OSIPP Discussion Paper: DP-2019-E-008

Successful and Dead-end Jobs in a Bureaucracy:
Evidence from Japan*
August 26, 2019
Kenta Kojima†
Assistant Professor, Faculty of Economics, Kansai University

Katsuya Takii‡
Professor, Osaka School of International Public Policy (OSIPP)【 Keywords 】 Internal labor market; Career paths; Promotion; Fast track;
Bureaucracy【JEL Classification】 M51, J41, H83【Abstract】 This paper develops a novel method that assigns a job a value tocapture both the likelihood and speed of promotion from each job to a top executive
and applies it to investigate the career paths of bureaucrats in Japan.

We find that

outwardly similar jobs within the same hierarchical rank, estimated using thestandard method in Baker, Gibbs, and Holmstrom (1994), have very different
opportunities to be promoted to a top executive.

We can also detect frequent real

demotions and the presence of early selection (read fast track) of elite bureaucrats
unable to be detected through use of hierarchical rank.

* We are thankful to Kong-Pin Chen, Hirokuni Iijima, Hiroaki Ino, Junichiro Ishida,
Hideshi Itoh, Takao Kato, Fu-Chuan Lai, Hodaka Morita, Toru Nakazato, Fumio Ohtake,
Hideo Owan, and Shinpei Sano, along with seminar participants at Doshisha University,
Hitotsubashi University, Hokkaido University, Kyoto University, Osaka University,
University of Tsukuba, and National Central University for their helpful comments andsuggestions. We also greatly appreciate the assistance of Takashi Mihara and unnamed
public officials for providing us with useful reference materials and valuable information on
Japanese institutions. We gratefully acknowledge the financial assistance of the Japan
Society for the Promotion of Science through Grants-in-Aid for Scientific Research Nos.
25245040 and 18H03636.
† E-mail: k-kojima@kansai-u.ac.jp‡ E-mail: takii@osipp.osaka-u.ac.jp

1

Introduction

The internal labor market has been widely investigated since Doeringer and Piore(1971), and its characteristics have been shown to be quite di¤erent from those of theexternal labor market. The main reason is that employees within an organization areshielded from competition in a series of spot markets. Instead, employees face career
paths in the organization that are relatively stable over time. Because it is likely thatthese career paths are designed to play several functions, including skill accumulation,
as a screening device and as an incentive mechanism, the accumulated evidence on internal labor market attracts theorists by providing several empirical regularities that must
be explained by economic theory (e.g., Gibbons and Waldman (1999a, 1999b, 2006)).
One of the obstacles to a solid quantitative examination of career paths is that mostimportant job characteristics are qualitative along several dimensions, such as function,
location, and business unit. Furthermore, there are uncodi…ed characteristics of jobs,
such as skill requirements.

Although the previous literature typically uses either anorganization chart or transition matrices between major job titles to identify the levelin a hierarchical organization (e.g., Baker, Gibbs, and Holmstrom (1994), Lin (2005)), asigni…cant heterogeneity of job characteristics is likely to remain at the same hierarchicallevel. This heterogeneity could be critically important for the analysis of promotions.
This would be particularly true for the examination of promotions in the public
sector.

As argued by Tirole (1994), because government generally pursues multiple

goals, many of which are challenging to measure, it is di¢ cult to provide high powered
incentives through a formal salary. Therefore, career concerns could be one of the mostimportant motivations for hard work. Likewise, because the number of highly ranked
positions in a hierarchical organization is limited, it is more likely that the public sector
strategically employs lateral transfers at the same hierarchical level to motivate workers
than does the private sector.
This paper develops a new method to assign each job a value that can evaluate boththe likelihood and speed of promotion from each job to a top executive and applies it to
the personnel data of an elite group of white-collar government o¢ cials working in the1Japanese Ministry of Land, Infrastructure, Transport and Tourism (MLIT). We showthat our method can reveal a silent feature of career paths for Japanese elite o¢ cials,
which cannot be uncovered by either an o¢ cial organization chart or the standard
method developed by Baker, Gibbs, and Holmstrom (1994).
As in the seminal study by Baker, Gibbs, and Holmstrom (1994), we use the transition across jobs as the basic information used to evaluate each job. However, unlike
Baker, Gibbs, and Holmstrom (1994), which used information on moves between major
job titles to de…ne levels, where the major titles are selected from their data set, weestimate transition probabilities between all individual jobs available in our data set.
We can distinguish these not only by the job titles, but also by functional departments
and business units. Using these transition probabilities, we de…ne the value of each job
using the discounted expected probability of becoming a top executive.

As a result,

this evaluates not only the likelihood of being promoted to a top executive position,
but also the speed of promotion. Using the job value, we can then extract the heterogeneity of individual jobs within the same formal rank typically passed over in existingstudies. We then compare the pattern of promotions to higher valued jobs with thatof promotions to jobs at a higher hierarchical rank.
We …nd that there are signi…cant di¤erences in job values within the same hierarchical rank. We also show that within the same relatively high hierarchical rank, there
are both successful jobs, whose discounted expected probabilities of being promoted to
top executive are nearly one, and so-called dead-end jobs, whose discounted expected
probabilities are nearly zero. This suggests that the heterogeneity of jobs within thesame hierarchical rank is important for the analysis of promotions in the Japanese public
sector.
We also …nd frequent real demotions (or job relegation) in the sense of downgrading
to a job with a lower job value. However, this is not in the sense of downgrading toa lower hierarchical rank. This …nding suggests that o¢ cials are likely to face intensecompetition for top executive positions through job assignment.
Finally, we can also detect the existence of implicit fast tracks for elite o¢ cials, a2matter undetected by the hierarchical rank.

Our data shows that most o¢ cials arepromoted to directors, and that it is rare to observe more than two hierarchical rankdi¤erences for elite o¢ cials of the same tenure until they attain 30 years of tenure.
Because the majority of o¢ cials retire by 35 years of tenure, they are seemingly treatedequally for the most of their careers. This con…rms the late selection of o¢ cials, whichis pointed out by several Japanese labor economists (e.g., Koike (2002)) as a common
feature of internal labor markets in Japanese …rms.

However, we also …nd that thevariation in job values within the same tenure gradually rises as the tenure of o¢ cials
increases, even during the early stages of their careers. This suggests that the public
sector may select o¢ cials during a much earlier stage of their careers than we usuallyconsider.
To con…rm the presence of fast tracks, we conduct regression analysis.

We …ndthat after controlling for tenure in the ministry and tenure at the current job value, thelength of tenure at the previous job value has a negative association with the increasein current job value. However, we cannot …nd the same result using hierarchical rank.
We also …nd that while o¢ cials’educational background does not have any signi…cantrelationship with their current hierarchical rank, a prestigious education dummy has
a signi…cant positive relationship with their current job value.

Moreover, we also

…nd that while o¢ cials’ hierarchical ranks in the early stages of their career have anegative association with their current hierarchical rank, job values at the same stage
have a positive association with their current job values. All these …ndings support the
hypothesis that while the Japanese government does not formally di¤erentiate betweeno¢ cials throughout their careers, it does select promising young o¢ cials through lateraltransfer much earlier than usually believed.
There have already been several attempts to analyze personnel data and provide thestylized features of the internal labor market of an organization (e.g., Medo¤ and Abraham (1980, 1981), Rosenbaum (1984), Baker, Gibbs, and Holmstrom (1994), Seltzer andMerrett (2000), Treble, Gameren, Bridges, and Barmby (2001), Lin (2005), and Kauhanen and Napari (2012)).

Most recently, several studies have begun to pay attention3

to movement within a hierarchical rank (e.g., Gibbs and Hendricks (2004), Gittings(2012)).

At least some of these examine how the frequency and broadness of lat-eral transfers in‡uence promotion (Koike (2002), Dohmen, Kriechel, and Pfann (2004),
Ariga (2006), Clemens (2012), Jin and Waldman (2016), Frederiksen and Kato (2018),
Belzil, Bognanno, and Poinas (2018)), while Takii, Sasaki, and Wan (2018) examine
the timing of promotion and lateral transfer. In addition, a number of other studies
provide theories on the role of job rotation (e.g., Ickes and Samuelson (1987), Cosgel
and Miceli (1999), Ortega (2001), Eguchi (2004, 2005), Eriksson and Ortega (2006), Jin
and Waldman (2016)). However, none of these consider the heterogeneity of individual
jobs within the same formal rank.
Other studies of personnel data in Japanese …rms consider the particular heterogeneity of the jobs observed in the data. Similar to our approach, these studies pointout that the di¤erentials in job assignment between promising and other employees canbe observed before a di¤erence in the speed of promotion arises in both Japanese …rms
(Matsushige (2000), Umezaki (2000), and Uehara (2007)) and the public sector (Ichise(2013)). However, because these analyses do not include systematic measurement toquantify the prospects for promotion to top executive for each job, they can only identify jobs with a distinguishing trait through casual observation. Therefore, they cannot
detect the broad heterogeneity of each job within the same level of hierarchy.

