estimating selection effects in occupational mobility in a 19th century city (hardy m., 1989)

8/22/2019 Estimating Selection Effects in Occupational Mobility in a 19th Century City (Hardy M., 1989)

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Estimating Selection Effects in Occupational Mobility in a 19th-Century CityAuthor(s): Melissa A. HardySource: American Sociological Review, Vol. 54, No. 5 (Oct., 1989), pp. 834-843Published by: American Sociological AssociationStable URL: http://www.jstor.org/stable/2117757 .

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ESTIMATING SELECTION EFFECTS INOCCUPATIONAL MOBILITY IN A 19TH-CENTURY CITY*MELISSA A. HARDYFlorida State University

This study examines the relationship between the processes of occupationalmobility and persistence. Using manuscript census data from Indianapolis,1850-1860, I assess the importanceof selection effects on the likelihood of upwardor downwardmobilityand on the socioeconomic status achieved by 1860, relativeto 1850 originstatus. Alternative peculationshave argued that out-migrants itherconstituted a sort of "permanent loating proletariat" (and therefore weredistinctlyunsuccessful n termsof occupationaladvancement),or wereparticularlyaggressive entrepreneursand therefore ikelyto be amongthe mostsuccessful).Asan indirecttestof these hypotheses, mobilityandpersistencewere modeled as jointoutcomes influencedby a commonset of "unobserved"variables. Theanalysis ofIndianapolisdata shows that the sorting processes of occupational mobilityandnonpersistencewere affected by a similar set of observedcharacteristics,but thatunmeasuredvariablesexerted no net effects.

Beginning in the 1960s, the "new urbanhistorians"utilizedfederal manuscript ensusschedules and other archival resources as abasis for investigatingoccupationalstatus andcareer patterns in 19th-centurycities (e.g.,Blumin 1969; Knights 1971; Thernstrom1973; Glasco 1978;Griffin and Griffin 1978).In general, these studies concluded that theadult male populations were marked byconsiderable flux both geographically andoccupationally-although Grusky's(1986) re-cent reassessment suggests that the 19th-centuryrate of careermobilitywas only abouthalf as great as today's rate. However,because the data bases of those studies wereconstructed by record linkage and couldinclude information only for residents whowere present and located during successiveenumerations,migrantswereneglected. Spec-ulationsabout the out-migrants-their subse-quent occupational successes, their motiva-tions for leaving, and so forth-typicallyconceived of the migration as a sortingprocessthat at least tendedto be equilibrating

* Direct all correspondenceto Melissa Hardy,Department f Sociology, FloridaState University,Tallahassee,FL 32306-2011.The data file was constructedprimarily romthe1850 and 1860 federal manuscriptcensus sched-ules of MarionCounty, IN. I wish to thankMaryMathisfor her assistance n expanding he data fileand Lawrence Hazelrigg, Charles Nam, AageSorensen, and anonymous reviewers for theircomments on earlier versionsof this paper.

of wage and price and/or other labor-marketdifferentials. One of the more extremespeculations reasoned that the out-migrantsmay have constituted a sort of "permanentfloating proletariat" Thernstrom1973, p. 42)who mostly drifted from one city to another.Conversely, the out-migrantsmay have beenespecially "entrepreneurial n spirit" andamong the most successful. More likely thesecharacterizationsre much too broadlypainted;it may well be that, then as today, citydifferences n income, employment,and otherlabor-market haracteristicswere not relatedin any simple way, if at all, to the flows ofintercity (or interregional)migration.The importanceof the question of 19th-century city out-migrants(and, correspond-ingly, in-migrants) s twofold. In addition tothe compositional side of the question-whothe out-migrants were, why they left, whattheir subsequentcareer records were, and soon-it is important o consider the selectioneffects of out-migration n estimates of careermobility among the persisters. If the out-migrants were part of a permanent floatingproletariat, estimates based on only thepersisters may overstate the amount ofmobility experienced by city residents-unless, of course, that "floating proletariat"phenomenonwas sufficiently common that acity's in-migrantswere largelydrawnfromit.Or, if the out-migrants were unusuallyentrepreneurial nd among the most success-ful, persister-based stimates could paint too

