Content
--------------------------------------------------------------------------------------------------------------------------------------------
name:
log: C:\doug work\Colin\JHR cluster paper\work Summer 2014\empirical example code\table3.log
log type: text
opened on: 6 Jul 2014, 15:47:00
. set more off ;
. cap log close t3out ;
. qui log using table3_out.csv , text replace name(t3out) ;
. qui log off t3out ;
. clear ;
. clear mata ;
. set seed 10101 ;
. set matsize 10000 ;
. run set_directory_macros ;
. run t3_data_setup ;
. run t3_ols ;
. run t3_ar1 ;
. run CR23_IK_CSS ;
cr2cr3() not found
. run t34_programs ;
. cap prog drop runme ;
. prog def runme ;
1. local bsreps = 999 ;
2. local beta_hypothesis = 0 ;
3. tempfile main_data ;
4. /* get the dataset ready for estimation */
> qui t3_setup , keylhs("lnwage_sy") sourcedata("${madedat}/CPS_panel") outdata(`main_data') ;
5. /* estimate "model 1" */
> /* the t3_ols code will partial out state and year fixed effects */
> t3_ols , bsreps(`bsreps') sourcedata(`main_data') lhs(lnwage_sy) rhs(policy) keyrhs(policy) ;
6. /* estimate "model 2" */
> /* the t3_ols code will partial out state and year fixed effects */
> t3_ols , bsreps(`bsreps') sourcedata(`main_data') lhs(lnwage_sy) rhs(policy) keyrhs(policy) yearonly ;
7. /* estimate "model 3" */
> /* the t3_ar1 code does not partial out any fixed effects, so need to directly pass these in as regressors */
> t3_ar1 , bsreps(`bsreps') sourcedata(`main_data') lhs(lnwage_sy) rhs(policy i.statefip i.year) keyrhs(policy) ;
8. end ;
. runme ;
Source | SS df MS Number of obs = 1836
-------------+------------------------------ F( 1, 1835) = 18.08
Model | .027835588 1 .027835588 Prob > F = 0.0000
Residual | 2.82495041 1835 .001539483 R-squared = 0.0098
-------------+------------------------------ Adj R-squared = 0.0092
Total | 2.852786 1836 .001553805 Root MSE = .03924
----------------------------------------------------------------------------------
lnwage_sy_devi~n | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0155778 .0036635 4.25 0.000 .0083928 .0227629
----------------------------------------------------------------------------------
Linear regression Number of obs = 1836
F( 1, 1835) = 18.20
Prob > F = 0.0000
R-squared = 0.0098
Root MSE = .03924
----------------------------------------------------------------------------------
| Robust
lnwage_sy_devi~n | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0155778 .0036513 4.27 0.000 .0084168 .0227389
----------------------------------------------------------------------------------
Linear regression Number of obs = 1836
F( 1, 50) = 1.73
Prob > F = 0.1947
R-squared = 0.0098
Root MSE = .03924
(Std. Err. adjusted for 51 clusters in statefip)
----------------------------------------------------------------------------------
| Robust
lnwage_sy_devi~n | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0155778 .0118516 1.31 0.195 -.0082269 .0393826
----------------------------------------------------------------------------------
Note: +/- means the corresponding matrix is added/subtracted
Calculating cov part for variables: statefip (+)
Number of obs = 1836
Num clusvars = 1
Num combinations = 1
G(statefip) = 51
----------------------------------------------------------------------------------
lnwage_sy_devi~n | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0155778 .0118516 1.31 0.189 -.007651 .0388066
----------------------------------------------------------------------------------
