Extended Schooling and Internalized Training
Skill Elements Evolution of Blue-collar Workers in an Internal Labor Market*
ISS Discussion Paper Series
F-157
April 2015
Masaki Nakabayashi†
Institute of Social Science
The University of Tokyo

AbstractLong-term employment and internal promotion at major firms are common in developed
economies. We examine the long-range changes in the returns on skill elements andtraining using a micro dataset of a Japanese ironworks. We show that, 1) the return onschooling rose from the late 1940s and that on tenure surged but that on previous experience became modest from the mid-1950s, 2) complementarity between schooling andexperience strengthened from the mid-1950s, and 3) training programs focused on bettereducated employees from the late 1940s, which formed an internal labor market in theflexible labor market in the 1960s.
Key words: specific skills; asymmetric employer learning; return on schooling; internal
labor markets; Japan.
JEL: J31; L22; M52.
* This research has been funded by the JSPS Grant-in-Aid (22243022).
†

The author is grateful to the corporation that allowed him to use its records, and appreciates the helpfulcomments from Michael Waldman, Katharine Abraham, Daiji Kawaguchi, Yuji Genda, Hideo Owan, Mathias
Hoffmann, Shintaro Yamaguchi, Daiju Kitano, Dan Sasaki, Dan Bogart, Ryuichi Tanaka, Kozo Kiyota, Konosuke
Odaka, Bing Ye, Changkeun Lee, Takashi Kurosaki, Norihito Abe, Chiaki Moriguchi, Lawrence W. Kenny,
Gary Richardson, Sng Tuan Hwee, Janet Hunter, Keisuke Nakamura, Naofumi Nakamura, Michio Nitta, andMinoru Sawai, as well as the participants of the Society of Labor Economists Annual Conference 2014, the 18th
Annual Conference of The International Society for New Institutional Economics, the International Industrial
Organization Conference 2013, the Asian Meeting of the Econometric Society 2013, the Association for Public
Economic Theory Annual Conference 2013, the Labor and Employment Relations Association Annual Meeting
2013, the Midwest Economic Association Annual Meeting 2013, the Southern Economic Association Annual
Conference 2012, Osaka Workshop on Economics of Institutions and Organizations, and seminars at Universityof Zürich, National Graduate Institute for Policy Studies, the University of Tokyo, London School of Economics
and Political Science, Free University of Berlin, University of Tübingen, Hitotsubashi University, and Universityof California, Irvine. Correspondence address: Institute of Social Science, The University of Tokyo, Hongo
7-3-1, Tokyo 103-0033, Japan. E-mail: mn@iss.u-tokyo.ac.jp

1 Introduction
Major firms in developed economies, and particularly those regarded as excellent companies,
tend to prefer long-term employment and internal promotion. Workers at the executive levelare often more mobile, working for shorter length of time and at different firms. However,the firm organizations as a whole are usually dominated by middle management promoted
from within, unless the firm is so young that it lacks sufficient internal skilled employees.
This preference for long-term employment and internal promotion, a combination known as
an internal labor market, is still widely observed in developed economies, even after labormarket reforms and increasing international integration of labor markets (Ariga, Ohkusa andBrunello (1999, 2000); Altonji and Williams (2005); Pfeifer (2008); and Ben-Ner, Kong andLluis (2012)). There are a few reasons for this practice: to encourage workers to acquire firmspecific skills, to provide risk-averse workers with job security as an insurance, and to enable
employers to learn about their employees’ abilities (Osterman (2011) and Waldman (2013)).
Major Japanese companies are well-known examples of the internal labor market practice.
This study examines how the personnel practice for blue-collar workers in the manufacturingsector formed in early 20th-century Japan by analyzing a dataset newly built from the original
wage records of a major ironworks. The performance of the Japanese economy until the
1980s, once admired, was based largely in the manufacturing, especially within efficient bluecollar organizations. At that stage, anecdotal descriptions of blue-collar workers in Japanesemanufacturing were actively discussed (Aoki (1988)). However, the excitement disappeared
before empirical analyses were conducted. Thus, examining the incentives used and the way
skills of blue-collar workers developed is necessary to understand the history of the Japanese
economy.
However, such an examination has meaning beyond the Japanese experience as well. Organizations of full-time blue-collar workers in other developed economies are extremely inflexible owing to historical industrial relations institutions. For example, in the United Statesand in Germany, the management of major firms cannot freely determine individual wages
or promote blue-collar workers in the same way as they can for white-collar workers, beingbound by trade union agreements. Thus, major Western manufacturing firms are unable to apply finely tuned incentive mechanisms to blue-collar workers, and instead have to apply muchcoarser or flatter wage schemes. As a natural result, blue-collar workers are expected to workin a routine way.
The aforementioned situation is common in American and European manufacturing firms.
However, for most of the world, that type of institutional arrangement is neither relevant nor
ideal. If there is a direction of sophistication for organizations in today’s emerging economies,
it is more likely be toward Japan than toward Europe or the United States. With regard to
manufacturing, the dominant players are likely to be Asian countries, where Western unionism
does not occur.
Work organization and personnel practices in contemporary Japanese firms can be summarized as follows. First, both white-collar workers and blue-collar workers work under adeliberately designed wage and promotion system with long-term employment. Every year,
all blue-collar and white-collar employees are eligible for a possible substantial upgrade to1their basic wage adding to a mere seniority based rise, based on merit. An employee’s performance during the previous dictates whether he or she is upgraded and by how much. Thus, theso-called “seniority-based wage” system in Japan is a simply a myth because seniority-based
rise counts quite a small portion in wage growth as a whole. While it is true that long-term employment is guaranteed, winners and losers are strictly differentiated every year. This pressure
empowers employees, and dedicated effort is the norm in the workplace, for both blue-collar
and white-collar employees (Aoki (1988) and Kike (1996)).
Second, because major firms predominantly stick to this strict internal meritocracy, workers with greater ability and longer service are more likely to earn higher wages. Thus, wage
growth is highly responsive to tenure (Abe (2000)). Again, this does not mean there is anemphasis on seniority. “Losers” are more likely to quit their first employers. People in thiscategory find it more difficult than new graduates do to find long-term employment at anothermajor firm, because major firms tend to commit to an internal labor market practice. Thus,
those who leave find it more difficult to re-enter a long-term employment at another major
firm and their tenure tends to be shorter. This competition structure within the labor market
further amplifies the return on tenure, on aggregate.
Third, employers’ investments in employees’ skills, typically from off-the-job training
programs, concentrate on better-educated employees (Higuchi (1994)). Fourth, and lastly,
major firms primarily hire new graduates (Genda, Kondo and Ohta (2010) and Sugayama(2014)).
As an approach to determine the origin of these practices, we analyze the wage dynamics
and training programs at a major ironworks in Japan. To do so, we create and examine a newlong-term employee-level panel dataset for the ironworks for the period 1930–1960.
Section 2 presents the underlying framework for the analysis. Here, we adopt the model of
DeVaro and Waldman (2012). The model captures general and firm-specific skill acquisition,
as well as asymmetric employer learning, which we assume are essential factors of internal
labor markets. The predictions in this section are based on this model.
Section 3 describes the features of the case plant within the steel industry and the dataset.
The dataset is created from the original wage records of individual employees of the ironworks. Then, we verify the existence of an internal labor market at the case plant during thesample period.
Section 4 decomposes the wage growth in the plant into human capital components, including physiological characteristics, schooling, previous career experience, tenure at the plant,
and completion of in-house training programs at the plant. Then, we track the evolution of
the returns on skill elements in cohorts. The principal findings are as follows. First, the returnon firm tenure rose sharply from the late 1940s onwards. Second, the return on schoolingsurged from the late 1940s. Third, the growth in the return on previous career experience,
which captures the return on general and/or industry-specific skills, became modest from themid-1940s, before increasing again in the 1960s. Mid-career experience appears to have been
supplanted by schooling from the late 1940s. However, at the same time, mid-career recruiting was active during the sample period until the end of the 1960s, with the return on previous
career experience still being valued, albeit being modest.
Section 5 investigates the in-house off-the-job training policy. Here, we also find a dis2

continuous change in the late 1940s. Before and during the Second World War, regulations
required major firms to complement the public education system by providing training programs to employees who had not completed their secondary education. Them, the postwar
education reform, led by the United States, meant that junior high school became compulsory,and the regulations on in-house off-the-job training programs were abandoned. In response,
off-the-job training programs focused on less-educated employees until the mid-1940s, andon better-educated employees from the late 1940s. At the same time, employees who had
more previous experience were more likely to be accepted as trainees from the 1930s to themid-1940s. They were then less likely to be accepted through the 1950s, but more likely to be
accepted again in the 1960s. While the case firm continuously invested in better-educated employees from the 1940s, the value they ascribed to previous experience became modest fromthe late 1940s to the 1950s, before picking up again in the 1960s. This result is consistent
with the aforementioned trends in the return on previous experience. With regard to customs
specific to contemporary major Japanese firms, there was a preference for new graduates with
better physiological characteristics in the 1960s. During this time, there was a shortage of labor in the Japanese labor market, as shown by the return on previous experience rising again,
when the domestic migration of slack labor in the rural regions ended.1 Thus, the case firm
began to focus on new graduates with better physiological characteristics.
In summary, the emphasis on schooling and tenure became intangible in the late 1940s andin the mid-1950s, while a preference for new graduates endowed with better characteristics
became prominent only in the 1960s. Furthermore, the case firm actively sought experienced
workers. Complementarity between extended general education and enhanced internal labormarkets has a long history, and hence is deeply rooted in the Japanese economy. Meanwhile, astrong preference for new graduates was barely observed before the 1970s, thus is a relatively
new phenomenon, and might not be necessarily structurally entrenched.

2 Underlying framework
2.1 Technology, skill, and organization
The desirable structure of an organization depends on who possesses relevant information.
At the same time, technological conditions shape the informational structure, which affects
the organizational structure. This relationship is particularly evident in the work organization
within a firm. Technological changes affect the types of skills required, which, in turn, determine whether employees or the firm possesses more information about the skill. If the firm has
more information about the skill, then more centralized control within the work organization
could more efficiently provide employees with incentives. The firm chooses an internal labormarket, a centralized incentive mechanism, when it has more information about the necessary
skills and when the skills are complementary and/or are firm-specific (Rosen (1988); Aoki
(1988); Osterman (2011); and Waldman (2013)).
1

Japan’s rapid postwar growth in the 1950s and the 1960s relied considerably on internal migration of workers from rural regions.

3Internal labor markets characterized by long-term employment and internal promotion
have been thought to work as a monitoring and evaluation device to make wages sensitive
to employee performance and to give employees incentives to acquire industry- and/or firmspecific skills. Thus, the wages determined within internal labor markets are not expected
to differ much in the long term, on average, from marginal productivity. However, they are
somewhat shielded from the competitive outside market and, hence, are not necessarily equal
to workers’ marginal productivity at any particular point in time (Baker, Gibbs and Holmstrom(1994a)).
Since workers’ abilities are generally private information at the time of recruitment, employers use proxies for these abilities during recruiting. One such proxy is schooling. Since
better-educated people are presumed to be more able, with a positive probability, employers
discriminate between applicants statistically, based on education. However, once a worker ishired, employers gradually learn about the worker’s innate ability. Then to determine wages,
employers come to rely more on information observed after hiring, and less on educational
background. Accordingly, the relative impact of educational background on wages decreases
as workers acquire work experience, which is called the “employer learning” process (Farberand Gibbons (1996) and Altonji and Pierret (2001)). While the employer learning process
occurs in the market as a whole, a firm can accelerate the process with long-term employment(Baker et al. (1994a, 1994b) and Pinkston (2009)). Furthermore, such asymmetric employer
learning makes internal labor markets self-sustainable. If a current employer knows their employees better than potential employers do, the current employers can retain their employees
by capitalizing on this informational advantage (Waldman (1984)).