834 AmericanSociological Review, 1989, Vol. 54 (October:834-843)

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SELECTIONEFFECTSIN OCCUPATIONALMOBILITY 835pessimistica pictureof careeradvancementsespecially if the city's in-migrants, whotypically exceeded in number the out-migrants during any given interval, sharedthat same "spirit"and record of success.The majoraim of this paper s to attemptananswer to that questionof "selection effects"by analyzing census data for one city,Indianapolis, Indiana, 1850 to 1860.1 India-napolis was then making the transition rom asmall isolated town to a major wholesale andretail commercial center, a transformationmade possible by factors associated with theintroductionof the railroad. By 1855 India-napolis had become the railway hub of eightmajor lines radiating outward from thenation's first union depotto Chicago, Detroit,Cleveland, Cincinnati, Louisville, St. Louis,and points beyond. During the 1850s thepopulationdoubled n size, andchangesin theoccupational structure increasingly reflectedthe importanceof, industrialactivities in anemerging industrial-commercialcenter. ButIndianapoliswas also a gateway to the greatexpanse of still unsettledarea to the west, andto cities just beginningto take shape;it was acity in which the channels for both occupa-tional andgeographicmobility were consider-able (Hardy 1978). The mid-1800s were atime of rapid and profound social change inmany Americancities, and Indianapoliswasnot unique in these respects. However,relative to more established east-coast citiessuch as Thernstrom's Boston or Blumin'sPhiladelphia, the rate of population growthwas greater and the transformation rom acraft-orientedto an industrialjob structurewas in an earlier and more rapid stage ofdevelopment.

ESTIMATINGOUT-MIGRATION,1850 TO 1860This analysis can yield at best only a "first

approximation"of selection effects of out-migration. One reason is the paucity ofinformationavailable in the manuscriptcen-sus schedules. Moreover, as the alternativescenarios depicted above indicate, adjustingmobilityestimates for selection effects shouldattend to the in-migrant as well as theout-migrantpopulation.But historical censusdata ncludedno retrospectivenformation, nddata files constructedfrom record linkageshave typically been "forward ooking"; onlythe selection effects of out-migrationcan beaddressed. Further,since the basic operationof record linkage is the identification ofpersisters, out-migrants are defined residu-ally, but the residualcategoryis not homoge-neous. It includes cases of mortality, cases ofenumerator rror,and no doubt at least a fewcases of errorin the record-linkageprocess.There is no direct way of segregatingthesevarious categories in the data file. But thesituation s farfromhopeless, as we shall see.Nearly 7 of every 10 of the 2,337 adultmales enumerated in Indianapolis in 1850could not be located in the 1860 enumerationor in the 1862 city directory.To anyone notacquaintedwith studies of 19th-century ities,a nonpersistencerate of 69 percent may seemastoundingly high. It is not. Parkerson's(1982, p. 102) review of publisheddata fromrecord-linkage tudies of 68 separatecommu-nities shows thatin 40 of the communities he10-year rate of nonpersistence ranged be-tween 60 and 80 percent.The averagerate forall 68 communities was 62 percent. Thequestion is, how much of that69 percentwasactually due to out-migration?Some reason-able estimatescan be constructed.First, mortality. Using the Coale-Demenymodel life tables, Parkerson estimated adecadalmortalityamong white males, 1850-60, of nearly 15 percent. But that estimatewas based on a life expectancyat birth(37.3years). Since the base populationof interesthere was aged 16 or older in 1850 (past thehigh-risk years of infancy and childhood), 15percent is surely too high. Barrow's (1980)calculationsfor late-century ndianapolissug-gest that5 to 8 percentof the residentsdid notsurvive to the next decennial count. Assum-ing from Barrows' calculations an outsidelimit of 10 percent, it seems likely that atmost only one of every seven cases ofnonpersistencewas due to mortality.The combined effect of enumerator andrecord-linkageerror can be estimated indi-

1 The datafile consists of the entire adult (i.e.,16+) male populationof Indianapolis n 1850, asenumerated n the manuscriptcensus schedulesofthe Seventh U.S. Census. Record linkage to the1860 enumerationwas by visual inspectionof theentire set of manuscriptschedules of the EighthCensus. Dodd, Talbott, and Parsons'IndianapolisCityDirectoryand Business Mirror or 1862 wasused as a supplementalsource for record linkage(though in fewer than 10 percent of the linkedcases).



