* Clean environment
clear all
macro drop _all
set more off
version 12
* Install packages: SPMAT, XSMLE, SPWMATRIX
*net install st0292, from (http://www.stata-journal.com/software/sj13-2)
*net install xsmle, from (http://fmwww.bc.edu/RePEc/bocode/x)
*net install spwmatrix, from (http://fmwww.bc.edu/RePEc/bocode/s)
* Generate row-standardized W matrix from .dta file as spwmatrix (required for the xsmle package)
use "https://github.com/quarcs-lab/data-open/raw/master/cigar/Wct_bin.dta", replace
spmat dta Wst m1-m46, norm(row) replace
* Panel data set up
use "https://github.com/quarcs-lab/data-open/raw/master/cigar/baltagi_cigar.dta", clear
sort year state
xtset state year
xtsum
Panel variable: state (strongly balanced)
Time variable: year, 0 to 29
Delta: 1 unit
Variable | Mean Std. dev. Min Max | Observations
-----------------+--------------------------------------------+----------------
state overall | 23.5 13.28073 1 46 | N = 1380
between | 13.42262 1 46 | n = 46
within | 0 23.5 23.5 | T = 30
| |
year overall | 14.5 8.658579 0 29 | N = 1380
between | 0 14.5 14.5 | n = 46
within | 8.658579 0 29 | T = 30
| |
logc overall | 4.793396 .2245991 3.977811 5.696758 | N = 1380
between | .1867313 4.210951 5.445617 | n = 46
within | .1277085 4.165548 5.446414 | T = 30
| |
logp overall | -.1064185 .1517772 -.6098096 .3639895 | N = 1380
between | .0728611 -.3304814 .0186238 | n = 46
within | .1335636 -.431509 .3478483 | T = 30
| |
logpn overall | -.1944676 .1511349 -.6098096 .2408056 | N = 1380
between | .0780512 -.3343323 -.0283751 | n = 46
within | .1299149 -.4814573 .223349 | T = 30
| |
logy overall | 4.545251 .2099475 3.766334 5.116979 | N = 1380
between | .1482028 4.194623 4.852767 | n = 46
within | .1502524 4.10143 4.919302 | T = 30
| |
pop overall | 4537.113 4828.836 319 30703.3 | N = 1380
between | 4806.843 414.8433 23149.27 | n = 46
within | 835.3623 -1056.16 12091.14 | T = 30
| |
pop16 overall | 3366.616 3641.847 215.2 22920 | N = 1380
between | 3599.646 298.9867 17339.16 | n = 46
within | 760.3231 -1900.547 8947.453 | T = 30
reg logc logp logy
estimate store pool
Source | SS df MS Number of obs = 1,380
-------------+---------------------------------- F(2, 1377) = 325.34
Model | 22.3226886 2 11.1613443 Prob > F = 0.0000
Residual | 47.2406342 1,377 .034306924 R-squared = 0.3209
-------------+---------------------------------- Adj R-squared = 0.3199
Total | 69.5633228 1,379 .050444759 Root MSE = .18522
------------------------------------------------------------------------------
logc | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
logp | -.8590232 .0341394 -25.16 0.000 -.925994 -.7920525
logy | .267733 .0246803 10.85 0.000 .2193179 .3161481
_cons | 3.485067 .1133264 30.75 0.000 3.262756 3.707378
------------------------------------------------------------------------------
xtreg logc logp logy, fe
estimate store rfe
Fixed-effects (within) regression Number of obs = 1380
Group variable: state Number of groups = 46
R-sq: Within = 0.5446 Obs per group: min = 30
Between = 0.1255 avg = 30.0
Overall = 0.2579 max = 30
F(2,1332) = 796.45
corr(u_i, Xb) = 0.0394 Prob > F = 0.0000
------------------------------------------------------------------------------
logc | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