Note: +/- means the corresponding matrix is added/subtracted
Calculating cov part for variables: statefip (+)
Calculating cov part for variables: statefip year (-)
Calculating cov part for variables: year (+)
Number of obs = 1836
Num clusvars = 2
Num combinations = 3
G(statefip) = 51
G(year) = 36
----------------------------------------------------------------------------------
lnwage_sy_devi~n | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0155778 .0116717 1.33 0.182 -.0072982 .0384539
----------------------------------------------------------------------------------
(bootstrap: table3_np_boot)
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
t_pairs_bs | 999 -.0660729 1.0325 -2.92475 2.453464
file C:\Users\dlmiller\AppData\Local\Temp\ST_01000003.tmp saved
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
t_rad_res | 999 .0028013 3.332879 -10.39086 8.510225
t_webb_res | 999 -.0302131 3.334671 -10.64774 8.799172
t_pairs_bs | 999 -.0660729 1.0325 -2.92475 2.453464
obs was 0, now 1
(1000 missing values generated)
Fixed Effects, lnwage_sy, policy
beta, 0.0156
se default, 0.0037, 0.0000
se rob, 0.0037, 0.0000
se clu, 0.0119, 0.1947
se CR2, 0.0118, 0.1946
se CR2 wIK, 0.0118, 0.1946
se pairs BS, 0.0117, 0.1908
percentile T pairs, , 0.1620
percentile T Rad2, , 0.7420
percentile T Webb6, , 0.7220
I-K DOF, 50
CSS effctv clustrs, 51
Num obs, 1836
Num clusters, 51
15:47:00
15:47:13
15:47:22
Source | SS df MS Number of obs = 1836
-------------+------------------------------ F( 1, 1835) = 0.41
Model | .003659806 1 .003659806 Prob > F = 0.5213
Residual | 16.3184525 1835 .00889289 R-squared = 0.0002
-------------+------------------------------ Adj R-squared = -0.0003
Total | 16.3221123 1836 .008890039 Root MSE = .0943
----------------------------------------------------------------------------------
lnwage_sy_devi~n | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0039941 .0062261 0.64 0.521 -.0082168 .016205
----------------------------------------------------------------------------------
Linear regression Number of obs = 1836
F( 1, 1835) = 0.52
Prob > F = 0.4701
R-squared = 0.0002
Root MSE = .0943
----------------------------------------------------------------------------------
| Robust
lnwage_sy_devi~n | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0039941 .0055284 0.72 0.470 -.0068486 .0148368
----------------------------------------------------------------------------------
Linear regression Number of obs = 1836
F( 1, 50) = 0.03
Prob > F = 0.8605
R-squared = 0.0002
Root MSE = .0943
(Std. Err. adjusted for 51 clusters in statefip)
----------------------------------------------------------------------------------
| Robust
lnwage_sy_devi~n | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0039941 .0226151 0.18 0.861 -.0414296 .0494178
----------------------------------------------------------------------------------
Note: +/- means the corresponding matrix is added/subtracted
Calculating cov part for variables: statefip (+)
Number of obs = 1836
Num clusvars = 1
Num combinations = 1
G(statefip) = 51
----------------------------------------------------------------------------------
lnwage_sy_devi~n | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0039941 .0226151 0.18 0.860 -.0403306 .0483188
----------------------------------------------------------------------------------
Note: +/- means the corresponding matrix is added/subtracted
Calculating cov part for variables: statefip (+)