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836 AMERICANSOCIOLOGICALREVIEWrectly with the aid of Parkerson's tudy of the1855 New York State Census, whichincludeda question asking all residents how long theyhad lived in their current community ofresidence. Parkerson concluded that therecord-linkage studies overstated nonpersis-tence by about two-fifths. Whereas theaverage rate among the 68 record-linkagestudies was 62 percent, it was 44 percentamong the New York communities. Further-more, among communities that experiencedrapid growth, the discrepancywas not .62 -.44 = .18 but .34. Since the populationofIndianapolis doubled during the 1850s, thislarger figure will be adopted as a maximumestimate of the extent to which nonpersistencewas overstated n the record-linkage tudy ofIndianapolis.But this figure of .34 includescases of mortalityas well as enumerationandrecord-linkageerror. Subtracting he mortal-ity component (no more than .10) leaves anestimate of at least .24 attributable toenumerationand record-linkage rror.Thus, it is reasonable to conclude that nomore than 10 percentof the 2,337 adult malesenumerated in 1850 died before the 1860count, 35 to 40 percent were out-migrants,and the remainder(50 to 55 percent) were

persisters, althoughas many as two-fifths ofthese persisters were missed by the censustakersor by the record-linkageprocess. Whilethe data source does not afford means bywhich to segregate or reclassify these lattercases, thatinability is not particularly ignifi-cant to the majoraim of this paper-assessingthe effect of "sample selection" on estimatesof occupationalmobility-since all sources ofselection effect are relevant. It limits what canbe said specifically about the selection effectsof out-migration, as distinguished from theselection effects of undetectedpersisters. Butwhetherout-migrantor undetected persister,if one or more of these categories of mendiffered in mobility-related ways from themen who were capturedby the enumerationand record-linkage processes, estimates ofcareer mobility based on only the latter couldbe seriouslybiased.ESTIMATINGA PERSISTENCEMODELAs reported in Table 1, persisters andnonpersisterssignificantly differ in composi-tion on nearly all available measures. Thedifferences are consistent with findings fromother studies of 19th-centurycities. Nonper-

Table 1. Comparisonsof PersistersandNonpersisters n 1850Rate of CompositonaNonpersistence Persisters Nonpersisters

Total 69% (N= 730) (N= 1607)Nativity: Indiana 73% 14% 17%Other U.S. 64 63 52Foreign 74 23 30Race: White 68 97 95Nonwhite 77 3 5Age: 16-19 80 6 1120-29 76 31 4430-39 65 29 2440-49 57 21 1250+ 60 13 9

Mean 34.9 30.9s.d. 11.5 11.3Marital:Married 58 72 46Not married 81 28 54Occupation:Professional 55 9 5MajorP,M,O 46 6 2Clerk, sales 61 8 6PettyP,M,O 44 14 5Skilled 72 40 48Semiskilled 68 8 9Unskilled 78 15 25DuncansSEI: Mean 32.0 24.4s.d. 22.7 18.0

a The compositionalcomparisons columns2 and 3) are signficantat the .001 level for all variables except race.



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SELECTIONEFFECTSIN OCCUPATIONALMOBILITY 837Table 2. Rates of Nonpersistence (cell values) by Age, Marital Status, and White-Collar versus Blue-CollarOccupation

White-Collar Blue-CollarAge Married Unmarried Total Married Unmarried Total16-29 .46 .66 .59 .70 .83 .7930+ .43 .69 .47 .61 .84 .66All ages .43 .67 .51 .64 .83 .73

sisters were more likely to be unmarried,foreign-born (predominantly German andIrish), younger, and of lower status. Ingeneral, men in occupational categories thatincluded propertyownershiphad the lowestrates of nonpersistence, followed by theprofessionalsand then the clerks and sales-men. Blue-collar men, especially the un-skilled, had the highestrates. Maritalcompo-sition is partly confounding of thosedifferences: for example, 84 percent of themajor proprietors,managers, and officials,and 74 percent of their "smaller" counter-parts, were married, which contrasts withonly 36 percentof the clerks and salesmen,54 percentof the skilled and46 percentof thesemiskilled and unskilled men. However,even after marital status is controlled, somenotableoccupationaldifferencesremain. Un-skilled laborers had the highest rates ofnonpersistenceregardless of marital status,althoughthe rate among single skilled work-ers was about as high. And while theoccupation-specific rates of nonpersistenceamongsingle men were generally n excess of70 percent, the rate for petty (but not major)proprietors,managers, and officials was acomparatively ow 57 percent.2The age gradient of nonpersistencerates(column 1, Table 1) approximatesthe agegradient of rates of internal migration re-ported n present-daystudies (e.g., Long andBoertlein 1976)-a high rate among those intheir late teens and 20s, followed by rapiddiminution of rate. (The small up-tick innonpersistenceamong the Indianapolismenaged 50 andolder is most likely a manifesta-tion of the mortality component of thenonpersister category.) However, as thenonpersistencerates (cell values) in Table 2

