Vehicle Manufacturing Employment
The Post and Courier article on vehicle manufacturing needs clarification. The impact data stated is incorrect. A typical impact multiplier for transportation manufacturing is approximately 1.7 jobs for each NEW job created in transportation, not the claimed 4.8. The claimed 4.8 is a crazy number (marketing hype) and not possible.
Furthermore, according to the Bureau of Labor Statistics, vehicle parts manufacturing employment (state of South Carolina) decreased by 1443 jobs from 2006 to 2008. Data for 2009 has not been released, but I expect another 300-500 jobs lost, bringing the total closer to 2000 jobs.
One item not reported in the article was the INCREASE in number of firms in this industry – from 10 firms in 2006 to 18 firms in 2008, a substantial increase. However, when we look at the bigger picture, transportation manufacturing employment as a whole has declined 15 percent.
It is important for the reader to know that I have offered a number of times, in writing, to assist the Post and Courier in their analysis of these data at no charge to them. So far they have ignored me, or anybody else for that matter. Until that time whereby they ask and receive technical assistance, I suspect most of these data will be reported incorrectly.
United States – South Carolina Unemployment Comparison
I had a recent question as to why South Carolina (SC) unemployment rates appear to be lower than the United States (U.S.) rates before 2001 and higher after 2001. With this question we need to back up a few steps. There are three factors which, when taken into account, explain unemployment rate expected variation.
First, the U.S. unemployment rate is calculated using the Current Population Survey or CPS. State and local unemployment data is calculated using Local Area Unemployment Statistics or LAUS. These are different programs with different methodologies, although related. Many times, as reported in the press, these data do not corroborate.
Second, compatibility of reference data sets. Many forget that SC is a state with a population of only about 5 million persons. The U.S. has 300 plus million persons. In other words it is more likely than not that SC is not a representative sample of the U.S. So there is no reason to believe that what happens either in the U.S. or in SC will affect the other by the same proportion at any time, historical or otherwise! This is an issue not only in this case, but with many data comparisons- the old apple and oranges problem. Because they appear to be related, we make a big deal out of it when in fact the two are independent events.
Alternatively, it is more likely the economies of Georgia or North Carolina, our trading partners, will have a greater impact on SC, in both the short and long run.
A third factor, and a complicated one at that, is the change in survey method over time. There have been significant survey updates in 1996, 2000 (Census), and 2003 to mention a few. Often data is labeled with codes indicating a methodological change in the series. The Bureau of Labor Statistics often describes these changes in great detail with formula- yikes! It is safe to say, the changes do impact the data, sometimes with sudden jumps up or down, considered by some to be either favorable or unfavorable. The fact is, it was a change in method and all data still sums to 1. Unfortunately, the next day you will still be either employed, unemployed or looking for work in this data set. Here is a link to the summary of differences.
NOTE: The BLS does make mistakes, most recently with the Current Employment Statistics. However, they are a group with integrity who fix mistakes, correct data, and describe the impact. What I like most about the BLS is their drive continually to improve data through refining their techniques. Businesses and individuals who use these data have benefited significantly.
How to Think About Unemployment Data-
Example: As a former labor market analyst, I emphasize the big picture, the trend. Here is a link to a spreadsheet that compares, for the fun of it, SC, MI, US and SD back to 1976. Note how differently these states labor forces have reacted to this and other booms and recessions. Recently, the MI labor force has crashed, likely driven by the employment outlook, thus creating a high unemployment rate. SC, on the the other hand, has strong labor force growth, maybe too strong (over new employment), creating higher unemployment. This is better than a labor force crash, however! Have you ever been to SD? I am poking fun at a former neighboring state of one where I previously lived. The point is that each state has its own economy, and it is best to understand that economy and focus on what it can and can’t do. In SC, we have been hit hard in the textile industry (another plant announced a closure today), missed the finance crash, but took it on the chin in the auto parts industry (about 2000 jobs since 2007). We are a rural state where persons have a difficult time migrating to new jobs. We are also a state where people go to spend money- tourism. Persons have been tight with that money recently. Most employment and unemployment data makes sense when we take a look at a regions industry make-up (mix), and how those industries manage over time in up and down economies.
Sorting text and numbers within an Microsoft Excel Spreadsheet Cell
I was cleaning some data for a project and ran across the “text/number in the same cell” sort problem. I researched the web and found three links that were very useful for sorting text and numbers when displayed in the same spreadsheet cell. Cleaning and organizing data is a big part of what I do to prepare information for analysis. This process is critical since, accurately loading data into a data base requires consistent data type; otherwise data will default to text (unknown), not useful for making calculations. Cleaning data is a great way to begin immersing one’s self in what one actually has in terms of data. This process takes the information into its most basic form.
I have included a link to a sheetsheet that shows the two different formula with comments and links. I have also used the “iserror” function in one of the formula, just in case you have forgotten that one..hmmm!
South Carolina Labor Market Information
South Carolina LMI
08.24.09 Resources- LMI Resource development: Source: lovetowork.org
08.25.09 OES Method Two-Tail T-Test
08.25.09 Statistics UI Variation
08.26.09 Normality
08.26.09 Box Plot Description
08.26.09 Basic Statistics Glossary
08.31.09 Alternative UI Rates
08.31.2009 Sample Design CPS
08.31.2009 Occupational Supply Demand System
