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. The Nobel Prizes 1993, Editor Tore Frängsmyr, [Nobel Foundation], Stockholm, 1994
This autobiography/biography was written at the time of the award and later published in the book series Les Prix Nobel/Nobel Lectures. The information is sometimes updated with an addendum submitted by the Laureate. To cite this document, always state the source as shown above.
Copyright © The Nobel Foundation 1993