WSJ Housing Inventory Trends

Check out this Wall Street Journal Interactive graphic showing changes in housing inventory in the past two years. It has some useful and novel features that make exploring the 18 different cities and 3 different regions easier over the past 20 months.

Here's one of the more interesting charts that I created in just a few minutes of exploration.


For the six cities shown (Miami, Orlando, Chicago, Las Vegas, Los Angeles and Phoenix) the upward trends since October 2005 are plain to see.

Try it out yourself and see what you can discover.

Here are my thoughts on the pluses and minuses of these interactive chart features

On the plus side

1. A single click selects a new factor to add to the mix of factors already selected for the chart

2. When adding a new factor into the mix, it highlights that new factor on the chart and reduces the intensity of the other factors on the chart until you move the mouse over the chart again when all factors selected come into full view. This helps you lock in on the colors for the new factor before they become blended with the other factors.

3. When you move the mouse over the check box for a factor that has already been selected, that factor is highlighted against the other factors currently selected with a little pop up text box that tells you the current inventory value exactly.

4. A single click as all that's required to de-select a factor.

5. A single click for one of the three areas (East, Central, West) selects all the factors for that area. And once a whole area has been selected, a single click de-selects all factors currently checked.

6. All of the above pluses add to ease of use and time saving when exploring this data set for the most interesting and telling patterns.

On the minus side

A. Way too short a time range. To make full sense of these trends and put the recent behavior in perspective needs at least 5 years and preferably 10 to 25 years of history.

B. Some major cities that are in the top 10 in population are missing - New York, Philadelphia, and San Antonio.

C. No way to adjust Y axis scaling. This is a serious drawback. The scale runs from zero to 110 thousand which is fine for viewing the trend for Los Angeles which has a range between 45, 000 and 103,000, but it makes it difficult to grasp the trends for such cities as Minneapolis which varies from 25,000 to 31,000 or Baltimore which ranges from 5,000 to 10,000. Both of these cities look flat line during this period even though when you examine them closely they really aren't. Y axis scaling options such as the possibility of calculating the Min-Max scaling for the factors charted would help bring the trends for all cities into clear view.

D. No available view of the data using percentage change from a baseline value for determining the Y axis value. Such a normalizing option would simplify comparisons between cities.

E. No option for showing aggregate results for a region or for stacking the factors selected.

F. If you wish to look at each factor separately, it takes two clicks. One to de-select the previous factor, and one to select the new factor.

G. No option for smoothing with features such as moving averages

H. Missing trend data for other related factors for each city such as

• Inventory breakdown by New and Existing housing
  
• Average number of months houses have been on the market (total, new, existing)
• Median selling price in that market (total, new, existing)
• Rate of sales per month in that market (total, new, existing)
• Number of months of inventory at current sales rate (total, new, existing)

I. Missing option for downloading the underlying data set thereby enabling further analysis.

Hat tip to Barry Ritholtz at The Big Picture

St. Louis Fed - National Economic Trends - June 2007

The newest edition of the always excellent National Economic Trends is available today from the St. Louis Fed.

Here are a sampling of the charts that caught my eye. Click for larger size version.

From their engaging cover article, this first chart shows the percentage of the population age 55 or over engaged in part time employment. The upward trend for women is particularly clear. The article discusses possible causes and notes areas for follow-up investigation.


This next chart shows trends in national income as a percentage of GDP.

Corporate profits weighs in at almost 14% of GDP and is close to the recently set 25 year highs. This is approximately double where it was in 1982.

Proprietor's Income registers at almost 9% of and it also is close to its 25 year highs. This is almost 50% higher than it was in 1982.

Compensation at a little over 64% of GDP is close to its 25 year lows. This is down approximately 3% from the 67% level of 1982.

The remaining National Income components (not shown) must by deduction be down net 7% from about 20% to 13%.


This third chart shows pretty clearly that the rise in corporate profits before tax is directly reflected in the rise in after tax profits as a percentage of GDP. After tax profits have more than doubled since 1982 from 4% to over 8%.


The fourth chart shows that the current account balance is close to its 25 year low at approximately 6% of GDP. Note the striking and steady downward trend since 1991.

And this final chart is noteworthy for the clarity with which it shows the rise of debt service payments to approximately 14.5% of personal income - close to the highest levels in 25 years. The steady upward trend since 1992 is also clearly visible.


Commentary.

1. As I mentioned in previous posts, one of the reasons that I value the St. Louis Fed's monthly National Economic Trends report is their use of long term trends. These help put the current behavior into perspective. The charts I have selected offer a glimpse at how a 25 year trajectory adds understanding to the most recent behavior.

2. That's not to say that their monthly report couldn't be improved. Here's my short list of suggestions on just how that might be done.

• Show all selected factors using the same long term 25 year time frame trend chart as the default setting and template.
• Show each factor on its own before combining it with other factors in a dual chart. The dual chart approach while extremely helpful for showing the possible relationship between a set of factors and simplifying comparison sometimes obscures the underlying trend in some of the factors due to the Y axis scaling used.
  
• For the single charts created for each important factor, consider using MIN-MAX scaling for the Y axis rather than zero based scaling as the default. This is not correct in every instance but it often proves useful in helping make the trend patterns easier to read and understand.
  
• Add at least some minimum commentary (could be 25 words or less) with 20% of each month's set of charts. Add comments for the charts that the St Louis Fed considers to be the most interesting and which have some interesting pattern to observe. E.g. follow the example we have set with the selected charts above. A picture is worth a thousand words, but not every important nuance seen by the expert creators of these charts will register immediately with every viewer, especially to non-expert viewers.
  
• Make it easy to download a cross-tabulated table of all the data contained in all the charts for further examination by interested parties.