Recession and Recovery in St. Charles, MO: Exploring FRED’s County-Level Data Series
I learned recently that the Federal Reserve Bank of St. Louis publishes county-level data in it’s Federal Reserve Economic Data (FRED) portal (in its 300th blog post FRED highlighted its county-level data in a look at Spartanburg County, S.C. Get it — 300? Sparta?). My first thought was to explore the available data by looking up my hometown, St. Charles, MO, and look at the information with an eye toward how things have gone since the recession.
For the rest of this post, I’ll pull in graphs from FRED illustrating trends in various economic indicators for St. Charles along with some of my thoughts and observations. I’ve grouped related data series together and treated them under a themed subheading.
Unemployment, Income, Inequality, and Poverty
My overall takeaway when looking at the main economic health indicators is that St. Charles has yet to really get back to normal since the 2008 recession. While unemployment is down, most indicators signalling other forms of economic health (poverty, inequality, etc.) have yet to return to the status quo pre-recession, and it some cases these indicators were already trending in a negative direction well before the recession began.
Starting with the unemployment rate (blue is St Charles, red is the nation as a whole), the first thing that stands out is how dramatically it has recovered since the 2008 recession. The second is that St. Charles performs consistently better than the nation as a whole.
Looking back to the mid-1990s, you see that St. Charles and the nation as a whole have yet to come close to the extreme lows in unemployment experience just before the 2001 recession. In fact, neither St. Charles nor the United States as a whole had recovered from the 2001 recession before the 2008 housing and financial crisis, making the impact of that economic shock even worse. In fact, the unemployment rate in St. Charles is closer now to its pre-2001 level than at any other time.
While unemployment is dramatically improved, other indicators of economic health are not faring as well.
Turning to median household income, St. Charles performs well compared to the rest of the country, making over $20,000 or 38% more than the rest of the nation annually.
That story changes a bit when looking at change in median income relative to a fixed point in time. The national median household income has grown more since 2000 than St. Charles’s has:
That story gets worse when looking at change income relative to the high point immediately preceding the recession. Median household income in St. Charles fell farther relative to its pre-recession level than the national median did following the 2008 recession, and has recovered slower, returning to its pre-recession high (red line) over two years later (2013) than the nation as a whole did (2011).
So while St. Charles outperforms the nation as a whole, the recession hit it harder and it recovered more slowly in comparison to the prevailing norm beforehand. That’s not so bad. But the tepidness of the recovery becomes clearer when looking at indicators for poverty and inequality.
FRED uses the 20:20 ration or “quintile ratio” to measure inequality. This is simply the media income of the top 20% of earners (the top quintile) divided by the median income of the bottom 20% of earners (the bottom quintile). In the graph below for St. Charles, the ratio today is 9.3. That means the median earner in the top 20% makes 9.3 times as much as the median earner in the bottom 20%.
The inequality ratio in St. Charles has risen a full point since 2010, which is the earliest data FRED provides for this series. The median earner in the top 20% made 8.3 times as much as the median earner in the bottom 20% in 2010; today they make 9.3 times as much.
How does St. Charles stack up against the nation as a whole? FRED doesn’t have a nation-wide data series, but the United Nations Development Programme reports that the ratio of the average (note median, as FRED uses) income for the 20% to that of the bottom 20% is 9.1. The UNDP doesn’t indicate when that estimate was made; only that it’s no older than 2010. That’s not terribly helpful.
Instead, to get a more apples-to-apples comparison, I looked at St. Charles in comparison to some counties that “feel” comparable, plus a randomly-selected borough of New York City. These include Des Moines County, IA; Douglas County, NE (home to Omaha); DuPage County, IL (home to Naperville); and Queens County, NY.
The left-hand graph simply compares the raw 20:20 ratio for each of these counties. St. Charles comes out pretty well, with the gap between the top 20% and bottom 20% closer than of any of the other comps.
However, the right-hand graph shows that the inequality ration in St. Charles grew the second fastest of this set after the recession. This graph normalizes each county’s ratio to 100 — it shows how the ratio changes over time compared to its own value in 2010. Here you see that while income inequality is lower in St. Charles, it grew faster during this period than it did in any other county except Queens, NY. Inequality in all counties is higher today than in 2010, which is in line with expectations: the problem of growing national income inequality was a theme of last year’s presidential election and was one of the main explanations highlighted by economists and journalists in for the popularity of candidates like Bernie Sanders and Donald Trump, whose rhetoric pointed to an economic malaise not apparent in popular top-line numbers like the unemployment rate, GDP growth, and stock market performance.
