Horizontal Transfer, Vertical Promotion and Evolution of Firm Organization ∗ Kenn Ariga [email protected]Institute of Economic Research, Kyoto University Yoshida Honmachi Sakyoku Kyoto 6068501 Japan January 4, 2003 Abstract This paper investigates the interactions among horizontal transfer, promotions across ranks, and creations and destructions of jobs inside a large Japanese manufacturing firm. In this sample firm, we find that job destructions and creations accounts for the majority of horizontal transfers of employees within the firm. This is in sharp contrast to a conventional view that employees move according to well-defined career path in a stable organization with internal labor market. Instead, we find that units and jobs are constantly created and destructed at this firm and that individual career paths are far more dynamic and state and path dependent. The econometric analysis on the determinants of promotion policy also confirm these findings. First of all, transfers which enable employee to acquire multiple skills do enhance the promotion probability, whereas transfers to functionally different units have negative impacts on sub- sequent promotion prospect. Secondly, individual career is significantly influenced by the success and failure of units, in particular we find: (1) promotion probability is significantly higher if employees belong to fast growing and/or higher gross job flow rate divisions, (2) promotion prob- ability is significantly higher also for those transferred from destructed sections, and also for those transferred into newly created sections. Journal of Economic Literature Classification Numbers: J24, J41. ∗ I benefitted from valuable comment from Giorgio Brunello on earlier draft of the paper. 1
Transcript
Horizontal Transfer, Vertical Promotion andEvolution of Firm Organization∗
Kenn Ariga [email protected] of Economic Research, Kyoto UniversityYoshida Honmachi Sakyoku Kyoto 6068501 Japan
January 4, 2003
Abstract
This paper investigates the interactions among horizontal transfer,promotions across ranks, and creations and destructions of jobs insidea large Japanese manufacturing firm. In this sample firm, we find thatjob destructions and creations accounts for the majority of horizontaltransfers of employees within the firm. This is in sharp contrast to aconventional view that employees move according to well-defined careerpath in a stable organization with internal labor market. Instead, wefind that units and jobs are constantly created and destructed at this firmand that individual career paths are far more dynamic and state and pathdependent.
The econometric analysis on the determinants of promotion policyalso confirm these findings. First of all, transfers which enable employeeto acquire multiple skills do enhance the promotion probability, whereastransfers to functionally different units have negative impacts on sub-sequent promotion prospect. Secondly, individual career is significantlyinfluenced by the success and failure of units, in particular we find: (1)promotion probability is significantly higher if employees belong to fastgrowing and/or higher gross job flow rate divisions, (2) promotion prob-ability is significantly higher also for those transferred from destructedsections, and also for those transferred into newly created sections.
Journal of Economic Literature Classification Numbers: J24, J41.
∗I benefitted from valuable comment from Giorgio Brunello on earlier draft of the paper.
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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 are intricately interwoven with the processof creation and destructions of jobs. In spite of the obvious and paramountimportance of the impact of demand side disturbances, the analysis of internallabor market has hardly paid any attention to it, due, perhaps, mainly to thelack of supporting empirical data1. We believe that the analysis of internal labormarket should benefit from incorporating this facet of worker mobility, juts asit has become standard to do so in the analysis of external labor market2.In this paper, we use unique data set taken from personnel file of a large
Japanese manufacturing firms to explore the complex interactions among orga-nization changes, job creation and destruction, and vertical and lateral transferof employees. The data offers us with a unique opportunity to investigate therelationship between lateral transfer, promotion, relocation of workplace, andfirm 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, especially thosefacilitating multi-skilling and its impact on productivity growth. Regular jobrotation is often cited as a standard practice of HRM among Japanese firms andregarded as a principal means to achieve multi-skilling among employees. Tothe extent that such lateral transfer is an integral part of HRM policy, mobilityacross sections and departments within an establishment should be treated asa positive signal regarding the future prospect of promotion3. In the previouspaper [Ariga, Brunello, and Ohkusa (1999)], we documented and demonstratedthat the sample firm used in this and previous paper does employ ‘fast track’policy in the sense that the promotion probability is higher for those who werepromoted to the current position within shorter period. It is of considerableinterests to see if such ‘fast track’ can be characterized by specific types of lat-eral transfers: i.e., to see if those on ‘ fast track’ exhibit distinctive patternof lateral transfer compared to the others. Related to this issue is a popularfolklore among the Japanese businessman that the transfer to a functionallydifferent section is often a bad signal that implies relatively poor evaluation ofthe performance at the current job. This can be also cast in a framework ofmulti- skilling.Another strand of issues stems from the literature on job creation and de-1Belzil (2000) is the only paper that I could find which incorporate job creation destructions
