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Empirical Analysis of Economic Institutions Discussion Paper Series No.15 Horizontal Transfer, Vertical Promotion and Evolution of Firm Organization Kenn Ariga December 27, 2003 This discussion paper series reports research for the project entitled “Empirical Analysis of Economic Institutions”, supported by Grants-in-Aid for Scientific Research of the Ministry of Education and Technology.
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Empirical Analysis of Economic Institutions Discussion Paper Series

No.15

Horizontal Transfer, Vertical Promotion and Evolution of Firm Organization

Kenn Ariga

December 27, 2003

This discussion paper series reports research for the project entitled “Empirical Analysis of Economic Institutions”, supported by Grants-in-Aid for Scientific Research of the Ministry of Education and Technology.

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Horizontal Transfer, Vertical Promotion andEvolution of Firm Organization∗

Kenn Ariga [email protected] of Economic Research, Kyoto UniversityYoshida Honmachi Sakyoku Kyoto 6068501 Japan

December 27, 2003

Abstract

This paper investigates interactions among horizontal transfer, promo-tions across ranks, and creations and destructions of jobs inside a largeJapanese manufacturing firm. In this sample firm, we find that job de-structions and creations accounts for the majority of horizontal transfersof employees within the firm. This is in sharp contrast to a popular per-ception that employees move according to a well-defined career path ina stable organization with internal labor market. Instead, we find thatunits and jobs are constantly created and destructed at this firm andthat individual career paths are far more dynamic, and, state and pathdependent.

The econometric analysis on determinants of promotion policy con-firm these findings, as well as predictions based on multi-skilling model ofhuman capital. First of all, transfers to a functionally similar units whichenable employee to acquire multiple skills do enhance the promotion prob-ability. On the other hand, transfers to functionally or geographicallydifferent units are often detrimental to the promotion prospect, especiallythose at earlier stage of career. In general, an employee career at thisfirm is significantly influenced by the success and failure of units, and, inparticular, we find that promotion probability for some type of employeesis significantly higher for those transferred from destructed sections, andalso for those transferred into newly created sections.

Journal of Economic Literature Classification Numbers: J24, J41.

∗I benefitted from valuable comments by Giorgio Brunello on earlier drafts of the paper.Two anonymous referees and Mark Rebick, representing this Journal, also helped me in cor-recting errors and improving presentations. I thank all of them. They are not responsiblefor any remaining errors. This paper is based on the research conducted jointly with GiorgioBrunello and Yasushi Ohkusa. We acknowledge financial support from Nihon Syoken SyogakuZaidan.

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1 IntroductionRecent empirical researches on job flows highlight the critical role of demandside disturbances in reallocating jobs across industries, firms, and occupations.Matching and reallocation of workers to jobs are intricately interwoven withthe process of creation and destructions of jobs. In spite of the obvious andparamount importance of the impact of demand side disturbances, the analysisof internal labor market has hardly paid any attention to it, due, perhaps,mainly to the lack of supporting empirical data1. We believe that the analysisof internal labor market should benefit from incorporating this facet of workermobility, in a manner that has become a standard in the analysis of externallabor market2.In this paper, we use unique data set taken from the personnel file of a

large Japanese manufacturing firms in order to explore the complex interactionsamong organization changes, job creation and destruction, and vertical andlateral transfer of employees. The data offers us an unique opportunity toinvestigate the relationship between lateral transfer, promotion, relocation ofworkplace, and firm re-organization.The observed relationships can be cast in a variety of theoretical perspec-

tives. First of all, the relation between lateral transfer and vertical promotioncan be analyzed as the processes of skill formation within a firm, especiallythose facilitating multi-skilling and its impact on productivity growth. Regu-lar job rotation is often cited as a standard practice of human resource man-agement (HRM) among Japanese firms and regarded as a principal means toachieve multi-skilling among employees. To the extent that such a lateral trans-fer is an integral part of HRM policy, mobility across sections and departmentswithin an establishment should be treated as a positive signal regarding the fu-ture prospect of promotion3. In a previous paper [Ariga, Brunello, and Ohkusa(1999)], we documented and demonstrated that the sample firm used in this andprevious papers does employ ‘fast track’ policy in the sense that the promotionprobability is higher for those who were promoted to the current position withinshorter period. It is of considerable interests to see if ‘fast track’ can be charac-terized by specific types of lateral transfers: i.e., to see if those on ‘ fast track’exhibit distinctive pattern of lateral transfer compared to the others. Relatedto this issue is a popular folklore among the Japanese workers that a transfer toa functionally different section is often a bad signal in that it reflects relativelypoor performance at the current job as evaluated by management. This line oflogic can be also cast in a framework of multi-skilling.

1Belzil (2000) is the only paper that I could find which incorporate job creation/destructiondata into microscopic analysis of internal labor market. He uses Swedish data on gross andnet job creations at establishment level in individual wage regressions.

2The standard reference is Davis, Haltiwanger and Schuh (1996). Davis and Haltiwanger(2000) contains rich international comparisons. Japanese data are explored in Genda (1998),and Higuchi(1998).

3Lateral transfers are analyzed in detail by Imada and Hirata (1994) using personnel datasimilar to ours, although they do not explicitly incorporate their findings in lateral transfersto vertical promotion. See also Matsushige (1995a,b) and Kusunoski and Numagami (1997).

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Another strand of issues stems from the literature on job creation and de-struction. In our data, we keep track of the deaths and births of the sections.Our record shows that this firm constantly slashes units with poor performanceand creates a large number of new units every year. Gross rate of job creationat section level in this firm is more than 30% per year. To the extent that jobcreations and destructions are the other side of the coins of employment andunemployment in the context of economy wide labor market, our data can beused as such corresponding to the internal labor market. We could ask a varietyof questions in this context. For example, do employees suffer from job destruc-tions within a section in the sense that their subsequent career is negativelyinfluenced by such events? We can look at the other side of the coin and ask:do employees fare better by being positioned in sections that grow faster in size?Devereux (2000) analyzes the impact of negative demand shocks on task assign-ments in the context of specific human capital model. He finds that the negativedemand shocks induce reallocation of workers to tasks that require less skillsin order to retain senior workers with larger amounts of specific human capital.This line of reasoning suggests that the workers with shallow tenure (and hencesmaller amount of specific human capital) are more likely to be transferred toaccommodate shifts in demand across different units of a firm.In Airga, Brunello and Ohkusa (1999) we found that the promotion patterns

differ significantly between two types of employees, i.e., between those whoare hired in regular hiring cycle and mostly new graduates from schools, andthose who are hired on ad hoc basis, mostly with workers with previous workexperience4. One reason behind the observed difference can be the extent inmulti-skilling. Those hired on ad hoc basis have previous work experience andthey are hired mainly for specific positions that need to be filled. Then wewould expect that such workers will experience less frequent transfers, acrossfunctionally different sections.In what follows, we will conduct a series of statistical analysis to see how

each of these predictions fares with our data. The sequel of the paper is or-ganized as follows. In the next section, we briefly review the recent literatureon internal labor market as it relates to the horizontal transfers and job de-struction/creations. Section 3 introduces the data and we provide a variety ofdescriptive statistics on lateral transfers and organizational changes. Section 4is the main body of the paper. First, we will focus on the multi-skilling and itsrelation to promotions. We find that transfers to neighboring units in terms ofprincipal function and department affiliation do indeed have positive impact onpromotion. On the other hand, transfers to functionally different units or thoseacross departments or divisions often have negative impact on promotion. Sec-ond, we also find that the impact on promotion varies across recruitment types

4The data file contains information on recruitment type for each employee. Most of newschool graduates are hired in regular recruitment cycle and the employment starts typicallyat April 1 of each year. Firms also post vacancies on ad hoc basis. Those recruited in this wayare typically not new graduates but tend to have some previous work experiences. Althoughnot perfect, we use recruitment type as an important measure to distinguish between thosewith prior work experience (irregular recruits) from those without (regular recruits)

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and seniority. Impacts are generally stronger for workers with shallow tenureand younger in age. We also estimate impacts of job creation and destructions.For some types of workers, we find significant positive impact of job destructionand creation. We will also provide some new evidence on exit behavior as itrelates to the mobility of workers within and across firms. A brief concludingremarks are given in section 5.

