Timeline for Terminology: unconditional heteroskedasticity
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| Dec 9, 2020 at 8:11 | vote | accept | Richard Hardy | ||
| Dec 3, 2020 at 19:39 | comment | added | Alecos Papadopoulos | @CloseToc If we really cannot do anything about it, still, it is important to know it, because we should know that, for example, the estimator variance will be wrongly computed. In practice, in such instances researchers may attempt a latent- or proxy- variable model, linking the unavailable $m$ to some available data. | |
| Dec 3, 2020 at 19:19 | comment | added | CloseToC | It seems like the modelling-relevant instances of unconditional heteroscedasticity are really instances of conditional heteroscedasticity: There is some observable variable, with which which the error variance has a systematic relationship ($m$, or a proxy). I wonder whether anything is to be gained from entertaining the notion that error variances could vary across an index when there is no such variable. | |
| Dec 3, 2020 at 14:03 | history | edited | Alecos Papadopoulos | CC BY-SA 4.0 |
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| Dec 3, 2020 at 13:47 | history | edited | Alecos Papadopoulos | CC BY-SA 4.0 |
Added example responding to comments
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| Dec 3, 2020 at 10:17 | comment | added | Henry | and give an example of "unconditional heteroskedasticity" | |
| Dec 3, 2020 at 8:40 | comment | added | Richard Hardy | Could you outline briefly what you mean by structural reasoning? | |
| Dec 2, 2020 at 20:24 | history | edited | Alecos Papadopoulos | CC BY-SA 4.0 |
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| Dec 2, 2020 at 19:30 | comment | added | Alecos Papadopoulos | @whuber By structural reasoning. At least this is what we do in economics. | |
| Dec 2, 2020 at 19:26 | comment | added | whuber♦ | If we don't have variables on which the amount of scatter depends, how are we even to recognize heteroscedasticity? | |
| Dec 2, 2020 at 19:20 | history | answered | Alecos Papadopoulos | CC BY-SA 4.0 |