Dear Statalist forum,
I have a situation where I am not sure whether a multi-level analysis is needed. Or whether it might suffice to include a firm dummy.
The analysis I run is intended for a paper in the field of management/ strategy. So, the relationship I study is how a certain characteristic of a business unit (BU) affects the business unit’s financial performance. Each of the business units belongs to a firm:
BU_performance = BU_characteristic_of_interest + controls
The controls include some other characteristics of the BU (e.g. the size of the BU). But the controls also include some variables that come from the firm-level (for example, the ‘percentage of the firm that is owned by the firm’s CEO and the firm’s top management team’).
So for example, I have 9 observations in my dataset that belong to the firm Generel Electric (GE) in the year 2000. These 9 observations reflect the 9 business units that GE operated in that year. The BU_characteristic_of_interest differs for each of the 9 BUs of GE in that year. Similarly, some of the controls are different for each of the BUs of GE (e.g., the size of the BU). Yet for other variables, all of the 9 BUs will have the same values (e.g., all of the 9 BUs will have the same value for the ‘percentage of the firm that is owned by the firm’s CEO and the firm’s top management team’).
Now, the business unit observations are not really independent from each other.
So I wonder whether for the case describe above I will *have* to use a multi-level model (Stata XT Mixed). Or whether it might suffice to include a firm dummy for each firm.
The reason I would like to avoid the multi-level model is that I worry that I might run it the wrong way or misspecify the model. I am not a big expert on econometrics whatsoever.
Also, I feel that in my field (strategic management), multi-level models are not common at all. Although I wonder whether (by a similar logic described to the above), they would actually be needed. In strategic management, we often compare different firms with each other – but firms typically come from different industries – i.e. firms are nested in different industries. So wouldn’t that mean that all these researchers should actually use multi-level models when they study these different firms? (But, I just don’t really see them using multi-level models.)
So I wonder what is the correct thing to do econometrically?
Can one also just include firm dummies (for the business unit example which I described in the beginning of this post)? Would using firm dummies be alright as well, or would this approach break some econometrics rule?
Or, alternatively do I have to use a multi-level model for this situation?
Thanks so much.
Best,
Franz
I have a situation where I am not sure whether a multi-level analysis is needed. Or whether it might suffice to include a firm dummy.
The analysis I run is intended for a paper in the field of management/ strategy. So, the relationship I study is how a certain characteristic of a business unit (BU) affects the business unit’s financial performance. Each of the business units belongs to a firm:
BU_performance = BU_characteristic_of_interest + controls
The controls include some other characteristics of the BU (e.g. the size of the BU). But the controls also include some variables that come from the firm-level (for example, the ‘percentage of the firm that is owned by the firm’s CEO and the firm’s top management team’).
So for example, I have 9 observations in my dataset that belong to the firm Generel Electric (GE) in the year 2000. These 9 observations reflect the 9 business units that GE operated in that year. The BU_characteristic_of_interest differs for each of the 9 BUs of GE in that year. Similarly, some of the controls are different for each of the BUs of GE (e.g., the size of the BU). Yet for other variables, all of the 9 BUs will have the same values (e.g., all of the 9 BUs will have the same value for the ‘percentage of the firm that is owned by the firm’s CEO and the firm’s top management team’).
Now, the business unit observations are not really independent from each other.
So I wonder whether for the case describe above I will *have* to use a multi-level model (Stata XT Mixed). Or whether it might suffice to include a firm dummy for each firm.
The reason I would like to avoid the multi-level model is that I worry that I might run it the wrong way or misspecify the model. I am not a big expert on econometrics whatsoever.
Also, I feel that in my field (strategic management), multi-level models are not common at all. Although I wonder whether (by a similar logic described to the above), they would actually be needed. In strategic management, we often compare different firms with each other – but firms typically come from different industries – i.e. firms are nested in different industries. So wouldn’t that mean that all these researchers should actually use multi-level models when they study these different firms? (But, I just don’t really see them using multi-level models.)
So I wonder what is the correct thing to do econometrically?
Can one also just include firm dummies (for the business unit example which I described in the beginning of this post)? Would using firm dummies be alright as well, or would this approach break some econometrics rule?
Or, alternatively do I have to use a multi-level model for this situation?
Thanks so much.
Best,
Franz
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