2.2 Skill acquisition and asymmetric employer learning
Of models presented in related studies, the model of DeVaro and Waldman (2012) provides
a comprehensive and tractable insight into internal labor markets. Based on the work of
Gibbons and Waldman (1999) and Gibbons and Waldman (2006), the model captures work
experience and schooling as channels of skill acquisition, as well as employers’ learning processes. In addition, DeVaro and Waldman (2012) introduce asymmetric employer learningand the acquisition of firm-specific skills from Waldman (1984, 1996), which are essential
factors of internal labor markets. A consistent theoretical description of employer learningand skill acquisition was requested by empirical works such as that of Ariga, Ohkusa andBrunello (1999). They showed the existence of a fast track, controlling for time-invariant factors, within Japanese internal labor markets, which could not be explained by pure learningof time-invariant innate abilities. The Gibbons and Waldman (1999) model, and subsequentmodels based on this model, captures how employers learn about workers’ ability to acquire
skills in the workplace, which is consistent with the findings of Ariga et al. (1999). Primaryfactors of internal labor market practice is long-term employment and internal promotion.
DeVaro and Waldman (2012) justify the practice by assuming that asymmetry of employer
learning and firm-specificity of skills are considerable.
Let us first summarize the two-period model of DeVaro and Waldman (2012). Hereafter,
θi denotes worker i’s ability to acquire skills on the job, Experiencei,t denotes worker i’s
4labor-market experience until period t, ηi,t = θi f (Experiencei,t ) denotes worker i’s “onthe-job” skill in period t, where f (1) > f (0) > 0, and Schooli denotes worker i’s yearsof schooling. Then, assume θi = φi + B(Schooli ), where B(School) > B(School − 1),
for School = 2, 3, . . . , N and φi ∈ (φL , φH ) is a random draw from the probability density
function g(φ), assuming that g(φ) > 0, for φ ∈ (φL , φH ) and g(φ) = 0 lies outside theinterval. All firms are presumed to have homogenous production functions and each firmcomprises two jobs, 1 and 2. The product of worker i assigned to job j in period t is given by
yi,j,t = (1 + ki,t )(dj + cj ηi,t ) + G(Schooli ), where 0 < d2 < d1 , 0 < c1 < c2 , G is increasingin School, and ki,t > 0 if worker i was employed at the same firm in period t − 1. Here,
Experiencei,t , Schooli , f (·), B(·), G(·), dj , cj , and ki,t all form public information, while yi,j,t
is privately observed by the current employer, and φi is unknown to an employer in worker i’s
first period of employment. Employers learn about workers’ abilities asymmetrically, such that
φi is learned at the end of worker i’s first period only by the current employer who privately
observes worker i’s product, yi,j,t. Lastly, we assume no transaction costs and a common
discount factor.
′′′
Define η ≡ (d1 − d2 )/(c2 − c1 ) that solves d1 + c1 η = d2 + c2 η and assume that′(E[φ | School] + B(School)) f (0) ≡ θE (School)f (0) < η for any School. That is, any
worker in her/his first period, when no employer learning has yet occurred, is efficiently as′
signed to job 1. Furthermore, assume (φL + B(School)) f (1) < η < (φH + B(School)) f (1),which ensures that some workers in their second period are efficiently assigned to job 1, andthe remainder are efficiently assigned to job 2. After worker i finishes her/his first period,
the current employer either offers the worker a job assignment for her/his second period orfires her/him. This decision is publicly observed by other firms and wages are determined
before each period by spot-market contracting. Observing the current employer’s decision
on worker i, other firms offer a wage, and the worker’s employer in the first period offers awage that is weakly greater than that offered by other firms. Consider η + (School) such thatPN
in worker i’s second period if ηi,t = η + (School), where w N denotes
yi,1,t − wi,t= yi,2,t − wi,t
the wage paid to the worker assigned to job 1 and w P is the wage paid to the worker assigned
to job 2. That is, the profit is indifferent to promoting worker i to job 2 if ηi,t = η + .
In this setting, there is a perfect Bayesian equilibrium that applies to worker i’s second
period of being employed by firm A. In this equilibrium, if ηi,t < η + (Schooli ), then the worker
remains at firm A, is assigned to job 2, and is paid wtP (Schooli , ηi,t ) = d2 + c2 η + (Schooli ) +G(Schooli ); and if ηi,t ≥ η + (Schooli ), then the worker remains at firm A, is assigned to job
1, and is paid wtN (Si , ηi,t ) = d1 + c1 (φL + B(Schooli )f (1)) + G(Schooli ). In summary,outside employers offer wages that comprise a return on the general skills acquired at school,
G(Schooli ), and the least on-the-job skill possible, given the public information available
about promotion at the current employer. Then, the current employer makes a counterofferthat is only weakly greater than the wage offered by other firms.2
We can immediately derive useful implications for the existence of internal labor markets
as places of asymmetric employer learning and workers’ acquisition of firm-specific skills, aswell as places in which to evaluate schooling and work experience.
2

See DeVaro and Waldman (2012), pp. 96–101, 140–142.

5

Lemma 1. Allow the difference in the fixed parts of the productivity of each job, d1 − d2 , tochange depending on the state of the world in each period. Then, if the return on firm-specificskills, k, is strictly positive, the threshold of promotion, η + , changes in each period, provided
that schooling and work experience are fixed at the same level.
Proof. By the definition of η + , we have(1)N
yi,1,t − wi,t
= (1 + k) d1 + c1 η + (Schooli ) − [d1 + c1 (φL + B(Schooli )f (1))]
P= (1 + k) d2 + c2 η + (Schooli ) − d2 + c2 η + (Schooli ) = yi,2,t − wi,t.

We can rearrange this equation to the threshold of promotion, η + (Schooli ), as follows:η + (Schooli ) = −(2)

k(d1 − d2 ) − c1 φL f (1)c1 B(Schooli )f (1) +,k(c2 − c1 ) − c1k(c2 − c1 ) − c1

which increases in d1 − d2 only if k > 0.
Lemma 1 states that wage profiles that depend on promotion can be different in different
cohorts under different phases of business cycles. The point is that this phenomenon emerges
only if k > 0, which means that the return on firm-specific skills is strictly positive. As
an implication for empirical tests, this lemma predicts cohort effects in wage profiles if the
return on firm-specific skills is strictly positive under asymmetric employer learning inside andoutside internal labor markets. When verifying the existence of internal labor markets basedon this lemma, we presume that essential elements of internal labor markets are asymmetriclearning by employers and firm-specific skill acquisition by workers.
A caveat is that Gibbons and Waldman (2006), based on the same production technology, predict that allowing task-specificity generates cohort effects under symmetric employer
learning. Therefore, to verify the existence of an internal labor market consisting of asymmetric employer learning and firm-specific skill acquisition, we need to control for the effect ofindustry-specific skill acquisition.
Another observation from prior literature is the potential insurance role of internal labor markets. As Beaudry and DiNardo (1991) clarify, internal labor markets, which somehow “shield” internal wage dynamics from the outside market, provide insurance for riskaverse employees against macroeconomic shocks and, hence, could also deliver cohort effects.
Therefore, to prove the existence of an internal labor market that facilitates asymmetric employer learning and firm-specific skill acquisition, as well as insures employees, we need tocontrol for macroeconomic shocks.
Lemma 2. If the return on firm-specific skills, k, is sufficiently large, then an increase inschooling, School, alone decreases the threshold of promotion, η + , or, allows a smaller returnon work experience, f (1), to sustain the same level of η + .
Proof.
(3)c1 B(School) − B(School − 1)
η (School) − η (School − 1) = −f (1) < 0,k(c2 − c1 ) − c1++

if k > c1 /(c2 − c1 ).
6Lemma 2 describes how schooling and work experience are substitutes for promotion if
k is sufficiently large. Both schooling and work experience are observable to other employers
and, thus, increase the wage they offer, irrespective of whether a worker is promoted. Whilethe cost of promotion is to raise the wage offered by the other employers, because promotions
are also observable, an increase in the product of schooling and work experience increases
wages anyway, which lowers the threshold for promotion. This result predicts that when firmspecificity of skills becomes sufficiently large, schooling could replace work experience as abasis for worker promotion.

2.3 Transformation in the steel industry and the postwar reform
Japanese manufacturing, led by heavy industry, as in the United States, moved toward theformation of internal labor markets in the 1920s. Then, after the Second World War, internal
labor market practices developed further (Hashimoto and Raisian (1985); Aoki (1988); andMoriguchi (2003)). While it is true that the contemporary Japanese labor market is more
inflexible owing to the internal labor market practice of major firms, high-performing firms
in the United States have also continued to manage long-term employment. As a result, thereturn on tenure has actually increased during the last few decades (Altonji and Williams(2005)). Thus, even if their scopes show different depths and levels of sophistication in termsof internal labor market practices, the postwar development of the internal labor market itself
has been a common trend in both economies.
A significant difference, between the two economies was the development of unionization.
Under postwar U.S. occupation, unions were legalized and rapidly prevailed. However, enterprise unions, rather than trade unions, became dominant. The management and the enterprise
union of a firm shared the growth of the firm as their goal. Furthermore, unions negotiatedjob security and only average wages with the management of a firm. Individual incentives forblue-collar workers were under the perfect control of the management, as they were for whitecollar workers. Therefore, internal distortion of individual incentives due to unionization isthought to have been negligible in Japan.
Meanwhile, the postwar reform profoundly changed the Japanese system. Before the 1947
reform led under the US occupation, secondary education from 7th grade or higher had notbeen mandate. Instead, major firms were required to offer training programs that covered
secondary level education. Thus, the Japanese system was closer to the European system,
under which students were separated into general education and vocational education after
the primary education. Then, by the 1947 reform stipulated junior high school as mandate,and junior high school uniformly provided general education, instead of vocational training.
The number of high school was drastically increased, and they were predominantly generalhigh schools. Japanese secondary education came to provide mass workforce who received
standardized secondary education focusing on general cognitive skills.
Industries that Doeringer and Piore (1971) describe as those in which internal labor markets were formed in the 20th twentieth century, such as the steel industry, are those that Goldin
and Katz (2008) describe as having grown with technology-skill (education) complementarity.
In the United States, since the early 20th century, high schools have supplied a large number
7

of graduates with general skills. These better-educated workers were better suited to internal
labor markets in which workers’ general cognitive skills were engaged in firm-specific operations.3 In postwar Japan, the accelerated prevalence of internal labor markets after the Second
World War was associated with U.S.-led education reforms, which resulted in a massive increase in secondary school graduates.
For the Japanese steel industry, large technological transitions were observed in the 1920s
and in the 1950s, as larger open-hearth furnaces were introduced, and in the 1960s, whenconverter furnaces were introduced. In the iron and steel industry prior to the Second World
War, sophisticated production procedures were developed by employees. These procedures
were then taught to younger employees by the senior employees of the company. Along withthe technological transition, the traditional skills ascribed to individual senior employees weretransformed into manualized skills and made known to the management.4.

3 Existence of an internal labor market
3.1 Case plantThis study uses wage records of one of the oldest modern ironworks in Japan. From the
1950s to the 1960s, the government adopted an industrial policy that coordinated the long-term
credit supply to induce steel and other important manufacturing companies to invest in newtechnology. For the steel industry, three phased modernization investments were coordinatedfrom the 1950s to the 1960s.
As part of a company-wide investment plan, the firm in this case study decided to build
a new state-of-the-art plant at another, distant city. The firm also decided to shrink the caseironworks’ capacity and to relocate its skilled workers to the new plant. Consequently, 1,600
skilled workers moved from the case ironworks to the new ironworks in the late 1960s. Selection for relocation was handled in cooperation with the union and, in principle, anyone who
was willing to move was relocated.5

3.2 Data
This study examines a panel dataset newly created from the preserved wage records for 1,558
relocated employees. The records track these workers from the late 1920s or later, dependingon the employee’s entry year, to the 1960s, when they left the ironworks. The total numberof observations is 23,120. The original personnel documents contain all the important information about the employees’ characteristics they reported when recruited such as education,
previous work experience, licenses they had, physiological characteristics when hired, as well
as job assignments, promotions, and basic wages. This enables us to recover employees’ lives
from when they were born to the 1960s, when they were relocated.
3

See Goldin and Katz (2008), pp. 102–125, 176–181.
See Nakamura (2010), pp. 8–25.
5
See Umezaki (2010), pp. 33–38, 47–49.
4

8

Owing to the nature of the original documents, our dataset could potentially have twokinds of bias. The first is a selection bias owing to selection procedures for the relocation in
the 1960s. The second is a selection bias. The descriptive evidence of the selection procedures
indicates that the former might not be serious. However, the latter type could be significant.
The case ironworks belonged to a large steel company in Japan. Thus, while leaving theironworks for a company offering better pay was unlikely, movement in the other direction
was likely. Our dataset does not include employees who joined the ironworks in the early
period, lost out to the internal competition, and then left.
Thus, our dataset only include the employees who survived until the late 1960s.end of thesample period and does not include those who had dropped during the sample period. Thismeans first that sample distribution might be more upward than the original population, andsecond that the sample is immune from a possible bias or distortion of distribution due tocross sections who dropped during the sample period, because they are excluded. Therefore,
the sample bias contained in this dataset might affect, for instance, estimates of absolute levelof wages but does not affect estimated growth in wages during the sample period, which
would have been affected by including employees who had dropped during the sample period.
Also, if our dataset includes employees who had dropped during the sample period, it would
have made estimates of the increase in the return on tenure during the sample period higher
than real, and higher than the returns on other skill elements, because employees who had
dropped in early stages likely had lower productivity than survivors and hence including themoverestimate the return on tenure. Our dataset is free from such contamination.
The aim of this research is to inquire the long-term changes in wage dynamics, particularly
focusing on the return on tenure, instead of estimation of the absolute level of wages. Therefore, the specific structure of our dataset would not distort estimates we perform, but rather
would help produce unbiased estimates.
Each individual wage record includes the following information: (1) educational background; (2) physiological characteristics when employed (height, weight, and lung capacity);(3) information on prior labor market experience; (4) panel data of wages; (4) panel data ofranks, jobs, department assignments, in-house training programs, and promotions; (5) licenses
the employee held; (6) family composition; and (7) clinical history. The in-house training programs include the following: (a) 1927–1935: “Development Center for Youth,” 3 days a week,
4 years, 800 hours total; (b) 1935–1948: “School for Youth,” part-time, 3 days a week, 4 years;(c) 1939–1946: “Development Center for Technicians,” full-time, 3 years, 6,453 hours total;and (d) 1946–1973: “Development Center,” 3 days a week before 1950, 6 days a week from1950, for 2 years; from 1963, only high school graduates were admitted. The firm also provided short-term programs, such as elementary calculus, which were also recorded.
INSERT Table 1 HERE
The composition of the cohorts is shown in Table 1. While major contemporary Japanesefirms predominantly hire new graduates, this did not hold for the case firm from the 1930s
to the 1960s. Through the sample period, new graduates were not the primary source of theworkforce. In some periods, such as the late 1940s or the 1960s, we see a higher portion of new
graduates. In the late 1940s, the supply of the male workforce dropped owing to conscription.
9

Then, in the 1960s, the demand for labor surged following the rapid growth of the national
economy. These occasions tentatively indicate that new graduates were hired when there wasa shortage of experienced workers.
Entry volumes were not stable. Some cohorts, such as 1948 and 1949, when many maleworkers came back from the war, had much larger volumes. We control for potential biases from this unbalanced size of cohorts by inserting a two-year-joined dummy variable(Yearjoined19XX−YY ) in later analyses whenever the case is cohort sensitive.
Compulsory education was extended from six years to nine years in 1947. Thus, the difference in educational backgrounds across employees who graduated before 1947 is primarily
distributed between the six years spent completing mandatory elementary school and the eight
years comprising the mandatory six years and additional two years at high elementary school.
Similarly the difference across employees who graduated after 1947 is distributed mainly between the mandatory nine years, comprising six years of elementary school and three yearsof junior high school, and the twelve years comprising the mandatory nine years and an additional three years of high school. High elementary school graduates made up the majority of
employees before 1947, and junior high school graduates made up the majority after 1947.

