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Shawn Hemelstrand
Shawn Hemelstrand
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I'm interested in studying the effect of x$x$ on y$y$ using a fixed effects method. The residuals follow a heavy tail distribution, as the normal qQ-qQ plot suggests. For inference, I need a normal distribution of the residuals.

Which strategies can be applied to the model such that the residuals become more normally distributed? I thought about log-log transformations. This made the residuals indeed more normally distributed, but the heavy tails still persist.

I'm interested in studying the effect of x on y using a fixed effects method. The residuals follow a heavy tail distribution, as the normal q-q plot suggests. For inference, I need a normal distribution of the residuals.

Which strategies can be applied to the model such that the residuals become more normally distributed? I thought about log-log transformations. This made the residuals indeed more normally distributed but the heavy tails still persist.

I'm interested in studying the effect of $x$ on $y$ using a fixed effects method. The residuals follow a heavy tail distribution, as the normal Q-Q plot suggests. For inference, I need a normal distribution of the residuals.

Which strategies can be applied to the model such that the residuals become more normally distributed? I thought about log-log transformations. This made the residuals indeed more normally distributed, but the heavy tails still persist.

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TFT
TFT
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Correction for heavy-tailed distribution of residuals?

I'm interested in studying the effect of x on y using a fixed effects method. The residuals follow a heavy tail distribution, as the normal q-q plot suggests. For inference, I need a normal distribution of the residuals.

Which strategies can be applied to the model such that the residuals become more normally distributed? I thought about log-log transformations. This made the residuals indeed more normally distributed but the heavy tails still persist.