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From |
"Nick Cox" <[email protected]> |

To |
"Dawit Lidia" <[email protected]>, <[email protected]>, <[email protected]>, <[email protected]> |

Subject |
RE: st: RE: test predicted values |

Date |
Sun, 16 Jan 2005 22:52:14 -0000 |

That clarifies what you have and want to do; thanks. It's your project and your call, but it seems to me that a unified model is not crazy as an alternative to what you are following here. Nick [email protected] > -----Original Message----- > From: Dawit Lidia [mailto:[email protected]] > Sent: 16 January 2005 22:40 > To: [email protected]; [email protected]; Nick Cox; > [email protected] > Subject: RE: st: RE: test predicted values > > > Thanks Nichols, Nick, and Mark. Nichols got my question > (E[Y|x1,x2,con=1] = > E[Y|x1,x2,con=0]). Y1 and Y2 are different. Let me tell you > the whole story > in short as follow. > > I am assessing the effect of soil conservation technology on > crop yields > (productivity) using plot level data. To do this I am > following Fuglie and > Bosch's (1995) and Khanna's (2001) work. Their work is > similar to Lee's > (1978). They were estimated separate regression for > technology adopters and > non-adopters. From the regressions they estimated fitted values at > representative values (mean) of some of the regressors and then they > compared the mean predicted values. They used endogenous switching > regression analysis. > > What I posted is exogenous switching regression model. In my > case as in the > above authors, I divided the sample into those plots that adopt soil > conservation technlogy and those that do not. In the > regressions below the > variable con== 1 indicates those who adopted the technology > and con == 0 > those that do not. The variable y1 and y2 also indicate > yields obtained from > adopters and non-adopter of soil conservation technology, > respectively. > > areg y1 x1 x2 if con ==1, absorb(hhno) cluster(hhno) > predict conhat if con ==1, xbd > > areg y2 x1 x2 if con ==0, absorb(hhno) cluster(hhno) > predict wconhat if con ==0, xbd > > Hope this will help. Thanks again for your help. > Dawit > > Fuglie, K. O., and Bosch, D. J. 1995. Economic and Environmental > Implications of Soil Nitrogen Testing: A > Switching-Regression Analysis. > American Journal of Agricultural Economics 77: 891- 900. > Khanna, M. 2001. Sequential adoption of site-specific > technologies and its > implication for nitrogen productivity: A double > selectivity model. American > Journal of Agricultural Economics 83(1): 35-51. > Lee, L.F. 1978. Unionism and wage rates: A simultaneous > equations model with > qualitative and limited dependent variables. > International Economic Review > 19(2):415-433. > > > > >From: "Nichols, Austin" <[email protected]> > >To: 'Mark Schaffer' <[email protected]>, > "'[email protected]'" > ><[email protected]>, "'[email protected]'" > <[email protected]> > >Subject: RE: st: RE: test predicted values > >Date: Sun, 16 Jan 2005 15:44:41 -0500 > > > >I think that Dawit Lidia wants to test that > >E[Y|x1,x2,con=1] = E[Y|x1,x2,con=0] > >where Y=(y1, y2) and it's unclear whether y1=y2 from the post. > > > >-----Original Message----- > >From: Nichols, Austin > >Sent: Sunday, January 16, 2005 3:37 PM > >To: '[email protected]' > >Cc: '[email protected]' > >Subject: RE: st: RE: test predicted values > > > > > >Are the dependent variables in the 2 models really different vars? > >If not, Nick has indicated the solution: > > > >. g double x1c1=x1*con > >. g double x2c1=x2*con > >. areg y x1 x2 con x1c1 x2c2, absorb(hhno) cluster(hhno) > >. test con x1c1 x2c2 > > > >will test for difference in predicted vals across the 2 models. > > > >-----Original Message----- > >From: Dawit Lidia [mailto:[email protected]] > >Sent: Sunday, January 16, 2005 3:09 PM > >To: [email protected] > >Subject: RE: st: RE: test predicted values > > > > > >Dear Nick Cox, > > > >Thanks you for your response. I think I have to refine my question as > >follow. Can I do the following test on predicted values > without adjusting > >the standard errors since observations are not independent > within group > >(hhno)? > > > >ttest conhat = wconhat unequal > > > >where conhat and wconhat are predicted below. > >areg y1 x1 x2 if con ==1, absorb(hhno) cluster(hhno) > >predict conhat if con ==1, xbd > > > >areg y2 x1 x2 if con ==0, absorb(hhno) cluster(hhno) > >predict wconhat if con ==0, xbd > > > >Hope this will be clear. Many thanks for your help. > >Dawit > > > > > > >From: "Nick Cox" <[email protected]> > > >Reply-To: [email protected] > > >To: <[email protected]> > > >Subject: st: RE: test predicted values > > >Date: Sun, 16 Jan 2005 16:35:28 -0000 > > > > > >It would seem more straightforward, > > >and more appropriate, to fit > > > > > >areg y1 x1 x2 con, absorb(hhno) cluster(hhno) > > > > > >which provides your test directly -- unless > > >I am missing some subtlety here. > > > > > >Nick > > >[email protected] > > > > > >Dawit Lidia > > > > > > > I am running the following types of regressions > > > > > > > > areg y1 x1 x2 if con ==1, absorb(hhno) cluster(hhno) > > > > predict conhat if con ==1, xbd > > > > > > > > areg y2 x1 x2 if con ==0, absorb(hhno) cluster(hhno) > > > > predict wconhat if con ==0, xbd > > > > > > > > y1 and y2 are dependent variables and xs are > independent variables. > > > > > > > > > > > > I want to test if there is mean difference between the two > > > > predicted values > > > > uisng simple 'ttest'. > > > > > > > > My question is, do I need to correct standard errors(se) of > > > > the 'ttest' > > > > since the observed ys are not independent. If the answer is > > > > yes, would you > > > > please suggest me how i can correct it or any other > > > > altenative test that can > > > > adjust se. > > > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: RE: test predicted values***From:*"Dawit Lidia" <[email protected]>

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