Calculating cov part for variables: statefip year (-)
Calculating cov part for variables: year (+)
Number of obs = 1836
Num clusvars = 2
Num combinations = 3
G(statefip) = 51
G(year) = 36
----------------------------------------------------------------------------------
lnwage_sy_devi~n | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
policy_deviation | .0039941 .0220024 0.18 0.856 -.0391297 .0471179
----------------------------------------------------------------------------------
(bootstrap: table3_np_boot)
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
t_pairs_bs | 999 -.0193459 1.008218 -3.69574 3.69019
file C:\Users\dlmiller\AppData\Local\Temp\ST_01000003.tmp saved
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
t_rad_res | 999 -.0398545 3.521215 -11.94488 11.92573
t_webb_res | 999 -.0556638 3.548204 -11.6274 12.26853
t_pairs_bs | 999 -.0193459 1.008218 -3.69574 3.69019
obs was 0, now 1
(1000 missing values generated)
Fixed Effects, lnwage_sy, policy
beta, 0.0040
se default, 0.0062, 0.5213
se rob, 0.0055, 0.4701
se clu, 0.0226, 0.8605
se CR2, 0.0226, 0.8605
se CR2 wIK, 0.0226, 0.8605
se pairs BS, 0.0221, 0.8573
percentile T pairs, , 0.8780
percentile T Rad2, , 0.9680
percentile T Webb6, , 0.9420
I-K DOF, 50
CSS effctv clustrs, 51
Num obs, 1836
Num clusters, 51
15:47:22
15:47:31
15:47:40
panel variable: statefip (strongly balanced)
time variable: year, 1977 to 2012
delta: 1 unit
Iteration 1: tolerance = .02845206
Iteration 2: tolerance = .00146256
Iteration 3: tolerance = .00009165
Iteration 4: tolerance = 5.966e-06
Iteration 5: tolerance = 3.892e-07
GEE population-averaged model Number of obs = 1836
Group and time vars: statefip year Number of groups = 51
Link: identity Obs per group: min = 36
Family: Gaussian avg = 36.0
Correlation: AR(1) max = 36
Wald chi2(86) = 2491.78
Scale parameter: .0016397 Prob > chi2 = 0.0000
---------------------------------------------------------------------------------------
lnwage_sy | Coef. Std. Err. z P>|z| [95% Conf. Interval]
----------------------+----------------------------------------------------------------
policy | -.0042342 .0061831 -0.68 0.493 -.0163529 .0078845
|
statefip |
Alaska | .3289668 .0184015 17.88 0.000 .2929006 .365033
Arizona | .1112691 .0184261 6.04 0.000 .0751546 .1473835
Arkansas | -.0209478 .0184261 -1.14 0.256 -.0570623 .0151667
California | .2186875 .0184015 11.88 0.000 .1826213 .2547537
Colorado | .1443437 .0184015 7.84 0.000 .1082775 .1804099
Connecticut | .245278 .0184015 13.33 0.000 .2092118 .2813441
Delaware | .1672697 .0184261 9.08 0.000 .1311553 .2033842
District of Columbia | .2225865 .0184261 12.08 0.000 .186472 .2587009
Florida | .058999 .0184261 3.20 0.001 .0228845 .0951134
Georgia | .09088 .0184261 4.93 0.000 .0547655 .1269945
Hawaii | .1299187 .0184261 7.05 0.000 .0938042 .1660332
Idaho | .0204769 .0184015 1.11 0.266 -.0155893 .0565431
Illinois | .1926391 .0184015 10.47 0.000 .1565729 .2287053
Indiana | .1146251 .0184015 6.23 0.000 .0785589 .1506912
Iowa | .0635945 .0184261 3.45 0.001 .02748 .0997089
Kansas | .0549369 .0184261 2.98 0.003 .0188224 .0910514
Kentucky | .066781 .0184015 3.63 0.000 .0307148 .1028472
Louisiana | .0667025 .0184015 3.62 0.000 .0306363 .1027687
Maine | .0299914 .0184015 1.63 0.103 -.0060748 .0660576
Maryland | .2403775 .0184261 13.05 0.000 .204263 .2764919
Massachusetts | .2231633 .0184015 12.13 0.000 .1870971 .2592295
Michigan | .2025633 .0184261 10.99 0.000 .1664488 .2386778