3.3 Existence of an internal labor market
This subsection empirically establishes the existence of an internal labor market practice in thecase firm. The wage determination based on the practice is shielded because of asymmetricemployer learning and the intention to motivate the acquisition of firm-specific skills. Persistent cohort effects indicate the firm-specificity of skills and asymmetric employer learning
described by Lemma 1. To specify the firm-specificity of skill acquisition and the asymmetry of employer learning, we need to control for task-specificity of skill acquisition (Gibbons
and Waldman (2006)) and the insurance effect against macroeconomic shocks (Beaudry and
DiNardo (1991)).
Table 2 contains a regression of log real wages (log(wi,t)) on age (Agei,t ), years of schooling (Schooli ), labor market experience prior to joining the ironworks (PreExperience i ), tenureat the ironworks (Tenurei,t ), their square terms, and on the two-year-joined dummy variables(i.e, Yearjoined1930−31, Yearjoined1932−33, etc.), where Yearjoined19XX−YY i takes 1 if workeriii joined the firm in 19XX–19YY and Yearjoined1928−29 i = 1 is the control group. Macroeconomic shocks are controlled for using the growth of the real gross national product (∆GNP).
We also include year dummy variables to control for the rapid growth in average productivity
during the sample period. The result show that the cohort effects survive among most cohorts,
which suggests that an internal labor market at the case ironworks seems to have formed in
the 1930s. This statistical inference is consistent with the descriptive picture formed fromdocuments and interviews.6
INSERT Table 2 HERE
6

See Umezaki (2010), pp. 42–51.

10

As described by Baker, Gibbs and Holmstrom (1994b), the serial correlation of wage residuals is another useful indicator of an internal labor market.7 In a competitive market, we assume that the observable variables provide an unbiased forecast of wages. Then, the wage
residuals calculated by subtracting the wages estimated using the observable variables fromthe observed wages should be serially independent. If the firm more or less shields wage determination from the market using some wage policy, this result would be different. Here,
we use the following benchmark Mincerian specification in 3-1 in Table 3 to run a pooled
regression of log real wage (log(wt )) for Tenuret ≥ 1.
log(wt ) =Constant + α1 Schooli + α2 School2i + α3 Postwar · Schooli+ α4 PreExperience + α5 PreExperience2+ α6 PreEmployment + α7 PreEmployment2+ α8 Tenuret + α9 Tenure2+ α10 Training1927−35 + α11 Training1927−35 Tenuret+ α12 Training1935−48 + α12 Training1935−48 · Tenuret+ α13 Training1939−46 + α14 Training1939−46 · Tenuret+ α15 Training1946−73 + α16 Training1946−73 · Tenuret + ǫ(4)where Postwar denotes the postwar education generation dummy variable that takes 1 if theworker graduated in or after 1947; PreExperience denotes labor market experience before
joining the case firm, PreEmployment denotes employment experience before joining thecase firm, which does not include self-employment and working for a family-run business suchas farming; Training1927−1935 is a dummy variable for completing the firm-sponsored program, Development Center for Youth (1927–1935); Training1935−1948 denotes completing the
School for Youth program (1935–1948); Training1939−1946 denotes the Development Center
for Technician program (1939–1946); and Training1946−1973 denotes the Development Centerprogram (1946–1973). Then, we regress ŵTenuret , estimated by equation (4), for Tenuret ≥ 1,
on the independent variables in equation (4) and ŵt−1 . Here, the coefficient of ŵt−1 is significant, which indicates a serial correlation of wage residuals.8 The result is consistent with theassumption that the way the firm determined wages shielded the internal wage dynamics fromthe market.

4 Evolution of skill elements
4.1 Skill acquisition and wage growth
Table 3 provides the results after regressions after controlling for the random effect of log real
wage (log(wi,t )) on the constant (Constant), the relative height when employed by the com7

See Baker et al. (1994b), pp. 943–953.
The coefficient of ŵt−1 , 1.7109, has a t-statistic of 27.3944∗∗∗, adjusted R2 of 0.7389, and F -statistic of
3389.2152∗∗∗.
811

pany (height divided by the national average height for that age in the year joined, Heighti ),9age (Agei,t ), years of schooling (Schooli ), years of previous labor market experience before joining the company (PreExperience i ), years of previous employment experience (otherthan being self-employed or working in a family-operated business) (PreEmployment i ), theirsquared terms, the interaction terms of previous employment experience with the equivalentprevious industry dummy variable (EqIndustry i · PreEmployment i ) and with the equivalentprevious job dummy variable (EqJobi · PreEmployment i ), tenure at the company (Tenurei,t ),its squared term, the dummy variables for completing in-house training programs, (i.e., theDevelopment Center for Youth (Training1927−35), School for Youth (Training1935−48), Develi,ti,t1939−46
opment Center for Technicians (Trainingi,t), and Development Center (Training1946−73)
i,t
1927−35
programs), and the interaction of these dummy variables with tenure (Trainingi,t·Tenurei,t ,1935−48
1939−46
1946−73
Trainingi,t· Tenurei,t , Trainingi,t· Tenurei,t , Trainingi,t· Tenurei,t ).10 In addition, compulsory schooling was extended from six years to nine years in 1947. Since thisextension may have had an impact on productivity and wages (Oreopoulos (2005)), we include the interaction between the postwar education generation dummy variable and years ofschooling (Postwari · Schooli ). Then, our estimation model is as follows.
log(wi,t) =Constant + β1 Heighti + β2 Height2i + β3 Agei,t + β4 Age2i,t+ β5 Schooli + β6 School2i + β7 Postwari · Schooli+ β8 PreExperiencei + β9 PreExperience 2i+ β10 PreEmployment i + β11 PreEmployment 2i+ β12 EqIndustry i · PreEmployment i + β13 EqJobi · PreEmployment i(5)+ β14 Tenurei,t + β15 Tenure2i,t+ β16 Training1927−35+ β17 Training1927−35· Tenurei,ti,ti,t+ β18 Training1935−48+ β19 Training1935−48· Tenurei,ti,ti,t+ β20 Training1939−46+ β21 Training1939−46· Tenurei,ti,ti,t+ β22 Training1946−73+ β23 Training1946−73· Tenurei,t + µi + νi,ti,ti,tINSERT Table 3 HERE

Years of schooling (Schooli ) has a positive coefficient, indicating that it raised productivity and real wages. In specifications 3–2 and 3–4, relative height (Heighti ) has a positivecoefficient, showing that physical strength mattered in the steel industry. The positive coefficient of previous labor market experience (PreExperiencei ) indicates that work experienceraised productivity and was rewarded. In particular, the positive coefficient of the interaction between the equivalent industry dummy variable and previous employment experience9

To control for improved nutrition throughout the period, we use height relative to the national averageheight. Thus, we use (observed height)/(average height for a person’s age in that year, according to the Ministryof Education statistics) as “height (Heighti ).”10Note that the records of employees who joined the firm before 1939 lack information on physiologicalcharacteristics.

12

(EqIndustry i · PreEmployment i ) shows that acquiring industry-specific skills from previous
labor market experience significantly increased productivity.

4.2 Evolution of returns on skill elements
Since the time window of aforementioned benchmark results is the entire sample period,
the evolution of the emphasis on skill elements is not differentiated. To focus on intra-firmchanges in the returns on acquiring different skill elements, we need to control for highly
likely complementarity between the skill elements. To estimate the evolution of each skill element while factoring in potential complementarity between them, we assume a Translog work
function of workers as an approximation whose restriction on the substitutability between skill
elements is smaller than other specifications. We also reasonably assume that wages largely
reflect marginal labor productivity. Hence, using a logarithmic specification, we estimate alogarithmic wage formula as follows:log (wi,t ) =Constant + β1 x21,i,t · log2 (x1,i,t )+ β2 x2,i,t · log (x2,i,t ) + β3 x22,i,t · log2 (x2,i,t )+ β4 x3,i,t · log (x3,i,t ) + β5 x23,i,t · log2 (x3,i,t )(6)+ β6 x1,i,t · x2,i,t · log (x1,i,t ) · log (x2,i,t )+ β7 x1,i,t · x3,i,t · log (x1,i,t ) · log (x3,i,t )+ β8 x2,i,t · x3,i,t · log (x2,i,t ) · log (x3,i,t )+ γ1 Yearjoined1930−31 i · x1,i,t · log (x1,i,t )+ γ2 Yearjoined1932−33 i · x1,i,t · log (x1,i,t )+···+ γ19 Yearjoined1966−67 i · x1,i,t · log (x1,i,t ) + µi + νi,t ,where x1 is the element in interest of three elements, years of schooling (Schooli ), previous experience (PreExperiencei ), and tenure (Tenurei,t ); x2 and x3 denote the other two;
Yearjoined19XX−YY i denotes a two-year-joined dummy variable, which takes the value 1 ifworker i joined the case company in 19XX–19YY, with the cohort who joined the firm in
1928–1929 as the control group. While this specification differs from the standard Mincerian
type and, hence, its estimates cannot be directly compared with those in prior studies, it isstraightforward to track the intra-firm evolution along for cohorts by observing changes in thecoefficients of the interactions, γ1 , . . . , γ19 .
Table 4 shows the results by a standard Translog formula in specification 4-1, and thetwo-year-joined dummy variables are inserted in specification 4-2. As the coefficients of twoyear-joined dummy variables of specification 4-2 show, a rapid rise in wage, and hence, a
rapid increase in productivity over cohort is observed. We then decompose the increase overcohort.
INSERT Table 4 HERE
13

First, for the return on schooling, the results are reported in Table 5.
INSERT Table 5 HERE
The coefficients of the terms Yearjoined19XX−YY i · Schooli · log (Schooli ) in specification
5-1 indicate that the return on schooling slowly grew in the 1930s, then the growth accelerated
the 1948–1849 cohort. From 1947, compulsory schooling was extended from six years tonine years, and the supply of workers with more years of schooling increased exogenously.
Thus, the surging return on schooling from the late 1940s cannot be attributed to supply-side
constraints. Rather, the demand for better-educated labor increased.
Second, for the return on previous labor market experience, the results are reported inTable 6.
INSERT Table 6 HERE
Specification 6-1 shows that the return on previous labor market experience gradually
increased from the mid-1930s, and hit the peak in the mid-1950s, while it gained a little again
in the late 1960s. The result is consistent with the fact that the firm continuously recruited
experienced workers (Table 1)
Third, Table 7 shows the results for the return on tenure. The coefficients of the interactions of the two-year-joined dummy variable with tenure (Yearjoined19XX−YY i ·log (Tenurei,t + 1))
in specification 7–1 show an aggregate growth of the return on tenure during the period. This
growth began in the mid-1930s, which indicates that an internal labor market practice wasforme and the gain surged from the late 1950s-cohort. The surge disappears once we control
for the year dummy variables in specification 7–2. Thus the surge was plant-wide, including
both technological and organizational achievements.
INSERT Table 7 HERE
INSERT Figure 1 HERE
Figure 1 summarizes the results shown in Tables 5–7. In 1938, just after the invasionof China and before the attack on Pearl Harbor, the National General Mobilization Act, Act
55 of 1938, came into force, suspending the market economy. The act was repealed in 1946
after Japan’s defeat. Thus, between 1938 and 1945, Japan was a state-controlled economy inwhich wages were strictly regulated. Indeed, the returns on skill elements, measured by thecontributions to the growth in the real wage, were stable during the period as shown in Figure
1. A comparison of the periods before 1938 and after 1946 shows that the return on previous
work experience in the early stages of workers’ careers was surpassed by that on extended
schooling from the 1948–1949 cohort onwards. The return on schooling elevated from the
1948-1949 cohort nd that on tenure surged from the late 1950s cohorts.
These returns capture each year’s promotion in terms of basic wages. Assuming that theincrease in the return on tenure captures an increase in the firm-specificity of skills internallyacquired, we can conclude that the surge in the return on longer tenure combined with better
14

