感谢回复，初入论坛经验不足，请大家海涵~
1.以下为数据处理代码：
clear
use "E:\学术小天地\房子与幸福感\data\2017年家庭金融调查数据库\2017年家庭金融调查数据_数据集_13版\chfs2017_master_city_20191120.dta", clear
keep hhid province rural swgt_h swgt_p
sort hhid
save province_house, replace
use "E:\学术小天地\房子与幸福感\data\2017年家庭金融调查数据库\2017年家庭金融调查数据_数据集_13版\ind2017_20191202_所有.dta", clear
keep hhid a2001 a2005 a2012 a2024 a2003 a2025b
gen age = 2017 - a2005
gen age2 = age^2
drop a2005
rename a2012 edu
***初中及以下***
replace edu = 1 if edu == 1 | edu == 2 | edu == 3
***高中、中专、职高***
replace edu = 2 if edu == 4 | edu == 5
***大专***
replace edu = 3 if edu ==6
***本科、硕士、博士***
replace edu = 4 if edu == 7 | edu == 8 | edu == 9
rename a2024 marital
replace marital = 0 if marital == 1 | marital == 3 | marital == 4 | marital == 5 | marital == 6
replace marital = 1 if marital == 2 | marital == 7
rename a2003 gender
replace gender = 0 if gender == 2
rename a2025b health
replace health = 7 if health == 1
replace health = 6 if health == 2
replace health = 2 if health == 4
replace health = 1 if health == 5
replace health = 5 if health == 7
replace health = 4 if health == 6
sort hhid
merge m:m hhid using province_house,update
drop _merge
sort hhid
save ind_house, replace
use "E:\学术小天地\房子与幸福感\data\2017年家庭金融调查数据库\2017年家庭金融调查数据_数据集_13版\hh2017_20191120_所有.dta", clear
keep hhid total_income h3514 c1001 c1004 c2004_1 c2004_2 c2004_3 c2004_4 c2004_5 c2004_6 c2008b_1 c2008b_2 c2008b_3 c2008b_4 c2008b_5 c2008b_6
rename total_income income
gen lnincome = log(income)
rename h3514 happiness
replace happiness = 7 if happiness == 1
replace happiness = 6 if happiness == 2
replace happiness = 2 if happiness == 4
replace happiness = 1 if happiness == 5
replace happiness = 5 if happiness == 7
replace happiness = 4 if happiness == 6
rename c1001 htype
gen property = 0
replace property = 1 if htype == 1
gen hsquare = c1004 if htype == 2 | htype == 3
replace hsquare = c2004_1 if c2008b_1 == 1
replace hsquare = c2004_2 if c2008b_2 == 1
replace hsquare = c2004_3 if c2008b_3 == 1
replace hsquare = c2004_4 if c2008b_4 == 1
replace hsquare = c2004_5 if c2008b_5 == 1
replace hsquare = c2004_6 if c2008b_6 == 1
drop c1004 c2004_1 c2004_2 c2004_3 c2004_4 c2004_5 c2004_6 c2008b_1 c2008b_2 c2008b_3 c2008b_4 c2008b_5 c2008b_6
sort hhid
merge m:m hhid using ind_house,update
drop _merge
save hh_house, replace
import excel "E:\学术小天地\房子与幸福感\data\2017房价数据-省-年度.xls", sheet("Sheet1") firstrow clear
keep A D
rename A provincestr
rename D hprice
gen lnhprice = log(hprice)
sort provincestr
save hprice, replace
use hh_house, clear
decode province, gen(provincestr)
sort provincestr
merge m:1 provincestr using hprice
drop _merge
drop provincestr
drop if a2001 !=1
drop a2001
egen miss = rowmiss(_all)
drop if miss != 0
drop miss
winsor2 income hsquare age, replace cuts (1 99)
sum happiness hprice income age edu marital gender health rural property hsquare
save full_data1, replace
2. 执行以上命令2次，得到相同的描述性统计，如下：
（1）第一次结果：
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
happiness | 18323 3.84091 .8188524 1 5
hprice | 18323 9934.169 7090.194 4165 34117
income | 18323 91898.81 119020.5 193.085 788576.5
age | 18323 52.64007 16.08309 20 85
edu | 18323 1.734214 1.03079 1 4
-------------+--------------------------------------------------------
marital | 18323 .7960487 .4029442 0 1
gender | 18323 .5028653 .5000054 0 1
health | 18323 3.454947 .9993328 1 5
rural | 18323 .2262184 .4183936 0 1
property | 18323 .6840583 .4649025 0 1
-------------+--------------------------------------------------------
hsquare | 18323 84.17151 64.1467 10 400