show, it was not age so muchas marital tatusthat discriminated the persisters from thenonpersisters.Whetheryoung or old, unmar-ried blue-collar men disappeared n droves.Of course, singleunskilledmen wereundoubt-edly among the most "invisible" to censustakers, but it is also highly probable that agreat many of these men had actually leftIndianapolis.After all, married white-collarmen aged 30 or older would have been amongthe most visible to enumerators, and 43percent of them were nonpersisters. Sincethere is good reason to believe that young,single, blue-collar workers were more likelythan older, married, white-collar men tomove on to anothercity, our estimatedoverallrate of out-migration (35 to 40 percent)probablymeans that at least half of the singleblue-collarmen were out-migrants.Results from probit estimationsreported nTable 3 confirm that marital status is asignificantand strongnet predictorof persis-tence, as are foreign nativityand white-collarstatus. Blue-collarmen in generalwere morelikely to have out-migratedor to have beenoverlookedby enumerators,even aftertakinginto account the effects of maritalstatus andforeign nativity. This model provides themeans of assessing selection effects ofnonpersistenceon the probability of careermobility.

SELECTIONEFFECTSINOCCUPATIONALMOBILITY

Careermobility, 1850 to 1860, is measured ntwo ways. First, using Thernstrom'stypol-ogy, I examine the probabilityof upwardordownwardmobility across the seven catego-ries previouslynominated,assumingordinal-ity among them. Because of the floor andceiling effects inherent in this definition ofmobility (see footnote 5), I also examine thedistributionof statusdistancesbetween 1850

2 This difference between petty and majorproprietors, managers, and officials is partlycompositional:a largerproportionof the "petty"than of the "major" category consisted ofproprietors s opposedto managersand officials.



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838 AMERICANSOCIOLOGICALREVIEWTable 3. ProbitEstimationof PersistenceModel

Eq I Eq 2Constanta - .46 - .47

(.09) (.07)-5.02 -6.40Foreign-born -.16 -.17(.08) (.07)-2.12 -2.29Not married -.51 -.51

(.07) (.07)-7.20 -7.17Age: 16-29 -.06 -.07(.07) (.07)-.91 - 1.02Professional .41(.14)2.94Major P,M,O .49(.18)2.78Clerks, sales .52(.14)3.58Petty P,M,O .69(.13)5.38Skilled .12(.09)1.39

Semiskilled .22(.13)1.66Duncan SEI .008(.002)5.179Log-likelihood - 1107 - 1080N 1941 1894a The reference category for foreign-born is allU.S.-born; for age, 30 years and older; for occupation,unskilled.

and 1860 occupationsby relying on Hauser'smappingof occupational itles into Duncan'sindex.3

To allow for correlationof the processes ofoccupational mobility and persistence, Iestimate a series of two-equation probitmodels. The first equation specifies themobility process by assessing the impact ofworkers' occupational location and demo-graphic characteristics on the likelihood ofupward (or downward) mobility relative tooccupational stability. The second equationspecifies the selectionprocessthat defined thegroup of workers whose occupationalmobil-ity was assessed. The two-equation modelallows joint estimationof both selection andmobility equations without enforcing theassumption of zero correlation between un-measurable factors that might have beeninfluencingthe likelihood of both persistenceand mobility.4

3The use of scales such as Duncan's SEI withhistorical data has been criticized for allegedinsensitivityto long-termchanges in statushierar-chies. Hauser's analysis argued that, even thoughthe use of 20th-century SETscores carries somebias, use of alternative scales developed byhistorians on the basis of in-depth analyses ofspecific urbansites also raises the question of bias;he concludes that "true occupationalstatus in thetwentiethcenturyis aboutas good an indicatoroftrue occupationalstatus in the nineteenth centuryas are any of the five-city ratings" (1982, p. 118).Hauser(1982, p. 122) also estimateda correlationof .88 betweenoccupationalstatusin the mid-19thcentury and prestige in 1925. Blau and Duncan(1967, p. 120) had previouslyreporteda correla-