education is consistent with our prediction. Lemma 1 predicts that an increase in the firmspecificity of skill, k, is accompanied by a larger impact of schooling on wage promotion.
Also, Lemma 2 predicts that when the return on firm tenure increased, previous work experience was replaced by extended schooling as k increases. An increase in wage of worker i inyear t reflect in a major Japanese firm worker i’ promotion in wage notch in year t. Figure 1
show that as firm specific skills (tenure) was more rewarded, impact of schooling on promotion was more rewarded from the 1948-1949 cohort, being consistent with the predictions.
Next, we track evolution of complement of complementarity between skill elements. To
inquire the evolution of complementarity, we estimate the formula,log (wi,t ) =Constant + β1 x21,i,t · log2 (x1,i,t ) + β2 x21,i,t · log2 (x1,i,t )+ β3 x2,i,t · log (x2,i,t ) + β4 x22,i,t · log2 (x2,i,t )+ β5 x3,i,t · log (x3,i,t ) + β6 x23,i,t · log2 (x3,i,t )(7)+ β7 x1,i,t · x3,i,t · log (x1,i,t ) · log (x3,i,t )+ β8 x2,i,t · x3,i,t · log (x2,i,t ) · log (x3,i,t )+ γ1 Yearjoined1930−31 i · x1,i,t · x2,i,t · log (x1,i,t ) · log (x2,i,t )+ γ2 Yearjoined1932−33 i · x1,i,t · x2,i,t · log (x1,i,t ) · log (x2,i,t )+···+ γ19 Yearjoined1966−67 i · x1,i,t · x2,i,t · log (x1,i,t ) · log (x2,i,t ) + µi + νi,t ,where complementarity between skill elements x1 and x2 are in our interest and we focus on evolution of coefficients of their interactions with two-year-cohort dummy variables,
γ1 · · · γ19 .
Table 8 reports complementarity between tenure and schooling and Table 9 reports thatbetween tenure and previous labor market experience. In either case, complementarity gained
rapidly from the late 1940s cohorts. As specifications 8-2 and 9-2 in which year dummy
variables are controlled for show further modest increases, the increases complementarity
between tenure and schooling and tenure and previous labor market experience were companywide phenomenon. Given massive investment in new technologies in the 1950s and 1960s, thecomplementarity seems to be strengthened by technological changes through the period.
INSERT Table 8 HERE
INSERT Table 9 HERE
The summary is depicted in Figure 2. Thus, while own return on previous labor market
experience was largely dominated by that on schooling from the late 1940s cohorts, complementarity between previous labor market experience and tenure was not by that between
schooling and tenure.
As a result, the firm still actively poached skilled workers in terms of mid-career recruiting
until the end of 1960s, as shown in Table 1. Unless the first year of tenure strictly overwhelms
15that of general work experience as a preparation for entry-level training, an employer does not
exclusively seek new graduates. Presuming that a real intention to provide entry-level training
should appear in offers of in-house training programs to employees, we next focus on trainee
selection for in-house off-the-job training programs.

5 Changes in selection policy of training programs
5.1 Impact of education reform in 1947
Wage determination was not the only aspect to change over time, as the role of in-house training programs changed as well. Specifications 3–1 and 3–2 Table 3 show that the dummy
variables for completing the pre-war and wartime training programs, namely the Development Center for Youth (Training1927−35 ), School for Youth (Training1935−48 ) and Development Center for Technicians (Training1939−46 ), have a negative coefficient. However, thedummy variable for the postwar program, the Development Center (Training1946−73 ), has apositive coefficient.
Between the two periods, governmental regulations changed. The Cabinet Order on Training Programs for Youth in 1926 and the Cabinet Order on School for Youth in 1939 required that major firms provide training programs, namely the Development Center for Youth(Training1927−35 ) or School for Youth programs (Training1935−48 ). These programs included
second-level education for employees who had not graduated from a junior high school inorder to complement the public education system. This requirement was repealed in 1946 ascompulsory education was extended from six years to nine years including three years at ajunior high school, in 1947.
By the mid-1940s, while the training program completion dummies (Training1927−35 ,Training1935−48 , Training1939−46 ) have negative coefficients, interactions with tenure (Training1927−35 ·Tenurei,t , Training1935−1948 · Tenurei,t , Training1946−73 · Tenurei,t ) have positive coefficients.
This indicates that employees who were selected for training first compensated for the cost of
training by accepting reduced wages, and then earned the return on those skills during theirtenure. This scheme was reasonable given that the mid-career market was so flexible that thecost paid by the firm in advance might have resulted in a rather higher turnover.
From the late 1940s, with the ordinances being repealed, the training program completion
dummy variable (Training1946−73 ) has a positive coefficient, while the interaction with tenure(Training1946−73 · Tenurei,t ) has a negative coefficient. This indicates that the selected employees no longer compensated for the cost of training. Given that junior high school became
compulsory and was provided free by the state, this change makes sense.
Therefore, we can tentatively infer that the in-house training programs until the mid-1940s
were expected to complement the public education system under the governmental regulations,and that employees at least partly compensated for the cost themselves. However, any programfrom the mid-1940s onwards, after the regulation was abandoned, was provided as a firm’s
own program, and the cost was paid by the firm.
When relative contribution of skill elements to productivity change, this should be reflectedin training policies, the exact investment in employees’ skills, as well as wage in formulation,
16

which is a hedonic compensation to acquired skills.
Thus, it is likely that changes in the role of training were accompanied by changes intrainee selection. The latter changes would have reflected the management’s decisions on
those employees in which they chose to invest. Owing to the number of observations, we
restrict our analysis the to the School for Youth (Training1935−48 ) and Development Center(Training1946−73 ) programs. These two programs ran the longest, providing the most observations.

5.2 Pre-reform program
Tables 10 decomposes the probability of acceptance to the pre-reform in-house training program, School for Youth (Training1935−48 , from 1935 to 1948, into relative height (Heighti ),age (Age), years of schooling (School), previous labor market experience (PreExperience),and previous employment experience (Employmentpervious ), their squared terms, the dummy
variable for new graduate (New), which takes 1 if the employee was hired by the case firm immediately after graduation (PreExperience = 0) and 0 otherwise,11 and its interaction termswith years of schooling and relative height (New · School, New · Heighti ). Thus,(8)

Training =Constant + α1 Heighti + α2 Height2 + α3 Age + α4 Age2
+ α5 School + α6 School2 + α7 New + α8 New · School + α9 New · Heighti+ α10 PreExperience + α11 PreExperience2+ α12 PreEmployment + α13 PreEmployment 2 + ǫ,using a probit estimation. Assuming that selected employees joined the firm within three years
before the program began in 1935, or later, until the program ended, we include employees
who joined the firm between 1933 and 1948.
INSERT Table 10 HERE
Then, in all specifications (10–1, 10–2, and 10–3), years of schooling (School) has a negative coefficient, which is consistent with the regulatory constraint that the program provide
a substitute for public education for less educated employees. Further, in all specifications,relatively shorter employees (i.e., with smaller relative height, (Height)) were more likely tobe accepted as trainees. If both educational achievement and height can be assumed to be aproxy of ability, the pre-reform program regulated invested in less-educated and hence lessable employees, being regulated by the government ordinance.
At the same time, longer previous employment (PreEmployment) consistently has a positive coefficient. The pre-war and wartime program tended to invest in more experienced,
though less-educated and shorter employees. Thus, the firm tried to invest in better-skilledemployees within the allowance of regulation that required investment in less-educated employees.
11

Thus, NEWi = 1 does not mean that worker i was new graduate when accepted as a trainee, but mean thatworker i was immediately hired after graduation and thus PreExperience = 0 and PreEmployment = 0

17

Thus, the trainee selection policy was mainly inclusive and supportive of less advantaged
employees. In other words, it chose less educated employees and less physiologically advantaged employees. Among the employees who satisfied the regulatory constraints, thosewith more previous work experience were preferred, as they were expected to have acquired
general or industry-specific skills, were preferred.
Related to pervious experience, we now consider the new graduate dummy variable (New).
Contemporary major Japanese firms predominantly hire new graduates and less appreciate previous experience. In the case of the School for Youth program (Training1935−48 ), it seems as
if new graduates (New) were preferred in specification 7–2 in Table 7. However, consistently
positive coefficients of previous employment experience (PreEmployment) in all specifications 7–1, 7–2, and 7–3 show that previous experience, particularly in factories, was strongly
appreciated.
This apparently paradox is solved in Table 1. The entry of new graduates in the period
from 1935 to 1948 concentrated on the early 1940s as the war against China and the UnitedStates escalated, and males with better physiological characteristics were drafted. A possible
inference is that, to fill places, new graduates were hired, but experienced workers were preferred, if available. Further, to supplement the shortage of human capital in the new graduates,
the new graduates were more likely accepted as trainees.
Tables 11 presents the results of the equivalent specifications for the postwar program,
Development Center (Training1946−73 ) between 1946 and 1962. Here, we include cohorts
from year joined 1943 to year joined 1962. Since the program explicitly required a educational
level from 1963, namely, a high school graduate or higher (12 years or longer), we separate
the sample period at 1963. Then, in all specifications (i.e., 11–1, 11–2, and 11–3), years ofschooling (School) has a positive coefficient. Further, when relative height (Heighti ) has asignificant coefficient in specifications 11–1 and 11–3, it is positive. In contrast to the School
for Youth program (Training1935−48 ) in Table 10, the postwar program, which was free from
regulatory requirements, was more likely to invest in employees who possessed better humancapital before entering the labor market, such as physiological characteristics and education.
With regard to previous experience, both previous labor market experience (PreExperience)and previous employment experience (PreEmployment) have negative coefficients. The firm
began to invest more in the better-educated when the complementarity between schooling andtenure was enhanced and the regulatory restriction to do so was abandoned.
For new graduates (New), between 1946 and 1962, the interaction terms of the new graduate dummy variable with relative height and years of schooling (New · Heighti , New · School)
have a negative coefficient in specification 11–3 in Table 11. This indicates that the program
invested in new graduates whose physiological and schooling backgrounds were relatively inferior. Only with controlling for these aspects, new graduates were generally preferred, as
shown in specification 11–2.
INSERT Table 11 HERE
Tables 12 presents the results of the specifications from which years of schooling (School)
are dropped for the Development Center program (Training1946−73 ) between 1963 and 1969.
Here, the cohorts form year joined 1960 to year joined 1967 are included. From 1963, a high18

school graduate education level was a formal requirement to be accepted as a trainee. Specification 6-1 in Table 6 (Figure 1) shows that the return on previous labor market experience
gained from the 1962-1963 cohort. Indeed, previous labor market experience (PreExperience)turns out to have positive coefficients in all specifications, in contrast to the results shown in
Table 11. Here, the preference for experienced workers recovered slightly.
INSERT Table 12 HERE
Between 1963 and 1969, new graduates came to be preferred, in general, as shown in
specification in 12–2 in Table 12. Moreover, the interaction term between the new graduate
dummy variable and relative height (New · Heighti ) has a positive coefficient in specification
9–3. Thus, new graduates with an advantage in physiological characteristics, provided thatthey were high school graduates, were preferred as trainees for the first time.
Therefore, while an obvious preference for experienced employees disappeared from 1946,a preference for new graduates with better physical endowments became prominent in the
1960s for the first time. At the same time, a positive coefficient of previous labor market
experience (PreExpeirence) in all specifications (12–1, 12–2, and 12–3) in Table 12 showsthat, in contrast to the results for the late 1940s to the 1950s in Table 11, experienced workers became more sought after. Given that the labor shortage due to the rapid growth of theJapanese economy had become inexorable in the 1960s, it is possible that new graduates withgood physical and educational endowments were a second choice, with experienced workers
being preferred, if available.
At the same time, specification 12-3 shows that, when controlling for the interaction withrelative height, the new graduate dummy variable itself negatively affected the probabilityof acceptance as a trainee. With the return on previous experience ticking up after hitting
the bottom in the 1960s (Figure 1), if employees were better-educated but relatively shorter,
those with more previously experience were preferred as trainees. In that sense, the preference
for new graduates over those with experience was still limited, mainly to workers who were
better-educated and who were physiologically better endowed.

6 Discussion
The secondary school system in pre-war Japan, introduced from Europe, focused on traininga small group of elites. The system was then subsequently transformed, making a massive
investment in the human capital of the majority of the people (Ueshima, Funaba and Inoki(2006), pp. 72–73). The postwar junior high schools and most high schools provided general
education that teaches general cognitive skills, as opposed to vocational education, whichteaches specific skills.
The coefficient of the interaction between the postwar education dummy and years ofschooling (Postwar ·School) is positive (Table 3), which indicates that the return on schoolingincreased under the postwar education system, despite the rapid increase in the number ofbetter-educated workers. Indeed, the return on schooling continuously increases from the19

1948-1949 cohort. The enhanced role of schooling largely dominated the value of early career
experience before being employed by the plant in this case study (Figure 1).
The return on schooling rose from the late 1940s and the return on skill acquisition within
the company rapidly increased from the mid-1950s (Figure 1). Accompanying this trend, thefirm-sponsored training program from the late 1940s to the 1950s focused on employees who
were expected to have more talent, but who had less previous work experience. In particular,
the program selected those who were better-educated new graduates, as described in Table 11.
If the returns on skill elements estimated by observed wages reflect the productivity of eachelement, and if the training program is a complement to those skill elements, the shift in the
trainee selection policy should track that of the relative return on skill elements. The positive
impact of schooling and the negative impact of previous experience on the probability of being
accepted as a trainee from the late 1940s to the 1950s (Table 11) dovetail with the rinsing
return on schooling overwhelming that on previous experience during the same period (Figure1). This indicates that the firm altered its trainee selection policy in the most productive way
it was able to predict.
Furthermore, new graduates endowed with better physiological characteristics came tobe preferred as trainees, as the eligibility for trainees was limited to high school graduatesfrom 1963 (Table 12). The firm began to focus on physiologically advantaged new graduatesequipped with better education. However, as shown by results in Tables 10-12, the preference
only emerged in the 1960s in a contained manner for better-educated and employees endowedwith better physiological characteristics. It means that, as for a phenomenon specific forcontemporary Japanese major firms, the preference for new graduates never appeared only inthe 1960s. Thus, adhesion of contemporary major Japanese firms to new graduates was notcommon until the end of the 1960s, and if it came to be, it should not be earlier than the 1970s.
The fact that the return on schooling rose from the late 1940s and that on tenure rosefrom the mid-1950s as the return on previous experience became relatively behind suggeststhat general cognitive skills taught at school and specific skills acquired at the workplace
were complements. It was relatively commmon among developed economies after the Second
World War that education replaced work experience.12 Our case might also be placed in a
broader context of skill-biased growth in a “race between education and technology” (Goldin
and Katz (2008)) in developed economies, where a complementarity between education andexperience with advanced technology was observed. Such complementarity between schooling and experience has been widely observed in the postwar developed world.
Then a striking difference between the United States and Japan in the 1980s was that employers in Japan strongly preferred new graduates, which indicates that the complementarity
between schooling and firm-specific experience dominated that between schooling general orindustry experience. However, as shown in Figure 4, complementarity between schoolingand tenure and that between schooling and previous labor market experience never showeda distinctive gap until the end of the 1960s. In particular, previous experience in the same
industry was strongly rewarded as shown in Table 3. The characteristics and complementarityof skill elements earned at school and workplace in Japan by the end of the 1960s seems toshow little difference from those in the United States. While general or industry experience
12

See Dohmen, Kriechel and Phann (2004), pp. 218–219.