Comparing median income and inequality for St. Charles together, we see that both have risen since 2010 (the first year that inequality data is available). Incomes have recovered since the recession, but inequality has increased as well:
Turning to the poverty rate, the story gets more disheartening:
On the left, you can see that the poverty rate in St. Charles County increased after the 2001 recession, and never fully recovered before the 2008 recession hit. Then it jumped almost two percentage points. While unemployment has come down since the 2008 recession, the poverty rate has not, and in fact appears to still be on an upward trajectory.
On the right I pulled in the national poverty rate to get a sense for where St. Charles stands. As in the income and unemployment measures, St. Charles is still doing better than the nation as a whole despite the poverty rate not showing any signs of coming back to pre-recession levels. One thing to note, however, is that this data series ends in 2014. It’s possible that the poverty rate turned a corner in the following two years; we’ll see when the data becomes available.
A quick note on how poverty is measured here: the census bureau measures poverty by family unit; either everyone in the family is in poverty or no one is. To determine this, the census bureau sets a dynamic threshold of household income that varies by size of the family and number of related children under 18 years old in the family. For example, in 2014 (the last year shows in the above graphs) the poverty threshold for a family of four with two children was $24,008. If the total household income for a family is below the threshold, everyone in that family is considered to be living in poverty. More on how the census bureau measures poverty can be found here; poverty threshold tables can be found here.
What’s interesting is that by 2014, the national poverty rate did start trending back downward even though it did not in St. Charles (right, below). This becomes more apparent by indexing the St. Charles and national rates to 2008 (left, below):
Though the poverty rate is lower in St. Charles than it is nationally throughout this period, when you compare each rate to its level at the start of the recession, the national poverty rate plateaued at about a 20% increase and has even started to inch back downward. The St. Charles rate, on the other hand, is still about 36% higher and is still trending upward.
This stands in contrast to the recovery pattern after the 2001 recession (graph on right with poverty rates indexed to 2000). After 2001, both the St. Charles poverty rate and the national poverty rate settled at about the same level above their 2000 levels (~15%). Yet after the financial crisis later in the decade, the St. Charles and national rates are still moving in opposite directions.
In addition to poverty rate, the number of SNAP benefits recipients (Supplemental Nutrition Assistance Program, or food stamps) can also indicate improving or declining economic health:
In both absolute terms and as a percentage of the population, SNAP benefit recipients have been on a steady rise. As a percentage of the population, the SNAP recipient rate accelerated after the 2001 recession, plateaued, and just started to dip down again right before the 2008 recession hit. The percentage jumped again after the 2008 rate recession, peaked in 2011, and had only just started to decline by 2013. It will be interesting to see if this downward trend continues in data from 2014-onward.
Taking a long term indexed view of various poverty indicators in St. Charles County since 2000 (below)— the percentage of people in different age groups living in poverty and the percentage of people receiving SNAP benefits — the emerging theme is that the 2008 recession compounded the lingering negative effects of the 2001 recession, from which St. Charles had not yet fully recovered (all of these poverty indicators were still above their pre-2001 levels). While it’s common to trace negative aspects of today’s economy back to 2008, the story really starts sooner:
If the effects of the 2001 recession lingered, what about those of the recent financial crisis? Since unemployment peaked in 2009, the poverty rate has continued to clime. While unemployment fell precipitously, poverty rates were still over 30% higher in 2014 than they were during peak unemployment in 2009.
This helps explain how inequality has been rising since the recession while median incomes have also been rising.
Rising poverty rates signal that the bottom income quintiles are worse off. Meanwhile, everyone else is doing so much better that median incomes are rising overall despite the poverty rate also rising. Top income earners are better off now than they were nine years ago, and those at the bottom are worse off, hence growing inequality.
One gets the impression that the story of the economic recovery as it is often measured — by simply looking at the improved unemployment rate — looks rather weak upon closer examination. If unemployment has improved so much since the recession but the poverty rate and inequality are increasing, it must mean that for those in lower income rungs, new jobs gained since the recession simply aren’t as well paying as the ones that were lost.
The Housing Market
The housing market collapse triggered the most recent recession. How has the housing market in St. Charles fared since then?
Home prices: The below graph shows the housing price index for St. Charles County (blue), and the United States overall (red), with both indexed to 1990. A full explanation of how the housing price index is measured can be found here, but in short it’s measured by looking at price changes for the same property over time as indicated by repeat sales and refinancings.
