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From |
"easycalcs" <[email protected]> |

To |
[email protected] |

Subject |
Re: st: random coefficient models |

Date |
Mon, 20 Oct 2003 22:24:04 -0000 |

There's no need at the estimation stage to know the variance of e(i) or n(i): Substititute for b(i) in the y equation y = b0+Bx(i)+v(i) where v(i)=e(i)+x(i)n(i) The new equation has a heteroskedastic error Var[v(i)]= Var[e(i)]+x(i)^2Var[(n(i)] = Var[e(i)]{1+kx(i)^2} where k= Var[e(i)]/Var[n(i)] If e(i) and n(i) are iid ~ normally, a loglikelihood formulation can be set up. If the weights are computed as w(i)=(1+kx(i))^1/2 the weighted least squares is y(i)/w(i) on 1/w(i) and x(i)/w(i). A concentrated loglikelihood may be established (with unknown paramter k) where the residual sum of (weighted) least is formulated in terms of the unknown parameter k. This is then maximised wrt k! Does anyone have the formulation/Stata specification proc for such a concentrated loglikelihood function? I'm not a Stata coder! Thanks. GM,Reading(aka easycalcs) --- In [email protected], "Stephen P. Jenkins" <stephenj@e...> wrote: > On Mon, 20 Oct 2003 12:54:33 -0400 Steven Devaney > <DevaneySP@n...> wrote: > > > Hello again > > > > Off-list I was asked to clarify what I meant. > > > > What I am interested in is whether anyone knows about or has written an MLE procedure for estimating B in the set-up? > > > > y(i) = b0 + b1(i) + e(i) > > > > where > > > > b1(i) = B + n(i) > > > > I was hoping to use Hildreth and Houck, but cannot constrain xtrchh so that t = 1. > > If t = 1 (single cross-section), can you identify the variance of the > b1(i), or equivalently the variance of the n(i) ? > > > Stephen > ---------------------- > Professor Stephen P. Jenkins <stephenj@e...> > Institute for Social and Economic Research (ISER) > University of Essex, Colchester, CO4 3SQ, UK > Tel: +44 (0)1206 873374. Fax: +44 (0)1206 873151. > http://www.iser.essex.ac.uk > > * > * 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/ * * 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: random coefficient models***From:*"easycalcs" <[email protected]>

**Re: st: random coefficient models***From:*"easycalcs" <[email protected]>

**Re: st: random coefficient models***From:*"easycalcs" <[email protected]>

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