Dear all,
xtabond2 L(0/3)*lnGDP L(0/0)*lnDALY lnLE lnHALE lnINCI lnDEATH lnFERT lnMMR L(0/0)*lnMYS lnEYS yr*, gmm(lnLE lnDALY lnHALE, lag(2 .) collapse) gmm(lnDEATH lnINCI L.lnGDP lnMYS lnEYS, lag(1 .) collapse) iv(L(0/12)*lnSMOPREV L(0/12)*lnTRFAT L(0/12)*lnMMR yr*, eq(level)) iv(L(0/13)*lnSMOPREV L(0/13)*lnTRFAT L(0/13)*lnMMR, eq(diff)) twostep robust small orthogonal
.
I am new to Stata and I am confused about cycles.
Arellano-Bond test for AR(1) in first differences: z = -7.87 Pr > z < 0.05
Arellano-Bond test for AR(2) in first differences: z = -0.68 Pr > z >= 0.05
Hansen test of overid. restrictions: chi2(216) = 319.00 Prob > chi2 I need the xtabond value that satisfies the conditions 0.1 : 0.3.
For this, I need to put the following code into a loop L (1 -> 24) and write the code in a way that will give the output that meets the above conditions, how can I do it?
iv(L(0/12)*lnSMOPREV L(0/12)*lnTRFAT L(0/12)*lnMMR yr*, eq(level)) iv(L(0/13)
xtabond2 L(0/3)*lnGDP L(0/0)*lnDALY lnLE lnHALE lnINCI lnDEATH lnFERT lnMMR L(0/0)*lnMYS lnEYS yr*, gmm(lnLE lnDALY lnHALE, lag(2 .) collapse) gmm(lnDEATH lnINCI L.lnGDP lnMYS lnEYS, lag(1 .) collapse) iv(L(0/12)*lnSMOPREV L(0/12)*lnTRFAT L(0/12)*lnMMR yr*, eq(level)) iv(L(0/13)*lnSMOPREV L(0/13)*lnTRFAT L(0/13)*lnMMR, eq(diff)) twostep robust small orthogonal
Dynamic panel-data estimation, two-step system GMM
------------------------------------------------------------------------------
Group variable: CrossID Number of obs = 7018
Time variable : Years Number of groups = 319
Number of instruments = 250 Obs per group: min = 22
F(33, 318) = 1.41e+09 avg = 22.00
Prob > F = 0.000 max = 22
------------------------------------------------------------------------------
| Corrected
lnGDP | Coefficient std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
lnGDP |
L1. | 1.347017 .0197859 68.08 0.000 1.30809 1.385945
L2. | -.2354743 .0284106 -8.29 0.000 -.2913708 -.1795779
L3. | -.1224467 .0130395 -9.39 0.000 -.1481013 -.0967921
|
lnDALY |
--. | -.0380735 .0306168 -1.24 0.215 -.0983106 .0221635
L1. | .0376609 .0287099 1.31 0.191 -.0188245 .0941462
|
lnDEATH | -.0000725 .0002255 -0.32 0.748 -.0005162 .0003713
lnINCI | -.0003889 .0014688 -0.26 0.791 -.0032787 .0025009
lnPREV | .0008673 .0030126 0.29 0.774 -.00506 .0067945
lnHALE | -.0266481 .0288268 -0.92 0.356 -.0833634 .0300672
lnFERT | -.0052581 .0017629 -2.98 0.003 -.0087266 -.0017896
lnMYS | .0114667 .0028589 4.01 0.000 .005842 .0170913
lnEYS | .0078119 .0026697 2.93 0.004 .0025593 .0130645
yr_4 | .0063233 .0017276 3.66 0.000 .0029243 .0097222
yr_5 | .0128136 .0013974 9.17 0.000 .0100643 .0155628
yr_6 | .0199789 .0014529 13.75 0.000 .0171203 .0228374
yr_7 | -.0090997 .0010594 -8.59 0.000 -.011184 -.0070154
yr_8 | .0010859 .001203 0.90 0.367 -.0012809 .0034528
yr_9 | .0027304 .0011911 2.29 0.023 .0003869 .0050738
yr_10 | .020091 .0013386 15.01 0.000 .0174574 .0227245
yr_11 | .0063348 .0013794 4.59 0.000 .0036208 .0090488
yr_12 | .0143739 .0009711 14.80 0.000 .0124634 .0162845
yr_13 | .0104529 .0011043 9.47 0.000 .0082802 .0126256
