Keeping only households with one wife and one husband

[Enrique Alameda]

// Generating indicators for husband, wife, son, and daughter
gen is_wife = (sex == 3 & (relationtohead == 1 | relationtohead == 2))
gen is_husband = (sex == 1 & (relationtohead == 1 | relationtohead == 2))
gen is_daughter = (sex == 3 & (relationtohead == 3 | relationtohead == 4))
gen is_son = (sex == 1 & (relationtohead == 3 | relationtohead == 4))

// Checking the number of husbands and wives in each household and wave
bysort household_id wave: egen wives_per_wave = total(is_wife)
bysort household_id wave: egen husbands_per_wave = total(is_husband)

// Determining if there is at most one husband and one wife in each household
bys household_id: egen max_husbands = max(husbands_per_wave)
bys household_id: egen max_wives = max(wives_per_wave)
bys household_id: gen unique_husband = (max_husbands == 1)
bys household_id: gen unique_wife = (max_wives == 1)

// Keeping households with at most one husband and one wife
bys household_id: keep if unique_husband == 1 & unique_wife == 1

However, although when browsing the data it appears that there is only when husband and one wife (across various waves) for each household, when I do:

distinct pidlink if is_wife == 1 and distinct pidlink if is_husband == 1, I still get more wives than husbands (regardless of waves given the distinct command. Thus, implying, that I have kept households where more than one wife exists).

I provide a data example below:

clear
input str10(household_id person_id) float(wave is_husband is_wife)
"0010651" "001060004" 5 0 1
"0010651" "001065102" 5 1 0
"0010651" "001065103" 5 0 0
"0010651" "001065104" 5 0 0
"0010851" "001080003" 5 1 0
"0010851" "001080012" 5 0 1
"0010851" "001085103" 5 0 0
"0010851" "001085104" 5 0 0
"0010851" "001085105" 5 0 0
"0010851" "001085106" 5 0 0
"0010851" "001085107" 5 0 0
"0012200" "001220001" 1 1 0
"0012200" "001220001" 2 1 0
"0012200" "001220001" 3 1 0
"0012200" "001220001" 4 1 0
"0012200" "001220001" 5 1 0
"0012200" "001220002" 1 0 1
"0012200" "001220002" 2 0 1
"0012200" "001220002" 3 0 1
"0012200" "001220002" 4 0 1
"0012200" "001220002" 5 0 1
"0012200" "001220003" 1 0 0
"0012200" "001220003" 2 0 0
"0012200" "001220003" 3 0 0
"0012241" "001220003" 4 1 0
"0012241" "001220003" 5 1 0
"0012200" "001220004" 1 0 0
"0012200" "001220004" 2 0 0
"0012200" "001220004" 3 0 0
"0012200" "001220004" 4 0 0
"0012200" "001220004" 5 0 0
"0012200" "001220005" 1 0 0
"0012200" "001220005" 2 0 0
"0012200" "001220005" 3 0 0
"0012200" "001220005" 4 0 0
"0012200" "001220005" 5 0 0
"0012200" "001220006" 1 0 0
"0012200" "001220006" 2 0 0
"0012200" "001220006" 3 0 0
"0012200" "001220006" 4 0 0
"0012200" "001220006" 5 0 0
"0012200" "001220007" 1 0 0
"0012200" "001220007" 2 0 0
"0012200" "001220007" 3 0 0
"0012200" "001220007" 4 0 0
"0012200" "001220007" 5 0 0
"0012200" "001220008" 1 0 0
"0012200" "001220008" 2 0 0
"0012200" "001220008" 3 0 0
"0012200" "001220009" 1 0 0
"0012200" "001220009" 2 0 0
"0012200" "001220009" 3 0 0
"0012200" "001220009" 4 0 0
"0012200" "001220010" 1 0 0
"0012200" "001220010" 2 0 0
"0012200" "001220010" 3 0 0
"0012200" "001220010" 4 0 0
"0012200" "001220010" 5 0 0
"0012241" "001220011" 4 0 1
"0012241" "001220011" 5 0 1
"0012241" "001220013" 4 0 0
"0012241" "001220013" 5 0 0
"0012200" "001220014" 4 0 0
"0012200" "001220014" 5 0 0
"0012200" "001220015" 4 0 0
"0012200" "001220015" 5 0 0
"0012241" "001224104" 4 0 0
"0012241" "001224104" 5 0 0
"0012241" "001224105" 4 0 0
"0012241" "001224105" 5 0 0
"0012241" "001224106" 5 0 0
"0012400" "001240001" 1 1 0
"0012400" "001240001" 2 1 0
"0012400" "001240001" 5 1 0
"0012400" "001240002" 1 0 1
"0012400" "001240002" 2 0 1
"0012400" "001240002" 5 0 1
"0012400" "001240003" 1 0 0
"0012400" "001240003" 2 0 0
"0012400" "001240003" 5 0 0
"0012400" "001240004" 1 0 0
"0012400" "001240004" 2 0 0
"0012400" "001240004" 5 0 0
"0012400" "001240005" 1 0 0
"0012400" "001240005" 2 0 0
"0012451" "001240005" 5 0 1
"0012400" "001240006" 1 0 0
"0012400" "001240006" 2 0 0
"0012400" "001240006" 5 0 0
"0012400" "001240007" 1 0 0
"0012400" "001240007" 2 0 0
"0012400" "001240007" 5 0 0
"0012400" "001240008" 1 0 0
"0012400" "001240008" 2 0 0
"0012400" "001240008" 5 0 0
"0012400" "001240009" 1 0 0
"0012400" "001240009" 2 0 0
"0012452" "001240009" 5 0 1
"0012400" "001240010" 1 0 0
"0012400" "001240010" 2 0 0

Thank you in advance,

Enrique

[Devra Golbe]

Hi Enrique,

Thank you for supplying some sample data.

list if inlist(household, "0012451", "0012452")

produces the following, indicating that your sample data contain two household-wave pairs where there is a wife but no husband.