Minnesota | .1566676 .0184261 8.50 0.000 .1205531 .1927821
Mississippi | -.0429117 .0184015 -2.33 0.020 -.0789778 -.0068455
Missouri | .0872822 .0184261 4.74 0.000 .0511677 .1233967
Montana | -.0338175 .0184015 -1.84 0.066 -.0698837 .0022487
Nebraska | .021383 .0184261 1.16 0.246 -.0147315 .0574975
Nevada | .153587 .0184015 8.35 0.000 .1175208 .1896532
New Hampshire | .1554903 .0184261 8.44 0.000 .1193758 .1916048
New Jersey | .2677121 .0184261 14.53 0.000 .2315977 .3038266
New Mexico | .0427163 .0184015 2.32 0.020 .0066502 .0787825
New York | .1969257 .0184015 10.70 0.000 .1608595 .2329919
North Carolina | .0482115 .0184261 2.62 0.009 .012097 .084326
North Dakota | -.0203138 .0184261 -1.10 0.270 -.0564283 .0158006
Ohio | .1437024 .0184015 7.81 0.000 .1076362 .1797686
Oklahoma | .0330299 .0184015 1.79 0.073 -.0030363 .0690961
Oregon | .1151325 .0184015 6.26 0.000 .0790663 .1511986
Pennsylvania | .1568971 .0184015 8.53 0.000 .1208309 .1929633
Rhode Island | .1636518 .0184015 8.89 0.000 .1275856 .199718
South Carolina | .0344238 .0184261 1.87 0.062 -.0016907 .0705383
South Dakota | -.0579254 .0184015 -3.15 0.002 -.0939916 -.0218592
Tennessee | .0486733 .0184015 2.65 0.008 .0126071 .0847394
Texas | .1081395 .0184261 5.87 0.000 .072025 .144254
Utah | .0990007 .0184261 5.37 0.000 .0628862 .1351152
Vermont | .0383452 .0184261 2.08 0.037 .0022307 .0744597
Virginia | .1670745 .0184015 9.08 0.000 .1310083 .2031407
Washington | .1836033 .0184261 9.96 0.000 .1474889 .2197178
West Virginia | .061403 .0184015 3.34 0.001 .0253368 .0974692
Wisconsin | .1324531 .0184261 7.19 0.000 .0963386 .1685676
Wyoming | .0759297 .0184261 4.12 0.000 .0398152 .1120442
|
year |
1978 | .0052097 .0037105 1.40 0.160 -.0020627 .0124821
1979 | -.0010979 .0049354 -0.22 0.824 -.0107712 .0085754
1980 | -.0212629 .0057041 -3.73 0.000 -.0324427 -.0100831
1981 | -.0612727 .0062347 -9.83 0.000 -.0734925 -.049053
1982 | -.080269 .0066173 -12.13 0.000 -.0932387 -.0672992
1983 | -.0918282 .0069004 -13.31 0.000 -.1053527 -.0783037
1984 | -.0933083 .0071131 -13.12 0.000 -.1072498 -.0793669
1985 | -.0975133 .0072748 -13.40 0.000 -.1117715 -.083255
1986 | -.0960996 .0073985 -12.99 0.000 -.1106004 -.0815988
1987 | -.0872681 .0074938 -11.65 0.000 -.1019557 -.0725805
1988 | -.0955074 .0075675 -12.62 0.000 -.1103394 -.0806754
1989 | -.1049596 .0076246 -13.77 0.000 -.1199036 -.0900156
1990 | -.1146679 .0076691 -14.95 0.000 -.129699 -.0996368
1991 | -.1373327 .0077037 -17.83 0.000 -.1524316 -.1222338
1992 | -.1856639 .0077306 -24.02 0.000 -.2008157 -.1705121
1993 | -.1911906 .0077517 -24.66 0.000 -.2063837 -.1759975
1994 | -.2001138 .0077682 -25.76 0.000 -.2153391 -.1848885
1995 | -.2055368 .0082988 -24.77 0.000 -.2218021 -.1892715
1996 | -.2136272 .0083081 -25.71 0.000 -.2299107 -.1973436
1997 | -.2128064 .0083154 -25.59 0.000 -.2291043 -.1965086
1998 | -.1983205 .0083211 -23.83 0.000 -.2146295 -.1820115
1999 | -.1754062 .0083255 -21.07 0.000 -.191724 -.1590885
2000 | -.1587121 .008329 -19.06 0.000 -.1750367 -.1423875
2001 | -.1525916 .0083318 -18.31 0.000 -.1689216 -.1362617
2002 | -.1510823 .0083339 -18.13 0.000 -.1674164 -.1347481
2003 | -.13922 .0083356 -16.70 0.000 -.1555574 -.1228825
2004 | -.1411515 .0083369 -16.93 0.000 -.1574915 -.1248115
2005 | -.1460817 .0083379 -17.52 0.000 -.1624237 -.1297396
2006 | -.1556052 .0083387 -18.66 0.000 -.1719488 -.1392615
2007 | -.1563965 .0083394 -18.75 0.000 -.1727414 -.1400517
2008 | -.1494961 .0083399 -17.93 0.000 -.165842 -.1331502
