person will be known to be above a quality eutoffeither because the individual is a current member of acomparable orchestra or because the person was a semifi-nalist or finalist in a previous audition.

^' For 13 percent of the contestants, sex was confirmedby personnel managers, resumes, or audition summarysheets.

•'' Most of the remainder were sexed using census databy assigning to them the dominant sex of individuals withtheir first name.


TABLK 3—DESCRIPTIVE STATISTICS ABOLIT Ai DmoNS. BY YEAR AND ROUND OF AUDITION

YearNumber ofauditions

Proportionfemale

Number of Number of Proportionmusicians auditions female

Number of Number of Proportionmusicians auditions female

Completely blind auditions Not completely blind auditionsAll

Pre-1970

1970-1979

1980-1989

1990+

Round

Preliminaries.withoutsemifinals

Preliminaries,withsemifinals

Semifinals

Finals

254

10

69

102

73

170

137

114

167

0.367(0.013)0.187

(0.042)0.329

(0.026)0.394

(0.019)0.390

(0.027)

0.357(0.015)

0.3%(0.019)0.415

(0.019)0.430

(0.016)

43.4(3.13)

42.5(4.29)44.6(4.64)

34.3(1.S7)

45.5(2.54)12.3(0.649)4.93

(0.448)

60

33

27

Blindrounds

125

134

89

28

0.393(0.029)

0.375(0.034)0.415

(0.049)

0.367(0.017)

0.395(0.019)0.404

(0.022)0.472

(0.040)

38.1(1-74)16J( 2 ^31.4(2.10)39.6(2.73)50.6(4.52)

24.7(2.33)

49.3(17.0)10.4(1.21)7.12

(0.310)

194

10

69

69

46

Not-blindrounds

45

3

25

130

0.359(0.015)0.187

(0.042)0.329

(0.026)0.403

(0.022)0.375

(0.033)

0.327(0.029)

0.425(0.205)0.455

(0.043)0.422

(0.017)

Notes: The unit of ob.servation for the top portion is the audition, whereas it is the round for the bottom portion (e.g..proportion female in the top portion of the table is averaged across the auditions). Standaid eirors are in parentheses.Source: Eight-orchestra audition sample. See text.

the candidates played with the orchestra.^^ Inaddition, we generally consider each round ofthe audition separately. These sample restric-tions exclude 294 rounds (199 contained nowomen) and 1.539 individuals. Our final anal-ysis sample has 7,065 individuals and 588 au-dition rounds (from 309 separate auditions)resulting in 14,121 person-rounds and an aver-age of 2.0 rounds per musician."*•*

As can be seen In the bottom portion ofTable 3, 259. or 84 percent, of our 307 pre-liminary rounds were blind. 78 percent ofthe114 semifinals were blind, but just 17 percentof the 167 final rounds were hlind. Most ofour audition sample is for the period after1970. The blind preliminaries contained 40

• Although the results are unaffected, harp auditions areexcluded because it has typically been a female-dominatedinstrument.

^ See Table Al for descriptive statistics.

candidates on average, whereas those withoutthe screen had 26. Women were about 37percent of all preliminary candidates but 43percent of finalists, and the difference holdsfor both the blind and not-blind auditions.The percentage female among all candidatesincreased over time, from 33 percent in the1970 to 1979 period to 39 percent in thepost-1990 years (see upper portion).

Roster Data.—Our second source of infor-mation comes from the final results of the au-dition process, the orchestra personnel rosters.We collected these data from the personnel pageof concert programs, one each year for elevenmajor symphony orchestras. These records arein the public domain and thus we have used theorchestra names in the graphs containing thosedata alone. As opposed to the auditionees, wewere able to confirm the sex of the playerswith the orchestra personnel managers and


archivists. We considered a musician to be newto the orchestra in question if he or she had notpreviously been a regular member of that or-chestra (i.e., we did not count returning mem-bers as new). We excluded, when possible,temporary and substitute musicians, as well asharpists and pianists. Our final sample for 1970to 1996 has 1,128 new orchestra members (seeTable A2).

Econometric Framework.—We take advan-tage of the variation that exists across orcbes-tras, time, and audition round to identify theeffect of the screens on the likelihood that afemale is advanced from one round to the nextand ultimately hired. The probability that indi-vidual i is advanced (or hired) from an auditionat orchestra j , in year /, from round r, is afunction of the individual's sex (f) , whether ascreen is used (B), and other individual (X) andorchestral (Z) factors, that is:

(1)

The screen, it will be recalled from Table 1, var-ies across orchestra, time, and audition round.Orchestras adopted the screen in different years.Some used the screen in the preliminary roundonly, whereas others used the screen for theentire audition process. We use this variation toestimate a differences-in-differences strategy.In linear form, we write

(2) P,^,, ^ a + /3F,- + yBj,, + S(F,- X B,,,)

The coefficient on Bj,^, y, identified from themen who audition with a screen, controls forwhether all individuals are more or less likely tobe advanced from a blind than from a not-blindaudition. Thus the parameter of interest is thaton the interaction between F, and Bj^,, S, whichmeasures the change in the probability that awoman will be advanced if a screen is used,relative to her auditioning without a screen (af-ter accounting for other blind audition effects).We aiso test whether the use of the screeneliminates sex differences in the likelihood anindividual is advanced from one round to the

next. Because no restrictions exist on the num-ber of individuals advanced from the prelimi-nary and semifinal rounds, there is no zero-sumgame between men and women for theserounds.

B. The Effect of the Screen on the Likelihoodof Being Advanced

Tabulations and Regression Results With andWithout Individual Fixed Effects.—The rawdata in Tables 4 and 5 can reveal the impact onwomen of changes in the audition process andprovide an important introduction to the data.We demonstrate that in the absence of a variablefor orchestral "ability," women fare less well inblind auditions than otherwise. But if the or-chestral "ability" of the candidate is held fixed,the screen provides an unambiguous and sub-stantial benefit for women in almost all auditionrounds.

Table 4 gives the success rate by sex, roundof audition, and over time. We define "relativefemale success" as the proportion of womenadvanced (or hired) minus the proportion ofmen advanced (or hired). The relative successof female candidates appears worse for blindthan for not-blind auditions and this finding alsoholds for each round of the audition process.One interpretation of this result is that the adop-tion of the screen lowered the average quality offemale auditionees in the blind auditions. Onlyif we can hold quality constant can we identifytbe true impact of the screen.

Because we have tbe names of the candi-dates, we are able to link their success in oneaudition to that in another. (In our sample, 24percent of the individuals competed in morethan one audition.) In Table 5 we report audi-tion success statisfics, by round and overall, formusicians who appear more than once in oursample and for whom at least one audition (orround) was blind and one was not blind. Theevidence tells a very different story from that inTable 4, and taken together they suggest tbatblind auditions expanded the pool of femaleapplicants to include more who were less qual-ified. When we limit the sample to those whoauditioned both with and without a screen, thesuccess rate for women competing in blind au-ditions is almost always higher than in thosethat were not blind.


