Real Estate and In-Migration
The Post and Courier covered a local real estate economist’s presentation on the Real Estate Recovery. Core to any real estate recovery is, of course, employment and wage growth. However, a key statistic overlooked in this presentation was migration patterns. I had mentioned in my June Unemployment post that areas such as Detroit were having problems as a result of a declining labor force. This map from Forbes graphically displays the migration problems Detroit is having.
But when you click on Berkley, Charleston, or Dorchester counties, a picture of in-migration emerges. This is an important indicator of growth potential because people have jobs when they move here, have decided to collect transfer payments (retirement) in this region or believe there is potential for work in the area.
Another important statistic this map displays is how our rural population is moving to metro areas (short black lines). This is important for two reasons: 1) unemployed people may have the opportunity to find work and 2) if they find work, the state increases its tax base while decreasing social services.
Unlike the economist quoted in the article, I predict our real estate growth will be better than the median national real estate growth, primarily because of in-migration. This is not to say it will be even close to the bubble years (when we had an unrealistic and unsustainable market), but we should see steady improvement as a result of our region’s possibilities.
I am bullish, for a change. I do believe we have significant control over our own growth since the most important contributors to growth and sustainability include education, health care, public safety, urban planning, convenience and infrastructure (including biking and walking trails), which all are within our control.
Thank you to Keihly Moore for her assistance with this article.
Discouraged Workers
A recession can really change people’s attitudes about looking for work, and many become discouraged (PDF). Unemployment rates in South Carolina are hovering between 10 and 12 percent. But another way to look at that is 9 out of 10 people are actually working! In addition, even with high unemployment, there is still considerable churn in the market place, meaning that jobs are being filled and vacated every day.
So what is the problem? One issue is that the right work is more difficult to find, and takes more time to find, which is discouraging. Matching one’s skills to a job is challenging especially when jobs skills for work are in a constant state of flux. Unlike some employed workers, who may receive retraining assistance from their employer, the unemployed need to finance their own retraining with no guarantee of a job at the end of the training.
Another reason is that the employment picture is likely worse than reported in the media. For example, if we hold the workforce steady at April 2009 numbers, 2,185,673 persons, (people don’t just disappear) and use that number to calculate unemployment in June 2010, holding employment constant, the unemployment rate jumps to 12.2 percent not the current South Carolina adjusted rate of 10.7 percent.
As employment data is published in the coming months, it is important to keep in mind these variances:
- Where we were and where we are now,
- Whether the gap is shrinking or growing and
- The effect this has on unemployment prospects for both the employed and the unemployed.
By keeping these points in mind, we will have a better feel for the current labor situation going forward.
June 2010 South Carolina Unemployment
The Post and Courier wrote and excellent article on the June employment situation here in SC. By focusing on the labor force, the P and C is highlighting a major issue not only for our state but for the country. From the labor analyst perspective, one of the disturbing trends is the “discouraged worker”. The Bureau of Labor Statisics defines Discouraged workers (Current Population Survey) as:
“Persons not in the labor force who want and are available for a job and who have looked for work sometime in the past 12 months (or since the end of their last job if they held one within the past 12 months), but who are not currently looking because they believe there are no jobs available or there are none for which they would qualify.” The data suggests a worsening situation on the labor front.
Here is a table (PDF) with the BLS discouraged worker annual data. I would like to think these data are about to turn, especially with the number of temporary workers being hired. However, one issue which may prevent that, is the skills gap.
Reverse Pivot Table: Matrix → xyz Format
I like to add a few technical tools now and again. Here is a sweet piece of programming that could save time converting a matrix to a xyz table. The surface plot on my web page can be created by converting matrix data to an xyz format.
Issue
The problem I often run into with excel spreadsheets, is the data is defined in a matrix. Sometimes it is more convenient to reorgainze the data with a pivot table in order to represent the data as xyz coordinates. At first glace it appears this should be an easy task, but with out the right excel module or the full version of sql- forget it.
Solution
A solution to this problem is provided by The Spreadsheet Page, a reverse pivot table. The link does an excellent job of explaining the process. At the bottom a VBA link allows one to copy the code into your excel application. A big thank you to these guys for sharing this- it saved me many hours of work.
South Carolina May 2010 Unemployment Numbers
Problem- Not Really
I had some questions on the May unemployment numbers which did not seem to make sense to me. The article posts the state unemployment rate. Further down in the article however, a key piece of information reveals the rate quoted was an adjusted state rate.
Issue
In this case it makes a big difference, since the state rate is mentioned in conjunction with the regional unemployment rates. Once this point was brought to my attention, I realized the error of my thinking. Local unemployment rates are not adjusted! So when comparing local and state rates one needs to compare the state unadjusted data with the local data. This process yields similar results with both local and state rates moving in the same direction. In the case of the May data, adjusted state data was quoted (correctly) with unadjusted local data. The result is unemployment rates moving in opposite directions (in this case) since in reality we are comparing apples and oranges.
Conclusion
Even though the adjusted state rate is the most commonly reported rate in the media, I tend to use unadjusted just for this reason, I want to compare it to the local rate. Another reason, which is a little old fashioned, is because the state data will be adjusted again at the end of the year, smoothed in this case. Also as I describe in my Unemployment Definition, I am focused on the overall trend and do not get to hung up on an individual data point. Key point is to make sure we do not compare or imply the state adjusted rate is related to the local unemployment rates.
