i have split my sample into two parts and ran a fe regression for both of them.
is it possible to say that one effect ist stroger than the other? can i say that the coefficient of the governance variable in period 2 is stronger than in period 1?
Code:
Linear regression Number of obs = 2,088
F(53, 430) = .
Prob > F = .
R-squared = 0.7361
Root MSE = .09705
(Std. Err. adjusted for 431 clusters in company_code)
----------------------------------------------------------------------------------------------
| Robust
return_volatility_w | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
governance_score | -.0248947 .0150816 -1.65 0.100 -.0545375 .0047481
company_size_w | -.0404233 .0086368 -4.68 0.000 -.0573988 -.0234478
dividend_ratio_w | -.8944752 .187322 -4.78 0.000 -1.262656 -.5262946
earnings_smoothing_2_w | -.0219127 .0050407 -4.35 0.000 -.0318202 -.0120053
leverage_w | .0228574 .0284547 0.80 0.422 -.0330702 .0787849
research_development_ratio_w | .0840555 .101191 0.83 0.407 -.1148351 .2829461
sales_growth_w | -.0268705 .0161192 -1.67 0.096 -.0585527 .0048118
tangability_ratio_w | .0415229 .0149298 2.78 0.006 .0121784 .0708674
turnover_rate_w | .0268959 .0016942 15.88 0.000 .023566 .0302258
blockholder | .0008572 .0022735 0.38 0.706 -.0036114 .0053257
trade_union_coverage | -.0000485 .0004925 -0.10 0.922 -.0010165 .0009196
bank_power | .387277 .0397159 9.75 0.000 .3092155 .4653385
|
sic_2 |
13 | -.0304118 .0150801 -2.02 0.044 -.0600516 -.000772
20 | -.1392726 .0161967 -8.60 0.000 -.1711072 -.107438
21 | -.1314665 .0323268 -4.07 0.000 -.1950048 -.0679282
22 | -.1170602 .0116354 -10.06 0.000 -.1399296 -.0941908
23 | -.0864256 .0288507 -3.00 0.003 -.1431315 -.0297196
24 | -.0144642 .0172295 -0.84 0.402 -.0483288 .0194003
25 | -.0491051 .014703 -3.34 0.001 -.0780037 -.0202065
26 | -.0932712 .0265203 -3.52 0.000 -.1453966 -.0411457
27 | -.1102874 .0213453 -5.17 0.000 -.1522415 -.0683332
28 | -.1001355 .0143351 -6.99 0.000 -.1283111 -.07196
29 | -.0705352 .0149799 -4.71 0.000 -.0999782 -.0410922
30 | -.0265549 .0369599 -0.72 0.473 -.0991994 .0460896
31 | -.0848841 .0332142 -2.56 0.011 -.1501664 -.0196017
32 | .0024467 .0159965 0.15 0.879 -.0289944 .0338879
33 | .0167423 .0388873 0.43 0.667 -.0596906 .0931752
34 | -.0953966 .0169065 -5.64 0.000 -.1286262 -.062167
35 | -.0498152 .0162776 -3.06 0.002 -.0818087 -.0178216
36 | -.0549001 .0180429 -3.04 0.002 -.0903634 -.0194368
37 | -.0394992 .0181193 -2.18 0.030 -.0751127 -.0038858
38 | -.1142142 .0159051 -7.18 0.000 -.1454755 -.0829528
39 | -.0832297 .0223976 -3.72 0.000 -.1272521 -.0392072
50 | -.1162061 .024314 -4.78 0.000 -.1639952 -.0684169
51 | -.0762255 .0210122 -3.63 0.000 -.117525 -.0349261
52 | -.090609 .0116039 -7.81 0.000 -.1134164 -.0678016
53 | -.1292317 .0149522 -8.64 0.000 -.1586202 -.0998431
54 | -.1221297 .0142309 -8.58 0.000 -.1501005 -.0941589
55 | -.1201868 .0281467 -4.27 0.000 -.175509 -.0648646
56 | -.0906343 .0237194 -3.82 0.000 -.1372546 -.0440139
57 | -.1217428 .0272069 -4.47 0.000 -.1752178 -.0682678
58 | -.1360863 .0194496 -7.00 0.000 -.1743144 -.0978583
59 | -.0626834 .0200505 -3.13 0.002 -.1020925 -.0232742
70 | .0141774 .0388447 0.36 0.715 -.0621716 .0905265
72 | -.0498467 .0193437 -2.58 0.010 -.0878666 -.0118268
73 | -.0595291 .0167802 -3.55 0.000 -.0925105 -.0265477
75 | -.0240225 .0618428 -0.39 0.698 -.1455743 .0975293
78 | -.0734657 .0236273 -3.11 0.002 -.1199051 -.0270264
79 | -.0495513 .0308397 -1.61 0.109 -.1101666 .011064
80 | -.1468875 .0238443 -6.16 0.000 -.1937534 -.1000217
82 | -.0930031 .0181935 -5.11 0.000 -.1287624 -.0572438
87 | -.0597639 .0310283 -1.93 0.055 -.1207499 .0012221
|
year |
2004 | -.1906044 .014588 -13.07 0.000 -.219277 -.1619318
2005 | -.490761 .0420629 -11.67 0.000 -.5734355 -.4080864
2006 | -.7040922 .0631446 -11.15 0.000 -.8282028 -.5799817
2007 | -.7784349 .0708597 -10.99 0.000 -.9177093 -.6391604
2008 | -.3461531 .0470228 -7.36 0.000 -.4385762 -.2537299
2009 | 0 (omitted)
|
_cons | -2.18514 .3043332 -7.18 0.000 -2.783305 -1.586974
----------------------------------------------------------------------------------------------
.
end of do-file
. do "C:\Users\Paddy\AppData\Local\Temp\STD307c_000000.tmp"
.
