Multiple regression analysis, econometrics, and statistics

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Homework Help Overview

The discussion revolves around multiple regression analysis within the context of econometrics and statistics. The original poster expresses confusion regarding the implications of model specifications and the properties of estimators in the presence of unobserved error terms.

Discussion Character

  • Exploratory, Conceptual clarification, Problem interpretation

Approaches and Questions Raised

  • Participants are attempting to understand the conditional expectations and variances in a regression context. There are inquiries about the consequences of incorrect model specifications on bias and variance of parameter estimates, as well as the validity of standard errors. Some participants are also questioning the initial steps in deriving expected values.

Discussion Status

The discussion is ongoing, with participants seeking clarification on specific parts of the problem. Some have begun to explore the implications of their assumptions, while others are looking for guidance on how to approach the questions posed in the original post.

Contextual Notes

The original poster has expressed a lack of understanding and is seeking help without wanting direct answers. There is an emphasis on the need for foundational understanding of the concepts involved in regression analysis.

jasper90
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I am sooo lost in this class, please help.

1. Let the true (population) model be y = B0+B1x1+B2x2+u where u is an unobserved error term with u (conditional) x1, x2 and N(0, sigma^2). Hence, u is normally distributed with mean 0 and variance sigma^2 (i.e., E[u (conditional) x1, x2] = 0 and V ar(u (conditional) x1, x2) = sigma^2) conditional on the observed sample. Also, assume that Cov(x1, x2) = sigma(x1x2) does not equal 0.
a) Find y hat = E[y (conditional) x1, x2]
b) Find Var(y (conditional) x1, x2)
c) Assume that the econometrician (falsely) believes that y = B0 + B1x1 + v is the true model and
uses OLS in order to estimate this model. What are the consequences of this in terms of bias and variance
(homoskedasticity) of parameter estimates. Are the standard errors from this regression valid? If not why?
d) Assume that the econometrician (falsely) believes that y = B0 + B1x1 + B2x2 + B3x3 + v is the true
model and uses OLS in order to estimate this model. What are the consequences of this in terms of bias and
variance (homoskedasticity) of parameter estimates. Are the standard errors from this regression valid? If
not why?Please help.
 
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can anyone help? or does anyone have the link to a similar problem?
 
can someone help me out? i don't need the answer straight up, just need help even getting this started

is this right for a)?

yhat = E[y (conditional) x1, x2] = E[ B0+B1x1+B2x2+u (conditional) x1, x2] = B0+B1x1+B2x2
 
Last edited:
can someone help me with C and D? I am not rly sure what to do
 

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