Good morning, I hope all Texas users are keeping safe.
I'm exploiting a rotating panel with 6115 observations and 2 time periods to inquiry about the households propensity for financial planning. The dependent variable is "financial planning (having_fin_plan)" and the core independent variable is "financial literacy (Know_01)". To address the reverse causality problem, measurement errors and correlation between financial literacy and the errors I regress a two-stage least squares model. I instrument financial literacy with four instrumental variables which match the endogeneity test, over-identification test and weak correlation test. The problem in the estimated model is that financial literacy (Know_01) has a negative coefficient which seems counterintuitive. Indeed, I would expect that financial literacy was upward or downward estimated compared to the pooled OLS, in line with the household finance literature. Why is it negative? Below I'll show you the code and output, what I'm missing?

Code:
ivreg having_fin_plan male edu_univ property_01 rent_to_buy age employee selfemployment retired married_01 single_01 ///
family_comp high_financial_wealth income_1 income_2 income_3 income_4 savers investors budget_always_respected Bank_mortgage_for_house Bank_mortgage_for_goods ///
Debt_vs_Relatives_for_house Debt_vs_Relatives_for_goods trust_fin_01 risk_av01 ansia01 ovc_dummy ///
(know_01 = fin_lit_parents_very_high procrastination01 score_mism self_efficacy01 ), first
First-stage regressions
Source SS df MS Number of obs = 6,115
F(30, 6084) = 110.94
Model 296.247241 30 9.87490803 Prob > F = 0.0000
Residual 541.5296 6,084 .08900881 R-squared = 0.3536
Adj R-squared = 0.3504
Total 837.776841 6,114 .13702598 Root MSE = .29834
know_01 Coef. Std. Err. t P>t [95% Conf. Interval]
male .0168844 .0116729 1.45 0.148 -.0059986 .0397674
edu_univ .085349 .0101787 8.39 0.000 .0653951 .1053028
property_01 .030976 .0099083 3.13 0.002 .0115523 .0503998
rent_to_buy -.1683492 .0283214 -5.94 0.000 -.2238691 -.1128293
age .0285246 .0043348 6.58 0.000 .0200268 .0370224
employee -.0053213 .0150374 -0.35 0.723 -.0348 .0241574
selfemployment .0301084 .0171975 1.75 0.080 -.0036047 .0638215
retired -.0394019 .0172869 -2.28 0.023 -.0732904 -.0055135
married_01 -.0226717 .0109923 -2.06 0.039 -.0442206 -.0011229
single_01 .0184531 .0152224 1.21 0.225 -.0113881 .0482943
family_comp -.0204504 .0036722 -5.57 0.000 -.0276492 -.0132516
high_financial_wealth .1340889 .0100631 13.32 0.000 .1143618 .1538161
income_1 -.1652771 .0277103 -5.96 0.000 -.2195991 -.1109552
income_2 -.0440917 .0262445 -1.68 0.093 -.0955402 .0073569
income_3 .0313992 .0279559 1.12 0.261 -.0234042 .0862026
savers .0275331 .0100178 2.75 0.006 .0078947 .0471715
investors .0425231 .0100509 4.23 0.000 .0228197 .0622265
budget_always_respected .0587958 .0093423 6.29 0.000 .0404815 .07711
Bank_mortgage_for_house .0716105 .0095376 7.51 0.000 .0529135 .0903076
Bank_mortgage_for_goods .0975432 .0094648 10.31 0.000 .0789889 .1160975
Debt_vs_Relatives_for_house .0218174 .0188575 1.16 0.247 -.01515 .0587848
Debt_vs_Relatives_for_goods -.0508886 .0195532 -2.60 0.009 -.0892199 -.0125574
trust_fin_01 .0453005 .0079837 5.67 0.000 .0296496 .0609515
risk_av01 .0267872 .0091672 2.92 0.003 .0088163 .0447581
ansia01 -.2892181 .027524 -10.51 0.000 -.3431748 -.2352614
ovc_dummy -.0176948 .0082522 -2.14 0.032 -.033872 -.0015176
fin_lit_parents_very_high .0240546 .0344159 0.70 0.485 -.0434127 .0915219
procrastination01 -.213733 .024521 -8.72 0.000 -.2618029 -.1656631
score_mism -.1105298 .0036258 -30.48 0.000 -.1176376 -.1034219
self_efficacy01 -.0569813 .0252711 -2.25 0.024 -.1065216 -.007441
_cons .7031922 .0428844 16.40 0.000 .6191237 .7872608
Instrumental variables (2SLS) regression
Source SS df MS Number of obs = 6,115
F(27, 6087) = 44.65
Model 196.196325 27 7.26653054 Prob > F = 0.0000
Residual 1252.30834 6,087 .2057349 R-squared = 0.1354
Adj R-squared = 0.1316
Total 1448.50466 6,114 .236916039 Root MSE = .45358
having_fin_plan Coef. Std. Err. t P>t [95% Conf. Interval]
know_01 -.2017086 .0470621 -4.29 0.000 -.2939669 -.1094503
male .0006796 .0177038 0.04 0.969 -.034026 .0353853
edu_univ .055142 .0159639 3.45 0.001 .0238471 .0864369
property_01 -.0130917 .0151052 -0.87 0.386 -.0427034 .0165199
rent_to_buy .1597795 .0441939 3.62 0.000 .0731438 .2464152
age .0157596 .0067115 2.35 0.019 .0026027 .0289165
employee -.0115554 .0228601 -0.51 0.613 -.0563693 .0332584
selfemployment .0129597 .0261764 0.50 0.621 -.0383554 .0642748
retired -.0349907 .0263005 -1.33 0.183 -.086549 .0165675
married_01 .0014361 .0167017 0.09 0.931 -.0313052 .0341773
single_01 .0000588 .0231749 0.00 0.998 -.0453722 .0454898
family_comp .000029 .0056854 0.01 0.996 -.0111164 .0111744
high_financial_wealth .1271248 .0167759 7.58 0.000 .0942381 .1600116
income_1 -.0687145 .0426131 -1.61 0.107 -.1522512 .0148222
income_2 -.0039936 .0398652 -0.10 0.920 -.0821435 .0741564
income_3 .043217 .0425109 1.02 0.309 -.0401195 .1265534
savers .1254683 .0151701 8.27 0.000 .0957295 .1552071
investors .2052635 .0153481 13.37 0.000 .1751758 .2353513
budget_always_respected .1422106 .0142898 9.95 0.000 .1141976 .1702237
Bank_mortgage_for_house .0640574 .0149921 4.27 0.000 .0346676 .0934471
Bank_mortgage_for_goods .0983141 .0152916 6.43 0.000 .0683371 .128291
Debt_vs_Relatives_for_house .1743292 .0286238 6.09 0.000 .1182165 .230442
Debt_vs_Relatives_for_goods .1688118 .0297898 5.67 0.000 .1104132 .2272104
trust_fin_01 .0642439 .012246 5.25 0.000 .0402375 .0882504
risk_av01 -.0773862 .0139455 -5.55 0.000 -.1047243 -.0500481
ansia01 -.1329287 .0401689 -3.31 0.001 -.211674 -.0541835
ovc_dummy .0893044 .0125974 7.09 0.000 .064609 .1139998
_cons .2623593 .0632222 4.15 0.000 .1384214 .3862972