In: Economics
6. The Altham statistic does not distinguish between occupations with more and less workers. If some occupations are growing and other occupations are shrinking, then why might it be problematic to use the Altham statistic to compare occupational mobility at different points in time?
Consider the example of two different occupations, construction and teaching. Ignoring the fact that the skills set requirements are very different in the two occupations, construction is a labor-intensive job and needs many labors, however, teaching is something which requires only a few teachers in a school to teach many students. Therefore, construction can be said to be an occupation that requires many workers, while teaching requires only a few workers.
Now, Altham statistics does not differentiate between these two occupations. In other words, if job opportunities are considered, Altham statistics will consider these two types of occupations equivalent.
Understand this with the help of an example. Suppose that the data says that there are 100 teachers in a district, while there are 1000 laborers in the construction. If there is a need for 2 more teachers in a school, 2 of the laborers will shift from construction to teaching (again, assume that the skillset are not required). In an extreme situation, a new school opens up and there is a need for 100 teachers. There will be a labor mobility from construction to teaching sector. However, if a new plant has to be made, there might be a requirement of 1000 workers to be working on a site. In this case, it will be believed that all the teachers shifted from teaching to construction, so there must be a growth aspect in the construction field. But this is not true.
This is why the statistics of Altham may give ambiguous image of the reality and therefore, it could become problematic to use it.