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“Big Data” in Economic History

Published online by Cambridge University Press:  03 April 2018

Myron P. Gutmann
Affiliation:
Myron P. Gutmann is Professor, Department of History and Director, Institute of Behavioral Science, University of Colorado Boulder, 483 UCB, Boulder, CO 80309. E-mail: Myron.Gutmann@colorado.edu.
Emily Klancher Merchant
Affiliation:
Emily Klancher Merchant is Assistant Professor, Science and Technology Studies, University of California, Davis, One Shields Avenue, Davis, CA 95616. E-mail: ekmerchant@ucdavis.edu.
Evan Roberts
Affiliation:
Evan Roberts is Assistant Professor, Department of Sociology and Minnesota Population Center, University of Minnesota, 909 Social Sciences, 267 19th Ave S, Minneapolis, MN 55455. E-mail: eroberts@umn.edu.

Abstract

Big data is an exciting prospect for the field of economic history, which has long depended on the acquisition, keying, and cleaning of scarce numerical information about the past. This article examines two areas in which economic historians are already using big data – population and environment – discussing ways in which increased frequency of observation, denser samples, and smaller geographic units allow us to analyze the past with greater precision and often to track individuals, places, and phenomena across time. We also explore promising new sources of big data: organically created economic data, high resolution images, and textual corpora.

Type
Reviews and Reflections
Copyright
Copyright © The Economic History Association 2018 

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Footnotes

We thank the editors of the Journal for the opportunity to undertake this review, and for their comments and feedback throughout the writing of the paper. Jeremy Mikecz provided assistance in the research on agriculture and environment data. Evan Roberts gratefully acknowledges support from the Minnesota Population Center (Project 5R24HD041023), funded through grants from the Eunice Kennedy Shriver National Institute for Child Health and Human Development. Myron Gutmann acknowledges support from the University of Colorado Population Center funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (Project 2P2CHD066613-06) for research and administrative support.

References

Aaronson, Daniel, Dehejia, Rajeev, Jordan, Andrew, et al. “The Effect of Fertility on Mothers' Labor Supply over the Last Two Centuries.” NBER Working Paper No. 23717, Cambridge, MA, 2017.Google Scholar
Abowd, John M., Stephens, Bryce E., Vilhuber, Lars, et al. “The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators.” In Producer Dynamics: New Evidence from Micro Data, 149230. Chicago: University of Chicago Press.Google Scholar
Abramitzky, Ran, Boustan, Leah Platt, and Eriksson, Katherine. “Europe's Tired, Poor, Huddled Masses: Self-Selection and Economic Outcomes in the Age of Mass Migration.” American Economic Review 102, no. 5 (2012): 1832–56.CrossRefGoogle ScholarPubMed
Abramitzky, Ran, Boustan, Leah Platt. “Have the Poor Always Been Less Likely to Migrate? Evidence from Inheritance Practices During the Age of Mass Migration.” Journal of Development Economics 102 (2013): 214.CrossRefGoogle ScholarPubMed
Abramitzky, Ran, Boustan, Leah Platt. “A Nation of Immigrants: Assimilation and Economic Outcomes in the Age of Mass Migration.” Journal of Political Economy 122, no. 3 (2014): 467506.CrossRefGoogle ScholarPubMed
Anderson, Albert F.Statistics and Massive Data Sets: One View from the Social Sciences.” In Massive Datasets: Proceedings of a Workshop, Committee on Applied and Theoretical Statistics, National Research Council, 33–38. Washington, DC: National Academies Press, 1997.Google Scholar
Antenucci, Dolan, Cafarella, Michael J., Levenstein, Margaret C., et al. “Using Social Media to Measure Labor Market Flows.” NBER Working Paper No. 20010, Cambridge, MA, 2014.Google Scholar
Ashplant, T.G., and Wilson, Adrian. “Present-Centred History and the Problem of Historical Knowledge.” Historical Journal 31, no. 2 (1988): 253–74.CrossRefGoogle Scholar
Atack, Jeremy, Bateman, Fred, and Gregson, Mary Eschelbach. “‘Matchmaker, Matchmaker, Make Me a Match’ a General Personal Computer-Based Matching Program for Historical Research.” Historical Methods 25, no. 2 (1992): 5365.CrossRefGoogle Scholar
Atkinson, Anthony B., Piketty, Thomas, and Saez, Emmanuel. “Top Incomes in the Long Run of History.” Journal of Economic Literature 49, no. 1 (2011): 371.CrossRefGoogle Scholar
Bagger, Jesper, and Seltzer, Andrew. “Administrative and Survey Data in Personnel Economics.” Australian Economic Review 47, no. 1 (2014): 137–46.CrossRefGoogle Scholar
Bailey, Martha. “Longitudinal, Intergenerational Family Electronic Micro-Database Project.” Ann Arbor: University of Michigan, 2017. Available at http://sites.lsa.umich.edu/life-m/.Google Scholar
Bandiera, Oriana, Rasul, Imran, and Viarengo, Martina. “The Making of Modern America: Migratory Flows in the Age of Mass Migration.” Journal of Development Economics 102 (2013): 2347.CrossRefGoogle Scholar
