[R] restricted coefficient and factor in linear regression.

[Oh Dong-hyun]

Hi,

my data set is data.frame(id, yr, y, l, e, k).

I would like to estimate Lee and Schmidts (1993, OUP) model in R.

My colleague wrote SAS code as follows:
** procedures for creating dummy variables are omitted **
** di# and dt# are dummy variables for industry and time **
data a2; merge a1 a2 a; by id yr;
     proc sysnlin maxit=100 outest=beta2;
     endogenous y;
     exogenous  l e k di1-di12 dt2-dt10;
     parms a0 0.94 al -0.14 ae 1.8 ak -0.9
     b1 0 b2 0 b3 0 b4 0 b5 0 b6 0 b7 0 b8 0 b9 0 b10 0 b11 0
     b12 0 c2 0 c3 0 c4 0 c5 0 c6 0 c7 0 c8 0 c9 0 c10 0;
     y=a0+al*l+ae*e+ak*k
         +(b1*di1+b2*di2+b3*di3+b4*di4+b5*di5+b6*di6
         +b7*di7+b8*di8+b9*di9+b10*di10+b11*di11+b12*di12)*
         (1*dt1+c2*dt2+c3*dt3+c4*dt4+c5*dt5+c6*dt6+c7*dt7
         +c8*dt8+c9*dt9+c10*dt10);
     title '***** lee/schmidt parameter estimates *****';

My R code is as follows:
##############
library(plm)
dt <- read.table("dt.dta", sep = "\t", header= T)
dt$id <- factor(dt$id)
dt$yr <- factor(dt$yr)
fit.model <- I(log(y)) ~ I(log(l)) + I(log(e)) + yr * id
re.fit.gls <- pggls(fit.model, data = dt)
#################

I've got the following error message:
##### Error message ###############
Error in dimnames(x) <- dn :
  length of 'dimnames' [2] not equal to array extent
#### End of Error message############

I would like to figure out three things.
1. How can I restrict coefficient in model? As you can see in SAS  
code, coefficient of dt1 is restricted to 1.
2. If it is possible to restrict coefficients, it is possible to  
restrict coefficients of factors? If so, how?

Thanks in advance.

Best,