6 2018 5 18 1 / 29
1. 2. 3. 2 / 29
Stata Stata dta merge master using _merge master only (1): using only (2): matched (3): 3 / 29
Stata One-to-one on key variables Many-to-one on key variables One-to-many on key variables Many-to-many on key variables One-to-one by observation 4 / 29
One-to-one on key variables master prefecture male v 1 Tokyo 1 51 2 Tokyo 0 65 3 Aomori 1 32 4 Aomori 0 28 5 Saitama 1 45 using prefecture male w 1 Tokyo 1 7 2 Tokyo 0 9 3 Aomori 1 2 4 Aomori 0 3 5 Saitama 1 5 6 Saitama 0 2 prefecture male 5 / 29
One-to-one on key variables prefecture male v w _merge 1 Tokyo 1 51 7 matched (3) 2 Tokyo 0 65 9 matched (3) 3 Aomori 1 32 2 matched (3) 4 Aomori 0 28 3 matched (3) 5 Saitama 1 45 5 matched (3) 6 Saitama 0. 2 using only (2) 6 / 29
Many-to-one on key variables master prefecture district a 1 Tokyo Kanto 26 2 Aomori Tohoku 29 3 Saitama Kanto 22 4 Aichi Chubu 21 5 Iwate Tohoku 24 6 Kochi Shikoku 20 using district x 1 Tohoku 15 2 Kanto 13 3 Chubu 12 4 Kinki 11 district 7 / 29
Many-to-one on key variables prefecture district a x _merge 1 Tokyo Kanto 26 13 matched (3) 2 Aomori Tohoku 29 15 matched (3) 3 Saitama Kanto 22 13 matched (3) 4 Aichi Chubu 21 12 matched (3) 5 Iwate Tohoku 24 15 matched (3) 6 Kochi Shikoku 20. master only (1) 7. Kinki. 11 using only (2) 8 / 29
One-to-many on key variables master district x 1 Tohoku 15 2 Kanto 13 3 Chubu 12 4 Kinki 11 using prefecture district a 1 Tokyo Kanto 26 2 Aomori Tohoku 29 3 Saitama Kanto 22 4 Aichi Chubu 21 5 Iwate Tohoku 24 6 Kochi Shikoku 20 district 9 / 29
One-to-many on key variables district x prefecture a _merge 1 Tohoku 15 Aomori 29 matched (3) 2 Tohoku 15 Iwate 24 matched (3) 3 Kanto 13 Tokyo 26 matched (3) 4 Kanto 13 Saitama 22 matched (3) 5 Chubu 12 Aichi 21 matched (3) 6 Kinki 11.. master only (1) 7 Shikoku. Kochi 20 using only (2) 10 / 29
One-to-one by observation master x 1 15 2 13 3 12 4 11 using a 1 26 2 29 3 22 4 21 5 24 6 20 11 / 29
One-to-one by observation x a _merge 1 15 26 matched (3) 2 13 29 matched (3) 3 12 22 matched (3) 4 11 21 matched (3) 5. 24 using only (2) 6. 20 using only (2) 12 / 29
master prefecture income male 1 Hokkaido 227349 1 2 Aomori 233967 1.... 47 Okinawa 214233 1 48 Hokkaido 207155 0 49 Aomori 169422 0.... 93 Okinawa 144644 0 13 / 29
using prefecture deposit 1 Hokkaido 131180 2 Aomori 35527... 47 Okinawa 34381 master 2 using 1 prefecture Many-to-one on key variables 14 / 29
prefecture income male deposit _merge 1 Hokkaido 227349 1 131180 matched (3) 2 Aomori 233967 1 35527 matched (3)...... 47 Okinawa 214233 1 34381 matched (3) 48 Hokkaido 207155 0 131380 matched (3) 49 Aomori 169422 0 35527 matched (3)...... 93 Okinawa 144644 0 34381 matched (3) prefecture 15 / 29
master using master using 16 / 29
Command rename ( ) ( ) Enter rename 17 / 29
Data Data Editor Data Editor (Edit) Enter Data Editor (Edit) 18 / 29
1 1. Stata 2. File Log Begin... 2018microdata1 lecture20180518.smcl 3. File Open 4. consumption2009.dta 19 / 29
5. Data Data Editor Data Editor (Edit) 6. 1 prefecture Command rename ( ) prefecture Enter rename prefecture 7. Command list prefecture male female Enter list more 20 / 29
8. Hokkaido, Aomori, Iwate, Miyagi, Akita, Yamagata, Fukushima, Ibaraki, Tochigi, Gumma, Saitama, Chiba, Tokyo, Kanagawa, Niigata, Toyama, Ishikawa, Fukui, Yamanashi, Nagano, Gifu, Shizuoka, Aichi, Mie, Shiga, Kyoto, Osaka, Hyogo, Nara, Wakayama, Tottori, Shimane, Okayama, Hiroshima, Yamaguchi, Tokushima, Kagawa, Ehime, Kochi, Fukuoka, Saga, Nagasaki, Kumamoto, Oita, Miyazaki, Kagoshima, Okinawa Data Data Editor Data Editor (Edit) Enter Data Editor (Edit) 21 / 29
9. 10. Command clear Enter Stata 11. File Open 12. deposit2009.dta 22 / 29
13. Data Data Editor Data Editor (Edit) 14. 1 prefecture Command rename ( ) prefecture Enter rename prefecture 15. Command list prefecture deposit Enter list more 23 / 29
16. Hokkaido, Aomori, Iwate, Miyagi, Akita, Yamagata, Fukushima, Ibaraki, Tochigi, Gumma, Saitama, Chiba, Tokyo, Kanagawa, Niigata, Toyama, Ishikawa, Fukui, Yamanashi, Nagano, Gifu, Shizuoka, Aichi, Mie, Shiga, Kyoto, Osaka, Hyogo, Nara, Wakayama, Tottori, Shimane, Okayama, Hiroshima, Yamaguchi, Tokushima, Kagawa, Ehime, Kochi, Fukuoka, Saga, Nagasaki, Kumamoto, Oita, Miyazaki, Kagoshima, Okinawa Data Data Editor Data Editor (Edit) Enter Data Editor (Edit) 24 / 29
17. 18. Command clear Enter Stata 25 / 29
2 consumption2009.dta master deposit2009.dta using 1. File Open 2. consumption2009.dta 3. Data Combine datasets Merge two datasets 4. Main Type of merge Many-to-one on key variables (unique key for data on disk) 5. Key variables: (match variables) prefecture prefecture 26 / 29
6. Filename of dataset on disk: Browse... deposit2009.dta 7. OK Results not matched 0 matched 93 27 / 29
8. Command generate deposit_th=deposit/1000 Enter 1,000 9. 10. Command list prefecture male female expenditure_th income_th deposit_th _merge Enter list more 28 / 29
3 1. File Log Close 2. Stata lecture20180518.smcl 2018microdata1 3. lecture20180518.smcl 29 / 29