data into microscopic analysis of the labor market. He uses Swedish data on gross and netjob 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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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 creationin this firm is more than 30% per year. To the extent that job creations anddestructions are the other side of the coins of employment and unemploymentin the context of economy wide labor market, our data can be used as suchcorresponding to the internal labor market. We could ask a variety of questionsin this context. For example, do employees suffer from job destructions in thesense that their subsequent career is negatively influenced by such events? Wecan look at the other side of the coin and ask: do employees fare better bybeing positioned in sections that grow faster in size? Devereux (2000) analyzesthe impact of negative demand shocks on task assignments in the context ofspecific human capital model. He finds that the negative demand shocks inducereallocation of workers to tasks that require less skills in order to retain seniorworkers with larger amounts of specific human capital. This line of reasoningsuggests that the workers with shallow tenure (and hence smaller amount ofspecific human capital) are more likely to be transferred to accommodate shiftsin 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 who arehired in regular hiring cycle and mostly new graduates from schools, and thosewho are hired on ad hoc basis, mostly with workers with previous work experi-ence. One reason behind the observed difference is the difference in the scopeof multi-skilling. Those hired on ad hoc basis have previous work experienceand they 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 testing to see how each of these
predictions fares with our data. The sequel of the paper is organized as follows.In the next section, we briefly review the recent literature on internal labormarket as it relates to the horizontal transfers and job destruction/creations.Section 3 introduces the data and we provide a variety of descriptive statistics onlateral transfers and organizational changes. Section 4 is the main body of thepaper. First, we will focus on the multi-skilling and its relation to promotions.We find that transfers to neighboring units in terms of principal function anddepartment affiliation do indeed have positive impact on promotion. On theother hand, transfers to functionally different units or those across departmentsor divisions often have negative impact on promotion. Second, we also find thatthe impact on promotion varies across recruitment types and seniority. Impactsare generally stronger for workers with shallow tenure and younger in age. Wealso estimate the impact of job creation and destructions. We find significantpositive impact of rapid expansion of one of the division within the firm. We willalso provide some new evidence on exit behavior as it relates to the mobility ofworkers within and across firms. A brief concluding remarks are given in section5.
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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-served4. 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 internally5.The more fundamental reason, however, is that none of the important theo-
retical approaches to internal labor market is well suited to analyze the phenom-enon. Above all, horizontal transfers make little sense unless we explicitly incor-porate horizontal job heterogeneity within a firm. Most of theoretical modelsincorporating heterogeneous jobs are concerned with vertical transfer, or pro-motions to fill vacancies at upper managerial ranks6. In this context, Demouginand Siow (1996) analyzes the choice over training within and external hiringto fill manager’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 focusing on skill formations within firm. Lateral transfers and verticalpromotions are combined to form a career ladder through which each employeeacquires different but related skills. Job rotation within a shopfloor amongblue-collar workers is a common practice among large Japanese manufacturingfirms. Employees within a section rotate their job responsibility so that thosewithin rotation cycle are capable of performing multiple tasks. Most of largeJapanese firms routinely transfer employees to different sections/departments7.
4For 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).
5Outside 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.
6Vertical promotions may also involve different skill requirements, which might explain thedecline in productivity immediately after promotion. To the extent that transfers involve (withvarying degrees) different skill requirements at new jobs, we should expect similar decline inproductivity at least during the early periods after the transfer.