yr_14 | -.0182252 .0012798 -14.24 0.000 -.0207433 -.0157072
yr_15 | -.0500418 .0011233 -44.55 0.000 -.0522518 -.0478319
yr_16 | .0294793 .0013268 22.22 0.000 .026869 .0320897
yr_17 | .0067008 .0021873 3.06 0.002 .0023974 .0110042
yr_18 | -.0121422 .0011354 -10.69 0.000 -.0143759 -.0099084
yr_19 | .0011706 .0008797 1.33 0.184 -.0005602 .0029015
yr_20 | .0097036 .0008876 10.93 0.000 .0079573 .0114499
yr_21 | .0139568 .001893 7.37 0.000 .0102324 .0176812
yr_22 | .0012744 .0011808 1.08 0.281 -.0010489 .0035976
yr_23 | .0109761 .0007277 15.08 0.000 .0095443 .0124078
yr_24 | .0057573 .000671 8.58 0.000 .0044372 .0070774
_cons | .1839954 .1159094 1.59 0.113 -.0440509 .4120417
------------------------------------------------------------------------------
Instruments for orthogonal deviations equation
Standard
FOD.(lnDEATH lnINCI lnHALE lnFERT lnEYS lnMYS yr_1 yr_2 yr_3 yr_4 yr_5
yr_6 yr_7 yr_8 yr_9 yr_10 yr_11 yr_12 yr_13 yr_14 yr_15 yr_16 yr_17 yr_18
yr_19 yr_20 yr_21 yr_22 yr_23 yr_24 yr_25)
GMM-type (missing=0, separate instruments for each period unless collapsed)
L(1/24).(L.lnDALY L.lnPREV L.lnGDP lnDEATH lnINCI lnHALE lnFERT lnEYS
lnMYS) collapsed
Instruments for levels equation
Standard
lnDEATH lnINCI lnHALE lnFERT lnEYS lnMYS yr_1 yr_2 yr_3 yr_4 yr_5 yr_6
yr_7 yr_8 yr_9 yr_10 yr_11 yr_12 yr_13 yr_14 yr_15 yr_16 yr_17 yr_18 yr_19
yr_20 yr_21 yr_22 yr_23 yr_24 yr_25
_cons
GMM-type (missing=0, separate instruments for each period unless collapsed)
D.(L.lnDALY L.lnPREV L.lnGDP lnDEATH lnINCI lnHALE lnFERT lnEYS lnMYS)
collapsed
------------------------------------------------------------------------------
Arellano-Bond test for AR(1) in first differences: z = -7.87 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = -0.68 Pr > z = 0.497
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(216) =2111.53 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(216) = 319.00 Prob > chi2 = 0.000
(Robust, but weakened by many instruments.)
------------------------------------------------------------------------------
Group variable: CrossID Number of obs = 7018
Time variable : Years Number of groups = 319
Number of instruments = 250 Obs per group: min = 22
F(33, 318) = 1.41e+09 avg = 22.00
Prob > F = 0.000 max = 22
------------------------------------------------------------------------------
| Corrected
lnGDP | Coefficient std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
lnGDP |
L1. | 1.347017 .0197859 68.08 0.000 1.30809 1.385945
L2. | -.2354743 .0284106 -8.29 0.000 -.2913708 -.1795779
L3. | -.1224467 .0130395 -9.39 0.000 -.1481013 -.0967921
|
lnDALY |
--. | -.0380735 .0306168 -1.24 0.215 -.0983106 .0221635
L1. | .0376609 .0287099 1.31 0.191 -.0188245 .0941462
|
lnDEATH | -.0000725 .0002255 -0.32 0.748 -.0005162 .0003713
lnINCI | -.0003889 .0014688 -0.26 0.791 -.0032787 .0025009
lnPREV | .0008673 .0030126 0.29 0.774 -.00506 .0067945
lnHALE | -.0266481 .0288268 -0.92 0.356 -.0833634 .0300672
lnFERT | -.0052581 .0017629 -2.98 0.003 -.0087266 -.0017896
lnMYS | .0114667 .0028589 4.01 0.000 .005842 .0170913
lnEYS | .0078119 .0026697 2.93 0.004 .0025593 .0130645