     +--------------------------------------------------+
     | househ~d   person_id   wave   is_hus~d   is_wife |
     |--------------------------------------------------|
 86. |  0012451   001240005      5          0         1 |
 98. |  0012452   001240009      5          0         1 |
     +--------------------------------------------------+

When I run the following part of your code those two observations are dropped. Note that they satisfy the condition in the comment -- "at most one husband and one wife"-- though not the condition "exactly one husband and one wife" your code appears to check for.

// Checking the number of husbands and wives in each household and wave
bysort household_id wave: egen wives_per_wave = total(is_wife)
bysort household_id wave: egen husbands_per_wave = total(is_husband)

// Determining if there is at most one husband and one wife in each household
bys household_id: egen max_husbands = max(husbands_per_wave)
bys household_id: egen max_wives = max(wives_per_wave)
bys household_id: gen unique_husband = (max_husbands == 1)
bys household_id: gen unique_wife = (max_wives == 1)

bys household_id: keep if unique_husband == 1 & unique_wife == 1

pidlink is not defined, so I can't comment on that part of your code.

[George Ford]

drop if state=="Utah"

[Enrique Alameda]

Hi Enrique,

Thank you for supplying some sample data.

list if inlist(household, "0012451", "0012452")

produces the following, indicating that your sample data contain two household-wave pairs where there is a wife but no husband.

+--------------------------------------------------+
| househ~d person_id wave is_hus~d is_wife |
|--------------------------------------------------|
86. | 0012451 001240005 5 0 1 |
98. | 0012452 001240009 5 0 1 |
+--------------------------------------------------+

When I run the following part of your code those two observations are dropped. Note that they satisfy the condition in the comment -- "at most one husband and one wife"-- though not the condition "exactly one husband and one wife" your code appears to check for.

// Checking the number of husbands and wives in each household and wave
bysort household_id wave: egen wives_per_wave = total(is_wife)
bysort household_id wave: egen husbands_per_wave = total(is_husband)

// Determining if there is at most one husband and one wife in each household
bys household_id: egen max_husbands = max(husbands_per_wave)
bys household_id: egen max_wives = max(wives_per_wave)
bys household_id: gen unique_husband = (max_husbands == 1)
bys household_id: gen unique_wife = (max_wives == 1)

bys household_id: keep if unique_husband == 1 & unique_wife == 1

pidlink is not defined, so I can't comment on that part of your code.

Hi Devra,

Thank you so much for your help. Pidlink is actually person_id in the data example. Do you know how I could change the code to exactly one husband and one wife?

Thanks a lot,

Enrique

[George Ford]

bys household wave: egen husbandwife = total(is_husband + is_wife)

looking for a 2

[Enrique Alameda]

bys household wave: egen husbandwife = total(is_husband + is_wife)

looking for a 2

Hi George,

Thanks a lot, this is a smart and elegant solution.

However, some wives appear in certain waves where husbands do not (although both are present in the household). This causes the "distinct pidlink if is_husband == 1" to yield slightly different distinct values to "distinct pidlink if is_wife == 1" (i.e., there are still slightly more wives than husbands) upon keeping instances where husbandwife == 2. Do you know how I can fix this?

Thanks a lot,

Enrique.

[Devra Golbe]

Enrique,

I think your code gives exactly one husband and one wife. Indeed, when I run George's code after the code I quoted in my post husbandwife =2 for all observations. And when I run

distinct person_id if is_wife == 1
distinct person_id if is_husb == 1

I get identical results from each command.

Perhaps you need to supply a different sample of observations in order to illustrate the issues you are having.

[Enrique Alameda]

Enrique,

I think your code gives exactly one husband and one wife. Indeed, when I run George's code after the code I quoted in my post husbandwife =2 for all observations. And when I run

distinct person_id if is_wife == 1
distinct person_id if is_husb == 1

I get identical results from each command.

Perhaps you need to supply a different sample of observations in order to illustrate the issues you are having.

Hi Devra and George,

Here is a data example prior to running mine or George's code. I have changed notation to make it easier to understand:

clear
input str10(pidlink hhid) float(wave husband wife)
"272010001" "2720100" 1 1 0
"272010001" "2720100" 2 1 0
"272010001" "2720100" 3 1 0
"272010001" "2720100" 4 1 0
"272010001" "2720100" 5 1 0
"272010002" "2720100" 1 0 1
"272010002" "2720100" 2 0 1
"272010002" "2720100" 3 0 1
"272010002" "2720100" 4 0 1
"272010002" "2720151" 5 0 0
"272010003" "2720100" 1 0 0
"272010003" "2720100" 2 0 0
"272010003" "2720100" 3 0 0
"272010003" "2720100" 4 0 0
"272010003" "2720100" 5 0 0
"272010004" "2720100" 2 0 0
"272010004" "2720100" 3 0 0
"272010004" "2720100" 4 0 0
"272010004" "2720100" 5 0 0
"272010005" "2720100" 5 0 0
"272010006" "2720100" 5 0 1
"272020001" "2720200" 1 1 0
"272020001" "2720211" 2 1 0
"272020001" "2720211" 3 1 0
"272020001" "2720211" 4 1 0
"272020001" "2720211" 5 1 0
"272020002" "2720200" 1 0 1
"272020002" "2720211" 2 0 1
"272020002" "2720211" 3 0 1
"272020002" "2720211" 4 0 1
"272020002" "2720211" 5 0 1
"272020003" "2720200" 1 0 0
"272020003" "2720211" 2 0 0
"272020003" "2720211" 3 0 0
"272020003" "2720211" 4 0 0
"272020003" "2720211" 5 0 0
"272020004" "2720200" 2 1 0
"272020004" "2720200" 3 1 0
"272020004" "2720200" 4 1 0
"272020004" "2720200" 5 1 0
"272020005" "2720200" 2 0 1
"272020005" "2720200" 3 0 1
"272020005" "2720200" 4 0 1
"272020005" "2720200" 5 0 0
"272021104" "2720211" 2 0 0
"272021104" "2720211" 3 0 0
"272021104" "2720211" 4 0 0
"272021104" "2720211" 5 0 0
"272030001" "2720300" 1 1 0
"272030001" "2720300" 2 1 0
"272030001" "2720300" 3 1 0
"272030001" "2720300" 4 1 0
"272030001" "2720300" 5 1 0
"272030002" "2720300" 1 0 1
"272030002" "2720300" 2 0 1
"272030002" "2720300" 3 0 1
"272030002" "2720300" 4 0 1
"272030002" "2720300" 5 0 1
"272030003" "2720300" 1 0 0
"272030003" "2720300" 2 0 0
"272030003" "2720300" 3 0 0
"272030003" "2720341" 4 0 1
"272030004" "2720300" 2 0 0
"272030004" "2720300" 3 0 0
"272030004" "2720300" 4 0 0
"272030004" "2720300" 5 0 0
"272030005" "2720300" 3 0 0
"272030005" "2720300" 4 0 0
"272030005" "2720300" 5 0 0
"272034101" "2720341" 4 1 0
"272034101" "2720341" 5 0 0
"272034103" "2720341" 4 0 0
"272034104" "2720341" 5 1 0
"272040001" "2720400" 1 1 0
"272040001" "2720400" 2 1 0
"272040001" "2720400" 3 1 0
"272040001" "2720400" 4 1 0
"272040001" "2720400" 5 1 0
"272040002" "2720400" 1 0 1
"272040002" "2720400" 2 0 1
"272040002" "2720400" 3 0 1
"272040002" "2720400" 4 0 1
"272040002" "2720400" 5 0 1
"272040003" "2720400" 1 0 0
"272040003" "2720400" 2 0 0
"272040003" "2720400" 3 0 0
"272040003" "2720400" 4 0 0
"272040003" "2720451" 5 1 0
"272040004" "2720400" 1 0 0
"272040004" "2720400" 2 0 0
"272040004" "2720400" 3 0 0
"272040004" "2720400" 4 0 0
"272040004" "2720400" 5 0 0
"272040005" "2720400" 4 0 0
"272040005" "2720400" 5 0 0
"272050001" "2720500" 1 1 0
"272050001" "2720500" 2 1 0
"272050001" "2720500" 3 1 0
"272050001" "2720500" 4 1 0
"272050001" "2720500" 5 1 0
end


