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From |
Veit Böckers <[email protected]> |

To |
[email protected] |

Subject |
st: Simulating Heteroscedasticity and correcting it |

Date |
Wed, 06 Jun 2012 12:33:55 +0200 |

Hello, I really hope you can help me out on this. I want to simulate heteroscedasticity and then correct under the two regimes a) known heteroscedasticity factor b) unknown heteroscedasticity factor (i.e. white-robust). My question concerns the correction of heteroscedasticity if the factor causing the heteroscedasticity, Omega, is known. Omega is defined as: Var(Residual)=sigma^2*Omega ; Omega= diag[(lambda_1)^2; (lambda_2)^2; (lambda_3)^2… (lambda_t)^2] If I recall correctly, my regression can be corrected like this : y/lambda = constant+ beta* x/lambda + residual/lambda. However, I seem to have made a mistake that I cannot find. Here is my do-file: set obs 1000 gen x1 = 2 * invnorm(uniform()) gen x2 = 4 * invnorm(uniform()) *** Generate Residual gen e = 2*invnorm(uniform()) sum e replace e = e-r(mean) *Generate Heteroscedasticity with factor “s” influencing my residual “e” gen s = exp(0.4*x1) gen e_het= s*e *Generate true y under heteroscedasticity gen y_het=10 +3*x1 + 2*x2 +e_het * Estimation under total disregard of heteroscedasticity reg y_het x1 x2 *** Estimation under the “known heteroscedasticity factor” regime gen known_y=y/s gen known_x1=x1/s gen known_x2=x2/s reg known_y known_x1 known_x2 --- Why do I not get close to the true relationship of y and x1/x2? Thank you very much in advance for your answers, Veit |

**Follow-Ups**:**Re: st: Simulating Heteroscedasticity and correcting it***From:*Tirthankar Chakravarty <[email protected]>

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