tion of .93 between 1925 and 1963 prestigerankings. William Form has noted in a personalcommunication hathe "founda gross overestima-tion of skilled workers in the pre-1900 censusesand almost no way to be certain whether manyoccupations were 'semiskilled'" (see Form 1985,pp. 92-93). The classification scheme used in theBureau's tabulationsdid change a numberof timesafter 1870, as did the amount (and no doubt thestandardization f quality) of information olicitedby enumerators (see Conk 1978). The presentstudy is based not on the Bureau's tabulateddata,however, but on the manuscript chedules and thespecific occupational titles there recorded byenumerators.Following Thernstrom's 1973) clas-sification scheme, more than 85 percent of thecases I coded as "skilled workers"consisted of thefollowing occupationaltitles: carpenter,brickma-son, plasterer, painter, blacksmith, carriage orwagonmaker, harnessmaker, saddler, tailor orhatter, shoemaker, and printer. Other titles in-cluded gunsmith, millwright, foundryman,baker,silversmith, bookbinder, and jeweler. In anynumberof the cases, the accuracyof the nominalattributionmay be doubted, of course. A self-attribution f "carpenter," or instance,may havebeen an exaggerationof the respondent's"real"skill status of "carpenter'sassistant." With suchquestionswe simply face the limits of the data.4 This technique expands specification of themobility equation by including a latent variablethatis based on unmeasured haracteristics elatedto persistence. Rho provides an estimate of thecorrelation between the probabilitiesof mobilityand persistence, net of the influence of specifiedindependentvariables.Estimating he SES modelsfollows the same logic, using lambda to denote ahazardrate that capturesthe instantaneousproba-bility of being excluded from the persisterpopulation,conditional on membership n the risk



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SELECTIONEFFECTSIN OCCUPATIONALMOBILITY 839Table 4. ProbitEstimationof UpwardMobility, with and without Selection

without selection with selection1 2 3 4 5 6

Constant -.49 - 1.63 - 3.09 - 1.37 -2.07 -3.10(.06) (.21) (.53) (.06) (.23) (.68)-8.20 -7.63 -5.80 -24.46 -9.10 -4.53Petty P,M,O 1.58 1.61 1.58 1.61(.27) (.28) (.28) (.28)5.79 5.83 5.69 5.69Skilled 1.01 .99 .91 .99(.23) (.24) (.25) (.25)4.36 4.21 3.63 3.97Semiskilled 1.47 1.58 1.35 1.58

(.29) (.31) (.33) (.32)5.08 5.15 4.08 4.97Unskilled 1.73 1.79 1.50 1.79(.25) (.27) (.35) (.30)6.84 6.53 4.31 5.99Race:White .95 .95(.41) (.40)2.33 2.34Foreign-born -.15 -.15(.16) (.17)-.91 -.88Age: 16-29 .78 .78

(.30) (.35)2.57 2.2330-49 .47 .46(.30) (.34)1.55 1.38Log-likelihood -300 -264 -256 - 1285 -1260 - 1253Rho .94 .47 .00(.08) (.26) (.40)12.18 1.80 .00

Probit estimationsof models predictingtheprobabilityof upwardand downwardmobilityare reported n Tables 4 and 5, respectively.5In each table, equations 1-3 describe models

without adjustment for selection effects.Equation1 fits only a constant, showing theprobabilityof mobility(upwardor downward)relative to immobility. Thus, on average therelative probability of career advancementwas .31 (associated with a Z-value of -.49),while the relative probabilityof careerdeclinewas about half that large, at .16 (i.e., aZ-value of -1.01). Equation2 assesses theprobabilityof upwardor downward mobilityfor specific occupationalcategories;equation3 adds demographicvariablesto the model.These results are straightforward,but fourspecific findingscan be noted. First, althoughrace was not a significant predictor ofpersistence, white men (95 percent of the1850 total) were more likely upwardlymobile, net of other factors. Second, foreignnativity predictedpersistencebut not mobil-ity. Third, whereasmaritalstatuswas a strong

pool; the coefficient of lambda estimates theassociationof the two processes, net of specifiedfactors.5 Since none of the men in the top twooccupationalcategorieswas upwardlymobile (forprofessionalsthis was by definition;for the majorproprietors,managers,and officials it was proba-bly an effect of career tracking and thereforevirtuallydefinitional),thetopthreecategorieswerecollapsed into one reference category. For down-ward mobility the unskilled and semiskilledcategories were collapsed into a reference cate-gory. Also, initial specification of the modelsincluded marital status, but it proved to beexcessively collinear with other variables (espe-cially age) and was thereforedeleted.



