Dear Statalists
I am actually doing a IV regression with one single endogenous regressior (penetration_row) and two instrumental variables (real_exchange_final & tariff_rate_row). I am using the command ivreghdfe and get the following output:
For the Hansen-J statistic I get e value of 13.598 and a P-Value of 0.002. Is it therefore right, that my instruments are not valid and the coefficient of the endogenous regressor on the dependent variable may be biased?
Thanks for your help
Roman
I am actually doing a IV regression with one single endogenous regressior (penetration_row) and two instrumental variables (real_exchange_final & tariff_rate_row). I am using the command ivreghdfe and get the following output:
Code:
ivreghdfe share_zombiesBH2 (L3.penetration_row = L4.tariff_rate_row L4.real_exchange_final) L3.ln_at L3.age L3.F_E L3.tnic3hhi L3.dtfp4 L3.tangibility, first absorb(year sic) cluster(gvkey) First-stage regression of L3.penetration_row: Statistics robust to heteroskedasticity and clustering on gvkey Number of obs = 9497 Number of clusters (gvkey) = 1285 ------------------------------------------------------------------------------------- | Robust L3.penetration_row | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------------+---------------------------------------------------------------- tariff_rate_row | L4. | -.5737043 .3361944 -1.71 0.088 -1.232718 .085309 | real_exchange_final | L4. | .0243828 .004553 5.36 0.000 .0154579 .0333077 | ln_at | L3. | -.0003283 .000159 -2.06 0.039 -.00064 -.0000166 | age | L3. | .0000254 .0000657 0.39 0.699 -.0001034 .0001542 | F_E | L3. | .0006308 .0000899 7.02 0.000 .0004547 .000807 | tnic3hhi | L3. | -.001099 .0009947 -1.10 0.269 -.0030489 .0008508 | dtfp4 | L3. | .0265433 .0017163 15.47 0.000 .0231791 .0299075 | tangibility | L3. | -.0040824 .0022 -1.86 0.064 -.0083949 .0002301 ------------------------------------------------------------------------------------- F test of excluded instruments: F( 2, 1284) = 14.34 Prob > F = 0.0000 Sanderson-Windmeijer multivariate F test of excluded instruments: F( 2, 1284) = 14.34 Prob > F = 0.0000 Summary results for first-stage regressions ------------------------------------------- (Underid) (Weak id) Variable | F( 2, 1284) P-val | SW Chi-sq( 2) P-val | SW F( 2, 1284) L3.penetrati | 14.34 0.0000 | 28.84 0.0000 | 14.34 NB: first-stage test statistics cluster-robust Stock-Yogo weak ID F test critical values for single endogenous regressor: 10% maximal IV size 19.93 15% maximal IV size 11.59 20% maximal IV size 8.75 25% maximal IV size 7.25 Source: Stock-Yogo (2005). Reproduced by permission. NB: Critical values are for i.i.d. errors only. Underidentification test Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified) Ha: matrix has rank=K1 (identified) Kleibergen-Paap rk LM statistic Chi-sq(2)=161.09 P-val=0.0000 Weak identification test Ho: equation is weakly identified Cragg-Donald Wald F statistic 421.18 Kleibergen-Paap Wald rk F statistic 14.34 Stock-Yogo weak ID test critical values for K1=1 and L1=2: 10% maximal IV size 19.93 15% maximal IV size 11.59 20% maximal IV size 8.75 25% maximal IV size 7.25 Source: Stock-Yogo (2005). Reproduced by permission. NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors. Weak-instrument-robust inference Tests of joint significance of endogenous regressors B1 in main equation Ho: B1=0 and orthogonality conditions are valid Anderson-Rubin Wald test F(2,1284)= 3.70 P-val=0.0251 Anderson-Rubin Wald test Chi-sq(2)= 7.43 P-val=0.0244 Stock-Wright LM S statistic Chi-sq(2)= 59.52 P-val=0.0000 NB: Underidentification, weak identification and weak-identification-robust test statistics cluster-robust Number of clusters N_clust = 1285 Number of observations N = 9497 Number of regressors K = 7 Number of endogenous regressors K1 = 1 Number of instruments L = 8 Number of excluded instruments L1 = 2 IV (2SLS) estimation -------------------- Estimates efficient for homoskedasticity only Statistics robust to heteroskedasticity and clustering on gvkey Number of clusters (gvkey) = 1285 Number of obs = 9497 F( 7, 1284) = 20.97 Prob > F = 0.0000 Total (centered) SS = 4.652722306 Centered R2 = -0.0218 Total (uncentered) SS = 4.652722306 Uncentered R2 = -0.0218 Residual SS = 4.754029143 Root MSE = .02243 --------------------------------------------------------------------------------- | Robust share_zombies~2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] ----------------+---------------------------------------------------------------- penetration_row | L3. | .2754187 .0562641 4.90 0.000 .165039 .3857983 | ln_at | L3. | .000142 .0001487 0.95 0.340 -.0001498 .0004338 | age | L3. | -.0000765 .0000626 -1.22 0.222 -.0001994 .0000463 | F_E | L3. | -.0001973 .0001446 -1.36 0.173 -.000481 .0000863 | tnic3hhi | L3. | -.0025562 .0010006 -2.55 0.011 -.0045192 -.0005931 | dtfp4 | L3. | .0244666 .0030023 8.15 0.000 .0185765 .0303566 | tangibility | L3. | -.0002343 .0021431 -0.11 0.913 -.0044387 .00397 --------------------------------------------------------------------------------- Underidentification test (Kleibergen-Paap rk LM statistic): 161.088 Chi-sq(2) P-val = 0.0000 ------------------------------------------------------------------------------ Weak identification test (Cragg-Donald Wald F statistic): 421.176 (Kleibergen-Paap rk Wald F statistic): 14.342 Stock-Yogo weak ID test critical values: 10% maximal IV size 19.93 15% maximal IV size 11.59 20% maximal IV size 8.75 25% maximal IV size 7.25 Source: Stock-Yogo (2005). Reproduced by permission. NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors. ------------------------------------------------------------------------------ Hansen J statistic (overidentification test of all instruments): 13.598 Chi-sq(1) P-val = 0.0002 ------------------------------------------------------------------------------ Instrumented: L3.penetration_row Included instruments: L3.ln_at L3.age L3.F_E L3.tnic3hhi L3.dtfp4 L3.tangibility Excluded instruments: L4.tariff_rate_row L4.real_exchange_final Partialled-out: _cons nb: total SS, model F and R2s are after partialling-out; any small-sample adjustments include partialled-out variables in regressor count K ------------------------------------------------------------------------------ Absorbed degrees of freedom: -----------------------------------------------------+ Absorbed FE | Categories - Redundant = Num. Coefs | -------------+---------------------------------------| year | 19 0 19 | sic | 19 1 18 | -----------------------------------------------------+
Thanks for your help
Roman
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