TIP Strategies is a privately held Austin-based economic development consulting firm committed to providing quality solutions for public and private‑sector clients.
This blog is dedicated to exploring new data and trends in economic development.
By: Chris Tomlinson
Via: The Houston Chronicle
Graphic shows how jobs surge and contract across the country
Job data is important to understanding the nation’s economy, but the spreadsheets can be painful to analyze. The economic development consulting firm TIP Strategies, though, has developed a very cool visualization tool to understand how employment surges and contracts over time and geography.
The Greater Houston Partnership recently crowed about adding 600,000 in the first nine months of this year, and that is truly remarkable. But how does this recent boom compare to the last 15 years? When Houston is adding jobs, what is the rest of the country doing?
Hitting the play button, it’s fascinating to watch the pulsing blue circles of added jobs from 1999 to 2002. Dallas and New York added jobs at a much higher rate than Houston. Then a recession hits in 2002 and the whole country begins losing jobs as the dot-com bubble burst. Other parts of the country suffered much more than Houston.
Then in early 2004, Houston lags behind the rest of the nation as the economy takes off elsewhere. This is where you can see how a growing economy demands more energy, and in response, Houston begins adding jobs to meet those needs.
Perhaps most stunning, Hurricane Katrina hits in 2005 and like a bomb, the orange circles of lost jobs explode over New Orleans as thousands of jobs are lost. The number of new jobs in Houston surges as workers flee Louisiana.
Then in 2007, Houston’s job growth begins to lead the rest of the country. The recession hits, and while most U.S. cites, particularly Los Angeles, lays off tens of thoussands of workers each month, Houston continues to add until 2009 when it begins registering losses. The fracking boom takes hold in 2010, and we know the story from there.
The lesson from the data is that Houston has done remarkably well compared to the rest of the country. The reasons are many and debateable. There’s also an intense debate over the quality of those jobs, and the state’s 15.9 percent poverty rate which just dropped to become the same as the national average.
Fundamentally, though, the map is simply very cool, and a reminder of how good Houston has it.
By: Jeff Marcell, Senior Partner and John Karras, Consultant, TIP Strategies
We hope you will take a moment to check out our “new and improved” Geography of Jobs. In our updated version, we’ve included 372 metros* and extended the timeline back to 1999. As in the previous version, each bubble shows the net change in employment in a given metro area compared to the same period one year earlier. The diameter of each bubble reflects the size of the loss or gain. But, unlike the original Geography of Jobs, you can now place your cursor over any of the metros and watch the actual job numbers change over time . If you press the pause button, you can also move your cursor over any metro and compare actual job losses or gains at any point in the timeline. Another “behind the scenes” feature is our ability to map new datasets, such as job change by sector.
At TIP Strategies, we are always looking for ways to translate data into insights about economic development. We hope you will help us with this task by providing feedback and sharing your insights at the end of this blog post.
- The Great Recession officially lasted from December 2007 to June 2009, but the job losses spanned a longer timeframe, beginning early in 2007 and extending well into 2010. Some regions were hit harder than others, some were hit earlier, and some took longer to recover, but no corner of the US was spared.
- The Dot-Com Bubble was marked by rapid job growth in some of the country’s leading high-tech regions (Silicon Valley, Boston, Seattle, Austin) in 1999 and 2000. You can then see these same regions losing lots of jobs from 2001 to 2003 during the Dot-Com bust and subsequent recession. Silicon Valley actually continued losing jobs into 2004, even while the rest of the country had come out of the recession and was gaining jobs.
- The Housing Bubble, following the relatively mild recession that began in 2001, led to unprecedented job growth across the country. Buoyed by easy money (i.e., subprime mortgages), housing supported strong job growth in places like Las Vegas, Phoenix, Atlanta, and Southern Florida. You will also see that these same places were the first to begin losing jobs as the housing market collapsed, starting in 2007.
- Hurricane Katrina slammed into New Orleans in late July 2005, a disaster that had an immediate and lingering impact on jobs in the region. However, you will notice that metros in the periphery, most notably Baton Rouge, actually saw a significant uptick in jobs during that time due to temporary (and perhaps permanent for many) outmigration from New Orleans.
