A Tale of Two Stimuli (One For Each America)
“It was the best of times. It was the worst of times.” – Charles Dickens from A Tale of Two Cities.
The current economic stimulus plan, as measured by budget execution, as of 2010 March, has been distributed in a non-equalitarian manner that does not favor the least wealthy cities of our nation. The patterns of Government expenditure by US urban area also strongly suggest inequalities in distributed dollars per unemployed worker among US cities. These patterns suggest that the current United States Government economic stimulus operation has either been executed without sufficient governing skill, or without regard to the needs of economically disadvantaged Americans. Analysis in support of these conclusions follows below.
Those of us left who still care if the game is fair, or believe our government serves the people, not vice-versa, owe Veronique de Rugy serious gratitude. Her work with The Mercatus Center of George Mason University resulted in the release of a paper entitled Stimulus Facts – Period 2. The data associated with this paper, which Veronique makes publically available, dispels any misguided illusion that the stimulus has been targeted towards helping the jobless or the poor.
The data tracks stimulus grants made to 363 US Statistical Metropolitan Areas (SMAs). The areas are described by Population, Stimulus Dollars Received, Unemployment Rates and Per-Capita Income. Using this information, I decided to examine whether the stimulus was being distributed in a fair manner based on several categories. These categories include Dollars Received Per Capita, Dollars Received Per Workforce Member (Est.) and Dollars Received Per U3 Worker (Est.)
Dollars Received per Capita involved dividing the SMA Stimulus Dollars Received by the SMA Population. The other two variables required additional research beyond the scope of Ms. De Rugy’s collection of data. The CIA Factbook estimated that 9.4% of the US workforce was unemployed (U3 definition) at its estimate point in 2009. At the same point in time, it estimated the employed population of American workers at 154.5 Mil and the entire American Population at 307.2 Mil.
I extrapolated from the employed US population to estimate that a 0% unemployment rate would result in a 170.5 Million member US workforce, assuming a constant 2009-level population in 2010. This extrapolated figure served as an estimate of the total US population that desired to work. 55.5% of the US population fit into that category.
I estimated work force membership in each SMA by multiplying SMA population by the 55.5% factor. Dividing SMA Stimulus Dollars Received by The Estimated SMA Workforce gave the Estimated Dollars per Workforce Member each SMA received from the stimulus.
The U3 Worker Population in each SMA equalled the estimated workforce multiplied by the SMA U3 rate. Dividing the stimulus Dollars Received in each SMA by the US Worker Population resulted in the Stimulus Dollars Received per U3 Worker for each SMA.
Employing simple arithmetic, I calculated the mean totals for Dollars Received by SMA, Dollars Received Per Capita by SMA, Dollars Received Per Worker by SMA and Dollars Received Per U3 Worker by SMA. These values follow in the table below.
|Category||Average Stimulus Received|
|Per Capita By SMA||$721.10|
|Per Worker By SMA||$1,299.28|
|Per U3 Worker By SMA||$17,447.91|
The means made possible an informed count of how many SMAs fell above and below each mean value. Those who did better than average were classified as “Haves”, those which received less, were classified as “Have-Nots.” The table below shows the Have’s Vs. The Have-Nots, by Population in Millions of people.
|Category||Haves (Pop In Mil)||Have-Nots (Pop in Mil)||Ratio of Have-Nots to Haves|
|Dollars By SMA||147||107||0.73|
|Per Capita By SMA||51||203||3.97|
|Per Worker By SMA||28||113||3.97|
|Per U3 Worker By SMA||2||12||5.86|
Having established that vastly more people lives in over-stimulated SMAs (see row 1 in table above), there may be basis to conclude the government has done at least a few things well in figuring out how to share the monies. However, this conclusion is facile and does not accurately effect how well the money reaches actual people. While almost 58% of the US urban population lives in cities that get more stimulus dollars than average, few of these people actually get more dollars than average in stimulus receipts.
This conclusion is borne out by examining table rows 2,3, and 4. Here we see that only a pittance over 20% of the urban American population or workforce live in cities that get more per Capita stimulus dollars. For the U3 worker, only 9% live in SMAs that received more stimulus per U# worker than average.
This data alone does not demonstrate the extent to which stimulus dollars are unequally dispersed. The table below (last one, I promise) makes that argument.
|Category||Haves ($ per Capita)||Have-Nots ($ per Capita)||Ratio of Haves to Have-Nots ($ per Capita)|
|Dollars By SMA||$975.59||$137.25||7.11|
|Per Capita By SMA||$2,385.63||$177.53||13.44|
|Per Worker By SMA||$4,298.44||$319.88||13.44|
|Per U3 Worker By SMA||$59,951.02||$3,471.32||17.27|
The $ per person categories were calculated by determining how many people lived in SMAs that got more receipts than average or less than average by category. The dollars given to each category were added up by dollars received per SMA. The dollars received by “Have SMAs” in each category were divided by the summed populations living in these have SMAs to get the $ Per Have values. The $ Per Have-Not totals were similarly tabulated. The ratio shown in column four was a simple arithmetic comparison of $ Per Have over $ Per Have-Not.
In conclusion, the stimulus favors a lucky few over a suffering multitude. The receipts have not been equitable, or in any proportion to economic hardships endured. Accusations that the stimulus is basically a political pork barrel could well gain further credence unless the Executive Branch of The United States Government significantly alters the current pattern of outlays to better favor the unemployed.