They

also cannot detect demotion from the perspective of competition for promotion.
Our paper also contributes to the literature by providing valuable evidence of aninternal labor market in the public sector.

At present, there are few attempts to

examine an internal labor market in the public sector. Inoki (1995), Inatsugu (1996),
Gibbs (2001), Inoki (2002) and Ichise (2013) are exceptions. In particular, like ourselves,
Ichise (2013) reviews the personnel records of police bureaucrats in Japan and …nds thatexperience in a speci…c job in‡uences their future careers. However, as discussed, thisapproach cannot grasp a full understanding of the broad heterogeneity of individual jobs
in the same rank and the evolution of promotion competitions throughout careers. For
our part, we can show that the Japanese government gradually selects promising people4during their early careers and the competition for promotion becomes more intense as
they spend more and more of their career in a public sector organizations.
The paper is organized as follows. The next section explains our data set. The third
section provides evidence using a hierarchical rank.
career paths using a job value.

The fourth section investigates

The …fth section conducts regression analysis using

hierarchical ranks and job values and shows that we can detect a fast track only when we
use the job value. The …nal section concludes and discusses future research extensions.

2

Data

The data set used in this paper is the personnel records for an elite group of whitecollar o¢ cials working in the Japanese Ministry of Land, Infrastructure, Transport andTourism (MLIT). This ministry was established in 2001 through the merger of four
government o¢ ces: the Ministry of Construction (MOC), the Ministry of Transport(MOT), the National Land Agency, and the Hokkaido Development Agency.
We mainly construct the data set using 13 editions of the Kokudo Kotsu Sho Meikan(Directory of MLIT o¢ cials) from 2003 to 2015 published by Jihyo Sha. Each edition
includes all middle managers (Kacho class) and higher-ranked o¢ cials in the internalbureaus of both the ministry and the extra-ministerial agencies as of October 31 eachyear.1 Each observation contains an o¢ cial’s name, date of birth, education, job title,
the departments and sections of the current job, the year and month of taking up thecurrent job, and the o¢ cial’s past job history.
It is a common personnel practice in the Japanese bureaucracy to exchange o¢ cials
between the central government and other organizations. Those transferred to externalorganizations usually return to the central government after a few years. The directories also include all the top management and directors in some external organizations
1

Speci…cally, the extra-ministerial agencies are four organizations attached to the MLIT. These are

the Japan Coast Guard, the Japan Meteorological Agency, the Japan Tourism Agency, and the Japan
Transport Safety Board, along with two agencies formerly attached to the Prime Minister’s O¢ ce, being
the National Land Agency and the Hokkaido Development Agency.

5such as local branch o¢ ces, research institutes, and educational facilities establishedin a¢ liation with the ministry.

However, data are not available for retired o¢ cials

and those transferred to the other external organizations, including other ministries,
embassies, local governments, and public or private …rms.
To …ll part of these missing data, we also use iJAMP as supplemental material,
which is an internet service on public administrative information provided by Jiji Press.
This data source enables us to obtain information on careers for almost all middle- andhigh-rank managers in the internal bureaus of most Japanese ministries.
Finally, we include the omitted jobs for some o¢ cials by referring to the …les of
personnel changes for all o¢ cials in MLIT since April 1, 2004, which are publicly available on the MLIT website.

These …les also allow us to specify the retirement date

for retired o¢ cials, whereas the other two aforementioned data sources do not identify
whether o¢ cials not included in the data sources have retired or were transferred to an
external organization.
Through the data enrichment process discussed, once an o¢ cial is assigned to a
middle- or high-rank management position in an internal bureau or an a¢ liate of MLIT
between 2003 and 2015, we thereafter have a complete job history.

Hence, we caninvestigate the career paths for middle- or high-rank managers without too much concern
about any sample selection bias.
To obtain information on early careers before managers enter a middle management
position, however, we need to rely on their recall of events. This presents two potential
problems. First, some managers do not report all of their early jobs. Hence, the job
history records of low-rank positions for some of these managers are not perfect. When
we encounter data that do not exhibit any job changes over the long term, we can only
assume that these managers have remained in the same job.
Second, if some o¢ cials retire from the ministry before becoming middle managers,then they are also omitted from our data set. Figure 1 illustrates the representativenessof our data set. In total, there are 659 o¢ cials, of which 284 entered MOC and 375
entered MOT over the period 1969–2000. The dark shaded bar in Figure 1 represents

6the number of the o¢ cials included in the data set for each entry year.

The light

shaded area represents the o¢ cials we could not capture because they either retired orwere not yet promoted to middle manager. As shown, while our data set covers morethan 70 percent of all o¢ cials who entered the two ministries in each entry year during
the period 1974–1988, it does not for other entry years.
<< Figure 1 here >>To maximize the amount of information we can extract from the data and to minimize any potential sample selection bias, we utilize two di¤erent samples from our dataset.
1. To obtain an overall picture of career paths that includes the early career, we
combine our complete panel data with the early career recall data and construct
data pro…les for the entire personnel history following entry. Hereafter, we referto this as the sample of job histories with recall data. To minimize any potential
sample selection biases, we sometimes utilize a subsample of this data. We reportwhich (sub)sample is used in each …gure or table.
2. When we pay greater attention to the career paths of middle- or high-rank management positions, we use the panel data of o¢ cials between 2003 and 2015 because
we can observe their full job histories. Hereafter, we refer to this as the sample
of complete job histories for middle- or high-rank managers.

3

Hierarchical Rank

We can potentially identify the hierarchical rank of each job using the name of the titleof each o¢ cial.

The standard names of job titles and their ranks are prescribed by

Japanese cabinet ordinance and the hierarchy in the internal organization of a ministry
consists of the eight ranks listed in Table 1.

The ordinance also provides a formal

statement on the required abilities and skills for each rank, though it would be di¢ cultto grasp the precise contents of the required skills from the statement.

7

The salarystructure is prescribed by other laws and rules so that the range of wage levels hasa solid link with job ranks.

It is almost certain that the ranks of job titles play animportant role in characterizing the hierarchy of bureaucracy.
<< Table 1 here >>One of the di¢ culties in identifying the hierarchical ranks is that our data set contains many job titles other than the prescribed standard titles; therefore, their ranks
are not straightforward. To assign a hierarchical rank to all jobs, we apply the method
developed in Baker, Gibbs, and Holmstrom (1994) to the sample of job histories withrecall data.
To start, we construct a transition matrix to represent the moves between jobs withthe selected major titles in the internal bureaus of the MLIT and classify each one into
one of seven ranks (Ranks 2–8).

We additionally assign Rank 1 to the …rst job ofeach o¢ cial by taking advantage of the fact that there is a single port of entry for new
graduates into the ministry. Next, we assign appropriate ranks to the jobs with titles
other than the major ones based on the transition patterns between titles. Because it
is common to exchange o¢ cials between internal bureaus and other organizations, we
require additional procedures not prescribed by Baker, Gibbs, and Holmstrom (1994).
We provide more details on this procedure in the Appendix.

3.1

Promotion and Demotion

Table 2 provides the transition matrix between the hierarchical ranks using the sample
of complete job histories for middle- or high-rank managers after each o¢ cial is observedin the directory.2 In this table, moves to the right of a boxed cell are promotions, andmoves to the left are demotions.

As shown, promotions of more than one rank anddemotions are quite rare, with the probability of moving one rank below being quite
low, and the probability of moving more than two ranks above also being low. These2

We report the same transition matrix using the sample of job histories with recall data in the

Appendix.

