This is a fundamental question I have, and so far I have not found a convincing answer.
My theory is this: $$ w_{ijt} = \theta_{jt} a_{ij} $$ where $w_{ijt}$ is wage of worker $i$ in occupation $j$ in period $t$, $\theta_{jt}$ is the "efficiency wage" paid to every worker in occupation $j$, in period $t$, and $a_{ij}$ is the ability of worker $i$ in occupation $j$. (Since workers are observationally identified by $i$ and $t$, we could define $w_{ijt}=w_{it}$)
Now, we observe wages but not ability nor "efficiency wage". So, to estimate these two components, I use a two-way error component model (taking logs):
$$ \log(w_{it}) = \log(\theta_{jt}) + \log(a_{ij}) + e_{it} $$ Notice that this decomposition is possible because each component varies across different dimensions.
Now, from my estimations I get $\hat{\theta_{jt}}$ and $\hat{a_{ij}}$.
The question: How can I know that the units of measurement of my estimated components are the same than those of my theory?
Does the answer change if I extend my estimation with:
$$ \log(w_{it}) = X\beta + \log(\theta_{jt}) + \log(a_{ij}) + e_{it} $$ where $X$ are other determinant of wages?