2 Matching Workers to Jobs within a Firm: ABrief Literature Review

2.1 Lateral Transfers

Surprisingly little is known about job matching and worker reallocations withina firm. There are two underlying reasons for this. First of all, transfers of thistype may not be important in certain types of firms. If a firm relies primarilyupon external recruitment to fill job vacancies, lateral transfers are rarely ob-served5. By the same token, it is hardly surprising that relatively large amountof empirical work are found in Japan, where lateral transfers are a very popularmeans to reallocate workers internally6.The more fundamental reason, however, is that none of the important the-

oretical approaches to internal labor market is well suited to analyze the phe-nomenon. Above all, horizontal transfers make little sense unless we explicitlyincorporate horizontal job heterogeneity within a firm. Most of theoreticalmodels incorporating heterogeneous jobs are concerned with vertical transfer,or promotions to fill vacancies at upper ranks. In this context, Demougin andSiow (1994) analyzes the choice over training within and external hiring to fillmanager’s position. They show in their model that either fast track, or, up-or-out rule emerges as the optimal policy of a firm, depending upon, amongother things, the firm size. In their model, lateral transfers arise as a meansto retain non-promotable employees within a firm: to transfer them away fromtrainee position. In essence, their model predicts lateral transfers as the resultsof failures of trainees to obtain skills needed for upper rank positions becausethe only difference among unskilled positions is whether or not each positioncan be used for training for the upper level position.A diagonally different view is advanced by Koike and others in industrial

relations [Koike(1988)] focusing on skill formations within firm. Lateral trans-fers and vertical promotions are combined to form a career ladder throughwhich each employee acquires different but related skills. Job rotation within ashopfloor among blue-collar workers is a common practice among large Japanese

5For example, Lazear’s voluminous book on personnel management [Lazear (1998)] has nosection or chapter on transfers (actually the book index has only one entry on ’transfer’ whichis parenthetically touched upon in the section dealing with internal promotion or externalrecruitment).

6Outside Japan, Seltzer and Merrett (2000) analyze a large set of personnel data of theUnion Bank of Australia. They find important link between lateral transfer and subsequentpromotion similar to our own discussion and many others regarding the role of lateral transfer.

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manufacturing firms. Employees within a section rotate their job responsibil-ity so that those within a rotation cycle are capable of performing multipletasks. Most of large Japanese firms routinely transfer employees to differentsections/departments7. Our sample firm is no exception and employees typi-cally experience transfers within two to three year period. The upshot of theargument is simple: lateral transfers are necessary ingredients for this type ofskill formation and hence viewed as positive signal on the productivity of indi-vidual employees8. Complications arise, however, because they simultaneouslyfind that not all the lateral transfers are considered as positive signals of learningcapacity of each employee. In particular, transfers to jobs which differ greatly inskill requirements can be detrimental to the career progression and those types,especially at higher age, are often regarded as a strong negative signal on thefuture trainability, and hence also on the promotion prospect of employees.9 .

2.2 Worker Mobility and Job Creations and Destructionswithin a Firm

One of the reasons often suggested for the relative ease10 at which Japanese firmsreshuffle their employees within each firm is their wage and promotion policy,which jointly guarantee that each employee retain her current (horizontal) rankirrespective of the job assignment. Such an argument suggests that not allthe lateral transfers are used primarily to foster multi-skilling, or to generatewhatever the desired impact on worker productivity by transfers. Instead, manysuch transfers are ’demand’ induced: to facilitate large swings in demand fordifferent types of skills across factories, departments, etc. within a firm. If thesystem of horizontal rank minimizes the uncertainty and anxiety on the sideof employees experiencing such transfers, Japanese firms find it less costly toundergo major organizational changes which would require major reallocationof workers.In spite of the safeguard, transfers induced by organizational change may

have different implications and consequences from those ’planned’ moves as astep within the long progression along the career ladder. Suppose that suchorganization changes are driven primarily by demand disturbances. Marginalproductivities of jobs across sections vary over time and the firm accommodatesthese shifts by reallocating workers. It would seem likely under the circum-stances that the impact of transfer on the skill formation of each employeewould be at least noisier than without such disturbances.First of all, many recent studies on displaced workers indicate significant

losses in earnings [Hall (1995), Topel (1990)]. To the extent that displacement7Even in those firms, transfers across divisions are not common except for major organi-

zation changes such as creation/destruction of divisions.8Transfers can be analyzed in the context of information and skill dissemination. Kusunoki

and Numagami (1997) argue that regular and frequent transfers between R&D and productionsections facilitate close and timely communications and information sharing.

9 See Kusunoki and Numagami (1997) and Matsushige (1995a).10The strongest evidence is by Hildreth and Ohtake (1998) wherein they find the high and

continuous rate of employment adjustment to demand shifts across major plants within a firm.

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from the current job at least partially destroy or diminish efficacy of humancapital, we expect significant negative impact from transfers induced by jobdestructions. The impact of displacement by job loss may well go beyond the lossin productivity at the current job if the newly assigned job after displacementis not a suitable one from the viewpoint of career progression. Therefore, thosetransfers induced by job destructions are likely to have negative impact oncurrent and the future productivity of transferred workers.Gibbons and Katz (1991), on the other hand, offers a somewhat different

implication of worker displacement. They compare workers seeking employmenteither after the job loss due to plant closure, as opposed to those due to layoffsand find that the wage loss is significantly larger for those laid off. They arguethat the adverse signal of those laid off is stronger in that they are selectedto leave their jobs as opposed to arguably exogenous job losses in the case ofcomplete plant closing. The implication for internal transfer would be that thedemand induced transfers are more detrimental if they are selective, as opposedto those due to complete shutdown of a unit.On the other hand, it is not entirely obvious what we should expect from

transfers induced by positive demand disturbances: i.e., transfers into sectionswith vacancies due to the expansion of their business. It seems plausible, how-ever, that the transfers into expanding sections will have more favorable impacton individual employees than transfers due to job destructions, for, many (mu-tually related) reasons. To begin with, productivity of an employee is likelyto be higher at growing sections. To the extent growing sections have moreopportunities to learn newer skills not easily available elsewhere, transfers intogrowing sections will enhance learning (by employees). Moreover, the selec-tion of employees into growing sections may itself reflect favorable evaluationby firms of employee ability. It is conceivable, however, that employees willsuffer from transfer to growing sections because of the high opportunity cost oftraining at sections whose productivity is higher. We know that trainings aregenerally counter-cyclical and also that firms invest more in training when theyhave excess labor.In sum, what we expect is that the overall impact of transfers induced by

demand shifts in either way are likely to have less favorable impact on theprospect of skill formation of transferred employees.

2.3 Lateral Transfers as Signals of Employer Learning

Although the models of employer learning are not meant to analyze transfersdirectly, it is still useful to consider the likely implications of the employerlearning when it is applied to incorporate job and worker heterogeneity. In itssimplest form, we can directly apply the original model of Jovanovic’s learningmodel by simply re-defining the job shopping process as those across jobs withina firm. Then, most of the statements regarding inter-firm mobility can beredefined as statements regarding intra-firm, across jobs, mobility. The followingproperties of across job mobility are immediate:

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(1) The mobility out of current job is declining function of the tenure at thecurrent job.(2) Expected productivity at current job conditional upon the available in-

formation is constant.(3) The expected value of outside option (other jobs within the firm) does

not depend upon either the current job or the information available.It is clear that the property (3) rests upon the independence of expected

productivity at ’other jobs’ from that at the current job. When applied to thejobs within the firm, it probably makes more sense to assume that the pro-ductivity across jobs of a worker are mutually correlated so that the expectedvalue of outside option is likely to depend positively upon the expected produc-tivity at the current job. This is tantamount to assuming that the reservationproductivity level is increasing over tenure.Farber and Gibbons (1996) made an important extension of the Jovanovic

model to investigate econometric implications of the employer learning model.The most important result is that the explanatory power in wage regressions ofinformation available to the employer from the beginning should stay constantover time whereas the explanatory power of a variable not available to employerbut to an econometrician should increase over time. Bauer and Haisken-DeNew(2001) test Faber-Gibbons hypothesis using the European data and find littlesupport for the hypothesis. Human capital model can be contrasted vis-a-visemployer learning model: conventional human capital model combined withthe positive impact of generic ability on the efficacy of training would indicatethe impact of formal education to actually increase over time. They interpretthe evidence in favor of human capital model as the more skilled workers aregiven better opportunity to advance further their skills, thereby magnifying theimpact of the initial (known) ability due to schooling.

