Economic Data Archive

Forecasting with Internet Search Data – Liberty Street Economics

A January 4 article from the New York Fed’s blog, Liberty Street Economics, suggests that Internet search statistics can be used as coincident indicators, demonstrating correlations between keyword search frequency and time-lagged economics data releases. The authors also suggest that Internet search statistics may be useful leading indicators for the movements of financial markets in the presence of language barriers or other impediments to efficient information aggregation.

Forecasting with Internet Search Data – Liberty Street Economics.

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Cullen Roche: Rail Traffic Shows Continued Economic Expansion

On his excellent blog, Pragmatic Capitalism, Cullen Roche regularly features charts of data drawn from the AAR Weekly Rail Traffic Summary.  At the present time, Roche does not see a recession on the immediate horizon.  I didn’t see a chart in the most recent edition of Roche’s coverage of the rail data, but much of the AAR weekly summary data can be easily extracted from their PDF reports using simple text-processing tools.

Read more at Pragmatic Capitalism:  RAIL TRAFFIC SHOWS CONTINUED ECONOMIC EXPANSION | PRAGMATIC CAPITALISM.

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Data Directory Roundup

I recently ran across several data directories. This is not a complete list, but it does cover some of the major ones:

  1. Government Data Directories
    • Eurostat – Statistical and economics data on the Euro area countries.
    • Data.gov – An Obama administration initiative to unify the federal government’s published data. There is quite a bit of government data here, along with information on its format and other metadata, but it doesn’t have everything. Still, it’s worth checking out.
    • FedStats – while there is no data on this site, it does link together scores of the major U.S. government data providers. A great starting point for finding U.S. government data.
  2. Commercial Data Directories
    • Infochimps Data Marketplace – Infochimps bills itself as the “Amazon of data.” I wouldn’t go that far, but they have been around for a while and do have some valuable data sets, and it is worth taking a look if you are thinking of selling data.
    • Factual – This is the Amazon of data.
    • Economagic – An extensive directory of datasets, with charting capabilities and data downloads. It is easy to use and puts the data right at your fingertips.
    • EconData.net – An extensive set of links to economics data sites.
  3. Central Bank Data Directories
    • People’s Bank of China Statistics – The site is mostly in Chinese, and there isn’t a whole lot of data here. If you are aware of a better source for Chinese economics data, please let me know.
    • Federal Reserve Economic Data – This is a fantastic resource which is heavily used by economists. It contains thousands of time series covering numerous aspects of national and regional economics, searchable, linked and organized into folders. The data is updated relatively quickly (usually the day following its release).
    • European Central Bank Statistical Data Warehouse – This site provides a top-down view of datasets covering various aspects the economies of countries in the Euro area.
  4. NGO Data Directories
  5. Educational and Nonprofit Data Directories
    • B&E DataLinks – An excellent data link directory maintained by the Business & Economics Section of the American Statistical Association. You can search for links on economics data, add new links and even–get this–view user ratings of data links. It’s a great resource.
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Pi Trading – Free Market Data

I found a collection of free daily historical data covering sundry topics at Pi Trading.

They also have some technical analysis tools, covering “volatility bands” (Bollinger bands) and “pivot points,” which are apparently used for day trading. I think most traders are familiar with Bollinger bands, but I’m going to have to look into pivot points to get an idea of how they are calculated.

Pi Trading also offers programming services and sells one-minute data for various stocks and commodities. They also offer trading systems. I don’t know anything about the quality of their products, but the prices look fairly reasonable.

Pi Trading – Free Market Data.

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Infochimps Data Marketplace

Infochimps bills itself as the “Amazon of data.”  They permit buying, selling and sharing all varieties of data. I’ve been thinking about putting together a data directory (more like the Yahoo! of data), and frankly, I’m not terribly impressed with Infochimps’ selection or their organization, but they do have some interesting data sets available.  It’s worth taking a look.

Infochimps Data Marketplace + Commons: Download Sell or Share Databases, statistics, datasets for free | Infochimps.

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Clive Thompson on How Information Can Fuel Jobs | Wired

Interesting article here from Clive Thompson at Wired on how open data can create jobs.  I’m not strongly convinced that open data creates significantly more jobs, but I like open data.

ceteris paribus – latin, “All else being equal.”
ceteris parabis – latin, “You will prepare for the others.”

Clive Thompson on How Information Can Fuel Jobs | Wired.