- Watching the Midwestern US, especially the manufacturing-centric states of Michigan, Ohio, and Indiana, reveals that many of the metro areas in these states never enjoyed the economic growth experienced by most of the country from 2003 to 2006. Red bubbles cover much of the area surrounding Detroit from 2002 all the way until the end of the Great Recession in 2010. However, the employment situation in the Midwest has taken a turn for the better in recent years thanks to the recovery of the US automotive industry beginning in 2010.
We are excited about the upgrades to the Geography of Jobs and hope you find it useful. And we would love to hear from you. Please take a moment to share your comments on how the tool did (or did not) provide any insights about your community, any regional or national trends of significance, and other datasets we should consider mapping.
Thanks for viewing.
*NOTE: Map includes the 372 MSAs for which data are available from the US Bureau of Labor Statistics.
By: Kyle Vanhemert
Last year, a pair of researchers from Duke University published a report with a bold title: “The End of the Segregated Century.” U.S. cities, the authors concluded, were less segregated in 2012 than they had been at any point since 1910. But less segregated does not necessarily mean integrated–something this incredible map makes clear in vivd color.
The map, created by Dustin Cable at University of Virginia’s Weldon Cooper Center for Public Service, is stunningly comprehensive. Drawing on data from the 2010 U.S. Census, it shows one dot per person, color-coded by race. That’s 308,745,538 dots in all–around 7 GB of visual data. It isn’t the first map to show the country’s ethnic distribution, nor is it the first to show every single citizen, but it is the first to do both, making it the most comprehensive map of race in America ever created.
White people are shown with blue dots; African-Americans with green; Asians with red; and Latinos with orange, with all other race categories from the Census represented by brown. Since the dots are smaller than pixels at most zoom levels, Cable assigned shades of color based on the multiple dots therein. From a distance, for example, certain neighborhoods will look purple, but zooming-in reveals a finer-grained breakdown of red and blue–or, really, black and white.
“There are a lot of moving parts in this process, so this can cause different shades of color to appear at different zoom levels in really dense areas, like you see in NYC,” Cable explains. “I played around with dot size and transparency for a while and settled on the current scheme as being adequate.” You can read more about Cable’s methodology here, but it comes down to this: When you’re dealing with 300 million dots at varying levels of zoom, getting the presentation just right is as much an art as a science.
Looking at the map, every city tells a different story. In California, for example, major cities aren’t just diverse, they’re integrated to a great degree, too. We see large swaths of Sacramento dotted variously with reds, blues, oranges, greens and browns. Los Angeles is more distinctly clustered, but groups still bleed into one another.
In the Midwest, though, the racial divide can be shockingly exact. In Chicago, bands of whites, blacks, and Latinos radiate out from the city center like sun beams. In St. Louis, a buffer of a few blocks separates a vast area of largely black citizens from another of white and Asian ones. In Detroit, the most segregated city in America according to one recent study, there’s no buffer at all. We see how 8 Mile Road serves as the dividing line between two largely homogenous swaths–one predominantly white and one predominantly black.
Looking at the Southeast, a wide, faint band of green represents the Black Belt, a region originally named for the dark soil in Alabama and Mississippi that eventually came to describe the greater region shaped by plantation agriculture. And while the West looks awfully barren, the density of cities like Los Angeles, Dallas, and Houston gives us a sense of why those states are actually so populous.
Responding to the Duke University study last year, experts were quick to expound on the complexities of the issue. Housing desegregation, one pointed out, is not a magic bullet for equal opportunity. Another made clear that blacks remained more segregated from whites than Latinos or Asians. Here, at least, Cable’s given us a chance to see how things stand today in greater detail than ever before.
Check out the full, interactive map for yourself here.
Via: Flowing Data
CLICK IMAGE FOR INTERACTIVE VERSION
The chart [above] shows what people do and what they get paid. These vary depending on where you live. Select a state in the drop-down menu, and use the slider to adjust the median annual salary.
Prominent industries in a state can say a lot about an area. Is there a lot of farming? Is there a big technology market? Couple the jobs with salary, and you also see where the money’s at. You see a state’s priorities.
