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MetroDynamics: Ranking Analysis

Metro Ranking Analysis. Analyze metros by using the powerful MD RankingAnalyst. This section shows a few examples of using the RankingAnalysis feature.

Metro Ranking Analysis is a two-step process. A master ranking table is developed. Then the RankingAnalyst is used to with the master ranking table. The master ranking table can be developed with different types and levels of subject matter data. See http://proximityone.com/md3table.htm for more information about data extracts and table building, processing and content.

Once the master ranking table is developed, metros can be rank analyzed in ascending/descending order by right-clicking the field (subject matter item) title/name. Click on any graphic in this section (then press F11 key) for a larger view.

Population 2006. In this example, the descending sort button is checked and the Population 2006 title is right-clicked. The resulting descending sort shows that, for example, the San Antonio, TX MSA ranks 29th among MSAs and has total 2006 population of 1,942,217. These population data are based on official county estimates.

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Population 2006 - Metros in Selected State. Starting with the above view, suppose that you want to see the rankings but only for metros in a selected state (or some set of states). Use the Filter button to set the query condition "at('VA',name)" -- this says to include only those metros that have VA in the metro name in the grid view. Here is the list of 11 Virginia MSAs.

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Per Capita Personal Income (PCPI). PCPI is regarded as one of the best measures of the overall economy. The next view shows metros sorted in descending order on 2004 PCPI. This view tells us many things.

  • San Antonio ranks 179th based on PCPI 2004 ($26,751) -- just above the median.
  • Immediately view peers to the selected MSA.
    (the closet MSA of similar population size was Orlando with 2004 PCPI of $27,017)
  • Going to the top (not shown) the highest 2004 PCPI was $62,979 -- where is it?

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Average Weekly Wages: Quarterly Data; Annual Change. You can build the ranking table and select the subject matter data that you want. In the next view, quarterly average weekly wages (AWW06Q3) -- for total covered employment -- and quarterly housing prices indexes (HPI1) are shown for two quarters (HPI1=2005Q4 and HPI2=2006Q4), their change and percent change. This view tells us many things.

  • San Antonio ranks 147th in AWW as of 3th quarter 2006.
  • Immediately view peers to the selected MSA.

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Housing Price Index: Quarterly Data; Annual Change. How does San Antonio compare based on a cost of living measure, say the Housing Price Index for the 4rd quarter 2006? To get this information, simply right-click the HPI2 title and the following view appears. This view tells us many things.

  • San Antonio ranks 253rd based on the HPI as of 4th quarter 2006.
  • Immediately view peers to the selected MSA.

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Characteristics Based on Specific Industry. The first ranking table shows the AWW ranking based on total employment. What about a specific industry of interest? The next view shows the descending sorted quarterly average weekly wages (AWW) -- for the retail trade industry employment. This view tells us many things.

  • San Antonio ranks 87th in AWW as of 3rd quarter 2006.
  • Immediately view peers to the selected MSA.
  • Going to the top (not shown) the highest AWW is $661 -- where is it?
  • The cost of labor in the San Antonio MSA in the retail trade industry is relatively high.
  • These data could be used to compute a labor force participation rate for MSAs in this industry.

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Many of these data items change quarterly. Using MD makes it easy to get updated views of trends and how trending relationships among metros are changing.

More in general, view these any of these data, integrated with other data, sorted on any of the items in the master file. Sort on any data field by clicking on the column header name in the dbasegrid shown in the lower section of the form.

See links in the left column for information about other MD features.


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