Hello,

I'm trying to regress the impact that fiscal rules might have on the Primary Balance of a Country. I have a panel data with 28 countries and 28 years. So t=28 and n=28. The problem is when i'm using the fixed effects regression for panel data i get the wrong coefficient comparing with all the previous literature.

When i asses the same regression on random effects i get a correct coefficient, however from the BP Lagrange result, random effects are not appropriate and i need robust std errors due to the existence of heterokedasticity...

I've been using the -xtreg, fe vce(r)- to regress this unbalanced dynamic panel data. I'm getting the same result for the IV-fe estimator... Is it a problem of the fixed effects model? Here's some example:

Fixed-effects (within) regression Number of obs = 552

Group variable: id Number of groups = 28

R-sq: Obs per group:

within = 0.5762 min = 12

between = 0.5118 avg = 19.7

overall = 0.5144 max = 23

F(7,27) = 128.73

corr(u_i, Xb) = -0.4775 Prob > F = 0.0000

(Std. Err. adjusted for 28 clusters in id)

Robust

PB Coef. Std. Err. t P>t [95% Conf. Interval]

PB1 .624859 .0553634 11.29 0.000 .5112626 .7384554

Debt1 .0388924 .0104554 3.72 0.001 .0174397 .0603451

Gap1 .0363654 .0568418 0.64 0.528 -.0802644 .1529951

EXPDEC .0863861 .0625988 1.38 0.179 -.0420561 .2148284

Election -.071106 .2191869 -0.32 0.748 -.5208403 .3786282

FSI -11.35462 2.135158 -5.32 0.000 -15.7356 -6.973639

Rules -.3425743 .136504 -2.51 0.018 -.6226573 -.0624912

_cons -3.107349 2.058504 -1.51 0.143 -7.331051 1.116353

sigma_u 1.5384986

sigma_e 1.9666157

rho .37965466 (fraction of variance due to u_i)

I'm trying to regress the impact that fiscal rules might have on the Primary Balance of a Country. I have a panel data with 28 countries and 28 years. So t=28 and n=28. The problem is when i'm using the fixed effects regression for panel data i get the wrong coefficient comparing with all the previous literature.

When i asses the same regression on random effects i get a correct coefficient, however from the BP Lagrange result, random effects are not appropriate and i need robust std errors due to the existence of heterokedasticity...

I've been using the -xtreg, fe vce(r)- to regress this unbalanced dynamic panel data. I'm getting the same result for the IV-fe estimator... Is it a problem of the fixed effects model? Here's some example:

Fixed-effects (within) regression Number of obs = 552

Group variable: id Number of groups = 28

R-sq: Obs per group:

within = 0.5762 min = 12

between = 0.5118 avg = 19.7

overall = 0.5144 max = 23

F(7,27) = 128.73

corr(u_i, Xb) = -0.4775 Prob > F = 0.0000

(Std. Err. adjusted for 28 clusters in id)

Robust

PB Coef. Std. Err. t P>t [95% Conf. Interval]

PB1 .624859 .0553634 11.29 0.000 .5112626 .7384554

Debt1 .0388924 .0104554 3.72 0.001 .0174397 .0603451

Gap1 .0363654 .0568418 0.64 0.528 -.0802644 .1529951

EXPDEC .0863861 .0625988 1.38 0.179 -.0420561 .2148284

Election -.071106 .2191869 -0.32 0.748 -.5208403 .3786282

FSI -11.35462 2.135158 -5.32 0.000 -15.7356 -6.973639

Rules -.3425743 .136504 -2.51 0.018 -.6226573 -.0624912

_cons -3.107349 2.058504 -1.51 0.143 -7.331051 1.116353

sigma_u 1.5384986

sigma_e 1.9666157

rho .37965466 (fraction of variance due to u_i)

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