8

observations are consistent with the stylized facts presented in the literature, including
by Baker, Gibbs, and Holmstrom (1994).
<< Table 2 here >>Table 3 details how many o¢ cials belong in each hierarchical rank at any given yearsof tenure. To examine the selection process from entry for 35 years, we use the sample
of job histories with recall data for those entering the ministry between 1974 and 1980.
Note that these account for 87.2 percent of all o¢ cials in the same cohort and that allo¢ cials in this sample have more than 35 years of tenure. Hence, this sample minimizes
any possible sample selection bias in early careers.
As shown, holding tenure constant, there is no signi…cant di¤erence in the speed ofpromotion until o¢ cials spend about 30 years of their careers in the ministry. Even if
we can observe some di¤erences in the speed of promotion, they seem not to last long.
For example, most of the surviving o¢ cials are in Rank 3 at 12 years of tenure. Somedi¤erentials seem to appear at 15 years of tenure, but disappear at 18 years of tenure.
The di¤erent patterns of selection procedure gradually appear after 30 years oftenure.

For example, 70 percent of the surviving o¢ cials are in Rank 6 at 31 yearsof tenure.

The various ranks of o¢ cials are evident at 33 years of tenure and thisdi¤erence does not contract thereafter. This suggests that the selection procedure for
the Japanese bureaucracy is quite slow. Several Japanese labor economists, including
Koike (2002), have pointed out that the late selection is a prominent feature of theinternal labor market in Japanese …rms. Our result provides similar evidence for theJapanese public sector.3<< Table 3 here >>3

Ichise (2013) shows that there is “quite late selection” in the National Police Agency, anotherJapanese government organization. In other words, the di¤erence in the speed of promotion does notlast until the unpromising o¢ cials retire.

9

3.2

Retirement

We can …nalize the competition for promotion when an o¢ cial retires. Many o¢ cials
seem to retire as soon as the selection appears to occur. We now more closely look at
the retirement of o¢ cials.

Table 4 presents the timing of retirement for 255 o¢ cials

retiring over the period 2004–2015. Panel (A) in this table shows the number of o¢ cials
who have retired at each hierarchical rank of their last jobs by tenure at retirement. As
shown, most o¢ cials have retired at Rank 6 or higher before the mandatory retirementage.
In actuality, there is an institutional arrangement in the Japanese bureaucracy designed to motivate o¢ cials to retire following promotion to Rank 6.

Firstly, o¢ cials

belonging to Ranks 6–8, called “o¢ cials of designated service (shitei-shoku),” receive
discontinuously higher salaries as a reward for their promotion from Rank 5 because thesalary schedule applied to them has changed according to the remuneration act.4 The
higher salaries for designated o¢ cials also result in much higher retirement allowances,which ultimately depend on the salaries for the last jobs of their careers. Secondly, as
Inoki (1995) showed, o¢ cials who have retired at Rank 6 or higher tend to be assigned
to higher positions as executive o¢ cers in public or private …rms and receive greater remuneration following retirement. In Japanese, this practice is called amakudari. Thus,
being a designated o¢ cial is economically important in that it has a considerable in‡uence on lifetime wages. Under this system, o¢ cials are likely to have a great incentive
to remain in service until promotion to Rank 6.
<< Table 4 here >>Interestingly, most o¢ cials retire as soon as they are promoted to Rank 6. Panel(B) in Table 4 details the years of tenure at retirement only for the 131 o¢ cials who
have retired at Rank 6 in relation to tenure at their promotion to that rank.
4

We

The Annual Report on Salaries of National Public O¢ cials 2011 published by the National Per-sonnel Authority states that university-graduate o¢ cials at Rank 5 to whom the highest salary grade
is applied receive on average 559,810 yen per month, whereas the lowest monthly salary for designatedo¢ cials is 724,000 yen.

10

…nd that 26.7 percent of these retired one year after their promotion to Rank 6 andthat 71.7 percent retired within four years after their promotion. This exit behavior
suggests that they are making the best possible use of amakudari because the outside
options of o¢ cials signi…cantly improve when they are promoted to Rank 6. We canalso conjecture that because o¢ cials who do not retire tend to be promoted to Rank
7, they are already aware of their opportunities of being promoted to Rank 7 when
promoted to Rank 6.

4

Job Value

The promotion and retirement pattern observed in the previous section suggests that allo¢ cials are equally treated during most of their careers before they become o¢ cials ofdesignated service (Rank 6). Once promoted to Rank 6, most o¢ cials soon retire. For
their part, the remaining o¢ cials are promoted to top executives. Therefore, o¢ cials
seem to recognize their own likelihood of being promoted to top executive before being
promoted to Rank 6. A relevant question is then when and how they learn about their
future promotion likelihood. We would like to argue that the career path itself reveals
how they are evaluated by their supervisors.
For this purpose, we develop a method to value each individual job by not only theprospects but also the speed of promotion to top executive. If an o¢ cial is promoted
to top executive with a high probability shortly after being assigned to a certain job, weassign the job a high value. In our method, we utilize richer information on jobs thanin the method of identifying the hierarchical ranks employed in the previous section
because individual jobs are distinguished by organizations and functional departments
as well as job titles.

4.1

De…nition

More speci…cally, let Vi(1) Vi be the value of job i, where Vi satis…es

Vi = wi +nX

P (jji)Vj ; for all i; j;

j=1

11

(1)

and wi is the instantaneous value of job i;

is a discount factor; n is the numberof available jobs including retirement; and P (jji) is the probability that an o¢ cialcurrently belonging to job i would be transferred to job j in the next period, which
can be calculated from the half-yearly panel data from personnel records.5 Using thematrix notation such as
2
2 3
2 3
P (1j1)
w1
V1
6
6 7
6 7
6 ..
6 .. 76 .. 7
V = 6 . 7;w = 6 . 7;P = 6 .
4
4 5
4 5
wn
P (1jn)
Vn

..

.

3
P (nj1)
7
.. 7
. 7;
5
P (njn)(1) can be expressed as
V = w + PV:
Hence, we can compute the job value by
V

(1

) (I

P) 1 w;(2)

where I is an identity matrix.
We assume that wi = 1 if job i indicates a top management position or retirement
after top executive, and wi = 0 otherwise.

We set the probability when retiring as

P (rjr) = 1 and P (jjr) = 0 for any j 6= r, where r denotes retirement.

Under theseassumptions, Vi = 1 when i indicates either a top executive or retirement after top
executive, and Vi = 0 when i denotes retirement after jobs other than top executive.
Hence, the value of a job is close to one when the o¢ cial in the job has a high probability of shortly being promoted to top management, while the value is close to zero
either when the job has a high probability of retirement without being promoted to top
management or when it is expected to take a long time to become a top executive fromthis job. Thus, our measure can capture both the likelihood and speed of promotion
from each job to top executive.
5

If there exists a job k …rst appearing in the last period of the data set, it is impossible to computethe values of the job k and the previous jobs that are transferred to job k because there is no information
on job transitions to other jobs from job k. We assume that P (kjk) = 1 and P (jjk) = 0 for any j 6= k
for such job k. In this way, the value of job k is set to be 0.

12

To estimate the job value, we must specify which jobs are the top management
positions. We identify these based on the formal rules and directives by the National
Personnel Authority about salary grades for o¢ cials of designated service.6 Top executives are de…ned as jobs in the internal bureaus of ministries accompanied by Grade
5 salary or more.7 The set of top executives de…ned in this way is a subset of jobs athierarchical ranks 7 and 8, 87 percent of which are top management positions as de…ned
here. We assume that once an o¢ cial reaches a top management position, they remain
assigned to a top management position. Because we are interested in promotion to the
top management position, once an o¢ cial is promoted to the top executive, we omitthat data thereafter.

4.2

Successful and Dead-end Jobs

Assuming that

= 0:97, which is frequently used by many macroeconomists as being

most appropriate, we compute the job values for all individual jobs. The distributionof the job values using the sample of complete job histories for middle- or high-rankmanagers is presented in Figure 2.8

This boxplot shows that while jobs at a highhierarchical rank have on average high job values, there are still large variations in job
values within the same hierarchical rank.