20

had been continuously complements of schooling, the relative return of tenure gained morefrom the mid-1950s than general or industry experience. This seems to be the primary reason
why Japanese firms tilted toward longer-term employment.
Over the last two decades, the Japanese labor market has become more flexible. This is
widely recognized, but there is some debate about the scope of the transformation. Someemphasize that long-term employment is still robustly prevalent, mainly focusing on existing
tenured workers. (Kato (2001); Shimizutani and Yokoyama (2009); and Ono (2010)) Others
believe that the change is structural, largely considering younger workers (Kawaguchi andUeno (2013)). The greater mobility of younger workers seems to support the latter observation. Our case study suggests that the coexistence of high mobility of younger workers andstable internal labor markets for experienced employees in major firms was the norm in Japan
until the end of the 1960s, as it was in the United States. Rising income inequality, widening
wage differentials between secondary education graduates and tertiary education graduates,and even greater mobility in the labor market as a whole have consistently increasing returns
on tenure for workers who have gained stable employment in the United States (Altonji andWilliams (2005)). Indeed, Speltzer (2015) shows that considerable chunk of wage inequality
in the United States has been generated by employees who work for large firms. This suggeststhat Japan, and probably the United States, are returning to the situation that prevailed prior to
the 1970s.

References
Abe, Yukiko, “A comparison of wage structures in the United States and Japan: Results fromcell mean regressions,” The Japanese Economic Review, Jun 2000, 51 (2), 252–267.
Altonji, Joseph G. and Charles R. Pierret, “Learning and statistical discrimination,” The
Quarterly Journal of Economics, Feb 2001, 116 (1), 313–350.
and Nicolas Williams, “Do wages rise with job seniority? A reassessment,” Industrial
and Labor Relations Review, Apr 2005, 58 (3), 370–397.
Aoki, Masahiko, Information, Incentives, and Bargaining in the Japanese Economy, Cambridge: Cambridge University Press, 1988.
Ariga, Kenn, Giorgio Brunello, and Yasushi Ohkusa, Internal Labor Markets in Japan,
Cambridge: Cambridge University Press, 2000.
, Yasushi Ohkusa, and Giorgio Brunello, “Fast track: is it in the genes?: The promotion theory of a large Japanese firm,” Journal of Economic Behavior & Organization,
Apr 1999, 38 (4), 385–402.
Baker, George, Michael Gibbs, and Bengt Holmstrom, “The internal economics of the firm:
Evidence from personnel data,” The Quarterly Journal of Economics, Nov 1994a, 109(4), 881–919.
21

,
, and
, “The wage policy of a firm,” The Quarterly Journal of Economics,
Nov 1994b, 109 (4), 921–955.
Beaudry, Paul and John DiNardo, “The effect of implicit contracts on the movement ofwages over the business cycle: Evidence from micro data,” The Journal of Political
Economy, August 1991, 99 (4), 665–688.
Ben-Ner, Avner, Fanmin Kong, and Stéphanie Lluis, “Uncertainty, task environment, andorganization design: An empirical investigation,” Journal of Economic Behavior & Organization, Apr 2012, 82 (1), 281–313.
DeVaro, Jed and Michael Waldman, “The signaling role of promotions: Further theory andempirical evidence,” Journal of Labor Economics, Jan 2012, 30 (1), 91–147.
Doeringer, Peter B. and Michael J. Piore, Internal Labor Markets and Manpower Analysis,
Lexington, MA: Heath Lexington Books, 1971.
Dohmen, Thomas J., Ben Kriechel, and Gerard A. Phann, “Monkey bars and ladders: The
importance of lateral and vertical job mobility in internal labor market careers,” Journalof Population Economics, Jun 2004, 17 (2), 193–228.
Farber, Henry S. and Robert Gibbons, “Learning and wage dynamics,” The Quarterly Journal of Economics, Nov 1996, 111 (4), 1007–1047.
Genda, Yuji, Ayako Kondo, and Souichi Ohta, “Long-term effects of a recession at labormarket entry in Japan and the United States,” Journal of Human Resources, Winter 2010,45 (1), 157–196.
Gibbons, Robert and Michael Waldman, “A theory of wage and promotion dynamics insidefirms,” The Quarterly Journal of Economics, Nov 1999, 114 (4), 1321–1358.
and, “Enriching a theory of wage and promotion dynamics inside firms,” Journalof Labor Economics, January 2006, 24 (1), 59–107.
Goldin, Claudia and Lawrence F. Katz, The Race Between Education and Technology, Cambridge, MA: The Belknap Press of Harvard University Press, 2008.
Hashimoto, Masanori and John Raisian, “Employment tenure and earnings profiles in Japanand the United States,” The American Economic Review, Sep 1985, 75 (4), 721–735.
Higuchi, Yoshio, “Effects of job training and productivity growth on retention of male andfemale workers in Japan,” in Toshiaki Tachibanaki, ed., Labour Market and Economic
Performance: Europe, Japan and the USA, St. Martin’s Press New York 1994, pp. 155–
182.
Hyatt, Henry and James Spletzer, “The shifting tenure distribution,” March 2015. presented
at Midwest Economic Association Annual Meeting 2015.
22

Kato, Takao, “The end of lifetime employment in Japan?: Evidence from national surveys
and field research,” Journal of the Japanese and International Economies, December
2001, 15 (4), 489–514.
Kawaguchi, Daiji and Yuko Ueno, “Declining long-term employment in Japan,” Journal of
the Japanese and International Economies, Jun 2013, 28, 19–36.
Kike, Kazuo, The Economics of Work in Japan, Tokyo: LTCB International Library Foundation, 1996.
Moriguchi, Chiaki, “Implicit contracts, the Great Depression, and institutional change: A
comparative analysis of U.S. and Japanese employment relations, 1920-1940,” The Journal of Economic History, Sep 2003, 63 (3), 625–665.
Nakamura, Naofumi, “Sengo Kamaishi seitetsujo ni okeru jukuren no saihen: hozen shokuba
no jirei (From apprenticeships to firm-specific skills: a case of the maintenance workshop
in the post-war Kamaishi Steel Works),” Shakai Kagaku Kenkyu (The Journal of Social
Science), Mar 2010, 61 (5-6), 3–26. Institute of Social Science, The University of Tokyo.
Nippon Tokei Kyokai (Japan Statistical Association), ed., Nippon Choki Tokei Soran (Historical Statistics of Japan), Vol. 4, Tokyo: Nippon Tokei Kyokai (Japan Statistical Association), 1988.
Ohkawa, Kazushi, Nobukiyo Takamatsu, and Yuzo Yamamoto, Choki Keizai Tokei 1
Kokumin Shotoku (Estimates of Long-term Economic Statistics of Japan since 1968, volume 7, National Income), Tokyo: Toyo Keizai Shinposha, 1974.
, Tsutomu Noda, Nobukiyo Takamatsu, Saburo Yamada, Minoru Kumazaki, Yuichi
Shinomiya, and Ryoshin Minami, Choki Keizai Tokei 8 Bukka (Estimates of Long-term
Economic Statistics of Japan since 1968, volume 8, Price Index, Tokyo: Toyo Keizai
Shinposha, 1967.
Ono, Hiroshi, “Lifetime employment in Japan: Concepts and measurements,” Journal of theJapanese and International Economies, Mar 2010, 24 (1), 1–27.
Oreopoulos, Philip, “Estimating average and local average treatment effects of education
when compulsory schooling laws really matter,” The American Economic Review, Mar
2005, 96 (1), 152–175.
Osterman, Paul, “Institutional labor economics, the new personnel economics, and internal
labor markets: A reconsideration,” Industrial and Labor Relations Review, Jul 2011, 64(4), 637–653.
Pfeifer, Chrsitian, “An empirical note on wages in an internal labor market,” Economics
Letters, Jun 2008, 99 (3), 570–573.
Pinkston, Joshua C., “A model of asymmetric employer learning with testable implications,”
The Review of Economic Studies, 2009, 76 (1), 367–394.
23

Rosen, Sherwin, “Transaction costs and internal labor markets,” The Journal of Law, Economics, & Organization, Spring 1988, 4 (1), 49–64.
Shimizutani, Satoshi and Izumi Yokoyama, “Has Japan’s long-term employment practicesurvived? Development since the 1990s,” Industrial and Labor Relations Review, Apr
2009, 62 (3), 313–326.
Speltzer, James, “Inequality statistics from the LEHD,” March 2015. presented at Midwest
Economic Association Annual Meeting 2015.
Sugayama, Shinji, “Recent developments in Japanese labour history,” Labour History, Nov
2014, (107), 211–220.
Ueshima, Yasuhiro, Takuji Funaba, and Takenori Inoki, “New technology and demand for
educated workers: The experience of Japanese manufacturing in the ear of high-speed
growth,” Journal of the Japanese and International Economies, Mar 2006, 20 (1), 50–76.
Umezaki, Osamu, “Keiei gorika to tokai tenshutsu: 1960 nendai ni okeru naibu rodo shijo
keisei no ichi sokumen (Restructuring of Kamaishi Iron and Steel Works and the transfer
of emoloyees to Tokai Iron and Steel Works: an analysis of the internal labour market
formation in the 1960s),” Shakai Kagaku Kenkyu (The Journal of Social Science), Mar
2010, 61 (5-6), 27–54. Institute of Social Science, The University of Tokyo.
Waldman, Michael, “Job assignments, signalling, and efficiency,” Rand Journal of Economics, Summer 1984, 15 (2), 255–267.
, “Asymmetric learning and the wage/productivity relationship,” Journal of Economic
Behavior & Organization, Dec 1996, 31 (3), 419–429.
, “Theory and evidence in internal labor markets,” in Robert Gibbons and John Roberts,
eds., The Handbook of Organizational Economics, Princeton University Press Princeton,
NJ 2013, pp. 520–569.

Appendix I: Data sources
Wages and workers’ characteristics

Original wage records of the case firm in Japan.

Series of national data Consumer prices (to deflate nominal wages): Nippon Tokei Kyokai(Japan Statistical Association), ed (1988), p.362. National average height: the School Health
Statistics surveyed by the Ministry of Education, Science, Sports and Culture (http://www.estat.go.jp/). Real gross national product: Ohkawa, Takamatsu and Yamamoto (1974), pp. 232(1885-1929) – 233 (1930–70); to connect series before and after 1955, when governmental
statistics are not continuous, a deflator from Ohkawa, Noda, Takamatsu, Yamada, Kumazaki,
Shinomiya and Minami (1967), p. 134, is used.

24

Appendix II Definition and descriptive statistics of variables.
Variablewi,tHeighti
Agei , t
Schooli
Postwari

PreExperiencei

Definition
Real daily wage of worker i in year t : yen per day.
Relative height of worker i when employed by the firm: (observedheight)/(national average height at his age in the year).
Age of worker i in year t .
Years of schooling of worker i .
Postwar education generation dummy variable: =1 if 12 years old or
younger in 1947, and 0 otherwise.
Years of previous labor market experience of worker i prior joining thefirm: Agei Schooli +Tenurei , t . Every sample employee had
worked at the firm until the last year of his record.

Years of previous employment experience of worker i with anotherPreEmploymenti employer prior joining the firm. Does not include self-employment or
employed by family business such as farming.