3 Data and Preliminary Exploration

3.1 Sample Firm

We use the data from personnel files of a large manufacturing firm in Japan11,which we used in Ariga, Brunello and Ohkusa (1999). We refer to this paperfor the details of promotion data. This sample firm produces electric partsand products employing more than 10,000 at major plants and establishments.The firm is organized into 8 major production divisions and each division isdemarcated by its line of products. Table 1 shows the compositions of majordivisions and offices of this firm. This firm has many subsidiaries in and out ofJapan and has earned reputation internationally as one of the leading firms inthe field, especially in its unique technology and custom made products.11 See Ariga, Brunello and Ohkusa (1999, 2000) for the details. Chapter 5 of the latter

especially provide many descriptive statistics on promotion patters of this sample firm. Onecautionary note is that we have no data on individual wages.

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This firm is somewhat unique compared to other major manufacturing firmsin Japan. First of all, this firm grew rapidly in 1970’s and again in late 1980’s, arelatively newcomer, and as such, the firm retains relative flexibility. Especiallynoteworthy is its frequent reappraisal and creation and destructions of newunits within each division. The firm employs internal accounting system toevaluate profitability of each unit, and, the performance is constantly monitoredso that unprofitable units are destroyed and new units are created. Anothernotable characteristic of this firm is that a large portion of its core employeesare irregular recruits with significant previous job experiences. Although therelative share of irregular recruits declined in the most recent years, the shareamong existing employees is still large.

3.2 Personnel File

The personnel file that we use consists of four annual waves of employee recordscompiled in June of 1994, 1996, 1997, and 1998. In each wave, the recordcovers all the full time employees who are under direct control of the personneldepartment at the headquarter; i.e., those with rank 8 or higher and those hiredat the headquarter12 . Those who were originally hired at plant level and havenot advanced to rank 8 or above are not included in the data. The majorityof those excluded are blue collar production workers. Temporary employeesare also excluded. Also those excluded from the list are the board membersas they are not employees of the firm. In short, the data covers all the coreclerical, managerial and administrative stuffs, engineers and supervisors. Intotal, we have the record for 8762 individual employees. Each record includes thefollowing information: (1) current affiliation (section and establishment names),(2) current rank, (3) year entered firm, (4) recruitment type, (5) education, and(6) promotion records in terms of the rank.From the affiliation record, we can classify each employee according to (a)

geographical location of office or plant where he/she works, (b) division, depart-ment, and section affiliations13 . Based on (b) we can also identify the functioncharacteristics of each section. We used a generic functional code table andclassified each section into 47 (c) functional codes, which are in turn classifiedinto 11 major functional groups. The list of major functional groups and codesare shown in Table 2. These coded variables can be used to construct transferof each employee (a) across establishments, (b) across divisions, departments,or sections, and (c) across functions. Henceforth we call each type of trans-fer as (a) relocation across geographically different establishments, (b) transferacross sections/departments/divisions, and (c) job change across functionallydifferent units,. Needless to say, all the job change [(b)] entail transfer [(c)], but12Virtually all university graduates are hired at the headquarter, irrespective of actual

locations of their workplace. Most of blue collar jobs are posted and filled by respectivefactories.13 In this firm, most of establishments (factory or offices) contain units from more than

one departments and divisions. Hence, relocation can occur without transfer or job change.Similarly, transfer across departments or divisions can occur inside the same establishment.

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some transfers can occur without job change. Relocation [(a)] can occur withor without transfer [(b)] or job changes [(c)] and the opposite also holds.

3.3 Ranking system at a sample firm

The personnel data contains information on rank for each individual as of Juneeach year. 16 ranks are grouped into 5 major rank groups14 and each groupcorresponds somewhat loosely to the range of positions to which each employeeof a rank is assigned to. This type of ranking system is quite common and wide-spread among major Japanese firms and they form the basis of the allocation ofworkers to specific jobs. Although we refer to our previous work for the details ofsuch ranking system, we note here two important characteristics of the system.First of all, the rank is a generic measure of potential ability of each employeeat a firm. It is generic in the sense that the rank is attached to each individualrather than to a specific job or skill. Second, broad association between rankand position (such as the head of a section) stems from this property in thesense that the level of necessary skills, responsibility, and discretionary powerendowed upon specific position calls for workers whose general ability potentialis in the specific range. Similarly, base wage or salary is linked to rank, althoughother parts of total wage depend upon positions, hours worked, or on individualperformance evaluation.In line with the general understanding of this type of rank system, we assume

that each rank can be considered as a discrete approximation of the generalability of each individual as assessed by its employer.

3.4 Deaths and Births of Jobs

Table 3 summarizes the organizational changes as they relate to the deathsand births of the new positions. It is immediately clear that in each year ofthe observation, the firm undergoes substantial reshuffling of its organizationsand transfers of employees. During the four year period of our observation,the sample size of employees grew by 1,900, or 31%15. The total numberof existing units increased from 692 to 798, registering roughly 15% growth.The deaths and births of sections and jobs are much larger than the net change.During the period, this firm created 819 new sections and destroyed 712 sections.Similarly, the firm created 8599 new jobs and destroyed 6699 jobs. These jobcreations and destructions correspond to 54% of the gross job flow rate peryear. Moreover, most of job creations are due to creation of new sections: theyaccount for roughly 70% of total new jobs in each year. By the same token,section destructions account for the majority of jobs lost, again accounting for14 In terms of our rank variable, R, 5 major groups correspond, respectively, to: ranks 0-2,

3-6, 7-10, 11-13, and 14-16.15The change in total employment during the period is much smaller. The large increase

in the sample size reflect the increase in average age and tenure, as well as relative increasein the share of new recruits at the headquarter, in comparison with those hired at regionaloffices and factories.

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70% or more of job destructions. In spite of huge number of destructions andcreations of new sections, the divisional and departmental structures changedlittle. During the entire course of the four year period in our observation, thereis only one divisional level change, and, even this change was rescinded withina few months. We have no record of creations or destructions of departmentswithin each division.This sharp difference can be seen clearly by constructing similar statistics

of job creations and destructions within each division. Taking each divisionas a unit of measurement, the gross job creations and destructions are muchsmaller: The gross rate of job destructions ranges from 1.6% (1997/1998) to2.3% (1994/1996), whereas the creation rate ranges from 5.0% (1997/1998) to9.8% (1994/1996). These numbers are roughly comparable to the establishmentlevel study by Genda for Japanese firms [Genda (1998)]. To put it differently, acomparison with our section level data suggests that figures computed at estab-lishment levels musk much of the job flows taking place within establishmentsor divisions16 .Table 4 summarizes the division level destructions and creations of jobs,

using again each section as the unit of measurement. In spite of the smoothexpansion of the firm size during the period, we find substantial variations in thejob creations and destructions across divisions. Not surprisingly, the headquar-ter office remained relatively stable and exhibits the smallest gross job flow rate,about 17% per year. The divisions 6 and 7 produce relatively new product linesand division 8 is purchased through acquisition of an independent firm in themid-1980s. The first 5 divisions are the core of the firm. As we might expect,newer divisions have higher rate of GJFRs (Gross Job Flow Rates); 89%, and79%, respectively, in divisions 6 and 7. The GJFRs of main 5 divisions rangefrom 30 to 73% and the average is around 50%.

3.5 Transfers across Divisions and Functional Groups

In order to characterize relative size and directions of horizontal transfers amongfunctional groups and divisions, we use a conventional gravity model:

log(F ji ) = α1 log(Ni) + α2 log(Nj)−

Xij

βijZji

where F ji , Ni, Nj , and Z

ji are, respectively, number of transfers from unit i

to unit j, number of employees at respective units i, j, and the dummy variablefor each distinct combinations of (i, j). Then the estimated coefficients forthese dummy variables can be used as our measure of relative distances amongdifferent units within the firm.Figures 1and 2 show the estimated distance coefficients. In each figure,

the darker (lighter) cells represent small (large) coefficient value, i.e., shorter(longer) distance. In Figure 1, we used the functional group classifications and16We need to remind the readers again that the sample firm may be exceptional in terms

of creations and destructions of sections.

