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    the Study on the Policy Changes of Social Integration Courses for Foreigners- Focusing on the activities of the external environment changes and policy entrepreneurs relating to immigration policy -

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› : ํ–‰์ •ํ•™๊ณผ(์ •์ฑ…ํ•™ ์ „๊ณต), 2015. 8. ์ž„๋„๋นˆ.ํ•œ๊ตญ ์‚ฌํšŒ๋Š” ์ €์ถœ์‚ฐ?๊ณ ๋ นํ™”๋กœ ์ธํ•ด ์ƒ์‚ฐ๊ฐ€๋Šฅ์ธ๊ตฌ์˜ ๊ฐ์†Œ๊ฐ€ ๋น ๋ฅธ ์†๋„๋กœ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋Š”๋ฐ, ์šฐ๋ฆฌ๋‚˜๋ผ๋Š” 2006๋…„๋ถ€ํ„ฐ ์ €์ถœ์‚ฐยท๊ณ ๋ น์‚ฌํšŒ ๊ธฐ๋ณธ๊ณ„ํš์„ ์ˆ˜๋ฆฝํ•˜๊ณ  ์žˆ์Œ์—๋„ ์ง€๋‚œ 10๋…„ ๋™์•ˆ ์ถœ์‚ฐ์œจ ์ฆ๊ฐ€์˜ ๊ฐ€์‹œ์  ํšจ๊ณผ๋Š” ์—†๊ณ , ์˜คํžˆ๋ ค ํ•ฉ๊ณ„์ถœ์‚ฐ์œจ์€ 2010๋…„์— 1.23%์—์„œ 2013๋…„์— 1.19%๋กœ ๋–จ์–ด์กŒ๋‹ค. ์ด๋ฏผ์ •์ฑ…์ด ์ถœ์‚ฐ์ •์ฑ…๊ณผ ๋ณ‘ํ–‰ํ•˜์—ฌ ์ถ”์ง„ํ•˜๋Š” ๊ฒƒ์ด ๋ถˆ๊ฐ€ํ”ผํ•œ ์ƒํ™ฉ์ด๋‹ค. ์šฐ๋ฆฌ๋‚˜๋ผ๋Š” ์™ธ๊ตญ์ธ์˜ ์œ ์ž…๊ณผ ์ •์ฐฉ์„ ํ—ˆ์šฉํ•˜๋Š” ํ›„๋ฐœ์ด๋ฏผ๊ตญ๊ฐ€๋กœ ์ง„์ž…ํ–ˆ๊ณ , 2015๋…„ 12์›”์— ๊ตญ๋‚ด ๊ฑฐ์ฃผํ•˜๋Š” ์™ธ๊ตญ์ธ ์ˆ˜๋Š” 200๋งŒ ๋ช…์— ๋„๋‹ฌํ•  ์ „๋ง์ด๋‹ค. ๋ฐ˜๋ฉด์— ์™ธ๊ตญ์ธ์€ ๊ตญ๋‚ด ์ ์‘์— ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ์œผ๋ฉฐ ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ์šด์˜๋ฐฉ์‹์— ๋Œ€ํ•˜์—ฌ ์ •๋ถ€๋ถ€๋ฌธ๊ณผ ๋ฏผ๊ฐ„๋ถ€๋ฌธ ๋ชจ๋‘์—์„œ๋Š” ์ƒ์ดํ•œ ์‹ ๋…์ฒด๊ณ„๋ฅผ ์ง€๋‹Œ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋“ค์ด ํ˜•์„ฑ๋˜์–ด ๊ฐˆ๋“ฑ ์–‘์ƒ์„ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์ด ๋„์ž…๋˜์–ด ๊ทธ ์ค‘์˜ ์ผ๋ถ€ ๊ต์œก๊ณผ์ •์ด ํ‘œ์ค€ํ™” ๋˜๋Š” ์˜๋ฌดํ™”๋˜์–ด ๊ฐ€๋Š” ์ •์ฑ…๋ณ€๋™ ๊ณผ์ •๊ณผ ๊ทธ ์›์ธ์„ ๋…ธ๋ฌดํ˜„, ์ด๋ช…๋ฐ•, ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ๋กœ ๋‚˜๋ˆ„์–ด ๋ถ„์„ํ–ˆ๋‹ค. ๋ถ„์„๋œ ๊ฒฐ๊ณผ๋Š” ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ๋ฐ”๋žŒ์งํ•œ ์šด์˜๋ฐฉ์‹์„ ์„ค์ •ํ•˜๊ณ  ์ƒ์ดํ•œ ์‹ ๋…์ฒด๊ณ„๋ฅผ ์ง€๋‹Œ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋“ค ๊ฐ„์˜ ๊ฐˆ๋“ฑ์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ํ•„์š”ํ•œ ์š”์†Œ๊ฐ€ ๋ฌด์—‡์ธ์ง€๋ฅผ ๋ชจ์ƒ‰ํ•  ์ˆ˜ ์žˆ๋Š” ์ด๋ก ์ ?