7Even in those firms, transfers across divisions are not common except for major organi-
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Our sample firm is no exception and employees typically experience transferswithin two to three year period. The upshot of the argument is simple: lateraltransfers are necessary ingredients for this type of skill formation and henceviewed as positive signal on the productivity of individual employees8. Compli-cations arise, however, because they simultaneously find that not all the lateraltransfers are considered as positive signals of learning capacity of each employee.In particular, transfers to jobs which differ greatly in skill requirements can bedetrimental to the career progression and those types, especially at higher age,are often regarded as a strong negative signal on the future trainability, andhence 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 ease at which Japanese firmsreshuffle their employees is their wage and promotion policy which jointly guar-antee that each employee retain her current (horizontal) rank irrespective of thejob assignment10. Such an argument implies that not all the lateral transfersare used to foster multi-skilling, or to generate whatever the desired impact onworker productivity by transfers. Instead, many such transfers are primarily’demand’ induced: to facilitate large swings in demand for different types ofskills across factories, departments, etc. If the system of horizontal rank min-imizes the uncertainty and anxiety on the side of employees experiencing suchtransfers, Japanese firms find it less costly to undergo major organizationalchanges which would require reallocation of workers at a large scale.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. Whateverthe cause, marginal productivity of jobs across sections vary over time and thefirm accommodates these shifts by reallocating workers. It would seem likelyunder the circumstances that the impact of transfer on the skill formation ofeach employee would 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 displacementfrom the current job at least partially destroy or diminish efficacy of humancapital, we expect significant negative impact from transfers induced by job de-structions. The impact of displacement by job loss may well go beyond the costat the current job if the newly assigned job after displacement is not a suitable
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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one from the viewpoint of career progression. Therefore, transfers induced bythe job destructions are likely to have negative impact on current and the futureproductivity 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 layoffs(’slack labor’) and find that the wage loss is significantly larger for those laidoff. They argue that the adverse signal of those laid off is stronger in that theyare selected to leave their jobs as opposed to arguably exogenous job losses inthe case of complete plant closing. The implication for internal transfer wouldbe that the demand induced transfers are more detrimental if they are selective,as opposed to 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 moreopportunity 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.All in all, what we know for sure is that the 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 redefining the job shopping process as those across jobs butwithin a 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:(1) The mobility out of current job is declining function of the tenure at the
current job.(2) Expected productivity at current job conditional upon the available in-
formation is constant.
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(3) The expected value of outside option (other jobs within the firm) doesnot 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 consider 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 the econometric implications of the employer learningmodel. The most important result is that the explanatory power in wage re-gressions of information available to the employer from the beginning shouldstay constant over time whereas the explanatory power of a variable not avail-able to employer but to an econometrician should increase over time. Bauer andHaisken-DeNew (2001) test Faber-Gibbons hypothesis using the European dataand find little support for the hypothesis. Human capital model can be con-trasted vis-a-vis employer learning model: conventional human capital modelcombined with the positive impact of generic ability on the efficacy of trainingwould indicate the impact of formal education to actually increase over time.They interpret the evidence in favor of human capital model as the more skilledworkers are given better opportunity to advance further their skills, therebymagnifying the impact 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.This firm is somewhat unique compared to other major manufacturing firms
in 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 highly frequent reappraisal and creation and destructions ofnew units within each division. The firm employs internal accounting systemto evaluate profitability of each unit, and the record is constantly monitored11See 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.
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so 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 waves of employee records com-piled in 1994, 1996, 1997, and 1998. In each wave, the record covers all thefull time employees who are under direct control of the personnel departmentat the headquarter. 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 employees arealso excluded. In short, the data covers all the core clerical, managerial and ad-ministrative stuffs, engineers and supervisors. In total, we have the record for8762 individual employees. Each record includes the following information: (1)current affiliation (section and establishment names), (2) current rank, (3) yearentered firm, (4) recruitment type, (5) education, and (6) promotion records interms 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 affiliations12 . 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. The list of functional 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 transfer as(a) relocation, (b) transfer, and (c) job change. Needless to say, all job changes[(c)] entail transfer [(b)], but not vice versa. Relocation [(a)] can occur with orwithout transfer [(b)] or job changes [(c)] and vice versa.
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 groups13 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 andwidespread among major Japanese firms and they form the basis of the allo-cation of workers to specific jobs. Although we refer to our previous work forthe details of such ranking system, we note here two important characteristics12 In this firm, most of establishments (factory or offices) contain units belonging to differ-
ent departments and divisions. Hence, relocation can occur without transfer or job change.Similarly, transfer across departments or divisions can occur inside the same establishment.13 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.