. regress return_volatility_w governance_score company_size_w dividend_ratio_w earnings_smoothing_2_w leverage_w resear
> ch_development_ratio_w sales_growth_w tangability_ratio_w turnover_rate_w blockholder trade_union_coverage bank_power
> i.sic_2 i.year if year > 2010, vce (cluster company_code)
note: 2019.year omitted because of collinearity
Linear regression Number of obs = 3,134
F(54, 420) = .
Prob > F = .
R-squared = 0.6752
Root MSE = .06619
(Std. Err. adjusted for 421 clusters in company_code)
----------------------------------------------------------------------------------------------
| Robust
return_volatility_w | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
governance_score | -.0195744 .0086024 -2.28 0.023 -.0364835 -.0026654
company_size_w | -.0251767 .0046063 -5.47 0.000 -.0342309 -.0161225
dividend_ratio_w | -.6324831 .0940964 -6.72 0.000 -.8174417 -.4475244
earnings_smoothing_2_w | -.0057561 .002902 -1.98 0.048 -.0114604 -.0000518
leverage_w | .0344702 .0170789 2.02 0.044 .0008995 .0680409
research_development_ratio_w | .2468165 .0671307 3.68 0.000 .1148625 .3787705
sales_growth_w | .0341093 .0120846 2.82 0.005 .0103555 .0578631
tangability_ratio_w | .0181575 .0102887 1.76 0.078 -.0020663 .0383813
turnover_rate_w | .0263781 .0017497 15.08 0.000 .0229387 .0298174
blockholder | .0054793 .0015189 3.61 0.000 .0024937 .0084649
trade_union_coverage | -.0000215 .0003034 -0.07 0.944 -.0006179 .0005749
bank_power | -.0966771 .0245319 -3.94 0.000 -.1448976 -.0484566
|
sic_2 |
21 | .0304405 .0172305 1.77 0.078 -.0034283 .0643093
22 | -.0055592 .0282167 -0.20 0.844 -.0610228 .0499044
23 | .0420466 .0417709 1.01 0.315 -.0400596 .1241527
24 | .0224067 .0157591 1.42 0.156 -.0085697 .0533832
25 | .050406 .0108798 4.63 0.000 .0290203 .0717917
26 | -.006852 .0167531 -0.41 0.683 -.0397824 .0260785
27 | .0284892 .0194864 1.46 0.144 -.0098139 .0667923
28 | .0263143 .0120419 2.19 0.029 .0026444 .0499843
29 | .0581011 .0141749 4.10 0.000 .0302385 .0859637
30 | .0381382 .0160436 2.38 0.018 .0066023 .069674
31 | .0727234 .013591 5.35 0.000 .0460085 .0994383
32 | .0307623 .009945 3.09 0.002 .0112141 .0503105
33 | .0098386 .0422816 0.23 0.816 -.0732713 .0929486
34 | .0013414 .0119072 0.11 0.910 -.0220638 .0247465
35 | .038221 .0130557 2.93 0.004 .0125583 .0638836
36 | .0334714 .015186 2.20 0.028 .0036215 .0633213
37 | .0242125 .0139162 1.74 0.083 -.0031415 .0515666
38 | -.0049464 .0118221 -0.42 0.676 -.0281842 .0182913
39 | .0342769 .0152831 2.24 0.025 .004236 .0643178
50 | .0017851 .0166087 0.11 0.914 -.0308614 .0344315
51 | .0551732 .0232763 2.37 0.018 .0094206 .1009257
52 | .0083861 .0131168 0.64 0.523 -.0173966 .0341689
53 | -.0032044 .013684 -0.23 0.815 -.0301021 .0236933
54 | .0099408 .018664 0.53 0.595 -.0267457 .0466273
55 | -.0136201 .0189074 -0.72 0.472 -.050785 .0235449
56 | .0292476 .0178389 1.64 0.102 -.0058171 .0643122
57 | .0104898 .0372296 0.28 0.778 -.0626898 .0836695
58 | -.0067515 .0190734 -0.35 0.724 -.0442427 .0307396
59 | .0356023 .0134419 2.65 0.008 .0091806 .0620239
70 | .0100439 .0273551 0.37 0.714 -.043726 .0638138
72 | .0390487 .0122056 3.20 0.001 .0150571 .0630404
73 | .0164809 .0127765 1.29 0.198 -.0086329 .0415946
75 | .0205875 .0281016 0.73 0.464 -.0346498 .0758248
78 | .0251894 .0122396 2.06 0.040 .0011308 .0492479
79 | .0247439 .0196943 1.26 0.210 -.0139678 .0634556
80 | -.0274531 .0145026 -1.89 0.059 -.0559598 .0010535
82 | .0988074 .0148506 6.65 0.000 .0696166 .1279981
87 | .0399987 .0188036 2.13 0.034 .0030378 .0769596
|
year |
2012 | -.0734135 .0070246 -10.45 0.000 -.0872213 -.0596057
2013 | -.0924838 .0093868 -9.85 0.000 -.1109348 -.0740328
2014 | -.1007837 .0090648 -11.12 0.000 -.1186018 -.0829656
2015 | -.0743972 .009796 -7.59 0.000 -.0936525 -.0551419
2016 | -.0636849 .0125124 -5.09 0.000 -.0882797 -.0390901
2017 | -.1162378 .0117682 -9.88 0.000 -.1393696 -.093106
2018 | -.0432795 .0077273 -5.60 0.000 -.0584686 -.0280904
2019 | 0 (omitted)
|
_cons | 1.017701 .1710983 5.95 0.000 .681385 1.354016
----------------------------------------------------------------------------------------------
0 Response to Comparing two Coefficients
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