Hi,
I am running several regressions and then want to ouput the results in a concise manner in Excel. Here is the code I have so far:
Here are my data:
Here is the output I'm getting:
I would like to present the regression coefficients on the same row:
How can I achieve this outcome? Thanks!
I am running several regressions and then want to ouput the results in a concise manner in Excel. Here is the code I have so far:
Code:
use sample_noise.dta, clear global var "ch3m_noise_w" global All_ANO "beta as_turn retvol gma maxret ms ps rsup stdacc baspread chfeps" foreach i of varlist $All_ANO { gen D_`i'_L1_$var = D_`i'*L1_$var gen D_`i'_L1_D_$var = D_`i'*L1_D_$var quietly newey `i' L1_D_$var D_`i'_L1_D_$var D_`i', lag(5) force outreg2 using "publi_date_B", label ctitle(`i') dta dec(3) tstat nocons drop(Mkt_RF SMB HML) alpha(.02, .10, .20) nonotes addnote(t-statistics in parentheses, one-sided t-statistics, ***p<0.01; **p<0.05; *p<0.10) } use "publi_date_B_dta.dta", clear export excel using $var.xlsx , /*replace*/ sheetreplace sheet("Publication Date - B")
Code:
ym beta as_turn retvol gma maxret ms ps rsup stdacc baspread chfeps RF Mkt_RF SMB HML ch_noise_w 1987m4 -4.031828 .5665293 -3.562902 2.933317 -1.926573 3.800406 -2.135415 -.9528576 1.526641 -2.12236 .44 -2.11 -1.69 -.32 1.411289 1987m5 -3.087543 2.355569 -.9416796 2.959575 -1.319767 1.384146 .5161018 -1.156925 -.0712486 -1.06877 .38 .11 -.52 .12 .9583769 1987m6 7.496861 1.482077 6.705112 -.1577106 4.175952 -2.045524 2.241884 -.0834573 4.511261 6.729168 .48 3.94 -2.19 1.06 -1.572835 1987m7 -.7845994 4.364578 -1.916614 1.008461 -1.837684 -.1531013 -3.019662 .2370811 -.0668041 -1.103105 .46 3.85 -.63 .71 .5004749 1987m8 -2.976107 -2.516852 1.206757 .2214915 2.291762 3.888111 -.4897887 -.438806 1.781745 -.5335383 .47 3.52 -.74 -.93 -.1788225 1987m9 1.904939 -1.197485 .1444719 -1.925517 .0050595 .6573381 -.7300012 -.0531384 -1.353002 .2657921 .45 -2.59 .54 .28 -1.031109 1987m10 17.75418 -5.55263 15.11718 -3.967996 13.53885 1.86781 7.497076 -5.16283 8.344318 11.80085 .6 -23.24 -8.42 4.23 3.158195 1987m11 10.24424 -3.26521 6.36503 -2.471189 6.13591 -4.476544 2.878814 -.4599758 -.158664 7.624292 .35 -7.77 2.76 3.08 -1.720168 1987m12 -14.48465 6.121767 -9.588703 10.2468 -2.803698 11.10483 -.6215067 3.757487 2.847481 -8.252355 .39 6.81 .14 -4.45 -.218431 1988m1 8.98735 -4.744936 2.563546 -6.0894 5.822382 -8.084696 -.9711636 -2.828097 .4125161 3.11357 .29 4.21 -.71 5.17 -1.605674 1988m2 -11.30435 5.810012 -7.698685 5.288568 -5.822155 -.1363569 .1767531 1.833565 -2.178874 -6.341976 .46 4.75 3.35 -1.65 -.3186386 1988m3 -4.71446 2.996438 -3.620034 .6127492 -4.374222 -2.141388 -1.642055 2.848933 -1.324977 .2735081 .44 -2.27 6.14 .75 .9501665 1988m4 -1.944875 2.094418 .1226072 1.455372 -.3637265 -2.17255 -.7365742 .7938695 .3418547 .0474411 .46 .56 .96 1.68 -.4561872 1988m5 4.106129 -1.57732 1.219917 -3.584458 2.328698 -1.720937 .313263 -.3385183 -2.443667 .5164252 .51 -.29 -2.65 2.28 -.2478542 1988m6 -6.995058 -.1835973 -1.383736 1.829104 .2131224 -.6020278 .8326551 4.12623 .341608 -3.691374 .49 4.79 2.1 -1.11 .2288923 1988m7 4.299152 -1.0834 1.712216 -4.078659 1.927485 -3.047734 -.3123012 -.7608059 -1.164788 2.128115 .51 -1.25 -.2 2.27 .2419186 1988m8 5.018091 -1.384443 4.545624 -2.733395 3.714663 -4.245328 -1.209007 -1.721197 -.1595033 3.795788 .59 -3.31 .08 2.08 .527565
Here is the output I'm getting:
Code:
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) VARIABLES Test beta assetturnover retvol gma maxret ms ps rsup stdacc baspread chfeps Ch. Noise(t-1) 0.212* 0.776** 0.365*** -0.388 0.453*** 0.648** 0.194 -0.207 0.089 0.257** 1.224*** 0.373** (1.396) (2.080) (2.383) (-0.482) (3.547) (2.127) (0.656) (-1.172) (0.841) (2.215) (5.639) (2.330) D_beta_L1_ch3m_noise_w -4.393*** (-3.507) D_beta 1.028 (0.937) D_assetturnover_L1_ch3m_noise_w = o, - D_assetturnover = o, - D_retvol_L1_ch3m_noise_w 1.599** (1.884) D_retvol -0.688 (-0.859) D_gma_L1_ch3m_noise_w -0.297 (-0.295) D_gma -0.407 (-0.862) D_maxret_L1_ch3m_noise_w -0.641 (-0.458) D_maxret -0.191 (-0.282) D_ms_L1_ch3m_noise_w 0.138 (0.453) D_ms -0.033 (-0.096) D_ps_L1_ch3m_noise_w 0.676*** (3.428) D_ps 0.205 (0.770) D_rsup_L1_ch3m_noise_w 0.566** (2.201) D_rsup 0.168 (0.607) D_stdacc_L1_ch3m_noise_w -1.079** (-2.093) D_stdacc -0.163 (-0.364) D_baspread_L1_ch3m_noise_w -0.418 (-0.905) D_baspread -0.026 (-0.031) D_chfeps_L1_ch3m_noise_w = o, - D_chfeps = o, - Observations 312 332 332 332 332 332 332 332 332 332 332 312 t-statistics in parentheses one-sided t-statistics ***p<0.01; **p<0.05; *p<0.10
Code:
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) VARIABLES Test beta assetturnover retvol gma maxret ms ps rsup stdacc baspread chfeps Ch. Noise(t-1) 0.212* 0.776** 0.365*** -0.388 0.453*** 0.648** 0.194 -0.207 0.089 0.257** 1.224*** 0.373** (1.396) (2.080) (2.383) (-0.482) (3.547) (2.127) (0.656) (-1.172) (0.841) (2.215) (5.639) (2.330) D_ANO_L1_ch3m_noise_w -4.393*** - 1.599** -0.297 -0.641 0.138 0.676*** 0.566** -1.079** -0.418 - (-3.507) (1.884) (-0.295) (-0.458) (0.453) (3.428) (2.201) (-2.093) (-0.905) D_ANO 1.028 - -0.688 -0.407 -0.191 -0.033 0.205 0.168 -0.163 -0.026 - (0.937) (-0.859) (-0.862) (-0.282) (-0.096) (0.770) (0.607) (-0.364) (-0.031) Observations 312 332 332 332 332 332 332 332 332 332 332 312 t-statistics in parentheses one-sided t-statistics ***p<0.01; **p<0.05; *p<0.10
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