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classified each section into 11 functional groups (G1-G11) as indicated in Table2. In Figure 2, we used each division as the unit (Table 4).In Figure 1, we find that groups 6 to 11 have shorter distances (i.e., cells

are darker) overall than those for other groups. These are variety of functionalgroups directly related to production and R&D. Groups 1 to 5 are all clerical andadministrative functions and the figures show that the transfers are relativelysmall within as well as across these groups. Figure 1 allows the distance to differdepending upon the direction. We find that G9 (production) has large outflows(cells on row 9 are all dark) to virtually all the other functional groups whereasthe inflows are relatively small (cells on column 9 are lighter). To a lesser extent,group 3 (sales and sales representatives) has similar property, i.e., relativelysmall inflows but large outflows. To put it differently, many employees starttheir career with jobs in these functional groups; production lines for engineersand sales offices for white collars17.In Figure 2, we exhibit relative distances among divisions (See Table 1, panel

(2) and a footnote thereof). First thing we notice is that most of the off-diagonalcells are lighter (i.e., large distances). Each of the first 8 product divisions haveits own administrative units, thus, they are semi-autonomous. This explainsrelatively small inter-divisional transfers. There are exceptions, however. Wefind relatively large transfer flows between D1 and D2, and also between D6and D7. This makes sense because divisions 1 and 2 are the oldest ones ofthe firm and division 1 supplies the material to division 2. Divisions 6 and 7produce final products and division 6 is the offspring (about 15 years ago) ofa department in division 7. HQTR is the headquarter and LEAVE is not anactual division but all the employees on leave at affiliates and subsidiaries areclassified into this group. Not surprisingly, HQTR and LEAVE have relativelylarge flows with the rest of divisions. It is also interesting to note that thedivision 6, the fastest growing one also with the largest GJFR, has relativelylarge inflows (column 6 is darker) but the outflows are smaller (row 6 is lighter).Figure 2 also shows that inflows into division R&DS (column10) is very small.This reflects the fact that the firm gradually dissolved firm wide R&D centersand relocated researchers back into R&D units within each division.

3.6 Relocation, Transfer and Job Changes

Table 5 offers the broad picture of lateral changes (transfers) from the viewpointof individual employees at our sample firm. The first thing we notice is the sheermagnitude of the changes. Even in the case of transfer across divisions, annualfrequency is larger than 10%. Equally surprising is the high frequency of jobchanges, ranging between 15 and 20% per year18. Figures 3 through 6 showsfrequencies of various types of transfers across age and rank.17See Kusunoki, K. and T. Numagami (1997) and Matushige (1995a,b) for similar findings.18On the other hand, these figures are not inconsistent with the conventional wisdom that

employees are transferred on regular and periodic manner, typically every 3 to 5 years, atlarge Japanese firms.

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The difference between the recruitment type is consistent with the fact thatthe irregular recruits are hired for specific positions and most of them haveprevious job experiences. Although the difference is not large, it suggests thatthe scope of intra- firm movements are somewhat limited for irregular employees.To the extent that the transfer across jobs are used to train employees for a widerspectrum of skills, we might expect that the mobility will diminish as employeeaccumulate experience and specialize.This is indeed the case as can be seen clearly from Figures 3 and 4 showing

average transfer frequencies across age. All types of lateral transfers declineover age [and also over experiences (tenure), not shown]. On the other hand,the frequency of lateral transfers do not decline monotonically over ranks, asshown in Figures 5 and 6. There is general tendency that transfers are U-shapedacross ranks.This can be understood as one way to facilitate skill formation over a long

career. At shallow tenure, employees are primarily moved within neighboringunits in which they accumulate closely related skills. As they climb up thepromotion ladder, they will be transferred to more functionally different sec-tions, especially, - we suspect-, when they are promoted to managerial leveljobs. Monotonic decline in transfer frequency over age or tenure, in conjunc-tion with U-shaped transfer frequency across ranks, suggest that beyond certainage/tenure/rank, the transfers are largely limited to those at senior managerialpositions. In this second phase of the transfers, we therefore suspect that thetransfer is based more upon general managerial/administrative capability, thanskill based expertise and know-hows specific to individual sections or functions.In other words, transfers at early stage of career tend to be more skill-based,whereas those at later career is based more on managerial ability, and, per-haps, more demand oriented. Note that this characterization is consistent withour observations that within each department or division, section transfers arefar more common at among the younger cohorts, whereas the divisional anddepartmental transfers are relatively more common at senior levels.

3.7 Prototype Careers

It is often alleged that at large Japanese firms, certain type of career progressionis considered as the norm against which one can evaluate individual’s career andinfer the future prospect. Table 6 summarizes relative frequencies of varioustypes of transfers across groups. Regular recruits seem in general to experiencemore transfers to neighboring sections and less of those across departments ordivisions. They also are less likely to experience relocations. Notice that thesecharacteristics are shared by university graduates.In the previous paper, we found out the significant fast track effect exists

in this firm: i.e., those advancing in shorter period to a current rank will beon average expected to be promoted further from the current rank in a shorterperiod. To see if such effect manifests itself in some of the characteristics of lat-eral transfers, we picked up ’fast flyers’(Fast Pr .) and ’slow movers’ (Slow Pr .)and compare their records. Specifically, we selected 357 fast flyers, and similarly

12

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446 slow movers based upon the promotion records up to 1994. Table 6 showsthat the fast flyers tend to move less often across divisions or establishments,whereas slow movers experience more frequently transfers across departments,divisions and establishments. They also tend to experience relocation morefrequently. These characteristics are again consistent with the popular percep-tion that transfers across functionally different units or relocations are not goodsignal to the employees.If the transfer to a different section within a department is a norm from

the viewpoint of career ladder, these findings suggest that regular recruits, ’fastflyers’, and university graduates are relatively immune to irregular transfersinduced by relative demand shifts across departments and divisions. Across ageand tenure, we find, as we indicated already, that younger workers with shallowtenure tend to move more often. This tendency is most consistent for sectionchange, whereas for other types of transfers, we find important exceptions tothis rule. For example, group of employees with tenure between 5 to 9 years areless likely to experience these types of transfers than the average, and frequencyof functional transfers is higher than the average for employees with 30-34 yearsof tenure. These can be confirmed also in Figures 3 through 6. Although mostof transfer frequencies are by and large smaller for older employees, we tend tofind that these frequencies across ranks are U shaped, i.e., employees with lowand high ranks tend to move more often than the middle ranked.Although we do not show in Figures, we also find that employees with lower

ranks are substantially more likely to be transferred to newly created sections.This perhaps reflects the firm’s policy to mobilize relatively younger employeesto start-up new projects. Unlike frequencies of other types of transfers, we alsonotice that transfers generated by section destructions are more likely amongirregular recruits at senior ranks. Although the underlying factor responsible forthis pattern is not immediately clear, it seems to indicate at least that careersof senior irregular recruits are more hazardous in the sense that their units aremore vulnerable to restructuring.

3.8 A Brief Summary

In this section, we reviewed the records of lateral transfers and organizationchanges of a large Japanese firm. We find that most of lateral transfers and jobcreations and destructions occur at the section level. Once we aggregate to divi-sion level, most of these changes are masked and disappear. We also found thatmuch of lateral transfers are induced by job creations and destructions. Thisis in sharp contrast to the prototypical image of such transfers as being supplyoriented to foster skill formation along the pre-determined promotion ladder.Although this observation does not imply that firms ignore the impact of eachtransfer on the subsequent skill formation of individual employees, it is fair tosay that the magnitude and timing of lateral transfers are often dictated by thefluctuations in internal labor demand. Nevertheless, correlations between inci-dence of transfers and worker characteristics lend some support to conventionalviews on the role of horizontal transfers in large Japanese firms. In particular,

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the evidence is consistent with the view that such transfers facilitate skill for-mation of broader job categories (multi-skilling). In a sense, multi-skilling andthe large flows of demand induced transfers are complementary to each other.On one hand, multi-skilling facilitates large and swift flows of lateral transfersto meet changing labor demand at different units within the firm. On the otherhand, these lateral transfers in turn provides the opportunities for employees tolearn related but different set of skills as they mover from one section to theother.To put it differently, paths along promotion ladder at this firm are filled with

surprises. Multi-skilling is a cumulative consequence of random paths taken byindividual employees.

4 Econometric Analysis of Lateral and VerticalMobility

In this section, we analyze the personnel file and estimate a model for promo-tion probability. Much of what follows takes our previous analysis in Ariga,Brunello and Ohkusa (1998) as the starting point. In this paper we add infor-mation on lateral transfers and we introduce a set of new variables to representthis facet of worker mobility. First, we consider the impact of lateral transferper se and consider the impact in the context of multi-skilling. The next stepis to introduce the impact of organization changes, in particular, job destruc-tions and creations due to scrap and build of production units. Finally, we alsoincorporate the impact of worker mobility across firms. As is well known, sepa-rations induce selectivity bias in the regression unless the process of separationis econometrically exogenous to the process in which promotions are generated.

