Mulbrandon Research, Design & Insights

I had a chance to participate on a panel about Visualizing Data at the American Association for Budget and Program Analysis 2012 Spring Symposium (lots of talks for budget geeks) along with Jonathan Schwabish from Congressional Budget Office and Ellie Fields from Tableau Software. We discuss the analysis, design, and editing process for creating data graphics.

If you made it to the session and would like to see my slides again or missed it but want to learn about the methods and resources I find most helpful take a look:

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Here is a sneak peek at my An Illustrated Guide to Income in the United States. These are a set of data graphics looking at the average income and change in number of jobs over the last ten years for 800+ occupation by industry and by education. Be sure to sign up to be notified when the Income Guide is done.

Data from EMSI

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Due to popular demand, I have updated my 2010 graph on top marginal tax rates. In addition, during this year’s tax season, I will be selling copies of my Top Marginal Tax Rates graph as a tabloid size 11″x17″ poster.  

FYI, your marginal tax rate is the rate you pay on the “last dollar” you earn; but when you view the taxes you paid as a percentage of your income, your effective tax rate is less than your marginal rate, especially after you take into account the deductions and exemptions, i.e. income that is not subject to any tax.

Tax Data: Married filing jointly, Capital Gains & Regular, Historical Corporate, Corporate Tax Schedule (page 16) pdf

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First published in Slate to accompany an article written by Tim Noah, I created these graphs about income inequality covering the changes in income inequality as well as looking at changes in race, gender, education, taxes and political party in the White House.

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I worked with Economic Modeling Specialists on a data graphic that looks to distinguish between growth from large national forces vs. local competitive advantages within a state.

Learn more about the data and analysis at the EMSI Blog.

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This one of the graphics that I presented recently at The Big Picture conference here in New York City. It is from a project I am currently working on called An Illustrated Guide to Income in the United States: a collection of infographics, maps and charts looking at the different incomes and occupations in the United States.

Recently the conversation in the news has been about the top 1%, however, in this graphic I show the breakdown of personal income by different percentiles, including the top 0.01% (i.e. income above $9 million). I have used 10,000 “people” to represent the tax returns filed in 2008, each “person” one equals 15,246 tax units. (A tax unit is single adult or married couple living together, including their dependents.)

So the top 1% are represented by the 100 “people” in the four (orange, yellow, magenta & red) rectangles the upper left corner.

Approximately $8.2 trillion in personal income (including capital gains) was reported to the IRS in 2008. Divide that by 152 million tax units you get an average income of $54,315. I have the size of the “people” represent the average income for each percentile group. For example the Average Income for the Top 0.01% = $27 million.

Data is from Saez and Piketty research which is now available at the The World Top Incomes Database 

Sign up to be notified when the Income Guide is done:

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A simple example showing what happens when you only pay the minimun monthly payment on your credit card debt. I submitted this to Longshot magazine’s issue on Debt but my graphic didn’t make it in but you can take a look at the other submissions on their site.

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I will be speaking at the The Big Picture Conference on October 11th. Early Registration ($395) has begun. You can sign up at Eventbrite

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While my blog has been pretty quiet over the summer as I work to finish my Income Guide I just wanted to pass on some good news. I recently applied for and received one of four $12,000 NMWE grants from the J-Lab: The Institute for Interactive Journalism at American University. This initiative is supported by the McCormick Foundation. J-Lab helps news organizations and citizens use new media technologies to create fresh ways for people to participate in public life. This grant lasts until the fall of 2012 and supplements $14,000 that I raised on Kickstarter. My plan over the next year is to build on the work I am doing this summer by redesigning my website while continuing to create infographic explainers using economic data that help journalists, teachers, students, financial bloggers and citizens understand economic numbers and policy.

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This is the second map that I created with my urban geographer brother Matthew Mulbrandon on the Housing Price Index (HPI). A description of these maps as well as the first set can be found on Design & Geography. This new set is inflation adjusted and covers the entire span of the Federal Housing data set 1991-2010.

