An expert helps readers understand what the big economic picture means for their money—and how to respond. Today's investors must play an active role in managing their money. This guide introduces the leading U.S. economic indicators and shows how to use them to make better investment decisions. Indicators covered include: national output; employment; consumer reports; housing and construction; and inflation. • The recession: the days of putting money in an index fund and forgetting about it are over • Most books on economic indicators are too academic, aimed at professionals, and written before the financial crisis • Author with over 25 years of tracking the economy
This text provides a thorough explanation of the non-financial economic indicators that are closely watched by the financial markets. It details how the indicators are compiled and what the statistical significance is for the economy, as well as presenting insights into interpreting the data.
We are bombarded with economic numbers: unemployment, retail sales, inflation, GDP—the list goes on and on. Some analyst or another is constantly telling us about an obscure statistic that is the key to our future, or is apparently the indicator that the "Fed" will be using to key off its decisions. With economic numbers playing such a central role in the national and world dialogue on policy and markets, and spilling over into the political arena, a broad review of what they are all about is timely. This book reviews the critical US economic data, and how one may put the numbers into an intellectual structure that will depict evolving economic reality. The work is aimed at those who want and need to get some understanding about how the data contributes to a big picture of the economy and guides policy. The objective is for the reader to grasp the overall logic of the data—how each piece of the puzzle contributes to our understanding of the overall economy. This is the way the Fed looks at the numbers. There are other books that go through the economic numbers, but they do so in a "bottom-up" fashion, describing a series in some detail and adding something about how financial markets may respond to it. This book naturally has considerable discussion of series, but views them as part of the overall mosaic, not items of fundamental interest in themselves.
Maps capture data expressing the economic complexity of countries from Albania to Zimbabwe, offering current economic measures and as well as a guide to achieving prosperity Why do some countries grow and others do not? The authors of The Atlas of Economic Complexity offer readers an explanation based on "Economic Complexity," a measure of a society's productive knowledge. Prosperous societies are those that have the knowledge to make a larger variety of more complex products. The Atlas of Economic Complexity attempts to measure the amount of productive knowledge countries hold and how they can move to accumulate more of it by making more complex products. Through the graphical representation of the "Product Space," the authors are able to identify each country's "adjacent possible," or potential new products, making it easier to find paths to economic diversification and growth. In addition, they argue that a country's economic complexity and its position in the product space are better predictors of economic growth than many other well-known development indicators, including measures of competitiveness, governance, finance, and schooling. Using innovative visualizations, the book locates each country in the product space, provides complexity and growth potential rankings for 128 countries, and offers individual country pages with detailed information about a country's current capabilities and its diversification options. The maps and visualizations included in the Atlas can be used to find more viable paths to greater productive knowledge and prosperity.
Environmental Economics and Policy is a best-selling text for environmental economics courses. Offering a policy-oriented approach, it introduces economic theory, empirical fieldwork, and case studies that show how underlying economic principles provided the foundation for environmental policies. Key features include: Introductions to the theory and method of environmental economics, including externalities, benefit-cost analysis, valuation methods, and ecosystem goods and services. Extensive coverage of the major issues including climate change mitigation and adaptation, air and water pollution, and environmental justice. Boxed "Examples" and "Debates" throughout the text, which highlight global examples and major talking points. This text will be of use to undergraduate students of economics. Students will leave the course with a global perspective of how environmental economics has played and can continue to play a role in promoting fair and efficient environmental management. The text is fully supported with end-of-chapter summaries, discussion questions, and self-test exercises in the book. Additional online resources include references, as well as PowerPoint slides for each chapter.
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.