4.1 An Econometric Model of Promotion and Transfer

As we indicated above, we treat rank variable as a discrete approximation of theestimate of worker productivity conditional upon the set of available informationfor the employer. This interpretation suggests a straightforward model not onlyof human capital accumulation but also of employer learning on the productivityof each employee. To begin, we assume that the current rank for an employeei, Ri

t,is defined as follows:

Rit = r, iff Q

r ≤ E(Qit) < Q

r+1, r = 1, 2, ...16

where Qit is productivity of an employee i, and is a latent variable, and Q

r isthe lower threshold productivity level for rank r. For simplicity, we assume Qi

t

is non-decreasing over time19. Promotion is treated as an outcome reflecting re-appraisal and updating of individual productivity based upon the performanceof each worker.19We ignore the possibilities of demotions of any kind and also promotions for more than

one ranks within a year (we have no observation for either case).

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PRrt = 1 iff ∆Qi

t ≥ ∆r

PRrt = 0 iff ∆Qi

t < ∆r

We posit the growth of productivity is given by

∆Qit = g(Z

it ,D

it)

wherein Zit represents vector of person specific variables that explains the

growth of human capital. We assume that the actual growth is influenced alsoby the set of variables, Di

t, representing the allocation of employees to specificjobs. We can think of two different interpretations of Di

t. These variables canbe regarded as the record of matching processes within the firm a la Jovanovic.According to this interpretation, any job change has non-negative impact onproductivity growth ,but, under mild regularity conditions, we also expect thatthe positive impact will be decreasing over tenure as the employee will be as-signed to near-best matched job after many years of job shopping process. Thisinterpretation also suggests that the impact of Di

t can be separated out fromthose by Zi

t as far as both are included in the information set of employer andemployees.According to multi-skilling interpretation, Di

t represents the effects of jobassignments on skill formation. In section 2, we reviewed the relevant literatureand we noted several times that the transfers can arise for two reasons. Firstof all, transfers are used to facilitate skill formation of individual employees.As such, they are planned and largely along the line of long term career path.Our analysis in the preceding sections also suggest that transfers occur as thefirm find it necessary to reshuffle its employees across units, establishments andfunctional groups to accommodate changing labor demands at different unitswithin a firm.Our next task in this section is, therefore, to find proxy variables represent-

ing these two underlying factors for transfers. Although not perfect, we use thefollowing measure as useful to distinguish ’planned’ transfers along the promo-tion ladder from those arising from demand disturbances: denote by i(k) the setof employees who are transferred to section k at time t. The transfer is definedas ’planned’ if and only if the number of employees at section k (nk

t ) remainunchanged between (t− 1) and t.

PLANNEDi(k)t = 1 iff nk

t = nkt−1

The record shows only 486 such ’planned’ transfers, out of 14,267 transfers.As we indicated above, we classify lateral transfers into the following four types:SECCi

t , DEPCit , DIV C

it , FCC

it , and LCC

it . They are respectively, transfers

to: a different section within the same department, a section in a differentdepartment within the same division, a section in a different division, a func-tionally different section, and a section located in a (geographically) differentestablishment.

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On the demand side variables, the most obvious are transfers out of destruc-ted sections and transfers into newly created sections as they clearly reflectsthe organization changes which need to be accommodate by employee transfers.Formally, then we define:

DESTRUCTki

t−1

t = 1 iff nki

t−1

t−1 > 0 and nki

t−1

t = 0

, where kit−1 is the index of the section to which individual i belonged at

(t−1) and the condition indicates that the section was destructed between (t−1)and t. Similarly, section creation variable is defined as:

CREATEki

tt = 1 iff n

kit−1

t−1 = 0 and nki

tt > 0

To represent the general influence of the demand shifts20, we use employ-ment growth and gross job flow rates at departmental and divisional level;GROWTH

p(d)t , GJFR

p(d)t .

4.2 Base Results

The model that we estimate is

PRit =

Xj

βjZijt +

Xm

βmDkitm + ui

t

Zit = {ranki

t−1, years_at_rankit−1, years_edu

i, regulari}Dki

t = {SECCit ,DEPC

it ,DIV C

it , FCC

it , LCC

it ;PLANNED

i(k),

DESTRUCTki

t−1, CREATEki

t , GROWTHd,p(k)t , GJFR

d,p(k)t }

wherein variables in Zit , viz, rank

it−1, years_at_rank

it−1, years_edu

i,and regulari

are, respectively, rank dummies, number of years spent at the current rank,years of education, and a dummy variable for regular recruits. Table 7 reportssummary statistics for the major variables used in regressions reported below.We first estimate the model including transfers variables only among Dki

t [firstfive variables in Dki

t ] using clogit and probit models. The result shown in Ta-ble 8 generally support the thesis that transfers, especially those amenable tofostering a variety of skills have positive impact on promotion probability. On20The impact of demand shifts may not be confined to those sections immediately influ-

enced by re-organization or reshuffling. For example, consider a section from which manyof employees are pulled out to a newly created section. Unless the section had some slackworkforce, this section needs to replenish its members. The chain of induced transfers couldcontinue many rounds and there is no clear-cut way to define which of the transfers are de-mand induced and others supply induced. Our selection of GROW T H

p(d)t , GJF R

p(d)t is a

compromise between this inherent difficulty and the need to distinguish demand induced andsupply oriented transfers

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the other hand, transfers involving functional change or geographical reloca-tion of workplace per se have negative impact, although some of the estimatedcoefficients are not statistically significant.Table 8 also displays the estimates of the base model separately for regular

and irregular recruits. The result indicates that the recruitment type mattersgreatly. Specifically, we find that the strong positive impact of SEC applies onlyto the regular recruits (for irregular recruits the coefficient is positive in clogitbut not significant, and it is negative in probit). This again suggests systematicdifference in the way lateral transfers are used for two types of workers. Forregular recruits, our finding is consistent with the conventional view that lateraltransfers to closely related sections are used to facilitate multi-skilling. We findno such evidence for irregular recruits. Interestingly, the impact of FCC, trans-fers to functionally different sections, has the opposite impacts for two typesand both coefficients are significant. For regular recruits, the negative impactis consistent with the view that transfers into functionally distinct sections aredetrimental to employees’ career in that the newly assigned positions are notwell suited for their accumulated skills. For irregular recruits, the impact ismostly insignificant and some times positive. The results in Table 8 for theestimated impact of LCC (location change) are similar to those of FCC. Theimpact on regular recruits are negative and often significant whereas those onirregular recruits are mixed in signs and all insignificant. We come back to thispuzzling results later in this section21.

4.3 The Impact of Job destructions on Promotion

One valuable information available in our data is destructions and creationsof new jobs. According to company’s stated policy, individual sections are con-stantly monitored and their performances are evaluated using accounting profitsof individual sections. Moreover, it is also a part of the stated policy that eachsection is given substantial decision making power including ’recruiting’ outsideemployees. To the extent that individual sections are given such discretionaryand decision making power, we would expect that the destruction of sectionsshould have significant negative impact on promotions of those in destructedsections.Table 9 shows the estimated conditional logit model which incorporate the

impact of job destructions, creations together with the impact of planned trans-fers on promotion prospect. The results are rather surprising. Whereas we findpositive impact of section destruction variable, the impact of PLANNED isnegative and marginally significant. In probit model, we find that transfers into21When we replace SEC by DEP i

t or DIV it ,results (not shown) are qualitatively similar

except that the positive impact of transfer is often not significant even for regular employees.Since majority of employees in our sample are engineers or engineering background, we expectthat tasks may be highly product specific. Therefore transfers to even functionally equivalentsections in a different department or a division may well involve important changes in the setof tasks. Over all our econometric results show that the only transfers to functionally similarunits have consistently positive impacts on promotion.

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newly created section have significant positive impact on promotion, whereasthe impact of section destruction is insignificant and negative22 .These results are mixed and it is highly speculative to make any definitive

statements. It seems fair, however, to say that results do not support the thesisthat only perfectly planned transfers facilitates multi-skilling, nor the one thatdemand induced transfers are detrimental to future promotion prospect. Theseresults are surprising at least for two reasons. First of all, as we noted in theprevious section, many pieces of anecdotal evidence suggest existence of a welldefined and largely determined course of career progression such that thosepromoted fast tend to advance along such paths. The results in Table 9 seem toindicate instead that demand driven section level transfers actually may havesome additional positive impact on promotion23. Secondly, we reviewed theevidence regarding negative impacts on wage by inter-firm mobility induced bylayoffs or plant closings. Our results indicate that the analogy from inter-firmmobility does not apply to intra-firm mobility.