TABLE A—AVERAGE SUCCESS AT AUDITIONS BV SEX, YEAR, AND ROUND OF AUDITION

Year

All

Pre-1970

1970-1979

1980-1989

1990+

Round

Preliminaries, without semifinals

Preliminaries, with semifinals

Semifinals

Finals

All audition.s

-0.001(0.008)0.053

(0115)0.001

(0.021)-0.006(0.009)

-0.003(0.010)

All rounds

-O032(0.019)

-0.048(0.016)

-0.030(0.038)0.009

(0.036)

Relative female success

Completely blindauditions

-0.022(0.012)

-0.039(0.016)

-0.001(0.017)

Blind rounds

-0.048(0.021)

-0.052(0.016)

-0.059(O044)

-0.028(0.102)

Not completely blindauditions

0.006(0.010)0.053

(0.115)0.001

(0.021)0.010

(0.009)-0.003(0.013)

Noi-blind rounds

0.012(0.040)0.116

(0.228)0.071

(O080)0.016

(0.038)

Notes: For the top part of the table "success" is a "hire." whereas for the bottom portion "success" is advancement from onestage of an audition to the next. The unit of observation for the top ponion is the audition, whereas it is the round for thebottom ponion (e.g.. relative female success in the top ponion of the table is averaged across ihe auditions). Standard errorsare in parentheses. "Relative female success" is the proportion of women advanced (or hired) minus the proponion of menadvanced (or hired). By hired, we mean those who were advanced from the final round oul of the entire audition.Source: Eight-orchestra audition sample. See lext.

Take the preliminary round with no semifinals,for example, in Table 5. In the blind auditions 28.6percent of the women are advanced, as are 20.2percent of the men. But in the not-blind column,just 19.3 percent of the women are advanced,although 22.5 percent ofthe men are. Even thougha woman has a small advantage over a man whenthe screen is used (by 8.4 percentage points), hersuccess rate, relative to that of a man, is increasedby 11.6 percentage points above that in the not-blind regime. Note that because these are the samewomen. Table 5 suggests that a woman enhancesher own success rate by 9.3 percentage points byentering a blind preliminary round. Not only dothese differences suggest that women are helpedby the screen, the differences are large relative tothe average rate of success. ^

Women's success is also enhanced by the

'^ Because of the inlrequency of position availability, itis unlikely there was much gaming by women (e.g.. tryingout only lor blind auditions), although the change in the

screen in the finals and for the overall audition(termed "hired" in the table). For the finals, awoman's success rate is increased by 14.8 per-centage points moving to blind auditions(23.5 - 8.7) and is enhanced by a hefty 28.1percentage points above that of men. All suc-cess rates are very low for auditions as a whole,hut the female success rate is 1.6 times higher(increasing from 0.017 to 0.027) for blind thanfor not-blind auditions. The only anomalousresult in the table concems the semifinals, towhich we return later. We now show that theseresults stand up to the controls we can add.including the year of the audition and theinstrument.^''

general environment of auditions could have altered thepool of contestants.

'^ We do not discuss the regression analog to Table4. that is, the analysis without individual fixed effects,because we have firmly established thai individual fixedeffect. matter. Table A3 shows the results of regressions


TABLE 5—AVERAGE SUCX:ESS AT AUDITIONS BY SEX AND STAGE OF AUDITION FOR THE SUBSETOF MUSICIANS WHO AUDITIONED BOTH BLIND AND NOT BLIND

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Proportionadvanced

0.286(0.043)0.202

(0.026)

0200(0.092)0.083

(0.083)

0.385(0.061)0.368

(0.059)

0.235(0.106)0.000

(0.000)

0.027(0.008)0.026

(0.005)

Blind

Number ofperson-rounds

Preliminaries without

112

247

Proportionadvanced

semifinals

0193(0.041)0.225

(0.031)Preliminaries with semifinals

20

12

Semifinals

65

68

Finals

17

12

"Hired"

445

816

0133(0.091)0.000

(0.000)

0.568(0.075)0.295

(0.069)

O087(0.060)0.133

(0.091)

0.017(0.005)0.027

(0.005)

Not blind

Number ofperson-round.s

93

187

15

8

44

44

23

15

599

1102

Notes: The unit of observation is a person-round. Standard errors are in parentheses. For the round in question, only musicianswho auditioned more than once and who auditioned at least once behind a screen and at least once withoui a screen areincluded. "Hired" means those who were advanced from the final round out of the entire audition. Blind in the "hired"category means for all rounds. Not blind in the "hired" category means that at least one round was not blind. This differencein the definition of what consfitutes a "blind" round or audition is one reason why the number of observations in the first fourpanels is less (han the number of observations in the "hired" panel. The number of observations also differ because we excludeauditions or rounds in which no individual is advanced or in which there are only women or no women. Finally, unlike insubsequeni tables, we exclude a (ew candidates for whom we could not detennine or impute their sex. Note that the bindingconstraint for the preliminaries is the not-blind category, for which we have only one orchestra. The binding constraint in the"hired" category are the blind auditions, for which we have (at most) three orchestras. Musicians can appear more than oncein either the blind or not-blind categories.Source: Eight-orchestra audition sample. See text.

The results given in Table 6 are the regres-sion analogs to the raw tabulations in Table5.-* Because the effect of the blind procedure

comparable to those in Table 6 but without individual fixedeffects.

^ In the (total) subsample of individuals auditioningboth with and without a screen, all eight orchestras in ouraudition sample are represented, and seven of the orchestra.schanged audition policy during our sample time frame. Thesample sizes in Table 6 are considerably larger than those in

could differ by the various rounds in the au-dition process, we divide audition rounds intothe three main rounds (preliminary, semifinal,and final) and also separate the preliminariesinto those that were followed by a semifinal

Table 5. The reason is that the regressions in Table 6 Includeail individuals whether or not they auditioned more thanonce, whereas Table 5 includes only those who auditionedat least twice, bhnd and not blind.


TABLE 6~LiNEAR PROBABILITY EsirMATES OF THE LIKELIHOOD OF BEING ADVANCED: WITH INDIVIDUAL FIXED EFFECTS

Blind

Female x Blind

Number of auditions attended

Years since last audition

Automatic placement

"Big Five" orchestra

Total number of auditioners inround (-100)

Proportion female at the auditionround

Principal

Substitute

p-value of //(,: Blind + (FemaleX Blind) = 0

Year fixed effects?R-Number of observations

Preliminaries

Withoutsemifinals

(!)