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of the system. First of all, the rank is a generic measure of potential ability ofeach employee at a firm. It is generic in the sense that the rank is attached toeach individual rather than to specific job or skills. Second, broad associationbetween rank and position stems from this property in the sense that the levelof skills, responsibility, and discretionary power endowed upon specific positioncalls for workers whose general ability potential is in the specific range.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 firms 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%14. The total number ofexisting units increased from 692 to 798, registering roughly 15% growth. Thedeaths and births of sections and jobs are much larger than these net changes.During the period, this firm created 819 new sections and destroyed 713 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 for70% 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 contrasting difference can be seen clearly by constructing similar statis-
tics 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,the comparison with section level data suggests that the figures computed atestablishment levels musk much of the job flows taking place within establish-ments or divisions15 .14The change in total employment during the period is much smaller. The large increase in
the sample employees 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.15We need to remind the readers again that the sample firm may be exceptional in terms
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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:
ji are, respectively, transfer from unit i to unit j,
size of units i, j, and (unknown) distance between (i, j). The equation abovecan be used to estimate the distance between two units by running the followingregression:
log(F ji ) = α1 log(Ni) + α2 log(Nj)− βZj
i + u
wherein Zji is the set of dummy variable for each distinctive combination of
(i, j). We run a pair of regressions: in the first case, we imposed the symmetryconditions:
distji = distij
distii = d
wherein the second set of conditions impose the condition that the distance bethe same for no transfer. In the second regression, we allow each distance todiffer depending upon the direction.We used two types of groupings in the analysis. First, we used the functional
group classifications and classified each section into 11 functional groups (G1-G11) as indicated in Table 2. In the next set of regressions, we used division asthe unit and each section belongs to 12 division groups (Table 4). Figure 10through 14 show the estimated coefficients β for Zj
i . In each figure, the darker(lighter) cells represent small (large) coefficient value, i.e., short (long) distance.In Figure 10 and 11, we show the estimated distance among 11 functional
groups. In either figure, it can be confirmed that groups 6 to 11 have shorter
of creations and destructions of sections.
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distances (i.e., cells are darker) overall than those for other groups. These arevariety of functional groups directly related to production and R&D. Groups 1to 5 are all clerical and administrative functions and the figures show that thetransfers are relatively small within as well as across these groups. Figure 11allows the distance to differ depending upon the direction. The most notablein the figure is the group 9 (production). The figure show that the group haslarge outflows (cells on row 9 are all dark) to virtually all the other functionalgroups whereas the inflows are relatively small (cells on column 9 are lighter). Toa lesser extent, group 3 (sales and sales representatives) has similar property,i.e., relatively small inflows but large outflows. To put it differently, manyemployees start their career with jobs in these functional groups; productionlines for engineers and sales offices for white collars16.In Figures 12 and 13, we exhibit relative distances among divisions. First
thing we notice is that most of the off diagonal cells are lighter (i.e., largedistances). Each of the first 8 product divisions have their own administrativeunits and largely self-contained. This explains relatively small inter-divisionaltransfers. There are exceptions, however. We find relatively large transfer flowsbetween division 1 and 2, and also between 6 and 7. This makes sense becausedivisions 1 and 2 are the oldest ones of the firm and division 1 supplies thematerial to division 2. Divisions 6 and 7 produce final products and division 6is the offspring (about 15 years ago) of a department in division 7. 11 is theheadquarter and 12 is not an actual division but all the employees on leave ataffiliates and subsidiaries are classified into this group. Not surprisingly, 11 and12 have large flows with the rest of divisions. It is also interesting to note thatthe division 6, the fastest growing and largest GJFR, has relatively large inflows(column 6 is darker) but the outflows are smaller (row 6 is lighter). Figure 13shows that inflows into division 10 (column 10) is very small. This reflectsthe fact that the firm gradually dissolved firm wide R&D centers and relocatedresearchers 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) of employees at oursample firm. The first thing we notice is the sheer magnitude of the changes.Even in the case of transfer across divisions, annual frequency is larger than10%. Equally surprising is the high frequency of job changes, ranging between15 and 20% per year17. Figure 1 through 9 shows frequencies of various typesof transfers across age, tenure and rank.The difference between the recruitment type is consistent with the fact that
the 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.16 See Kusunoki, K. and T. Numagami (1997) and Matushige (1995a,b) for similar findings.17On 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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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 general tendency as can be seen clearly from Figures 1 and
