Demographic Research Monographs omas K. Burch Model-Based Demography Essays on Integrating Data, Technique a n d e o r y Demographic Research Monographs A Series of the Max Planck Institute for Demographic Research Editor-in-chief James W. Vaupel Max Planck Institute for Demographic Research Rostock, Germany More information about this series at http://www.springer.com/series/5521 Thomas K. Burch Model-Based Demography Essays on Integrating Data, Technique and Theory Thomas K. Burch Department of Sociology and Population Research Group University of Victoria Victoria, BC, Canada ISSN 1613-5520 ISSN 2197-9286 (electronic) Demographic Research Monographs ISBN 978-3-319-65432-4 ISBN 978-3-319-65433-1 (eBook) DOI 10.1007/978-3-319-65433-1 Library of Congress Control Number: 2017951857 © The Editor(s) (if applicable) and The Author(s) 2018. This book is published open access. 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Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland For my wife, Karen Halling Burch, and in memory of my son, Thaddeus J. Burch Preface The papers in this collection – most of them previously published – are the fruits of an intellectual odyssey over the last decades of my career as a sociologist/demog- rapher. Beginning in the late 1980s, longstanding questions about the status of demography as a science came to the surface, and I began to pursue them actively. Looking back, I realize that at some point I became less a demographer and more a demography critic – cf. art critic or music critic – and an amateur philosopher of science. My central concern has been with the role and status of theory in demography. For some, it was enough that demography did rigorous analysis of data using standard demographic and statistical techniques, notably emerging methods of multivariate analysis as applied to micro-data files. Theoretical explanations and models of behavioral processes often were left to other disciplines. Becker and the microeconomists had become the leading theorists of demographic behavior, while social demographers made relatively little systematic use of the large fund of relevant theory from sociology, social psychology, and cultural anthropology. Microeconomic theory enjoyed widespread acceptance, if not consensus, among economists. And it was stated in clear, unambiguous form, often mathematically. Social-behavioral theory, by contrast, was formulated with less rigor, in loose verbal form, and commanded nothing approaching consensus. As a graduate student in sociology and demography in the late 1950s, I had taken several excellent courses on social theory and cultural anthropology (Wilbert Moore; Marion J. Levy, Jr.; and Melvin Tumin) and trained in demography and statistics with leaders in the field – Frank Notestein, Ansley Coale, and Frederick Stephan. But there was little integration. My dissertation was a largely technical work on measurement of internal migration, with virtually no behavioral content and no theory. Some of my sociology professors were dismayed. My demography and statistics professors were satisfied if not ecstatic. As I pursued my career, I lived this schizoid life as an empirical demographer with an interest in theory – a small example of the split between theory and empirical research famously described by Robert Merton (1957). With a primary commitment to demography, my vii viii Preface relationship to theory, like that of the discipline, was characterized by ambivalence and malaise. In reviewing the development of my thinking on these matters, I can single out three works as crucial. Robert Hanneman’s Computer-Assisted Theory Building: Modeling Dynamic Social Systems (1988) provided a detailed introduction to dynamic systems modeling as a potential theoretical tool for demographers and other empirical social scientists. It promised rigor in the statement and manipula- tion of theoretical models – including complex dynamic models with feedbacks and delays – and reoriented thinking away from comparative statics and equilibrium toward process and change. To this day, I remain puzzled why social scientists, including demographers, have made so little use of this powerful analytic tool. An earlier work – discovered much later and by accident – was Explanation in Social Science: A System Paradigm by Eugene Meehan, a political scientist (1968). Meehan provided a convincing critique of logical positivism as a dead-end approach to social science and set forth a practical alternative involving ‘systems’ – roughly equivalent to theoretical models. He also insisted on the importance of purpose or aim, as well as logical consistency with data, in evaluating models. A model well-suited to one purpose may not be adequate for another. Ronald Giere’s Science Without Laws (1999) appeared to me to support Meehan’s general approach, while placing it in the context of late twentieth- century philosophy of science. Accessible to the nonprofessional philosopher, this work argues that the model, not the law, is the central element in science. Models are not ‘true’ in any strong sense of that word. They simply fit some portion of the real world closely enough in certain respects to make them useful for certain purposes. At best, they embody ‘realism without truth.’ Taken together, these works convinced me that demography had more and better theory than generally recognized and pointed the way toward fruitful systematiza- tion and codification. Demography could be a full-fledged discipline, with its ample foundation of empirical data and technique balanced by a rich body of theory. From time to time, I have wondered whether I had touched bottom with respect to the philosophical and methodological issues involved in demography as a science. Eventually, I realized there probably is no bottom. Professional students of science – philosophers, sociologists of science, and cognitive psychologists – disagree on many points. It is not likely that I would be able beat them at their own game and come up with a definitive view on science. I agree with Paul Teller (2001), who has warned against ‘the perfect model model’ of science, and with Samir Okasha who writes: ‘Like most philosophical questions, these questions do not admit of final answers, but in grappling with them we learn much about the nature and limits of scientific knowledge’ (2002, p. 39). In any case, I am convinced that the model-based view of science as developed by Giere and others has much to offer demography as a liberating view of demo- graphic theory. Its acceptance and routine application to our work could lead to a rich collection – a toolkit – of useful theoretical models, general, middle range, and Preface ix “low range.” As noted above, we can achieve a better balance among data, technique, and theory and become a complete science of human population.1 Even after a career of nearly 60 years in demography, however, I may be presumptuous to sit in judgment on the discipline and to suggest directions for its future development. But I have been encouraged by many other demographers who, over the years, have expressed their concern for the character and status of the field, their lingering feeling that something was missing. It seems to me that the model- based approach to science will encourage and enable us to provide what has been missing, notably a carefully crafted body of theory. But just as there is no perfect model in science, there is no perfect model of science. And I am not a philosopher of science nor familiar with the practice and accomplishments of all the sciences, social, behavioral, biological, and physical. I can do no better than to close with a quote from E.O. Wilson. In the Preface to On Human Nature, in which he argues for the usefulness of evolutionary biology for understanding human behavior, he comments: “I might easily be wrong” (p. x). But it will be enough if this work promotes a lively discussion of what demography is and might become. As lightly edited versions of papers written at different times and in different contexts, many of the following chapters repeat central ideas, for example, the contrasts between logical empiricism and the model-based approach to science, or the idea that much of ‘technical’ demography can be viewed as theory. Sometimes, this repetition may seem unnecessary.