1. 1/12 Sex Miscoding and Same-Sex Couple Estimates IUSSP XXVIIe International Population Conference Busan, South Korea, August 26-31th 2013 Maks Banens Centre Max Weber – CNRS Lyon University France

2. 2/12 What is Sex Miscoding? Sex Miscoded Individual: Man coded Woman or Woman coded Man Sex Miscoded Couple: Opposite-Sex Couple coded Same-Sex Couple or Same-Sex Couple coded Opposite-Sex Couple Sex Miscoded Individual: Man coded Woman or Woman coded Man Sex Miscoded Couple: Opposite-Sex Couple coded Same-Sex Couple or Same-Sex Couple coded Opposite-Sex Couple Sex Miscoding occurs at declaration, data input or data treatment Sex Miscoding is present in self-declared Censuses and Surveys and in face-tot-face computer assisted surveys (Laurent et al., 2013; French 2011 Family Survey) Sex Miscoding occurs at declaration, data input or data treatment Sex Miscoding is present in self-declared Censuses and Surveys and in face-tot-face computer assisted surveys (Laurent et al., 2013; French 2011 Family Survey)

3. 3/12 Effects of Sex Miscoding SMR = Sex Miscoding Rate %MOSC = Part of Miscoded OS Couples / Total Recorded SS Couples %MSSC = Part Miscoded S-S Couples / Total Recorded OS Couples SMR = Sex Miscoding Rate %MOSC = Part of Miscoded OS Couples / Total Recorded SS Couples %MSSC = Part Miscoded S-S Couples / Total Recorded OS Couples Example: If individual SMR = 1 ‰  couple SMR = 2 ‰ If Total Recorded S-S Couples = 6 ‰  %MOSC = 33 % and %MSSC ≈ 0.001 % Example: If individual SMR = 1 ‰  couple SMR = 2 ‰ If Total Recorded S-S Couples = 6 ‰  %MOSC = 33 % and %MSSC ≈ 0.001 % Couple SMR (%) %MOSC (%) Source US 2010 Census0.4028Hogan et al., 2012 England/Wales 2001 Census 0.3155ONS, 2005

4. 4/12 Question How can we target and remove miscoded OS couples from Census and large Survey data? O’Connell et al. (2006): name index adjustment method Black et al. (2007): adjustment by marital status and child’s presence Gates et al. (2012): adjustment by marital status, age and race/ethnicity O’Connell et al. (2006): name index adjustment method Black et al. (2007): adjustment by marital status and child’s presence Gates et al. (2012): adjustment by marital status, age and race/ethnicity Banens and Le Penven (2013): generalized adjustment method, applied on French 2008 Census data French 2011 Family Survey: allows direct measure of sex miscoding and check of generalized adjustment method

5. 5/12 Generalized Adjustment Method Step 1: Estimate SMR and dependent characteristics Step 2: Apply SMR to subpopulations of OS Couples according to different sociodemographic characteristics Step 1: Estimate SMR and dependent characteristics Step 2: Apply SMR to subpopulations of OS Couples according to different sociodemographic characteristics

6. 6/12 1. Looking for minimums Exemple: Subpopulation: married couples living in households of 3 persons or more Recorded % of Male (Blue) and Female (Pink) S-S couples according to some demographic characteristics

7. Step 1: First findings and Assumptions Prevalence:Male couples: 0.17 % or more Female couples: 0.11 % or more Dependent characteristicsSize of household Age over 85 Prevalence:Male couples: 0.17 % or more Female couples: 0.11 % or more Dependent characteristicsSize of household Age over 85 Individual SMR (%) Persons in householdMenWomAll 2 persons0.100.160.26 3 persons0.150.200.34 4 persons0.170.230.39 5 persons0.170.240.40 6 and more persons0.230.300.52 All0.130.190.33

8. Step 2: Adjustment Recorded SS Couples considered as a biased sample of OS couples according to age, education, marital status, geographic area, sector of activity, mobility and age difference between partners SS Couples recalibrated on OS couples by sample calibrating technics (Calmar, SAS). New weights reflect sex miscoding likelihood. Results compared to 2011 Family Survey results. Recorded SS Couples considered as a biased sample of OS couples according to age, education, marital status, geographic area, sector of activity, mobility and age difference between partners SS Couples recalibrated on OS couples by sample calibrating technics (Calmar, SAS). New weights reflect sex miscoding likelihood. Results compared to 2011 Family Survey results.

9. Comparing Assumptions and Observations Sex Miscoding by sex and size of household France 2008 Banens and Le Penven (%) France 2011 Family Survey (%) MenWomAllMenWomAll 2 persons0.100.160.260.140.150.29 3 persons0.150.200.340.190.220.41 4 persons0.170.230.390.170.240.41 5 persons0.170.240.400.160.310.47 6 and more persons0.230.300.520.070.300.37 All0.130.190.330.150.200.36

10. Comparing Adjustments and Observations Part of miscoded OS couples by marital status and children Part of sex miscoded OS couples Census France 2008 Banens/Le Penven Census France 2011 (EFL - INSEE) Total4743 Unmarried couples no children10 All couples without children29 Female couples with children7569 Male couples with children92100

11. Thank You 11/12 More Data Comments and Methodological notes: www.banens.fr/sex.php