Within the jobs at Rank 5 or greater, inparticular, there are both successful jobs, whose job values are nearly one, and dead-end
jobs, whose job values are nearly zero. When an o¢ cial is assigned to a successful job,that o¢ cial would be in a position near the top executive.
<< Figure 2 here >>6

The rule of the National Personnel Authority No. 9–42 provides an ambiguous expression of the links

between individual jobs and salary grades for designated o¢ cials. The particular rules are prescribed by
the directives of the National Personnel Authority, which are not publicly available. However, speci…clinks were revealed by the formal answers submitted to an ordinary session of the Diet (the Japaneseparliament) to questions from a member of the House of Councilors in May 2011.
7
There are eight salary grades for o¢ cials of designated service according to rule No. 9–42 by the
National Personnel Authority.
8
We report the same transition matrix using the sample of job histories with recall data in the
Appendix.

13

The lower images in Figure 2 show that the variations in job values gradually increase
with the hierarchical rank, which may suggest that o¢ cials are gradually screened within
the organization. Within Rank 4, the share of the jobs whose job values are higher than
0.15 is very low, but a small number of jobs whose job values are higher than 0.3 areobserved within Rank 5. The jobs at Rank 6 can be divided into three groups: a very
few successful jobs, some middle-valued jobs, and many dead-end jobs. This con…rms
our previous conjecture that assigned jobs make many o¢ cials realize their likelihoodof being promoted to top executive when promoted to Rank 6.
To investigate how the heterogeneity of job values develops through o¢ cials’tenure,
we match the calculated job values to individual panel data and plot the relationshipbetween the value of the job each o¢ cial belongs to and the tenure of the o¢ cials.
Figure 3 depicts the result using the sample of job histories with recall data for thoseentering the ministry between 1974 and 1980. A darker point in the …gure indicatesthat more o¢ cials belong to that job value. As expected, this shows that the varianceof job values gradually increases as tenure becomes longer. The increase in the varianceappears even before 20 years of tenure, but certainly accelerates after 20 years. Hence,
it is likely that the competition for promotion becomes more intense after 20 years oftenure. The majority of o¢ cials seem to be screened out before 20–25 years of tenure.
Finally, after 36 years of tenure, there is a clear separation between o¢ cials in jobs that
almost guarantee their being promoted to top executive and o¢ cials in the jobs thathave no chance of being promoted to the top executive.
<< Figure 3 here >>Nonetheless, Figure 3 may provide a misleading picture of the variability of early
career jobs.

The values of early jobs must be low and have small variations as byde…nition they are heavily in‡uenced by the discount factor . To eliminate the in‡uenceof the discount factor, we construct a measure of relative job value by dividing ano¢ cial’s job value at some year of tenure by the mean of the job value over o¢ cials withthe same length of tenure.

14

Table 5 details the distribution of relative job value by tenure using the sample
of job histories with recall data for those entering the service of the ministry between
1974 and 1980. In contrast to the distribution of the hierarchical ranks by tenure in
Table 3, we can observe a gradual increase in the variation of relative job values. The
proportion of relative values between 0.75 and 1.25 is down to 80 percent up until 16
years of tenure, and further declines to 70 percent at 20 years of tenure, 50 percent at 26
years of tenure and 17 percent at 30 years of tenure. While it is true that the variationin relative job values rapidly increases after 20 years of tenure, the increase up until 20
years of tenure cannot be ignored. This leads us to surmise that the ministry mightalso di¤erentiate among o¢ cials, even early in their careers. While we previously foundthat the ministry seems not to formally di¤erentiate between o¢ cials until 30 years oftenure, the results in this table suggest the possibility of the tacit selection of promisingo¢ cials through job assignment.
<< Table 5 here >>We also examine the persistence of the values of jobs in which o¢ cials belong. For
this purpose, we construct a transition matrix among “the value ranks” classi…ed into
each quintiles of job values calculated using the sample of complete job histories for
middle- or high-rank managers. Table 6 provides the result. As shown, most of thebottom quintile remain in the bottom quintile and most of the top quintile either remainin the top quintile or are promoted to the top executive in the next 6 months. This
con…rms a strong persistency for the job values in which o¢ cials belong for low- andhigh-value jobs.

That is, there are sets of almost always dead-end jobs and almost

always successful jobs in the Japanese bureaucracy.
<< Table 6 here >>This table also demonstrates that we observe frequent large promotions and real
demotions for the set of jobs with job values between 0.2 and 0.8.

This means thatthe government aggressively selects o¢ cials from those in jobs with values between 0.2

15and 0.8. In particular, frequent real demotions may attract special attention. Those
assigned to jobs with values between 0.6 and 0.8 can expect promotion with a probabilityof about 18 percent in the next 6 months. However, they can also be demoted to lowvalue jobs with a probability of about 10 percent in the next 6 months. It is thus likelythat o¢ cials in jobs with values between 0.2 and 0.8 face intense competition.

5

Existence of Fast Tracks

5.1

Empirical Strategy

In Section 3, we revealed that the speed of promotion to a higher hierarchical rank isroughly the same for all o¢ cials. However, we also obtained suggestive evidence thatthe government may select promising o¢ cials much earlier during their careers. The
following more closely investigates the existence of fast tracks by conducting regression
analysis with both hierarchical and value ranks.
For this purpose, we …rst estimate the probability of promotion to a higher rank
using the following ordered probit model9 :
Yit =

0+

1 T Pit +2 Dit +

3 (T Pit

Dit ) +

4 T Cit +2
5 T Cit +6 Tit +

2
7 Tit + Xit+ "it ;

(3)
8>
1 if Yit a1 ;
>
>
>
>
>
< 2 if a1 < Y
it
Yit =
>
> 3 if a2 < Yit>>>>: 4 if a < Y ;
3
it

a2 ;
a3 ;

where Y is a latent variable; T P is tenure in the previous rank; D is a dummy indicatingthat an o¢ cial is assigned to the current rank by demotion from the previous rank; T C
is tenure in the current rank; T is total tenure in the ministry; X is a vector of othercontrol variables; " is a normally distributed error term. Y is an outcome variable that
9This speci…cation is a modi…ed version of that in Ariga et al. (1999).

16

takes four kinds of values. Yit = 4 if an o¢ cial i in period t is promoted to a higher
rank in the next period t + 1; Yit = 3 if an o¢ cial remains in the same rank in the next
period; Yit = 2 if an o¢ cial is demoted to a lower rank in the next period; Yit = 1 if
an o¢ cial retires in the next period after holding some job other than top executive.
The parameter aj (j = 1; 2; 3) is the threshold for each outcome. As control variables
X, we use dummies indicating the current rank, half-year dummies, education, and theministry an o¢ cial joined.
The education variable is a dummy variable that takes a value of one if an o¢ cial
graduated in law at the University of Tokyo and zero otherwise.

These o¢ cials are

relatively homogeneous in terms of academic skill because they passed an employment
examination that places a heavy weight on academic skill. They also typically entered
the MOC or the MOT with no full-time job experience immediately after graduatingfrom university. About 80 percent of the o¢ cials in our data set graduated from the
University of Tokyo, 80 percent of which are law graduates. Graduates of the Universityof Tokyo have long occupied a prestigious position in the elite group of o¢ cials in theJapanese central government as well as in the judiciary, as pointed out by Kawaguchi
and Ma (2008).
We are mainly interested in the estimate of the coe¢ cient

1 , which is the association

between the duration in the previous rank and the future probability of promotion, forthe key variable T P .

If there are fast tracks, then the estimate of1should be

negative. This parameter corresponds to the de…nition of fast tracks by Baker, Gibbs,
and Holmstrom (1994). We estimate

1 using the hierarchical and value ranks, andthen compare the e¤ects.10
For this estimation, we utilize the sample of complete job histories for middle- or
high-rank managers between 2003 and 2015. Because there are no missing observations
once o¢ cials reach middle rank in this sample, there is no sample selection bias. While
problems due to self-selection may cause di¢ culty in the estimates of causal e¤ects,
10

Similar to the calculation of job values, once an o¢ cial is promoted to top executive, we omit any

following data because no more variation in the rank can be observed.

17

because the de…nition of a fast track does not require any information on causality, thenegative value of

1 can be safely interpreted as evidence for it.