For example, look at California. You see an increased prominence of farmworkers and laborers, whereas the farming, fishing, and forestry sector is nearly nonexistent in many other parts of the country. I expected a lot more in the midwest states, but relative to the other occupations in those states, the farming sector doesn’t seem that big from an employee perspective.
For a drastic change, switch to Washington, D.C., where people who work in the legal and business sectors are much more common. I realize it’s a comparison between a city and states, but whoa, that’s a lot of lawyers packed in one place.
Move the median salary up a bit, and you get a sense of overall salaries (and a correlating cost of living, kind of) as you check out different states.
Anyway, it’s an interesting first look at employment data from the Bureau of Labor Statistics.
By: Alan Flippen
Via: The New York Times
Annie Lowrey writes in the Times Magazine this week about the troubles of Clay County, Ky., which by several measures is the hardest place in America to live.
The Upshot came to this conclusion by looking at six data points for each county in the United States: education (percentage of residents with at least a bachelor’s degree), median household income, unemployment rate, disability rate, life expectancy and obesity. We then averaged each county’s relative rank in these categories to create an overall ranking.
(We tried to include other factors, including income mobility and measures of environmental quality, but we were not able to find data sets covering all counties in the United States.)
The 10 lowest counties in the country, by this ranking, include a cluster of six in the Appalachian Mountains of eastern Kentucky (Breathitt, Clay, Jackson, Lee, Leslie and Magoffin), along with four others in various parts of the rural South: Humphreys County, Miss.; East Carroll Parish, La.; Jefferson County, Ga.; and Lee County, Ark.
We used disability — the percentage of the population collecting federal disability benefits but not also collecting Social Security retirement benefits — as a proxy for the number of working-age people who don’t have jobs but are not counted as unemployed. Appalachian Kentucky scores especially badly on this count; in four counties in the region, more than 10 percent of the total population is on disability, a phenomenon seen nowhere else except nearby McDowell County, W.Va.
Remove disability from the equation, though, and eastern Kentucky would still fare badly in the overall rankings. The same is true for most of the other six factors.
The exception is education. If you exclude educational attainment, or lack of it, in measuring disadvantage, five counties in Mississippi and one in Louisiana rank lower than anywhere in Kentucky. This suggests that while more people in the lower Mississippi River basin have a college degree than do their counterparts in Appalachian Kentucky, that education hasn’t improved other aspects of their well-being.
As Ms. Lowrey writes, this combination of problems is an overwhelmingly rural phenomenon. Not a single major urban county ranks in the bottom 20 percent or so on this scale, and when you do get to one — Wayne County, Mich., which includes Detroit — there are some significant differences. While Wayne County’s unemployment rate (11.7 percent) is almost as high as Clay County’s, and its life expectancy (75.1 years) and obesity rate (41.3 percent) are also similar, almost three times as many residents (20.8 percent) have at least a bachelor’s degree, and median household income ($41,504) is almost twice as high.
By: Karen Beard (Intro)
In recent years, the widespread availability of high speed internet access coupled with a proliferation of new technologies and the growth of transparency movements like the federal Open Government Initiative, have resulted in dramatic growth in data visualizations. In its broadest sense, the term applies to any pictorial representation of data including charts and infographics. But the true power of data visualization is best seen when the tools are applied to enormous data sets to reveal patterns that would otherwise be impossible to discern.
A new interactive data visualization from Ben Schmidt, an assistant professor of history at Northeastern University and core faculty at the NuLab for Texts, Maps, and Networks, is an example of this power. Schmidt’s flow diagram—presented under the heading “What are you going to do with that degree?”—visualizes employment and education data from the American Community Survey. The figure explores the relationships between college majors and professions.
In many cases, the data reflect the common wisdom that many people work in fields unrelated to their degree. For example, less than half of people employed as police officers have degrees in criminal justice. The visualization also highlights differences in employment outcomes between narrowly focused degrees and those that are more academic. As might be expected, career-specific degrees such as nursing and education, have more consistent outcomes while broader fields of study, like mathematics and communications, feed into a more disparate array of professions.
Additional data visualizations created by Mr. Schmidt can be found here.