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840 AMERICANSOCIOLOGICALREVIEWTable 5. Probit Estimationof DownwardMobility, with and withoutSelection

without selection with selection1 2 3 4 5 6

Constant -1.01 -1.68 - 1.23 -.09 -2.22 - 1.87(.08) (.27) (.45) (.24) (.44) (.56)-13.24 -6.26 -2.70 - .38 -5.07 - 3.34

Professional .83 .83 .99 1.05(.34) (.40) (.33) (.39)2.46 2.09 2.96 2.68

MajorP,M,O .42 .51 .64 .79(.41) (.46) (.43) (.49)1.02 1.10 1.50 1.62Clerks,sales 1.14 1.14 1.25 1.30(.35) (.41) (.34) (.39)3.25 2.79 3.71 3.37Petty P,M,O 1.44 1.46 1.58 1.65

(.33) (.40) (.32) (.36)4.42 3.85 5.00 4.52Skilled .38 .40 .42 .50

(.30) (.36) (.29) (.36)1.26 1.10 1.46 1.46Race: White - .37 - .35(.53) (.52)-.71 -.68Foreign-born -.39 -.43(.27) (.26)

-1.46 -1.65Age: 50 + -.21 -.12(.18) (.20)- 1.14 -.62Log-likelihood -170 -152 -150 -1006 -992 -989Rho - .65 .41 .45(.13) (.36) (.40)-4.95 1.14 1.14

predictor of persistence, it did not haveseparatelyestimable net effects on mobility.Fourth, while age had no net effects in themodel of persistence, younger men (16-29)were more likely upwardly mobile, net ofotherfactors.6Such conclusions are hardlynovel (cf. thepreviously cited studies). The question ofcentral nterest,however, turnson the charac-teristicsor dispositionsof workersthat couldnot be specified in either the persistence or

the mobility equations and whether unmea-sured traits that increased the probability ofpersistencealso increased (or decreased)theprobability of career mobility. If the out-migrants, for example, and perhaps as wellthose overlooked by enumerators,were char-acterized by some unmeasured personalitytraits associated with career advancement(e.g., "entrepreneurial spirit"), the two-equationestimations should show this interre-latedness as a negative correlation (rho)between the error erms of the persistence andmobility equations. If, however, it is thepersisters who possess traits conducive tocareeradvancement,rho should be positive inthe case of upward mobility and negative inthe case of downward mobility. Equation4assesses the impact of unmeasuredfactorsthat increasethe likelihood of persistence on

6 Because downwardmobilitywas less frequentthan upward mobility, it was not possible todiscriminate among the three age-groups. Thecontrastbetween young and middle-agedworkers(a combined reference group) and older workerswas maintained o see whetherold age (relativetothe age structureof the time) increased a worker'svulnerability o downwardmobility.



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SELECTIONEFFECTSIN OCCUPATIONALMOBILITY 841the probabilityof careermobility. For upwardmobility the value of rho is large, positive,and clearly significant; that is, unmeasuredfactors associated with career advancementalso increasedthe probabilityof persistence.Moreover, the estimate for the constantis alarger negative number than in equation 1;thatis, the probabilityof careeradvancement,net of unmeasured actors related to persis-tence, was very small (only .09). The resultsfor downwardmobility correspond: unmea-sured traits that decreased the risk ofnonpersistencewere associated with a lowerrisk of downwardmobility.Equations5 and 6 successively introducethe occupational categories and the demo-graphic variables. As a result, the value ofrho is no longer significantly different fromzero. What's more, the parameterestimatesof equations5 and 6 are virtuallyidenticaltothose of equations2 and 3, for both upwardand downwardmobility. In sum, if we thinkof career mobility as a process that selectsworkerswith characteristics avorable to jobperformanceor productivity,we can questionwhetherworkerspossessing these traitswere,on the whole, more likely to remain inIndianapolisduring this 10-year period, ormore likely to have been lost to out-migration, enumerator error, or mortality.The evidence favors the persisters, showing

