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I
was born in New York City in 1926, four years after my parents and my
brother migrated to the United States from the city of Odessa in Russia.
Although they arrived in New York penniless, my parents scraped together
enough savings to establish the first of several small businesses just
after I was born. Despite the hard times of the Great Depression and the
modest financial circumstances in which we lived, they created a joyful
household and they encouraged my brother and me to be optimistic about
the future.
My parents' reverence for learning encouraged both my brother and me toward
academic pursuits. In many ways, however, it was my brother who was the
main intellectual influence on me until he joined the armed forces in
1941. Almost six years my senior in age and nine years ahead of me in
school, he inspired me with his intellectual brilliance. I still remember
the intense discussions by my brother and his college classmates about
the social and economic issues of the Depression that I overheard as I
lay in my bed, supposedly asleep, in the next room.
My education in the public schools of New York City between 1932 and 1944
was an excellent preparation for a life in science. Because of the Depression,
these schools were able to attract a remarkably talented and dedicated
collection of teachers who encouraged their students to strive for the
highest levels of accomplishment. That environment led me to aspire to
a career in science, and also kindled my love for literature and history.
My professional training
began at Cornell University (BA 1948) and continued at Columbia University
where I obtained my MA (1960), and at Johns Hopkins University, where
I obtained my Ph.D. (1963). It was at Cornell that my scientific interests
shifted from physics and chemistry to economics and history. The switch
in focus was precipitated by the widespread pessimism about the future
of the economy during the second half of the 1940s, when forecasts about
the imminent return to the massive unemployment of the Great Depression
were rife.
I began my graduate training with the naive belief that by combining the
study of history and economics I would quickly discover the fundamental
forces that had determined technological and institutional changes over
the ages and that such knowledge would point to solutions to the current
problems of economic instability and inequity. As I became aware of how
little was actually known about these large processes and their interconnections,
I began to focus on more discrete issues: What did we really know about
the role of the factory system in economic and institutional change during
the nineteenth century? What was the nature and the magnitude of the contribution
of particular new technologies, such as railroads or steel mills, to economic
growth? I also concluded that to answer such questions, much greater use
had to be made of quantitative evidence, so I set out to master the most
advanced analytical and statistical methods that were then taught in the
economics department. It was only later that I discovered that the training
program I had worked out for myself was unorthodox for an economic historian.
The two teachers who influenced me the most during my year at Columbia
were George J. Stigler, who taught the graduate microeconomics sequence,
and Carter Goodrich, who taught the sequence in American economic history.
Stigler made microeconomic theory come alive. He emphasized not its elegance
but its applicability to a wide range of issues in economic policy. He
continually moved between theory and evidence, carefully considering the
empirical validity for the assumptions that theorists made about the slope
or other aspects of the shape of key functions. He often considered when,
with what model, and under what implicit assumptions one could draw a
particular inference from a given body of data.
Goodrich impressed me not only with his knowledge of the literature of
American economic history, but with his willingness to identify the gaps
in the profession's collective knowledge of key issues. By the end of
the course one not only had a good grasp of what was known about the process
of American economic growth, but a list of potential projects. It was
to Goodrich that I turned for advice on my master's thesis. He was then
engaged in research for his book, Government Promotion of Canals and Railroads
and raised a number of issues that puzzled him about the financing, riskiness,
and benefits of the Union Pacific Railroad. These questions became the
subject matter of my master's thesis, which was also my first published
book. Although Goodrich did not himself make use of the new mathematical
and statistical methods of economics, he encouraged me to do so. He also
suggested that, given my substantial interests and quantitative approaches
to economic history, Simon Kuznets at Johns Hopkins was probably the best
economist to guide my future training.
The teachers who
taught me the most at Johns Hopkins, aside from Simon Kuznets, were Abba
Lerner and Fritz Machlup in microeconomic theory; Evsey Domar in macroeconomic
theory and the theory of economic growth; T.C. Liu in mathematical economics,
and two teachers of mathematical statistics and of sampling design in
the School of Public Health.
