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Re: st: xtlogit - lagged dependent variable as independent variable
From
Andreas Schiffelholz <[email protected]>
To
[email protected]
Subject
Re: st: xtlogit - lagged dependent variable as independent variable
Date
Tue, 23 Apr 2013 10:03:29 +0200
Jeremy,
thanks a lot for your fast and detailed answer.
One short question just to make sure:
As I understand from your answer there is no further adjustment -
comparable to the Arellano-Bond adjustment - needed when using a lagged
dependent variable (given my dataset characteristics and the fact that I
use -xtlogit, re- and not a linear regression model). Does this stand
true if I add more than one lagged variable?
-xtlogit strategy L.strategy L2.strategy L3.strategy L4.strategy company_age company_size industry, re-
I want to use this model to check how many years back have an influence
on the choice of the strategy in the current period.
Thanks a lot and best wishes
Andreas Schiffelholz
Am 22.04.2013 22:51, schrieb Jeremy Wells:
Andreas,
There is a pretty intense debate over how to model autocorrelation,
especially within political science. I would suggest work by Beck and
Katz, especially in the Annual Review of Political Science (2011,
vol. 14: 331-352). They prefer lagging the dependent variable, but there
are other methods.
I would also suggest using the time-series operators built into Stata to lag
your DV, so your command would look like this:
-xtlogit strategy L.strategy company_age company_size industry, re-
(I also took out the year variable, because I am not sure how well that would
factor in with a lagged DV and the company age variable, though it may not
be problematic or they may be unrelated, but I would bet there would be a lot
of multicollinearity there.)
HTH.
Jeremy Wells
Ph.D. Student
LSU Dept. of Poli. Sci.
324 Stubbs Hall
Baton Rouge, LA 70803
Sorry, the Stata command mentioned below got messed up:
- xtlogit strategy strategy_lag1 company_age company_size industry year, re -
Andreas
Am 22.04.2013 20:15, schrieb Andreas Schiffelholz:
Hello,
I'm currently working with a company dataset in the form of an unbalanced panel (overall sample size: 1.300 company years, T: 10, X: ~170 different companies). One of two strategic types was assigned to each of the company years. To get a better understanding, why companies are pursuing a specific strategic type, I am using a random effects model -xtlogit, re-:
- xtlogitstrategystrategy_lag1company_agecompany_sizeindustryyear, re -
with "industry" and "year" being a set of dummy variables.
Part of this model is the independent variable "strategy_lag1" which is the strategic type (dependent variable) of the previous year. This variable is added to get a better understanding of the stability of the strategic type in terms of time. As far as I know there is an adjustment of the model needed when adding lagged dependent variables to the model. I did find the -xtabond- command for linear models, which is using the adjustment procedure suggested by Arellano, Bond (1991). For the xtlogit model I did not find a comparable command.
Given the characteristics of my data set, is there an adjustment of the standard -xtlogit, re- model needed? Does the answer to this question change if I add additional variables with longer lags to the regression (strategy_lag2, strategy_lag3, …)? If so, is this adjustment implemented into Stata or does anybody know a user programmed command dealing with this issue?
Thanks very much,
Andreas Schiffelholz
P.S.: This is my first time posting something on Statalist. If the description of my problem is not precise enough or if I broke a specific rule of the list, please let me know.
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