Bankoff, Greg. “Comparing Vulnerabilities: Toward Charting an Historical Trajectory of Disasters.” Historical Social Research/Historische Sozialforschung (2007): 103–14.Google Scholar
Barclay, Kieron, Keenan, Katherine, Grundy, Emily, et al. “Reproductive History and Post-Reproductive Mortality: A Sibling Comparison Analysis Using Swedish Register Data.” Social Science & Medicine 155 (2016): 8292.CrossRefGoogle ScholarPubMed
Barclay, Kieron, and Kolk, Martin. “Birth Order and Mortality: A Population-Based Cohort Study.” Demography 52, no. 2 (2015): 613–39.CrossRefGoogle ScholarPubMed
Bates, David W., Saria, Suchi, Ohno-Machado, Lucila, et al. “Big Data in Health Care: Using Analytics to Identify and Manage High-Risk and High-Cost Patients.” Health Affairs 33, no. 7 (2014): 1123–31.CrossRefGoogle ScholarPubMed
Bauer, Thomas K., Bender, Stefan, Heining, Jörg, et al. “The Lunar Cycle, Sunspots and the Frequency of Births in Germany, 1920–1989.” Economics & Human Biology 11, no. 4 (2013): 545–50.CrossRefGoogle Scholar
Beach, Brian, Ferrie, Joseph, Saavedra, Martin, et al. “Typhoid Fever, Water Quality, and Human Capital Formation.” Journal of Economic History 76, no. 1 (2016): 4175.CrossRefGoogle Scholar
Bearman, Peter. “Big Data and Historical Social Science.” Big Data & Society 2, no. 2 (2015).CrossRefGoogle Scholar
Becker, Sascha O., and Woessmann, Ludger. “Was Weber Wrong? A Human Capital Theory of Protestant Economic History.” Quarterly Journal of Economics 124, no. 2 (2009): 531–96.CrossRefGoogle Scholar
Bengtsson, Tommy, Campbell, Cameron, Lee, James Z., et al. Life Under Pressure: Mortality and Living Standards in Europe and Asia, 1700–1900. Cambridge: MIT Press 2004.Google Scholar
Bengtsson, Tommy, Dribe, Martin, Quaranta, Luciana, et al. “The Scanian Economic Demographic Database, Version 4.0 (Machine-Readable Database).” Lund: University of Lund, 2014. http://www.ed.lu.se/databases/sedd.Google Scholar
Bholat, David. “Big Data and Central Banks.” Big Data & Society 2, no. 1 (2015).CrossRefGoogle Scholar
Black, Sandra E., Devereux, Paul J., and Salvanes, Kjell G.. “Under Pressure? The Effect of Peers on Outcomes of Young Adults.” Journal of Labor Economics 31, no. 1 (2013): 119–53.CrossRefGoogle Scholar
Blake, Kellee. “‘First in the Path of the Firemen’: The Fate of the 1890 Population Census.” Prologue Magazine 28, no. 1 (1996): 6481.Google Scholar
Blaser, Lucinda. “Old Weather: Approaching Collections from a Different Angle.” In Crowdsourcing Our Cultural Heritage, edited by Ridge, Mia, 4556. London: Routledge, 2014.Google Scholar
Bleakley, Hoyt, and Ferrie, Joseph. “Shocking Behavior: Random Wealth in Antebellum Georgia and Human Capital across Generations.” Quarterly Journal of Economics 131, no. 3 (2016): 1455–95.CrossRefGoogle Scholar
Boberg-Fazlic, Nina, Sharp, Paul, and Weisdorf, Jacob. “Survival of the Richest? Social Status, Fertility and Social Mobility in England 1541–1824.” European Review of Economic History 15, no. 3 (2011): 365–92.CrossRefGoogle Scholar
Boustan, Leah Platt. “Competition in the Promised Land: Black Migration and Racial Wage Convergence in the North, 1940–1970.” Journal of Economic History 69, no. 3 (2009): 755–82.CrossRefGoogle Scholar
Bowyer, Alex, Lintott, Chris, Hines, Greg, et al. “Panoptes, a Project Building Tool for Citizen Science.” Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) Conference on Human Computation and Crowdsourcing (HCOMP 15). San Diego: AAAI Press, 2015.Google Scholar
Broeckel, Ulrich, Hengstenberg, Christian, Mayer, Bjoern, et al. “A Locus on Chromosome 10 Influences C-Reactive Protein Levels in Two Independent Populations.” Human Genetics 122, no. 1 (2007): 95102.CrossRefGoogle ScholarPubMed
Burrows, Roger, and Savage, Mike. “After the Crisis? Big Data and the Methodological Challenges of Empirical Sociology.” Big Data & Society 1, no. 1 (2014). doi: 10.1177/2053951714540280.CrossRefGoogle Scholar
Candido dos Reis, Francisco J., Lynn, Stuart, Raza Ali, H., et al. “Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer.” EBioMedicine 2, no. 7 (2015): 681–89.CrossRefGoogle Scholar
Cantoni, Davide. “The Economic Effects of the Protestant Reformation: Testing the Weber Hypothesis in the German Lands.” Journal of the European Economic Association 13, no. 4 (2015): 561–98.CrossRefGoogle Scholar
Cavallo, Alberto, and Rigobon, Roberto. “The Billion Prices Project: Using Online Prices for Measurement and Research.” Journal of Economic Perspectives 30, no. 2 (2016): 151–78.CrossRefGoogle Scholar
Chen, Qiang. “Climate Shocks, Dynastic Cycles and Nomadic Conquests: Evidence from Historical China.” Oxford Economic Papers 67, no. 2 (2015): 185204.CrossRefGoogle Scholar
Chetty, Raj, Hendren, Nathaniel, Kline, Patrick, et al. “Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility.” American Economic Review 104, no. 5 (2014): 141–47.CrossRefGoogle Scholar
Chetty, Raj, Stepner, Michael, Abraham, Sarah, et al. “The Association between Income and Life Expectancy in the United States, 2001–2014.” JAMA 315, no. 16 (2016): 1750–66.CrossRefGoogle ScholarPubMed
