User’s Guide

Socioeconomic Data for Understanding Your Regional Economy: A User’s Guide

This 100-page guide to finding and using socioeconomic data to analyze local and regional economies is now available in print and on the Web. Written in an easy-to-read, informal style, the User’s Guide offers practical advice on a wide range of data topics, drawn from the experience of analysts nationwide.

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Economic development decisions are supposed to be based on good data analysis. But a dirty little secret of economic development is that no one teaches us much of anything about what data are available, how to get them, and what to do with them. Socioeconomic Data for Understanding Your Regional Economy: A User’s Guide aims to address this problem.

The User’s Guide is a comprehensive and easy-to-use reference for both novices and experienced data users to find and use economic statistics. The heart of the User’s Guide is a thorough, plainly written explanation of the principal data series used for analyzing the performance and structure of local economies, on topics such as population, income and earnings, employment and unemployment, cost of living, and exports. For each series, the User’s Guide lists specific measures, time frame, geographic detail, methodology, means to accessing the data, and staff contacts. The User’s Guide also gives overviews of key statistical agencies, points to data intermediaries who can help you get the data you need, discusses approaches to using data, provides references for further self-education, and lists important data sources to put in your library.

Contents

Part One: The Basics

  1. Tools of the Trade
  2. Data Sources: Where the Numbers Come From
  3. Statistics for Analyzing Your Economy
  4. Data Intermediaries: Guides in the Statistical Jungle

Part Two: Lessons of Practice

  1. Ten Habits of Highly Effective Data Analysts
  2. Bookshelf Basics for Economic Analysts
  3. The Web’s Twelve Best Sources for Regional Data
  4. Seven Pitfalls of Data Analysis
  5. Advanced Analysis: Power Tools for Data