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US manufacturing employment is down, but each state has its own story
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The trouble with food and energy
Posted on February 29, 2016
There are many ways to measure inflation. One popular method used for monetary policy purposes is to look at the price index for personal consumption expenditures excluding food and energy. Why exclude food and energy? Aren’t those important items that matter a great deal to households? The reason is straightforward: These price categories are considered to be excessively volatile, and including them would make it more difficult for policymakers to pin down the inflation trend. The graph above makes this point visually by comparing the PCE inflation rates with and without food and energy.
Usually when you add items to an index, you reduce the volatility of that index. This same premise is at work when you add assets to an investment portfolio—i.e., when you diversify to reduce volatility. But this does not happen when the item you add is excessively volatile. And, again, food and energy are excessively volatile. Food is subject to large price variations due to external shocks, mostly on the supply side, such as weather. Energy is subject to shocks as well: supply shocks such as discoveries, wars, political risk, and infrastructure issues and demand shocks such as climate events. This happens with food and energy much more than it does for other items included in personal consumption expenditures.
How this graph was created: Search for “PCE.” Then go to the “Filter Series by Tags” box to the left and enter “price index.” Select the first two monthly series that appear and add them to the graph. Change the units for both series to “Percent Change From Year Ago.”
Suggested by Christian Zimmermann
View on FRED, series used in this post:
PCEPI, PCEPILFE
Tagged PCEPI, PCEPILFE
--
New York City vs. suburban incomes
Posted on February 25, 2016
FRED offers plenty of U.S. county-level data, including per capita personal income. One can look closely at individual counties in FRED and create regional maps in GeoFRED. This map focuses on New York City and the surrounding counties. One peculiarity worth noting is that each city borough is also its own state county: New York (Manhattan borough), Bronx, Kings (Brooklyn borough), Queens, and Richmond (Staten Island borough). There are stark contrasts in income across all these counties, with Manhattan clearly on top. The surrounding counties, however, have incomes higher than any borough other than Manhattan. Thus, even the Big Apple obeys the rule that incomes are generally higher for suburban residents.
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
The state of median household income
Posted on February 22, 2016
Fortunes can vary widely from one neighborhood to the next and also from one state to the next. The map above, which looks at U.S. states, shows median household income. This measure of income is basically a line through the middle: Half the households within that state receive more income and half receive less income. The map shows some regional correlations, but it is quite interesting to see how median income in one state can be almost twice as high (or low) as it is in a neighboring state. Use the “View on GeoFRED” link above to visit the site. There you can interact with each state on the map and gather more details about it. You can also change the applicable date to see how the distribution of the median income has changed over the years.
How this map 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
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