Claus, Iris, Creedy, John, and Teng, Josh. “The Elasticity of Taxable Income in New Zealand.” Fiscal Studies 33, no. 3 (2012): 287303.CrossRefGoogle Scholar
Clotfelter, Charles T.Tax Evasion and Tax Rates: An Analysis of Individual Returns.” Review of Economics and Statistics 65, no. 3 (1983): 363–73.Google Scholar
Collins, William J.Looking Forward: Positive and Normative Views of Economic History's Future.” Journal of Economic History 75, no. 4 (2015): 1228–33.CrossRefGoogle Scholar
Collins, William J., and Wanamaker, Marianne H.. “The Great Migration in Black and White: New Evidence on the Selection and Sorting of Southern Migrants.” Journal of Economic History 75, no. 4 (2015): 947–92.CrossRefGoogle Scholar
Conrad, Alfred J., and Meyer, John R.. “The Economics of Slavery in the Antebellum South.” Journal of Political Economy 66, no. 2 (1958): 95130.CrossRefGoogle Scholar
Cutler, David M., Glaeser, Edward L., and Vigdor, Jacob L.. “The Rise and Decline of the American Ghetto.” Journal of Political Economy 107, no. 3 (1999): 455506.CrossRefGoogle Scholar
Daly, Christopher, Gibson, Wayne P., Taylor, George H., et al. “A Knowledge-Based Approach to the Statistical Mapping of Climate.” Climate Research 22, no. 2 (2002): 99113.CrossRefGoogle Scholar
Daly, Christopher, Halbleib, Michael, Smith, Joseph I., et al. “Physiographically Sensitive Mapping of Climatological Temperature and Precipitation across the Conterminous United States.” International Journal of Climatology 28, no. 15 (2008): 2031–64.CrossRefGoogle Scholar
Deane, Glenn, and Gutmann, Myron P.. “Blowin'down the Road: Investigating Bilateral Causality between Dust Storms and Population in the Great Plains.” Population Research and Policy Review 22, no. 4 (2003): 297331.CrossRefGoogle Scholar
Devereux, Paul J., Black, Sandra E., and Salvanes, Kjell G. “From the Cradle to the Labor Market? The Effect of Birth Weight.” Quarterly Journal of Economics 122, no. 1 (2007): 409–39.Google Scholar
Dillon, Lisa, Amorevieta-Gentil, Marilyn, Caron, Marianne, et al. “The Programme De Recherche En Démographie Historique: Past, Present and Future Developments in Family Reconstitution.” History of the Family (2017): 134.Google Scholar
Dittmar, Jeremiah, and Seabold, Skipper. “Media, Markets and Institutional Change: The Protestant Reformation.” Center for Economic Performance Discussion Paper, London, UK, 2015.Google Scholar
Dorman, Robert L.The Creation and Destruction of the 1890 Federal Census.” American Archivist 71 (2008): 350–83.CrossRefGoogle Scholar
Dribe, Martin, David Hacker, J., and Scalone, Francesco. “The Impact of Socio-Economic Status on Net Fertility During the Historical Fertility Decline: A Comparative Analysis of Canada, Iceland, Sweden, Norway, and the USA.” Population Studies 68, no. 2 (2014): 135–49.CrossRefGoogle ScholarPubMed
Dribe, Martin, and Helgertz, Jonas. “The Lasting Impact of Grandfathers: Class, Occupational Status, and Earnings over Three Generations in Sweden 1815–2011.” Journal of Economic History 76, no. 4 (2016): 9691000.CrossRefGoogle Scholar
Easterlin, Richard A.Population Change and Farm Settlement in the Northern United States.” Journal of Economic History 36, no. 1 (1976): 4575.CrossRefGoogle Scholar
Eijkemans, Marinus J.C., Poppel, Frans Van, Habbema, Dik F., et al. “Too Old to Have Children? Lessons from Natural Fertility Populations.” Human Reproduction (2014): 19.Google ScholarPubMed
Einav, Liran, and Levin, Jonathan. “Economics in the Age of Big Data.” Science 346, no. 6210 (2014): 1243089.CrossRefGoogle ScholarPubMed
Epstein, Steven. “The Construction of Lay Expertise: AIDS Activism and the Forging of Credibility in the Reform of Clinical Trials.” Science, Technology & Human Values 20, no. 4 (1995): 408–37.CrossRefGoogle ScholarPubMed
Eveleigh, Alexandra, Jennett, Charlene, Blandford, Ann, et al. “Designing for Dabblers and Deterring Drop-Outs in Citizen Science.” In Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems, 2985–94. Toronto, Canada: Association for Computing Machinery, 2014.Google Scholar
Feigenbaum, James J.A Machine Learning Approach to Census Record Linking.” Cambridge: Harvard University, 2016. Available at http://scholar.harvard.edu/files/jfeigenbaum/files/feigenbaum-censuslink.pdf.Google Scholar
Feldman, Naomi E.; Peter Katuščák, and Kawano, Laura. “Taxpayer Confusion: Evidence from the Child Tax Credit.” American Economic Review 106, no. 3 (2016): 807–35.CrossRefGoogle Scholar
Ferrie, Joseph P.The Wealth Accumulation of Antebellum European Immigrants to the U.S., 1840–60.” Journal of Economic History 54, no. 1 (1994): 133.CrossRefGoogle Scholar
Ferrie, Joseph P.. Yankeys Now: Immigrants in the Antebellum United States. New York: Oxford University Press, 1999.Google Scholar
Ferrie, Joseph P.. “History Lessons: The End of American Exceptionalism? Mobility in the United States since 1850.” Journal of Economic Perspectives 19, no. 3 (2005): 199215.CrossRefGoogle Scholar
Ferrie, Joseph P., and Rolf, Karen. “Socioeconomic Status in Childhood and Health after Age 70: A New Longitudinal Analysis for the U.S., 1895–2005.” Explorations in Economic History 48, no. 4 (2011): 445–60.CrossRefGoogle Scholar