2009 | -.1627607 .0083403 -19.52 0.000 -.1791073 -.1464141
2010 | -.1425136 .0083406 -17.09 0.000 -.1588608 -.1261664
2011 | -.1512476 .0083408 -18.13 0.000 -.1675953 -.1348999
2012 | -.1661184 .008341 -19.92 0.000 -.1824665 -.1497704
---------------------------------------------------------------------------------------
Iteration 1: tolerance = .02845206
Iteration 2: tolerance = .00146256
Iteration 3: tolerance = .00009165
Iteration 4: tolerance = 5.966e-06
Iteration 5: tolerance = 3.892e-07
GEE population-averaged model Number of obs = 1836
Group and time vars: statefip year Number of groups = 51
Link: identity Obs per group: min = 36
Family: Gaussian avg = 36.0
Correlation: AR(1) max = 36
Wald chi2(36) = 7185.95
Scale parameter: .0016397 Prob > chi2 = 0.0000
(Std. Err. adjusted for clustering on statefip)
---------------------------------------------------------------------------------------
| Robust
lnwage_sy | Coef. Std. Err. z P>|z| [95% Conf. Interval]
----------------------+----------------------------------------------------------------
policy | -.0042342 .0084102 -0.50 0.615 -.0207179 .0122495
|
statefip |
Alaska | .3289668 .0092174 35.69 0.000 .310901 .3470326
Arizona | .1112691 .0074525 14.93 0.000 .0966625 .1258756
Arkansas | -.0209478 .0074525 -2.81 0.005 -.0355544 -.0063413
California | .2186875 .0092174 23.73 0.000 .2006217 .2367534
Colorado | .1443437 .0092174 15.66 0.000 .1262779 .1624096
Connecticut | .245278 .0092174 26.61 0.000 .2272121 .2633438
Delaware | .1672697 .0074525 22.44 0.000 .1526632 .1818763
District of Columbia | .2225865 .0074525 29.87 0.000 .2079799 .237193
Florida | .058999 .0074525 7.92 0.000 .0443924 .0736055
Georgia | .09088 .0074525 12.19 0.000 .0762735 .1054866
Hawaii | .1299187 .0074525 17.43 0.000 .1153122 .1445253
Idaho | .0204769 .0092174 2.22 0.026 .0024111 .0385428
Illinois | .1926391 .0092174 20.90 0.000 .1745733 .2107049
Indiana | .1146251 .0092174 12.44 0.000 .0965592 .1326909
Iowa | .0635945 .0074525 8.53 0.000 .0489879 .078201
Kansas | .0549369 .0074525 7.37 0.000 .0403304 .0695435
Kentucky | .066781 .0092174 7.25 0.000 .0487152 .0848468
Louisiana | .0667025 .0092174 7.24 0.000 .0486367 .0847683
Maine | .0299914 .0092174 3.25 0.001 .0119256 .0480573
Maryland | .2403775 .0074525 32.25 0.000 .2257709 .254984
Massachusetts | .2231633 .0092174 24.21 0.000 .2050975 .2412291
Michigan | .2025633 .0074525 27.18 0.000 .1879568 .2171699
Minnesota | .1566676 .0074525 21.02 0.000 .1420611 .1712742
Mississippi | -.0429117 .0092174 -4.66 0.000 -.0609775 -.0248458
Missouri | .0872822 .0074525 11.71 0.000 .0726756 .1018887
Montana | -.0338175 .0092174 -3.67 0.000 -.0518833 -.0157517
Nebraska | .021383 .0074525 2.87 0.004 .0067764 .0359896
Nevada | .153587 .0092174 16.66 0.000 .1355212 .1716529
New Hampshire | .1554903 .0074525 20.86 0.000 .1408837 .1700968
New Jersey | .2677121 .0074525 35.92 0.000 .2531056 .2823187
New Mexico | .0427163 .0092174 4.63 0.000 .0246505 .0607822
New York | .1969257 .0092174 21.36 0.000 .1788599 .2149916
North Carolina | .0482115 .0074525 6.47 0.000 .033605 .0628181
North Dakota | -.0203138 .0074525 -2.73 0.006 -.0349204 -.0057073
Ohio | .1437024 .0092174 15.59 0.000 .1256365 .1617682
Oklahoma | .0330299 .0092174 3.58 0.000 .0149641 .0510957
Oregon | .1151325 .0092174 12.49 0.000 .0970666 .1331983
Pennsylvania | .1568971 .0092174 17.02 0.000 .1388313 .1749629
Rhode Island | .1636518 .0092174 17.75 0.000 .145586 .1817177