logp | -.7022931 .0183743 -38.22 0.000 -.7383389 -.6662473
logy | -.0105558 .0163335 -0.65 0.518 -.042598 .0214863
_cons | 4.766638 .0748331 63.70 0.000 4.619835 4.913442
-------------+----------------------------------------------------------------
sigma_u | .17521962
sigma_e | .08768915
rho | .79971016 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(45, 1332) = 106.92 Prob > F = 0.0000
reg logc logp logy i.year
estimate store tfe
Source | SS df MS Number of obs = 1,380
-------------+---------------------------------- F(31, 1348) = 34.22
Model | 30.634167 31 .988198935 Prob > F = 0.0000
Residual | 38.9291559 1,348 .028879196 R-squared = 0.4404
-------------+---------------------------------- Adj R-squared = 0.4275
Total | 69.5633228 1,379 .050444759 Root MSE = .16994
------------------------------------------------------------------------------
logc | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
logp | -1.205073 .0537684 -22.41 0.000 -1.310552 -1.099594
logy | .5653635 .0306256 18.46 0.000 .5052846 .6254425
|
year |
1 | -.0368768 .0354671 -1.04 0.299 -.1064535 .0326999
2 | -.0634675 .0355731 -1.78 0.075 -.1332521 .0063171
3 | -.0604443 .0356918 -1.69 0.091 -.1304618 .0095732
4 | -.0749865 .0357795 -2.10 0.036 -.145176 -.0047969
5 | -.0715308 .035932 -1.99 0.047 -.1420196 -.001042
6 | -.1134109 .0359722 -3.15 0.002 -.1839785 -.0428432
7 | -.1099368 .0361216 -3.04 0.002 -.1807974 -.0390761
8 | -.0874159 .036296 -2.41 0.016 -.1586187 -.0162132
9 | -.076202 .0365951 -2.08 0.038 -.1479915 -.0044125
10 | -.1576615 .0370772 -4.25 0.000 -.2303968 -.0849261
11 | -.2044241 .0371111 -5.51 0.000 -.2772258 -.1316223
12 | -.2121127 .0372077 -5.70 0.000 -.2851039 -.1391215
13 | -.180509 .0372304 -4.85 0.000 -.2535447 -.1074732
14 | -.23904 .0377844 -6.33 0.000 -.3131627 -.1649174
15 | -.2202074 .0378659 -5.82 0.000 -.2944899 -.145925
16 | -.3077263 .0384621 -8.00 0.000 -.3831784 -.2322741
17 | -.3670241 .0391172 -9.38 0.000 -.4437612 -.290287
18 | -.4215176 .0400197 -10.53 0.000 -.5000252 -.34301
19 | -.3811895 .0391436 -9.74 0.000 -.4579784 -.3044005
20 | -.2891464 .037761 -7.66 0.000 -.363223 -.2150697
21 | -.2518812 .0376071 -6.70 0.000 -.3256561 -.1781063
22 | -.246525 .0377181 -6.54 0.000 -.3205175 -.1725325
23 | -.2283626 .0380327 -6.00 0.000 -.3029723 -.1537529
24 | -.2319815 .0382428 -6.07 0.000 -.3070035 -.1569596
25 | -.2397264 .0386953 -6.20 0.000 -.3156358 -.1638169
26 | -.2408173 .0390885 -6.16 0.000 -.3174982 -.1641363
27 | -.2413188 .0396915 -6.08 0.000 -.3191826 -.163455
28 | -.2408803 .0397528 -6.06 0.000 -.3188643 -.1628963
29 | -.1583213 .0416749 -3.80 0.000 -.2400761 -.0765665
|
_cons | 2.287257 .1329677 17.20 0.000 2.026411 2.548103
------------------------------------------------------------------------------
xtreg logc logp logy i.year, fe
estimate store rtfe
Fixed-effects (within) regression Number of obs = 1380
Group variable: state Number of groups = 46
R-sq: Within = 0.6768 Obs per group: min = 30
Between = 0.3285 avg = 30.0
Overall = 0.4382 max = 30
F(31,1303) = 88.01
corr(u_i, Xb) = 0.0677 Prob > F = 0.0000
------------------------------------------------------------------------------
logc | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
logp | -1.034884 .0415191 -24.93 0.000 -1.116336 -.9534329