-0.017(0.039)0.125

(0.068)

0.053

No0.7485,395

(2)

0.003(0.046)0.111

(0.067)-0.020(0.014)

-0.005(0.007)

-0.154(0.035)

-0.003(0.081)0.118

(0.139)-0.079(0.037)0.165

(0.081)0.063

Yes0.7755,395

With semifinals

(3)

0.109(0.172)0.013

(0.215)

0.342

No0.6876.239

(4)

0.224(0.242)

-0.025(0.251)0.010

(0.010)-0.006(0.005)

-0.059(0.024)0.014

(0.031)0.312

(0.134)-0.078(0.019)0.123

(0.093)0.285

Yes0.6976,239

Semifinals

(5)

0.026(0.089)

-0.179(0.126)

0.089

No0.7741.360

(6)

0.102(0.096)

-0.235(0.133)0.015

(0.030)-0.005(0.013)

-0.096(0.064)0.006

(0.081)-0.371(0.521)0.104

(0.218)-0.082(0.066)0.167

(0.183)0.170

Yes0.7941,360

Finals

(7)

-0.154(0.150)0.308

(0.196)

0.222

No0.8111,127

(8)

-0.060(0.149)0.331

(0.18!)0.126

(0.028)0.016

(0.015)-0.069(0.073)

-0.059(0.084)

-0.262(0.756)0.067

(0.159)-0.185(0.076)0.079

(0.217)0.042

Yes0.8781.127

Notes: The unit of observation is a person-round. The dependent variable is 1 if the individual Is advanced to the next roundand 0 if not. Standard errors are in parentheses. All specifications include individual fixed effects, an interaction for the sexbeing missing and a blind audition round, a dummy indicating if years since last audition is missing, and (in columns (3)-(8)]whether an automatic placement is missing.Source: Eight-orchestra audition sample. See text.

round and those that were not. In the even-numbered columns we include year and in-strument fixed effects, as well as individualand audition covariates. The individual corre-lates are whether the musician had an auto-matic placement in a semifinal or final round,years since the last audition in the sample,and the number of previous auditions inwhich we observe the musician to have com-peted. We also control for the total number ofmusicians in the round, the proportion femaleamong contestants, and whether the auditionis for a principal or substitute position.

Because 42 percent of the individuals in oursample competed in more than one round in ourdata set (24 percent of the musicians competedin more than one audition) and 6 percent com-peted both with and without a screen for a

particular type of round (e.g., semifinal), we areable to use an individual fixed-effects strategyto control for contestant "ability" that does notchange with time. In all columns of Table 6 weinclude individual fixed effects, in which casethe identification is from individuals who audi-tioned both with and without a screen. ** The

'^ There are 639 person rounds comprised of individualswho auditioned at a preliminary round that was not followedby a semifinal round [columns (I) and (2) of Table 6], hothwith and without a screen; on average the.se individualscompeted in 2.7 such preliminary rounds. There are 55person-rounds comprised of individuals who auditioned at apreliminary round that was followed by a semitinal round[columns (3) and (4)], both with and without a screen; onaverage these individuals competed in 2.4 such preliminaryrounds. There are 223 person-rounds comprised of individ-uals who auditioned at a semifinal [columns (5) and (6)],


effect ofthe screen here, therefore, is identifiedfrom differing audition procedures both withinand across orchestras. " Note that we include adummy variable for whether the orchestra isamong the "Big Five," to control for the qualityof the orchestra.

The coefficient of interest is the interactionbetween "Female" and "Blind." A positivecoefficient would show that screened audi-tions enhance a woman's likelihood of ad-vancement. Because screened auditions aremore likely to take place in later years thanauditions without screens, the interaction be-tween "Female" and "Blind" might simplyreflect the fact that female musicians get bet-ter over time. Note, however, that for thiseffect to bias the coefficient, female musi-cians would have to improve faster with timethan male musicians. Nevertheless, we havealso included (in the individual covariates)the number of previous auditions the musi-cian attended in our sample, the number ofyears since the last audition in the sample,and whether the candidate was an automaticplacement. The coefficient on "Blind" revealswhether blind auditions change the likelihoodthat all contestants are advanced.

As in the raw tabulations of Table 5, wefind that the screen has a positive effect on thelikelihood that a woman is advanced from thepreliminary round (when there is no semifi-

both with and without a screen; on average these individualsparticipated in 2.8 semifinal rounds. Finally, there are 67person-rounds comprised of individuals who auditioned at afinal round [columns (7) and (8)]. both with and without ascreen; on average these individuals participated in 2.4 finalrounds. It should he noted that the number of person-roundsoff of which we are identified in Table 6 can aiso be foundin Table 5. with one exception. There are 223 person-roundscomprised of individuals who auditioned at the semifinal,both with and without a screen, in Table 6 and only 221 inTable 5 because there are two individuals we could not sex.We include these individuals in the regressions in Table6 and add a dummy variable indicating that the sex ismissing.

^ An analysis of variance (ANOVA) across the entiresample, that is pooling ail rounds, indicates that 19 percentof the variation in the use of the screen is across orchestras.Looking by audition round reveals that 73 percent of thevariation in preliminaries, 53 percent of the variation in.semifinals, and 71 percent of the variation in finals is acrossorchestras. By contrast, in Table 7 (which includes a subsetof the orchestras, see table notes), just 1 percent of thevariation in the use of the screen is across orchestra.s.

nal) and from the finals.*" The effects, more-over, are statistically significant in both cases.The effect in the semifinal round, however,remains strongly negative."' In addition, themagnitudes of the effects in Table 6 are sim-ilar to those implied by the raw tabulations(Table 5). For preliminaries that are not pre-ceded by a semifinal, the blind audition in-creases the likelihood that a woman will beselected by about 11 percentage points. Forfemale musicians who made it to the finalround, the individual fixed-effects regressionresult indicates that the screen increases thelikelihood of their winning by about 33 per-centage points.42

Assessing Potential Biases.—A concem withthe preceding fixed-effects analysis is that, asnoted earlier, female musicians who are im-proving over time are those who switch fromnot-blind to blind auditions and that the growthrate of their "ability" is faster than that of men.We attempted to address this potential bias byincluding several individual time-varying co-

""' An exception occurs when preliminaries are followedby semifinals. There are, however, only three preliminaryrounds that are not blind when there is also a semifinalround (see Table 3). Thus the coefficients in columns (3)and (4) of Table 6 are identified using very few separateaudition rounds. We also note that when we estimate fixed-effects logit models we obtain results similar to those incolumns (I) and (2) in Table 6 (and in Table 7). Because ofthe small samples with the identifying requirements of thefixed-effects logit. standard errors for the estimates in col-umns (3)-(8) of Table 6 could not be computed. Further, forthe results without individual fixed effects. logits and linearprobability models give qualitatively similar results.