South Carolina | .0344238 .0074525 4.62 0.000 .0198173 .0490304
South Dakota | -.0579254 .0092174 -6.28 0.000 -.0759913 -.0398596
Tennessee | .0486733 .0092174 5.28 0.000 .0306074 .0667391
Texas | .1081395 .0074525 14.51 0.000 .0935329 .122746
Utah | .0990007 .0074525 13.28 0.000 .0843942 .1136073
Vermont | .0383452 .0074525 5.15 0.000 .0237386 .0529517
Virginia | .1670745 .0092174 18.13 0.000 .1490087 .1851404
Washington | .1836033 .0074525 24.64 0.000 .1689968 .1982099
West Virginia | .061403 .0092174 6.66 0.000 .0433372 .0794688
Wisconsin | .1324531 .0074525 17.77 0.000 .1178465 .1470596
Wyoming | .0759297 .0074525 10.19 0.000 .0613232 .0905363
|
year |
1978 | .0052097 .0033144 1.57 0.116 -.0012863 .0117057
1979 | -.0010979 .0047089 -0.23 0.816 -.0103271 .0081313
1980 | -.0212629 .005744 -3.70 0.000 -.0325209 -.0100049
1981 | -.0612727 .0067682 -9.05 0.000 -.0745381 -.0480074
1982 | -.080269 .0075779 -10.59 0.000 -.0951214 -.0654166
1983 | -.0918282 .0068655 -13.38 0.000 -.1052844 -.0783721
1984 | -.0933083 .0073237 -12.74 0.000 -.1076625 -.0789542
1985 | -.0975133 .0078828 -12.37 0.000 -.1129633 -.0820632
1986 | -.0960996 .0081225 -11.83 0.000 -.1120194 -.0801798
1987 | -.0872681 .0084236 -10.36 0.000 -.103778 -.0707582
1988 | -.0955074 .0097918 -9.75 0.000 -.1146991 -.0763158
1989 | -.1049596 .0110956 -9.46 0.000 -.1267066 -.0832126
1990 | -.1146679 .0112389 -10.20 0.000 -.1366957 -.09264
1991 | -.1373327 .0114647 -11.98 0.000 -.1598031 -.1148623
1992 | -.1856639 .0113039 -16.42 0.000 -.2078191 -.1635087
1993 | -.1911906 .0106125 -18.02 0.000 -.2119907 -.1703905
1994 | -.2001138 .0105963 -18.89 0.000 -.2208822 -.1793454
1995 | -.2055368 .0136677 -15.04 0.000 -.232325 -.1787487
1996 | -.2136272 .0113842 -18.77 0.000 -.2359399 -.1913145
1997 | -.2128064 .012279 -17.33 0.000 -.2368729 -.18874
1998 | -.1983205 .0131548 -15.08 0.000 -.2241034 -.1725375
1999 | -.1754062 .0138696 -12.65 0.000 -.2025902 -.1482223
2000 | -.1587121 .0132661 -11.96 0.000 -.1847131 -.1327111
2001 | -.1525916 .0143385 -10.64 0.000 -.1806945 -.1244887
2002 | -.1510823 .0142137 -10.63 0.000 -.1789406 -.123224
2003 | -.13922 .0142912 -9.74 0.000 -.1672302 -.1112097
2004 | -.1411515 .0149519 -9.44 0.000 -.1704567 -.1118463
2005 | -.1460817 .0142497 -10.25 0.000 -.1740105 -.1181528
2006 | -.1556052 .0144469 -10.77 0.000 -.1839207 -.1272897
2007 | -.1563965 .0145682 -10.74 0.000 -.1849497 -.1278434
2008 | -.1494961 .0141717 -10.55 0.000 -.1772721 -.1217201
2009 | -.1627607 .0142575 -11.42 0.000 -.1907048 -.1348166
2010 | -.1425136 .0141919 -10.04 0.000 -.1703291 -.114698
2011 | -.1512476 .0154444 -9.79 0.000 -.1815181 -.1209771
2012 | -.1661184 .0149552 -11.11 0.000 -.1954301 -.1368068
---------------------------------------------------------------------------------------
file C:\Users\dlmiller\AppData\Local\Temp\ST_01000003.tmp saved
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
beta_bs | 999 -.0074718 .0086332 -.0338359 .0241234
FGLS AR(1), lnwage_sy, policy
beta, -0.0042
se default, 0.0062, 0.4936
se rob, -, -
se clu, 0.0084, 0.6169
se CR2, -, -
se CR2 wIK, -, -
se pairs BS, 0.0086, 0.6260
percentile T pairs, , -
percentile T Rad2, , -
percentile T Webb6, , -
I-K DOF, -,
CSS effctv clustrs,-,
Num obs, 1836
Num clusters, 51
. qui log close t3out ;
. log close _all ;
name:
log: C:\doug work\Colin\JHR cluster paper\work Summer 2014\empirical example code\table3.log
log type: text
closed on: 6 Jul 2014, 16:08:50
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