What stands out most is how far prices fell after the 2008 recession. The St. Charles index peaked at 198.8 in 2007 (or 98.8% above 1990 prices), then fell for five straight years and bottomed out at 165 in 2012. Housing prices then recovered at about the same rate they fell; four years after they bottomed out, the national price index is already higher than its pre-crisis peak and St. Charles’s index is just below it.
The next thing that stands out is how quickly prices started to ramp up in the as the housing market overheated — the rate of change in the national index became incredibly steep in early- to mid-2000s. Expanding the time period, (the housing price index series goes back to 1975) one gets a sense for how abnormal the rate of change in prices in the early 2000s was compared to earlier periods:
At the peak in 2007, national housing prices were six times higher (600+ on the index) than they were in 1975 (100). One would expect prices to rise over time given the reality of inflation, and from 1975 to about 1995, home prices appear to increase at a steady linear rate. However, in the mid 1990s, they appear to depart from this trend and start accelerating exponentially — leading to the overheated market, the housing crisis, and eventually a downward price correction.
Looking at inflation over this same period (below left, using the Urban Consumer Price Index), we see that inflation maintained a linear trend from 1975 to 2016, so the temporary “exponential” acceleration in home prices right before the crash really does appear to be an aberration. This becomes even more apparent when you overlay the CPI on the home price index (below right). We see that the St. Charles home price increase generally followed inflation until about 2000, at which point price increases started accelerating. They reached an unsustainable level, corrected downward, and finally rose back to about where they would have been anyway had they continued to follow the linear inflation trend.
I ran a linear approximation of national and St. Charles home prices from 1975 to 1995, since both appeared to follow a linear trend in the observational data, to see how closely the trend fit the actual indexes. I then carried the projection forward from 1996 through 2016 as a forecast, to see where housing prices during and after the bubble and recovery stood in relation to the 1975–1995 trend:
The linear approximations (thin lighter color lines) were a surprisingly great fit. Both the national and St. Charles indexes follow a linear rate of increase almost perfectly during the 1975–1995 period. For St. Charles, a house that cost $100 in 1975 consistently added about $7.24 in value each year through 1995. Nationally, a house that cost $100 in 1975 consistently added about $10.32 in value annually through 1995.
Looking past 1995, the indexes continue to follow their linear trends until about 1998, when both begin to accelerate rapidly, leaving their long term trend lines behind, and peak in 2007 at the top of the bubble. The degree of departure from the 1975–1995 trend is really quite dramatic, especially for the national index.
What’s interesting is that when the market corrected the overheated prices from their top-of-the-bubble peaks, they essentially bottomed out to the point they would have been at had they followed their 1975–1995 trends.
So have home prices “recovered” post-recession? There’s nothing special about the 1975–1995 trend line or anything that says it’s the “right” or appropriate rate of increase , but overall, if you treat that period as a baseline for how an individual homeowner would expect their home value to appreciate over time, it looks like post-recession home prices in St. Charles have more or less recovered. Interestingly, national prices appear to have not only recovered but are accelerating again.
Home Construction: Unsurprisingly, the number of new houses built (as measured by the number of building permits issues) hit a low during the recession. What’s surprising is that the number actually peaked in 2004 — four years before the recession actually hit. Even so, the fall over that four year period was dramatic. By 2011 the number of new houses built in St. Charles was half the number built in the year 1990.
The pace of building new housing hasn’t come anywhere close to pre-recession levels. This seems to make sense. One could hypothesize that the run up of new houses built between 1990 and 2005 saturated the market with an unsustainable level of supply, especially as prices remained high. The market seems to have corrected itself and found a new level of new housing to build each year that is more appropriate for market demand. Prices have started to tick back up, yet new housing starts remain closer to 1990 levels than at any point since then, and are about 56% lower than their 2004 peak. Perhaps this is the new baseline for normal.
Lower demand for new housing is probably caused by a range of factors — tighter loan requirements make it more difficult to get a mortgage (easy mortgages helped fuel the the bubble’s continuous demand for ever-more-expensive new houses, and the inability to keep up with mortgage payments for expensive houses burst it and the economy), and prices dipped only temporarily while poverty and inequality has increased, making it harder to afford buying instead of renting. But these factors apply nationally as well as locally in St. Charles.
One other factor to consider: net migration to St. Charles has declined significantly since 2009 (unfortunately data is only available for 2009–2013). As net migration approached zero it may have negatively affected the demand for new housing — as the number of those leaving St. Charles draws even with the number of people moving to St. Charles, the need to build new housing to accommodate the newcomers dwindles (they can simply move into the homes vacated by those leaving). The new housing stock then only needs to grow in tandem with the “natural” rate of population growth.
