In this chapter, I discuss innovation and entrepreneurship in residential real estate and construction (housing). Based on R&D spending and patent statistics, housing does not appear to be a very innovative sector. But in the last two decades, there has been a significant increase in the amount of investment going to real estate technology companies. I discuss the companies and technologies which have drawn the most attention from investors. I then review the literature on two major innovation trends in housing: the growth of the internet as a tool for housing search, and the development of home-sharing platforms which allow homeowners to use their homes as short-term rentals. These innovations have likely increased the efficiency of housing markets, leading to higher quality matches between buyers and sellers, and more efficient utilization of space. However, the effects are hard to measure due to the difficulty of separating quality changes from price changes. In comparison to residential real estate, there appears to have been less recent innovation in residential construction. In many areas, residential construction is artificially constrained by local land use policies, and estimates from the literature suggest that relaxing these constraints could increase economic growth significantly. Finally, I discuss anti-competitive practices in real estate which may hinder entrepreneurship and the adoption of new innovations, and I discuss how innovation and entrepreneurship in other sectors may affect the housing market.

"Innovation and entrepreneurship are ubiquitous today, both as fields of study and as starting points for conversations among experts in government and economic development. But while these areas on continue to attract public and private investments, many measurements of their resulting economic growth-including productivity growth and business dynamism-have remained modest. Why this difference? Because not all business sectors are the same, and the transformative gains of some industries have been offset by stagnation or contraction in others. Accordingly, a nuanced understanding of the economy requires a nuanced understanding of where innovation and entrepreneurship occur and where they matter. Answering these questions allows for strategic public investment and the infrastructure for economic growth.The Role of Innovation and Entrepreneurship in Economic Growth, the latest entry in the NBER conference series, seeks to codify these answers. The editors leverage industry studies to identify specific examples of productivity improvements enabled by innovation and entrepreneurship, including those from new production technologies, increased competition, new organizational forms, and other means. Taken together, the volume illuminates whether the contribution of innovation and entrepreneurship to economic growth is likely to be concentrated, be it selected sectors or more broadly"--

This volume presents studies from experts in twelve industries, providing insights into the future role of innovation and entrepreneurship in driving economic growth across sectors. We live in an era in which innovation and entrepreneurship seem ubiquitous, particularly in regions like Silicon Valley, Boston, and the Research Triangle Park. But many metrics of economic growth, such as productivity growth and business dynamism, have been at best modest in recent years. The resolution of this apparent paradox is dramatic heterogeneity across sectors, with some industries seeing robust innovation and entrepreneurship and others seeing stagnation. By construction, the impact of innovation and entrepreneurship on overall economic performance is the cumulative impact of their effects on individual sectors. Understanding the potential for growth in the aggregate economy depends, therefore, on understanding the sector-by-sector potential for growth. This insight motivates the twelve studies of different sectors that are presented in this volume. Each study identifies specific productivity improvements enabled by innovation and entrepreneurship, for example as a result of new production technologies, increased competition, or new organizational forms. These twelve studies, along with three synthetic chapters, provide new insights on the sectoral patterns and concentration of the contributions of innovation and entrepreneurship to economic growth.

Businesses, consumers, industry groups, and governments understand the importance of innovation and the innovation process for continued economic success and improvements in quality of life. However, innovation remains an opaque topic. A paradox exists in housing at-large; using innovation is vital yet accounting for the value to individual organizations remains a challenge. This paradox is supported by a landscape that includes a sizeable graveyard of failed attempts at innovation on grand and small scales. This book seeks to decrease the opacity of innovation processes in residential construction and housing. Along with the next book in the collection, this book addresses key questions pertinent to the potential for widespread diffusion of green buildings and for improvements in community sustainability. The overarching purpose of this book is to provide context and foundation for later books in the collection and to assist readers in peeling back the complex layers of innovation in housing and residential construction.

The central role of the housing market in the recent recession raised a series of questions about similar episodes throughout economic history. Were the underlying causes of housing and mortgage crises the same in earlier episodes? Has the onset and spread of crises changed over time? How have previous policy interventions either damaged or improved long-run market performance and stability? This volume begins to answer these questions, providing a much-needed context for understanding recent events by examining how historical housing and mortgage markets worked—and how they sometimes failed. Renowned economic historians Eugene N. White, Kenneth Snowden, and Price Fishback survey the foundational research on housing crises, comparing that of the 1930s to that of the early 2000s in order to authoritatively identify what contributed to each crisis. Later chapters explore notable historical experiences with mortgage securitization and the role that federal policy played in the surge in home ownership between 1940 and 1960. By providing a broad historical overview of housing and mortgage markets, the volume offers valuable new insights to inform future policy debates.

This proceedings book focuses on innovation, cooperation, and sustainable development in the fields of construction management and real estate. The book provides a detailed analysis and description of the disciplinary frontiers in the field of building management and real estate and how they can be promoted in the context of the epidemic. A wide variety of papers provide a reference value for both scholars and practitioners. The proceedings book is the documentation of “the 25th International Symposium on Advancement of Construction Management and Real Estate” (CRIOCM 2020), which was held at the School of Public Administration, Central China Normal University, Wuhan, China, in 2020.

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.