Executives and managers hear or read headlines about recent economic data nearly every business day. Most important economic statistics are the products of programs designed to collect and analyze data to report summary results at regular intervals. Properly interpreted, these economic indicators provide useful barometers for different aspects of the economy and identify trends that aid better planning decisions. Economic indicators are available at the national level, state level, and even the regional and municipal level. This text focuses on economic indicators for the overall U.S. economy, identifying major categories of economic indicators and describing the key indicators in each of the categories. The text will also provide guidance for interpreting indicators expressed in terms of an index (which reports values as percentage of a base period value) or in real dollar values (which remove the impact of inflation.) Most key economic indicators are reported promptly on the World Wide Web and provided as formatted time series that can be readily downloaded and analyzed. The text will include links to the sources for key economic indicators as well as websites that maintain calendars of upcoming announcements and consensus forecasts of the indicators shortly prior to a formal announcement. This book is a companion to two other Business Expert Press by the authors that address managerial economics and time series data/forecasting. Together these books will equip the manager and the student with a solid understanding of economic indicators and how to analyze them.
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Donald N. Stengel is a professor and chair of the Department of Information Systems and Decision Sciences at California State University, Fresno. Previously he served as the director of the MBA program at California State University, Fresno. He received a PhD in Engineering-Economic Systems from Stanford University. Prior to joining the faculty at California State University, Fresno, Dr. Stengel worked for eight years as a management consultant developing planning models for agriculture and energy.
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