I have the following problem that I hope to find help with:
My data structure is as follows, with employee-employer links over several years:
y | j | i | yj | xj | xi |
1 | 1 | 1 | a | x | f |
1 | 1 | 2 | a | x | g |
1 | 1 | 3 | a | x | h |
2 | 1 | 1 | b | y | f |
2 | 1 | 2 | b | y | g |
2 | 1 | 3 | b | y | h |
1 | 2 | 4 | c | z | l |
1 | 2 | 5 | c | z | j |
1 | 2 | 6 | c | z | n |
2 | 2 | 1 | d | xy | f |
2 | 2 | 4 | d | xy | I |
2 | 2 | 5 | d | xy | j |
My aim:
To explain an y-variable on the j-level (firm-level), for example profitability, from both j-level explanatory variables (for example debt) and individual characteristics (for example gender), to investigate the influence of individuals on firm outcomes.
My problems:
* How do i explain the yj variable, when it's on a higher level than the explanatory variables? For example, for firm j in y 1: the yj (dependent variable) is repeated three times...
* Individuals (i) are nested within firms (j) - but they can also move between firms! For example, in my example above individual 1 moves from firm (j) 1 in year (y) 1 to firm (j) 2 in year (y) 2.
* How do I incorporate into the model the fact that employees are ranked within the firm-year? Within each firm-year I rank employees according to salary, assuming that the highest paid employees have most influence on firm outcomes.
I am looking forward to your valuable inputs!
Best,
Morten Jensen
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