Dear All
I am estimating a quantile regression by including the interaction effect.
For your information, I estimate two interaction terms.
1) the interaction between the commercialization index (hci), which is continuous, and treatment (categorical 0 = treated, 1 = control, 2 = pure control)
2) the interaction between gender-based decision-making (who_d_sell_jbase) (0 = joint decision-makerS, 1 = women-alone decision-makers, 2 = men-alone decision-makers)
The main interest is to see the impact of treatment (intervention) on income through commercialization and gender-based decision-making.
I had reviewed many papers and the post in the STATALIST FUROM to understand the interaction terms; however, I found it difficult to interpret them.
The main challenge is that my interaction variables have three categories (3 by 3)
I need your expert's feedback!
Many Thanks for your contribution and help!
Asmiro
. sqreg horticulture_income c.hci##i.treatment i.treatment##i.who_d_sell_jbase age_hh educ_hh sex_
> hh no_adult_female no_adult_male exp_horticulture landsize_horti total_tlu dist_main_mkt_minutes
> dist_coop_minutes training extension_freq aggr_fertilizer_cost aggr_pesticide_cost aggr_herbici
> de_cost aggr_family_labor aggr_total_wage, q(0.10 0.30 0.50 0.80)
(fitting base model)
Bootstrap replications (20)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
....................
Simultaneous quantile regression Number of obs = 610
bootstrap(20) SEs .10 Pseudo R2 = 0.1819
.30 Pseudo R2 = 0.2269
.50 Pseudo R2 = 0.2448
.80 Pseudo R2 = 0.2835
--------------------------------------------------------------------------------------------
| Bootstrap
horticulture_income | Coefficient std. err. t P>|t| [95% conf. interval]
---------------------------+----------------------------------------------------------------
q10 |
hci | 16.07821 3.835897 4.19 0.000 8.544296 23.61212
|
treatment |
control | 5.56498 3.63354 1.53 0.126 -1.571493 12.70145
pure control | 5.06777 3.546513 1.43 0.154 -1.897777 12.03332
|
treatment#c.hci |
control | -9.626297 3.847812 -2.50 0.013 -17.18361 -2.068981
pure control | -8.900875 4.543659 -1.96 0.051 -17.82487 .0231244
|
who_d_sell_jbase |
women | .2544384 3.703499 0.07 0.945 -7.01944 7.528317
men | 1.546936 1.880126 0.82 0.411 -2.145734 5.239607
|
treatment#who_d_sell_jbase |
control#women | -1.030214 3.629587 -0.28 0.777 -8.158924 6.098497
control#men | -1.35017 2.329159 -0.58 0.562 -5.924768 3.224428
pure control#women | -6.661781 3.31126 -2.01 0.045 -13.16528 -.1582826
pure control#men | -2.782454 1.838179 -1.51 0.131 -6.39274 .8278326
|
age_hh | -.0210189 .0406752 -0.52 0.606 -.1009073 .0588696
educ_hh | .1426188 .0899775 1.59 0.113 -.034102 .3193396
sex_hh | -.1585406 1.72688 -0.09 0.927 -3.550229 3.233148
no_adult_female | .2314458 .5784765 0.40 0.689 -.9047141 1.367606
no_adult_male | .6602095 .4313727 1.53 0.126 -.1870304 1.507449
exp_horticulture | .1657768 .091027 1.82 0.069 -.0130053 .3445588
landsize_horti | .1585103 1.764812 0.09 0.928 -3.307677 3.624698
total_tlu | .3356373 .3365084 1.00 0.319 -.3252838 .9965583
dist_main_mkt_minutes | .0065382 .0067208 0.97 0.331 -.0066617 .0197381
dist_coop_minutes | -.0184738 .0115368 -1.60 0.110 -.0411327 .0041851
training | .1513161 .8237403 0.18 0.854 -1.466555 1.769188
extension_freq | -.0593119 .0535895 -1.11 0.269 -.1645646 .0459409
