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Uneven fortunes in U.S. industry

Tracking types of industrial production

This FRED graph shows three very different stories for three different types of goods production in the U.S. The clothing sector dominated the other two for about 60 of the 70 years shown in this sample, only to collapse in the first decade of the millennium and slowly decline thereafter. This shift is a direct consequence of cheaper manufacturing opportunities abroad. The automotive products sector has been steadily increasing its output, except for some hard times during the financial crisis, when car manufacturers were struggling. Occasionally, short dips occurred during strikes in the car industry. Finally, the electronics sector comes out of nowhere in the 1990s to establish itself as a core component of American industry.

How this graph was created: Search for the release table for the Industrial Production index by market and industry group, select the series shown here (or those you’d like to see), and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: IPB51110S, IPB51121S, IPB51212S

Jealous of the Aleutian commute?

Census data show average U.S. commutes range from 5 to 45 minutes

FRED has all sorts of socioeconomic data beyond the traditional macroeconomic fare, and today we highlight data on commuting time provided by the U.S. Census Bureau. These data are available at the county level, which makes it possible to compare various areas of the country. In the graph above, we can see that commuting times on the coasts (New York and Los Angeles) are longer and have increased more rapidly than the commuting times in St. Louis. This should surprise no one, but we thought we’d highlight a perk for those living in FRED’s hometown.

We can get a bigger (and much less anecdotal) picture by looking at the relevant GeoFRED map below. Non-urban commuting times tend to be shorter, but you’ll have a hard time finding the county with the shortest commuting time: We centered the map on the continental U.S., so you have to work a little to find Aleutians East Borough, Alaska, which has a daily commute of 5.13 minutes, closely followed by its neighboring counties. In the continental U.S., Kent County, Texas, has the shortest commute: 7.7 minutes. The longest is Clay County, West Virginia, which beats the metropolitan areas with a commute of over 45 minutes.

How this graph was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: B080ACS006037, B080ACS029510, B080ACS036061

500 for the FRED Blog

Recognizing the FRED team and its partners

This is the 500th post for the FRED Blog, which is a great opportunity to acknowledge all those who make FRED the wonderful data tool that it is.

First, there’s the FRED team itself. These dedicated data specialists and web developers sustain and expand FRED’s structure and service. Of course, the fuel behind FRED is data and FRED’s mission is to disseminate the data. So, it’s the work of 87 data-producing institutions and agencies that allow FRED to do this—by collecting and producing data with integrity and usefulness. See the list of data producers below, but also indulge us for a moment as we acknowledge one especially effective partnership.

The U.S. Census Bureau is one of FRED’s most prolific data producers, and their data team in the Economic Indicators Division has worked closely with the FRED team to ensure all their series are in top form. The two teams share a commitment to deliver data to the public to help everyone make better economic decisions.

The Census team also promotes the FRED mobile apps in their economic indicator press releases, since they made the choice to take advantage of those FRED apps instead of creating their own. By doing so, they conserved funds and avoided duplication of effort—one example of what the two teams call “smart government.” Partnerships like this are a win-win-win for data producers, FRED, and users who need access to the data.

For a deeper dive into this world of data, take a look at the St. Louis Fed’s 2018 Annual Report, which is all about FRED and its family of data and information services. Read the essays, watch the interviews, and find out what FRED enthusiasts have to say about the importance of data access for informed decisionmaking.

FRED’S DATA PRODUCERS AND PARTNERS

U.S. Institutions and Agencies

Research and Policy: The Federal Reserve Banks of Atlanta, Chicago, Cleveland, Dallas, Kansas City, New York, Philadelphia, Richmond, San Francisco, and St. Louis (of course) and the Board of Governors of the Federal Reserve System, including the Federal Open Market Committee; National Bureau of Economic Research, Council of Economic Advisers, Dartmouth Atlas of Healthcare

U.S. Government: Bureau of Economic Analysis, Bureau of Labor Statistics, Census Bureau, Congressional Budget Office, Bureau of Transportation Statistics, Department of Housing and Urban Development, Department of Labor, Department of the Treasury (including Fiscal Service and Internal Revenue Service), Employment and Training Administration, Energy Information Administration, Federal Highway Administration, Federal Housing Finance Agency, Office of Management and Budget, Patent and Trademark Office, Federal Deposit Insurance Corporation, Federal Financial Institutions Examination Council, Federal Bureau of Investigation, Centers for Disease Control and Prevention

Professional: National Association of Realtors, Automatic Data Processing, Inc., Cass Information Systems, Inc., DHI Group, Inc.

Analytical, Financial, Exchange: Haver Analytics, Moody’s, S&P Dow Jones, Equifax, Freddie Mac, NASDAQ, Coinbase, Chicago Board Options Exchange, Wilshire Associates

Academic: Oklahoma State University, University of California–Davis, University of Louisville’s Logistics and Distribution Institute, University of Michigan, University of Pennsylvania

International Institutions and Agencies

The central banks of England, Italy, Japan, Mexico, Turkey, Germany, Australia, and Switzerland; the European Central Bank, the World Bank, Eurostat, International Monetary Fund, Bank for International Settlements, Organisation for Economic Co-operation and Development, JP. Cabinet Office (Japan), GB. Office for National Statistics (Great Britain), Nikkei Industry Research Institute, ICE Benchmark Administration Limited (IBA), University of Groningen

Suggested by George Fortier.



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