


Dear R helpers!,

I have a question on how to run a regression with many indices.
To give you a practical example,

let
 y_{itabp} be an dependent variable (representing   prices) indexed by 
i=country, t=time,  a=area, b=brand and p=package size.

In 
particular, we  collected prices on the product "cereals"  from  i=1...,I countries 
over a period of t=1,...,T_{i} months. For example, for Italy we  have 
price information over24 months whereas for Germany we  have  price 
information over 36 months.
For each country, we have price 
information  by area (a=1,...,A_{i}- for example, for Italy we  have 
price information for 5 areas whereas for Germany we  have  price 
information for 9  areas). 
For each area we have  information on prices by brand (b=1,...,4 )
Finally, for each brand prices are broken down by package size (p=1,2,3)

I want to run a semiparametric regression to see the effect of package size on   y_{itcabp}  
I display  a sample of my data


 
 
 
 
  Country
  Area
  brand
  packsize
  dates
  price
  Package_size
 
 
  AA
  A1
  b1
  ps1
  01/11/2008
  1.760342
  0.075
 
 
  AA
  A1
  b1
  ps1
  01/12/2008
  1.786739
  0.075
 
 
  AA
  A1
  b1
  ps2
  01/11/2008
  1.725466
  0.075
 
 
  AA
  A1
  b1
  ps2
  01/12/2008
  1.678327
  0.075
 
 
  AA
  A1
  b1
  ps3
  01/11/2008
  1.941369
  0.075
 
 
  AA
  A1
  b1
  ps3
  01/12/2008
  1.874848
  0.075
 
 
  AA
  A2
  b2
  ps1
  01/11/2008
  21.49573
  0.075
 
 
  AA
  A2
  b2
  ps1
  01/12/2008
  22.40766
  0.075
 
 
  AA
  A2
  b2
  ps2
  01/11/2008
  23.44514
  0.075
 
 
  AA
  A2
  b2
  ps2
  01/12/2008
  23.1251
  0.075
 
 
  AA
  A2
  b2
  ps3
  01/11/2008
  22.14254
  0.075
 
 
  AA
  A2
  b2
  ps3
  01/12/2008
  21.04197
  0.075
 
 
  BB
  A1
  b1
  ps1
  01/01/2009
  17.38787
  0.05
 
 
  BB
  A1
  b1
  ps1
  01/02/2009
  18.45013
  0.05
 
 
  BB
  A1
  b1
  ps2
  01/01/2009
  17.59772
  0.05
 
 
  BB
  A1
  b1
  ps2
  01/02/2009
  18.41634
  0.05
 
 
  BB
  A1
  b1
  ps3
  01/01/2009
  18.55188
  0.05
 
 
  BB
  A1
  b1
  ps3
  01/02/2009
  19.08645
  0.05
 

I also created the variables

 countryN that takes 1 for AA, 2 for BB etc,
AreaN  that takes 1  for A1, 2 for A2, etc,
brandN   that takes 1 for b1, 2 for b2 etc,
packsizeN that takes 1 for ps1, 2 for ps2 etc,
timeN that takes 1 for 01/11/2008 or 01/01/2009 and  2 for 01/12/2008 or 01/02/2009
I, then, run

data<- read.csv("cereals.csv")
rm(list=ls())
foo <- read.csv("cereals.csv")
attach(foo)
require(np)
model <- npreg(price~factor(Package_size)+factor(timeN)+factor(countryN)+factor(AreaN)+ordered(brandN)+ordered(packsizeN))
summary(model)
plot(model,common.scale=FALSE)


Do you think that these commands serve my goal (to estimate the effect of package size on   y_{itcabp})?

Any code provided is greatly appreciated.

Thank you very much in advance,

andrews


 		 	   		  
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