2 for age and 4 and 5 for tenure. All types of lateral transfers decline over ageand experiences(tenure). On the other hand, the frequency of lateral transfersdo not decline monotonically according to rank, as shown in Figures 7 and 8.There is general tendency that transfers are U-shaped.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 theladder, they will be transferred to more functionally different sections, especially,- we suspect-, when they are promoted to managerial jobs. Monotonic declinein transfer frequency over age or tenure, in conjunction with U-shaped transferfrequency across ranks, suggest that beyond certain age/tenure, the transfersare largely limited to those at senior managerial positions. In this second phaseof the transfers, we therefore suspect that the transfer is based more upongeneral managerial capability, than skill based expertise and know-hows specificto individual sections or functions. In other words, transfers at early stage ofcareer tend to be more skill-based, whereas those at later career is based moreon managerial ability and demand oriented. Note that this characterization isconsistent with our observations that within department 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 progres-sion is considered as the norm against which one can evaluate individual’s careerand infer 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 and fast flyer groups as well.On the other hand, slow movers tend to have more of transfers across depart-ments, divisions, functionally different sections, and also relocations. If thetransfer to a different section within a department is a norm from the viewpointof career ladder, these findings suggest that these groups of employees are rel-atively immune to irregular transfers induced by relative demand shifts acrossdepartments and divisions. Across age and tenure, we find as we indicated al-ready that younger workers with shallow tenure tend to move more often. Thistendency is most consistent for section change, whereas for other types of trans-fers, we find important exceptions to this rule. For example, group of employeeswith tenure between 5 to 9 years are less likely to experience these types oftransfers than the average, and frequency of functional transfers is higher thanthe average for employees with 30-34 years of tenure.
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In the previous paper, we found out the significant fast track effect: thoseadvancing in shorter period to a current rank will be on average expected tobe promoted further from the current rank in a shorter period. To see if sucheffect manifests itself in the lateral transfers, we picked up ’ fast flyers’ and’slow movers’ and compare their records. Specifically, we selected 357 fast fly-ers, and similarly 446 slow movers based upon the promotion records up to 1994.Table 6 shows that the fast flyers tend to move less often across divisions or es-tablishments, whereas slow movers experience more frequently transfers acrossdepartments, divisions and establishments. These characteristics are again con-sistent with the popular perception that transfers across functionally differentunits or relocations are not good signal.Figures 3, 6 and 9 display the frequency of employees experiencing section
creations and destructions. As we expected, there exist clear tendency that em-ployees with lower ranks are substantially more likely to be transferred to newlycreated sections. This perhaps reflects the firm’s policy to mobilize relativelyyounger employees to start-up new projects. Unlike frequencies of other typesof transfers, we also notice that transfers generated by section destructions aremore likely among irregular employees for senior ranks. Although the under-lying factor responsible for this pattern is not immediately clear, it seems toindicate at least that careers of senior irregular employees are more hazardousin the sense that their units are more vulnerable to restructuring. If we add tothis fact that transfers are generally less frequent for irregular employees, wehave to conclude that the average frequency of transfers generated for reasonsother than job destructions is smaller for irregular employees.We conclude from these findings that transfer probability is substantially
influenced by the trainability and general versatility of employees.
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 di-vision level, most of these changes are masked and disappear. This suggest twothings. First of all, much of lateral transfers are induced by job creations and de-structions. This is in sharp contrast to the prototypical image of such transfersas being supply oriented to foster skill formation along the pre-determined pro-motion ladder. Although this observation does not preclude the possibility thatfirms do take into account the impact of each transfer on the subsequent skillformation of individual employees, it is fair to say that the magnitude and timingof lateral transfers are dictated by the demand side. Nevertheless, correlationsbetween incidence of transfers and worker characteristics lend some support toconventional views on the role of horizontal transfers in large Japanese firms. Inparticular, the evidence is consistent with the view that such transfers facilitateskill formation of broader job categories (multi-skilling).
13
4 Econometric Analysis of Lateral and VerticalMobility
In this section, we analyze the personnel file and estimate a model for pro-motion probability. Much of what follows takes the similar analysis in Ariga,Brunello and Ohkusa (1998) as our starting point. Innovations in this paperis the introduction of the data on lateral transfers and we introduce the set ofnew variables on this facet of worker mobility. First, we consider the impact oflateral transfer per se and consider the impact in the context of multi skilling.The next step is to introduce the impact of organization changes, in particular,job destructions and creations due to scrap and build of production units. Fi-nally, we also incorporate the impact of worker mobility across firms. As is wellknown, separations induce selectivity bias in the regression unless the processof separation is econometrically exogenous to the process in which promotionsare 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 time18. Promotion is treated as an outcome reflecting re-appraisal and updating of individual productivity based upon the performanceof each worker.