Fitzgerald, Michael. “Better Data Brings a Renewal at the Bank of England.” MIT Sloan Management Review (May 2016): 313.Google Scholar
Fleisig, Heywood W.Slavery, the Supply of Agricultural Labor, and the Industrialization of the South.” Journal of Economic History 36, no. 3 (1976): 572–97.CrossRefGoogle Scholar
Fogel, Robert W., Costa, Dora L., Haines, Michael, et al. “Aging of Veterans of the Union Army: Version M-5.” Center for Population Economics University of Chicago Graduate School of Business, Department of Economics Brigham Young University, and The National Bureau of Economic Research, 2000. http://uadata.org.Google Scholar
Fogel, Robert William, and Engerman, Stanley L.. Time on the Cross: The Economics of American Negro Slavery. Boston: Little, Brown and Company, 1974.Google Scholar
Franzosi, Roberto, Fazio, Gianluca De, and Vicari, Stefania. “Ways of Measuring Agency: An Application of Quantitative Narrative Analysis to Lynchings in Georgia (1875–1930).” Sociological Methodology 42, no. 1 (2012): 142.CrossRefGoogle Scholar
Gagnon, Alain, Smith, Ken R., Tremblay, Marc, et al. “Is There a Trade-Off between Fertility and Longevity? A Comparative Study of Women from Three Large Historical Databases Accounting for Mortality Selection.” American Journal of Human Biology 21, no. 4 (2009): 533–40.CrossRefGoogle Scholar
Gagnon, Alain, Tremblay, Marc, Vézina, Hélène, et al. “Once Were Farmers: Occupation, Social Mobility, and Mortality During Industrialization in Saguenay-Lac-Saint-Jean, Quebec 1840–1971.” Explorations in Economic History 48, no. 3 (2011): 429–40.CrossRefGoogle Scholar
Gandomi, Amir, and Haider, Murtaza. “Beyond the Hype: Big Data Concepts, Methods, and Analytics.” International Journal of Information Management 35, no. 2 (2015): 137–44.CrossRefGoogle Scholar
Gao, Cheng, and Mizrach, Bruce. “Market Quality Breakdowns in Equities.” Journal of Financial Markets 28 (2016): 123.CrossRefGoogle Scholar
Gentzkow, Matthew, and Shapiro, Jesse M. “What Drives Media Slant? Evidence from US Daily Newspapers.” Econometrica 78, no. 1 (2010): 3571.Google Scholar
Glaeser, Edward L., Kominers, Scott Duke, Luca, Michael, et al. “Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life.” Economic Inquiry 56, no. 1 (2018): 114–37.CrossRefGoogle Scholar
Goeken, Ron, Huynh, Lap, Lynch, T. A., et al. “New Methods of Census Record Linking.” Historical Methods 44, no. 1 (2011): 714.CrossRefGoogle ScholarPubMed
Goldewijk, Kees Klein. “Estimating Global Land Use Change over the Past 300 Years: The Hyde Database.” Global Biogeochemical Cycles 15, no. 2 (2001): 417–33.CrossRefGoogle Scholar
Goldin, Claudia. “Female Labor Force Participation: The Origin of Black and White Differences, 1870 and 1880.” Journal of Economic History 37, no. 1 (1977): 87108.CrossRefGoogle Scholar
González, Felipe, Marshall, Guillermo, and Naidu, Suresh. “Start-up Nation? Slave Wealth and Entrepreneurship in Civil War Maryland.” Journal of Economic History 77, no. 2 (2017): 373405.CrossRefGoogle Scholar
Graham, Mark, and Shelton, Taylor. “Geography and the Future of Big Data, Big Data and the Future of Geography.” Dialogues in Human Geography 3, no. 3 (2013): 255–61.CrossRefGoogle Scholar
Grayson, Richard. “A Life in the Trenches? The Use of Operation War Diary and Crowdsourcing Methods to Provide an Understanding of the British Army's Day-to-Day Life on the Western Front.” British Journal for Military History 2, no. 2 (2016).Google Scholar
Gregory, Ian N., Marti-Henneberg, Jordi, and Tapiador, Francisco J.. “Modelling Long-Term Pan-European Population Change from 1870 to 2000 by Using Geographical Information Systems.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 173, no. 1 (2010): 3150.CrossRefGoogle Scholar
Griffith, Rachel, and O'Connell, Martin. “The Use of Scanner Data for Research into Nutrition.” Fiscal Studies 30, no. 3–4 (2009): 339–65.CrossRefGoogle Scholar
Grimmer, Justin. “We Are All Social Scientists Now: How Big Data, Machine Learning, and Causal Inference Work Together.” PS: Political Science & Politics 48, no. 1 (2015): 8083.Google Scholar
Groves, Robert M.Three Eras of Survey Research.” Public Opinion Quarterly 75, no. 5 (2011): 861–71.CrossRefGoogle Scholar
Grundy, Emily, and Kravdal, Øystein. “Fertility History and Cause-Specific Mortality: A Register-Based Analysis of Complete Cohorts of Norwegian Women and Men.” Social Science & Medicine 70, no. 11 (2010): 1847–57.CrossRefGoogle ScholarPubMed
Grundy, Emily, and Kravdal, Øystein. “Do Short Birth Intervals Have Long-Term Implications for Parental Health? Results from Analyses of Complete Cohort Norwegian Register Data.” Journal of Epidemiology and Community Health 68, no. 10 (2014): 958–64.CrossRefGoogle ScholarPubMed
Gullickson, Aaron. “Black/White Interracial Marriage Trends, 1850–2000.” Journal of Family History 31, no 3 (2006): 289312.CrossRefGoogle Scholar
Gutmann, Myron P.Great Plains Population and Environment Data: Agricultural Data, 1870–1997 [United States].” Ann Arbor: Inter-university Consortium for Political and Social Research, 2005.Google Scholar