Upon running the code, if I do:

keep if husbandwife == 2
(41,234 observations deleted)

And then the distinct:

. distinct pidlink if wife == 1

| Observations
| total distinct
---------+----------------------
pidlink | 39619 15910

. distinct pidlink if husband == 1

| Observations
| total distinct
---------+----------------------
pidlink | 40025 16008



As you can see there is a different number of husband and wives. I provide a data example following this step below:

clear
input str10(pidlink hhid) float(wave husband wife)
"001060005" "0010600" 1 0 0
"001060006" "0010600" 1 0 0
"001060001" "0010600" 1 1 0
"001060002" "0010600" 1 0 1
"001060004" "0010600" 1 0 0
"001060003" "0010600" 1 0 0
"001060004" "0010600" 2 0 0
"001060002" "0010600" 2 0 1
"001060006" "0010600" 2 0 0
"001060005" "0010600" 2 0 0
"001060003" "0010600" 2 0 0
"001060001" "0010600" 2 1 0
"001065104" "0010651" 5 0 0
"001060004" "0010651" 5 0 1
"001065102" "0010651" 5 1 0
"001065103" "0010651" 5 0 0
"001080008" "0010800" 1 0 0
"001080006" "0010800" 1 0 0
"001080003" "0010800" 1 0 0
"001080005" "0010800" 1 0 0
"001080007" "0010800" 1 0 0
"001080009" "0010800" 1 0 0
"001080002" "0010800" 1 0 1
"001080010" "0010800" 1 0 0
"001080004" "0010800" 1 0 0
"001080001" "0010800" 1 1 0
"001080009" "0010800" 2 0 0
"001080008" "0010800" 2 0 0
"001080010" "0010800" 2 0 0
"001080001" "0010800" 2 1 0
"001080004" "0010800" 2 0 0
"001080006" "0010800" 2 0 0
"001080005" "0010800" 2 0 0
"001080003" "0010800" 2 0 0
"001080007" "0010800" 2 0 0
"001080002" "0010800" 2 0 1
"001085107" "0010851" 5 0 0
"001085104" "0010851" 5 0 0
"001085105" "0010851" 5 0 0
"001080012" "0010851" 5 0 1
"001080003" "0010851" 5 1 0
"001085106" "0010851" 5 0 0
"001085103" "0010851" 5 0 0
"001220009" "0012200" 1 0 0
"001220008" "0012200" 1 0 0
"001220002" "0012200" 1 0 1
"001220001" "0012200" 1 1 0
"001220003" "0012200" 1 0 0
"001220004" "0012200" 1 0 0
"001220006" "0012200" 1 0 0
"001220005" "0012200" 1 0 0
"001220010" "0012200" 1 0 0
"001220007" "0012200" 1 0 0
"001220010" "0012200" 2 0 0
"001220001" "0012200" 2 1 0
"001220004" "0012200" 2 0 0
"001220002" "0012200" 2 0 1
"001220008" "0012200" 2 0 0
"001220006" "0012200" 2 0 0
"001220009" "0012200" 2 0 0
"001220007" "0012200" 2 0 0
"001220005" "0012200" 2 0 0
"001220003" "0012200" 2 0 0
"001220009" "0012200" 3 0 0
"001220002" "0012200" 3 0 1
"001220003" "0012200" 3 0 0
"001220007" "0012200" 3 0 0
"001220001" "0012200" 3 1 0
"001220005" "0012200" 3 0 0
"001220008" "0012200" 3 0 0
"001220010" "0012200" 3 0 0
"001220006" "0012200" 3 0 0
"001220004" "0012200" 3 0 0
"001220004" "0012200" 4 0 0
"001220007" "0012200" 4 0 0
"001220006" "0012200" 4 0 0
"001220001" "0012200" 4 1 0
"001220005" "0012200" 4 0 0
"001220009" "0012200" 4 0 0
"001220002" "0012200" 4 0 1
"001220014" "0012200" 4 0 0
"001220015" "0012200" 4 0 0
"001220010" "0012200" 4 0 0
"001220004" "0012200" 5 0 0
"001220006" "0012200" 5 0 0
"001220007" "0012200" 5 0 0
"001220014" "0012200" 5 0 0
"001220002" "0012200" 5 0 1
"001220005" "0012200" 5 0 0
"001220015" "0012200" 5 0 0
"001220001" "0012200" 5 1 0
"001220010" "0012200" 5 0 0
"001220003" "0012241" 4 1 0
"001224104" "0012241" 4 0 0
"001224105" "0012241" 4 0 0
"001220011" "0012241" 4 0 1
"001220013" "0012241" 4 0 0
"001220003" "0012241" 5 1 0
"001220013" "0012241" 5 0 0
"001224105" "0012241" 5 0 0
end
[/CODE]


I am grateful for any help, as I cannot comprehend my mistake.

