record linkage; selection bias; census records

Tayatat Kanjanapipatkul

English

Research Papers in Economics

1
What Predict Linkage to the 1910 and 1900 Census given that the veterans have the
pension record?
Hypothesis
According to the Census linking procedure, veterans living in the rural area and in the
North are easier to be linked. Commonness of last name and the presence of soundex
should matter as well.
Sample
The analysis was conducted with 8,884 veterans for 1910, and 13,193 veterans for 1900.
These veterans are linked to the census, have pension file and still alive by 1910,
respectively. There are 2 ways to link the recruits, by the link file or by checking the
presence of state name in the actual data set. The linkage rates are 63% and 67%,
respectively. Both methods are consistent. A recruited linked to the census by one
method is most likely to be linked by the other method. See Consistency Check.
Logistic Analysis
Explanatory variables are chosen to reflect the place of residence in 1910, occupation,
commonness of last name, and age. These variables are
1.  Urban/rural status of the place of residence constructed by Mario. A county is
considered urban if it contains at least one city with more than 25,000 inhabitants.
Place of residence in Mario’s data contain missing value of 41% and 43% for the
1910 and 1900 Census, respectively. 28% of veterans lives in urban county in 1910,
while only 23% lives in urban county in 1900.
2.  A dummy variable indicating whether the veterans live in the North or the South.
Northern states are states in the East North Central region, Middle Atlantic region,
New England region, and West North Central region. Southern states are located in
East South Central region, South Atlantic region, and West South Central region. The
states in Pacific and Mountain region considered Western states.
3.  4 sets of dummy variables for occupation from the combined data set. The first set
was taken from the first instance. The second approach picks the occupations
beginning before and ending after 1910 if both beginning date and ending date of
occupation are available, or pick the only available occupation if the veterans had
only one occupation throughout their life. If the occupation still can not be assigned,
the first instance was used. Instead of using the first instance when the cleaning rule
in the second approach did not work, the third method computes the distance between
beginning date or ending date to 1910 for all distance and assigns the instance with
the minimal distance. If this additional rule does not work, the first instance was
assigned.
For the forth set, the veterans, whose occupation can not be inferred after the 3
rd
method, were assigned an instance randomly picked from the non-missing instance.
The occupational classification is based on the 1950 occupational category.2
Professionals include Professional, Technical and Mangers and Proprietors. Clerks
include clerical and kindred workers, craftsmen, and service workers. Laborers
consist of sales workers, operative workers, and laborers. Farmers include farmers
and farm laborers. The mean composition is reported in the logistic regression table.
4.  The frequency of last name. This variable is constructed from the 1880 Census data
downloaded from IPUMS. A veteran was assigned the frequency of the last name
found in the IPUMS data, which spells exactly the same. If the name does not appears
in the IPUMS data, the veteran was assigned the frequency equal to 1.
5.  A dummy variable indicating whether the state the veterans live has soundex. This
variable is needed only for 1910 because all states have the soundex for the 1900
Census. The states which have soundex in 1910 are AL, AR, CA, FL, GA, ID, IL,
KS, KY, LA, MI, MS, NV, MO, NC, OH, OK, PA, SC, TN, TX, VA, WV, and WY.
For the 1900 Census, the intercept will capture the effect of the soundex.
Results
For the 1910 Census,
1.  A veteran is more likely to be linked if he is linked to the 1900 Census.
2.  A veteran is more likely to be linked if he lives in the state, which has soundex.
For both censuses,
3.  A veteran who lives in the rural county is statistically more likely to be linked.