Gutmann, Myron P.. “Great Plains Population and Environment Data: Social and Demographic Data, 1870–2000 [United States].” Ann Arbor: Inter-university Consortium for Political and Social Research, 2007.Google Scholar
Gutmann, Myron P., Brown, Daniel, Cunningham, Angela R., et al. “Migration in the 1930s: Beyond the Dust Bowl.” Social Science History 40, no. 4 (2016): 707–40.CrossRefGoogle ScholarPubMed
Hacker, J. David, and Roberts, Evan. “The Impact of Kin Availability, Parental Religiosity, and Nativity on Fertility Differentials in the Late Nineteenth-Century United States.” Demographic Research 37, no. 34 (2017): 1049–80.CrossRefGoogle Scholar
Hacking, Ian. “Biopower and the Avalanche of Printed Numbers.” Humanities in Society 5 (1982): 279–95.Google Scholar
Haines, Michael R.Historical, Demographic, Economic, and Social Data: The United States, 1790–2002.” Ann Arbor: Inter-university Consortium for Political and Social Research, 2010.Google Scholar
Hall, Patricia Kelly, McCaa, Robert, and Thorvaldsen, Gunnar, eds. A Handbook of International Historical Microdata for Population Research. Minneapolis: Minnesota Population Center, 2000.Google Scholar
Ham, F. Gerald. “Archival Choices: Managing the Historical Record in an Age of Abundance.” Armerican Archivist 47, no. 1 (1984): 1122.CrossRefGoogle Scholar
Hargittai, Eszter. “Is Bigger Always Better? Potential Biases of Big Data Derived from Social Network Sites.” Annals of the American Academy of Political and Social Science 659, no. 1 (2015): 6376.CrossRefGoogle Scholar
Hartman, Melannie D., Merchant, Emily R., Parton, William J., et al. “Impact of Historical Land-Use Changes on Greenhouse Gas Exchange in the US Great Plains, 1883–2003.” Ecological Applications 21, no. 4 (2011): 1105–19.CrossRefGoogle ScholarPubMed
Hausman, Jerry. “Sources of Bias and Solutions to Bias in the Consumer Price Index.” Journal of Economic Perspectives 17, no. 1 (2003): 2344.CrossRefGoogle Scholar
Henderson, J. Vernon, Storeygard, Adam, and Weil, David N.. “Measuring Economic Growth from Outer Space.” American Economic Review 102, no. 2 (2012): 9941028.CrossRefGoogle ScholarPubMed
Herweijer, Celine, Seager, Richard, Cook, Edward R., et al. “North American Droughts of the Last Millennium from a Gridded Network of Tree-Ring Data.” Journal of Climate 20, no. 7 (2007): 1353–76.CrossRefGoogle Scholar
Humphries, Jane. “‘The Most Free from Objection …’ The Sexual Division of Labor and Women's Work in Nineteenth-Century England.” Journal of Economic History 47, no. 4 (1987): 929–49.CrossRefGoogle Scholar
Committee, Index. “Report of Index Committee.” Wellington, NZ: Appendices to the Journals of the House of Representatives, 1948.Google Scholar
Irwin, Alan. Citizen Science: A Study of People, Expertise and Sustainable Development. New York: Routledge, 1995.Google Scholar
Ivancic, Lorraine, Erwin Diewert, W., and Fox, Kevin J.. “Scanner Data, Time Aggregation and the Construction of Price Indexes.” Journal of Econometrics 161, no. 1 (2011): 2435.CrossRefGoogle Scholar
Jackson, R. V. Index to the Eighth Census of the United States. Salt Lake City: Accelerated Indexing Systems International, 1992.Google Scholar
Jelveh, Zubin, Kogut, Bruce, and Naidu, Suresh. “Political Language in Economics.” Research Paper No. 14-57, Columbia Business School, New York, NY, 2015.Google Scholar
Jennett, Charlene, Kloetzer, Laure, Schneider, Daniel, et al. “Motivations, Learning and Creativity in Online Citizen Science.” Journal of Science Communication 15, no. 3 (2016): 123.Google Scholar
Jennings, Julia A., Sullivan, Allison R., and David Hacker, J.. “Intergenerational Transmission of Reproductive Behavior During the Demographic Transition.” Journal of Interdisciplinary History 42, no. 4 (2012): 543–69.CrossRefGoogle ScholarPubMed
Jensen, Jacob, Naidu, Suresh, Kaplan, Ethan, et al. “Political Polarization and the Dynamics of Political Language: Evidence from 130 Years of Partisan Speech [with Comments and Discussion].” Brookings Papers on Economic Activity 2 (2012): 181.CrossRefGoogle Scholar
Jia, Ruixue. “Weather Shocks, Sweet Potatoes and Peasant Revolts in Historical China.” Economic Journal 124, no. 575 (2014): 92118.CrossRefGoogle Scholar
Johnson, Ryan S.The Economic Progress of American Black Workers in a Period of Crisis and Change, 1916–1950.” Journal of Economic History 64, no. 2 (2004): 552–58.CrossRefGoogle Scholar
Kaplan, Greg, and Schulhofer-Wohl, Sam. “Inflation at the Household Level.” NBER Working Paper No. 22331, Cambridge, MA, 2016.Google Scholar
Kaplan, Jed O., Krumhardt, Kristen M., and Zimmermann, Niklaus. “The Prehistoric and Preindustrial Deforestation of Europe.” Quaternary Science Reviews 28, no. 27 (2009): 3016–34.CrossRefGoogle Scholar
Katz, Michael B. The People of Hamilton, Canada West: Family and Class in a Mid-Nineteenth-Century City. Cambridge: Harvard University Press, 1975.CrossRefGoogle Scholar
Kay, David, and Harmelen, Mark van. Activity Data - Delivering Benefits from the Data Deluge. London: Joint Information Systems Committee, 2012.Google Scholar