Although we examine the presence of fast tracks based on the commonly used de…nition in the above framework, there is an alternative stream of literature that examines
when the di¤erence in the speed of promotion …rst appears (e.g., Rosenbaum (1984),
and Uehara (2007)). They consider that there is a fast track when a lasting di¤erence
appears at an earlier stage of an employee’s career.
Investigating the fast track suggested by this literature, we execute the following
linear model to estimate the association between the early careers of o¢ cials and theirranks in a later period:
Rit =

0+

1 ECi +

2 Si +

3 Tit + Zit+ "it ;

(4)

where R is the current rank; EC is the hierarchical ranks or job values experienced in
the early career; S is a variable indicating that an o¢ cial graduated from a prestigious
university; Z is a vector of other control variables. The educational background S is thesame variable as the model (3) and as control variables Z, we use half-year dummies andthe ministry an o¢ cial joined. To construct variables EC, we use a dummy variableindicating whether an o¢ cial belongs in some rank at 5, 10, 15, or 20 years of tenure
for estimation with the hierarchical ranks, and the job value at the same years of tenure
for estimation with the value ranks. If there are early screening procedures, then we
expect that EC has a positive association with the current rank.
One of the di¢ culties in conducting this regression analysis is that our data on theearly career is not randomly sampled and possibly contains several sampling biases.
Note that our main data source, the Directory of MLIT o¢ cials, contains all o¢ cials
in Rank 5 inside the ministry each year, but does not include some o¢ cials in Ranks 3
or 4 each year. We thus need to rely on recall data to obtain early career information
about when o¢ cials were assigned to jobs in Ranks 1 or 2 and the number of jobs inRanks 3 or 4. More importantly, we face missing observations in the recall data.
To mitigate possible sampling bias, we utilize the sample of job histories with recall
data for those entering the ministry during the period 1974–1988, which covers 88.3

18

percent of all o¢ cials in the same cohort. Although we still need to interpret the regression result with caution, we believe that we can still extract meaningful informationfrom this data set. Because this is the best available early career data for the MLIT, we
report the regression results as supplementary evidence for the existence of fast tracks.

5.2

Results

The results of model (3) are in Table 7.

These show that tenure in the previous

value rank is signi…cantly and negatively associated with the probability of promotion,
while the association of tenure in the previous hierarchical rank on the probability ofpromotion is positive and not statistically signi…cant. This means that when an o¢ cialis assigned to the current rank through promotion from the previous rank, that o¢ cialis promoted to higher-value jobs with a greater probability if the speed of promotion
from the previous value rank to the current value rank is faster, while promotion to ahigher hierarchical rank is independent of, if any, a decrease in the speed of promotion
from the previous hierarchical rank to the current hierarchical rank. These results arerobust. As shown in columns (2) and (4) of Table 7, even when we restrict the sample
to those entering the service of the ministries for the years between 1974 and 1988, boththe magnitude and signi…cance of the tenure coe¢ cients in the previous rank do notchange. These results suggest the existence of implicit fast tracks unable to be observedby the formal hierarchical rank.
<< Table 7 here >>The results of model (4) for the hierarchical and value ranks are in columns (1) to (8)of Table 8. When using the hierarchical ranks, neither graduating from a prestigious
university nor early promotion to a higher rank is signi…cantly associated with the current rank. If anything, being Rank 4 by 15 years of tenure is negatively associated withthe current rank. When we use the job value, however, graduating from a prestigious
university is signi…cantly positively associated with the current job value.

As far as

we can take graduating from a prestigious university as a proxy of unobserved ability,

19the positive association with the current job value suggests that more able o¢ cials are
selected to a position with higher job values, but not with a higher hierarchical rank.
However, the coe¢ cients of early promotion to higher ranks remain insigni…cant evenif we use job values.

One possible explanation is that graduation from a prestigious

university is highly correlated with job values in the early career; therefore, the correlation between job values in the early career and current job values disappear once wecontrol for graduation from the prestigious university dummy variable. To investigate
this possibility, we conduct the same regression after omitting the prestigious university
dummy. Columns (9) to (16) of Table 8 provide the results. The coe¢ cients for theexperience of higher-valued jobs at 5 years of tenure now exhibit signi…cantly positive
signs. This supports our previous inference that we cannot …nd a correlation between
job values in the early career and the current position because we control for prestigious
university.
As a complementary analysis, we also estimate the relationship between graduatingfrom a prestigious university and rank in an early stage of career. The result is shownin Table 9. As shown, graduating in Law at the University of Tokyo has no signi…cantassociation with the earlier hierarchical rank, while it is positively associated with thevalue rank at 5 and 15 years of tenure. This provides evidence to support our argumentthat attending a prestigious university is highly correlated with early career job values.
These …ndings suggest that promising candidates are likely to be assigned to successfuljobs before they attain 15 years of tenure.
In sum, the evidence consistently indicates the possibility of implicit early selection
through job transfer.

This informal early selection cannot be observed using hierar-

chical ranks. That is, o¢ cials who are assigned to the promising jobs within the samehierarchical rank at the earlier stage of their careers have a high probability of being
assigned to successful jobs for top executives.
<< Table 8 here >><< Table 9 here >>20

6Conclusion

This paper develops a method to assign each job a value that evaluates the likelihoodand speed of promotion from each job to top executive and applies this method toinvestigate the career paths of o¢ cials in the Japanese public sector.

We …nd that

outwardly similar jobs within a hierarchical rank yield large di¤erences in the probabilityof being promoted to top executive. We also detect frequent real demotions and thepresence of implicit fast tracks for elite o¢ cials, matters unable to be detected throughuse of hierarchical rank.
Our …ndings are consistent with some of the anecdotal evidence.

Based on his

institutional analysis of Japanese public administration, Omori (2006) argues that theranges of regular salaries, which are prescribed by national law, depend only on thehierarchical rank and that o¢ cials are promoted to a higher hierarchical rank when
they spend a speci…c number of years at the current rank. This is consistent withthe results shown in Section 3.2.

However, Omori (2006) also argues that there is asecret order of jobs within the same job title. For instance, it is said that managers of
personnel divisions, budgets and accounts divisions, and general a¤airs divisions in the
Minister’s Secretariat at hierarchical rank 5 have better prospects of being promoted
to top executive than other division managers. It is noteworthy that the job values ofthese three types of division managers are extremely high.
Kishi (2015) also points out the role of the heterogeneity of jobs in future careerprospects, which is based on many interviews with active and retired o¢ cials, mainly
from the Ministry of Finance. These face three gateways to the top executive in theircareers: mid-30’s, mid-40’s, and mid-50’s. At each gateway, successful jobs are assigned
to the most promising o¢ cials. How well quali…ed an o¢ cial is for top executive depends
mainly on their reputation with both insiders and outsiders of the ministry.

Thissuggests informal early selection through lateral transfers within the same hierarchicalrank, which is supported by our analysis.
Because it seems a reasonable conjecture that organizations utilize movements within
the seemingly same hierarchical rank for several purposes, it would be possible that the21

great heterogeneity of jobs within the apparently same hierarchical rank can be foundin other institutions. Because the method provided in this paper can be applicablefor any organization that has a clear career goal of promotion, it would be useful forsystematically uncovering a silent feature of career movements. Hopefully, it can help
provide further important evidence about internal labor markets.

7

Appendix

7.1

Assignment of Hierarchical Ranks

This section discusses the detailed procedures for the assignment of hierarchical ranks.
Firstly, we select the 19 major titles from the 178 di¤erent titles in the internal bureausof the MLIT and the four ministries antecedent to the MLIT.11 The major titles are
the 18 titles that account for at least 0.5 percent of the observations with job titles, aswell as the top title to which one of the 18 titles are moved. These major titles cover
87.4 percent of the total observations with internal job titles.
Using the sample of job histories with recall data, we construct the transition matrix
to present moves between jobs with the major titles in the internal bureaus. Table A.1
shows the matrix. Because the names of the lowest-rank titles are blank in our dataset, the titles that should be categorized at Rank 1 do not appear in the transition
matrix. The earliest jobs are, however, moved only to Title A within the major titles,
and no one enters this title from the other titles. Thus, it is natural to categorize Title
A as Rank 2. The moves from Title A are then to Titles B, C, and D in the internalbureaus, save transfers at the same title (A) and transfers to external organizations, sothese three titles are categorized as Rank 3. Iterating this process, the major titles can
be classi…ed into the seven ranks. And we assign Rank 1 to the …rst job for each o¢ cialby taking advantage of the fact that there is a single port of entry for new graduates in
11

We …rst focus on the job titles in the internal bureaus of MLIT. This is because there are a great

variety of external organizations in the data set and because the rank of one title in an internal bureau
is likely to be di¤erent from that of the same title in an external organization.