Simon Kuznets, who supervised my doctoral dissertation, was by far the
most influential figure in my graduate training. Soft spoken and of moderate
stature, one did not have to be in his class very long to discover that
he was a towering intellect, erudite not only in economics, but also in
history, demography, statistics, and the natural sciences. His course
in economic growth covered the history of technological change during
the modern era, demography and population theory, and the use of national
income aggregates for the comparative study of economic growth and of
the size distribution of income. It was not until some years later that
I realized the course presented the substance of the research that later
appeared in a series of 10 supplements to Economic Development and Cultural
Change, and in his 1966 monograph, Modern Economic Growth: Rate, Structure,
and Spread - the work for which he was awarded the third Nobel Prize in
economics. Kuznets's course was valuable not only for the substance of
the material but also for the way that he used the material to transmit
the art of measurement. He repeatedly demonstrated that the central statistical
problem in economics was not random error but systematic biases in the
data, and he conveyed a number of powerful approaches to coping with that
problem, particularly emphasizing the role of sensitivity analysis.
By the time I left residence at Johns Hopkins, I had worked out a two-pronged
research strategy that I thought could keep me going for a decade or more.
The first was to measure the impact of key scientific and technological
innovations, key governmental policies, and key environmental and institutional
changes on the course of economic growth. The second was to promote the
wider use of the mathematical models and statistical methods of economics
in studying the complex, long-term processes that were the focus of economic
historians. In my mind these two objectives were closely interrelated.
The best argument for the new methods was the demonstration that in the
study of particular issues, such as the contribution of railroads to economic
growth, these methods were superior to traditional approaches. The new
methods made it possible to lay out the key analytical issues in a manner
that made them amenable to measurement, to identify the categories of
evidence needed to resolve the points at issue, to develop techniques
of measurement that were suitable for both the issues and the available
evidence, and to assess the robustness of the results.
Several factors made the realization of my research program possible.
One was the willingness of university administrators to provide me with
a generous share of the limited research funds at their disposal, a sine
qua non for work that was both labor and computer intensive. Even when
I was still an unproven new assistant professor at Rochester, Lionel W.
McKenzie provided several research assistants, a computer programmer,
and all of the computer time I could use. Deans D. Gale Johnson and Robert
McC. Adams made similar investments in my research at Chicago during the
1960s and early 1970s at levels that reflected as much their estimates
of my promise as of accomplishments. This type of support was continued
at Harvard by Henry Rosovsky during the last half of the 1970s.
Except for a small grant from the Social Science Research Council (SSRC)
when I was still a student at Johns Hopkins, my work on railroads was
supported exclusively from university funds. Since my later projects were
based on ever-larger data sets, obtained primarily from manuscript sources
at archives, these projects could not have been carried out without the
generous support of foundations, particularly the National Science Foundation
(NSF) and the National Institutes of Health (NIH), but to a significant
degree also such private foundations as the Ford Foundation, the Exxon
Educational Foundation, and the Walgreen Foundation Endowment Fund. University
funding still remained crucial since it took considerable outlays of funds
to bring a large project to a point that could win approval from peer
review committees.
Another key factor was the plunging cost of data processing made possible
by rapid advances in computer hardware and software. These technological
developments made it feasible to work with ever-larger data sets. By linking
together the data on individuals and households from a wide range of archival
sources, data sets could be customized for particular economic issues.
The sources include the manuscript schedules of decennial censuses, probate
records, military and pension records, genealogies, tax rolls, death certificates,
and public health records.
Still another important factor in making such research feasible was the
cooperation of offcials at the U. S. National Archives and of the Genealogical
Library of the Church of Jesus Christ of Latter-Day Saints in Salt Lake
City. The Genealogical Library is especially valuable because it is a
depository for vast quantities of records from all over the United States,
and from many other countries, relevant to economic, social, and biomedical
research. Although collected for religious reasons, officials of the Library
have made their holdings available to the scientific community, providing
a resource that would otherwise have required enormous sums of money to
reproduce.
No single organization has contributed more to the study of long-term
economic growth than the National Bureau of Economic Research (NBER).
The long-term approach figured prominently in NBER research programs conducted
between the late 1930s and the late 1960s. That work, which was conducted
mainly at the macro level, was a continuation of the Bureau's pioneering
work in the development of national income accounts and related measures
of macroeconomic behavior. However, during the 1970s the Bureau's work
on long-term growth processes had waned. When Martin Feldstein became
President of the NBER in 1977 he decided to undertake a new program on
the long-term Development of the American Economy (DAE), and asked me
to be its program director.