logy | .5285428 .0465828 11.35 0.000 .4371573 .6199282
|
year |
1 | -.0379187 .0157558 -2.41 0.016 -.0688282 -.0070092
2 | -.0609798 .0163344 -3.73 0.000 -.0930245 -.0289351
3 | -.0605349 .0170196 -3.56 0.000 -.0939238 -.0271461
4 | -.073178 .0174744 -4.19 0.000 -.107459 -.0388971
5 | -.0729554 .0182603 -4.00 0.000 -.1087781 -.0371327
6 | -.1107195 .0184484 -6.00 0.000 -.1469114 -.0745276
7 | -.11179 .0191899 -5.83 0.000 -.1494365 -.0741434
8 | -.0901122 .0199969 -4.51 0.000 -.1293418 -.0508826
9 | -.0779732 .0213762 -3.65 0.000 -.1199087 -.0360378
10 | -.1486597 .0231365 -6.43 0.000 -.1940486 -.1032707
11 | -.1837469 .021804 -8.43 0.000 -.2265217 -.1409721
12 | -.1883635 .0216207 -8.71 0.000 -.2307787 -.1459483
13 | -.1590794 .0221877 -7.17 0.000 -.202607 -.1155518
14 | -.2104651 .0230353 -9.14 0.000 -.2556553 -.1652748
15 | -.1955921 .0242441 -8.07 0.000 -.2431537 -.1480304
16 | -.2724383 .0241055 -11.30 0.000 -.3197281 -.2251485
17 | -.3209252 .0232264 -13.82 0.000 -.3664905 -.2753599
18 | -.3674333 .0238134 -15.43 0.000 -.4141501 -.3207165
19 | -.3346344 .0231613 -14.45 0.000 -.380072 -.2891968
20 | -.261862 .0232407 -11.27 0.000 -.3074552 -.2162688
21 | -.237841 .0248155 -9.58 0.000 -.2865237 -.1891583
22 | -.2355434 .0255306 -9.23 0.000 -.2856289 -.1854578
23 | -.2240761 .0270513 -8.28 0.000 -.277145 -.1710073
24 | -.2315843 .0278496 -8.32 0.000 -.2862193 -.1769493
25 | -.2443289 .0293194 -8.33 0.000 -.3018473 -.1868105
26 | -.2513339 .0303136 -8.29 0.000 -.3108026 -.1918651
27 | -.2586898 .0316423 -8.18 0.000 -.3207652 -.1966144
28 | -.2613347 .0314627 -8.31 0.000 -.3230577 -.1996116
29 | -.193703 .0349695 -5.54 0.000 -.2623057 -.1251004
|
_cons | 2.463499 .1958312 12.58 0.000 2.07932 2.847678
-------------+----------------------------------------------------------------
sigma_u | .15385703
sigma_e | .07469348
rho | .80926815 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(45, 1303) = 126.10 Prob > F = 0.0000
estimates table pool rfe tfe rtfe, b(%7.2f) star(0.1 0.05 0.01) stf(%9.0f)
------------------------------------------------------------------
Variable | pool rfe tfe rtfe
-------------+----------------------------------------------------
logp | -0.86*** -0.70*** -1.21*** -1.03***
logy | 0.27*** -0.01 0.57*** 0.53***
|
year |
1 | -0.04 -0.04**
2 | -0.06* -0.06***
3 | -0.06* -0.06***
4 | -0.07** -0.07***
5 | -0.07** -0.07***
6 | -0.11*** -0.11***
7 | -0.11*** -0.11***
8 | -0.09** -0.09***
9 | -0.08** -0.08***
10 | -0.16*** -0.15***
11 | -0.20*** -0.18***
12 | -0.21*** -0.19***
13 | -0.18*** -0.16***
14 | -0.24*** -0.21***
15 | -0.22*** -0.20***
16 | -0.31*** -0.27***
17 | -0.37*** -0.32***
18 | -0.42*** -0.37***
19 | -0.38*** -0.33***
20 | -0.29*** -0.26***
21 | -0.25*** -0.24***
22 | -0.25*** -0.24***
23 | -0.23*** -0.22***
24 | -0.23*** -0.23***
25 | -0.24*** -0.24***
26 | -0.24*** -0.25***
27 | -0.24*** -0.26***
28 | -0.24*** -0.26***
29 | -0.16*** -0.19***
|
_cons | 3.49*** 4.77*** 2.29*** 2.46***
------------------------------------------------------------------
Legend: * p<.1; ** p<.05; *** p<.01
xsmle logc logp logy, fe type(both) wmat(Wst) mod(sdm) effects nsim(999) nolog
estimate store sdm1
Warning: All regressors will be spatially lagged
convergence not achieved
Computing marginal effects standard errors using MC simulation...