Thank you in advance,

Enrique

[George Ford]

I get the same with this.

bys hhid wave: egen husbandwife = total(husband + wife)

. keep if husbandwife==2
(3 observations deleted)

. 
. distinct pidlink if wife == 1


total   distinct

pidlink         12          6


. distinct pidlink if husband ==    1


total   distinct

pidlink         12          6


. 
. distinct hhid if wife == 1


total   distinct

hhid         12          6


. distinct hhid if husband == 1


total   distinct

hhid         12          6

[George Ford]

If the problem is missing data, then any solution is going to be a bit of a kluge.

One option is to assume that if it's 2 2 1 2 2, then it should be a 2 in between due to missing values. I'd have more confidence if the household member count followed the same pattern.

bys hhid wave: egen hhsize = count(hhid)

[Enrique Alameda]

If the problem is missing data, then any solution is going to be a bit of a kluge.

One option is to assume that if it's 2 2 1 2 2, then it should be a 2 in between due to missing values. I'd have more confidence if the household member count followed the same pattern.

bys hhid wave: egen hhsize = count(hhid)

Hi George,

Thanks a lot for all your help.

Here is the output from your code. Note that the dataset also contains sons and daughters of these couples (i.e., to identify child-wife pairs):

bys hhid wave: egen hhsize = count(hhid)

.
end of do-file

. ta hhsize

hhsize | Freq. Percent Cum.
------------+-----------------------------------
2 | 10,314 5.96 5.96
3 | 34,371 19.88 25.84
4 | 48,292 27.93 53.77
5 | 36,365 21.03 74.80
6 | 21,594 12.49 87.28
7 | 11,137 6.44 93.72
8 | 6,056 3.50 97.23
9 | 2,943 1.70 98.93
10 | 1,160 0.67 99.60
11 | 495 0.29 99.88
12 | 132 0.08 99.96
13 | 52 0.03 99.99
15 | 15 0.01 100.00
------------+-----------------------------------
Total | 172,926 100.00

[George Ford]

This might get you started. I've dropped the middle observation of wife for hhid==0012200 to create some interest.

I think the kids condition may be redundant in markreplace.

The math to address a change in kids should be easy enough to implement, but this might tell you how big the problem is.

clear
input str10(pidlink hhid) float(wave husband wife)
"001060005" "0010600" 1 0 0
"001060006" "0010600" 1 0 0
"001060001" "0010600" 1 1 0
"001060002" "0010600" 1 0 1
"001060004" "0010600" 1 0 0
"001060003" "0010600" 1 0 0
"001060004" "0010600" 2 0 0
"001060002" "0010600" 2 0 1
"001060006" "0010600" 2 0 0
"001060005" "0010600" 2 0 0
"001060003" "0010600" 2 0 0
"001060001" "0010600" 2 1 0
"001065104" "0010651" 5 0 0
"001060004" "0010651" 5 0 1
"001065102" "0010651" 5 1 0
"001065103" "0010651" 5 0 0
"001080008" "0010800" 1 0 0
"001080006" "0010800" 1 0 0
"001080003" "0010800" 1 0 0
"001080005" "0010800" 1 0 0
"001080007" "0010800" 1 0 0
"001080009" "0010800" 1 0 0
"001080002" "0010800" 1 0 1
"001080010" "0010800" 1 0 0
"001080004" "0010800" 1 0 0
"001080001" "0010800" 1 1 0
"001080009" "0010800" 2 0 0
"001080008" "0010800" 2 0 0
"001080010" "0010800" 2 0 0
"001080001" "0010800" 2 1 0
"001080004" "0010800" 2 0 0
"001080006" "0010800" 2 0 0
"001080005" "0010800" 2 0 0
"001080003" "0010800" 2 0 0
"001080007" "0010800" 2 0 0
"001080002" "0010800" 2 0 1
"001085107" "0010851" 5 0 0
"001085104" "0010851" 5 0 0
"001085105" "0010851" 5 0 0
"001080012" "0010851" 5 0 1
"001080003" "0010851" 5 1 0
"001085106" "0010851" 5 0 0
"001085103" "0010851" 5 0 0
"001220009" "0012200" 1 0 0
"001220008" "0012200" 1 0 0
"001220002" "0012200" 1 0 1
"001220001" "0012200" 1 1 0
"001220003" "0012200" 1 0 0
"001220004" "0012200" 1 0 0
"001220006" "0012200" 1 0 0
"001220005" "0012200" 1 0 0
"001220010" "0012200" 1 0 0
"001220007" "0012200" 1 0 0
"001220010" "0012200" 2 0 0
"001220001" "0012200" 2 1 0
"001220004" "0012200" 2 0 0
"001220002" "0012200" 2 0 1
"001220008" "0012200" 2 0 0
"001220006" "0012200" 2 0 0
"001220009" "0012200" 2 0 0
"001220007" "0012200" 2 0 0
"001220005" "0012200" 2 0 0
"001220003" "0012200" 2 0 0
"001220009" "0012200" 3 0 0
/*"001220002" "0012200" 3 0 1*/
"001220003" "0012200" 3 0 0
"001220007" "0012200" 3 0 0
"001220001" "0012200" 3 1 0
"001220005" "0012200" 3 0 0
"001220008" "0012200" 3 0 0
"001220010" "0012200" 3 0 0
"001220006" "0012200" 3 0 0
"001220004" "0012200" 3 0 0
"001220004" "0012200" 4 0 0
"001220007" "0012200" 4 0 0
"001220006" "0012200" 4 0 0
"001220001" "0012200" 4 1 0
"001220005" "0012200" 4 0 0
"001220009" "0012200" 4 0 0
"001220002" "0012200" 4 0 1
"001220014" "0012200" 4 0 0
"001220015" "0012200" 4 0 0
"001220010" "0012200" 4 0 0
"001220004" "0012200" 5 0 0
"001220006" "0012200" 5 0 0
"001220007" "0012200" 5 0 0
"001220014" "0012200" 5 0 0
"001220002" "0012200" 5 0 1
"001220005" "0012200" 5 0 0
"001220015" "0012200" 5 0 0
"001220001" "0012200" 5 1 0
"001220010" "0012200" 5 0 0
"001220003" "0012241" 4 1 0
"001224104" "0012241" 4 0 0
"001224105" "0012241" 4 0 0
"001220011" "0012241" 4 0 1
"001220013" "0012241" 4 0 0
"001220003" "0012241" 5 1 0
"001220013" "0012241" 5 0 0
"001224105" "0012241" 5 0 0
end