22

the ministry.
<< Table A.1 here >>Next we assign appropriate ranks to the jobs with titles other than the major ones
based on the transition patterns between titles. As discussed, it is common to exchangeo¢ cials between the central government and other organizations. Hence, we need toassign a rank to a job in other organizations. One di¢ culty is that the same title appears
not only in the internal bureaus of the MLIT but also in the external organizations.
As it is likely that the same title in di¤erent external organizations has a di¤erent role,
we allow that a job title in one external organization can be at di¤erent rank from thesame title in another external organization. We assign a unique title if an o¢ cial’s title
is blank or an o¢ cial is studying abroad.

In the end, we have 1,236 di¤erent titles

except for the major ones to assign hierarchical ranks.
There is a caveat.

Because we have many minor titles not only in the internalbureaus but also in an external organization, we must extrapolate the ranks of someminor titles using a procedure not prescribed in Baker, Gibbs, and Holmstrom (1994).
Suppose that an o¢ cial is appointed to a position X that has an unknown rank x.
Suppose that s/he has spent t1 years to be appointed to the position since s/he had
been appointed to a di¤erent position that has Rank n.

Suppose also that s/he isappointed to a new position that has Rank m in t2 years later. The estimated rank xof the position X is the weighted average of the two known ranks:x=

t2 n + t1 m:
t1 + t2

This measure re‡ects the relative distance between the two positions with known ranks:
if t1 < t2 , then the rank of the position X should be relatively closer to Rank n.
Because we can observe several o¢ cials who were appointed to some position X, weassign the closest integer to the average of x over all o¢ cials belonging to position X
as the hierarchical rank of this position.
There are some o¢ cials belonging to position X but we are unable to calculate
their weighted average because we are unable to locate the two positions with known

23

rank needed for this calculation.
the following iteration.

To assign the rank to these positions, we conduct

We …rst estimate the hierarchical rank of minor titles that

we can calculate using the weighted average for all o¢ cials belonging to only major
titles. Because this increases the number of positions that can be utilized to calculate
the weighted average for some o¢ cials, we iterate this procedure until there is no jobthat we can assign a rank using this procedure. In the second round, we conduct thesame procedure for the minor titles that we can calculate a weighted average for the 90
percent of o¢ cials. We repeat this iteration by changing the criterion from 90 percent
to 80, 70, and then 66 percent. This iteration allows us to assign a rank to 86.4 percent
of titles.
Even when iterating this procedure, we cannot estimate the ranks of some titles ifthey move to retirement or if there is no title to which they are moved in the next
period. For each o¢ cial we set x =rank of the job in the previous period+0:5 in theformer case and x =rank of the job in the previous period in the latter case. Then we
assign the closest integer to the average of x across o¢ cials to the rest of the titles.
As a result of the process stated in this subsection, all job titles are successfully
categorized into eight hierarchical ranks, which are consistent with the ranks of standard
job titles prescribed by the cabinet ordinance. We consider that jobs at Ranks 7 and
8 in the internal bureaus of all ministries can be regarded as top executives. This isbecause Director-General, Title Q in Table A.1, at Rank 7 has the ultimate authority
and responsibility for each policy …eld under the jurisdiction of each bureau that is theprimary department of the central o¢ ces in the ministry.

7.2

Comparison Between Samples

In Section 3.1, we discuss the patterns of promotion and demotion based on the transition matrix between the hierarchical ranks using the sample of complete job histories for
middle- or high-rank managers. In Section 4, we discuss the distribution and transitionof job values using the same sample. In this section, we reveal the robustness of theresult even when using the sample of job histories with recall data.

24

Table A.2 details the transition matrix between the hierarchical ranks using thesample of job histories with recall data. Figure A.1 shows the distribution of job values
calculated using the same sample. The results are almost the same at Rank 4 or higher
as those using the sample of complete job histories. But we need to be careful about
the values for the jobs at Rank 3 or lower because the job history in the early career
stage is partly omitted.
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29

Figure 1. Number of officials by year of entry
Ministry of Construction

Ministry of Transport
0

5

10

15

20

25

1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
25

20

15

10

5

0

Notes: The darker shaded areas are officials included in the dataset and the lighter shaded areas arethose not captured in the dataset.
Source: National Personnel Authority annual reports.

30

Table 1. Standard job titles

Rank

Standard title(in Japanese)

8
7
6
5
4
3
2
1

Vice-Minister
Director-General
Director
Section Manager
Office Manager
Assistant Section Manager
Chief Official
Official(Jimu-Jikan )(Kyokucho )(Bucho )(Kacho )(Sitsucho )(Kacho-Hosa )(Kakaricho )(Kakariin )Source: “Cabinet Ordinance on Standard Job Titles”, March 6, 2009.

31

Table 2. Transition matrix for hierarchical ranks

Current
rank

Next rank
3

4

5

6

Top Exit Total

73

81.5 14.1

3.3

–

–

–

1.1 1004

0.3 88.6 11.0

0.0

–

–

0.1 100

5

0.1

5.4

–

0.1

0.7 100

6

0.1–

1.0 84.3

0.4

6.1

8.2 100

7

–

–

–

8.3 70.8 12.5

8.3 100

Top executive

–

–

–

1.4

Total

0.7 93.1

0.9 24.9 48.5 16.4

0.3 84.4 13.9 100
0.3

6.4

2.6 100

Notes: This table provides the transition matrix for the hierarchical ranks using the complete job
histories for middle or higher-ranked managers. – denotes zero transition probability. Moves within a
box are stays, moves to the right promotions, and moves to the left demotions.

32

33

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

Tenure
19

20

21

22

23

24

25

26

27

28

29

30

31

32 33 34 35
6.5 23.4 40.5 49.4
0.5 0.6 0.6 1.6 0.9
0.5 1.1 13.2 51.1 70.0 75.5 64.8 47.7 40.7
1.1 3.7 16.8 33.7 55.8 70.7 78.0 89.5 96.9 97.9 96.3 85.7 47.3 29.4 16.8 9.4 9.0 9.9
0.5 2.4 1.7 1.1 1.1 1.7 9.3 19.6 44.6 71.1 86.2 92.6 82.1 65.8 42.6 28.3 22.0 10.5 3.1 1.6 2.6 1.1 1.1
0.6 0.8 0.9
1.0 1.0 1.0 2.6 22.0 38.7 75.6 87.9 94.9 97.2 96.7 90.2 79.9 54.8 28.9 12.8 3.7 1.1 0.5 1.6 1.0
0.9
0.5 16.2 33.0 40.8 44.5 42.9 40.8 22.0 10.4 4.0 1.7 1.7 0.5 0.5 0.5
100 99.5 82.7 66.0 58.1 52.9 35.1 19.9

1entering the ministry between 1974 and 1980. The sample accounts for 87.2 percent of all officials from the same cohort and all have more than 35 years of tenure.

Notes: This table details the percentage of officials at each hierarchical rank for given years of tenure using the sample of job histories with recall data for those

Hierarchicalrank
Top executive
7
6
5
4
3
2
1

Table 3. Distribution of hierarchical ranks by tenureTable 4. Exit behavior of officials(A) The timing of retirement

Last hierarchical rank

Tenure at retirement29- 30

31

32

33

34

35

36

37 38+ Total

4-

1

0

0

0

0

1

1

0

0

0

3

5

7

1

9

5

0

2

5

1

0

1

31

6

0

7

23

24

11

28

20

12

6

0

131

7

0

0

0

0

1

0

0

1

0

0

2

Top executive

0

0

2

2

13

16

10

15

13

17

88

Total

8

8

34

31

25

47

36

29

19

18

255

37 Total(B) Retirement at Rank 6

Tenure at promotion to Rank 6

Tenure at retirement
30

31

32

33

34

35

36

25

0

1

0

0

0

0

0

0

1

27

0

2

1

0

0

0

0

0

3

28

0

3

8

1

3

1

0

0

16

29

7

4

7

2

5

3

6

0

34

30

0

13

3

3

4

5

2

3

33

31

0

0

5

3

4

6

3

2

23

32

0

0

0

2

7

2

1

1

13

33

0

0

0

0

5

0

0

0

5

34

0

0

0

0

0

2

0

0

2

35

0

0

0

0

0

1

0

0

1

Total

7

23

24

11

28

20

12

6

131

Notes: Panel (A) details the number of officials who have retired at each hierarchical rank of their last
job by tenure at retirement. Panel (B) shows the timing of retirement only for those who have retired at
Rank 6 in relation to tenure at promotion to the rank. Both tables use the sample of complete job histories
for middle or higher-ranked managers.