Data source: Federal Housing Finance Agency

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I saw this in a linkedin group I belong to. It is an interesting story from the Daily Mail with some OK pictures on empty cities in China. Also doom and gloom about the housing bubble in China. In brief the story suggest that housing is over valued by 50-70 percent and a crash will leave China like Japan in the 90s. I don’t study China’s housing so I can not vouch for any numbers or predictions. But there are indeed many empty developments which at the very lest shows the flip side of too much command and contral in city planning. The US has tremendous regulations and government influence on cities but this is mostly local and state. Government actions often is controlled by NIMBY’s and developers rather than planned.

This is an interesting Map from the Washington Post Real Estate Section. It shows which metro areas are recovering from the housing crash in the last 6 months. In total 101 out of 360 as measured by the National Association of Home Builders.

Very cool video of International Space Station (ISS) view of earth and night. I saw this at CASA while looking for R maps.

http://www.digitalurban.org/2012/03/time-lapse-footage-of-earth-as-seen.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+blogspot%2FEYWY+%28Digital+Urban%29

This is an interesting interactive graphic on home sales in the DC area. A metro area, because of the strong economy, had one of the smallest bubbles. The NW and central city ( I mean DC part of the DC metro area) was least effected.  Probably due to many young professionals (mostly white) moving into the city because of bad traffic in the suburbs and a better night life. The already wealthy areas in the NW suburbs the increases were real from 2000 to 2005 and was not just part of the Bubble. The African American population has plummeted the last decade from near 70 percent of DC to close to 50 percent.

This is the second installment (by Matthew Mulbrandon and Catherine Mulbrandon) on Housing Price Index (HPI) by state in the United States. The first set of maps can be seen here. This new set is inflation adjusted and covers the entire span of the Federal Housing data set 1991-2010.

Much of the present debate on the future of the US economy has centered around Case-Schiller HPI and their suggestion that housing has historically risen with inflation (at least in their 20-city database). Of course context is everything so unemployment, income, urban development, housing supply, demographic change, other financial opportunity all play their part.

HPI USA 1991-2010 (pdf)
Data source: Federal Housing Finance Agency

These maps give a nice snapshot into ground zero of the housing crisis in California, Nevada, Arizona, and Florida. Historically it would appear that California and Nevada are less prone to a further drop than fellow western states. Florida and Arizona, while up over the past twenty years, have not increased by much as compared with other parts of the country and both have had substantial population increases and are not fixed to the old industrial economy. Although it has been a bad decade for Michigan, it did well in the 90s and seems to fit in with fellow rust belt states of Ohio and Indian over the long term. State dominated by the megalopolis DC to Boston (while not having large increasing the 90s) have gone up substantially in the last decade. If this increase is justified remains to be seen. DC itself has gone up 112 percent and did not have the same decline in prices after the housing bubble burst as many other places (not shown on the scale). Louisiana probably had a larger increase in housing prices resulting from the destruction of the housing supply in 2005 by hurricane Katrina. The western states with large price increases have had large numbers of white/non Hispanics migrants from California as well as traditional immigrant groups Asians and Hispanics. It is also very urban, 90 percent or more, and the great plains states have weathered the recessions without much unemployment.

The value of owning a home is determined by the rent, increase over inflation minus depreciation 1.5 percent (estimated), taxes, insurance, although there are many tax brakes and financial incentives that homeownership brings. That along with increasing population of urban areas makes me think that housing will naturally increase faster than inflation in a growing economy like the US. The post below shows the difference between HPI methods in the last 20 years.

I created the maps below (with Catherine Mulbrandon) to show the nominal Housing Price Index (HPI). They give a quick and easy glance at the bubble in housing prices in the United States by state. As you have probably seen in the news the bubble was largest in the West in states such as California, Arizona, and Nevada and Florida in the South East. Those states had the largest increase from 2000-2006 (height of the bubble) and the largest decrees from 2006-2010. One can see how homeowners ended up “under water” on their mortgages and left banks and taxpayers with major loses. However, from 2000 to 2010 all states except Michigan had moderate nominal price increases. Michigan missed out on the price increase but with the nation’s highest unemployment rate and with it’s major metro area, Detroit, being the most segregated metropolitan area in the U.S., Michigan crashed along with California and Florida.  However, what goes up does not necessarily crash. Virginia, Maryland and NJ all experience large price increases with relatively small decrease. These states are dominated by NY and Washington DC metro areas. Future posts, will focus on smaller geographic areas as urban economic and social dynamics play an important roll in the nation. Unlike the stock market, which changes over time but is the same price no matter where you are located the housing bubble was characterized by change in space and time. (you can get a pdf here)

In the past, housing bubbles have been regional in nature but starting in 2006 nation-wide price declines (even global) are evident although certainly concentrated in particular regions.

