st: Nonlinear regression command

[Rick Kamphuis <r.kamphuis@tilburguniversity.edu>]

Dear Statalist,

I have a formula, but I don't know how to replicate it in Stata, because of
problems with the command.

The formula I want to put in is from the Nguyen and faff 2010 paper: Are
firms hedging or speculating? The relationship between financial
derivatives and firm risk.

The formula looks like this:

Total Riskit = Dsi [a0 + a1 Extentit + a2 Levit +a3 Sizeit + a4 DYit + a5
MTBVit + a6 Liqit + a7 CRit + a8 Exeshit + a9 Exeopit] + DLi [a10 + a11
Extentit + a12 Levit +a13 Sizeit + a14 DYit + a15 MTBVit + a16 Liqit + a17
CRit + a18 Exeshit + a19 Exeopit] +sigmait

Where a is alpha and Ds and DL are dummies. Extent is the most important
independent variable and all other variables are control variables. Behind
every variable it is paste behind it because of the paneldata format.

This formula is to test for a nonlinear relationship between total risk and
the Extent (derivatives outstanding divided by size). The first dummy
variable (Ds) is set equal to unity if the extent of derivative is 20% or
less and zero otherwise. Similarly, DL is set equal to unity if the extent
of derivative usage is 20% or more and zero otherwise. The threshold level
of 20% is chosen as it represent the average extent of derivative usage
demonstrated by firms in portfolio 6 (where maximum risk reduction is
achieved).

So the coefficients of primary interest in this equation are a1 and a11.
Consistent with the results obtained from the section 'portfolio analysis'
it is expected that moderate users (with an extent of derivative usage of
less than 20%) will experience a reduction in risk and hence a negative
sign is predicted for a1. For a11 it is the other way around.
My question is: what is the command in stata to run this regression from
above.

I have thought about to cut the groups and do this regression two times
with the moderate users and excessive users. However, I think this is not
the meaning of this test.

Hopefully someone can help me.

Thanks,

Rick Kamphuis
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