[Limdep Nlogit List] Industry Classifications in Random Parameter Model

[Cem Payasli]

Greetings,

 

I want to estimate a Random Parameter (NegBin-P)  panel count model with
industrial heterogenity effects accounted for by various type of  economic
activity classifications such 1) NACE2, 2) ISIC4 , 3) ISB3D   and finally
standard  Industry classification in the original dataset. Specifically my
Limdep command would look like :

 

NEGBIN;Lhs=PAT;Rhs=LRD,LRD1,LRD2,LNS,LCAP,RDORD;PANEL;Robust;RPM=NACE2;Fcn =
LCAP(n),LNS(n);Correlated;halton;Pts=25;Model=NBP$

 

In each round  NACE2 will be replaced by ISIC4 and then by ISB3D and finally
Industry categories. These classifications have 212, 32, 39 and 40 records.

 

I have seen Random parameters example based on Bertscheck and Lechner (1998)
study which defines an innovation binary logit variable as below:  

? Random parameters with industry heterogeneity (From Greene's Lab session
slide)

? Examine effect of industry heterogeneity.

Sample ; All $

Logit ; Lhs = IP ; Rhs = One,IMUM,FDIUM,SP,LogSales

      ; Pds = 5  ; RPM = InvGood, RawMtl

      ; Halton ; Pts = 15 ; Cor

      ; Fcn = One(n),IMUM(n),FDIUM(n) ; Marginal 

      ; Parameters $

Create; Bimum = beta_i(firm,2) $

Regress ; Lhs = Bimum ; Rhs = one,InvGood,RawMtl $

 

Because InvGood and RawMtl (Investment goods and Raw materials) are defined
as dummy variables, their range in RPM specification is restricted to 0 and
1 only. 

Since my own RPM predictors are not dummies but factor variables (in Stata
jargon) the only way to incorporate them seems to create dummies via
CREATE;Expand(NACE2)=N1,N2,N3......so on..

 

However, that would be formidable number of dummies for some
classifications.

 

Is there any other way around ?

 

Thanks for any suggestions.

   

 

Cem Payaslıoğlu

Department of  Economics

Eastern Mediterranaen University

Magusa, TRNC, Mersin 10 Turkey