MeanMedian Maximum Minimum

3.57823.370072.0600

0.34001.96502.4475

Numberofobservations
66.7437
23,1200.99571.00001.10000.80000.0406-0.47506.6180

16,63730.5638 30.0000
8.7093 8.0000

55.0000
15.0000

13.0000
5.00008.1126
1.61940.3644
1.18812.54974.335623,12023,1200.18050.00001.00000.00000.3846

1.66153.760623,1206.36316.000035.0000

0.00005.1436

0.76893.439323,1202.70151.000025.0000

0.00003.55781.61946.1774

23,1200.00001.00000.00000.42151.27582.6277

23,1200.00001.00000.00000.34822.06105.2477

23,1200.00001.00000.00000.37851.72653.980923,1209.000037.7500

0.00006.93910.61562.751523,1200.00001.00000.00000.030832.3714 1,048.9100

23,1200.00001.00000.00000.20044.572021.9034

23,1200.00001.00000.00000.22054.070017.5646

23,1200.00001.00000.00000.33162.2577

6.097023,120=1 if worker i had engaged in an equivalent industry as the steel
0.2311making prior joining the firm, and 0 otherwise.
=1 if worker i had engaged in an equivalent job before joining the firm
EqJob i0.1412as the one after joining the firm, and 0 otherwise.
= 1 if PreExperience i =0 (employed by the case firm immediately afterNewi
0.1733
graduation).
Tenure of worker i in year t : (years after employed by the firm).
10.0591
Tenurei , t=1
if
workeri
hadcompleted
Development
Centerfor
Youth(operated0.0010Trainingi , t 1927 35
from 1927 to 1935), and 0 otherwise.
=1 if completed School for Youth (operated from 1935 to 1948), and 0
0.0419Trainingi , t 1935 48
otherwise.
=1 if completed Development Center for Technician (operated from0.0513Trainingi , t 1939 46
1939 to 1946), and 0 otherwise.
=1 if completed Development Center (operated from 1946 to 1973),
0.1257
Trainingi , t 1946 73
and 0 otherwise.
2-year-joined dummy variable: =1 if worker i joined the firm from
Yearjoinedi 19XX YY
19XX to 19YY(=19XX+1), and 0 otherwise.
Year dummy variable: =1 if t is 19XX, and 0 otherwise.
Yeart 19XX
GNPt
Real gross national product in year t .
Sources : See Appendix I.
EqIndustryiStandard
Skewness
deviation

Kurtosis

1929

1

8

0.00

1930

1

1931

0

na

na

na

8

8

2.00

2

2

na

na

na

na

na

na

na

na

na

1932

0

na

na

na

na

na

na

na

na

na

na

na

na

1933

4

102

8.00

8

8

8

1.45

1

3

1

0

0.00%

1934

2

54

6.85

6

8

6

7.56

5

11

5

0

0.00%

1935

5

141

8.82

8

12

8

2.95

1

7

0

2

40.00%

1936

7

152

8.00

8

8

8

5.97

6

9

0

1

14.29%

1937

7

191

8.00

8

8

8

6.22

7

13

0

1

14.29%

1938

18

494

7.63

8

8

6

4.85

5

12

0

5

27.78%

1939

41

1,030

7.94

8

9

6

4.95

5

12

0

7

17.07%

1940

40

1,001

7.95

8

13

6

5.02

5

13

0

10

25.00%

1941

47

1,094

8.30

8

14

6

4.63

5

13

0

15

31.91%

1942

29

652

8.04

8

13

6

3.86

1

16

0

13

44.83%

1943

27

611

8.25

8

13

6

3.38

0

17

0

14

51.85%

1944

22

493

7.97

8

13

6

3.24

1

14

0

11

50.00%

1945

17

379

8.25

8

11

6

0.00

0

0

0

17

100.00%

1946

17

342

8.00

8

8

8

1.52

0

23

0

14

82.35%

1947

12

225

8.00

8

8

8

0.08

0

1

0

11

91.67%

1948

291

5,548

8.79

8

14

5

9.04

8

23

0

10

3.44%

1949

271

4,845

8.94

8

14

6

7.96

8

21

0

16

5.90%

1950

37

619

9.00

9

13

6

4.49

0

18

0

19

51.35%

1951

53

873

8.44

8

13

6

8.34

8

14

3

0

0.00%

1952

7

105

8.16

8

9

8

5.85

6

7

4

0

0.00%

1953

13

154

9.00

9

9

9

2.00

2

2

2

0

0.00%

1954

20

239

9.79

9

12

9

1.47

2

2

0

5

25.00%

1955

13

144

9.00

9

9

9

2.25

2

10

2

0

0.00%

1956

96

1,014

8.87

9

12

7

7.47

7

20

1

0

0.00%

1957

72

662

9.06

9

12

6

6.32

6

17

0

6

8.33%

1958

29

223

9.00

9

9

9

2.52

2

8

1

0

0.00%

1959

90

616 10.25

9

13

8

3.52

2

15

0

9

10.00%

1960

47

274 10.20

9

12

8

3.79

2

25

0

16

34.04%

1961

41

173

9.56

9

15

9

3.40

2

13

0

4

9.76%

1962

87

299 10.66

12

12

9

1.30

2

11

0

46

52.87%

1963

47

121

8.98

9

15

7

7.50

2

35

0

5

10.64%

1964

17

87

8.78

8

12

8 19.34

20

34

2

0

0.00%

1965

11

34 12.00

12

12

12

0.12

0

1

0

10

90.91%

19669

20 12.00

12

12

12

0.40

0

1

0

6

66.67%

3277

33.33%
17.78%

8.00

28

8.00

8
8

8

0
2

0

0

0

100.00%0.00%

Compulsory education extended
to 9 years in 1947
Rapid growth began

9
19 10.63
11 12
9 5.37
5 10
0
total
1,558
23,120Notes : Previous labor market experience: Years after graduating school, before employed by the firm.

1

Engaged in a war with China from1937 and with US from 1941

1967

38

Nationwide
eventsTable 1 Employee numbers, years of schooling, and previous labor market experience across cohorts.
Number of employees
Years of previous
Number
who joined without
Years of schoolingNumberYear joined
experienceofprevious
experience(School)of(PreExperience)(Yearjoined 19XX) employees(PreExperience=0)
observations
who joinedmean median max min mean median max min number percentage
1928
1
24 11.00
11 11 11 4.00
4
4
4
0
0.00%

Table 2 Effect of cohort and tenure.
21
Estimation method

panel least squares

Dependent variable
Cross-section
Period (year)
Independent variables
Constant
Age
Age2
SchoolSchool2
PreExperiencelog(w )
pooledfixedcoefficient
0.40150.0265-0.0003
0.0077-0.0001
0.0079t -statistic
12.6557 ***38.4943 ***-28.1745 ***2.4334 ***-0.8124
18.3520 ***PreExperience2-0.0001-6.8631 ***EqInduistry･PreExperience

0.00064.2582 ***EqJob･PreExperience
TenureTenure2
Yearjoined1930 1931

0.00260.0270-0.0003-0.040915.7884 ***31.4127 ***-24.0801 ***-2.1629 **Yearjoined1932 1933

-0.0122-0.8738

1934 1935

-0.0337-2.5582 ***Yearjoined1936 1937

-0.0249-1.8765 ***Yearjoined

1938 1939

-0.0031-0.2297

Yearjoined

1940 1941

-0.0374-2.5985 ***Yearjoined1942 1943

-0.0676-4.3799 ***Yearjoined1944 1945

-0.1064-6.4599 ***Yearjoined1946 1947

-0.0987-5.5509 ***1948 1949

-0.1237-6.6356 ***Yearjoined1950 1951

-0.1656-8.2573 ***1952 1953

-0.1702-7.8270 ***Yearjoined1954 1955

-0.1783-7.8401 ***Yearjoined1956 1957

-0.2778-11.6143 ***1958 1959

-0.3129-12.2271 ***Yearjoined1960 1961

-0.3449-12.8475 ***1962 1963

-0.3685-13.0792 ***Yearjoined1964 1965

-0.2886-9.4658 ***Yearjoined1966 1967
ΔGNP
cross-sections included
periods included (years)
included observations
adjusted R2
F statistic-0.3244yes-9.1470 ***Yearjoined

Yearjoined
Yearjoined

Yearjoined
Yearjoined

15,55541 (1929-1969)
21,5620.980916,059.0766 ***Notes : Base year joined dummy is Yearjoined1928-1929. ***, **and * respectively denote significance at the 1, 5 and 10
percentage levels. Definitions of variables are in the Appendix
II.

Table 3 Wage regression on skill elements.
3-4
32
33
31
Estimation method
panel extended generalized least squares
Dependent variablelog(w )
log(w )
log(w )
log(w )
Cross-section
random effectrandom effectrandom effectrandom effect
Period (year)
pooledpooledpooledpooledIndependent variables
coefficient t -statistic coefficient t -statistic coefficient t -statistic coefficient t -statistic
Constant-1.1086 -15.2919 *** -1.5083 -20.6046 *** -5.8535 -8.2002 *** -5.8634 -8.2384 ***Height8.7897
6.1427 *** 8.8814
6.2251 ***-4.1843 -5.7989 *** -4.2335 -5.8843 ***Height2***
Age
0.0483 20.1647
0.0434 17.7904 *** 0.0428 17.5626 ***-0.0003 -10.1117 *** -0.0003 -10.8816 *** -0.0003 -10.6185 ***Age2***School0.1575 10.4665
0.10447.4003 *** 0.0686
4.1045 *** 0.0635
3.8064 ***
***
***
***
2
-0.0066 -8.5994-0.0043 -6.0954-0.0034 -4.0343-0.0031 -3.6720 ***School
*********0.0518 63.6035
0.0473 60.0136
0.0566 68.9749
0.0559 67.9409 ***Postwar･School
***
***
***
PreExperience
0.0445 27.7912
0.0171
8.92880.02469.68140.02439.6052 ***-0.0006 -7.8483 *** -0.0006 -7.1253 *** -0.0012 -10.5445 *** -0.0012 -10.5231 ***PreExperience2
PreEmployment
0.01186.2975 *** 0.0099
5.5158 *** -0.0023 -1.0863-0.0050 -2.3281 **-0.0005 -3.2176 *** -0.0006 -3.9732 *** 0.0004
2.4653 **0.00042.1151 **PreEmployment2
EqIndustry･PreEmployment
0.00988.6664 ***0.00886.9875 ******EqJob･PreEmployment-0.0100 -8.7973-0.0051 -3.8458 ***
***
***
***
Tenure0.1249 146.6286
0.0921 55.9905
0.1335 69.3851
0.1338 69.6463 ***
***
***
***
2
-0.0016 -49.0251-0.0014 -35.3995-0.0028 -51.0070-0.0028 -51.1972 ***Tenure-0.8003 -4.7392 *** -0.5415 -3.2635 ***Training1927 35
Training1927 35･Tenure

0.01771.9966 **0.0164

1.8474 *Training1935 48-0.1668-7.6702 ***-0.1603-7.5813 ***Training1935 48･Tenure

0.00866.4654 ***0.00745.5960 ***Training1939 46
Training1939 46･Tenure
Training

1946 73

-0.2406 -11.8359 ***-0.2086 -10.5107 ***0.013010.5580 ***0.01139.1412 ***0.1619***0.220319.1373 ***14.1057-0.0038 -3.6088 ** -0.0081 -7.5189 ***Training1946 73･Tenure
1,558
1,558
1,246
1,246
cross-sections included
41(1929-1969)
41(1929-1969)
31(1939-1969)
31(1939-1969)
periods included (years)
23,12023,120
16,637
16,637
included observations
2
0.77730.86510.77730.8648adjusted R
***
***
***
***
8,188.6402
7,114.6473
4,747.3652
F statistic
3,842.8808
Notes : ***, ** and * respectively denote significance at the 1, 5, and 10 percentage levels. The records of the employees
who had joined the firm before 1939 lack the information about somatic characteristics. Definitions of variables are in the
Appendix II.

Table 4 Increase in productivity orver cohorts.
41
4
panel extended generalized least squares
log(w )
log(w )
random effectrandom effectpooledpooledcoefficient t -statisticcoefficient t -statistic-3.3287-21.1050 ***-2.0365-9.1847 ***Constant***
0.358827.20240.01501.3354
School･log(School)***22-0.0061-22.3191-0.0003-1.2980
School ･log (School)
0.050918.1989 ***0.01497.0923 ***PreExperience･log(PreExperience1)20.00000.4088-0.0001-3.1363 ***PreExperience ･log (PreExperience1)***0.069549.2151
0.073752.7715 ***Tenure･log(Tenure1)
0.00000.02300.0000-1.8274 *Tenure･log2(Tenure1)***-0.0020-17.9749-0.0001-3.0843 ***School･(PreExperience+1)･log(School)･log(PreExperience+1)***
0.00024.20580.00058.9775 ***School･(Tenure+1)･log(School)･log(Tenure+1)***
0.000525.75590.000319.9373 ***PreExperience･Tenure･log(PreExperience1)･log(Tenure+1)
0.06030.1968
Yearjoined19301931
19321933
0.45582.0965 **Yearjoined
0.95904.7957 ***Yearjoined19341935
1.1732
6.1946 ***Yearjoined19361937
1.61388.9934 ***Yearjoined19381939
1.74249.7599 ***Yearjoined19401941
19421943
1.972410.9626 ***Yearjoined
2.143611.8052 ***Yearjoined19441945
2.558813.9164 ***Yearjoined19461947
2.9337
16.5406 ***Yearjoined19481949
3.224017.9733 ***Yearjoined19501951
19521953
3.521418.5996 ***Yearjoined
3.7767
20.3943 ***Yearjoined19541955
3.830821.4202 ***Yearjoined19561957
3.917221.7057 ***Yearjoined19581959
3.959821.6052 ***Yearjoined19601961
19621963
4.006021.7260 ***Yearjoined
5.142325.4822 ***Yearjoined19641965
5.311321.0628 ***Yearjoined19661967
Yes
Yes
ΔGNP
1,555
1,555
cross-sections included
periods included (years)
40 (19301969)
40 (19301969)
21,562
21,562
included observations
2
0.79250.8291adjusted R***
8,237.9679
3,607.4663 ***F statistic
19281929
Notes : Base year joined dummy variable is Yearjoined. *** and ** respectively denote significance at the 1 percentage level and at
5 percentage levels. Definitions of variables are in the Appendix II.