SDM with spatial and time fixed-effects Number of obs = 1380
Group variable: state Number of groups = 46
Time variable: year Panel length = 30
R-sq: within = 0.4591
between = 0.2912
overall = 0.3110
Mean of fixed-effects = 2.2026
Log-likelihood = 1691.2918
------------------------------------------------------------------------------
logc | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
Main |
logp | -1.002454 .0401168 -24.99 0.000 -1.081081 -.9238265
logy | .6006541 .0571792 10.50 0.000 .488585 .7127232
-------------+----------------------------------------------------------------
Wx |
logp | .0564066 .0828302 0.68 0.496 -.1059376 .2187508
logy | -.2949799 .0770509 -3.83 0.000 -.4459968 -.143963
-------------+----------------------------------------------------------------
Spatial |
rho | .229154 .0327665 6.99 0.000 .1649328 .2933752
-------------+----------------------------------------------------------------
Variance |
sigma2_e | .0049782 .0001906 26.12 0.000 .0046046 .0053518
-------------+----------------------------------------------------------------
LR_Direct |
logp | -1.014508 .0395526 -25.65 0.000 -1.09203 -.9369866
logy | .5904437 .0548733 10.76 0.000 .482894 .6979933
-------------+----------------------------------------------------------------
LR_Indirect |
logp | -.213878 .0824432 -2.59 0.009 -.3754637 -.0522922
logy | -.1954389 .0846827 -2.31 0.021 -.3614139 -.0294639
-------------+----------------------------------------------------------------
LR_Total |
logp | -1.228386 .0941994 -13.04 0.000 -1.413014 -1.043759
logy | .3950048 .0781855 5.05 0.000 .241764 .5482455
------------------------------------------------------------------------------
xsmle logc logp logy, fe type(both) leeyu wmat(Wst) mod(sdm) effects nsim(999) nolog
estimate store sdm2
Warning: All regressors will be spatially lagged
convergence not achieved
Computing marginal effects standard errors using MC simulation...
SDM with spatial and time fixed-effects Number of obs = 1380
Group variable: state Number of groups = 46
Time variable: year Panel length = 30
R-sq: within = 0.4591
between = 0.2912
overall = 0.3110
Mean of fixed-effects = 2.2026
Log-likelihood = 1691.2918
------------------------------------------------------------------------------
logc | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
Main |
logp | -1.002454 .0401168 -24.99 0.000 -1.081081 -.9238265
logy | .6006541 .0571792 10.50 0.000 .488585 .7127232
-------------+----------------------------------------------------------------
Wx |
logp | .0564066 .0828302 0.68 0.496 -.1059376 .2187508
logy | -.2949799 .0770509 -3.83 0.000 -.4459968 -.143963
-------------+----------------------------------------------------------------
Spatial |
rho | .229154 .0327665 6.99 0.000 .1649328 .2933752
-------------+----------------------------------------------------------------
Variance |
sigma2_e | .0049782 .0001906 26.12 0.000 .0046046 .0053518
-------------+----------------------------------------------------------------
LR_Direct |
logp | -1.014508 .0395526 -25.65 0.000 -1.09203 -.9369866
logy | .5904437 .0548733 10.76 0.000 .482894 .6979933
-------------+----------------------------------------------------------------
LR_Indirect |
logp | -.213878 .0824432 -2.59 0.009 -.3754637 -.0522922
logy | -.1954389 .0846827 -2.31 0.021 -.3614139 -.0294639
-------------+----------------------------------------------------------------
LR_Total |
logp | -1.228386 .0941994 -13.04 0.000 -1.413014 -1.043759
logy | .3950048 .0781855 5.05 0.000 .241764 .5482455
------------------------------------------------------------------------------
estimates table sdm1 sdm2, b(%7.3f) star(0.1 0.05 0.01) stf(%9.0f)