aggr_fertilizer_cost | .0009165 .0002394 3.83 0.000 .0004463 .0013867
aggr_pesticide_cost | .0026011 .0022407 1.16 0.246 -.0017998 .007002
aggr_herbicide_cost | .0021813 .0042748 0.51 0.610 -.0062147 .0105772
aggr_family_labor | .0260528 .0118529 2.20 0.028 .002773 .0493326
aggr_total_wage | -.0000982 .0003276 -0.30 0.764 -.0007416 .0005452
_cons | -11.19576 4.543287 -2.46 0.014 -20.11903 -2.272494
---------------------------+----------------------------------------------------------------
q30 |
hci | 23.80775 5.688647 4.19 0.000 12.63493 34.98057
|
treatment |
control | 6.261003 4.872168 1.29 0.199 -3.308205 15.83021
pure control | 7.05637 4.566574 1.55 0.123 -1.912634 16.02537
|
treatment#c.hci |
control | -13.33513 6.003986 -2.22 0.027 -25.12729 -1.542972
pure control | -12.51599 6.339729 -1.97 0.049 -24.96757 -.0644146
|
who_d_sell_jbase |
women | -5.987112 4.687259 -1.28 0.202 -15.19315 3.218925
men | 3.554083 3.703052 0.96 0.338 -3.718917 10.82708
|
treatment#who_d_sell_jbase |
control#women | 3.518952 4.362878 0.81 0.420 -5.049982 12.08789
control#men | -2.765082 3.955208 -0.70 0.485 -10.53333 5.003166
pure control#women | -3.694923 6.853874 -0.54 0.590 -17.15631 9.766466
pure control#men | -5.425396 3.79868 -1.43 0.154 -12.88621 2.035423
|
age_hh | -.0796451 .0424518 -1.88 0.061 -.1630228 .0037326
educ_hh | -.0604033 .1242156 -0.49 0.627 -.3043698 .1835631
sex_hh | .1598726 2.226577 0.07 0.943 -4.213248 4.532993
no_adult_female | .4525415 .4560849 0.99 0.321 -.4432345 1.348318
no_adult_male | .2224867 .4822248 0.46 0.645 -.7246295 1.169603
exp_horticulture | .2704601 .1091465 2.48 0.013 .0560903 .4848299
landsize_horti | 2.730005 1.771872 1.54 0.124 -.7500488 6.210059
total_tlu | .0313827 .4127077 0.08 0.939 -.779198 .8419634
dist_main_mkt_minutes | .0016228 .0060131 0.27 0.787 -.0101873 .0134329
dist_coop_minutes | -.0288051 .0158938 -1.81 0.070 -.0600213 .0024111
training | .596237 1.086433 0.55 0.583 -1.537578 2.730052
extension_freq | -.1267907 .1210775 -1.05 0.295 -.3645937 .1110123
aggr_fertilizer_cost | .0008205 .0003891 2.11 0.035 .0000564 .0015847
aggr_pesticide_cost | .0030501 .0014933 2.04 0.042 .0001172 .005983
aggr_herbicide_cost | .0059289 .0088252 0.67 0.502 -.0114043 .0232621
aggr_family_labor | .0414697 .0158902 2.61 0.009 .0102606 .0726789
aggr_total_wage | -.0001773 .0008418 -0.21 0.833 -.0018306 .001476
_cons | -9.41699 5.29105 -1.78 0.076 -19.80891 .9749256
---------------------------+----------------------------------------------------------------
q50 |
hci | 30.27534 7.120569 4.25 0.000 16.29015 44.26053
|
treatment |
control | 7.876441 5.61415 1.40 0.161 -3.150062 18.90294
pure control | 9.270235 5.836843 1.59 0.113 -2.193648 20.73412
|
treatment#c.hci |
control | -14.98609 7.95743 -1.88 0.060 -30.61493 .6427411
pure control | -16.54325 7.474637 -2.21 0.027 -31.22385 -1.862649
|
who_d_sell_jbase |
women | -8.354089 6.070769 -1.38 0.169 -20.27742 3.569238
men | 4.84274 2.738068 1.77 0.077 -.5349786 10.22046
|
treatment#who_d_sell_jbase |
control#women | 4.344647 7.082358 0.61 0.540 -9.565496 18.25479
control#men | -1.309281 3.553745 -0.37 0.713 -8.289032 5.670471
pure control#women | -3.307821 12.09948 -0.27 0.785 -27.07187 20.45623
pure control#men | -5.975782 3.434484 -1.74 0.082 -12.7213 .7697353
|
age_hh | -.1045348 .0629445 -1.66 0.097 -.2281613 .0190917