thatunmeasured actors relatedto persistencewere positively related to the likelihood ofupward mobility and negatively related todownward mobility, but that these factors,which were distinct from the effects ofoccupationaland demographiccharacteristicsin predicting persistence, were mediatedthrough (or at least correlated with) originoccupationanddemographic raitsin predict-ing mobility.Since collapsing all nondiagonalelementsof the mobility table into two categories(upward or downward mobility) neglectsinformationon within-categorydifferences, Ialso estimatedmodels using Duncan's indexto assess selection effects on the statusdistance traversedthroughupward or down-ward mobility. Average improvement n jobstatus was 3.8 points; the positive value isconsistent with the predominanceof upwardover downward mobility, but the distribu-tional characteristicsof the distance measuresuggest incremental rather than dramaticchangesin job statusfor workers,on average.Results of this analysis (Table 6) corre-spond to those of Table 5. The positivelambdacoefficient in equation3 indicates thatunmeasured worker characteristics that in-creased the probability of persistence alsopredict a gain in status during the 10-yearperiod. However, the estimate is significant

Table 6. OLS Estimationof Duncan'sIndex with and without Selectionwithoutselection with selection

1 2 1 2Constant 11.04 4.16 3.07 -2.89(1.12) (3.68) (4.78) (6.03)9.88 1.13 .64 - .48Duncan1850 .78 .77 .82 .80(.03) (.03) (.04) (.04)27.68 25.50 21.72 20.71Race 8.17 8.13(3.76) (3.73)2.18 2.18Foreign-born -1.00 -1.04(1.62) (1.61)-.62 -.65Older - 1.70 -1.19(1.43) (1.46)-1.19 -.81lambda 5.93 5.20(3.45) (3.54)1.72 1.47R2 .58 .58 .58 .58



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842 AMERICANSOCIOLOGICALREVIEWonly by a one-tailed test (.05 level), andoncethe additional variables are specified (i.e.,race),7 the coefficient for lambda is furtherreduced n size andprecision.

DISCUSSIONResearchershave speculatedthat, because ofcompositionaldifferences between persistersand nonpersisterson traits relevant to thecareer-mobility rocess, studies based only onpersisters yield biased estimates of mobility.However, results of the present study leavelittleroom for doubting he mobility estimateson grounds of selectivity bias. Once thelikelihood of mobility was conditioned ondemographic traits, the two-equation esti-mates converged with the single-equationestimates, and the error correlation acrossequationsconvergedto zero.The general theoretical point is simple.Selectivity on an identifiable factor does notin itself necessarilyentail bias in subpopula-tion estimates; the nature of the selectionprocess must be considered. Nonrandomexplicit selection, as in exclusion of observa-tions because of a thresholdon the dependentvariable, leads to biased and inconsistentregressionestimates. But when selectivity isincidental, as in this study, it is difficult topredict the correlation between disturbancesof the selection equation and those of the"primary" quation-unless one can identifyfactors that have been omitted from bothequations and that are orthogonal to thespecified regressands Berk 1983).

Both career mobility and nonpersistence(out-migrationas well as enumerator errorand mortality) are selection processes; thequestion of interest is whether the processesoperatedby the same or by different criteria.Thernstrom's hypothesis of a "permanentfloating proletariat" implies the processeswere regulated by different criteria: lessskilled workers who had little chance ofadvancementwandered from place to place,in a futile search for betteropportunities.Thisthesis, buttressedby evidence of high rates ofblue-collarnonpersistence,seems to suggestthat whereas a city's working class fit

Schumpeter's (1955, pp. 127-29) generaldescription of "class" "a hotel or anomnibus, always full, but always of differentpeople"-this was partly because of theexistence of a large, regionally based contin-gent of mostly permanentdrifters.However,the pessimism of Thernstrom's speculationaboutthe prospectsof migratingworkersmaynot have been warranted.At least the presentstudy gives reason to doubtit.Since nonpersisterstended to be youngerand of lower status-traits associated withcareeradvancement-support for the hypoth-esis of a permanent loating proletariatwouldhave to come from characteristicsof persis-tence that were not included either inThernstrom'sdata or in mine. But the modelsestimatedhere allowed for mobilityeffects ofunmeasuredas well as measured traits. Inother words, the selection processes ofpersistence and mobility were modeled asjoint outcomes producedpartly by commonunmeasuredvariables. The results gave noindication of net effects of any unmeasuredtraits. In short, there seems to have beennothing distinctive about the nonpersistersthat entailed for them a competitivedisadvan-tage in chances of career mobility. That thenonpersisters were numerous and usuallyyoung, unmarried, and of lower status isindisputable. But taken as a whole they fitSchumpeter's "omnibus" depiction no lessthan did the working-class persisters ofIndianapolis.Indeed, it seems likely that theout-migrants, rather than being permanentmembers of a floating proletariat or lumpen-proletariat), ettledelsewhere,probably o thewest, and subsequently experienced careertrajectories hat, on the whole, mirrored hoseof their counterpartswho remained in India-napolis. The latter point is speculative, ofcourse. It is almost impossible to trackout-migrantsof l9th-century cities, but rele-vant evidence could be gained indirectlybycomparinga city's in-migrants o its nonper-sisters in terms of demographiccompositionand to the persistersin terms of mobility.