Kerber, Richard A., O'Brien, Elizabeth, Smith, Ken R., et al. “Familial Excess Longevity in Utah Genealogies.” Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56, no. 3 (2001): B130–B39.CrossRefGoogle ScholarPubMed
Khoury, Muin J.Planning for the Future of Epidemiology in the Era of Big Data and Precision Medicine.” American Journal of Epidemiology 182, no. 12 (2015): 977–79.Google ScholarPubMed
King, Gary. “Ensuring the Data-Rich Future of the Social Sciences.” Science 331, no. 6018 (2011): 719–21.CrossRefGoogle ScholarPubMed
Kirsch, David A.The Record of Business and the Future of Business History: Establishing a Public Interest in Private Business Records.” Library Trends 57, no. 3 (2009): 352–70.Google Scholar
Knights, Peter R. The Plain People of Boston, 1830–1860: A Study in City Growth. New York: Oxford University Press, 1971.Google Scholar
Kohara, Miki, and Kamiya, Yusuke. “Maternal Employment and Food Produced at Home: Evidence from Japanese Data.” Review of Economics of the Household 14, no. 2 (2016): 417–42.CrossRefGoogle Scholar
Kolk, Martin. “Multigenerational Transmission of Family Size in Contemporary Sweden.” Population Studies 68, no. 1 (2014): 111–29.CrossRefGoogle ScholarPubMed
Kosnik, Lea-Rachel D.What Have Economists Been Doing for the Last 50 Years? A Text Analysis of Published Academic Research from 1960–2010.” Economics 9 (2015): 138.Google Scholar
Kramer, Adam D. I., Guillory, Jamie E., and Hancock, Jeffrey T.. “Experimental Evidence of Massive-Scale Emotional Contagion through Social Networks.” Proceedings of the National Academy of Sciences 111, no. 24 (2014): 8788–90.CrossRefGoogle ScholarPubMed
Lazear, Edward P., and Shaw, Kathryn L.. The Structure of Wages: An International Comparison. Chicago: University of Chicago Press, 2009.CrossRefGoogle Scholar
Lee, James Z., and Campbell, Cameron D.. “China Multi-Generational Panel Dataset, Liaoning (CMGPD-LN), 1749–1909.” Ann Arbor: Inter-university Consortium for Political and Social Research, 2016. http://www.icpsr.umich.edu/icpsrweb/DSDR/series/00265.Google Scholar
Lee, James Z., Chen, Shuang, Campbell, Cameron D., et al. “China Multi-Generational Panel Dataset, Shuangcheng (CMGPD-SC), 1866–1913.” Ann Arbor: Inter-university Consortium for Political and Social Research, 2017. http://www.icpsr.umich.edu/icpsrweb/DSDR/series/00265.Google Scholar
Leicester, Andrew, and Oldfield, Zoe. “Using Scanner Technology to Collect Expenditure Data.” Fiscal Studies 30, no. 3–4 (2009): 309–37.CrossRefGoogle Scholar
Levin, Sharon G., Levin, Stanford L., and Meisel, John B.. “Market Structure, Uncertainty, and Intrafirm Diffusion: The Case of Optical Scanners in Grocery Stores.” Review of Economics and Statistics 74, no. 2 (1992): 345–50.Google Scholar
Liu, Mingliang, and Tian, Hanqin. “China's Land Cover and Land Use Change from 1700 to 2005: Estimations from High-Resolution Satellite Data and Historical Archives.” Global Biogeochemical Cycles 24, no. 3 (2010).CrossRefGoogle Scholar
Lloyd, Christopher, Metzer, Jacob, and Sutch, Richard. Settler Economies in World History. Leiden: Brill, 2013.CrossRefGoogle Scholar
Logan, John R., and Shin, Hyoung-jin. “Assimilation By the Third Generation? Marital Choices of White Ethnics at the Dawn of the Twentieth Century.” Social Science Research 41, no. 5 (2012): 11161125.CrossRefGoogle ScholarPubMed
Logan, John R., and Zhang, Weiwei. “White Ethnic Residential Segregation in Historical Perspective: US Cities in 1880.” Social Science Research 41, no. 5 (2012): 1292–306.CrossRefGoogle ScholarPubMed
Logan, Trevon, and Parman, John. “The National Rise in Residential Segregation.” Journal of Economic History 77, no. 1 (2017): 127–70.CrossRefGoogle Scholar
Long, Jason. “Rural-Urban Migration and Socioeconomic Mobility in Victorian Britain.” Journal of Economic History 65, no. 1 (2005): 135.CrossRefGoogle Scholar
Long, Jason, and Ferrie, Joseph P.. “The Path to Convergence: Intergenerational Occupational Mobility in Britain and the US in Three Eras.” Economic Journal 117, no. 519 (2007): C61C71.CrossRefGoogle Scholar
Long, Jason, and Ferrie, Joseph P.. “Intergenerational Occupational Mobility in Britain and the U.S. Since 1850.” American Economic Review 103, no. 4 (2013): 1109–37.Google Scholar
Lundh, Christer, and Kurosu, Satomi, et al. Similarity in Difference: Marriage in Europe and Asia, 1700–1900. Cambridge: MIT Press, 2014.CrossRefGoogle Scholar
Lusk, Jayson L., and Brooks, Kathleen. “Who Participates in Household Scanning Panels?American Journal of Agricultural Economics 93, no. 1 (2011): 226–40.CrossRefGoogle Scholar
Lynge, Elsebeth, Sandegaard, Jakob Lynge, and Rebolj, Matejka. “The Danish National Patient Register.” Scandinavian Journal of Public Health 39, no. 7 suppl. (2011): 3033.CrossRefGoogle ScholarPubMed
Maloney, Thomas N., Hanson, Heidi, and Smith, Ken. “Occupation and Fertility on the Frontier: Evidence from the State of Utah.” Demographic Research 30 (2014): 853–86.CrossRefGoogle Scholar
