Number of Naturalized Respondents (2 1 [귀화연도 있음] or 2 1 [1. 해당]) in the Sample
# A tibble: 2 × 2
naturalized_bi n
<dbl+lbl> <int>
1 0 [해당 없음] 9398
2 1 [귀화연도 있음] 8086
# A tibble: 3 × 2
naturalized_bi n
<dbl+lbl> <int>
1 0 [0. 해당없음] 18419
2 1 [1. 해당] 8296
3 NA 3225
# A tibble: 2 × 2
naturalized_bi n
<dbl+lbl> <int>
1 0 [0. 해당없음] 7280
2 1 [1. 해당] 8254
Number of Naturalizations by Year
Number of Naturalizations by Year Full Data
Number of Naturalizations by Year (entered KR before 2011)
Number of Naturalizations by Year (entered KR after 2000)
Number of Naturalizations by Year across Waves
Number of Naturalizations by Year (2015 wave)
Number of Naturalizations by Year (2018 wave)
Number of Naturalizations by Year (2021 wave)
Number of Years it Took to Naturalize post 2011 and pre 2011
Number of Years it Took to Naturalize (Naturalized between 2000 and 2011)
Number of Years it Took to Naturalize (Naturalized between 2011 and 2018)
By Country
Created a data with respondents from Vietnam, Philippines, Thailand, Japan, Mongolia, and China. Dual indicates 1 if the respondent is from Vietnam, Philippines, or Thailand and 0 if the respondent is from Japan, Mongolia, or China.
By Income
Do we observe that the changes particularly helped marriage migrants with lower language ability or from poorer households?
# A tibble: 9 × 4
varname code label `Monthly Income`
<chr> <dbl> <chr> <chr>
1 income 1 100만원 미만 $1,000
2 income 2 100~200만원 미만 $2,000
3 income 3 200~300만원 미만 $3,000
4 income 4 300~400만원 미만 $4,000
5 income 5 400~500만원 미만 $5,000
6 income 6 500~600만원 미만 $6,000
7 income 7 600~700만원 미만 $7,000
8 income 8 700~800만원 미만 $8,000
9 income 9 800만원 이상 over $8,000