"" This result on the semifinal.s is robust across time,instrument, position, and orchestra. One interpretation isthat it represents a form of affirmative action by the auditioncommittees. Committee.s may hesitate to advance womenfrom the preliminary rotmd if they are not confident of thecandidate's ability. On the other hand, semifinals are typi-cally held the same day as are preliminaries and give theaudition committee a second chance to hear a candidatebefore the finals. Thus, audition committees may activelyadvance women to the final round only when they arereasonably confident that the female candidate is abovesome threshold level of quality. If juries actively seek toincrease the presence of women in the final round, they cando so only when there is no screen.

"- As noted earlier, an obvious explanafion for the im-portance of the individual fixed effects in the estimation isthat the screen altered the pool of female applicants; how-ever, we have been unable to show this empirically.


variates (in the even-numbered columns of Ta-ble 6). The inclusion of these individualcovariates had little effect on the estimated ef-fect of the screen.

A related concem is that those individualswho get hired at their first audition, and there-fore do not contribute to the identification oftheeffect in the presence of individual fixed effects,are more able musicians than those who audi-tion multiple times. (Alternatively, some indi-viduals who audition and are not hired may getdiscouraged and not audition again and aretherefore worse than those who audition multi-ple times.) Although this is a potential source ofbias, it is important to remember that only avery small number of musicians win an auditionin any given year, since there are just a handfulof auditions (for a given instrument) among themajor orchestras. Furthermore, many of thecontestants in our sample did audition at leasttwice.

In addition, there are three pieces of em-pirical evidence that suggest this potentialsource of bias is not a major problem in ourdata. First, we control for the number of pre-vious auditions in the even columns of Table6, and this control does not change the resultssignificantly. Second, there is no significantdifference in the proportion female amongthose who auditioned both with and without ascreen and those who auditioned only once(or who auditioned under only one policyregime). Finally, the coefficient estimatesgenerated when the sample is restricted tothose who auditioned at least three times arenot perceptibly different from those generatedfrom the full sample or from the sample ofindividuals who auditioned both with andwithout a screen. (These results are presentedin Table A4.)

A third potential bias is that, because theeffect ofthe screen is partially identified fromdiffering audition procedures across orches-tras, the results in Table 6 may indicate thatorchestras that use screens are less discrimi-natory against women than those that do not.Specifically, because we include individualfixed effects, a bias would arise if womenwho are improving faster than average aremore likely to audition for orchestras that usescreens and are more likely to be advancedbecause these orchestras are intrinsically less

discriminatory. Our sample contains only oneorchestra per audition round that changedpolicy. As a result, we cannot separate theestimation by audition round and include or-chestra fixed effects. We can. however, poo!the audition rounds for the three orchestrasthat changed audition policy during our sam-ple frame and include both individual andorchestra fixed effects.•*' These results arepresented in Table 7.

In column (1) of Table 7 we include individualfixed effects, in which case the identification isfrom individuals who auditioned both with andwithout a screen. We add orchestra fixed effects incolumn (2) such that the identification now is fromindividuals who auditioned for a particular orches-tra both before and after the orchestra began usinga screen."* Finally, in column (3) we excludeindividual but keep orchestra fixed effects to illus-trate the importance of individual fixed effects.Again, the coefficient on "Blind" shows whetherall musicians are more likely to be advanced whenthe audition is blind. The interaction betweenwhether the individual is female and whether theaudition is blind indicates whether women receivean extra boost relative to men when the screen isused.

The coefficient of interest is positive incolumns (1) and (2) but negative in column(3), similar to the difference between thetabulations in Tables 4 and 5. In addition,the estimated effect of the blind auditions onthe success of women is similar to that inTable 6. The point is that individual fixed-effects estimation matters; orchestra fixed ef-fects, however, do not matter. In all cases,blind auditions increase the probability of ad-vancement for both men and women. More

•' We do not include the type of audition round since wehave only one orche.stra that changed procedures for thepreliminaries, one that changed for the semifinals, and onethai changed for the finals (and for which there were musi-cians who auditioned for that orchestra and audition roundwith and without a screen). We have also estimated theseregressions separately for each of these three orchestras.Although ihe point estimates are not statistically significant.the magnitudes are quite similar to those presented in Table6 for the corresponding round of the audition.

"" In this subsampie. there are 1,776 person-rounds com-prised of individuals who auditioned for a particular orches-tra, both behind and without a screen; on average these 552individuals competed in 3.2 audition rounds.


TABLE 7—LINEAR PROBABILITY ESTIMATES OF THE LIKELIHOOD OF BEING ADVANCED: WITH

INDIVIDUAL AND ORCHESTRA FIXED EFFECTS

Blind

Female x Blind

Female

p-value of H^:Blind + (Female X Blind)

Individual fixed effects?Orchestra fixed effects?Year fixed effects?Other covariales?R-Number of observations

= 0

Includefixed

(1)

0.404(0.027)0.044

(0.039)

0.000

YesNoYesYes

0.6158.159

individualeffects

(2)

0.399(0.027)0.041

(0.039)

0.000

YesYesYesYes

0.6158,159

Exclude individualfixed effects

(3)

0.103(0.018)

-0.069(0.022)

-0.005(0.019)0.090

NoYesYesYes0.0488.159

Note.s: The unit of observation is a person-round. The dependent variable is 1 if the person isadvanced to the next round and 0 if not. Standard errors are in parentheses. All specificationsinclude an interaction for the sex being missing and a blind audition: "Other covariales" includeautomatic placement, years since last audition, number of auditions attended, size of the auditionround, proportion female in audition round, whether a principal or substitute position, and adummy indicating whether years since last audition is missing. These regressions include only theorchestras thai changed their audition policy during our sample years and for which we observeindividuals auditioning for the audition round both before and after the policy change. Theseregressions include 4,836 separate persons and are identified off of 1.776 person-rounds comprisedof individuals who auditioned both before and after the policy change for a particular orchestra.Source: Eight-orchestra audition sample (three orchestras of which are used; see Noles). See text.

important, even though the effect is not sta-tistically significant, the blind procedure has apositive effect on women's advancement.'^^

Finally, sex misclassification may also biasour estimates because, if the misclassificationerrors are uncorrelated with the equation error,the estimated effect of the screen will be atten-uated (see. e.g.. Richard Freeman. 1984). Toaddress this potential problem, we use a less-subjective assessment ofthe probability that theindividual is male or female. A U.S. Bureau ofthe Census tabulation, based on the postenu-

*^ Although the results from these three orchestras maynot generalize lo the other five, it should be noted that thecoefficient estimate in column (3) of Table 7 is similar tothat derived from a similar regression on the entire sample.This result is nol surprising because the primary reason weare able to include both individual and orchestra fixedeffects for Ihese three orchestras is because they have un-usually good record keeping, which allows us to observe theresults of many auditions rather than another reason thatmight be correlated with how meritocratic the orchestra is.

meration survey ofthe 1990 census, gives us theproportion female and male of the top 90 per-cent of all names.*^

In Table 8 we estimate the same specifica-tions given by columns (2), (4), (6), and (8) ofTable 6 and column (2) of Table 7 using thecensus data in two ways. First, we simply re-place our female covariate with the census prob-ability."^^ Note that we also use a censusestimate ofthe percentage ofthe audition roundthat is female (slightly changing our samplesize), and a census estimate ofthe percentage ofour sample for which the sex is indeterminate.In addition, our interaction term is constructedusing the census probabilities. Second, we use

'^ These data can be dowrdoaded from http://www.census.gov/ftp/pub/genealogy/names. A possible problem with thedata is that names are generational; a male name in onegeneration may become female in another.