It would also be useful to replicate thepresentanalysis with data from one or more19th-centurycities differing from Indianapo-lis in size, age, and stage of economicdevelopment in order to determine whetherthe resultsreportedhere are generalizable.MELISSAA. HARDY is AssociateProfessorof Sociology and ResearchAssociate with the

7Equation 4 provides further support for therace effect detected in Table 5. Net of originstatus, the 1860 SES of white workersaveraged8points higher thanthatof black workers.



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SELECTIONEFFECTSIN OCCUPATIONALMOBILITY 843Instituteon Aging at FloridaState University.In addition to expanding her study ofhistorical patternsof occupational mobility,she continuesher researchon retirement,thechanging structuresof opportunityand con-straint faced by older workers, patterns ofindividualdecision making, and questions ofintergenerationalquity.REFERENCESBarrows,RobertG. 1980. "Hurryin'Hoosiersandthe American'Pattern':GeographicMobility inIndianapolisand UrbanNorthAmerica."SocialScienceHistory5:197-222.Berk, Richard A. 1983. "An Introduction to

Sample Selection Bias in Sociological Data."AmericanSociological Review48:386-98.Blau, Peter and Otis Dudley Duncan. 1967. TheAmerican Occupational Structure. New York:Wiley.Blumin, Stuart. 1969. "Mobility and Change inAnte-BellumPhiladelphia."Pp.165-208 in Nine-teenth-CenturyCities, editedby StephanThern-strom and RichardSennett. New Haven: YaleUniversityPress.Conk, Margo. 1978. "OccupationalClassificationin the United States Census: 1870-1940."Journalof InterdisciplinaryHistory9:111-30.Form,William. 1985. DividedWeStand:Working-Class Stratification in America. Urbana andChicago:Universityof Illinois Press.Glasco, Laurence. 1978. "Migrationand Adjust-ment in the Nineteenth-CenturyCity." Pp.123-75 in Population in Nineteenth-CenturyAmerica, edited by Tamara K. Hareven andMaris Vinovskis. Princeton:PrincetonUniver-sity Press.

Griffin, Clyde and Sally Griffin. 1978. Nativesand Newcomers:The Orderingof OpportunitynMid-NineteenthCentury Poughkeepsie. Cam-bridge:HarvardUniversityPress.Grusky,David B. 1986. "AmericanSocial Mobil-ity in the 19th and 20th Centuries." CDEWorking Paper 86-28. Madison: Center forDemography and Ecology, University of Wis-consin.Hardy, Melissa A. 1978. "OccupationalMobilityand Nativity-Ethnicityin Indianapolis, 1850-60." Social Forces 57:205-21.Hauser, RobertM. 1982. "OccupationalStatus inthe Nineteenthand Twentieth Centuries."His-torical Methods 15:111-26.Knights, Peter R. 1971. The Plain People ofBoston, 1830-1860. New York:Oxford Univer-sity Press.Long, Larry H. and Celia G. Boertlein. 1976."The Geographical Mobility of Americans."Current Population Reports, Series P-23, no.64. Washington,DC: U.S. GovernmentPrintingOffice.Mare, Robert D., Christopher Winship, andWarrenN. Kubitschek. 1984. "The Age Patternof Employment." American Journal of Sociol-ogy 90:326-58.Parkerson,Donald H. 1982. "How Mobile WereNineteenth-Century Americans?" HistoricalMethods 15:99-109.Schumpeter,Joseph. 1955. Imperialismand SocialClasses. New York: Meridian.Thernstrom, Stephan. 1973. The Other Bosto-nians. Cambridge:HarvardUniversityPress.U.S. Bureau of Census. 1980. "GeographicalMobility:March1975 to March 1979." CurrentPopulation Reports, Series P-20, no. 353.Washington, DC: U.S. Government PrintingOffice.

estimating selection effects in occupational mobility in a 19th century city (hardy m., 1989)

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