Other Social Indicators
FRED tracks a number of other indicators in addition to those on employment, income, and the housing market.
Small Business Ownership: FRED keeps stats on the small business ownership rate (or kept — the page I found this information on no longer exists but a cached version can still be found using Google).
FRED data is only available from 2010–2014, but a clear downward trend is apparent. The scale of the vertical axis exaggerates the downward trend (it’s only fluctuated withing a 0.6 point range), but the trend is negative nevertheless.
Since FRED defines the Small Business Ownership Rate as “the number of firms which employ fewer than 500 people, divided by the number of people in the labor force,” the rate can decline for two reasons: a decrease in the number of small businesses, or an increase in the labor force (as well some combination of the two).
FRED has data on the St. Charles Labor force (left), and when you look at this number over the same period against the small business ownership rate (right), it appears that the size of the labor force is the main factor driving changes in the small business ownership rate.
The St. Charles labor force increased each period that small business ownership rate fell, and decreased in the single year that the ownership rate increased. One could feel comfortable concluding then that even as the labor force grew, the number of small businesses in St. Charles either grew, but at a lesser rate, or shrank.
Overall, the small business ownership rate is a metric I’m not terribly familiar with, and it seems odd that FRED’s page for it appears to have disappeared, so it might not be worth reading too much into it (the reported drop is small in any case).
Size of the Civilian Labor Force: For what it’s worth, here is the monthly data on the size of the St. Charles labor force over a much longer timeline (January 1990 — May 2017). Interestingly, the labor force appears to have started a sustained shrinking trend over the last six months.
Since there’s a lot of seasonality in the data, I looked at the same monthly numbers but in terms of “percentage change on one year ago” (below) to determine whether the recent shrinking trend is significant. As it turns out, the recent six-month streak of a shrinking labor force (compared to the same month a year ago) has only been exceeded one other time in the past 17 years (in 2012).
Preventable Hospitable Visits: FRED stats on the rate of preventable hospital admissions (data available for 2008–2014) show a marked decrease in 2012. I’d be stepping way outside my expertise to comment on why, but here are some links to others who presumably do have more knowledge in this area:
Healthcare Cost and Utilization Project, “Trends in Potentially Preventable Inpatient Hospital Admissions and Emergency Department Visits,” 2015 (link)
HealthIT Analytics, “Preventable Hospital Readmissions Fall Dramatically Across US,” 2016 (link)
Violent and Property Crime Incidents: FRED reports violent and property crimes at the county level (which are in turn pulled from the FBI’s Uniform Crime Reporting database).
I’d again be stepping outside of area of knowledge to comment on why crime rates have fallen. I’d presume it’s some combination of economic, sociological, and cultural factors, as well as law enforcement approaches.
Journalist Matt Ford addressed this very question in his 2016 Atlantic article “What Caused the Great Crime Decline in the U.S.?” That seems like as good a a place to start as any for those interested in more.
The decline in St. Charles is emblematic of a national trend that’s been ongoing since the 1990s. Pew Research sums it up nicely in some longer-term national statistics they’ve compiled, also from the FBI:
That Pew article contains another interesting observation. From 1992 to 2001, the public perception of whether the crime rate was increasing or decreasing broadly stayed in line with the actual crime rate. Those trends diverged in 2001. Perhaps 9/11 created an atmosphere of fear, separated from reality, from which the U.S. has yet to recover.
Single Parent Households: As with the decline in small business ownership, the small span of the vertical axis here exaggerates what might otherwise be viewed as a small uptick in the number of single parent households in St. Charles. This is as far as FRED’s data goes, so it’s hard to see where this recent slight increase sits in relation to longer-term trends, or even just to the pre-financial crisis period.
The St. Charles rate is broadly in line with national rate (measured by Pew).
Pew argues that:
These changes have been driven in part by the fact that Americans today are exiting marriage at higher rates than in the past. Now, about two-thirds (67%) of people younger than 50 who had ever married are still in their first marriage. In comparison, that share was 83% in 1960. And while among men about 76% of first marriages that began in the late 1980s were still intact 10 years later, fully 88% of marriages that began in the late 1950s lasted as long, according to analyses of Census Bureau data.
The national trend appears to have flattened in the years following the financial crisis (2010–2014 in the Pew chart). Perhaps the recession made divorce more financially risky. However, I’m once again stepping beyond my field of knowledge so I’ll leave any further speculation on the why behind this trend aside.
The Federal Reserve (and the federal government more broadly) produces a wealth of publicly available information, ready for anyone to access. Take a look and enjoy one of the many valuable resources your tax dollars support!