Maxwell, Susan K., and Sylvester, Kenneth M.. “Identification of ‘Ever-Cropped’ Land (1984–2010) Using Landsat Annual Maximum NDVI Image Composites: Southwestern Kansas Case Study.” Remote Sensing of Environment 121 (2012): 186–95.CrossRefGoogle ScholarPubMed
Melser, Daniel. “Accounting for the Effects of New and Disappearing Goods Using Scanner Data.” Review of Income and Wealth 52, no. 4 (2006): 547–68.CrossRefGoogle Scholar
Mill, Roy, and Stein, Luke C.D.. “Race, Skin Color, and Economic Outcomes in Early Twentieth-Century America.” Tucson: Arizona State University, 2016. Available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2741797.Google Scholar
Miller, Rena S., and Shorter, Gary. “High Frequency Trading: Overview of Recent Developments.” Washington, DC: Congressional Research Service, 2016.Google Scholar
Minnesota Population Center. “North Atlantic Population Project: Complete Count Microdata. Version 2.2” [machine readable database]. Minneapolis, MN: Minnesota Population Center [distributor], 2015a.Google Scholar
Minnesota Population Center. 2015b. Terra Populus [Dataset]. Minneapolis: Minnesota Population Center.Google Scholar
Mitchener, Kris James. “The 4D Future of Economic History: Digitally-Driven Data Design.” Journal of Economic History 75, no. 4 (2015): 1234–39.CrossRefGoogle Scholar
Monroe, Burt. “The Five Vs of Big Data Political Science: Introduction to the Virtual Issue on Big Data in Political Science.” Political Analysis, Virtual Issue 4 (2013): 19.CrossRefGoogle Scholar
National Centers for Environmental Information. “Climate Data Online.” Silver Spring, MD: National Oceanic and Atmospheric Administration, 2016.Google Scholar
Newman, David J., and Block, Sharon. “Probabilistic Topic Decomposition of an Eighteenth-Century American Newspaper.” Journal of the American Society for Information Science and Technology 57, no. 6 (2006): 753–67.CrossRefGoogle Scholar
O'Connell, Allan F., Nichols, James D., and Ullas Karanth, K.. Camera Traps in Animal Ecology: Methods and Analyses. Dordrecht: Springer, 2011.CrossRefGoogle Scholar
Olmstead, Alan L., and Rhode, Paul W.. “Adapting North American Wheat Production to Climatic Challenges, 1839–2009.” Proceedings of the National Academy of Sciences 108, no. 2 (2011): 480–85.CrossRefGoogle ScholarPubMed
Olmstead, Alan L., and Rhode, Paul W.. “Were Antebellum Cotton Plantations Factories in the Field?” In Enterprising America: Businesses, Banks, and Credit Markets in Historical Perspective, edited by Collins, William J. and Margo, Robert A., 245–76. Chicago: University of Chicago Press, 2015.Google Scholar
Parker, William N. The Structure of the Cotton Economy of the Antebellum South. Washington, DC: Agricultural History Society, 1970.Google Scholar
Parker, William N., and Gallman, Robert E.. “Southern Farms Study, 1860.” Ann Arbor: Inter-university Consortium for Political and Social Research, 1991.Google Scholar
Parton, William J., Gutmann, Myron P., Hartman, Melannie D., et al. “Great Plains Population and Environment Data: Biogeochemical Modeling Data, 1860–2003.” Ann Arbor: Inter-university Consortium for Political and Social Research, 2012.Google Scholar
Parton, William J., Gutmann, Myron P., Hartman, Melannie D., et al. “Simulated Biogeochemical Impacts of Historical Land-Use Changes in the U.S. Great Plains from 1870 to 2003.” In Land Use and the Carbon Cycle: Science and Applications in Coupled Natural-Human Systems, edited by Brown, Daniel G., Robinson, Derek T., French, Nancy H. F., et al., 287304. New York: Cambridge University Press, 2013.CrossRefGoogle Scholar
Parton, William J., Gutmann, Myron P., Merchant, Emily R., et al. “Measuring and Mitigating Agricultural Greenhouse Gas Production in the US Great Plains, 1870–2000.” Proceedings of the National Academy of Sciences 112, no. 34 (2015): E4681–E88.CrossRefGoogle ScholarPubMed
Pearson, David. Johnsonville, Continuity and Change in a New Zealand Township. Sydney: George Allen & Unwin, 1980.Google Scholar
Porter, John H., Hanson, Paul C., and Lin, Chau-Chin. “Staying Afloat in the Sensor Data Deluge.” Trends in Ecology & Evolution 27, no. 2 (2011): 121–29.Google ScholarPubMed
Roberts, Evan, and Warren, John Robert. “Family Structure and Childhood Anthropometry in Saint Paul, Minnesota in 1918.” History of the Family 22, no. 2–3 (2017): 258–90.CrossRefGoogle Scholar
Rönnbäck, Klas. “Climate, Conflicts, and Variations in Prices on Pre-Colonial West African Markets for Staple Crops.” Economic History Review 67, no. 4 (2014): 1065–88.CrossRefGoogle Scholar
Ruggles, Steven. “Reconsidering the Northwest European Family System: Living Arrangements of the Aged in Comparative Historical Perspective.” Population and Development Review 35, no. 2 (2009): 249–73.CrossRefGoogle ScholarPubMed
Ruggles, Steven. “Big Microdata for Population Research.” Demography 51, no. 1 (2014): 287–97.CrossRefGoogle ScholarPubMed
Ruggles, Steven, Genadek, Katie, Goeken, Ronald, et al. “Integrated Public Use Microdata Series: Version 6.0” [machine-readable database]. Minneapolis, MN: University of Minnesota, 2015. www.ipums.org.Google Scholar
Ruggles, Steven, and Menard, Russell. “The Minnesota Historical Census Projects.” Historical Methods 28, no. 1 (1995): 610.CrossRefGoogle Scholar