educ_hh | -.1932976 .1222981 -1.58 0.115 -.4334978 .0469027
sex_hh | 2.011336 2.660109 0.76 0.450 -3.213267 7.235938
no_adult_female | .0252074 .5441845 0.05 0.963 -1.043601 1.094016
no_adult_male | -.3422318 .702222 -0.49 0.626 -1.721435 1.036971
exp_horticulture | .5173094 .2142428 2.41 0.016 .0965247 .9380941
landsize_horti | 6.63969 1.331197 4.99 0.000 4.025145 9.254235
total_tlu | .2923285 .8196908 0.36 0.721 -1.31759 1.902247
dist_main_mkt_minutes | .001502 .0100192 0.15 0.881 -.0181763 .0211802
dist_coop_minutes | -.0185829 .0184898 -1.01 0.315 -.054898 .0177322
training | 2.474459 1.197318 2.07 0.039 .1228597 4.826058
extension_freq | -.0810417 .114021 -0.71 0.478 -.3049853 .1429018
aggr_fertilizer_cost | .001695 .0006072 2.79 0.005 .0005024 .0028876
aggr_pesticide_cost | .0077112 .0029483 2.62 0.009 .0019206 .0135019
aggr_herbicide_cost | .0159355 .0085507 1.86 0.063 -.0008586 .0327296
aggr_family_labor | .043193 .0156041 2.77 0.006 .0125456 .0738403
aggr_total_wage | .0003289 .0013468 0.24 0.807 -.0023163 .0029741
_cons | -15.98439 6.070288 -2.63 0.009 -27.90677 -4.06201
---------------------------+----------------------------------------------------------------
q80 |
hci | 44.28434 8.577305 5.16 0.000 27.43804 61.13065
|
treatment |
control | 12.84738 9.918889 1.30 0.196 -6.633872 32.32862
pure control | 13.52576 9.351321 1.45 0.149 -4.840752 31.89227
|
treatment#c.hci |
control | -20.69357 8.480722 -2.44 0.015 -37.35018 -4.03696
pure control | -22.18628 11.33877 -1.96 0.051 -44.45625 .0837021
|
who_d_sell_jbase |
women | -10.42858 9.482943 -1.10 0.272 -29.0536 8.196448
men | 6.35468 8.86405 0.72 0.474 -11.05481 23.76417
|
treatment#who_d_sell_jbase |
control#women | 1.108775 10.81768 0.10 0.918 -20.13775 22.3553
control#men | -4.459718 10.60189 -0.42 0.674 -25.28242 16.36299
pure control#women | 1.254163 21.67506 0.06 0.954 -41.31686 43.82518
pure control#men | -7.464321 9.859976 -0.76 0.449 -26.82986 11.90122
|
age_hh | -.2780977 .112034 -2.48 0.013 -.4981386 -.0580568
educ_hh | -.5737076 .3428868 -1.67 0.095 -1.247156 .0997412
sex_hh | 4.279397 3.927358 1.09 0.276 -3.434151 11.99295
no_adult_female | .3192048 1.352893 0.24 0.814 -2.337953 2.976362
no_adult_male | -.6033649 1.660308 -0.36 0.716 -3.864301 2.657571
exp_horticulture | .9490994 .3107408 3.05 0.002 .3387872 1.559412
landsize_horti | 6.60538 4.017384 1.64 0.101 -1.284983 14.49574
total_tlu | 1.24648 1.228933 1.01 0.311 -1.167213 3.660172
dist_main_mkt_minutes | .0073455 .0286026 0.26 0.797 -.0488316 .0635226
dist_coop_minutes | -.0090014 .0237244 -0.38 0.705 -.0555974 .0375947
training | 3.720342 2.3862 1.56 0.120 -.9662861 8.40697
extension_freq | .3950899 .4739242 0.83 0.405 -.5357236 1.325903
aggr_fertilizer_cost | .0047735 .0016071 2.97 0.003 .0016171 .0079298
aggr_pesticide_cost | -.0001778 .0075955 -0.02 0.981 -.0150957 .0147402
aggr_herbicide_cost | .0121422 .0163661 0.74 0.458 -.0200017 .0442862
aggr_family_labor | .1280472 .0666859 1.92 0.055 -.0029276 .2590221
aggr_total_wage | .0017052 .0029141 0.59 0.559 -.0040183 .0074287
_cons | -21.96267 10.75125 -2.04 0.042 -43.07873 -.8466061
--------------------------------------------------------------------------------------------
qr_interaction_24092023.txt
I am estimating a quantile regression by including the interaction effect.