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Chart of the Day 2011/01/13: Ceridian-UCLA PCI

Dr. Mark Perry recently highlighted the Ceridian-UCLA Pulse of Commerce Index in an article on his excellent blog, Carpe Diem.

Though not as comprehensive as similar leading indicators available from the DOE and DOT, the Ceridian-UCLA PCI is released earlier. A convenient spreadsheet download is available.

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Chart of the Day 2010/05/27: Venture Capital Fundraising

The National Venture Capital Association has reported that Q1 2010 was the slowest opening quarter in venture capital fundraising since 1993.

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Transportation Data

Transportation series provide some of the better indicators of economic activity. Their releases are not listed in most popular economic calendars for investors.

The London-based Baltic Exchange‘s Baltic Dry Index has received considerable attention in the past year. It is an index that tracks costs of bulk ocean shipping prices world-wide. It is widely considered a leading indicator and is updated daily.

The Bureau of Transportation Statistics provides numerous time series detailing aggregate transportation usage in the United States. Some of the more prominent are listed in their Key Transportation Indicators report. The BTS also compiles a variety of other transportation statistics.

The Association of American Railroads provides weekly summaries of railroad transportation data.  The data tables are in PDF format.

more to come

It is clear that many transportation indicators have strong seasonal fluctuations, and the releases for many are not seasonally adjusted. One notable exception: the Transportation Services Index (TSI). Unfortunately, the TSI is subject to revisions as much as four months prior. It is still under active development. The BTS provides a nice overview of the TSI (which includes a tutorial on some common index weighting schemes and also some details on the TSI’s seasonal adjustment).

 

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The PPI Provides Poor Measures of Aggregate Inflation

The Bureau of Labor Statistics maintains two major inflation indices, the Consumer Price Index (CPI) and the Producer Price Index (PPI). Since it is more widely used, the CPI is often criticized. I can recall several anecdotes stating that during the administration of

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hamburger replaced steaks in the CPI, reflecting a lower standard of living for Americans. (Note: unlike many polls, the poll above is entirely unscientific and placed here solely for your own amusement; it serves no other useful purpose.) Without descending too far into sarcasm, I will say that although I haven’t seen the exact details of that particular change to the CPI, it does seem reasonable that changes in the price of hamburger would more accurately reflect changes in the cost of living than would changes in the cost of steak. Note that at the time the decision was made (whenever it may have been), the re-weighting would have had 0 impact on the index reading; future changes in the price of hamburger would be reflected in changes to the index. I don’t necessarily agree with all BLS decisions, and they do update the CPI to reflect changes in lifestyle, but as a tool to measure aggregate inflation, the CPI is actually pretty solid.

On the other hand, the BLS really does make some bizarre decisions in maintaining the PPI. For example, they decided that in late 2009, consumer-grade potatoes nearly halved in their production importance:

Relative importance of component series in the Producer Price Index
by stage of processing, December 2009 1/                                        02/16/10
________________________________________________________________________________________
      |         |                                                 | Relative importance |
      |  Com-   |                                                 |_____________________|
 SOP  | modity  |             Index                               | December | December |
 code |  code   |                                                 |  (2008)  |  (2009)  |
______|_________|_________________________________________________|__________|__________|
3111             Finished consumer foods, crude                        1.751     1.993
        011101   Citrus fruits                                         0.080     0.088
        011102   Other fruits and berries                              0.398     0.486
        011103   Melons                                                0.047     0.037
        011301   Dry vegetables                                        0.035     0.033
        011302   Fresh vegetables, except potatoes                     0.579     0.771
        011303   Sweet potatoes                                        0.005     0.005
        011304   Irish potatoes for consumer use                       0.096     0.053 
        011901   Tree nuts                                             0.095     0.084
        012101   Wheat                                                 0.010     0.009 

It’s hard to say exactly what the logic was behind this particular BLS PPI re-weighting decision. Maybe they thought that Americans were switching to a low-carb lifestyle… Perhaps they felt that changes in the price of consumer-grade potatoes had less impact on manufacturing costs than previously anticipated. That seems reasonable. But then again… why would potatoes have been weighted so much higher just a year previously? Furthermore, should tree nuts really be weighted so high relative to the other commodities? I don’t think there are satisfactory answers to these questions, but if you happen to come up with one, feel free to leave a comment.

For aggregate measures of inflation, the CPI is far superior to the PPI. I don’t generally suggest using the PPI aggregates for any purpose, although when the BLS updates the individual commodity series in a timely manner, it’s not hard to create custom price indices.

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