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 specific18We ignore the possibilities of demotion and promotion for more than one ranks within a
year (we have no observation for either case).
14
jobs. We can think of two different interpretations of Dit. These variables can
be 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.Our next task in this section therefore is to find proxy variables representing
these two underlying factors for transfers. Although not perfect, we use the fol-lowing measure as useful to distinguish ’planned’ transfers along the promotionladder from those arising from demand disturbances: denote by i(k) the set ofemployees who are transferred to section k at time t. The transfer is defined as’planned’ if and only if the number of employees (nk
t ) remain unchanged at thissection 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:SECi
t , DEPit , DIV
it , FUNC
it , and RELOC
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.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
15
The impact of demand shifts may not be confined to those sections immediatelyinfluenced by the re-organization. For example, consider a section from whichmany of employees are pulled out to a newly created section. Unless the sectionhad some slack workforce, this section needs to replenish its members. The chainof induced transfers could continue many rounds and there is no clear-cut wayto define which of the transfers are demand induced and others supply induced.To represent the general influence of the demand shifts, we use growth and grossjob flow rates at departmental and divisional level; GROWTHp(d)
t , GJFRp(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 = {SECit ,DEP
it ,DIV
it , FUNC
it , RELOC
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, yearsof education, and a dummy variable for regular recruits19 .We first estimate the model including the transfers variable only among
Dki
t using conditional logit and probit models. The results shown in Table 7generally support the thesis that lateral transfers, especially those amenable tofostering a variety of skills have positive impact on promotion probability. Onthe other hand, transfers involving the geographical relocation of workplace perse have negative impact, although the estimated coefficient is not statisticallysignificant. The impact of transfers differ substantially across employees.Table 7 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 appliesonly to the regular recruits (for irregular recruits the coefficient is positive butnot significant even at 10% confidence level). 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 FUNC,transfers to functionally different sections, has the opposite impacts for two19We also experimented other specifications including tenure years at the firm, years of
external work experience, and current age. Regression results including these variables arequalitatively similar to those in Tables 9 through 12 and not shown but available from theauthor.
16
types and both coefficients are significant. For regular recruits, the negative im-pact is consistent with the view that transfers into functionally distinct sectionsare detrimental to employees’ career in that the newly assigned positions arenot well suited for their accumulated skills. For irregular recruits, the impact ispositive and significant. The results in Table 7 are mixed for the estimated im-pact of LCC (location change) and no clear and robust pattern can be detected.We come back to this puzzling results later in this section.When we replace SEC by DEP i
t or DIVi
t ,results are qualitatively similarexcept that the positive impact of transfer is often not significant even for reg-ular employees. Since majority of employees in our sample are engineers orengineering background, we expect that tasks may be highly product and/orprocess specific. Therefore transfers to functionally equivalent sections in dif-ferent department or division may well involve important changes in the set oftasks. All in all, results in Table 7 show that the only transfers to functionallysimilar units have positive impacts on promotion.
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 8 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 and creation variables, the impact ofPLANNED is negative and significant. Namely, these results show that thetransfers from destructed sections or into newly created sections by themselveshave additional positive impact on promotion, whereas we have the oppositeresult for transfers into sections whose size remain unchanged.These results are surprising at least for two reasons. First of all, as we noted
in the previous section, many pieces of anecdotal evidence suggest existence of awell defined and largely determined course of career progression such that thosepromoted fast tend to advance along such paths. The results in Table 8 insteadshow that demand driven section level transfers actually have additional positiveimpact on promotion. Secondly, we reviewed the evidence regarding negativeimpacts on wage by inter-firm mobility induced by layoffs or plant closings.Our results indicate that the analogy from inter-firm mobility does not applyto intra-firm mobility.