4.  A veteran who lives in the northern states is more likely to be linked.
5.  Frequency of last name is not a significant predictor of linkage.
6.  Farmers are more likely to be linked
7.  Old veterans are more likely to be linked.
Note to Table 1 and 2
The variable abbreviations are
DAGEMISS = Dummy if the age is not missing.
AGEINT = An interation term of age and Dagemiss.
RURAL = Dummy if the veterans live in rural county.
URBAN = Dummy if the veterans live in urban county. The ommited group veterans
whose residences are missing.
DNORTH = Dummy if the veterans live in the Northern states. See definition above.
DSOUTH = Dummy if the veterans live in the Southern states. See definition above.
DPROF = Dummy if the veteran’s occupation is professionals.
DLABOR = Dummy if the veteran’s occupation is laborers.
DCLERK = Dummy if the veteran’s occupation is clerks
DRETIRE = Dummy if the veteran’s is retired.
DOCCNA = Dummy if the veterans’ occupation is missing.
FREQ = Log of frequency of last name from the 1880 Census.
SOUNDEX = Dummy if the state that the veterans live in have soundex.3
Table 1: Logistic Regression for the 1910 Census
Model 1 Model 2 Model 3 Model 4 Variable
Mean Parameter
Estimate
Mean Parameter
Estimate
Mean Parameter
Estimate
Mean Parameter
Estimate
INTERCPT -0.1751 -0.1328 -0.0351 -0.0406
AGEMISS 0.07 -0.557* -0.543* -0.4555 -0.4489
AGEINT 64.59 0.00975** 0.00944** 0.00827* 0.00818*
RURAL 0.42 0.2552** 0.2608** 0.2791** 0.2794**
URBAN 0.17 -0.3153*** -0.3037** -0.2856** -0.2918**
DNORTH 0.49 0.3352*** 0.3344*** 0.3241*** 0.3225***
DSOUTH 0.06 -0.0609 -0.0607 -0.0771 -0.0772
DPROF 0.02 -0.239* 0.05 -0.2075* 0.07 -0.2195** 0.08 -0.2013**
DLABOR 0.19 -0.4026*** 0.21 -0.4145*** 0.22 -0.3941*** 0.22 -0.3728***
DCLERK 0.16 -0.1669*** 0.17 -0.1952*** 0.17 -0.2145*** 0.17 -0.1864***
DRETIRE 0.03 -0.2411* 0.04 -0.2177* 0.09 -0.2472*** 0.09 -0.2328***
DOCCNA 0.001 -0.1525 0.001 -1.2946** 0.001 -1.1832
FREQ 0.00474 0.00535 0.00645 0.00659
SOUNDEX 0.32 0.411*** 0.407*** 0.3981*** 0.4005***
R square 0.055 0.056 0.055 0.054
Observation 8884 8884 8884 8884
Table2: Logistic regression for the 1900 Census
Model 1 Model 2 Model 3 Model 4 Variable
Mean Parameter
Estimate
Mean Parameter
Estimate
Mean Parameter
Estimate
Mean Parameter
Estimate
INTERCPT 1.0662*** 1.1344*** 1.2136*** 1.2069***
DAGEMISS 0.24 -0.0222 -0.0503 -0.1223 -0.1169
AGEINT 45.77 0.00562 0.0051 0.00406 0.00412
RURAL 0.44 0.2707** 0.2685** 0.2879** 0.284**
URBAN 0.13 -0.0474 -0.0381 -0.0268 -0.0334
DNORTH 0.49 0.4739*** 0.4754*** 0.4639*** 0.4674***
DSOUTH 0.05 0.2488 0.2418 0.2242 0.2269
DPROF 0.03 -0.0998 0.05 -0.033 0.07 -0.0994 0.07 -0.1051
DLABOR 0.20 -0.4148*** 0.22 -0.4655*** 0.23 -0.4816*** 0.23 -0.4717***
DCLERK 0.17 -0.2759*** 0.18 -0.34*** 0.18 -0.3172*** 0.18 -0.3078***
DRETIRE 0.03 -0.3777*** 0.03 -0.3215*** 0.07 -0.2924*** 0.07 -0.2825***
DOCCNA 0.002 0.0317 0.001 -0.6755 0.001 0.4523
FREQ -0.00259 -0.00221 -0.00175 -0.00181
R square 0.047 0.049 0.049 0.049
Observation 13193 13193 13193 131934
Illustrations
Consistency Check for the 1910 Census
Link in link file
No Yes
2920 9 No
89% 0%
342 5613
Link in
Actual
Data Set Yes
11% 100%
Chi-square 7458.05 0.001
Pearson Correlation 0.92
Linkage rate in 1910 
Census  by linkage to 1900 
Census
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
Link Not link
Linkage rate in 1910 
Census  by Soundex
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Yes No
Linkage rate by Urban-
Rural Status
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
Rural Urban
1900 1910
Linkage rate by Northern 
States
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
North Others
1900 19105
Consistency Check for the 1900 Census
Link in link file
No Yes
2451 30 No
79% 0%
642 10070
Link in
Actual
Data Set Yes
21% 100%
Chi-square 9665.24 0.001
Pearson Correlation 0.86

What predicts linkage to the 1900 and 1910 Censuses, given that a recruit entered the pension system?

http://www.cpe.uchicago.edu/publication/lib/Census.pdf

What predicts linkage to the 1900 and 1910 Censuses, given that a recruit entered the pension system?

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Research Papers in Economics