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Questions tagged [variance]

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6 votes
1 answer

Measurement Error - Multivariate Case

I have a linear regression model, with usual assumptions holding; $E[xu] = 0$ and rank condition. $y_i = \alpha_0 + \alpha_1x_{1i} + \alpha_2x_{2i} + u_i$ I observe $\bar{x}_{2i}$, where: $\bar{x}...
Wooldridge's user avatar
3 votes
1 answer

Sample weights in Stata: fweight vs. pweight

I'm working with IPUMS ACS and Census data in Stata. I'm interested in learning about income distributions and variability for specific subpopulations defined by education level, occupation, race and ...
user135550's user avatar
2 votes
1 answer

Variance of Quantile Regression

I have been looking at quantile regression (since it is a much better method when trying to quantify welfare effects), and I am struggling with the following, standard model: $\textbf{Model:}$ $y=x'\...
DornerA's user avatar
  • 1,568
2 votes
1 answer

Independent variables that don't vary much but are essential for the theoretical framework, what to do?

I'm working on finding out the impact of Covid.19 on commuting so income and distance will be relevant variables to include. However, these variables dont change from period to period, so it's ...
Shushue's user avatar
  • 37
1 vote
1 answer

Comparing degree of dispersion without calculating variance

There are two (price) distributions of the same class, but they differ in parameter values. One distribution has a smaller upper bound and a greater lower bound, so intuitively we know it has a ...
Adam's user avatar
  • 81
1 vote
1 answer

Derivation of autocovariances Lewis (2021) RES

I am studying this paper, and I don't understand the derivation of the covariances at the bottom of page 3090. Basically I have two shocks: $\varepsilon_{1t}$ has constant volatility $E[\varepsilon_{...
Giorgetto's user avatar
  • 223
1 vote
0 answers

What is the proper way to derive risk definitions from utility functions?

In typical mean-variance analysis, the risk-adjusted relative value of an individual asset takes the general form $\frac{\mu}{\sigma^2}$ with further weighting and normalization depending on the ...
Machinus's user avatar
1 vote
0 answers

Variance of OLS Error Variance Estimator

Consider a model $Y=X\beta+e$ and define the OLS error variance estimator as $\hat{\sigma^2}=1/n\sum_{i=1}^n \hat{e}_i^2$, assuming that $ E[e_i^2]=\sigma^2 $ More precisely I want to derive the ...
Paul Huang's user avatar
1 vote
0 answers

Clustering Degrees of Freedom Correction

In a regression model estimated with $n$ observations, $$y_i = \beta_0 +\beta_1 x_{1i}+...+\beta_k x_{ki} +u_i$$ the baseline degrees of freedom adjustment when calculating standard errors is to ...
Michael Gmeiner's user avatar
1 vote
0 answers

WLS or Feasible GLS?

For a question like this, would I use WLS or Feasible GLS? I am leaning towards WLS but my lecture slides tell me GLS is used when there is more than one variable that drives the residual variance.
theshadowers's user avatar
0 votes
1 answer

Simultaneous Causality and Variance within a supply and demand model

Given two single-variable regression equations, one for Demand and one for Supply, both with error terms and a constant. How does one solve for equilibrium quantity, price? Obviously you can set ...
baronwellingtoniii's user avatar
0 votes
0 answers

Do market volatility and optimal trade confirmation strength correlate?

In this video, it is suggested that in high volatility markets, trading algorithms which wait for more confirmation to buy perform better than trading algorithms which buy more quickly, while in low ...
user10478's user avatar
  • 423
0 votes
2 answers

Arch Model and $\sigma$

In my problem set about ARCH models I'm given that $\epsilon^2_{t}=\alpha\epsilon^2_{t-1}+v_{t}$ But then I'm asked to calculate $E(\sigma^2_{t+n}|I_{t-1})$. So is the same to calculate $E(\epsilon^2_{...
GregorSilvei's user avatar
0 votes
0 answers

variance of error term(econometrics)

I don't understand that the pointed part(with a red circle) is a negative sign. I expect it should be a positive sign since the whole parenthesis was squared. I don't know where I got wrong.
user30426's user avatar
0 votes
0 answers

Covariance between regression coefficient and residual

Given regression equation Y=Xβ + ε which satisfies all classical assumptions including those of homoscadasticity Estimated regression equation using OLS is the following - Y=Xb + e Where, b is ...
Elina Gilbert's user avatar
0 votes
1 answer

Ttest and heteroscedasticity problem in no intercept model

I was running a t test over two regression betas with the assumption of equal variance. I know that if the condition of homoscedasticity do not hold then there are chances to have type 2 error but ...
Rahul Kumar's user avatar
-2 votes
2 answers

Why can we replace dependent variable y with the residuals e?

I don't understand why we can replace y with e: Mainly, why can we simply replace y with e, given that y is defined as: Thanks ...
ReRed's user avatar
  • 101