Estimation method
Dependent variable
Cross-section
Period (year)
Independent variables

Table 5 Increase in return on schooling over cohort: : Relative to the 19281929 cohort.
51
52
Estimation method
panel extended generalized least squares
Dependent variablelog(w )
log(w )
random effectCross-section
random effect
Period (year)
pooledpooledcoefficient t -statistic
Independent variables
coefficient t -statistic-0.2401-2.9088 ***-0.1235-1.6539 *Constant***
2
2-0.0024-16.9816-0.0005-3.5263 ***School ･log (School)
0.022011.0916 ***0.0241
16.1812 ***PreExperience･log(PreExperience1)***2-0.0001-2.6905-0.0001-4.7853 ***PreExperience ･log (PreExperience1)***0.068950.4746
0.032720.4203 ***Tenure･log(Tenure1)
0.0000-1.63270.0001
16.8872 ***Tenure･log2(Tenure1)***-0.0002-6.5166-0.0002-8.8189 ***School･(PreExperience+1)･log(School)･log(PreExperience+1)***
0.000714.2406
0.00000.8736
School･(Tenure+1)･log(School)･log(Tenure+1)
0.000318.3477 ***0.000214.9905 ***PreExperience･Tenure･log(PreExperience1)･log(Tenure+1)-0.0534-3.2581 ***-0.0190-1.4184
Yearjoined19301931･School･log(School)***
19321933-0.0294-2.89820.00140.1681
Yearjoined･School･log(School)*
19341935
0.01491.78230.0122
1.8125 *Yearjoined･School･log(School)
0.01191.52780.02113.3607 ***Yearjoined19361937･School･log(School)***
19381939
0.03825.51410.03776.6904 ***Yearjoined･School･log(School)
0.05277.7349 ***0.03796.7068 ***Yearjoined19401941･School･log(School)***
0.06399.23120.03836.5602 ***Yearjoined19421943･School･log(School)
0.075510.6078 ***0.03806.2153 ***Yearjoined19441945･School･log(School)
0.096013.0380 ***0.04787.4441 ***Yearjoined19461947･School･log(School)***
19481949
0.115017.49840.0483
7.9915 ***Yearjoined･School･log(School)
0.129019.3338 ***0.0445
7.0694 ***Yearjoined19501951･School･log(School)
0.145719.7443 ***0.04366.2701 ***Yearjoined19521953･School･log(School)***
19541955
0.152522.0998
0.03945.8039 ***Yearjoined･School･log(School)
0.157724.2151 ***0.02593.7844 ***Yearjoined19561957･School･log(School)
0.156723.7414 ***0.02112.9940 ***Yearjoined19581959･School･log(School)***
19601961
0.158123.34070.01652.2639 ***Yearjoined･School･log(School)
0.157823.2891 ***0.01391.8806 *Yearjoined19621963･School･log(School)
0.203526.6981 ***0.01852.3182 ***Yearjoined19641965･School･log(School)***
19661967
0.199821.8890-0.0009-0.1132
Yearjoined･School･log(School)
19XX
No
Yes
Year
Yes
No
ΔGNP
1,558
1,555
cross-sections included
periods included (years)
40 (19301969)
41 (19291969)
21,562
23,120included observations
2
0.82750.9170adjusted R
3,693.8861 ***
3,815.1013 ***F statistic
19281929
1930
Notes : Base year joined dummy variable is Yearjoined
and base year dummy variable is Year . *** and ** respectively denotesignificance at the 1 percentage level and at 5 percentage levels. Definitions of variables are in the Appendix II.

Table 6 Increase in return on previous labor market experience over cohort: Relative to the 19281929 cohort.
61
62
Estimation method
panel extended generalized least squares
Dependent variablelog(w )
log(w )
random effectCross-section
random effect
Period (year)
pooledpooledcoefficient t -statistic
Independent variables
coefficient t -statistic-1.9224-12.9003 ***-0.2209-2.1397 **Constant***
0.228218.07110.04625.4110 ***School･log(School)***22-0.0034-12.9612-0.0008-4.4186 ***School ･log (School)-0.0005-16.3725 ***-0.0002-13.1286 ***PreExperience･log2(PreExperience1)***0.072179.5556
0.042057.2992 ***Tenure･log(Tenure1)
0.00001.31440.0001
12.4780 ***Tenure･log2(Tenure1)***-0.0021-20.1363-0.0003-4.4156 ***School･(PreExperience+1)･log(School)･log(PreExperience+1)*
0.00001.76000.00002.9284 ***School･(Tenure+1)･log(School)･log(Tenure+1)***
0.000634.02770.000214.6292 ***PreExperience･Tenure･log(PreExperience1)･log(Tenure+1)-0.6645-7.1871 ***-0.3565-5.8954 ***Yearjoined19301931･(PreExperience+1)･log(PreExperience+1)***
19321933-0.5375-10.3200-0.2346-6.8671 ***Yearjoined･(PreExperience+1)･log(PreExperience+1)-0.0331-3.8923 ***-0.0109-1.9632 **Yearjoined19341935･(PreExperience+1)･log(PreExperience+1)-0.0211-3.8496 ***0.00080.2165
Yearjoined19361937･(PreExperience+1)･log(PreExperience+1)
19381939
0.00250.68840.01656.9015 ***Yearjoined･(PreExperience+1)･log(PreExperience+1)
0.01193.5602 ***0.01908.7837 ***Yearjoined19401941･(PreExperience+1)･log(PreExperience+1)***
0.03559.53070.0287
11.8595 ***Yearjoined19421943･(PreExperience+1)･log(PreExperience+1)
0.03997.6444 ***0.0282
8.3177 ***Yearjoined19441945･(PreExperience+1)･log(PreExperience+1)
0.0772
14.5460 ***0.0451
12.9826 ***Yearjoined19461947･(PreExperience+1)･log(PreExperience+1)***
19481949
0.066923.6323
0.036219.1608 ***Yearjoined･(PreExperience+1)･log(PreExperience+1)
0.078525.4947 ***0.0366
17.6176 ***Yearjoined19501951･(PreExperience+1)･log(PreExperience+1)
0.117712.4495 ***0.04797.7020 ***Yearjoined19521953･(PreExperience+1)･log(PreExperience+1)***
19541955
0.1871
12.15480.05455.2811 ***Yearjoined･(PreExperience+1)･log(PreExperience+1)
0.093731.8980 ***0.026512.8000 ***Yearjoined19561957･(PreExperience+1)･log(PreExperience+1)
0.109524.7037 ***0.0171
5.5738 ***Yearjoined19581959･(PreExperience+1)･log(PreExperience+1)***
19601961
0.095023.5733
0.02208.0193 ***Yearjoined･(PreExperience+1)･log(PreExperience+1)
0.103224.1525 ***0.0294
10.5724 ***Yearjoined19621963･(PreExperience+1)･log(PreExperience+1)
0.113628.9626 ***0.040715.2521 ***Yearjoined19641965･(PreExperience+1)･log(PreExperience+1)***
19661967
0.192111.7046
0.01131.2384
Yearjoined･(PreExperience+1)･log(PreExperience+1)
19XX
No
Yes
Year
Yes
No
ΔGNP
1,555
1,558
cross-sections included
periods included (years)
41 (19291969)
40 (19301969)
21,562
23,120included observations
0.81160.9155adjusted R2
3,318.9535 ***3,738.3985 ***F statistic
19281929
1930
and base year dummy variable is Year . *** and ** respectively denote
Notes : Base year joined dummy variable is Yearjoined
significance at the 1 percentage level and at 5 percentage levels. Definitions of variables are in the Appendix II.

Table 7 Increase in return on tenure over cohort: Relative to the 19281929 cohort.
71
72
Estimation method
panel extended generalized least squares
Dependent variablelog(w )
log(w )
random effectCross-section
random effect
Period (year)
pooledpooledcoefficient t -statistic
Independent variables
coefficient t -statistic-0.7400-5.5678 ***0.12291.2069Constant
0.147013.0185 ***0.0253
2.9772 ***School･log(School)***22-0.0024-10.1083-0.0003-1.5563
School ･log (School)
0.035314.6048 ***0.0221
12.6917 ***(PreExperience+1)･log(PreExperience+1)-0.0001-3.1366 ***-0.0001-4.8324 ***PreExperience･log2(PreExperience1)***20.000448.04230.000333.8665 ***Tenure ･log (Tenure1)-0.0010-10.2214 ***-0.0002-3.3884 ***School･(PreExperience+1)･log(School)･log(PreExperience+1)***
0.00062.87600.00053.5333 ***School･(Tenure+1)･log(School)･log(Tenure+1)***
0.0001
3.94860.00015.4598 ***PreExperience･Tenure･log(PreExperience1)･log(Tenure+1)-0.0023-0.72100.0037
1.5795
Yearjoined19301931･(Tenure+1)･log(Tenure+1)***
19321933
0.0134
7.62790.0152
11.1974 ***Yearjoined･(Tenure+1)･log(Tenure+1)
0.01308.5243 ***0.015613.2135 ***Yearjoined19341935･(Tenure+1)･log(Tenure+1)***
19361937
0.020816.01770.019919.7499 ***Yearjoined･(Tenure+1)･log(Tenure+1)
0.031431.7209 ***0.026434.0617 ***Yearjoined19381939･(Tenure+1)･log(Tenure+1)
0.035938.5000 ***0.027738.7364 ***Yearjoined19401941･(Tenure+1)･log(Tenure+1)***
19421943
0.042643.59990.030641.4980 ***Yearjoined･(Tenure+1)･log(Tenure+1)
0.047343.5208 ***0.030537.3040 ***Yearjoined19441945･(Tenure+1)･log(Tenure+1)
0.057641.2480 ***0.035534.0143 ***Yearjoined19461947･(Tenure+1)･log(Tenure+1)***
19481949
0.064778.9103
0.039859.0901 ***Yearjoined･(Tenure+1)･log(Tenure+1)
0.071261.7984 ***0.042044.1548 ***Yearjoined19501951･(Tenure+1)･log(Tenure+1)
0.082728.3621 ***0.047121.4295 ***Yearjoined19521953･(Tenure+1)･log(Tenure+1)***
19541955
0.090534.5982
0.051625.4118 ***Yearjoined･(Tenure+1)･log(Tenure+1)
0.102859.6157 ***0.049629.3460 ***Yearjoined19561957･(Tenure+1)･log(Tenure+1)***
0.129439.09200.051217.3555 ***Yearjoined19581959･(Tenure+1)･log(Tenure+1)
0.155727.0473 ***0.050310.3875 ***Yearjoined19601961･(Tenure+1)･log(Tenure+1)
0.210124.0535 ***0.04485.9517 ***Yearjoined19621963･(Tenure+1)･log(Tenure+1)***
19641965
0.338225.13130.08407.6871 ***Yearjoined･(Tenure+1)･log(Tenure+1)
0.5066
12.1183 ***-0.0115-0.3763
Yearjoined19661967･(Tenure+1)･log(Tenure+1)
19XX
No
Yes
Year
Yes
No
ΔGNP
1,555
1,558
cross-sections included
periods included (years)
41 (19291969)
40 (19301969)
21,562
23,120included observations
2
0.83170.9149adjusted R
3,807.3085 ***3,710.5758 ***F statistic
19281929
1930
and base year dummy variable is Year . *** and ** respectively denote
Notes : Base year joined dummy variable is Yearjoined
significance at the 1 percentage level and at 5 percentage levels. Definitions of variables are in the Appendix II.