----------------------------------------
Variable | sdm1 sdm2
-------------+--------------------------
Main |
logp | -1.002*** -1.002***
logy | 0.601*** 0.601***
-------------+--------------------------
Wx |
logp | 0.056 0.056
logy | -0.295*** -0.295***
-------------+--------------------------
Spatial |
rho | 0.229*** 0.229***
-------------+--------------------------
Variance |
sigma2_e | 0.005*** 0.005***
-------------+--------------------------
LR_Direct |
logp | -1.015*** -1.015***
logy | 0.590*** 0.590***
-------------+--------------------------
LR_Indirect |
logp | -0.214*** -0.214***
logy | -0.195** -0.195**
-------------+--------------------------
LR_Total |
logp | -1.228*** -1.228***
logy | 0.395*** 0.395***
----------------------------------------
Legend: * p<.1; ** p<.05; *** p<.01
quietly xsmle logc logp logy, fe type(both) leeyu wmat(Wst) mod(sdm) effects nsim(999) nolog
* Wald test: Reduce to SAR? (NO if p < 0.05)
test ([Wx]logp = 0) ([Wx]logy = 0)
( 1) [Wx]logp = 0
( 2) [Wx]logy = 0
chi2( 2) = 16.06
Prob > chi2 = 0.0003
* Wald test: Reduce to SLX? (NO if p < 0.05)
test ([Spatial]rho = 0)
( 1) [Spatial]rho = 0
chi2( 1) = 48.91
Prob > chi2 = 0.0000
* Wald test: Reduce to SEM? (NO if p < 0.05)
testnl ([Wx]logp = -[Spatial]rho*[Main]logp) ([Wx]logy = -[Spatial]rho*[Main]logy)
(1) [Wx]logp = -[Spatial]rho*[Main]logp
(2) [Wx]logy = -[Spatial]rho*[Main]logy
chi2(2) = 8.62
Prob > chi2 = 0.0134
xsmle logc logp logy,fe type(both) wmat(Wst) mod(sdm) effects nsim(999) nolog
*estimate store sdm0
eststo SDM0
Warning: All regressors will be spatially lagged
convergence not achieved
Computing marginal effects standard errors using MC simulation...
SDM with spatial and time fixed-effects Number of obs = 1380
Group variable: state Number of groups = 46
Time variable: year Panel length = 30
R-sq: within = 0.4591
between = 0.2912
overall = 0.3110
Mean of fixed-effects = 2.2026
Log-likelihood = 1691.2918
------------------------------------------------------------------------------
logc | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
Main |
logp | -1.002454 .0401168 -24.99 0.000 -1.081081 -.9238265
logy | .6006541 .0571792 10.50 0.000 .488585 .7127232
-------------+----------------------------------------------------------------
Wx |
logp | .0564066 .0828302 0.68 0.496 -.1059376 .2187508
logy | -.2949799 .0770509 -3.83 0.000 -.4459968 -.143963
-------------+----------------------------------------------------------------
Spatial |
rho | .229154 .0327665 6.99 0.000 .1649328 .2933752
-------------+----------------------------------------------------------------
Variance |
sigma2_e | .0049782 .0001906 26.12 0.000 .0046046 .0053518
-------------+----------------------------------------------------------------
LR_Direct |
logp | -1.014508 .0395526 -25.65 0.000 -1.09203 -.9369866
logy | .5904437 .0548733 10.76 0.000 .482894 .6979933
-------------+----------------------------------------------------------------
LR_Indirect |
logp | -.213878 .0824432 -2.59 0.009 -.3754637 -.0522922
logy | -.1954389 .0846827 -2.31 0.021 -.3614139 -.0294639
-------------+----------------------------------------------------------------
LR_Total |
logp | -1.228386 .0941994 -13.04 0.000 -1.413014 -1.043759
logy | .3950048 .0781855 5.05 0.000 .241764 .5482455
------------------------------------------------------------------------------
xsmle logc logp logy, dlag(1) fe type(both) wmat(Wst) type(ind) mod(sdm) effects nsim(999) nolog
*estimate store dsdm1
eststo dySDM1
Warning: All regressors will be spatially lagged
convergence not achieved
Computing marginal effects standard errors using MC simulation...