4.4 Differential Impacts of Transfers across Tenure

In Table 10, we show the estimated coefficients for SECC,FCC,and LCC onlywhen we run the base model regression with split samples across tenure groups.Here we detect the following patterns. We find that the positive impact ofSECC is limited to lower to middle tenure groups and the impact becomeseither insignificant or negative for groups with longer tenure (say, above 15years). The impact of FCC, on the other hand, exhibits a different pattern.In this case, the impact is mostly negative and significant for regular employeeswith less than 15 years of tenure, then turns positive for the more experiencedbut the coefficients are mostly insignificant. For irregular employees, we also findthat the impact is negative for very shallow tenure but then turns positive andthey are mostly significant. The pattern is largely the same for LCC (locationchange). They tend to have negative impact at shallow tenure, especially for22Suppose, for the sake of argument that clogit model gives us unbiased estimates, whereas

estimates in probit model are biased due to the correlation of RHSs with error term. Thenthese results indicates upward bias in section destruction and downward bias in section cre-ation. An interpretation of the results along this line of reasoning runs as follows. Transfer outof destructed sections per se have positive impact on promotion but those with lower level ofunobserved ability are more likely to experience section destructions. For transfers into newlycreated sections, diagonally different results: such transfers per se do not have strong impacton promotion, whereas those transferred to these sections are on average higher ability work-ers and better promotion prospect. Along these lines, the estimated coefficients for plannedtransfers indicate that the impact is negative but those transferred in this manner tend tohave higher unobserved ability. Needless to say, these observations are highly speculative,especially given the large differences in sample size between the two estimations.23One referee commented on the finding, saying that perhaps sections destructed or created

tend to be smaller in size and that this section size effect may be responsible for the results. Wealso ran regressions [not shown] including size of the current, as well as the previous sectionsto which employees belong. The estimated coefficients on section size is mostly insignificantand no systematic pattern could be detected. More importantly, the results regarding theimpacts of section destruction or creation remain qualitatively unaffected by inclusion of thesevariables.

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regular workers, but become positive for employees with longer tenure and oftensignificant for irregular employees.These results are consistent with the interpretation that the transfers are

indeed used to facilitate skill formation along promotion ladder. Moreover, thedifferential impacts of FCC and LCC suggest that systematic differences inpromotion decision across tenure and recruitment types. The declining positiveimpact of section level transfer over tenure suggests that advancement of jobspecific skills play the key role mainly in earlier stage of promotion and transferdecision. Therefore, transfers involving function changes or relocation at thisstage are often detrimental to career advancement. At later stage of career,the emphasis perhaps shifts from job specific skill formation to more generaladministrative and managerial capability24. Hence the impact of FCC andLCC turns positive, especially for irregular recruits.Our interpretation of the results is consistent also with the difference across

recruitment types. We noted above that the positive impact of SECC at shallowtenure is more robust and often significant for regular recruits than the irregu-lars, whereas the positive impact by FCC or LCC at later stage is stronger forirregular recruits. This difference reflects the fact that irregular recruits haveprevious work experience and they are often hired for specific job vacancies. Asa matter of fact, many of them often hired at middle rank levels (rank 4 to 8).Hence the need for job specific skill formation is not nearly as important forthese workers as they are for regular recruits. On the other hand, for career ad-vancement beyond certain level, they need to have wider experiences within thefirm which they tend to lack compared to the regular recruits. This is reflectedin the stronger positive impact of FCC and LCC at later stage of career.

4.5 Impact of Division and Department Level Growth andJob Creations

Many practitioner of HRM at large Japanese firms voiced concern on the impactof success and failure of organization units on the career of individual employees.The concern is that those in more successful and growing divisions are givenbetter opportunity to make full use of own potential and thus more likely tobe noticed and hence promoted. This tends to create bias in favor of those inmore successful division in personnel evaluation. In order to incorporate thepossible impact of the division level and department growth in employmentsize, we used the year to year employment growth rate of division to which eachindividual belonged in the previous year. The result (not shown) indicates thatindeed the probability of promotion is significantly higher for employees in fastergrowing divisions. When the impact is separately estimated for age groups, wefind in this case that the impact is stronger for older employees, whereas thepoint estimate for younger cohort is actually slightly negative (not statisticallysignificant). The gross job flow variable also has positive impact on promotion24Recall discussions in 3.6 wherein we noted U-shaped frequency of transfers across rank,

but not across age or tenure.

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either at division or department levels.Putting these pieces of findings together, we conclude that horizontal trans-

fers need not be perfectly planned move in order to contribute to the long termcareer advancements. Instead, as we saw in section 3, most of transfers areinduced by the job creations and destructions at section level. One possibleexplanation is that divisions or departments with higher job turnovers or highergrowth can provide constantly new tasks and jobs in which transferred employ-ees are given better opportunity to learn new but related skills.

4.6 Separations and Selectivity Biases

As is well known, the data taken from personnel files of individual firms gener-ally suffer from the selectivity problems. Among others, typically, the data isavailable only for existing employees and we have relatively little informationon those who already have left the firm at the time of observation. Since ourdata is based upon four annual waves of observations, we can partially rectifythe situation by explicitly incorporating the selectivity bias arising from sepa-rations. We can identify separations by comparing the list of employees in thedata for each year (1994, 1996, 1997 and 1998). Since the data retains individualemployees in the list as far as they are employed at the parent or related firms(syukko), we can assume that those disappearing from the list must have beenseparated permanently.25 As of 1998 (the last year of observation in our data),this firm had mandatory retirement of age 60. From these pieces of informa-tion, we singled out those separated before the mandatory retirement age. Ourrecords show 3,495 (roughly 2% per year) separations not due to mandatoryretirement.In order to correct for the selectivity bias, we first estimate simple probit

model for separation behavior (actually the model estimates the determinantsof ’stay’ decision). The result is shown in the lower panel of Table 11. The mostnotable finding here is the negative (but not statistically) significant impact offast flyer and positive impact of slow movers on ’stay’ propensity. These resultsare especially surprising in view of the fact that the promotion probability isindeed significantly higher for fast flyer and lower for slow movers. We alsonotice that the foreign variable has strong negative influence on stay decisionas the variable indicates employees stationed in foreign subsidiaries or branches.One possible interpretation is along the lines suggested by Lazear(2001). Ifthose who are promoted faster have been ’lucky’, i.e., having received favorableshocks to his productivity, then the post promotion performance tend to belower than those who had to wait longer for promotion. It is possible in that25One anonymous referee commented, however, that some of separations might be actually

promotions to executives (board members). Although we cannot completely rule out thispossibility, we collected all the apparent separations from the highest rank and asked themanagement to identify those who became board members. They refused to identify individ-uals but told us only 2 among the employees joined the board during the period covered inthe data. We also confirmed through interview of the management of the firm that duringthe years covered in the data, they did not employ a policy of tenseki-syukko, i.e., transfer ofemployees at parent firm permanently to subsidiary or related firms.

20

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case that those fast flyers may quit the firm as they are not given rewardingjobs that they anticipated when they were promoted.In any case, the results for promotion shown in upper panel of Table 11

incorporate and correct for the selectivity bias due to the decision to stay beingendogenous. The quantitative results on promotion probability remain, how-ever, unaffected by separation behavior as far as our main interest lies in thepromotion determinants.

