business stats
The truth?
Too often, we think the data is straightforward math and simply draws on the underlying data sources. The reality is that it is anything but.   The following example will hopefully illustrate the point.

Recently in Washington a rather large number of economists from academia and government met to resolve an issue with data gathering. It has become more serious in the US and has distorted how we value the American economy itself. Central to this issue is how imports into the US are accounted.  

For example, when a part for $100 is imported from China and is used in an American automobile … something that happens much more often these days … the stats show that the finished car is American-made because it was assembled in the US. As a result, the US GDP is raised by that same $100 when in fact it should have been deflated by that figure instead.   In the process, American workers who might in the past have made the part are no longer doing so and hence a job is lost.

The unemployment data finds the unemployed worker and accounts for him or her, but the car that is assembled does not, and when it is produced and sold as it’s value makes it’s way through the system, it appears productivity has risen, when in fact it has not. {False conclusion of data:   Fewer workers needed to make a car}

As one of the economists attending that meeting said,

We don’t have the data collection structure to capture what is happening in a real-time way, or what is being traded and how it is affecting workers.   We have no idea how to measure the occupations being ‘offshored’ or what is being ‘inshore.’

Or as the Assistant Commissioner for International Prices at the Bureau of Labor Statistics (that’s a socialist sounding title if I’ve ever heard one) Mr William Alterman, said regarding the problem

What we are measuring as productivity gains may in fact be nothing more than changes in trade instead.

This is not an insignificant problem.   The US has become much more international in its trading scope.   Back in 1975, imports into the US were only 5% of our total economic activity, but in recent years that has swelled to 12%, excluding imports of energy. Thus, many imports into the US are being valued as though they were manufactured here in the US, when indeed they were manufactured abroad and merely assembled here in the US.

In autos, computers, appliances and similar manufacturing industries this is a large and growing problem, but the same is happening in areas of service as well.   For example, when an accounting firm out-sources some of its number-crunching to a group in India and then bills the client in the US, the work is done abroad but being recorded as having been done in the US, adding to US GDP when clearly that is not the case.   The same scenario plays out in medicine when patient files are sent to India and billed back to the US in US dollars.   GDP rises here in the US when it really should have been accounted for in India; productivity goes up; GDP goes up, when in reality neither has happened.  

It is important to look at the big picture when analyzing data, especially when assumptions of years past have changed considerably. Just as we adjust for inflation, we need an adjustment for outsourcing our productivity.