# Questions tagged [heteroskedasticity]

refers to non-constant variance of errors across different observations

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1answer
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### Heteroscedasticity and weighted least square estimator

"In presence of heteroscedasticity, OLS estimators are unbiased but inefficient" Showing the unbiased part is relatively easy. Some authors have explained the inefficiency with the help of new ...
1answer
30 views

### Annual Data and Heteroscredasticity (Engle's ARCH test)

GARCH models are often applied to financial time series (daily, weekly or monthly stock returns). What about lower frequency such as quarterly and annual time series? This could include macroeconomic ...
1answer
122 views

### possible Heteroskedasticity?

Based on the graph, would you say that there is some sort of heteroscedasticity in the data? Y-axis is residual squared and X-axis is predicted values of Y
3answers
75 views

### Heteroskedasticity assumption in fGLS into linear form?

I am following Chapter 8 ("Heteroskedasticity" p. 259) in the 6th edition of Woolridge Introductory Econometrics: A Modern Approach and I don't understand one piece of the transformation of our model. ...
1answer
7k views

### Testing for heteroskedasticity in panel data vs time series?

I watched this video on how to check for heteroskedasticity using Stata, and it helped me a lot. But the data example in the video was time series data. He used the Bruesh-Pagan test. ...
0answers
20 views

### Is this weighted least squares or just weighting the dependent variable

I am a little confused as to what the following line means. Do the authors mean they run a weighted least squares using the sample size as weights, or just weight the dependent variable using the ...
1answer
28 views

### Understanding General Least Squares

From what I understand, we have our OLS estimator in matrix form which is, $$\beta_{OLS} = (X'X)^{-1}X'Y$$ What we want to do is transform this, as the assumption that we have constant variance is ...
2answers
41 views