Table 8 Increase in complementarity between schooling and tenure over cohort: Relative to the 19281929 cohort.
81
82
Estimation method
panel extended generalized least squares
Dependent variablelog(w )
log(w )
random effectCross-section
random effect
Period (year)
pooledpooledcoefficient t -statistic
Independent variables
coefficient t -statistic-0.7147-5.3718 ***0.18411.7644
Constant
0.1570 14.1547 ***0.01802.0957 **School･log(School)***22-0.0030 -13.1874-0.0003-1.4749
School ･log (School)
0.0416 17.6357 ***0.0257 14.7527 ***(PreExperience+1)･log(PreExperience+1)-0.0001-4.2056 *** -0.0001-7.8192 ***PreExperience･log2(PreExperience1)***0.0442 33.2653
0.0329 32.2761 ***(Tenure+1)･log(Tenure+1)***
0.0003 34.4519
0.0002 16.3585 ***Tenure･log2(Tenure1)-0.0013 -13.4006 *** -0.0003-4.2532 ***School･(PreExperience+1)･log(School)･log(PreExperience+1)***
0.0002 13.5716 ***0.0002 12.9293
PreExperience･Tenure･log(PreExperience1)･log(Tenure+1)-0.0023 -12.7262 *** -0.0009-6.6037 ***Yearjoined19301931･School･(Tenure+1)･log(School)･log(Tenure+1)-0.0014 -14.1534 *** -0.0003-3.8211 ***Yearjoined19321933･School･(Tenure+1)･log(School)･log(Tenure+1)***
19341935-0.0013 -16.1102-0.0003-4.6720 ***Yearjoined･School･(Tenure+1)･log(School)･log(Tenure+1)-0.0011 -14.4269 *** -0.0002-2.8314 ***Yearjoined19361937･School･(Tenure+1)･log(School)･log(Tenure+1)***-0.0005-7.89520.00013.3303 ***Yearjoined19381939･School･(Tenure+1)･log(School)･log(Tenure+1)-0.0002-3.3392 ***0.00023.9402 ***Yearjoined19401941･School･(Tenure+1)･log(School)･log(Tenure+1)
0.00011.61800.0002
4.2362 ***Yearjoined19421943･School･(Tenure+1)･log(School)･log(Tenure+1)***
19441945
0.00045.48240.00012.7841 ***Yearjoined･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0010 10.5859 ***0.00034.9687 ***Yearjoined19461947･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0012 24.2901 ***0.0004 11.7657 ***Yearjoined19481949･School･(Tenure+1)･log(School)･log(Tenure+1)***
19501951
0.0015 22.4592
0.00048.4595 ***Yearjoined･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0023 14.2097 ***0.00075.7786 ***Yearjoined19521953･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0023 18.7990 ***0.00077.3932 ***Yearjoined19541955･School･(Tenure+1)･log(School)･log(Tenure+1)***
19561957
0.0031 33.5910
0.00055.3737 ***Yearjoined･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0042 27.4714 ***0.00032.3007 **Yearjoined19581959･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0049 20.5819 ***0.00000.1727
Yearjoined19601961･School･(Tenure+1)･log(School)･log(Tenure+1)*****
19621963
0.007920.5453-0.0008-2.4320
Yearjoined･School･(Tenure+1)･log(School)･log(Tenure+1)
0.0140 22.9747 ***0.0000-0.0708
Yearjoined19641965･School･(Tenure+1)･log(School)･log(Tenure+1)******
19661967
0.017211.7515-0.0049-4.6319
Yearjoined･School･(Tenure+1)･log(School)･log(Tenure+1)
No
Yes
Year19XX
Yes
No
ΔGNP
1,555
1,558
cross-sections included
periods included (years)
40 (19301969)
41 (19291969)
21,562
23,120included observations
0.82390.9147
adjusted R2
3,603.9462 ***3,701.8498 ***F statistic
19281929
1930
Notes : Base year joined dummy variable is Yearjoined
and base year dummy variable is Year . *** and ** respectively
denote significance at the 1 percentage level and at 5 percentage levels. Definitions of variables are in the Appendix II.

Table 9 Increase in complementarity between previous experience and tenure over cohort: Relative to the 19291930 cohort.
91
92
Estimation method
panel extended generalized least squares
Dependent variablelog(w )
log(w )
random effectCross-section
random effect
Period (year)
pooledpooledIndependent variables
coefficient t -statistic coefficient t -statistic-2.4988 -16.7853 ***0.0023 0.0215
Constant
0.2897 23.2657 ***0.0298 3.4155 ***School･log(School)***22-0.0046 -18.0405-0.0005 -2.7879 ***School ･log (School)
0.0554 20.6679 ***0.0272 15.3142 ***(PreExperience+1)･log(PreExperience+1)***

2-0.0003 -11.1455-0.0002 -11.8419 ***PreExperience ･log (PreExperience1)***0.0629 45.0056
0.0369 35.8491 ***(Tenure+1)･log(Tenure+1)
0.0002 18.9520 ***0.0001 15.5880 ***Tenure･log2(Tenure1)***-0.0020 -18.9012-0.0002 -2.3014 **School･(PreExperience+1)･log(School)･log(PreExperience+1)-0.0001 -1.0828
0.0002 4.6112 ***School･(Tenure+1)･log(School)･log(Tenure+1)***
19301931-0.0050 -7.4148 ***Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) -0.0119 -12.0854***-0.0020 -5.5210 ***Yearjoined19321933･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) -0.0059 -11.0985***-0.0004 -5.5485 ***Yearjoined19341935･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) -0.0013 -12.8839***
19361937-0.0002 -4.0925 ***Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) -0.0008 -13.1055***
0.0001 2.5163 **Yearjoined19381939･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) -0.0003 -8.0321***
0.0001 3.2341 ***Yearjoined19401941･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) -0.0001 -2.7406***
19421943
0.0002 6.8971 ***Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0003 6.2565***
0.0002 3.2278 ***Yearjoined19441945･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0004 5.1956***
0.0006 8.4580 ***Yearjoined19461947･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0009 8.3173***
19481949
0.0002 17.7132 ***Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0007 38.1278***
0.0003 7.6011 ***Yearjoined19501951･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0011 21.1810***
0.0006 3.1040 ***Yearjoined19521953･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0024 8.2233***
19541955
0.0010 2.2133 **Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0051 7.8316***
0.0001 1.4485
Yearjoined19561957･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0017 24.2455***
19581959
0.004413.5121-0.0005-2.1913 **Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1)***-0.0006 -2.9520 ***Yearjoined19601961･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0029 9.5495***-0.0004 -1.0094
Yearjoined19621963･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0075 12.4232***
19641965
0.005521.60520.0007 3.9762 ***Yearjoined･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1)***-0.0082 -2.1410 **Yearjoined19661967･(PreExperience+1)･(Tenure+1)･log(PreExperience+1)･log(Tenure+1) 0.0404 7.4237
No
Yes
Year19XX
Yes
No
ΔGNP
1,555
1,558
cross-sections included
periods included (years)
40 (19301969)
41 (19291969)
21,562
23,120included observations
2
0.81000.9144
adjusted R******
3,284.2079
3,687.0667
F statistic
19281929
1930
Notes : Base year joined dummy variable is Yearjoined
and base year dummy variable is Year . *** and ** respectively denotesignificance at the 1 percentage level and at 5 percentage levels. Definitions of variables are in the Appendix II.

Table 10 Probability of acceptance as a trainee for in-house training program School for Youth operated from 1935 to 1948.
102
103
101
Estimation method
binary probit
binary probit
binary probit
193548
Dependent variable Training193548
Training
Training193548
marginal
marginal
marginal
Independent variables coefficient z -statisticcoefficient z -statisticcoefficient z -statistic
effecteffecteffectConstant
54.4974 1.8714 *
48.8714 1.3020
54.6225 1.4524
Height-152.8145 -2.7186 *** 0.0000 -216.0014 -3.0201 *** 0.0000 -232.7837 -3.2121 *** 0.0000
77.1701 2.6980 ***108.8846 3.0061 ***116.2232 3.1844 ***Height2******Age2.3430 3.0105
0.00004.7747 3.4795
0.00005.0191 3.5010 *** 0.0000-0.0481 -2.7576 ***-0.0953 -3.2607 ***-0.1003 -3.2881 ***Age2School-1.4325 -2.3921 ** 0.0000-2.2741 -2.8979 *** 0.0000-2.2264 -2.7590 *** 0.0000*****
20.0710 2.3256
0.1124 2.8565
0.1101 2.7287 ***School***New
13.3524 3.4498
0.00009.4774 1.3058
0.0000
New･Height
5.9065 1.0706
New･School-0.1457 -0.3484
PreExperience-0.6688 -3.3064 *** 0.0000
1.3710 1.9179 * 0.0000
1.4897 2.0225 ** 0.0000
PreExperience2
PreEmployment20.02742.2734 **0.50522.5301 ***0.0000-0.0929-2.1609 **1.38851.8026 **0.0000-0.0995-2.2518 **1.35981.8194 **0.0000-0.0324 -1.7852-0.1140 -1.6963-0.1112 -1.7096
PreEmployment
493
493
493
total observations
period193548
193548
193548
cohort (Year joined)
193248
193248
193248
observations with25
25
25
dependent variable =1-70.8110-51.2832-50.5876
log likelihood
20.28400.48140.4885
McFadden R******
56.1700
95.2255
96.6167 ***LR statistic
Notes : Marginal effects are calculated by mean values of independent variables. ***, ** and * respectively denotesignificance at the 1, 5 and 10 percentage levels. Note that Height is the relative height to the national average. Definitions ofvariables are in the Appendix II.

Table 11 Probability of acceptance as a trainee for in-house training program School for Youth operated from 1946 to 1962.
112
113
111
Estimation method
binary probit
binary probit
binary probit
194673
Dependent variable Training194673
Training
Training194673
marginal
marginal
marginal
Independent variables coefficient z -statisticcoefficient z -statisticcoefficient z -statistic
effecteffecteffectConstant-35.7230 -7.3387 ***-13.5221 -2.7373 ***-35.7220 -5.5084 ***Height32.0055 3.3086 *** 1.0414-0.4086 -0.0418-0.0080
36.9066 2.9943 *** 1.5780-14.0605 -2.8660 ***1.4951 0.3011-15.4298 -2.5559 **Height2*****Age
0.0733 2.2888
0.00240.1345 3.9795
0.00260.1360 3.9746 *** 0.0058-0.0025 -3.8743 ***-0.0035 -5.1041 ***-0.0035 -5.1126 ***Age2School
4.0505 19.6932 *** 0.1318
3.0802 15.3184 *** 0.0600
3.3796 14.7371 *** 0.1445
***
***
2
-0.2254 -21.1101-0.1801 -17.2033-0.1916 -16.5875 ***School***New-1.6810 -19.3132-0.01516.3652 4.9452 *** 0.0005
New･Height-6.3390 -5.3334 ***New･School-0.1905 -3.2918 ***PreExperience-0.4218 -25.8720 *** -0.0137-0.8173 -29.3032 *** -0.0159-0.7933 -27.4783 *** -0.0339
PreExperience2
PreEmployment

0.0196 17.3620 ***0.0371 26.7257 ***-0.2299 -11.2626 *** -0.0075-0.1635-7.1300 *** -0.0032

0.0364 25.4694 ***-0.1619-7.0128 *** -0.0074

0.0115 8.4030 ***0.0055 3.9647 ***0.0054 3.9023 ***PreEmployment2
12,077
12,077
12,077
total observations
period194662
194662
194662
cohort (Year joined)194362
194362
194362
observations with
1649
1649
1649
dependent variable =1-2,352.9986-2,153.8561-2,131.9518
log likelihood
20.51120.5526
0.5572
McFadden R******
4,922.5964
5,320.8813
5,364.6898 ***LR statistic
Notes : Marginal effects are calculated by mean values of independent variables. ***, ** and * respectively denotesignificance at the 1, 5 and 10 percentage levels. Note that Height is the relative height to the national average. Definitions ofvariables are in the Appendix II.

Table 12 Probability of acceptance as a trainee for in-house training program School for Youth operated from 1963 to 1969.
122
123
121
Estimation method
binary probit
binary probit
binary probit
194673
Dependent variable Training194673
Training
Training194673
marginal
marginal
marginal
Independent variables coefficient z -statisticcoefficient z -statisticcoefficient z -statistic
effecteffecteffectConstant
20.7083 0.5032
15.1367 0.3634
76.5089 1.6463 *Height-45.4600 -0.5911
0.0000 -48.1758 -0.6222
0.0000 -151.1421 -1.7898 * 0.0000
20.1208 0.5403
21.6305 0.5767
65.0476 1.6211
Height2Age0.5945 0.6082
0.00000.8995 0.8563
0.00000.7452 0.6492
0.00002-0.0193 -0.8340-0.0266 -1.0631-0.0236 -0.8601
Age
**
New
3.5972 2.1557
0.0000 -16.2044 -2.4917 ** 0.0000
New･Height
19.8444 3.0817 *********PreExperience
3.1758 8.8440
0.00006.8434 3.4471
0.00007.6158 3.3360 *** 0.0000-0.8512 -5.6465 ***-1.7346 -3.0501 ***-1.9644 -3.0041 ***PreExperience2
PreEmployment2-0.4173-0.16530.00000.93970.01170.00000.96430.00200.0000-0.3000 -0.2494-0.9272 -0.0231-1.0338 -0.0044
PreEmployment
581
581
581
total observations
period196319691963196919631969
cohort (Year joined)196019671960196719601967
observations with
328
328
328
dependent variable =1-132.0007-129.2931-124.2776
log likelihood
0.66820.67500.6876
McFadden R2
531.7270 ***537.1421 ***547.1732 ***LR statistic
Notes : Marginal effects are calculated by mean values of independent variables. ***, ** and * respectively denotesignificance at the 1, 5 and 10 percentage levels. Note that Height is the relative height to the national average. Definitions ofvariables are in the Appendix II.

Figure 1 Return on schooling, previous experience, and tenure.
0.6
Return on schooling (5-1)

Return on previous experience (6-1)

Return on tenure (7-1)

0.5

0.4

γ

0.3

0.2

0.1

0.0

1966--1967

1964--1965

1962--1963

1960--1961

1958--1959

1956--1957

1954--1955

1952--1953

1950--1951

1948--1949

1946--1947

1944--1945

1942--1943

1940--1941

1938--1939

1936--1937

1934--1935(0.1)

Cohort: Year joined

Note: Control cohort: joined in 1928-1929.

Figure 2 Complementarity of schooling with previous experience and tenure.
0.05
Complementarity between tenure and schooling (8-1)

Complementarity between tenure and previous experience (9-1)

0.04

0.02

0.01
0 01

0.00

1966-1967

1964-1965

1962-1963

1960-1961

1958-1959

1956-1957

1954-1955

1952-1953

1950-1951

1948-1949

1946-1947

1944-1945

1942-1943

1940-1941

1938-1939

1936-1937-0.01
1934-1935γ

0.03

Cohort: Year joined

Note: Control cohort: joined in 1928-1929.