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I have a panel data set as follows:

    Year  Industry   FDI   RW   TFP   IY   CY   GDP   LP   IR  ER   PS
    1998  AGR        xx    xx   xx    xx   xx   xx    xx
    1998  MAN        xx    xx   xx    xx   xx   xx    xx
    1998  NTR        xx    xx   xx    xx   xx   xx    xx
    1998  TRN        xx    xx   xx    xx   xx   xx    xx
    1999  AGR        xx    xx   xx    xx   xx   xx    xx
    1999  MAN        xx    xx   xx    xx   xx   xx    xx
    1999  NTR        xx    xx   xx    xx   xx   xx    xx
    1999  TRN        xx    xx   xx    xx   xx   xx    xx
     ...

I want to build a multivariate model that can explain the variation in FDI between the Industry groups using the variables RW, TFP, IY, CY, GDP, LP.

The variables, RW, TFP, IY, CY, GDP, LP are specific to the Industry. The variables IR, ER, PS are not specific to any industry but I would like to be able to incorporate them into the model if possible.

How would I go about doing this in R?

Restemayer
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  • What have you tried so far that didn't work? People here on SO often expect the OP to do some research and have at least some minimal attempt on the problem. – acylam Mar 04 '18 at 18:00
  • I've never worked with panel data such as this, so I'm more so trying to distinguish what type of analysis needs to be done (i.e. fixed effects, random effects, ANOVA, etc.). That being said, I haven't tried much other than a few YouTube videos that haven't helped me much – Restemayer Mar 04 '18 at 18:48
  • In this case, this question is more suitable for [Cross Validated](https://stats.stackexchange.com/) because it is more about what type of analysis to be done instead of _how_ to program a particular analysis. – acylam Mar 04 '18 at 21:18

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