•" We do not impute census probabilities for the individ-uals whose sex we know with certainty (see footnote 31).

VOL 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIALITY 733

TABLE 8—LINEAR PROBABILITY ESTIMATES OF THE LIKELIHOOD OF BEING ADVANCED: ADDRESSING SEX MISCLAS.SIFICATION

Blind

Female X Blind

Other covariates?Individual fixed effects?Year fixed effects?R^Number of observations

Blind

Female x Blind

Other covariatesIndividual fixed effects?Year fixed effects?R'Number of observations

Part A; Preliminary rounds

Without semifinals

OLS

-0.012(0.043)0.139

(0.066)YesYesYes

0.7715,696

Part B: Semifinal and final round!

Semifinals

OLS

0.100(0.083)

-0.242(0.120)

YesYesYes

0.7761,600

IV

-0.197(0.700)

-0.193(0.429)

YesYesYe.s

1.360

IV

0.057(0.045)0.137

(0.068)YesYesYes

5.395

Preliminaries

OLS

-0.174(0.093)0.272

(0.188)YesYesYes

6.546

i. and with orchestra fixed effects

OLS

-0.028(0.125)0.160

(0.171)YesYesYes

0.8481,509

Finals

IV

-0.025(0.141)0.324

(0.181)YesYesYes

1.127

With semifinals

IV

0.290(0.241)

-0.035(0.251)

YesYesYes

6.239

With orchestras fixedeffects

OLS

0.010(0.028)0.069

(0.035)YesYesYes

0.6548,882

IV

0.061(0.033)0.052

(0.036)YesYesYes

8.159

Notes: The unit of observation is a person-round. The dependent variable is 1 if tbe individual is advanced to the next roundand 0 if not. Standard errors are in parentheses. The instruments are tbe census probability tbat tbe individual is female, adummy for wbether tbe person has been sexed with certainty, and proportion female calculated using the census data and aninteraction between whether the census data are missing and a screen has been used. The "'OLS" columns use these asregressors. All specifications include an inleraclion for tbe sex being missing and a blind audition; "Otber covariates" includeautomatic placement, years since last audition, number of auditions attended, whether a "Big Five" orchestra, size of tbeaudition round, proportion female at the audition round, whether a principal or substitute position, and a dummy indicatingwbether years since last audition and automatic auditioti are missing. These are the same specifications a.s in columns (2). (4).(6), and (8) of Table 6 and column (2) of Table 7. The sample sizes change because in the even-numbered columns we simplyreplace our female covariate witb the census probability and also use a census estimate of tbe percentage of Ibe audition roundthat is female, which changes the sample size slightly.Source: Eigbt-orchestra audition sample. See text.

the census probability as an instrument for ourestimate (and for the percentage of the auditionthat is female, the percentage missing sex, andthe interaction between female and whether theaudition is bhnd).

The results are quite robust across thesedifferent methods for addressing potentialmeasurement error. More important, the co-efficients and their standard errors are gener-ally similar in magnitude to those in Tables 6and 7. With the exception of the semifinalround, the screen appears to have increased

the likelihood that a woman would be ad-vanced.''**

** Another potential bias is from tbe short panel, whichmay affect the consistency ofthe estimates (Hsiao. 1986).We address tbe extent of tbis sbort panel problem in twoways. We first restrict our sample to tbose whom we ob-serve auditioning at least ibree times (for the same round).Second, we restrict tbe estimation to those who auditionedat least once in a blind round and al least once in a not-blindround (tbose off of wbom we are identified). The results donoi cbange markedly from those in Table 6, sbowing tbatthe short panel may not be a problem. See Table A4.


TABLE 9—LINEAR PROBABILITY ESTIMATES OF THE EFFECT OF BLIND AUDITIONS

ON THE L T K E L I H O O D OF BEING HiRED WITH INDIVIDUAL FiXED EFFECTS

Completely hiind auditioti

Completely blind audition X female

Year effects?Other covariates?R-Number of observations

Without

(1)

-0.024(0.028)0.051

(0.046)NoNo

0.8554.108

semifinals

(2)

0.047(0.041)0.036

(0.048)YesYes

0.8684,108

With

(3)

0.001(0.009)0.001

(0.016)NoNo

0.6925.883

semifinals

(4)

0.006(0.011)

-0.004(0.016)

YesYes

0.7075,883

Al!

(5)

0.001(0.008)0.011

(0.013)NoNo

0.6789,991

(6)

0.005(0.009)0.006

(0.013)YesYes

0.6919,991

Noles: The unit of observation is a person-round. The dependent variable is 1 if the individual is advanced (or hired) fromthe final round and 0 if not. Standard errors are in parentheses. All specitications include individual fixed effects, whether thesex is missing, and an interaction for sex being missing and a completely blind audition. "Other covariates" are the size ofthe audition, the proportion female at the audition, the number of individuals advanced (hired), whether a "Big Five"orchestra, the number of previous auditions, and whether the individual had an automatic semifinal or final.Source: Eight-orchestra audition sample. See text.

C. The Effect of the Screenon the Hiring of Women

Using the Audition Sample.—Our analysis,thus far, has concerned the rounds of the audi-tion process and the degree to which the screenenhances the Hkelihood of a woman's advanc-ing from one round to the next. We tum now tothe effect of the screen on the actual hire andestimate the likelihood an individual is hired outofthe initial audition pool.'*^ Whereas the use ofthe screen for each audition round was, more orless, an unambiguous concept, that for the entireprocess is not and we must define a hlind audi-tion. The definition we have chosen is that ablind audition contains all rounds that use thescreen. In using this definition, we compareauditions that are completely blind with thosethat do not use the screen at all or use it for theearly rounds only. We divide the sample intoauditions that have a semifinal round and thosethat do not, because the previous analysis sug-gested they might differ.