Ruggles, Steven, Roberts, Evan, Sarkar, Sula, et al. “The North Atlantic Population Project: Progress and Prospects.” Historical Methods 44, no. 1 (2011): 16.CrossRefGoogle ScholarPubMed
Saperstein, Aliya, and Gullickson, Aaron. “A ‘Mulatto Escape Hatch’ in the United States? Examining Evidence of Racial and Social Mobility During the Jim Crow Era.” Demography 50, no. 5 (2013): 1921–42.CrossRefGoogle Scholar
Shah, Dhavan V., Cappella, Joseph N., and Russell Neuman, W.. “Big Data, Digital Media, and Computational Social Science: Possibilities and Perils.” Annals of the American Academy of Political and Social Science 659, no. 1 (2015): 613.CrossRefGoogle Scholar
Silver, Mick, and Heravi, Saeed. “Scanner Data and the Measurement of Inflation.” Economic Journal 111, no. 472 (2001): F383F404.CrossRefGoogle Scholar
Smith, Ken R. and Huntsman Cancer Institute. “Utah Population Database.” Salt Lake City: University of Utah, 2017. http://healthcare.utah.edu/huntsmancancerinstitute/research/updb/.Google Scholar
Star, Susan Leigh, and Griesemer, James R.. “Institutional Ecology, ‘Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907–39.” Social Studies of Science 19, no. 3 (1989): 387420.CrossRefGoogle Scholar
Sundstrom, William A.The Geography of Wage Discrimination in the Pre–Civil Rights South.” Journal of Economic History 67, no. 2 (2007): 410–44.CrossRefGoogle Scholar
Swanson, Alexandra, Kosmala, Margaret, Lintott, Chris, et al. “Snapshot Serengeti, High-Frequency Annotated Camera Trap Images of 40 Mammalian Species in an African Savanna.” Scientific Data 2 (2015): 150026.CrossRefGoogle Scholar
Swanson, Alexandra, Kosmala, Margaret, Lintott, Chris, et al. “A Generalized Approach for Producing, Quantifying, and Validating Citizen Science Data from Wildlife Images.” Conservation Biology 30, no. 3 (2016): 520–31.CrossRefGoogle ScholarPubMed
Sylvester, Kenneth M., Brown, Daniel G., Deane, Glenn D., et al. “Land Transitions in the American Plains: Multilevel Modeling of Drivers of Grassland Conversion (1956–2006).” Agriculture, Ecosystems & Environment 168 (2013): 715.CrossRefGoogle Scholar
Sylvester, Kenneth M., Brown, Daniel G., Leonard, Susan H., et al. “Exploring Agent-Level Calculations of Risk and Returns in Relation to Observed Land-Use Changes in the U.S. Great Plains, 1870–1940.” Regional Environmental Change 15, no. 2 (2015): 301–15.CrossRefGoogle ScholarPubMed
Sylvester, Kenneth M., Gutmann, Myron P., and Brown, Daniel G.. “At the Margins: Agriculture, Subsidies and the Shifting Fate of North America's Native Grassland.” Population and Environment 37, no. 3 (2016): 362–90.CrossRefGoogle ScholarPubMed
Sylvester, Kenneth M., and Rupley, Eric S. A.. “Revising the Dust Bowl: High above the Kansas Grasslands.” Environmental History 17, no. 3 (2012): 603–33.CrossRefGoogle ScholarPubMed
Thernstrom, Stephan. Poverty and Progress; Social Mobility in a Nineteenth Century City. Cambridge: Harvard University Press, 1964.Google Scholar
Thernstrom, Stephan. The Other Bostonians; Poverty and Progress in the American Metropolis, 1880–1970. Cambridge: Harvard University Press, 1973.CrossRefGoogle Scholar
Tinati, Ramine, Halford, Susan, Carr, Leslie, et al. “Big Data: Methodological Challenges and Approaches for Sociological Analysis.” Sociology 48, no. 4 (2014): 663–81.CrossRefGoogle Scholar
Tsuya, Noriko O., Wang, Feng, Alter, George, et al. Prudence and Pressure: Reproduction and Human Agency in Europe and Asia, 1700–1900. Cambridge: MIT Press, 2010.Google Scholar
Turner, Frederick Jackson. “The Significance of the Frontier in American History.” Proceedings of the State Historical Society of Wisconsin 41 (1893): 79112.Google Scholar
Université du Québec à Chicoutimi; Université Laval; McGill University and Université de Montréal. “BALSAC Population Database.” Chicoutimi: Université du Québec à Chicoutimi, 2017. http://balsac.uqac.ca/.Google Scholar
Varian, Hal R.Big Data: New Tricks for Econometrics.” Journal of Economic Perspectives 28, no. 2 (2014): 327.CrossRefGoogle Scholar
Ward, Jonathan Stuart, and Barker, Adam. “Undefined by Data: A Survey of Big Data Definitions.” arXiv preprint arXiv:1309.5821, 2013.Google Scholar
Willett, Kyle W., Lintott, Chris J., Bamford, Steven P., et al. “Galaxy Zoo 2: Detailed Morphological Classifications for 304 122 Galaxies from the Sloan Digital Sky Survey.” Monthly Notices of the Royal Astronomical Society 435, no. 4 (2013): 2835–60.CrossRefGoogle Scholar
Wrigley, Edward A., and Schofield, Roger. The Population History of England 1541–1871. Cambridge: Cambridge University Press, 1981.Google Scholar
Wyber, Rosemary, Vaillancourt, Samuel, Perry, William, et al. “Big Data in Global Health: Improving Health in Low-and Middle-Income Countries.” Bulletin of the World Health Organization 93, no. 3 (2015): 203208.CrossRefGoogle ScholarPubMed
Wynne, Brian. “Misunderstood Misunderstanding: Social Identities and Public Uptake of Science.” Public Understanding of Science 1, no. 3 (1992): 281304.CrossRefGoogle Scholar
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