Hello,
It is my first post on the platform, thus I hope to be as clear as possible and compliant with the rules as well. I tried to find a clear answer in many other posts but did not quite manage.
I'm working with a large (unbalanced) panel dataset (45,000 firms in a time-span of 23 years). The panel contains information on firm's financial indicators and performance variables (e.g., liabilities, assets, debt, dummy for quoted firms, and others) and firm-level innovation variables (e.g., patent filed for each year, patent stock, green patents, technology-specific patents, and others).
Since my dependent variables are non-negative count variables, I am trying to estimate the effect of the following variables on the number of green patents using a fixed effects poisson model using the -xtpoisson, fe - command as indicated next:
Now, for other specifications of the same model (e.g., I am using winsorized variables, or I am adding some new controls, or I am clustering SE on different variables), -xtpoisson, fe- does not converge and returns no output. I know that this can be due to the large dataset. I encountered the -ppmlhdfe- command as a substitute to xtpoisson for those cases in which this latter does not properly returns output. I also came to know that, provided the same model specification, both commands deliver the same model with the same output coefficients. Here I give you an example of the same specification with the new command (here I call for robust standard errors, but this should not affect the coefficients, rather only their significance):
My question arises here: some groups (i.e., firms) in my panel have all dependent variable (green_pat, in this case) featuring 0 values for the entire period. As you already know, -xtpoisson- leaves out these observations for reasons of convergence, considering also the fact that they would not add any information to the estimation process. In particular , this is the STATA note when the command is called:
This is not done by the -ppmlhdfe- command leading to different results. What I naturally thought to do was to create a count variable that specified for each panel unit the number of green patents as a total for all the period. Then I ran the -ppmlhdfe- command with the same previous specification adding an -if- statement excluding groups with 0 green patents in the period. I expected that this solved the issue, but only 252 groups were dropped. In fact, by running -xtpoisson, fe- command with the same specification and -if- statement excluding all 0 groups, a note again appeared saying:
At this point, I am not sure of 1) which observations does -xtpoisson- command leave out of the estimation; 2) why does ppmlhdfe not bother doing the same thing; 3) how can I reach the same results employing both commands.
I hope I have been clear enough. Any help is highly appreciated.
I thank you all for availability in advance.
It is my first post on the platform, thus I hope to be as clear as possible and compliant with the rules as well. I tried to find a clear answer in many other posts but did not quite manage.
I'm working with a large (unbalanced) panel dataset (45,000 firms in a time-span of 23 years). The panel contains information on firm's financial indicators and performance variables (e.g., liabilities, assets, debt, dummy for quoted firms, and others) and firm-level innovation variables (e.g., patent filed for each year, patent stock, green patents, technology-specific patents, and others).
Since my dependent variables are non-negative count variables, I am trying to estimate the effect of the following variables on the number of green patents using a fixed effects poisson model using the -xtpoisson, fe - command as indicated next:
Code:
xtpoisson green_pat tot_pat pat_stock tobinsQ_ ln_tot_liab_ leverage roa_ebitda rev_growth RD_sales i.year i.GICS_code if year>=2010, fe
Code:
ppmlhdfe green_pat tot_pat pat_stock tobinsQ_ ln_tot_liab_ leverage roa_ebitda rev_growth RD_sales i.year i.GICS_code if year>=2010, vce(robust) nolog
note: 592 groups (5486 obs) dropped because of all zero outcomes
note: 340 groups (2850 obs) dropped because of all zero outcomes
I hope I have been clear enough. Any help is highly appreciated.
I thank you all for availability in advance.
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