5 ConclusionIn this paper, we offered what we believe as the first quantitative empiricalanalysis of the interactions between job flows and worker mobility inside a largeJapanese firm. The picture that emerges from the analysis suggests an impor-tant role of organizational changes in shaping the individual career over timewithin an organization. In particular, we find that the impact of the successand failure of the unit that each employee belongs have important impact onthe subsequent promotion prospect. This can be seen in two distinct but notnecessarily mutually exclusive perspectives. First of all, the impact can be seensimply as reflecting the policy that base promotions upon performance. Thisview is certainly consistent with the empirical results in this paper, although itis not clear how individual performances and the fate of organization units isrelated. A more simplistic view is that the result mirrors the better opportunityto advance career if one is assigned to growing business units, be it a section, de-partment, or a division. Our results do not offer any conclusive evidence to favorone over the other. We found, however, that the impact of section destructionis quantitatively more important and statistically significant for workers withlonger tenure, older age and higher rank. This result is not consistent with aview that the information generated by lateral transfers can be interpreted assignals on time invariant and unknown ability of each employee.We have shown that not all mobility within a firm is a good signal. Transfer

across offices in different locations by and itself has often significantly negativeimpact on future promotion for younger employees. Our reading of this result isthat the firm uses relocation as a device to reshuffle slack labor force, especiallywhen workers are relocated to functionally similar but geographically differentunits. Similarly, transfers to functionally different sections tend to have negativeimpact on promotion.Several due cautions are in order before closing. First of all, it should be

noted again that thesample firm may be highly special even among the largeJapanese firms, especially in terms of exceptionally high rate of job creationsand destructions. We know also that the firm employs highly profit oriented’scrap and build’ policy: the performance of each production unit is measuredand evaluated by internal rate of profit and the firm slashes and builds suchsections constantly. This is rather unique to the sample firm and we suspectthat the strong impact of job destructions on individual promotion probabilitywe found may well be something also unique to this firm. The literature should

21

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benefit from this type of studies using more diverse sample firms. Due to thenature of the data, our regression analysis contain several potential sources ofthe bias. Among other things, our data does not cover those employees of thesample firm who have left the firm at the point of the observation.Although we should be extremely cautious in drawing any general conclu-

sion from this type of study, one clear message that emerge from our study isthat worker mobility and organizational changes within a firm are intricatelyinterwoven. In the literature of internal labor market, it is commonly assumedthat individual workers are matched to a job chosen from the set of exogenouslygiven list of vacancies. Our study indicates, however, that jobs themselves arealso closely monitored and constantly evaluated and they often disappear orcreated, in no small part, due to the performance of individual workers whooccupy those positions. In short, the internal labor market is far more dynamicand evolutionary than some of theoretical models characterize.

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[22] Lazear, E. (2001), ’ The Peter Principle: Promotions and Declining Pro-ductivity,’ NBER Discussion Paper 8094

[23] Matsushige, T. (1995a), Kako Kumitate gata Sangyo ni okeru BunkeiDaisotsu howaito cara no Ido to Shoshin, JIL, n.68, Nihon Rodo KenkyuKiko.

[24] Matsushige, T. (1995b), Denki B-sha no Daisotsu Danshi Jyugyo-in noKinzoku 10-nen made no Idou to Sonogono Shoushin, in T. Tachibanaki(ed.) Shoushin no Keizaigaku, Tokyo, Toyo Keizai.

23

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[25] Meyer, M. (1991), Learning from Coarse Information: Biased Contests andCareer Profiles, The Review of Economic Studies, 58, 15-41.

[26] Prendergast,C. (1996), What Happens within Firms? A Survey of Empir-ical Evidence on Compensation Policies, NBER Working Paper no.5802.

[27] Seltzer, A. and Merrett (2000), ’Personnel Policies at the Union Bank ofAustralia: Evidence from the 1888-1900 Entry Cohorts,’ Journal of LaborEconomics, 18(4), 573-609

24

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7 TablesTable 1 Organization of Sample Firm

Panel (1) List of establishmentstypes Number of EstablishmentsMajor offices 8Factories 11Regional Sales Offices 31

Panel (2) Number of Sample Employees in Divisions and Headquarter Offices26

Code Divisions 1994 1996 1997 1998 1998/94D1 Division 1 717 836 914 1007 1.40D2 Division 2 905 966 1086 1158 1.28D3 Division 3 579 660 697 799 1.38D4 Division 4 365 400 412 458 1.26D5 Division 5 539 538 543 624 1.16D6 Division 6 300 554 732 755 2.52D7 Division 7 309 337 231 239 0.78D8 Division 8a 321 317 303 269 0.84D9 Departmentsb 242 276 294 294 1.21D10 R&D Centers 201 93 83 81 0.40D11 Headquarter 625 610 613 661 1.06D12 On Leavec 539 565 555 556 1.03- Unknown Affiliation 460 727 912 1280 -

26note: a: The division was purchased from independent firm in early 1980’s,.b: productiondepartments under direct control of headquarter. c:Employees at affiliate firms in and outsideJapan

25

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Table 2 Functional Groups Used in the DataFunctional Group % share Hazard Rate # of Sub Gs.G1 General Administration 4.8 10.7 16G2 Planning, 2.6 21.0 7G3 Sales 13.8 9.9 5G4 Procurement/Logistics 4.3 24.4 7G5 Overseas Operation 7.1 24.0 3G6 R&D 13.4 23.6 1G7 R&D administration 14.5 21.7 1G8 Product Development 2.4 30.1 4G9 Production Operation 25.2 13.0 1G10 Quality Control 5.1 22.5 1G11 Production Design/Control 6.9 21.2 2

26

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Table 3 Summary Statistics of Job Destructions and Creations1994 1996 1997 1998

Employee in the sample 6121 6855 7418 8021Sections 692 705 718 798New sections - 341 189 289Sections destroyed - 328 176 208Net new sections - 13 13 81New jobs - 3518 2157 2924- due to new sections - 2594 1445 2116Lost jobs - 2784 1594 2321- due to sections lost - 2124 1171 1612

Table 4 Job Creations and Destructions at 12 Divisions27

Jobs Created / Destructed per year

GJFR rate∗ Creation Destruction

total seccr1 total secdestr2

Division 1 .30 167 67 92 58

Division 2 .59 331 242 275 212

Division 3 .50 194 147 116 90

Division 4 .58 130 91 128 83

Division 5 .73 213 173 194 148

Division 6 .89 313 248 204 168

Division 7 .79 101 84 115 76

Division 81 .55 72 56 91 74

Departments2 .54 75 50 70 53

R&D Centers .56 51 43 17 13

Headquarter .17 56 18 49 27

On Leave .39 120 97 112 90

27Note: GJFR is 1996-1998 average gross job flow rate computed as (jobs created +jobsdestructed)/existing jobs, 1: job creations due to section creations, 2: job destructions due tosection destructions

27

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Table 5 Summary Statistics on Lateral TransfersAcross 1996/94 1997/96 1998/97

Relocation Establishments .28 .25 .20Job Change Functions .34 .16 .19

Transfer Divisions .21 .10 .11Departments .24 .11 .15Sections .54 .29 .37

Table 6 Differences across Groups in the Incidence of Transfers28

Transfers acrossGroup Section Dept. Division Function LocationRegular >∗ ' < ' <

University > ' < ' <

Fast Pr. '∗∗ ' < ' <

Slow Pr. ' > > > >

Rank Gr.1 > > > > >

Rank Gr.2 > > > > >

Rank Gr.3 < < < < <

Rank Gr.4 < ' < ' <

Rank Gr.5 > ' > ' '

28 *>(<) indicates that the group has significantly higher (lower) incidence compared tothe rest, at 1% significance level in chi − square statistic For example, the table shows thatregular recruits are significantly more likely to have section changes than irregular recruits.**' indicates that the difference is not statistically significant at 1% level.

28

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Table 6 (Continued)

Transfers acrossTenure Section Dept. Division Location Function<5 years >∗ > > > >

5-9 ' < < < <

10-14 ' > > > >

15-19 ' ' ' ' '20-24. < < < < <

25-29. < < < < <

30-34 < < < ' >

35-39 < ' < < <

40- < < < < <

Transfers acrossAge Section Dept. Division Location Function<20 >∗ > > > >

20-24 > ' ' ' '25-29 ' ' > > '30-34 ' < ' ' <

35-39. < < < < <

40-44. < < < < <

45-49 < ' < < '50-54 < < < < <

55- < < < < <

29

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Table 7 Summary Statistics

Variable Variable Name # Sample Mean S D. Min. Max.Education (Yrs.) schooling 43810 13.09 3.73 6 21Age age 43810 38.29 9.17 20 60Tenure tenure 41404 13.22 8.43 0 44Years at Rank tenure_at_rank 39662 1.65 2.48 0 30Regular Recruits regular 43810 .55 .50 0 1Separation quit 43810 .079 .27 0 1Fast Flyer fast_flyer 21160 .084 .28 0 1Slow Mover slow_mover 21160 .106 .31 0 1Section Change SECC 24782 .421 .49 0 1Department Change DEPC 24782 .264 .44 0 1Division Change DIV C 24565 .219 .41 0 1Function group Change FCC 24565 .300 .46 0 1Location Change LCC 24782 .240 .43 0 1Planned transfer Planned 26286 .069 .25 0 1Transfer into new section create 22429 .253 .43 0 1Transfer from destructed section destruct 20350 .221 .41 0 1Promotion PR 38600 .381 .49 0 1Division employment growth division_growth 24044 .022 .096 -.369 .306Average GJFR of each division division_GJFR 19510 .640 .37 .094 1.86Section Size s_size 30960 35.03 42.81 1 116