bys hhid wave: egen husbandwife = total(husband + wife)
bys hhid wave: egen hhsize = count(hhid)
g kids = hhsize - husbandwife

bys hhid: egen max_husbandwife = max(husbandwife)
keep if max_husbandwife==2 // delete cases not desired

bys hhid: egen max_hhsize = max(hhsize)
bys hhid: egen max_kids = max(kids)
bys hhid: egen min_wave = min(wave)
bys hhid: egen max_wave = max(wave)

g markreplace = (husbandwife - max_husbandwife)==-1 & (hhsize - max_hhsize)==-1 & (kids==max_kids) & (wave != min_wave) & (wave != !max_wave)
* wave included as condition since you don't have data to either side to confirm.
g markcheck = (husbandwife - max_husbandwife)==-1 & (hhsize - max_hhsize)==-1 & (kids!=max_kids)
replace husbandwife = 2 if markreplace

[Devra Golbe]

Enrique,

The data sample you provide cannot be the data sample on which you ran your code (> 40,000 observations deleted.) Try to extract a small set of data which produces the phenomenon that concerns you: more distinct wives than husbands.

I suspect also that you will get better answers if you describe your data more fully. I guess that you are using some kind of household sample which is resurveyed multiple times (waves.) I don't know anything about this sample-- even how a household is defined. I would not be surprised if the number of children changes over time in the same HH ID. But suppose a head of household changes spouses. Does the HH ID change or stay the same? If the spouse who is not designated head of HH gets a new spouse does he drop out of the survey or get a new HH ID? I'm not certain, given the possible changes in HH composition, whether the numbers of distinct husbands & wives should be the same.

[Enrique Alameda]

Enrique,

The data sample you provide cannot be the data sample on which you ran your code (> 40,000 observations deleted.) Try to extract a small set of data which produces the phenomenon that concerns you: more distinct wives than husbands.

I suspect also that you will get better answers if you describe your data more fully. I guess that you are using some kind of household sample which is resurveyed multiple times (waves.) I don't know anything about this sample-- even how a household is defined. I would not be surprised if the number of children changes over time in the same HH ID. But suppose a head of household changes spouses. Does the HH ID change or stay the same? If the spouse who is not designated head of HH gets a new spouse does he drop out of the survey or get a new HH ID? I'm not certain, given the possible changes in HH composition, whether the numbers of distinct husbands & wives should be the same.

Hi George and Devra,

Thank you very much once again.

Please find below a subset of the actual data that produces the problem. Previously I was using dataex, which may not have reproduced the actual dataset well. Now I list 348 observations of the variables. Please find these below:

The dataset refers to a household survey where members are interviewed based on the relationship to the head of the household, in a context where husbands may have more than one wife. If a household head changes spouses, then that person is interviewed in the following wave and shows up with a new pidlink. If a daughter interviewed in a given wave gets married, becomes a wife and moves out of the household, she is re-interviewed keeping the same pidlink but a new hhid. Does this help?