For your information, I estimate two interaction terms.
1) the interaction between the commercialization index (hci), which is continuous, and treatment (categorical 0 = treated, 1 = control, 2 = pure control)
2) the interaction between gender-based decision-making (who_d_sell_jbase) (0 = joint decision-makerS, 1 = women-alone decision-makers, 2 = men-alone decision-makers)
The main interest is to see the impact of treatment (intervention) on income through commercialization and gender-based decision-making.
I had reviewed many papers and the post in the STATALIST FUROM to understand the interaction terms; however, I found it difficult to interpret them.
The main challenge is that my interaction variables have three categories (3 by 3)
I need your expert's feedback!
Many Thanks for your contribution and help!
Asmiro
. sqreg horticulture_income c.hci##i.treatment i.treatment##i.who_d_sell_jbase age_hh educ_hh sex_
> hh no_adult_female no_adult_male exp_horticulture landsize_horti total_tlu dist_main_mkt_minutes
> dist_coop_minutes training extension_freq aggr_fertilizer_cost aggr_pesticide_cost aggr_herbici
> de_cost aggr_family_labor aggr_total_wage, q(0.10 0.30 0.50 0.80)
(fitting base model)
Bootstrap replications (20)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
....................
Simultaneous quantile regression Number of obs = 610
bootstrap(20) SEs .10 Pseudo R2 = 0.1819
.30 Pseudo R2 = 0.2269
.50 Pseudo R2 = 0.2448
.80 Pseudo R2 = 0.2835
--------------------------------------------------------------------------------------------
| Bootstrap
horticulture_income | Coefficient std. err. t P>|t| [95% conf. interval]
---------------------------+----------------------------------------------------------------
q10 |
hci | 16.07821 3.835897 4.19 0.000 8.544296 23.61212
|
treatment |
control | 5.56498 3.63354 1.53 0.126 -1.571493 12.70145
pure control | 5.06777 3.546513 1.43 0.154 -1.897777 12.03332
|
treatment#c.hci |
control | -9.626297 3.847812 -2.50 0.013 -17.18361 -2.068981
pure control | -8.900875 4.543659 -1.96 0.051 -17.82487 .0231244
|
who_d_sell_jbase |
women | .2544384 3.703499 0.07 0.945 -7.01944 7.528317
men | 1.546936 1.880126 0.82 0.411 -2.145734 5.239607
|
treatment#who_d_sell_jbase |
control#women | -1.030214 3.629587 -0.28 0.777 -8.158924 6.098497
control#men | -1.35017 2.329159 -0.58 0.562 -5.924768 3.224428
pure control#women | -6.661781 3.31126 -2.01 0.045 -13.16528 -.1582826
pure control#men | -2.782454 1.838179 -1.51 0.131 -6.39274 .8278326
|
age_hh | -.0210189 .0406752 -0.52 0.606 -.1009073 .0588696
educ_hh | .1426188 .0899775 1.59 0.113 -.034102 .3193396
sex_hh | -.1585406 1.72688 -0.09 0.927 -3.550229 3.233148
no_adult_female | .2314458 .5784765 0.40 0.689 -.9047141 1.367606
no_adult_male | .6602095 .4313727 1.53 0.126 -.1870304 1.507449
exp_horticulture | .1657768 .091027 1.82 0.069 -.0130053 .3445588
landsize_horti | .1585103 1.764812 0.09 0.928 -3.307677 3.624698
total_tlu | .3356373 .3365084 1.00 0.319 -.3252838 .9965583
dist_main_mkt_minutes | .0065382 .0067208 0.97 0.331 -.0066617 .0197381
dist_coop_minutes | -.0184738 .0115368 -1.60 0.110 -.0411327 .0041851
training | .1513161 .8237403 0.18 0.854 -1.466555 1.769188
extension_freq | -.0593119 .0535895 -1.11 0.269 -.1645646 .0459409