17
4.4 Differential Impacts of Transfers across Tenure
In Table 9, we include cross products of transfer variables with tenure variable.An interesting pattern can be detected from the table. Namely, the positiveimpact of transfers on promotion generally decreases as employees accumulateexperience at the firm. This is again consistent with the thesis that transfersfacilitate multi-skilling and the impact of skill formation on worker productivityshould decline over time. In short, accumulating experiences at different sectionsand functional responsibility is important at early stage of each career but itsimpact diminishes over time. This pattern is also consistent with our finding inthe last section that the transfers generally decline over rank, except for thoseacross divisions. The results shown in Table 9 include the cross products oftransfer variables and tenure. The results under variety of specifications areconsistent in predicting the following patterns. First of all, positive impact ofthe section changes declines over age. Similarly the negative impact of locationand functional change also decline over age. On the other hand, the impactof section destruction starts out at essentially zero ( the point estimate of thedestruction variable is not significantly different from zero and small), then theimpact turns negative and become larger in magnitude for older age, longertenure, and higher rank employees.In Table 10, we show the estimated coefficients for SECC,FCC,and LCC
only when we run the base model regression with split samples across tenuregroups. Here we detect the following patterns. As shown in Table 9, we findthat the positive impact of SECC is limited to lower to middle tenure groupsand the impact becomes either insignificant or negative for groups with longertenure (say, above 15 years). The impact of FCC, on the other hand, exhibita different pattern. In this case, the impact is mostly negative and significantfor regular employees with less than 15 years of tenure, then turns positivefor the more experienced but the coefficients are not significant. For irregularemployees, we also find that the impact is negative for very shallow tenure butthen turns positive and they are mostly significant. The pattern is largely thesame for LCC (location change). They tend to have negative impact at shallowtenure, especially for regular workers, but become positive for employees withlonger tenure and often significant 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 suggests that advancement of job specific skillsplay the key role in promotion and transfer decision. Therefore, transfers involv-ing function changes or relocation are often detrimental to career advancement.At later stage of career, the emphasis perhaps shifts from job specific skill for-mation to more general administrative and managerial capability. Hence theimpact of FCC and LCC turns positive.Our interpretation of the results is consistent also with the difference across
recruitment types. We noted above that the positive impact of SECC at shal-
18
low tenure is more robust and often significant for regular recruits than theirregulars, whereas the positive impact at later stage is stronger for irregularrecruits. This difference reflects the fact that irregular recruits have previouswork experience and they are often hired for specific job vacancies. As a matterof fact, many of them often hired at middle rank levels (rank 4 to 8). Hence theneed for job specific skill formation is not nearly as important for these workersas they are for regular recruits. On the other hand, for career advancementbeyond certain level, they need to have wider experiences which they tend tolack compared to the regular recruits. This is reflected in the stronger impactof FCC and LCC.
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 thosein more successful division in personnel evaluation. In order to incorporatethe possible impact of the division level and department (not shown but similarresults) growth in employment size, we used the year to year employment growthrate of division to which each individual belonged in the previous year. Theresult shown in Table 9 indicates that indeed the probability of promotion issignificantly higher for employees in faster growing divisions. When the impactis separately estimated for age groups, we find in this case that the impactis stronger for older employees, whereas the point estimate for younger cohortis actually slightly negative (not statistically significant). The gross job flowvariable also has positive impact on promotion either at division or department(not shown) levels. We have shown above that aside from the section destructionvariable, neither planned or create variable has significant impact on promotion.Putting these pieces of findings together, we conclude that horizontal transfersneed not be perfectly planned move in order to contribute to the long term careeradvancements. Instead, as we saw in section 3, most of transfers are induced bythe job creations and destructions at section level. One possible explanation isthat divisions or departments with higher job turnovers or higher growth canprovide constantly new tasks and jobs in which transferred employees are givenbetter opportunity to learn new but related skills.
4.6 Quit Behaviors and Selectivity Biases
As is well known, the data taken from personnel files of individual firms gen-erally 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 rectify
19
the situation by explicitly incorporating the selectivity bias arising from quits.For this purpose, we first estimate simple probit model for quit behavior. Theresult is shown in Table 11. The most notable finding here is the strong neg-ative impact of fast flyer and strong positive impact of slow movers on ’stay’propensity. These results are especially surprising in view of the fact that thepromotion probability is indeed significantly higher for fast flyer and slower forslow movers. We also notice that the foreign variable has strong negative in-fluence on stay decision as the variable indicates employees stationed in foreignsubsidiaries or branches.The results shown in Table 11 incorporate and correct for the selectivity bias
due to the decision to stay being endogenous. The quantitative results remain,however unaffected by the quit 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 the 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. Another more sanguine view is that the result simply mirrors the betteropportunity to advance career if one is assigned to growing business units, be itbe a section, department, or a division. Our results do not offer any conclusiveevidence to favor one over the other. We found, however, that the impact ofsection destruction is quantitatively more important and statistically significantfor workers with longer tenure, older age and higher rank. This result is notconsistent with a view that the information generated by lateral transfers can beinterpreted as signals 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 significantly negative impacton future promotion. Our reading of this result is that the firm uses relocationas a device to reshuffle slack labor force, especially when workers are relocated tofunctionally similar but geographically different units. As opposed to relocation,assignment to functionally different sections do convey a good signal which isconsistent with the view that transfers are used to facilitate multi-skilling inlarge Japanese firms.Several due cautions are in order before closing. First of all, it should be
noted again that the sample firm may be highly special even among the large
20
Japanese 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 build 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 shouldbenefit from this type of studies using more diverse sample firms.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 evolving than some of theoretical models characterize.
