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Re: st: regress
From
Yuval Arbel <[email protected]>
To
statalist <[email protected]>
Subject
Re: st: regress
Date
Tue, 27 Aug 2013 09:49:25 -0700
As an Economist, I have to say this analysis looks flawed to me. The
reason is that both inputs and output are endogenous variables in
Economic models. I advise Mohammed to do some reading both in
theoretical economic textbooks (e.g., Hal Varian - Microeconomic
Analysis) and econometric textbook. What Mohammed probably needs is a
simultaneous-equation model
On Tue, Aug 27, 2013 at 10:23 AM, Richard Williams
<[email protected]> wrote:
> This seems to be more of a substantive question for economics than it does a
> statistics or Stata question. But if I thought the sign for a coefficient
> seemed odd, I would (a) make sure all my coding is ok, and (b) check the
> bivariate correlations. If the bivariate correlation was positive and the
> regression coefficient was negative, I would start thinking about some sort
> of suppressor effect. Maybe greater amounts of labor indicate lower levels
> of efficiency, at least once other variables are taken into account. But do
> some reading in economics or get the opinion of someone in the field.
>
>
> At 10:32 AM 8/27/2013, Rezgar Mohammed wrote:
>>
>> Hello,
>> I am a beginner in Econ. I would like to test the effect of some
>> factors on the production of specific output using the Cobb-Douglass
>> production function. I would like to know if you have any concerns
>> about the results.
>> Y represents output, x1 labor, x2 fertilizer, x3 land, x4 seed and x5
>> is capital. I wonder why the x1 coefficient is negative for example.
>>
>>
>> reg lny lnx1 lnx2 lnx3 lnx4 lnx5
>>
>> Source | SS df MS Number of obs =
>> 160
>> -------------+------------------------------ F( 5, 154)
>> =22942.46
>> Model | 1.13880167 5 .227760334 Prob > F =
>> 0.0000
>> Residual | .001528829 154 9.9275e-06 R-squared =
>> 0.9987
>> -------------+------------------------------ Adj R-squared =
>> 0.9986
>> Total | 1.1403305 159 .00717189 Root MSE =
>> .00315
>>
>>
>> ------------------------------------------------------------------------------
>> lny | Coef. Std. Err. t P>|t| [95% Conf.
>> Interval]
>>
>> -------------+----------------------------------------------------------------
>> lnx1 | -.0398971 .0008289 -48.13 0.000 -.0415346
>> -.0382596
>> lnx2 | 1.063405 .0033848 314.17 0.000 1.056719
>> 1.070092
>> lnx3 | -.0008994 .0005395 -1.67 0.098 -.0019652
>> .0001664
>> lnx4 | .0023421 .0024396 0.96 0.339 -.0024772
>> .0071615
>> lnx5 | .0025708 .000884 2.91 0.004 .0008245
>> .0043171
>> _cons | -.3304083 .0228141 -14.48 0.000 -.3754774
>> -.2853393
>>
>> ------------------------------------------------------------------------------
>>
>> I tested for heteroskedasticity and auto-correlation but nothing changes.
>>
>>
>> Thank you.
>>
>>
>> *
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>> * http://www.ats.ucla.edu/stat/stata/
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> HOME: (574)289-5227
> EMAIL: [email protected]
> WWW: http://www.nd.edu/~rwilliam
>
>
> *
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--
Dr. Yuval Arbel
School of Business
Carmel Academic Center
4 Shaar Palmer Street,
Haifa 33031, Israel
e-mail1: [email protected]
e-mail2: [email protected]
You can access my latest paper on SSRN at: http://ssrn.com/abstract=2263398
You can access previous papers on SSRN at: http://ssrn.com/author=1313670
*
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