+---------------------------------------------+
| pidlink hhid wave husband wife |
|---------------------------------------------|
1. | 001060001 0010600 1 1 0 |
2. | 001060001 0010600 2 1 0 |
3. | 001060002 0010600 1 0 1 |
4. | 001060002 0010600 2 0 1 |
5. | 001060003 0010600 1 0 0 |
|---------------------------------------------|
6. | 001060003 0010600 2 0 0 |
7. | 001060004 0010600 1 0 0 |
8. | 001060004 0010600 2 0 0 |
9. | 001060004 0010651 5 0 1 |
10. | 001060005 0010600 1 0 0 |
|---------------------------------------------|
11. | 001060005 0010600 2 0 0 |
12. | 001060006 0010600 1 0 0 |
13. | 001060006 0010600 2 0 0 |
14. | 001065102 0010651 5 1 0 |
15. | 001065103 0010651 5 0 0 |
|---------------------------------------------|
16. | 001065104 0010651 5 0 0 |
17. | 001080001 0010800 1 1 0 |
18. | 001080001 0010800 2 1 0 |
19. | 001080002 0010800 1 0 1 |
20. | 001080002 0010800 2 0 1 |
|---------------------------------------------|
21. | 001080003 0010800 1 0 0 |
22. | 001080003 0010800 2 0 0 |
23. | 001080003 0010851 5 1 0 |
24. | 001080004 0010800 1 0 0 |
25. | 001080004 0010800 2 0 0 |
|---------------------------------------------|
26. | 001080005 0010800 1 0 0 |
27. | 001080005 0010800 2 0 0 |
28. | 001080006 0010800 1 0 0 |
29. | 001080006 0010800 2 0 0 |
30. | 001080007 0010800 1 0 0 |
|---------------------------------------------|
31. | 001080007 0010800 2 0 0 |
32. | 001080008 0010800 1 0 0 |
33. | 001080008 0010800 2 0 0 |
34. | 001080009 0010800 1 0 0 |
35. | 001080009 0010800 2 0 0 |
|---------------------------------------------|
36. | 001080010 0010800 1 0 0 |
37. | 001080010 0010800 2 0 0 |
38. | 001080012 0010851 5 0 1 |
39. | 001085103 0010851 5 0 0 |
40. | 001085104 0010851 5 0 0 |
|---------------------------------------------|
41. | 001085105 0010851 5 0 0 |
42. | 001085106 0010851 5 0 0 |
43. | 001085107 0010851 5 0 0 |
44. | 001220001 0012200 1 1 0 |
45. | 001220001 0012200 2 1 0 |
|---------------------------------------------|
46. | 001220001 0012200 3 1 0 |
47. | 001220001 0012200 4 1 0 |
48. | 001220001 0012200 5 1 0 |
49. | 001220002 0012200 1 0 1 |
50. | 001220002 0012200 2 0 1 |
|---------------------------------------------|
51. | 001220002 0012200 3 0 1 |
52. | 001220002 0012200 4 0 1 |
53. | 001220002 0012200 5 0 1 |
54. | 001220003 0012200 1 0 0 |
55. | 001220003 0012200 2 0 0 |
|---------------------------------------------|
56. | 001220003 0012200 3 0 0 |
57. | 001220003 0012241 4 1 0 |
58. | 001220003 0012241 5 1 0 |
59. | 001220004 0012200 1 0 0 |
60. | 001220004 0012200 2 0 0 |
|---------------------------------------------|
61. | 001220004 0012200 3 0 0 |
62. | 001220004 0012200 4 0 0 |
63. | 001220004 0012200 5 0 0 |
64. | 001220005 0012200 1 0 0 |
65. | 001220005 0012200 2 0 0 |
|---------------------------------------------|
66. | 001220005 0012200 3 0 0 |
67. | 001220005 0012200 4 0 0 |
68. | 001220005 0012200 5 0 0 |
69. | 001220006 0012200 1 0 0 |
70. | 001220006 0012200 2 0 0 |
|---------------------------------------------|
71. | 001220006 0012200 3 0 0 |
72. | 001220006 0012200 4 0 0 |
73. | 001220006 0012200 5 0 0 |
74. | 001220007 0012200 1 0 0 |
75. | 001220007 0012200 2 0 0 |
|---------------------------------------------|
76. | 001220007 0012200 3 0 0 |
77. | 001220007 0012200 4 0 0 |
78. | 001220007 0012200 5 0 0 |
79. | 001220008 0012200 1 0 0 |
80. | 001220008 0012200 2 0 0 |
|---------------------------------------------|
81. | 001220008 0012200 3 0 0 |
82. | 001220009 0012200 1 0 0 |
83. | 001220009 0012200 2 0 0 |
84. | 001220009 0012200 3 0 0 |
85. | 001220009 0012200 4 0 0 |
|---------------------------------------------|
86. | 001220010 0012200 1 0 0 |
87. | 001220010 0012200 2 0 0 |
88. | 001220010 0012200 3 0 0 |
89. | 001220010 0012200 4 0 0 |
90. | 001220010 0012200 5 0 0 |
|---------------------------------------------|
91. | 001220011 0012241 4 0 1 |
92. | 001220011 0012241 5 0 1 |
93. | 001220013 0012241 4 0 0 |
94. | 001220013 0012241 5 0 0 |
95. | 001220014 0012200 4 0 0 |
|---------------------------------------------|
96. | 001220014 0012200 5 0 0 |
97. | 001220015 0012200 4 0 0 |
98. | 001220015 0012200 5 0 0 |
99. | 001224104 0012241 4 0 0 |
100. | 001224104 0012241 5 0 0 |
|---------------------------------------------|
101. | 001224105 0012241 4 0 0 |
102. | 001224105 0012241 5 0 0 |
103. | 001224106 0012241 5 0 0 |
104. | 001240001 0012400 1 1 0 |
105. | 001240001 0012400 2 1 0 |
|---------------------------------------------|
106. | 001240001 0012400 5 1 0 |
107. | 001240002 0012400 1 0 1 |
108. | 001240002 0012400 2 0 1 |
109. | 001240002 0012400 5 0 1 |
110. | 001240003 0012400 1 0 0 |
|---------------------------------------------|
111. | 001240003 0012400 2 0 0 |
112. | 001240003 0012400 5 0 0 |
113. | 001240004 0012400 1 0 0 |
114. | 001240004 0012400 2 0 0 |
115. | 001240004 0012400 5 0 0 |
|---------------------------------------------|
116. | 001240005 0012400 1 0 0 |
117. | 001240005 0012400 2 0 0 |
118. | 001240005 0012451 5 0 1 |
119. | 001240006 0012400 1 0 0 |
120. | 001240006 0012400 2 0 0 |
|---------------------------------------------|
121. | 001240006 0012400 5 0 0 |
122. | 001240007 0012400 1 0 0 |
123. | 001240007 0012400 2 0 0 |