I appointed an executive committee consisting of Lance E. Davis, Stanley
L. Engerman, Robert M. Gallman, Claudia D. Goldin, Clayne L. Pope, and
myself to chart the direction of the new program. After reviewing the
Bureau's past work, and the new direction it was taking under Feldstein's
leadership, the committee sought to identify a set of current policy issues
to which the DAE could contribute. In the course of this review we consulted
with Simon Kuznets, Douglass C. North, Richard A. Easterlin, and Moses
Abramovitz, among others.
After more than a year of investigation, we concluded that to understand
the sources of the long-term decline in saving and investment rates, the
factors influencing the rate of technological change, or the long-term
shifts in the demographic structure of the population and the labor force,
we needed to know much more about microeconomic behavior than was known
at the time. Research at the microeconomic level, however, had been inhibited
by the absence of suitable data. The DAE, therefore, turned its attention
to the problem of constructing new data sets capable of illuminating the
relationship between the current and the past behavior of families and
firms.
The executive committee launched a series of pilot projects investigating
the feasibility of creating several representative data sets consisting
of intergenerationally linked families. Such data sets would open up entirely
new possibilities for examining the interaction of economic and cultural
factors and their mutual influence on such variables as the saving rate,
the rate of female entry into the labor force, fertility and mortality
rates, the inequality of the wealth distribution, migration rates, and
rates of economic and social mobility. These data sets could not be created
from a single set of records but required the linking of several different
types of archival records. The executive committee also began a pilot
study on the feasibility of constructing data sets based on firm records
that would permit the analysis of the way that firms respond to the changing
technological opportunities that are open to them, as well as to the changing
institutional and legal environment in which they must operate. Dealing
with such issues required the development of representative sets of firm
records stretching over long periods of time that not only contained information
on the decision-making processes of these firms, but also on the economic
consequences of the decisions.
The DAE's review of the pilot projects concluded that the design of portable
computers for data retrieval, and of software to manipulate large files,
had developed to the point where the creation of such microeconomic data
sets was feasible. A score of projects were set out by 1980 and investigators
to lead them were chosen. Claudia Goldin, who became the director of the
DAE in 1991, reported that there are now some forty DAE research associates.
Since the start of the DAE, they have created over fifty longitudinal
and cross-sectional data sets that span the period from the late 1700s
to the present. These data sets have formed the basis for scores of papers,
several conference volumes and a number of monographs.
My ability to work on the problem of creating and studying large lifecycle
and intergenerational data sets reached a new level in 1981 when Richard
N. Rosett, then Dean of the Graduate School of Business at The University
of Chicago, invited me to succeed George J. Stigler as the Charles R.
Walgreen Professor of American Institutions. In addition to the unusual
research fund endowed by Walgreen, Rosett offered to establish a Center
for Population Economics (CPE) that would focus on the interaction of
economic, demographic, and biological processes over life-cycles and generations.
The invitation was enthusiastically supported by Hanna Gray, who was then
the President of The University of Chicago. The generous support of the
CPE has been continued by John P. Gould, who succeeded Rosett as Dean,
by Robert S. Hamada, the current Dean, and by Hugo F. Sonnenschein, President
of The University of Chicago.
Without the resources of the Walgreen Chair and the CPE the current research
projects on which I reported in the Prize Lecture would not have been
possible. The data on health conditions, for example, comes from a project
called Early Indicators of Later Work Levels, Disease, & Death which is
tracing nearly 40,000 Union Army men from the cradle to the grave. It
takes over 15,000 variables to describe the life-cycle history of one
of these men. These life-cycle histories are created by linking about
a score of data sets. It took more than half a decade of work to investigate
the potential of these data sets, work out procedures for data retrieval
and file management, and to establish the feasibility of the enterprise
in our own minds.
