Large Databases In Economic History

‘Big data’ is now readily available to economic historians, thanks to the digitisation of primary sources, collaborative research linking different data sets, and the publication of databases on the internet. Key economic indicators, such as the consumer price index, can be tracked over long periods, and qualitative information, such as land use, can be converted to a quantitative form. In order to fully exploit these innovations it is necessary to use sophisticated statistical techniques to reveal the patterns hidden in datasets, and this book shows how this can be done. A distinguished group of economic historians have teamed up with younger researchers to pilot the application of new techniques to ‘big data’. Topics addressed in this volume include prices and the standard of living, money supply, credit markets, land values and land use, transport, technological innovation, and business networks. The research spans the medieval, early modern and modern periods. Research methods include simultaneous equation systems, stochastic trends and discrete choice modelling. This book is essential reading for doctoral and post-doctoral researchers in business, economic and social history. The case studies will also appeal to historical geographers and applied econometricians.

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

Historical scholarship is currently undergoing a digital turn. All historians have experienced this change in one way or another, by writing on word processors, applying quantitative methods on digitalized source materials, or using internet resources and digital tools. Digital Histories showcases this emerging wave of digital history research. It presents work by historians who – on their own or through collaborations with e.g. information technology specialists – have uncovered new, empirical historical knowledge through digital and computational methods. The topics of the volume range from the medieval period to the present day, including various parts of Europe. The chapters apply an exemplary array of methods, such as digital metadata analysis, machine learning, network analysis, topic modelling, named entity recognition, collocation analysis, critical search, and text and data mining. The volume argues that digital history is entering a mature phase, digital history ‘in action’, where its focus is shifting from the building of resources towards the making of new historical knowledge. This also involves novel challenges that digital methods pose to historical research, including awareness of the pitfalls and limitations of the digital tools and the necessity of new forms of digital source criticisms. Through its combination of empirical, conceptual and contextual studies, Digital Histories is a timely and pioneering contribution taking stock of how digital research currently advances historical scholarship.

This volume explores economic, social, and political dimensions of three catastrophic famines which struck mid-nineteenth and early-twentieth century Europe; the Irish Famine (An Gorta Mór ) of 1845–1850, the Finnish Famine (Suuret Nälkävuodet) of the 1860s and the Ukrainian Famine (Holodomor) of 1932/1933. In addition to providing new insights into these events on international, national and regional scales, this volume contributes to an increased comparative historiography in historical famine studies. The parallel studies presented in this book challenge and enhance established understandings of famine tragedies, including: famine causation and culpability; social and regional famine vulnerabilities; core–periphery relationships between nations and regions; degrees of national autonomy and self-sufficiency; as well as famine memory and identity. Famines in European Economic History advocates that the impact and long-term consequences of famine for a nation should be understood in the context of evolving geopolitical relations that extend beyond its borders. Furthermore, regional structures within a nation can lead to unevenness in both the severity of the immediate famine crisis and the post-famine recovery. This book will be of interest to those in the fields of economic history, European history and economic geography.

Der Sammelband Computational Social Science in the Age of Big Data beschäftigt sich mit Konzepten, Methoden, Tools und Anwendungen (automatisierter) datengetriebener Forschung mit sozialwissenschaftlichem Hintergrund. Der Fokus des Bandes liegt auf der Etablierung der Computational Social Science (CSS) als aufkommendes Forschungs- und Anwendungsfeld. Es werden Beiträge international namhafter Autoren präsentiert, die forschungs- und praxisrelevante Themen dieses Bereiches besprechen. Die Herausgeber forcieren dabei einen interdisziplinären Zugang zum Feld, der sowohl Online-Forschern aus der Wissenschaft wie auch aus der angewandten Marktforschung einen Einstieg bietet.

History and Economic Life offers students a wide-ranging introduction to both quantitative and qualitative approaches to interpreting economic history sources from the Middle Ages to the Twentieth Century. Having identified an ever-widening gap between the use of qualitative sources by cultural historians and quantitative sources by economic historians, the book aims to bridge the divide by making economic history sources more accessible to students and the wider public, and highlighting the need for a complementary rather than exclusive approach. Divided into two parts, the book begins by equipping students with a toolbox to approach economic history sources, considering the range of sources that might be of use and introducing different ways of approaching them. The second part consists of case studies that examine how economic historians use such sources, helping readers to gain a sense of context and understanding of how these sources can be used. The book thereby sheds light on important debates both within and beyond the field, and highlights the benefits gained when combining qualitative and quantitative approaches to source analysis. Introducing sources often avoided in culturally-minded history or statistically-minded economic history courses respectively, and advocating a combined quantitative and qualitative approach, it is an essential resource for students undertaking source analysis within the field.

This book gathers a selection of peer-reviewed papers presented at the second Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020) conference, held in Shanghai, China, on 28–29 December 2020. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

The relationship between natural capital and economic growth is an open debate in the field of economic development. Is an abundance of natural resources a blessing or a curse for economic performance? The field of Economic History offers an excellent vantage to explore the relevance of institutions, technical progress and supply-demand drivers. Natural Resources and Economic Growth contains theoretical and empirical articles by leading scholars who have studied this subject in different historical periods from the 19th century to the present day and in different parts of the world. Part I presents the theoretical issues and discusses the meaning of the "curse" and the relevance of the historical perspective. Part II captures the diversity of experiences, presenting thirteen independent case studies based on historical results from North and South America, Africa, Asia, Oceania and Europe. This book emphasizes that an abundance of natural resources is not a fixed situation. It is a process that reacts to changes in the structure of commodity prices and factor endowments, and progress requires capital, labour, technical change and appropriate institutional arrangements. This abundance is not a given, but is part of the evolution of the economic system. History shows that institutional quality is the key factor to deal with abundant natural resources and, especially, with the rents derived from their use and exploitation. This wide ranging volume will be of great relevance to all those with an interest in economic history, development, economic growth, natural resources, world history and institutional economics.