34

Figure 2. Distribution of job values within the same hierarchical rank

7

6

5

4

3
0

.2

.4

Job value

.6

.8

0

10

Percent
20

30

40

Hierarchical Rank 4

0.1

Job value

.2

35

.3

1

0

10

Percent

20

30

Hierarchical Rank 5

0

.2

.4
Job value

.6

.8

0

5

Percent
10

15

20

Hierarchical Rank 6

0

.2

.4

Job value

.6

.8

1

Notes: The boxplot and histograms detail the distribution of job values calculated using the sample ofcomplete job histories for middle or higher-ranked managers by hierarchical rank.

36

Figure 3. Distribution of job values by tenure

Notes: This figure details the distribution of job values. Darker points identify that more officials belong
to that job value. The job values use the sample of job histories with recall data for those entering theministry between 1974 and 1980. The sample accounts for 87.2 percent of all officials from the samecohort and all have more than 35 years of tenure.

37

38

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32 33 34 35
0.6 14.8 34.2 46.9
0.5
1.6 1.6 0.5 1.0 1.6 1.1 3.8 2.8 6.5
1.1
1.0 1.0 2.1 1.6 1.6 2.2 5.0 2.6 4.7
0.5 0.5 0.5
1.6 1.0 3.1 1.6 2.6 4.2 5.8 9.5 3.8 5.6 8.4 6.3 4.5
1.5 1.5 1.5
0.8 0.7
0.6 2.2 1.1
0.5
2.7 5.8 5.8 10.0 12.1 8.9 7.9 8.9 7.9 5.8 10.5 5.3 14.0 10.6 5.2 3.1 5.4 1.2
3.0 2.9 2.0 4.1 4.0 1.7 1.7 1.7 4.9 7.6 11.4 17.6 15.4 16.5 16.4 21.1 21.1 21.6 24.6 19.9 15.2 14.1 7.9 6.8 13.2 7.5 8.9 9.7 3.9 1.8 2.5
0.8 0.8
38.8 35.7 29.8 28.8 38.1 40.4 46.7 36.8 44.1 48.6 53.9 55.6 57.9 56.0 38.4 42.8 50.5 48.9 47.6 40.5 34.2 28.4 24.1 24.1 23.6 17.3 19.9 12.6 10.1 5.9 8.3 7.7 13.3 0.9 1.2
60.5 63.6 68.7 68.9 56.7 56.6 50.0 55.0 46.9 46.3 40.0 38.9 34.4 34.8 48.6 35.3 28.7 26.6 25.4 27.9 30.0 27.4 29.3 29.3 31.9 32.5 25.7 20.5 11.6 10.8 8.3 6.5 7.0 5.4 2.5
2.5
1.3 4.1 5.1 2.8 2.2 2.8 2.2 1.6 1.1 4.3 4.8 4.8 4.2 3.7 4.2 7.4 11.0 13.6 14.7 19.9 26.7 24.2 24.9 24.2 11.1 14.2 4.7
0.5
0.5
1.0 3.7 5.8 14.7 20.1 17.2 22.8 20.6 14.1 9.0 4.9
0.5 0.5 0.5 0.5 0.5 0.5 0.5 1.0 1.6 2.6 10.8 16.7 18.1 28.1 38.7 38.3

1

Tenureofficials from the same cohort and all have more than 35 years of tenure.

calculated using the sample of job histories with recall data for those entering the ministry between 1974 and 1980. The sample accounts for 87.2 percent of all

constructed by dividing an official’s job value for some year of tenure by the mean of the job value over officials with the same length of tenure. The values are

Notes: This table details the percentage of employees belonging to each range of relative job values for the given years of tenure. The relative job value is

Relative
job value RVTop executive
RV ≥ 2.25
2 ≤ RV < 2.25
1.75 ≤ RV < 2
1.5 ≤ RV < 1.75
1.25 ≤ RV < 1.5
1 ≤ RV < 1.25
0.75 ≤ RV < 1
0.5 ≤ RV < 0.75
0.25 ≤ RV < 0.5
0 ≤ RV < 0.25

Table 5. Distribution of relative job values by tenureTable 6. Transition matrix between value ranks

Current

Next rank

rank

1

2

3

4

5

Top Exit Total

0 ≤ Value < 0.2

1

93.5

4.0

0.3

0.0

0.0

0.1

2.1 100

0.2 ≤ Value < 0.42

8.4 82.8

5.5

1.1

0.5

0.5

1.3 100

0.4 ≤ Value < 0.6

3

4.7

5.3 75.9

4.3

4.1

4.1

1.5 100

0.6 ≤ Value < 0.8

4

3.1

1.2

7.5 10.6– 100

0.8 ≤ Value < 1

5

–

–

1.2

0.6 72.3 25.4

0.6 100

0.7

–

–

–

65.0 18.1

5.4

1.6

Value = 1 Top executive
Total

5.0 72.7

0.6 83.6 15.1 100
1.7

5.6

2.6 100

Notes: This table details the transition matrix among the value ranks using the sample of complete job
histories for middle or higher-ranked managers. The value ranks are classified into quintiles of job
values. – denotes zero transition probability.

39

Table 7. The effect of duration in the previous rank on the future possibility of promotion
Hierarchical rank

Value rank

Full sample

Subsample

Full sample

Subsample

(1)

(2)

(3)

(4)

0.00370.011-0.024**-0.025**(0.014)(0.015)(0.012)(0.013)

0.33

0.27

0.54***

0.49***(0.25)(0.26)(0.16)(0.16)-0.047-0.0430.072**

0.071**(0.075)(0.077)(0.034)(0.034)-0.021-0.0110.13***

0.13***(0.041)(0.043)(0.044)(0.046)0.014***

0.013***-0.0083-0.0081(0.0044)(0.0045)(0.0063)(0.0064)

0.60***

0.62***

0.83***

0.87***(0.098)(0.10)(0.11)(0.13)-0.011***-0.012***-0.016***-0.017***(0.0018)(0.0018)(0.0020)(0.0023)

Observations

4802

4300

3146

2943

Pseudo R-squared

0.065

0.061

0.053

0.053

Tenure in the previous rank TP
Demotion dummy D
Interaction term TP × D
Tenure in the current rank TC
Squared of tenure in the current rank TC
Tenure in the ministry T
Squared of Tenure in the ministry T 2

2

Notes: This table details the estimation results of the ordered probit model. Columns (1) and (3) provide
the results using the sample of complete job histories for middle or higher-ranked managers between
2003 and 2015. Columns (2) and (4) show the results using the subsample of officials entering theministries between 1974 and 1988, which covers 88.3 percent of all officials in the same cohort. All
specifications include current rank and half-year dummies, education, and the ministry an official
joined. Standard errors in parentheses are heteroscedasticity-robust and clustered at the individual level.
∗, ∗∗, and ∗∗∗ denote statistical significance at the 10 percent, 5 percent, and 1 percent level, respectively.

40

41

Observations
Adjusted R-squared

Tenure0.023

Graduating in Law at University of Tokyo

7497
0.587

6946
0.584

7295
0.589

7494
0.589

7788
0.584

7015
0.585

7385
0.589

7715
0.592

(0.024) (0.026) (0.024) (0.024)
0.15*** 0.15*** 0.15*** 0.15*** 0.15*** 0.15*** 0.15*** 0.15***(0.0043) (0.0043) (0.0042) (0.0038) (0.0042) (0.0043) (0.0042) (0.0038)(0.048)(8)(0.047)0.014(0.026)(7)(0.026)-0.011(0.053)(6)-0.057**0.025(0.027)(5)-0.056**(4)0.090*

0.030-0.0091(0.055)(3)

0.11**
0.017

0.0052(0.027)(2)

Being Rank 5 at 20 years of tenure

Being Rank 4 at 15 years of tenure

Being Rank 3 at 10 years of tenure

Being Rank 2 at 5 years of tenure(1)

Current hierarchical rank

Table 8. Relationship between achievement in early career and current rank

42

0.52***(0.048)(7)

8.85***

(8)

0.184

(9)
0.11*
(0.061)

Current value rank
(10)

0.10***

0.13**(0.062)0.11***

0.13**(0.062)0.11***

0.13**(0.062)0.10***

0.12*(0.061)

0.183

0.171

0.171

0.164

0.53***(0.047)

0.167

0.232

0.249

0.180

0.177

0.167

0.167

0.159

0.163

0.232

Standard errors in parentheses are heteroscedasticity-robust and clustered at the individual level. ∗, ∗∗, and ∗∗∗ denote statistical significance at the 10 percent,1974 and 1988 and covers 88.3 percent of all officials in the same cohort. All specifications include half-year dummies and the ministry an official joined.