6 References
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23
7 TablesTable 1 Organization of Sample Firm
(1) List of establishmentstypes Number of EstablishmentsMajor offices 8Factories 11Regional Sales Offices 31
(2) Number of Sample Employees in Divisions and Headquarter Offices20
20note: 1: The division was purchased from independent firm in early 1980’s,.2: productiondepartments under direct control of headquarter. 3:Employees at affiliate firms in and outsideJapan
23
Table 2 Functional Codes Used in the Datacode Group Name
1 G1 office of president
2 G1 office of other executives
3 G1 executive secretaries
10 G1 internal auditing monitoring
11 G1 credit evaluation
20 G1 general administration headquarter
21 G1 general administration (Somu)
22 G1 office of legal matters
23 G1 office of documents
24 G1 library/archive
30 G2 management planning
31 G2 new project development planning
32 G2 office of suppliers and related companies
33 G2 research
34 G2 environmental matters
40 G2 public relations
code Group Name
41 G2 advertisement
50 G1 personnel (white collar)
51 G1 personnel (blue-collar)
52 G1 recruitment and training
53 G1 fringe benefits
54 G1 safety/security
55 G1 hospital/medical services
60 G4 accounting
61 G4 finance
70 G3 sales
71 G3 regional sales representatives
72 G3 sales administration
73 G3 sales planning/promotion
74 G3 consumers (customers) office
81 G4 operations
82 G4 logistics/transportation
24
Table 2 Functional Codes Used in the Data (Cont’d.)code Group Name
83 G4 project development (operations)
90 G5 overseas operation
91 G5 overseas offices
92 G5 exports/imports
100 G6 research/development administration
101 G7 technology development /administration
102 G8 patents
103 G8 engineering
104 G8 research centers
105 G8 product planning /development
110 G9 production
111 G10 quality control
112 G11 product design
119 G11 production control
120 G4 procurement
130 G4 information system
25
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 Divisions21
Jobs Created / Destructed per year
GJFR rate∗ creation due to (1) destruction due to (2)
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
21Note: GJFR is 1996-1998 average gross job flow rate computed as (jobs created +jobsdestructed)/existing jobs
26
Table 5 Summary Statistics on Lateral TransfersAcross 1996/94 1997/96 1998/97
22 *>(<) indicates that the group has significantly higher (lower) incidence compared to therest, at 1% significance level in chi−square statistic For example, the table shows that regularrecruits are significantly more likely to have section changes than those without. ** 6=indicatesstatistically significant difference among the 5 year age or tenure bracket groups.***' indicatesthat the difference is not statistically significant at 1% level.
# of Observations 11494 19217 7465 11233 4029 7984
23 In Table 7 through 11, we used the following conventions. (1) c-logit : condtional 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 fo 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%). In Table 7 through 11, we used the following conventions. (1)c-logit : condtional logit model incorporating fixed effects. In this type of regressions, sampleindividuals with all PR=1 (positive) or 0 outcomes are dropped. (2) d-probit : probit modelresults. The coefficients shown are normalized to indicate the change in the probability for aninfinitesimal change in each independent and continuous variable, and those corresponding toa discrete change for the dummy variables.(3) All the regressions include 3 rank group dummyvariables ( out fo 5 rank group, the highest 2 have small samples and we merged these two toavoid collinearity), two year dummy for 1996 and 1997. (4) The coefficients with *** indicate1% significance (** for 5% and * for 10%).
29
Table 7 Base Model (Continued)Regression type Base with DEPC