aggr_fertilizer_cost | .0009165 .0002394 3.83 0.000 .0004463 .0013867
aggr_pesticide_cost | .0026011 .0022407 1.16 0.246 -.0017998 .007002
aggr_herbicide_cost | .0021813 .0042748 0.51 0.610 -.0062147 .0105772
aggr_family_labor | .0260528 .0118529 2.20 0.028 .002773 .0493326
aggr_total_wage | -.0000982 .0003276 -0.30 0.764 -.0007416 .0005452
_cons | -11.19576 4.543287 -2.46 0.014 -20.11903 -2.272494
---------------------------+----------------------------------------------------------------
q30 |
hci | 23.80775 5.688647 4.19 0.000 12.63493 34.98057
|
treatment |
control | 6.261003 4.872168 1.29 0.199 -3.308205 15.83021
pure control | 7.05637 4.566574 1.55 0.123 -1.912634 16.02537
|
treatment#c.hci |
control | -13.33513 6.003986 -2.22 0.027 -25.12729 -1.542972
pure control | -12.51599 6.339729 -1.97 0.049 -24.96757 -.0644146
|
who_d_sell_jbase |
women | -5.987112 4.687259 -1.28 0.202 -15.19315 3.218925
men | 3.554083 3.703052 0.96 0.338 -3.718917 10.82708
|
treatment#who_d_sell_jbase |
control#women | 3.518952 4.362878 0.81 0.420 -5.049982 12.08789
control#men | -2.765082 3.955208 -0.70 0.485 -10.53333 5.003166
pure control#women | -3.694923 6.853874 -0.54 0.590 -17.15631 9.766466
pure control#men | -5.425396 3.79868 -1.43 0.154 -12.88621 2.035423
|
age_hh | -.0796451 .0424518 -1.88 0.061 -.1630228 .0037326
educ_hh | -.0604033 .1242156 -0.49 0.627 -.3043698 .1835631
sex_hh | .1598726 2.226577 0.07 0.943 -4.213248 4.532993
no_adult_female | .4525415 .4560849 0.99 0.321 -.4432345 1.348318
no_adult_male | .2224867 .4822248 0.46 0.645 -.7246295 1.169603
exp_horticulture | .2704601 .1091465 2.48 0.013 .0560903 .4848299
landsize_horti | 2.730005 1.771872 1.54 0.124 -.7500488 6.210059
total_tlu | .0313827 .4127077 0.08 0.939 -.779198 .8419634
dist_main_mkt_minutes | .0016228 .0060131 0.27 0.787 -.0101873 .0134329
dist_coop_minutes | -.0288051 .0158938 -1.81 0.070 -.0600213 .0024111
training | .596237 1.086433 0.55 0.583 -1.537578 2.730052
extension_freq | -.1267907 .1210775 -1.05 0.295 -.3645937 .1110123
aggr_fertilizer_cost | .0008205 .0003891 2.11 0.035 .0000564 .0015847
aggr_pesticide_cost | .0030501 .0014933 2.04 0.042 .0001172 .005983
aggr_herbicide_cost | .0059289 .0088252 0.67 0.502 -.0114043 .0232621
aggr_family_labor | .0414697 .0158902 2.61 0.009 .0102606 .0726789
aggr_total_wage | -.0001773 .0008418 -0.21 0.833 -.0018306 .001476
_cons | -9.41699 5.29105 -1.78 0.076 -19.80891 .9749256
---------------------------+----------------------------------------------------------------
q50 |
hci | 30.27534 7.120569 4.25 0.000 16.29015 44.26053
|
treatment |
control | 7.876441 5.61415 1.40 0.161 -3.150062 18.90294
pure control | 9.270235 5.836843 1.59 0.113 -2.193648 20.73412
|
treatment#c.hci |
control | -14.98609 7.95743 -1.88 0.060 -30.61493 .6427411
pure control | -16.54325 7.474637 -2.21 0.027 -31.22385 -1.862649
|
who_d_sell_jbase |
women | -8.354089 6.070769 -1.38 0.169 -20.27742 3.569238
men | 4.84274 2.738068 1.77 0.077 -.5349786 10.22046
|
treatment#who_d_sell_jbase |
control#women | 4.344647 7.082358 0.61 0.540 -9.565496 18.25479
control#men | -1.309281 3.553745 -0.37 0.713 -8.289032 5.670471
pure control#women | -3.307821 12.09948 -0.27 0.785 -27.07187 20.45623
pure control#men | -5.975782 3.434484 -1.74 0.082 -12.7213 .7697353