The site committee of the National Institutes of Health which reviewed
the original project proposal in 1986 agreed that such a project could
in principle make a significant contribution to an understanding of the
process of aging, but they were skeptical about the quality of some of
the data, about whether the software and programming procedures we had
developed by that time were adequate for the management of such a large
data set, and about whether the project could be completed within the
proposed budget. To resolve these doubts it was necessary to draw a six
percent subsample which linked together all of the separate sources and
which demonstrated the effectiveness of the software by analyzing the
information in the subsample. It took an additional four years to complete
the second phase of the justification of the project. Thus nearly a decade
of preliminary research, much of it funded by Walgreen and the CPE, was
required before the project was accepted by the peer reviewers of NIH
and NSF.
No individual has
done more to help me pursue a career in science than my wife of forty-five
years. I met Enid Cassandra Morgan during the election campaign of 1948
when she was a Sunday school teacher, a leader of the youth organizations
of St. Phillips Episcopal Church, and the head of Harlem Youth for the
election of Henry Wallace. Over the years Enid has been both my most confident
supporter and my keenest critic. During my graduate training her earnings
contributed significantly to the income of our family. When I was an assistant
professor she combined care of the children with many hours of unpaid
labor as a research assistant in library archives. She helped boost my
self-confidence when my unorthodox findings provoked controversy and criticisms,
and she often provided insightful suggestions for the improvement of my
lectures, papers, books, letters, and research proposals.
Throughout the years
she has been the overseer of my social conscience, pulling me back to
reality when she saw that my preoccupation with the abstract aspects of
scientific issues had led me to extenuate their deeply human aspects.
I also benefitted greatly from her experiences as Student Counselor, Dean
of Students, and Director of Student Life at Rochester, Harvard, and Chicago.
She has helped me to understand the administrator's point of view and
to improve what she and my sons refer to as "people skills".
My sons, Michael
and Steven, have shared in the joys and the tribulations of being raised
by academic parents. They have encouraged me to adhere steadfastly to
scholarly principles in the face of unfair criticisms. They have read
my papers and books, offered helpful suggestions, and sometimes helped
substantially in the process of editing, teaching me how to say more with
fewer words.
One aspect of the
plunging cost of data processing has been the emergence of large-scale
collaborative projects in economic history. Such projects have been promoted
partly by economies of scale in the retrieval and cleaning of the data
sets and partly by the wide range of skills required to manipulate, analyze
and interpret the data. There were, for example, thirty five contributors
to the three technical volumes of Without Consent or Contract, many of
them former students who are now distinguished senior investigators. The
research team for the Early Indicators project is even larger. It has
been my good fortune to have had access not only to the pool of talented
students at Chicago, but also to those at Harvard and Rochester. In both
the slavery and aging projects these students were often far ahead of
the senior investigators in recognizing major unanticipated findings,
in proposing novel approaches to the analysis of the data, in discovering
new data sets, and in offering probing criticisms.
It is known far and
wide among economic historians that much of the credit for the success
of my research enterprises goes to Marilyn Coopersmith who has worked
with me for more than a quarter of a century. She was the administrative
assistant of the DAE program from its inception until 1991, and she has
been the associate director of the CPE since 1981. She is not only an
effective coordinator but has been a diligent researcher and a friend
to a legion of graduate research assistants, who often turned to her for
help in overcoming bureaucratic obstacles.
The companionship
of scholars and the thrill of continuous learning are two wonderful aspects
of a life in science. When one is engaged with students who are both very
curious and very bright, it is never quite clear who is teaching whom.
I have also had the good fortune of collaborating with senior investigators
who are all exceptional teachers with enthusiasm for their work and with
great patience for the bewilderment of novices. Their guidance greatly
facilitated my efforts to train myself for research involving the interconnections
between economics, demography, and the biomedical sciences. James Trussell
tutored me as I tried to master the mathematical models of demography
and the art of applying them to incomplete data. J.M. Tanner has spent
numerous hours teaching me the fundamentals of the branch of medicine
called auxology (the study of human growth), looking at our data and helping
to interpret them, guiding me through basic texts, calling my attention
to the latest relevant papers, and reading and criticizing my work. I
received a similar education from Nevin S. Scrimshaw in epidemiology (particularly
of infectious diseases), in nutrition, and in some aspects of both physiology
and clinical medicine.
From Les Prix Nobel
1993.
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