124. | 001240007 0012400 5 0 0 |
125. | 001240008 0012400 1 0 0 |
|---------------------------------------------|
126. | 001240008 0012400 2 0 0 |
127. | 001240008 0012400 5 0 0 |
128. | 001240009 0012400 1 0 0 |
129. | 001240009 0012400 2 0 0 |
130. | 001240009 0012452 5 0 1 |
|---------------------------------------------|
131. | 001240010 0012400 1 0 0 |
132. | 001240010 0012400 2 0 0 |
133. | 001240010 0012400 5 0 0 |
134. | 001240014 0012400 2 0 0 |
135. | 001240014 0012400 5 0 0 |
|---------------------------------------------|
136. | 001245101 0012451 5 1 0 |
137. | 001245103 0012451 5 0 0 |
138. | 001245104 0012451 5 0 0 |
139. | 001245105 0012451 5 0 0 |
140. | 001245106 0012451 5 0 0 |
|---------------------------------------------|
141. | 001245107 0012451 5 0 0 |
142. | 001245201 0012452 5 1 0 |
143. | 001245203 0012452 5 0 0 |
144. | 001250001 0012500 1 1 0 |
145. | 001250001 0012500 2 1 0 |
|---------------------------------------------|
146. | 001250001 0012500 3 1 0 |
147. | 001250002 0012500 1 0 1 |
148. | 001250002 0012500 2 0 1 |
149. | 001250002 0012500 3 0 1 |
150. | 001250003 0012500 1 0 0 |
|---------------------------------------------|
151. | 001250003 0012500 2 0 0 |
152. | 001250003 0012500 3 0 0 |
153. | 001250004 0012500 1 0 0 |
154. | 001250004 0012500 2 0 0 |
155. | 001250004 0012500 3 0 0 |
|---------------------------------------------|
156. | 001250005 0012500 1 0 0 |
157. | 001250005 0012500 2 0 0 |
158. | 001250005 0012500 3 0 0 |
159. | 001250006 0012500 1 0 0 |
160. | 001250006 0012500 2 0 0 |
|---------------------------------------------|
161. | 001250006 0012500 3 0 0 |
162. | 001250007 0012500 1 0 0 |
163. | 001250007 0012500 2 0 0 |
164. | 001250007 0012500 3 0 0 |
165. | 001290001 0012900 1 1 0 |
|---------------------------------------------|
166. | 001290001 0012900 2 1 0 |
167. | 001290001 0012900 3 1 0 |
168. | 001290001 0012900 4 1 0 |
169. | 001290002 0012900 1 0 1 |
170. | 001290002 0012900 2 0 1 |
|---------------------------------------------|
171. | 001290002 0012900 3 0 1 |
172. | 001290002 0012900 4 0 1 |
173. | 001290003 0012900 1 0 0 |
174. | 001290003 0012900 2 0 0 |
175. | 001290003 0012900 3 0 0 |
|---------------------------------------------|
176. | 001290003 0012900 4 0 0 |
177. | 001290003 0012951 5 0 1 |
178. | 001290004 0012900 1 0 0 |
179. | 001290004 0012900 2 0 0 |
180. | 001290004 0012900 3 0 0 |
|---------------------------------------------|
181. | 001290004 0012900 4 0 0 |
182. | 001290004 0012952 5 1 0 |
183. | 001290005 0012900 1 0 0 |
184. | 001290005 0012900 2 0 0 |
185. | 001290005 0012900 3 0 0 |
|---------------------------------------------|
186. | 001290005 0012900 4 0 0 |
187. | 001290005 0012953 5 1 0 |
188. | 001290006 0012900 1 0 0 |
189. | 001290006 0012900 2 0 0 |
190. | 001290006 0012900 3 0 0 |
|---------------------------------------------|
191. | 001290006 0012900 4 0 0 |
192. | 001290007 0012900 2 0 0 |
193. | 001290007 0012900 3 0 0 |
194. | 001290007 0012900 4 0 0 |
195. | 001290008 0012900 3 0 0 |
|---------------------------------------------|
196. | 001290008 0012900 4 0 0 |
197. | 001290010 0012900 4 0 0 |
198. | 001290011 0012900 4 0 0 |
199. | 001295101 0012951 5 1 0 |
200. | 001295103 0012951 5 0 0 |
|---------------------------------------------|
201. | 001295104 0012951 5 0 0 |
202. | 001295105 0012951 5 0 0 |
203. | 001295202 0012952 5 0 1 |
204. | 001295203 0012952 5 0 0 |
205. | 001295204 0012952 5 0 0 |
|---------------------------------------------|
206. | 001295205 0012952 5 0 0 |
207. | 001295206 0012952 5 0 0 |
208. | 001295304 0012953 5 0 1 |
209. | 001295305 0012953 5 0 0 |
210. | 002010001 0020100 1 1 0 |
|---------------------------------------------|
211. | 002010001 0020100 2 1 0 |
212. | 002010001 0020100 3 1 0 |
213. | 002010001 0020100 4 1 0 |
214. | 002010002 0020100 1 0 1 |
215. | 002010002 0020100 2 0 1 |
|---------------------------------------------|
216. | 002010002 0020100 3 0 1 |
217. | 002010002 0020100 4 0 1 |
218. | 002010003 0020100 1 0 0 |
219. | 002010003 0020100 2 0 0 |
220. | 002010003 0020100 3 0 0 |
|---------------------------------------------|
221. | 002010003 0020100 4 0 0 |
222. | 002010005 0020100 4 0 0 |
223. | 002010006 0020151 5 0 1 |
224. | 002015101 0020151 5 1 0 |
225. | 002015103 0020151 5 0 0 |
|---------------------------------------------|
226. | 002020001 0020200 1 1 0 |
227. | 002020001 0020200 2 1 0 |
228. | 002020002 0020200 1 0 1 |
229. | 002020002 0020200 2 0 1 |
230. | 002030001 0020300 1 1 0 |
|---------------------------------------------|
231. | 002030001 0020300 2 1 0 |
232. | 002030001 0020300 3 1 0 |
233. | 002030001 0020300 4 1 0 |
234. | 002030002 0020300 1 0 1 |
235. | 002030002 0020300 2 0 1 |
|---------------------------------------------|
236. | 002030002 0020300 3 0 1 |
237. | 002030002 0020300 4 0 1 |
238. | 002030003 0020300 1 0 0 |
239. | 002030003 0020300 2 0 0 |
240. | 002030003 0020300 3 0 0 |
|---------------------------------------------|
241. | 002030003 0020300 4 0 0 |
242. | 002040001 0020400 1 1 0 |
243. | 002040001 0020300 2 0 0 |
244. | 002040001 0020400 3 1 0 |
245. | 002040001 0020400 5 1 0 |
|---------------------------------------------|