30

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Table 8 Base Model of Promotion29

Regression # (1) Whole Sample (2) Regular Recruits (3) Irregular Recruits

Estimation Method c-logit probit c-logit probit c-logit probit

age -2.460*** -.0318*** -2.482*** -.0414*** -2.269*** -.0205***

years_at_rank 4.641*** .172*** 3.796*** .327*** 5.359*** .0809***

years_at_rank2 .587*** -.0180** 1.292*** -.0427*** .202* -.00732*

section_change .321** .0129 .322** .00130 .434 -.0254

location_change -.114 -.0237** -.131 -.0293** .0311 -.0182

function_change -.535*** -.0253** -.688*** -.0498*** .0528 -.00595

schooling - -.0465*** - -.0305* - -.00905

schooling2 - .00215*** - .00188** - -.00119

regular - .127*** - - - -

Pseudo R2 .8253 .2355 .7923 .2547 .8983 .01216

# of Observations 11494 19217 7465 11233 4029 7984

29 In Table 8 through 11, we used the following conventions. (1) c-logit : conditional logitmodel incorporating fixed effects. In this type of regressions, sample individuals with all PR=1(positive) or 0 outcomes are dropped. (2) d-probit : probit model results. The coefficientsshown are normalized to indicate the change in the probability for an infinitesimal change ineach independent and continuous variable, and those corresponding to a discrete change forthe dummy variables.(3) All the regressions include 3 rank group dummy variables ( out of 5rank group, the highest 2 have small samples and we merged these two to avoid collinearity),two year dummy for 1996 and 1997. (4) The coefficients with *** indicate 1% significance (**for 5% and * for 10%).

31

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Table 9 Impacts of Section Creation and DestructionRegression # (4)Whole Sample (5) Regular Recruits (6) Irregular RecruitsEstimation Method c-logit d-probit c-logit d-probit c-logit d-probitage -2.428*** -.0318*** -2.456*** -.0414*** -2.144*** -.0204***

years_at_rank 4.653*** .172*** 3.798*** -.0308 5.324*** .0804***years_at_rank2 .577*** -.0180** 1.288*** -.00189* .194* -.00727*section_change .299** .0275 .261* .0115 -.0562 -.0429***section_destruction .288* -.0168 .198 -.0298* .789* .00610section_creation -.00511 .0377*** -.111 .0427** .266 .0273**planned -.291* -.00404 -.365* -.00458 .0743 .0125location_change -.0974 -.0239** -.119 -.0279** .0228 -.0208function_change -.532*** -.0246** -.690*** -.0480*** -.0970 -.00685schooling - -.0467*** - -.0308 - -.000408

schooling2 - .00206*** - .00189** - -.000148regular - .0157** - - - -Pseudo R2 .8259 .2360 .7932 .2559 .8994 .1213# of Observations 11451 19170 7443 11207 4008 7693

32

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Table 10 Differential Impacts of Transfers across TenureSECC FCC

sample whole regular irregular whole regular irregulartenure < 5(c-logit) +* + +** - -* -

tenure < 5(probit) +** +** - -*** -*** -5 ≤ tenure < 10(c-logit) + +* + - -** +5 ≤ tenure < 10(probit) + + - - -*** +**10 ≤ tenure < 15(c-logit) - + - + - +10 ≤ tenure < 15(probit) +** +** + +*** -** +***15 ≤ tenure < 20(c-logit) - + - + - +15 ≤ tenure < 20(probit) + + - +*** + +***20 ≤ tenure < 25(c-logit) + - + - + -20 ≤ tenure < 25(probit) - - - +*** + +***

tenure > 25(c-logit) + + - - - +tenure > 25(probit) - + -** +*** + +***

Table 10 (continued)LCC

sample whole regular irregulartenure < 5(c-logit) - - +tenure < 5(probit) -*** -*** -5 ≤ tenure < 10(c-logit) - - +5 ≤ tenure < 10(probit) - - +**10 ≤ tenure < 15(c-logit) +*** +* +

10 ≤ tenure < 15(probit) +*** + +***15 ≤ tenure < 20(c-logit) + - +15 ≤ tenure < 20(probit) +*** +*** +***20 ≤ tenure < 25(c-logit) - - +20 ≤ tenure < 25(probit) +*** + +***tenure > 25(c-logit) + + +tenure > 25(probit) +*** + +***

33

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Table 11 The Probit Estimate of Promotionwith Heckman Correction for Selectivity Bias

Probit Model for PromotionSample Whole Sample Regular Recruits Irregular RecruitsHeckman Correction (7) Yes (8) No (9) Yes (10) No (11) Yes (12) Noyears at rank .0394*** .134*** .293*** .276*** .0899*** .0386years at rank2 -.0130*** -.0296 -.0710*** -.0691*** -.0151*** -.00624section change .0625*** .0646*** .0949*** .153*** -.0196 -.00503location change -.0857*** -.0786** -.0834** -.0771** -.0944** -.0233*function change -.121*** -.124*** -.151*** -.153*** -.0755 -.0215schooling .0522*** .0564*** .0831*** .0861*** .0204*** .00621***fast_flyer .0710* .0788** .178*** .0748*** .0432 .00780

slow_mover -.398*** -.413*** -.401*** -.170*** -.349*** -.0929***Pseudo R2 - .0957 - .0614 - .0195# of Observations 18882 19217 10999 11233 7883 7984

Table 11 (Continued)

Probit Model for ’Stay’ (No Quit)Sample Whole Sample Regular Recruits Irregular RecruitsCorrection for (7) (9) (11)age .232*** .281*** .116**age2 -.00264*** -.00322*** -.00134**Regular .159*** - -Univeristy -.202*** -.233*** .-.164**Foreign_offices -.182*** -.166** -.262**

Location_Change -.180*** -.204*** -.136fast_flyer -.182 -.114 -.217Slow_mover .381*** .306 .444***ρ .821 .980 .774Wald_test 112.45 (p = .000) 186.99 (p = .000) 195.11 (p = .000)# of Observations 18882 10999 7883

34

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Figure 1 Relative Distances Among 11 Funcitonal Groups1 2 3 4 5 6 7 8 9 10 11

1

2

3

4

5

6

7

8

9

10

11

1 ADMN 2 PLAN 3 SALE 4 LGST 5 OVSE 6 R&DE 7 R&DA 8 PRDV 9 PRDN 10 QCTL 11 PCTR

1 ADMN

2 PLAN

3 SALE

4 LGST

5 OVSE

6 R&DE

7 R&DA

8 PRDV

9 PRDN

10 QCTL

11 PCTR

FLOW DESTINATIONS

FLO

W O

RIG

INS

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Figure 2 Relative Distances Among 12 Divisions

2 4 6 8 10 12

2

4

6

8

10

12

DIV1 DIV2 DIV3 DIV4 DIV5 DIV6 DIV7 DIV8 DEPTS R&DS HQTR LEAVE

DEPTS

LEAVE

HQTR

R&DS

DIV8

DIV7

DIV6

DIV5

DIV4

DIV3

DIV2

DIV1

FLOW DESTINATIONS

FLO

W O

RIG

INS

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Figure 3 Section and Division Transfer Frequency across Ageage

Section Transfer for Regular Division Transfer for Regular Section Transfer for Irregular Division Transfer for Irregular

20 60

14.04

61.9

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Figure 4 Function and Location Transfer Frequency across Ageage

Function Transfer for Regular Location Transfer for Regular Function Transfer for Irregular Location Transfer for Irregular

20 60

16.58

52.38

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Figure 5 Section and Division Transfer Frequency across Rankrank

Section Transfer for Regular Division Transfer for Regular Section Transfer for Iregular Division Transfer for Iregular

0 16

12.34

61.9

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Figure 6 Function and Location Transfer Frequency across Rankrank

Function Transfer for Regular Location Transfer for Regular Function Transfer for Irregular Location Transfer for Irregular

0 16

14.81

52.38


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