Industrialization Puzzle”
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NBER WORKING PAPER SERIES SAMPLE-SELECTION BIASES AND THE “INDUSTRIALIZATION PUZZLE” Howard Bodenhorn Timothy W. Guinnane Thomas A. Mroz Working Paper 21249 http://www.nber.org/papers/w21249 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 June 2015 For comments and suggestions we thank Shameel Ahmad, Cihan Artunç, Gerard van den Berg, Claire Brennecke, Raymond Cohn, Thomas Cvrcek, Jeremy Edwards, James Fenske, Amanda Gregg, Farly Grubb, Sukjin Han, Brian A'Hearn, Philip Hoffmann, Sriya Iyer, John Komlos, John Murray, Sheilagh Ogilvie, Jonathan Pritchett, Paul Rhode, Mark Rosenzweig, Gabrielle Santangelo, Richard Steckel, Jochen Streb, William Sundstrom, Werner Troesken, James Trussell, Christopher Udry, Marianne Wannamaker, John Warner, David Weir, anonymous referees, and participants in seminars at the University of Michigan, the University of Nuremberg, Queen's University (Ontario), the Rhein-Westfälisches Wirtschaftsintitut, Tulane University, and the 2012 Cliometrics meetings. We thank Emilia Arcaleni, John Murray and Richard Steckel for sharing data. We acknowledge financial support from the Yale University Economic Growth Center. Meng Liu, Yiming Ma, and Adèle Rossouw provided excellent research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer- reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2015 by Howard Bodenhorn, Timothy W. Guinnane, and Thomas A. Mroz. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Sample-selection biases and the “industrialization puzzle” Howard Bodenhorn, Timothy W. Guinnane, and Thomas A. Mroz NBER Working Paper No. 21249 June 2015 JEL No. J11,N11,N31 ABSTRACT Understanding long-term changes in human well-being is central to understanding the consequences of economic development. An extensive anthropometric literature purports to show that heights in the United States declined between the 1830s and the 1890s, which is when the US economy industrialized and urbanized. Most research argues that declining heights reflects the impact of the industrialization process. This interpretation, however, relies on sources subject to selection bias. Changes in that selection mechanism may account for the declining heights. We show that the evidentiary basis of the puzzle is not as robust as previously believed. Our meta-analysis of more than 150 studies shows that declining-heights finding emerges primarily in selected samples. Finally, we offer a parsimonious diagnostic test for revealing (but not necessarily correcting for) selection bias. The diagnostic applied to four samples that underlay the industrialization puzzle shows compelling evidence of selection. Howard Bodenhorn Thomas A. Mroz John E. Walker Department of Economics Andrew Young School of Policy Studies College of Business and Behavioral Science Georgia State University 201-B Sirrine Hall 33 Gilmer St SE Clemson University Atlanta, GA 30302 Clemson, SC 29634 [email protected] and NBER [email protected] Timothy W. Guinnane Department of Economics Yale University PO Box 208269 New Haven CT 06520 [email protected] An online appendix is available at: http://www.nber.org/data-appendix/w21249 1. Introduction Introduced into economic history just over three decades ago, anthropometric history is now one component of the cliometrician’s standard toolkit. Roderick Floud et al (2011, 374 hereafter FFHH) note that anthropometric history originated with the limited objective of establishing the heights and health of the inhabitants of North America and Western Europe in the eighteenth century. Since then, the study of heights has “mushroomed into a study of the long-term development of human society,” drawing on the tools and insights of economics, statistics, and medicine, among others. It is fair to say that no other branch of cliometric history has had as many resources devoted to it in the past two decades as historical anthropometrics (Voth and Leunig 1996, 541). Anthropometricians have developed a systematic approach to the study of the connection between changes in the human body and economic development labeled the “techno-physical” approach, which is built on four premises (FFHH 2011). First, the typical body size and shape of a population reflect that generation’s longevity and work capacity. Second, a generation’s work capacity and the technology available to it determine its outputs. Third, a generation’s outputs and, therefore, its physical wellbeing, is both an inheritance from previous generations and a legacy to generations to follow. Thus, fourth, a society can embark on a path of long-run economic growth only if it witnesses improvements in each generation’s physical wellbeing, which it then passes to subsequent generations.1 Physiological improvement – greater mean stature, increases in mean body mass index toward modern norms – takes a central place in the list of factors that influence 1 Deaton (2013) offers a related argument. 2 economic development in the long run. But, as FFHH (2011) note in their summary of the British and American experiences, nutritional wellbeing in these now-rich economies did not grow monotonically. Most of the available evidence from these two countries reveals that heights stagnated or declined in the early phase of modern economic growth. In the United States, in particular, mean height apparently declined for cohorts born between (approximately) the 1830s and the 1890s. This apparent anomaly, now widely labeled the “antebellum puzzle,” is one of the most-studied issues in the field of economic history (FFHH 2010, 298). Similar substantial, long-term declines have also been identified for Great Britain, Sweden, and the Habsburg monarchy, although at different times (Floud, Wachter and Gregory 1990, Sandberg and Steckel 1987, Komlos 1989). Komlos (1994a, 493) calls the decline in heights in the early phase of economic modernization in these countries “the most amazing discovery” of anthropometric history. Studies have identified a number of potential causes, though most focus on the failure of food supplies (measured by quantity, quality or both) and public health, broadly conceived, to keep up with population growth and urbanization.2 “Economic growth in the nineteenth century,” write FFHH (2011, 348), “was very costly because economic booms caused rapid population growth, internal and external migration, urbanization, sanitation problems, and rampant diseases; all these reduced people’s productivity and their ability to accumulate human capital.” The apparent decline in heights in the United States, Great Britain, Sweden and Habsburg-era central Europe is indeed interesting. But we doubt the evidence adduced 2 Komlos (2012 working paper) also provides a summary of the literature and identifies at least a dozen different explanations for the puzzle. 3 for this apparent decline. These countries had very different economies at the time of the height reversal. But they did share an important feature: they filled their military ranks with volunteers rather than conscripts. Thus the samples height scholars rely on for the reversals are selected, in the sense that they contain only individuals who decided to join the army. Elsewhere we have shown that the sample-selection problems in inferring population heights from a group of volunteers can be grave (Bodenhorn, Guinnane and Mroz 2014). The implications of selection bias make the observed “shrinking in a growing economy” less of an anomaly (Komlos 1998a). As the economy grew, the outside option of military service became less attractive, especially to the productive and the tall. Military heights declined because tall people disproportionately chose non- military employment. Thus, we cannot really say whether population heights declined; perhaps only the heights of those willing to enlist in the military declined. Below we draw on published heights studies to document an important feature of the data: height reversals or “puzzles” emerge only rarely in countries that filled their ranks through (near universal) conscription. Sample selection can take two forms that the heights literature sometimes confuses. Exogenous selection pertains to sampling on an observable, exogenous characteristic, such as race or gender. Modern surveys often deliberately over-sample on such characteristics. If we know the proportions of such groups in the population, then we can construct and apply weights to obtain estimates that reflect the population’s characteristics. Endogenous selection reflects a situation where an individual enters the sample in part because of unmeasured characteristics that also are related to outcomes of interest. That is, a soldier in a volunteer army (for example) made a decision based on his 4 individual unobserved characteristics. We cannot use simple sampling weights to overcome endogenous selection because the required weights would be individual- specific and depend upon unmeasured characteristics. Endogenous selection likely afflicts many of the samples cliometricians use; the problem is not limited to the antebellum puzzle. But we focus on that issue. Two points warrant emphasis. First, endogenous