246. | 002040002 0020400 1 0 1 |
247. | 002040002 0020400 3 0 1 |
248. | 002040002 0020400 5 0 1 |
249. | 002040003 0020400 1 0 0 |
250. | 002040003 0020441 4 0 1 |
|---------------------------------------------|
251. | 002040003 0020441 5 0 1 |
252. | 002040004 0020400 1 0 0 |
253. | 002040004 0020400 3 0 0 |
254. | 002040005 0020400 1 0 0 |
255. | 002040005 0020400 3 0 0 |
|---------------------------------------------|
256. | 002040005 0020400 5 0 0 |
257. | 002040006 0020400 3 0 0 |
258. | 002040007 0020400 3 0 0 |
259. | 002040007 0020400 5 0 0 |
260. | 002040008 0020400 5 0 0 |
|---------------------------------------------|
261. | 002040009 0020400 5 0 0 |
262. | 002040011 0020400 5 0 0 |
263. | 002044102 0020441 4 1 0 |
264. | 002044102 0020441 5 1 0 |
265. | 002044104 0020441 4 0 0 |
|---------------------------------------------|
266. | 002044104 0020441 5 0 0 |
267. | 002044105 0020441 4 0 0 |
268. | 002044105 0020441 5 0 0 |
269. | 002044106 0020441 5 0 0 |
270. | 002044201 0020442 4 1 0 |
|---------------------------------------------|
271. | 002044201 0020442 5 1 0 |
272. | 002044202 0020442 4 0 1 |
273. | 002044202 0020442 5 0 1 |
274. | 002044204 0020442 5 0 0 |
275. | 002044205 0020442 5 0 0 |
|---------------------------------------------|
276. | 002050001 0020500 1 1 0 |
277. | 002050001 0020500 2 1 0 |
278. | 002050002 0020500 1 0 1 |
279. | 002050002 0020500 2 0 1 |
280. | 002050003 0020500 1 0 0 |
|---------------------------------------------|
281. | 002050003 0020500 2 0 0 |
282. | 002050004 0020500 1 0 0 |
283. | 002050004 0020500 2 0 0 |
284. | 002050005 0020500 1 0 0 |
285. | 002050005 0020500 2 0 0 |
|---------------------------------------------|
286. | 002050006 0020500 2 0 0 |
287. | 002060004 0020651 5 0 1 |
288. | 002065101 0020651 5 1 0 |
289. | 002065103 0020651 5 0 0 |
290. | 002065104 0020651 5 0 0 |
|---------------------------------------------|
291. | 002065105 0020651 5 0 0 |
292. | 002065106 0020651 5 0 0 |
293. | 002065107 0020651 5 0 0 |
294. | 002065108 0020651 5 0 0 |
295. | 002090001 0020900 1 1 0 |
|---------------------------------------------|
296. | 002090001 0020900 2 1 0 |
297. | 002090001 0020900 3 1 0 |
298. | 002090001 0020900 4 1 0 |
299. | 002090002 0020900 1 0 1 |
300. | 002090002 0020900 2 0 1 |
|---------------------------------------------|
301. | 002090002 0020900 3 0 1 |
302. | 002090002 0020900 4 0 1 |
303. | 002090003 0020900 1 0 0 |
304. | 002090003 0020900 2 0 0 |
305. | 002090003 0020931 3 0 1 |
|---------------------------------------------|
306. | 002090003 0020900 4 0 0 |
307. | 002090004 0020900 1 0 0 |
308. | 002090004 0020900 2 0 0 |
309. | 002090004 0020900 3 0 0 |
310. | 002090004 0020900 4 0 0 |
|---------------------------------------------|
311. | 002090006 0020932 3 1 0 |
312. | 002090007 0020933 3 0 1 |
313. | 002090008 0020900 4 0 0 |
314. | 002093102 0020931 3 1 0 |
315. | 002093202 0020932 3 0 1 |
|---------------------------------------------|
316. | 002093301 0020933 3 1 0 |
317. | 002100001 0021000 1 1 0 |
318. | 002100001 0021000 2 1 0 |
319. | 002100001 0021000 3 1 0 |
320. | 002100002 0021000 1 0 1 |
|---------------------------------------------|
321. | 002100002 0021000 2 0 1 |
322. | 002100002 0021000 3 0 1 |
323. | 002100003 0021000 1 0 0 |
324. | 002100003 0021000 2 0 0 |
325. | 002100003 0021000 3 0 0 |
|---------------------------------------------|
326. | 002100004 0021000 2 0 0 |
327. | 002100004 0021000 3 0 0 |
328. | 002110001 0021100 1 1 0 |
329. | 002110001 0021100 2 1 0 |
330. | 002110001 0021100 3 1 0 |
|---------------------------------------------|
331. | 002110001 0021100 4 1 0 |
332. | 002110002 0021100 1 0 1 |
333. | 002110002 0021100 2 0 1 |
334. | 002110002 0021100 3 0 1 |
335. | 002110002 0021100 4 0 1 |
|---------------------------------------------|
336. | 002110003 0021100 1 0 0 |
337. | 002110003 0021100 2 0 0 |
338. | 002110003 0021100 3 0 0 |
339. | 002110003 0021100 4 0 0 |
340. | 002110004 0021100 1 0 0 |
|---------------------------------------------|
341. | 002110004 0021100 2 0 0 |
342. | 002110004 0021100 3 0 0 |
343. | 002110005 0021100 1 0 0 |
344. | 002110005 0021100 2 0 0 |
345. | 002110005 0021100 3 0 0 |
|---------------------------------------------|
346. | 002110005 0021100 4 0 0 |
347. | 002110006 0021100 2 0 0 |
348. | 002110006 0021100 3 0 0 |
+---------------------------------------------+


Thank you in advance,

Enrique

[Devra Golbe]

The dataset refers to a household survey where members are interviewed based on the relationship to the head of the household, in a context where husbands may have more than one wife. If a household head changes spouses, then that person is interviewed in the following wave and shows up with a new pidlink. If a daughter interviewed in a given wave gets married, becomes a wife and moves out of the household, she is re-interviewed keeping the same pidlink but a new hhid.

If husbands may have more than one wife, why are you surprised that there are more distinct wives than husbands? I think your code checks whether a HH ever has more than one husband/wife per wave, not whether there are multiple husbands or wives per HH ID over all the waves in which that HH ID appears.