|
age_hh | -.1045348 .0629445 -1.66 0.097 -.2281613 .0190917
educ_hh | -.1932976 .1222981 -1.58 0.115 -.4334978 .0469027
sex_hh | 2.011336 2.660109 0.76 0.450 -3.213267 7.235938
no_adult_female | .0252074 .5441845 0.05 0.963 -1.043601 1.094016
no_adult_male | -.3422318 .702222 -0.49 0.626 -1.721435 1.036971
exp_horticulture | .5173094 .2142428 2.41 0.016 .0965247 .9380941
landsize_horti | 6.63969 1.331197 4.99 0.000 4.025145 9.254235
total_tlu | .2923285 .8196908 0.36 0.721 -1.31759 1.902247
dist_main_mkt_minutes | .001502 .0100192 0.15 0.881 -.0181763 .0211802
dist_coop_minutes | -.0185829 .0184898 -1.01 0.315 -.054898 .0177322
training | 2.474459 1.197318 2.07 0.039 .1228597 4.826058
extension_freq | -.0810417 .114021 -0.71 0.478 -.3049853 .1429018
aggr_fertilizer_cost | .001695 .0006072 2.79 0.005 .0005024 .0028876
aggr_pesticide_cost | .0077112 .0029483 2.62 0.009 .0019206 .0135019
aggr_herbicide_cost | .0159355 .0085507 1.86 0.063 -.0008586 .0327296
aggr_family_labor | .043193 .0156041 2.77 0.006 .0125456 .0738403
aggr_total_wage | .0003289 .0013468 0.24 0.807 -.0023163 .0029741
_cons | -15.98439 6.070288 -2.63 0.009 -27.90677 -4.06201
---------------------------+----------------------------------------------------------------
q80 |
hci | 44.28434 8.577305 5.16 0.000 27.43804 61.13065
|
treatment |
control | 12.84738 9.918889 1.30 0.196 -6.633872 32.32862
pure control | 13.52576 9.351321 1.45 0.149 -4.840752 31.89227
|
treatment#c.hci |
control | -20.69357 8.480722 -2.44 0.015 -37.35018 -4.03696
pure control | -22.18628 11.33877 -1.96 0.051 -44.45625 .0837021
|
who_d_sell_jbase |
women | -10.42858 9.482943 -1.10 0.272 -29.0536 8.196448
men | 6.35468 8.86405 0.72 0.474 -11.05481 23.76417
|
treatment#who_d_sell_jbase |
control#women | 1.108775 10.81768 0.10 0.918 -20.13775 22.3553
control#men | -4.459718 10.60189 -0.42 0.674 -25.28242 16.36299
pure control#women | 1.254163 21.67506 0.06 0.954 -41.31686 43.82518
pure control#men | -7.464321 9.859976 -0.76 0.449 -26.82986 11.90122
|
age_hh | -.2780977 .112034 -2.48 0.013 -.4981386 -.0580568
educ_hh | -.5737076 .3428868 -1.67 0.095 -1.247156 .0997412
sex_hh | 4.279397 3.927358 1.09 0.276 -3.434151 11.99295
no_adult_female | .3192048 1.352893 0.24 0.814 -2.337953 2.976362
no_adult_male | -.6033649 1.660308 -0.36 0.716 -3.864301 2.657571
exp_horticulture | .9490994 .3107408 3.05 0.002 .3387872 1.559412
landsize_horti | 6.60538 4.017384 1.64 0.101 -1.284983 14.49574
total_tlu | 1.24648 1.228933 1.01 0.311 -1.167213 3.660172
dist_main_mkt_minutes | .0073455 .0286026 0.26 0.797 -.0488316 .0635226
dist_coop_minutes | -.0090014 .0237244 -0.38 0.705 -.0555974 .0375947
training | 3.720342 2.3862 1.56 0.120 -.9662861 8.40697
extension_freq | .3950899 .4739242 0.83 0.405 -.5357236 1.325903
aggr_fertilizer_cost | .0047735 .0016071 2.97 0.003 .0016171 .0079298
aggr_pesticide_cost | -.0001778 .0075955 -0.02 0.981 -.0150957 .0147402
aggr_herbicide_cost | .0121422 .0163661 0.74 0.458 -.0200017 .0442862
aggr_family_labor | .1280472 .0666859 1.92 0.055 -.0029276 .2590221
aggr_total_wage | .0017052 .0029141 0.59 0.559 -.0040183 .0074287
_cons | -21.96267 10.75125 -2.04 0.042 -43.07873 -.8466061
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qr_interaction_24092023.txt
