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Socioeconomic Data For Economic Development Analysis

Socioeconomic Data For Economic Development Analysis. Joe Cortright, Impresa. May, 1999. Overview. 1. Objective 2. Methodology 3. Findings General Findings BLS/LMI Specific Findings 4. Helping Users. Objective. How can we improve understanding of state and local economies?

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Socioeconomic Data For Economic Development Analysis

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  1. Socioeconomic Data ForEconomic Development Analysis Joe Cortright, Impresa May, 1999

  2. Overview 1. Objective 2. Methodology 3. Findings • General Findings • BLS/LMI Specific Findings 4. Helping Users Prepared by Impresa, J. Cortright www.econdata.net

  3. Objective How can we improve understanding of state and local economies? • Assess attitudes and behaviors among practitioners • Identify system shortfalls and data needs • Recommend action by EDA, statistical agencies & users • Motivate and mobilize constituencies Prepared by Impresa, J. Cortright www.econdata.net

  4. Methodology • Focus Groups • Web-based Survey • Expert Interviews Prepared by Impresa, J. Cortright www.econdata.net

  5. Our Survey Prepared by Impresa, J. Cortright www.econdata.net

  6. Survey Population • Solicited via Email members of organizations • Economic Development • Planning • Academic/Regional Science • Others • Intensive, Web-based Survey • 613 responses Prepared by Impresa, J. Cortright www.econdata.net

  7. Findings • Who uses data? • What do they use it for? • How do they learn? • Concerns about data • How do users find data? • BLS/LMI Findings Prepared by Impresa, J. Cortright www.econdata.net

  8. Who uses data? • Cognoscenti (datascenti) • Executive & Legislative officials • Planners • Program Officers/Bureaucrats • Universities • Journalists Prepared by Impresa, J. Cortright www.econdata.net

  9. What do they use data for? Incredibly diverse uses for data • Economic development strategy & programs • Marketing & Planning • Workforce/labor market analysis • Academic & private research • Modeling • Facility Location/Industry Promotion Simple Techniques Dominate • Cross-Sectional and Time Series not Regressions Prepared by Impresa, J. Cortright www.econdata.net

  10. How do they learn to use data? • Learning by doing is critical • 87% self-taught in analytical techniques • 74% learn about data sources by using them • Web more frequently used than publications • Differences • Sophisticated Users (Top 25% Self rated) • more satisfied with learning opportunities • Typical Users • less satisfied with learning opportunities Prepared by Impresa, J. Cortright www.econdata.net

  11. Three recurring complaints • Not timely enough • Not enough geographic detail • Comparability Prepared by Impresa, J. Cortright www.econdata.net

  12. What improvements would they like to see? • Data access tools for web data • Microdata, using firm level data • Geo-coding & GIS, locating records in space • Sub-national export data • Measurement of the service sector • Industrial composition of temporary employment • Self-employed/microbusiness data • Interstate cost of living differentials Prepared by Impresa, J. Cortright www.econdata.net

  13. Awareness of Coming Changes is Low • ACS: American Community Survey (24%) • timeliness will improve • users need to understand confidence intervals • NAICS: North American Industry Classification System (37%) • better industry definitions • the mother of all series-breaks Prepared by Impresa, J. Cortright www.econdata.net

  14. Usefulness of Key Data Series Prepared by Impresa, J. Cortright www.econdata.net

  15. Rankings of BLS Series (Ranking of BLS series on a five point scale, 1 is best) Prepared by Impresa, J. Cortright www.econdata.net

  16. Kudos • “ES202 is very useful for us” • “OES matrices of occupation employment by industry are extremely useful to me” • “BLS has become enormously responsive to users of various series on their web page” • “CPI is a series I provide to users daily” • “Amount of BLS data on the web is wonderful” Prepared by Impresa, J. Cortright www.econdata.net

  17. Complaints • Web Access: “BLS data retrieval system is slow, unfriendly and cumbersome” • Comparable State Data: “Time consuming and frustrating to get the same figure from multiple states” • Cost of Living Differentials: “Cost of living stats are a real weakness” • Time Series: “Access to comparable data for 20+ years would be a real advantage” Prepared by Impresa, J. Cortright www.econdata.net

  18. Improving Accessibility or:The Data is Out There But like Sculley and Mulder, • Most users are still wandering around in a fog, • They suspect a conspiracy to keep them from finding the answer to their questions. • Nothing they learned at the academy prepared them for this. Prepared by Impresa, J. Cortright www.econdata.net

  19. Data Finding Strategies • Be a Nerd • Find a Nerd Prepared by Impresa, J. Cortright www.econdata.net

  20. Be a Nerd • Get your own data, chiefly from the Net • Primarily self-taught, learning by doing • Somewhat reliant on peer learning • Time consuming and often random web-searches Prepared by Impresa, J. Cortright www.econdata.net

  21. Find a Nerd • Find someone who knows about data • Key candidates • State LMI Offices • Census State Data Centers • AUBER, ACCRA members • Libraries Prepared by Impresa, J. Cortright www.econdata.net

  22. Most popular websites • Census Bureau (166) • BLS (67) • BEA (43) • STAT USA (13) • FedStats (12) • Federal Reserve branches (10) • Commerce Department (8) • Government Information Sharing Project (8) Prepared by Impresa, J. Cortright www.econdata.net

  23. Lessons from model web sites • Ease of use is paramount • visually appealing • clickable maps and lists • one or two step access to data • Cross-cutting access to data • Multiple sources in one place • Time series and cross-sectional comparisons • Powerful but well-hidden report generation Prepared by Impresa, J. Cortright www.econdata.net

  24. Government Information Sharing Project: Simple Prepared by Impresa, J. Cortright www.econdata.net

  25. Government Information Sharing Project: Clickable Prepared by Impresa, J. Cortright www.econdata.net

  26. Dismal Sciences: Profiles Prepared by Impresa, J. Cortright www.econdata.net

  27. Dismal Scientist: Rankings Prepared by Impresa, J. Cortright www.econdata.net

  28. Econ-Line.Com: State & Metro Profiles Prepared by Impresa, J. Cortright www.econdata.net

  29. Economagic.Com Prepared by Impresa, J. Cortright www.econdata.net

  30. Economagic.com: Charts Prepared by Impresa, J. Cortright www.econdata.net

  31. www.EconData.Net Prepared by Impresa, J. Cortright www.econdata.net

  32. User’s Guide: Free • 100 page User’s Guide • “Complete Dummies” Style • Explanations, Links, Contacts • Free from EDAjmcnamee@eda.doc.gov Prepared by Impresa, J. Cortright www.econdata.net

  33. Key Addresses • www.EconData.Net • jmcnamee@eda.doc.gov Prepared by Impresa, J. Cortright www.econdata.net

  34. From Here: • Understand User Needs • Build the System • Embrace Technology Prepared by Impresa, J. Cortright www.econdata.net

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