5 percent, and 1 percent level, respectively.

(15)(0.84)

8.78***

(16)

0.249

0.10*** 0.084*** 0.076*** 0.11*** 0.10*** 0.11*** 0.11*** 0.10*** 0.100*** 0.084*** 0.076***(0.0095) (0.0095) (0.0093) (0.0093) (0.0093) (0.0094) (0.0081) (0.0079)
6221
6221
7165
7165
7424
7424
7715
7715

0.11*
(0.061)(1.76)(0.88)
0.073 0.054(0.055) (0.055)

3.79**

(14)

3.14*

0.033
(0.064)(13)(1.82)

1.13(3.48)

1.25(12)(3.40)

0.011(0.060)(11)

Notes: This table details the estimation result of the linear model using the sample of job histories with recall data for officials entering the ministries between

Observations
Adjusted R-squared

0.10***

Tenure

(6)

4.66

0.018
(0.064)(5)(4.11)(4)

3.46
0.0065(0.060)(3)(4.07)(2)(0.0096) (0.0096) (0.0094) (0.0094) (0.0094) (0.0094) (0.0083) (0.0080)
6173
6173
7096
7096
7334
7334
7494
7494

0.12*
(0.062)0.095(0.062)

Graduating in Law at University of TokyoJob value at 20 years of tenure

Being in top 50% in job value at 20 years of tenure

Job value at 15 years of tenure

Being in top 50% in job value at 15 years of tenure

Job value at 10 years of tenure

Being in top 50% in job value at 10 years of tenure

Job value at 5 years of tenure

Being in top 50% in job value at 5 years of tenure

(1)

43

0.036
(0.031)0.14***(0.032)
376
0.056

0.050
(0.048)0.57***(0.047)406
0.267(0.048)393
0.030-0.032(0.052)0.18***(0.037)
405
0.048

0.020
(0.040)0.18***(0.00088)
321
0.011

0.0013*(0.00077)
0.0014(0.0010)383
0.003-0.00013(0.0012)-0.0017(0.0017)395
0.072

0.0040**(0.0017)0.0088***(0.0035)405
0.038

0.0059(0.0036)0.014***

Job value
Value at Value at Value at Value at
10 years 15 years 20 years
5 yearsof tenure of tenure of tenure of tenuresignificance at the 10 percent, 5 percent, and 1 percent level, respectively.

1988 and covers 88.3 percent of all officials in the same cohort. Heteroscedasticity-robust standard errors in parentheses. ∗, ∗∗, and ∗∗∗ denote statistical

Notes: This table details the result of the linear model using the sample of job histories with recall data for officials entering the ministries between 1974 andObservations
Adjusted R-squaredEntering Ministry of Transport

Graduating in Law at University of Tokyo

Hierarchical rank
Rank atRank atRank atRank at
10 years 15 years 20 years
5 yearsof tenure of tenure of tenure of tenure

Table 9. Relationship between educational background and early career achievement

44

1.2

B

–

N

–

–

–

3.1

0.3

3.1

Q

R

S

Other

External

Total

–

–

M

P

–

L

–

–

K

O

–

J

–

G

–

–

F

I

–

E

–

–

D

H

–

C

–

1.7

C

0.7

0.6

D

6.0

1.7

1.1

–

–

–

–

–

–

–

–

0.8

–

–

2.4

–

0.5

0.2

1.6

1.0

0.4

0.2

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

0.5

0.3

0.5

E

5.2

1.4

0.5

–

–

–

–

–

–

–

–

2.5

–

–

–

–

–

–

–

0.1

–

1.1

F

4.0

1.3

1.1

–

–

–

–

–

–

–

0.4

5.0

8.5

9.2

1.2

–

–

–

–

–

–

1.7

G

0.6

0.2

0.2

–

–

–

–

–

–

–

–

–

0.1

–

–

–

–

–

0.2

0.1

–

0.2

H

4

0.4

0.1

0.1

–

–

–

–

–

–

–

–

–

–

–

–

0.2

0.1

0.0

–

–

–

–

–

–

–

–

–

0.1

–

6.6

1.1

0.6

–

0.6

J

–

–

1.4

1.3

–

5.4

–

0.4

0.6

–

0.1

K

0.2

0.1

0.1

–

–

–

–

–

–

–

–

2.4

0.5

1.0

–

–

–

–

–

–

–

–

–

–

–

–

5.0

1.4

–

1.2

–

–

5.2

L

5

–

–

–

–

2.0

1.7

0.3

1.3

–

–

–

0.5

M

0.3

0.0

0.1

–

–

–

–

–

–
–

–

7.5

2.1

0.7

–

–

0.8

0.3

0.1

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

1.0

2.1

N

–

–

–

–

–

–

–

–

–

–

–

2.7

–

0.8

O

6

–

–

–

–

–

–

–

–

–

–

–

6.3

–

0.5

P

1.0

0.3

0.1

–

–

–

0.5

0.3

0.1

0.0

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

6.7

3.1

2.5

Q

7

0.5

0.1

0.0

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

5.0

R

8
S

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

0.6

0.1

0.5

–

0.2

0.0

0.2

0.1

–

–

– 50.0– 69.2 11.5

– 72.7

0.5 64.4

2.3 67.4 11.6

– 67.7––

0.3 24.9 61.3

0.0 79.8

1.7 14.2 56.7

0.8 71.8

2.6–– 25.9

0.5

–

0.1

–

0.0

I

– 63.2– 65.92.0 59.2

1.9 64.9

0.3 71.4

0.5 81.1

5.1 70.2 10.4

– 80.0

78.3

A

3

15.2

2.0

81.9

–

–

8.0

11.9

3.9

3.5

2.6

1.7

4.2

3.7

–

8.5

2.7

12.8

2.6

1.4

2.3

3.8

0.5

7.6

1.6

1.6

3.5

0.3

–

–

–

–

–

–

–

–

–

–

–

–

49.8

88.0

8.8

0.7

0.9

0.4

– 50.05.1 14.1

6.7

14.4

10.1

13.9

9.5

12.8

8.3

11.9

22.4

20.7

4.8

12.8

18.1

13.7

11.7

11.4

17.7

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

Other External Exit Total

denotes zero transition probability. Moves within a box are stays, moves to the right (except Other and External) promotions, and moves to the left demotions.

of job histories with recall data. “Other” are titles other than the major titles in the internal bureaus, and “External” are all titles in external organizations. –Notes: This table details the transition matrix among the major titles selected from the different titles in the internal bureaus of the ministry using the sample

8

7

6

5

4

3

A

2

B

Title

Rank

2

Table A.1. Transition matrix between major job titles

Table A.2. Transition matrix between hierarchical ranks

Current

Next rank

rank

1

2

3

4

1

91.2

7.5

1.4

0.0

–

–

–

–

– 100

2

– 86.5 13.3

0.2

–

–

–

–

– 100

3

–

6.8

0.1

–

–

–

0.0 100

4––

0.7 91.5

7.7

0.1

–

–

0.0 100

5

–

–

0.1

1.0 94.0

4.5

–

0.1

0.5 100

6

–

–

0.1

–

1.0 85.2

0.3

6.3

7.1 100

7

–

–

–

–

–

8.3 70.8 12.5

8.3 100

Top executive

–

–

–

–

–

1.3

0.3 85.5 12.9 100

9.3 25.7 21.8 20.5

5.2

0.1

Total

14.8

0.2 93.0

5

6

7

Top Exit Total

1.9

0.7 100

Notes: This table details the transition matrix among the hierarchical ranks using the sample of job
histories with recall data. – denotes zero transition probability. Moves within a box are stays, moves tothe right promotions, and moves to the left demotions.

45

Figure A.1. Distribution of job values within the same hierarchical rank
7
6
5
4
3
2
1
0

.2

.4

Job value

.6

.8

1

Notes: The boxplot provides the distribution of job values calculated using the sample of job histories
with recall data by hierarchical rank.

46