The impact of completely blind auditions onthe likelihood of a woman's being hired is givenin Table 9, for which all results include individ-

•" There are four auditions in which the committee couldnot choose between two players and therefore asked each toplay with the orchestra. We consider btJth to be winners.The results are not sensitive to this classification. For thisanalysis we exclude audilions with no women, all women,or no winner: these exclusions do not change the results.

ual fixed effects.-^" The impact of the screen ispositive and large in magnitude, but only whenthere is no semifinal round. Women are about 5percentage points more likely to be hired thanare men in a completely blind audition, al-though the effect is not statistically significant.The effect is nil, however, when there is asemifinal round, perhaps as a result of the un-usual effects of the semifinal round. The impactfor all rounds [columns (5) and (6)] is about 1percentage point, although the standard errorsare large and thus the effect is not statisticallysignificant. Given that the probability of win-ning an audition is less than 3 percent, wewould need more data than we currently have toestimate a statistically significant effect, andeven a 1-percentage-point increase is large, aswe later demonstrate.

" In Table 9 we are identified off of individuals whocompeted in auditions that were completely blind and thosethat were not completely blind (that is, any one round couldnot be blind). The unil of observation is the person-roundand there are 92 fulfilling this criterion for auditions withouta semifinal [columns (I) and (2)i; on average these personscompeted in 3.6 auditions in this sample. There are 625person-rounds fulfilling this criterion that included a semi-final [columns (3) and (4)] and on average these personscompeted in 3.5 auditions in this sample. Finally, there are911 person-rounds fulfilling this criterion across all audition[columns (5) and (6)] and on average these persons com-peted in 3.5 auditions in this sample. The sample off ofwhich we are identified is larger for ail auditions than for thesum of ihe other two because some individuals auditionedboth with and without a semifinal round.


TABLE 10—PROBIT ESTIMATES OF THE EFFECT OF BLIND AUDITIONS ON THE SEX OF NEW

MEMBERS: 1970 TO 1996

Any blind auditions

Only hlind preliminaries and/orsemifinals

Completely blind auditions

Section:Woodwinds

Brass

Percussion

/7-value of test: only blind preliminariesand/or semifinals = completely blind

pseudo R'Number of observations

Any blindauditions

(1)

0.238(0.183)[0.075]

-0.187(0.114)

[-0.058]-1,239(0.157)

[-0.284]-1.162(0.305)

[-0.235]

0.1061,128

Only blind preliminariesand/or semifinals vs.

completely blindauditions

(2)

0.232(0.184)[0.074]0.361

(0.438)[0.127]

-0.188(0.114)

[-0.058]-1.237(0.157)

[-0.284]-1.164(0.305)

[-0.235]0.756

0.1061,128

Notes: The dependent variable is t if the individual is female and 0 if male. Standard errorsare in parentheses. All specifications include orchestra fixed effects and orchestra-specifictime trends. Changes in probabilities are in brackets; see lexi for an explanation of how theyare calculaied. New members are those who enter the orchestra for the first time. Returningmembers are not considered new. The omitted section is strings.Source: El even-orchestra roster sample. See text.

The Roster Data.—The roster data af-ford us another way to evaluate the effect of thescreen on the sex composition of orchestras.Using the rosters we know the sex of new hireseach year for 11 orchestras, and we also haveinformation {see Table I) on the year the screenwas adopted by each orchestra. We treat theorchestra position as the unit of observation andask whether the screen affects the sex of theindividual who fills the position. We model thelikelihood that a female is hired in a particularyear as a function of whether the orchestra'saudition procedure involved a screen, again re-lying on the variation over time within a partic-ular orchestra. Thus, in all specifications, weinclude orchestra fixed effects and an orchestra-specific time trend.

The roster data extend further back in time

than do the audition data and could conceivablybegin with the orchestra's founding, althoughthere is no obvious reason to include manyyears when none used the screen. We report, inTable 10, the effects ofthe screen on the hiringof women from 1970 to 1996 using a probitmodel. The screen is first defined to include anyblind auditions [column (1)]. In column (2) weestimate separate effects for orchestras usingblind preliminary (and semifinal) rounds but notblind finals and those with completely blindauditions.

To interpret the probit coefficient, we firstpredict a base probability, under the assumptionthat each orchestra does not use a screen. Wethen predict a new probability assuming theorchestra uses a screen. The mean difference inthe probabilities is given in brackets.

THE AMERICAN ECONOMIC REVIEW SEPTEMBER 2000

The coefficient on blind in column (I) ispositive, although not significant at any usuallevel of confidence. The estimates in column (2)are positive and equally large in magnitude tothose in column (1). Further, these estimatesshow that the existence of any blind roundmakes a difference and that a completely blindprocess has a somewhat larger effect (albeitwith a large standard error)," ' According to thepoint estimates in column (1) of Table 10, blindauditions increase the likelihood a female willbe hired by 7.5 percentage points. The magni-tude of the effect must be judged relative to theoverall average and, for the period under con-sideration, it was about 30 percent. ' Thus blindauditions increased the likelihood a femalewould be hired by 25 percent.

Making Further Sense of the Results on Hir-ing.—The audition sample results suggest thatblind auditions increase the probability of even-tual success for a female candidate by 5 per-centage points, but otily if there is no semifinalround. The average effect for both types ofauditions is closer to 1 percentage point (with alarge standard error). The following example,using assumed values based on the actual data,demonstrates that an increase of about 2 per-centage points in the probability of a woman'ssuccess out of an audition can explain the entirechange in female hires, allowing the share ofcandidates who are female to increase from 0.2to 0.3. Thus an increase of I percentage point—our point estimate—can account for a substan-tial share.

Consider two regimes: one without the screen(not blind) and another with the screen (blind).In the not-blind regime, assume that 20 percentofthe candidates are female and that in the blindregime 30 percent are female.' ^ We know that

^' We have also attempted to interact the effect of Windauditions with section dumtnies. We find thai Ihe maineffect of blind auditions is almost identical to Ihai for thestring section, which is not surptising given thai the stringscomprise 65 percent of the observaiions. In addition, fewerthan 4 percent ofthe musicians hired into the percussion andbrass sections are female.

" See Table A2.•''•' The fraction female in the not-blind regime (taking it

lobe the period before 1970) is 0.187 in our data (see Table3). In the blind regime it was beiween 0.35 and 0.4. Wehave chosen the more conservative 0.3 in the example

in the era (say, before 1970) when few orches-tras used the screen for the preliminary round(see Table 1), 10 percent (that is, 0.0996) ofnew hires were women. Also assume that 30candidates enter each audition, independent ofaudition regime, and that one musician is hiredout of each audition. Using these assumptions,taken from the actual data, the success rate forthe typical female audition candidate in the not-blind regime will be 0.0166 and that for thetypical male will be 0.0375. If in the blindregime, however, the percentage of new hireswho are female increases to 35 percent (itsapproximate figure for the past 10 years), thesuccess rate for a female audition candidatemust have increased to 0.0389 (and that for amale must have decreased to 0.0310). That is.for consistency with the data on percent female,the success rate for female candidates wouldhave had to increase by about 2.2 percentagepoints, moving from the not-blind to the blindregime. Our point estimate is that about half ofthat increase—1 percentage point—was the re-sult of the effect of the screened audition pro-cess.