yr_4 | .0063233 .0017276 3.66 0.000 .0029243 .0097222
yr_5 | .0128136 .0013974 9.17 0.000 .0100643 .0155628
yr_6 | .0199789 .0014529 13.75 0.000 .0171203 .0228374
yr_7 | -.0090997 .0010594 -8.59 0.000 -.011184 -.0070154
yr_8 | .0010859 .001203 0.90 0.367 -.0012809 .0034528
yr_9 | .0027304 .0011911 2.29 0.023 .0003869 .0050738
yr_10 | .020091 .0013386 15.01 0.000 .0174574 .0227245
yr_11 | .0063348 .0013794 4.59 0.000 .0036208 .0090488
yr_12 | .0143739 .0009711 14.80 0.000 .0124634 .0162845
yr_13 | .0104529 .0011043 9.47 0.000 .0082802 .0126256
yr_14 | -.0182252 .0012798 -14.24 0.000 -.0207433 -.0157072
yr_15 | -.0500418 .0011233 -44.55 0.000 -.0522518 -.0478319
yr_16 | .0294793 .0013268 22.22 0.000 .026869 .0320897
yr_17 | .0067008 .0021873 3.06 0.002 .0023974 .0110042
yr_18 | -.0121422 .0011354 -10.69 0.000 -.0143759 -.0099084
yr_19 | .0011706 .0008797 1.33 0.184 -.0005602 .0029015
yr_20 | .0097036 .0008876 10.93 0.000 .0079573 .0114499
yr_21 | .0139568 .001893 7.37 0.000 .0102324 .0176812
yr_22 | .0012744 .0011808 1.08 0.281 -.0010489 .0035976
yr_23 | .0109761 .0007277 15.08 0.000 .0095443 .0124078
yr_24 | .0057573 .000671 8.58 0.000 .0044372 .0070774
_cons | .1839954 .1159094 1.59 0.113 -.0440509 .4120417
------------------------------------------------------------------------------
Instruments for orthogonal deviations equation
Standard
FOD.(lnDEATH lnINCI lnHALE lnFERT lnEYS lnMYS yr_1 yr_2 yr_3 yr_4 yr_5
yr_6 yr_7 yr_8 yr_9 yr_10 yr_11 yr_12 yr_13 yr_14 yr_15 yr_16 yr_17 yr_18
yr_19 yr_20 yr_21 yr_22 yr_23 yr_24 yr_25)
GMM-type (missing=0, separate instruments for each period unless collapsed)
L(1/24).(L.lnDALY L.lnPREV L.lnGDP lnDEATH lnINCI lnHALE lnFERT lnEYS
lnMYS) collapsed
Instruments for levels equation
Standard
lnDEATH lnINCI lnHALE lnFERT lnEYS lnMYS yr_1 yr_2 yr_3 yr_4 yr_5 yr_6
yr_7 yr_8 yr_9 yr_10 yr_11 yr_12 yr_13 yr_14 yr_15 yr_16 yr_17 yr_18 yr_19
yr_20 yr_21 yr_22 yr_23 yr_24 yr_25
_cons
GMM-type (missing=0, separate instruments for each period unless collapsed)
D.(L.lnDALY L.lnPREV L.lnGDP lnDEATH lnINCI lnHALE lnFERT lnEYS lnMYS)
collapsed
------------------------------------------------------------------------------
Arellano-Bond test for AR(1) in first differences: z = -7.87 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = -0.68 Pr > z = 0.497
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(216) =2111.53 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(216) = 319.00 Prob > chi2 = 0.000
(Robust, but weakened by many instruments.)
I am new to Stata and I am confused about cycles.
Arellano-Bond test for AR(1) in first differences: z = -7.87 Pr > z < 0.05
Arellano-Bond test for AR(2) in first differences: z = -0.68 Pr > z >= 0.05
Hansen test of overid. restrictions: chi2(216) = 319.00 Prob > chi2 I need the xtabond value that satisfies the conditions 0.1 : 0.3.
For this, I need to put the following code into a loop L (1 -> 24) and write the code in a way that will give the output that meets the above conditions, how can I do it?
iv(L(0/12)*lnSMOPREV L(0/12)*lnTRFAT L(0/12)*lnMMR yr*, eq(level)) iv(L(0/13)