Dynamic SDM with spatial and time fixed-effects Number of obs = 1334
Group variable: state Number of groups = 46
Time variable: year Panel length = 29
R-sq: within = 0.8860
between = 0.9885
overall = 0.9551
Mean of fixed-effects = 0.0107
Log-likelihood = 2272.9691
------------------------------------------------------------------------------
logc | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
Main |
logc |
L1. | .8663475 .0125261 69.16 0.000 .8417968 .8908981
|
logp | -.2645775 .0224803 -11.77 0.000 -.3086381 -.2205168
logy | .0993066 .0289526 3.43 0.001 .0425605 .1560527
-------------+----------------------------------------------------------------
Wx |
logp | .1571821 .0435758 3.61 0.000 .0717751 .2425892
logy | -.0195067 .0382102 -0.51 0.610 -.0943972 .0553839
-------------+----------------------------------------------------------------
Spatial |
rho | .0518087 .0204596 2.53 0.011 .0117087 .0919088
-------------+----------------------------------------------------------------
Variance |
sigma2_e | .0011861 .0000444 26.71 0.000 .0010991 .0012731
-------------+----------------------------------------------------------------
SR_Direct |
logp | -.2629964 .0217459 -12.09 0.000 -.3056175 -.2203753
logy | .1000495 .026752 3.74 0.000 .0476166 .1524824
-------------+----------------------------------------------------------------
SR_Indirect |
logp | .1483303 .0430288 3.45 0.001 .0639954 .2326653
logy | -.0146855 .0379474 -0.39 0.699 -.089061 .05969
-------------+----------------------------------------------------------------
SR_Total |
logp | -.1146661 .0471108 -2.43 0.015 -.2070015 -.0223306
logy | .085364 .0329065 2.59 0.009 .0208686 .1498595
-------------+----------------------------------------------------------------
LR_Direct |
logp | -1.939841 .1734313 -11.19 0.000 -2.27976 -1.599922
logy | .7739404 .1975708 3.92 0.000 .3867087 1.161172
-------------+----------------------------------------------------------------
LR_Indirect |
logp | .6017905 .4441151 1.36 0.175 -.2686592 1.47224
logy | .2704149 .4845123 0.56 0.577 -.6792118 1.220042
-------------+----------------------------------------------------------------
LR_Total |
logp | -1.33805 .5341109 -2.51 0.012 -2.384889 -.2912123
logy | 1.044355 .5126544 2.04 0.042 .0395712 2.049139
------------------------------------------------------------------------------
xsmle logc logp logy, dlag(2) fe type(both) wmat(Wst) type(ind) mod(sdm) effects nsim(999) nolog
*estimate store dsdm2
eststo dySDM2
Warning: All regressors will be spatially lagged
convergence not achieved
Computing marginal effects standard errors using MC simulation...