Using the example we just offered, the in-crease in the probability of a woman's beinghired out of an audition accounts for 66 percentof the total increase in the fraction femaleamong new hires. Half of the 66 percent comesfrom the switch to blind auditions.- "* The otherhalf could have resulted, for example, from a

because we want to use a number that is independent of theswitch to using the screen. That is, we would like to use afraction female that is solely Ihe result of increases infemale participation in general but independent of changesin audition procedures,

''•' The proportion female among new hires is (/i • A • a).where n = the number of audition candidates (in thisexample n = 30); A = the success rate of the averagefemale candidate, which may be enhanced by the screen (inthis example A increases from 0.0166 to 0.0389 or by 2.2percentage points, about half of which is due to the screen,based on our estimates); and a = the fraction female amongcandidates (a.ssumed here to increase from 20 to 30 percentindependent of A). The percentage of the total change ac-counted for by ihe change in A is given by (n • a •AA)/A(H • A • a) or on average by [(30 • 0.25 • 0.022)/(0.35 - 0.0996) = 66 percent, (The 0.25 figure is theaverage of that in the treatment period and that previously,)Since half is accounted for by the screen, aboul 33 percentof the increase in the proportion female among new hirescomes from the blind audition process.

VOL. 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIALTTY 737

greater acceptance of female musicians by mu-sic directors. The remainder (34 percent) of theincrease in the fraction female among new hiresis accounted for by the increased percentagefemale among audition candidates. That portioncomes primarily from the increase in the frac-tion female among music school graduates.

The point estimates from the roster data alsosuggest that a substantial portion ofthe increasein female hires across the two regimes, not-blind and blind, can be explained by the changein audition procedures. In the not-blind regimeabout 10 percent of all hires are female but inthe blind regime about 35 percent are, a differ-ence of 25 percentage points. The estimates incolumn (I) of Table 10 show that the switch tothe blind regime increases the likelihood awoman will be hired by 7.5 percentagepoints—30 percent of the total change—al-though we emphasize that the coefficient is im-precisely estimated.

One may wonder why there was disparatetreatment of female musicians before the screenwas used. A great orchestra is not simply acollection of the finest musicians. It is, rather, agroup of great musicians who play magtiifi-cently as an ensemble. Substantial amounts ofspecific human capital are acquired on the joband tenure differences by sex, therefore, couldinfluence hiring decisions.^'' Leaves of absenceare ordinarily allowed for medical (includingmaternity) and professional reasons. We find,using the roster sample from I960 to 1996, thatthe average female musician took 0.067 leavesper year, whereas the average male musiciantook 0.061, a difference that is not statisticallysignificant, and that their length of leave wastrivially different. Tenure differences were alsosmall and some specifications show that womenaccumulated more years with an orchestra,given their starting year and orchestra.^^ Tum-

^' Musicians of the Vienna Philharmonic made this ar-gument in a radio broadcast by the West German StateRadio in February 1996 [translation provided by WilliamOsborneJ. See also New York Times (1996) in which aplayer for the Vienna Philharmonic argued that femalemusicians would cost the orchestra considerably more be-cause substitutes would have to be hired if they becamepregnant.

*• The general sf)ecification is number of actual years withan orcheslra as a function of the starting year, section dum-mies, and a female dummy, for the period since 1959. The

over and leaves of absence do not appear todiffer by sex and thus should not have rationallyinfluenced hiring decisions.

IV. Conclusion

The audition procedures ofthe great U.S. sym-phony orchestras began to change sometime in the197O's. The changes included increasing the num-ber of candidates at auditions—a democratizationof the process—and using a physical screen dur-ing the audition to conceal the candidate's identityand ensure impartiaUty. We analyze what differ-ence blind auditions have meant for femalemusicians.

We have collected, from orchestral manage-ment files and archives, a sample of auditions foreight major orchestras. These records contain thenames of all candidates and identify those ad-vanced to the next round, inciuding the ultimatewinner of the competition. The data provide aunique means of testing whether discriminationexisted in the various rounds of a hiring pnxessand even allow the linkage of individuals acrossauditions. A strong presumption exists that dis-crimination has limited the employment of femalemusicians, especially by the great symphony or-chestras. Not only were their numbers extremelylow until the l970's, but many music directors,ultimately in charge of hiring new musicians, pub-licly disclosed their belief that female players hadlower musical talent.

The question is whether hard evidence cansupport an impact of discrimination on hiring.Our analysis of the audition and roster dataindicates that it can, although we mention var-ious caveats before we summarize the reasons.Even though our sample size is large, we iden-tify the coefficients of interest from a muchsmaller sample. Some of our coefficients ofinterest, therefore, do not pass standard tests ofstatistical significance and there is, in addition,one persistent result that goes in the oppositedirection. The weight ofthe evidence, however,is what we find most persuasive and what we

coefficient on the female dummy is -0.299 with a largestandard error (the mean of tenure is 11.7 years). With theaddition of orchestra fixed effects, the coefficient on the femaledummy is -fO,062. again with a large standard error. Thedifference in tenure by sex, therefore, is extremely small.


have emphasized. The poitit estimates, more-over, are almost all economically significant.

Using the audition data, we find that thescreen increases—by 50 percent—the proba-bility that a woman will be advanced fromcertain preliminary rounds and increases byseveralfold the likelihood that a woman willbe selected in the final round. By the use ofthe roster data, the switch to blind auditionscan explain 30 percent of the increase in theproportion female among new hires and pos-sibly 25 percent of the increase in the per-centage female in the orchestras from 1970 to1996." ^ As in research in economics and otherfields on double-blind refereeing (see, e.g..

'^The point estimate for the increased likelihood awoman would be a new hire, as a result of the adoption ofblind auditions, is 7,5 percentage points using the roster data(see Table 10). Because the percentage female among newhires increased from 10 to 35 percent from before 1970 tothe 199O's, our estimate implies that 30 percent of the 25percentage-point increase can be explained by the adoption

Blank, 1991), the impact of a blind procedureis toward impartiality and the costs to thejournal (here to the orchestra) are relativelysmall. We conclude that the adoption of thescreen and blind auditions served to help fe-male musicians in their quest for orchestralpositions.

of the screen. How this increase affected the percentagefemale in the orchestra depends on the sex composition ofthe orchestra, retirement (or lumover), and the time frame.We assume a 25-year time frame (from 1970 to 1995) andtwo retirements (thus two hires) per year. An increase in thepercentage female among new hires from 10 percent (itslevel pre-t970) lo 17.5 percent (10 + 1.5%) implies that in25 years, 13.75 women (out of 100) will be in the orchestra,or an increase of 3.75. The actual increase was 15 women,meaning 25 percent of the increase can be explained by theadoption ofthe screen. We assume in this example that theage distribution of the 100 players in 1970 is uniformbetween ages 25 and 74, that all hires occur at age 25. andthat men and women are drawn from the same age di.stri-bution.