（2）第二次结果：
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
happiness | 18323 3.84091 .8188524 1 5
hprice | 18323 9934.169 7090.194 4165 34117
income | 18323 91898.81 119020.5 193.085 788576.5
age | 18323 52.64007 16.08309 20 85
edu | 18323 1.734214 1.03079 1 4
-------------+--------------------------------------------------------
marital | 18323 .7960487 .4029442 0 1
gender | 18323 .5028653 .5000054 0 1
health | 18323 3.454947 .9993328 1 5
rural | 18323 .2262184 .4183936 0 1
property | 18323 .6840583 .4649025 0 1
-------------+--------------------------------------------------------
hsquare | 18323 84.17151 64.1467 10 400
3. 执行oprobit回归命令2次，得到不同的结果：
（1）第一次结果：
Ordered probit regression Number of obs = 18323
Wald chi2(13) = 700.97
Prob > chi2 = 0.0000
Log pseudolikelihood = -1.744e+08 Pseudo R2 = 0.0355
------------------------------------------------------------------------------
| Robust
happiness | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lnhprice | -.0438804 .0241215 -1.82 0.069 -.0911576 .0033968
lnincome | .0449901 .0086231 5.22 0.000 .0280891 .061891
age | -.0413227 .0048145 -8.58 0.000 -.050759 -.0318865
age2 | .0005369 .0000456 11.76 0.000 .0004475 .0006264
|
edu |
2 | .0098188 .0307178 0.32 0.749 -.0503869 .0700245
3 | -.0010152 .0414455 -0.02 0.980 -.0822468 .0802164
4 | .0133474 .0405819 0.33 0.742 -.0661917 .0928864
|
1.marital | .2308472 .0334034 6.91 0.000 .1653778 .2963167
1.gender | -.0590439 .0240239 -2.46 0.014 -.1061299 -.011958
health | .2214292 .0141692 15.63 0.000 .1936581 .2492002
1.rural | .0914092 .0338109 2.70 0.007 .025141 .1576774
1.property | .0562409 .0269148 2.09 0.037 .0034889 .1089929
hsquare | .0008728 .0002046 4.27 0.000 .0004719 .0012737
-------------+----------------------------------------------------------------
/cut1 | -1.8893 .2498203 -2.378938 -1.399661
/cut2 | -1.143309 .2464571 -1.626356 -.6602623
/cut3 | .0497612 .2476107 -.4355468 .5350692
/cut4 | 1.471006 .2485265 .9839029 1.958109
------------------------------------------------------------------------------
（2）第二次结果：
Ordered probit regression Number of obs = 18323
Wald chi2(13) = 735.30
Prob > chi2 = 0.0000
Log pseudolikelihood = -1.738e+08 Pseudo R2 = 0.0362
------------------------------------------------------------------------------
| Robust
happiness | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lnhprice | -.0369084 .023801 -1.55 0.121 -.0835576 .0097408
lnincome | .0455094 .0085176 5.34 0.000 .0288151 .0622037
age | -.0418628 .0047311 -8.85 0.000 -.0511356 -.03259
age2 | .0005423 .0000448 12.11 0.000 .0004546 .0006301
|
edu |
2 | .0162418 .0303299 0.54 0.592 -.0432036 .0756873
3 | -.0023572 .0416904 -0.06 0.955 -.0840689 .0793544
4 | .0094391 .0403457 0.23 0.815 -.0696371 .0885153
|
1.marital | .2280683 .0330819 6.89 0.000 .163229 .2929076
1.gender | -.0592456 .0240172 -2.47 0.014 -.1063184 -.0121727
health | .2247194 .014199 15.83 0.000 .1968898 .252549
1.rural | .0988372 .0337502 2.93 0.003 .0326879 .1649864
1.property | .0616099 .0268107 2.30 0.022 .0090618 .114158
hsquare | .0008722 .0002068 4.22 0.000 .0004668 .0012776
-------------+----------------------------------------------------------------
/cut1 | -1.817774 .2496122 -2.307005 -1.328543
/cut2 | -1.075892 .2459997 -1.558042 -.593741
/cut3 | .1208648 .2468216 -.3628966 .6046261
/cut4 | 1.545501 .2475751 1.060263 2.03074
------------------------------------------------------------------------------
问题：两次回归结果存在差异，可能是什么原因导致的？感谢各位大佬赐教~
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