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Error in derivation of variance of $\beta_1$ in SLR [duplicate]

I'm trying to derive the variance of the slope parameter for a simple linear regression in the following way, however I'm running into an issue I don't know how to resolve. Define $y_i=\beta_0+\beta_1\...
aort01's user avatar
  • 181
0 votes
0 answers
30 views

How to find the variance of an independent variable across the big number of linear regression equations?

Question I have a big number of linear regression equations with known dependent variables and coefficients, in a form of: T = Aa + Bb + Cc + Dd where ...
astef's user avatar
  • 121
3 votes
1 answer
101 views

Ideal Settings for Longitudinal Models?

The way I see it, logically speaking - Longitudinal Data (e.g. medical patients being measured repeatedly over a period of time) can have one of two forms: Case 1: All patients are measured exactly &...
stats_noob's user avatar
1 vote
1 answer
45 views

Where plus 1 came from in variance estimation [duplicate]

While $$ \mathrm{E}(\tilde{\mathrm{y}})=\alpha+\beta \tilde{\mathrm{x}} $$ Subject is Regression Analysis and this formula is from the "Features of Estimation ". and y is a neutral variable. ...
Joseph_Wesleyan's user avatar
4 votes
0 answers
1k views

What is the probability distribution and variance of the OLS estimate $s^2$ of the error variance $\sigma^2$ in linear regression?

Consider the standard linear regression model $$ y = X \beta + \varepsilon, $$ where the error $\varepsilon$ has fixed variance $\sigma^2$. We can make an unbiased estimate of the error variance in a ...
Bertus101's user avatar
  • 805
0 votes
2 answers
134 views

How are $n$ and $Var(\varepsilon)$ affecting to Variance of Estimation of Slope Parameter $\beta_1$ in Simple Linear Regression

Once I have derived the variance of $\hat{\beta_1}$ as: $\text{Var}(\hat{\beta_1})= \frac{\sigma^2}{\sum(x_i-\overline{x})^2}$ I would like to know how are affecting to this formula: the size of ...
E. Williams's user avatar
5 votes
1 answer
862 views

Interpretation of conditional variance of estimator of intercept in linear regression

$Y_i=a+bX_i+e_i$. $Y_i$ and $X_i$ are scalar r.v. We have, $$ V(\hat b|X)=\frac{\sigma^2}{n\left(\bar{X^2}-\left[\bar{X}\right]^2\right)} $$ and, $$ V(\hat a|X)=\frac{\sigma^2 \bar{X^2}}{n\left(\bar{X^...
ztyh's user avatar
  • 359
1 vote
0 answers
11 views

Variance of parameter estimators in terms of $\ n$ observations in a linear time series model

Let $\ X_t = b_1 + b_2.t + e_t$ be a linear model, where $\mathbb{E}(e_t)$ = 0, $\ var(e_t)$ = $\sigma_e^2$, and $\ cov(e_i,e_j)$ = 0 for all $\ i \neq j$. I have derived the equations for the ...
Hugo's user avatar
  • 706
3 votes
1 answer
921 views

MLE of regression coefficients with non-constant variance

In the simplest case of the statistical view of linear regression, we have that $$ y = f(\mathbf{x};\mathbf{w}) + \nu, \text{ where }\nu \sim \mathcal{N}(0,\sigma^2) $$ where $\mathbf{x}$ is an ...
Orest Xherija's user avatar
2 votes
1 answer
81 views

Variance of an estimator?

I've estimated a parameter $\theta$ of a linear model as $$\hat\theta = \frac{2 \sum x_i^2 Y_i}{\sum x_i^4}$$ Where $Y_i$ is the response variable. I was wondering how does one find the variance ...
ketchup's user avatar
  • 135
4 votes
1 answer
1k views

Sampling variance of regression intercept when there is no regressor

Suppose we have a model $y=\beta_0+u$, where $E(u)=0$ and $Var(u)=\sigma^2$. I get the unbiased estimator $\hat\beta_0$ is just $\bar y$. But how can I get the variance of $\hat\beta_0$? Is it correct ...
Jacky's user avatar
  • 93
3 votes
2 answers
10k views

Why does the parameter variance change when control variables are added to a regression model?

If I add a control variable to my regression, this changes the variances of the parameter estimates. Why is this the case? Is this because SSE(=explained sum of squares) increases and therefore the ...
Peter's user avatar
  • 81
2 votes
1 answer
2k views

When would you want to reduce variance?

In a sampling-estimation context, low variance of the estimate is a goal. Several things I've read suggest (though I can't quite connect the dots) that lowering variance in the data will improve the ...
J Kelly's user avatar
  • 517
3 votes
1 answer
880 views

Help computing asymptotic variance of a weird first difference estimator in a fixed effects model

I'm working on an econometrics problem set, and I'm having some major problems computing asymptotic variance for this estimator. I'm considering a fixed-effects model $$ Y_{it} = \beta_1 X_{it} + \...
crf's user avatar
  • 319