Dynamic SDM with spatial and time fixed-effects Number of obs = 1334
Group variable: state Number of groups = 46
Time variable: year Panel length = 29
R-sq: within = 0.5500
between = 0.3440
overall = 0.3794
Mean of fixed-effects = 1.9320
Log-likelihood = 1131.8326
------------------------------------------------------------------------------
logc | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
Main |
Wlogc |
L1. | .2657454 .057937 4.59 0.000 .1521909 .3792999
|
logp | -.9681121 .0412848 -23.45 0.000 -1.049029 -.8871955
logy | .5620682 .0580534 9.68 0.000 .4482857 .6758507
-------------+----------------------------------------------------------------
Wx |
logp | .1265543 .0878462 1.44 0.150 -.045621 .2987297
logy | -.3189209 .0784061 -4.07 0.000 -.4725941 -.1652478
-------------+----------------------------------------------------------------
Spatial |
rho | .0804046 .0469587 1.71 0.087 -.0116328 .172442
-------------+----------------------------------------------------------------
Variance |
sigma2_e | .0050358 .0001887 26.68 0.000 .0046659 .0054057
-------------+----------------------------------------------------------------
SR_Direct |
logp | -.967713 .0408697 -23.68 0.000 -1.047816 -.8876099
logy | .558341 .053602 10.42 0.000 .453283 .663399
-------------+----------------------------------------------------------------
SR_Indirect |
logp | .0475089 .0918987 0.52 0.605 -.1326092 .227627
logy | -.2903914 .0840545 -3.45 0.001 -.4551352 -.1256476
-------------+----------------------------------------------------------------
SR_Total |
logp | -.9202041 .0992352 -9.27 0.000 -1.114701 -.7257067
logy | .2679496 .0731491 3.66 0.000 .12458 .4113192
-------------+----------------------------------------------------------------
LR_Direct |
logp | -.9904018 .0428776 -23.10 0.000 -1.07444 -.9063633
logy | .5515737 .0519886 10.61 0.000 .4496779 .6534694
-------------+----------------------------------------------------------------
LR_Indirect |
logp | -.3063058 .130896 -2.34 0.019 -.5628573 -.0497544
logy | -.1736873 .1052254 -1.65 0.099 -.3799254 .0325508
-------------+----------------------------------------------------------------
LR_Total |
logp | -1.296708 .1491701 -8.69 0.000 -1.589076 -1.00434
logy | .3778864 .1056131 3.58 0.000 .1708884 .5848843
------------------------------------------------------------------------------
xsmle logc logp logy, dlag(3) fe type(both) wmat(Wst) type(ind) mod(sdm) effects nsim(999) nolog
*estimate store dsdm3
eststo dySDM3
Warning: All regressors will be spatially lagged
convergence not achieved
Computing marginal effects standard errors using MC simulation...
Dynamic SDM with spatial and time fixed-effects Number of obs = 1334
Group variable: state Number of groups = 46
Time variable: year Panel length = 29
R-sq: within = 0.8870
between = 0.9884
overall = 0.9553
Mean of fixed-effects = -0.0059
Log-likelihood = 2268.0526
------------------------------------------------------------------------------
logc | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
Main |
logc |
L1. | .8659549 .0125497 69.00 0.000 .841358 .8905519
|
Wlogc |
L1. | .0247315 .0366499 0.67 0.500 -.047101 .096564
|
logp | -.2638341 .0225083 -11.72 0.000 -.3079495 -.2197186
logy | .0995425 .0289669 3.44 0.001 .0427684 .1563166
-------------+----------------------------------------------------------------
Wx |
logp | .1595878 .0436443 3.66 0.000 .0740466 .2451289
logy | -.0216391 .0383273 -0.56 0.572 -.0967592 .053481
-------------+----------------------------------------------------------------
Spatial |
rho | .0327756 .035945 0.91 0.362 -.0376753 .1032266
-------------+----------------------------------------------------------------
Variance |
sigma2_e | .001187 .0000445 26.69 0.000 .0010999 .0012742
-------------+----------------------------------------------------------------
SR_Direct |