Typically what gets reported on the news is the Case-Shiller index for home prices. It only tracks the change in the price of recent homes sales compared to the the last time they were sold in 20 metropolitan areas around the country while excluding those that have undergone major improvement of renovations. This obviously create some bias as the country may experance different dynamics from the housing the Case-Shiller index. One can see the difference here:

The Federal government tracks the same numbers, but also has the information for over 200 metropolitan areas (MSA). They also provide a Housing Price Calculator for metropolitan areas going back 20 years so people can find out what has been happening where they live. Some of the results are surprising. For example over the last decade (starting in q40 middle of graph) there was a price bubble in Boise, Idaho with home prices up 80% over the 2000-2006 time period. However, by 2010 they were only up 30%, which just keeps pace with inflation.

This chart show housing prices for Boise, Idaho 1991-2010

Housing Price Calculator will also give you a chart like this for your community.

This is the link to Nimble video an innovative bus based transit system. It was Submitted to the Buckminster Fuller challenge.
This work is designed to make traditional urban transit more “nimble”. It is a new type of transit system built around the common bus. It can grow and change as the city does. NIMBLE can help shape even the most sprawling cities into transit friendly metropolises.

Describe the critical need your solution addresses.

NIMBLE was conceived to connect and re-shape auto-oriented, fragmented ‘new’ cities and underserved developing cities. It can provide a large service area, large capacity, operate cost effectively, and compete with the private automobile.

Explain your initiative in more depth and its stage of development.

Using two innovations, NIMBLE will connect three recent but proven technologies, buses running on rail, Bus Rapid Transit (BRT), and High Occupancy Toll lanes (HOT lanes) incorporating the best features from each system.
Bus Trains: Bus rail has been implemented in a few European and Australian cities but only running single buses. NIMBLE can, when the situation dictates, transform individual buses into bus trains, that is buses that link together like rail cars. These bus trains would run in tunnels and/or elevated busways in the most populated center core of a city. Research on fast linking and control technology is needed to make this work. Bus trains can transport more people faster and more safely in densely populated areas. However, in less populated areas the bus trains can unlink each individual bus, each of which travels to separate destinations.
Elevated “HOT lane” bus stops: HOT lanes have variable tolls determined by congestion levels while allowing HOV 3 vehicles free use. This money can be use for infrastructure cost and will control congestion. HOT lanes are operating in several cities. By installing elevated bus stops, buses can use the speed of freeways without pulling off to board passengers. This will turn the highway network into s bus transit system without requiring large initial ridership or capital investment. Buses can also bypass stops allowing for powerful scheduling possibilities. The elevated bus stops require greater bus acceleration and its design must be developed and tested.
NIMBLE shamelessly reuses innovation that can be found in Bus Rapid Transit (BRT) systems around the world. BRTs can be thought of as a surface subway, which re-brands the bus as cool/fun, safe, reliable, comfortable. Along with fast boarding, BRTs provide satisfaction equal to light rail for less cost.
The complete system integration of bus vehicles, bus rail, BRT, HOT lanes is NIMBLE.

Interactive map from Slate. Source of the data is Behavioral Risk Factor Surveillance System. I have used it is past research.

Map of countries fitting into Africa to show its size. Tries to counter distorted view of the world people have with some examples.

In an interesting twist they have China listed as the 3rd largest country in the world by land area. It is 4th just behind the USA as shown by the webpage data. Must have sorted wrong.

I saw this link to a TED talk as I was looking for population projections for China and the US. It is from a professor and co-creator of GAP minder (recently bought by Google I think). Not too many numbers but lots of animations of health, income by region for different countries. Starts by showing the people have out dated view of life expectances and family size. It is very interesting visually. I also think it is a powerful teaching tool.

Fact: Mexico and the US had almost identical birth rates in 2008. If you did not know that your knowledge is outdated.