APPENDIX

TABLE AI—SAMPLE DESCRIPTIVE STATISTICS, AUDITION DATA

AdvancedBlindFemaleFemale X BlindMissing femaleMissing female X BlindYears since lasl auditionYears since last audition.

missingAutomatic placementNumber of auditions

attended"Big Five" orchestraTotal number of

auditionersProponion female at roundPrincipalSubstituteNumber of observations

(person-rounds)

Without

Mean

0.1840.7930,3760,3050,0020,0022,4800,663

—1.611

0.60744.348

0.3750.1920.025

Preliminaries

semifinals

Standarddeviation

0.3870.4050,4850,4610,0470.0431.6610,473

—1.137

0.48822.202

0,2060.3940.157

5,395

With semifinals

Mean

0.1850.9760.3740,3620.0020.0022.6210.505

—2.147

0.32364,279

0.3730.3680,005

Standarddeviation

0.3880.1320.4840.4810.0470.0472.2090.500

—1.717

0,46735.914

0.2390,4820,071

6.239

Semifinals

Mean

0,3490.8080,4100.3250.0040.0042,4320.386

0.2672.490

0.21315.054

0.4070.3530.010

1,

Standarddeviation

0.4770.3940.4920,4690.0660,0612.3930,487

0.4431.886

0.4097.187

0.2110.4780.101

360

Mean

0.2000.1220.4110.056

00

2.2720.505

0.1372,051

0.3918,622

0.4110.2780.021

1

Finals

Standarddeviation

0.4000.3280.4920.230

00

1.8950.500

0,3451,513

0,4884.445

0,2130.4480.141

,127

Source: Eighl-orchestra audition sample. See text.

VOL. 90 NO. 4 GOLDIN AND ROUSE: ORCHESTRATING IMPARTIALITY 739

TABLE A2—SAMPLE DESCRIPTIVE STATISTICS, ROSTER DATA: 1970 TO 1996

Proponion female among new hires(Proportion female), _,Only blind preliminary auditionsAll auditions blindSection:

StringsWoodwindsBrabsPercussion

Number of observations

Mean

0.2930.1790.5720.104

0.6420.1580.1650.035

Standard deviation

0.4550.0810.4950.305

0.4800.3650.3710.185

1,128

Note: Means are musician weighted, nol audition weighted.Source: Eleven-orchestra roster sample. Sec text.

TABLE A3—LINEAR PROBABILITY ESTIMATES OF THE LIKELIHOOD OF BEING ADVANCED: BY ROUND

Female

Female X Blind

Blind audition

/)-value of //„:Female + (Female X

Blind) = 0Other covariates?Instrument fixed

effects?Year fixed effects?Orchestra fixed effects?R'Number of observations

(person-rounds)

Preliminaries

Withoutsemifinals

(1)

0.007(0.025)

-0.062(0.028)0.015

(0.022)0.000

YesYes

YesNo

0.0625,395

(2)

0.011(0.025)

-0.067(0.028)0.040

(0.030)0.000

YesYes

YesYes

0.0705,395

Withsemifinals

(3)

-0.054(0.069)0.005

(0.070)0.024

(0.057)0.000

YesYes

YesNo

0.0336.239

(4)

-0.085(0.069)0.037

(0.070)0.027

(0.062)0.000

YesYes

YesYes

0.0456,239

Semifinals

(5)

0.103(0.061)

-0.142(0.066)0.053

(0.049)0.210

YesYes

YesNo

0.0741.360

(6)

0.099(0.061)

-0.137(0.067)0.115

(0.078)0.222

YesYes

YesYes

0.0811,360

Finals

(7)

0.002(0.028)

-0.091(0.075)0.058

(0.058)0.207

YesYes

YesNo

0.0641,127

(8)

0.0004(0.028)

-0.078(0.075)0.123

(0.089)0.271

YesYes

YesYes0.0681.127

Notes: The dependent variable is I if the individual is advanced to the next round and 0 if not. Standard errors are inparentheses. All specifications include dummies indicaling wheiher the sex is missing, and an interaction for the sexbeing missing and a blind audition. "Other covariates" include automatic round, number of auditions attended, whethera "Big Five" orchestra, size of round, proportion female at the round, and whether a principal (including assistant andassociate principal) or substitute position; except in columns (2), (4), (6), and (8) for which "Other covariates" includeonly automatic placement and numher of auditions attended. These results are comparable to those in Table 6 butwithout individual hxed effects.Source: Eight-orchestra audition sample. See text.


TABLE A4—LINEAR PROBABILITY ESTIMATES OE THE LIKELIHOOD OF BEING ADVANCED: ASSESSING SHORT-PANEL BIAS

Blind

Female X Blind

/j-value of HQ.Blind + (Female X Blind) = 0

Other covariates?individual fixed effects?Year fixed effects?

Number of observations (person-rounds)

Blind

Female X Blind

p-value of H^:Blind + (Female X Blind) = 0

Other covariates?Individual fixed effects?Year fixed effects?R'Number of observations (person-rounds)

Part A;

Without semifinals

I"

-0.024{0,066)0.126

(0.095)0,233

YesYesYes

0.4911.025

II"

-0,042(0.063)0,095

(0.071)0.502

YesYesYes

0,537639

Preliminary rounds

Preliminaries

With semifinals

I

-0,047(0,383)

-0,035(0.403)0.807

YesYesYes

0.4231,928

II"

-0.095(0.744)0.041

(0.275)0.943

YesYesYes

0,73255

Part B; Semifinals and finals, and wilh orchestra fixed effects

Semifinals

I-' II"

0.060 0.169(0.133) (0.109)

-0.179 -0.284(0.195) (0.142)0.438 0.298

Yes YesYes YesYes Yes

0.438 0.593269 223

P

0.123(0.356)0.157

(0,408)0,212

YesYesYes

0.721127

With orchestrasFinals fixed

II" I'

-0.140 0.084(0,449) (0,047)0.403 0.042

(0,415) (0.051)0,587 0,011

Yes YesYes YesYes Yes

0.728 0,50667 2,321

effects

0.352(0.056)0.021

(0,041)0,000

YesYesYes

0,6031,776

Notes: The dependent variable is I if the individual is advanced lo the next round and 0 if not. Standard errors are inparentheses. These are the same specifications as in columns (2), (4), (6), and (8) of Table 6 and column (2) of Table 7.Source: Eight-orchestra audition sample. See text,

" Includes those who auditioned at least three times (for the relevant round)." Includes those who auditioned at least once in a blind audition and at least once in a not-blind audition (for the relevant

round).

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