logp | -.2622572 .021317 -12.30 0.000 -.3040377 -.2204767
logy | .0987061 .0287654 3.43 0.001 .0423269 .1550853
-------------+----------------------------------------------------------------
SR_Indirect |
logp | .1564995 .0435085 3.60 0.000 .0712245 .2417745
logy | -.0180026 .0380821 -0.47 0.636 -.0926422 .0566369
-------------+----------------------------------------------------------------
SR_Total |
logp | -.1057577 .0466974 -2.26 0.024 -.1972829 -.0142325
logy | .0807035 .0334237 2.41 0.016 .0151942 .1462128
-------------+----------------------------------------------------------------
LR_Direct |
logp | -1.919964 1.069856 -1.79 0.073 -4.016844 .1769151
logy | .7679913 .8310962 0.92 0.355 -.8609274 2.39691
-------------+----------------------------------------------------------------
LR_Indirect |
logp | -.1599878 17.56339 -0.01 0.993 -34.5836 34.26363
logy | .4232639 17.6333 0.02 0.981 -34.13738 34.9839
-------------+----------------------------------------------------------------
LR_Total |
logp | -2.079952 18.03038 -0.12 0.908 -37.41884 33.25894
logy | 1.191255 18.0063 0.07 0.947 -34.10044 36.48295
------------------------------------------------------------------------------
*estimates table sdm0 dsdm1 dsdm2 dsdm3, b(%7.2f) star(0.1 0.05 0.01)
esttab SDM0 dySDM1 dySDM2 dySDM3, mtitle("SDM" "dySDM1" "dySDM2" "dySDM3")
----------------------------------------------------------------------------
(1) (2) (3) (4)
SDM dySDM1 dySDM2 dySDM3
----------------------------------------------------------------------------
Main
logp -1.002*** -0.265*** -0.968*** -0.264***
(-24.99) (-11.77) (-23.45) (-11.72)
logy 0.601*** 0.0993*** 0.562*** 0.0995***
(10.50) (3.43) (9.68) (3.44)
L.logc 0.866*** 0.866***
(69.16) (69.00)
L.Wlogc 0.266*** 0.0247
(4.59) (0.67)
----------------------------------------------------------------------------
Wx
logp 0.0564 0.157*** 0.127 0.160***
(0.68) (3.61) (1.44) (3.66)
logy -0.295*** -0.0195 -0.319*** -0.0216
(-3.83) (-0.51) (-4.07) (-0.56)
----------------------------------------------------------------------------
Spatial
rho 0.229*** 0.0518* 0.0804 0.0328
(6.99) (2.53) (1.71) (0.91)
----------------------------------------------------------------------------
Variance
sigma2_e 0.00498*** 0.00119*** 0.00504*** 0.00119***
(26.12) (26.71) (26.68) (26.69)
----------------------------------------------------------------------------
LR_Direct
logp -1.015*** -1.940*** -0.990*** -1.920
(-25.65) (-11.19) (-23.10) (-1.79)
logy 0.590*** 0.774*** 0.552*** 0.768
(10.76) (3.92) (10.61) (0.92)
----------------------------------------------------------------------------
LR_Indirect
logp -0.214** 0.602 -0.306* -0.160
(-2.59) (1.36) (-2.34) (-0.01)
logy -0.195* 0.270 -0.174 0.423
(-2.31) (0.56) (-1.65) (0.02)
----------------------------------------------------------------------------
LR_Total
logp -1.228*** -1.338* -1.297*** -2.080
(-13.04) (-2.51) (-8.69) (-0.12)
logy 0.395*** 1.044* 0.378*** 1.191
(5.05) (2.04) (3.58) (0.07)
----------------------------------------------------------------------------
SR_Direct
logp -0.263*** -0.968*** -0.262***
(-12.09) (-23.68) (-12.30)
logy 0.100*** 0.558*** 0.0987***
(3.74) (10.42) (3.43)
----------------------------------------------------------------------------
SR_Indirect
logp 0.148*** 0.0475 0.156***
(3.45) (0.52) (3.60)
logy -0.0147 -0.290*** -0.0180
(-0.39) (-3.45) (-0.47)
----------------------------------------------------------------------------
SR_Total
logp -0.115* -0.920*** -0.106*
(-2.43) (-9.27) (-2.26)
logy 0.0854** 0.268*** 0.0807*
(2.59) (3.66) (2.41)
----------------------------------------------------------------------------
N 1380 1334 1334 1334
----------------------------------------------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001
%html
esttab SDM0 dySDM1 dySDM2 dySDM3, mtitle("SDM" "dySDM1" "dySDM2" "dySDM3") html