์ •์ฑ…์  ์‹œ์‚ฌ์„ฑ์„ ๊ฐ€์ง„๋‹ค. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•์€ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ์ •์ฑ…์˜์ œํ˜•์„ฑ๊ณผ ์ •์ฑ…๋ณ€๋™ ๊ณผ์ •์—์„œ ๋‚˜ํƒ€๋‚œ ๋‹ค์–‘ํ•œ ์›์ธ์„ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•๊ณผ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋ชจํ˜•์˜ ์žฅ์ ์„ ๊ฒฐํ•ฉํ•œ ์žฌ์„ค๊ณ„๋œ ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•์ด๋‹ค. ์žฌ์„ค๊ณ„๋œ ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•์„ ํ†ตํ•ด, ์™ธ๊ตญ์ธ์˜ ์œ ์ž…๊ณผ ๊ด€๋ จํ•œ ์™ธ๋ถ€ํ™˜๊ฒฝ ๋ณ€ํ™”์™€ ์ดˆ์ ์‚ฌ๊ฑด์˜ ์˜ํ–ฅ์„ ๋ฐ›์€ ์ •์ฑ…๊ธฐ์—…๊ฐ€์˜ ์—ญํ• ๋กœ ์ด๋ฃจ์–ด์ง„ ์ •์ฑ…ํ๋ฆ„์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๊ณผ ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ ๋ฐ ๊ทธ ์‹ ๋…์ฒด๊ณ„์˜ ์ฐจ์ด๋ฅผ ๋น„๊ต ๋ถ„์„ํ–ˆ๊ณ  ๊ฐ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋“ค์˜ ๊ฐˆ๋“ฑ ๋“ฑ ์—ญํ•™๊ด€๊ณ„์™€ ์ •์ฑ…์ง€ํ–ฅํ•™์Šต ๊ณผ์ •์ด ๋‹ค์‹œ ์ •์ฑ…๊ธฐ์—…๊ฐ€์—๊ฒŒ ์˜ํ–ฅ์„ ์ฃผ์–ด ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ์ผ๋ถ€ ๊ณผ์ •์ด ํ‘œ์ค€ํ™” ๋˜๋Š” ์˜๋ฌดํ™”๋˜๋Š”๋ฐ ์›์ธ์ด ๋˜์—ˆ๋‹ค๋Š” ๊ฒƒ์„ ํŒŒ์•…ํ•˜๊ณ ์ž ํ–ˆ๋‹ค. ์—ฐ๊ตฌ ๋Œ€์ƒ์€ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ํ‘œ์ค€ํ™” ๋ฐ ์˜๋ฌดํ™” ์—ฌ๋ถ€์ด๋‹ค. ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์€ ๊ตญ์ œ๊ฒฐํ˜ผ ์ค‘๊ฐœ์—…์ฒด๋ฅผ ํ†ตํ•ด 3~5์ผ๊ฐ„์˜ ์†์„ฑ์œผ๋กœ ๊ตญ์ œ๊ฒฐํ˜ผํ•˜๋ ค๋Š” ๊ตญ๋‚ด ์ž…๊ตญํ•˜๊ธฐ ์ „์˜ ๊ฒฐํ˜ผ์ด๋ฏผ์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” ํ•œ๊ตญ์–ด ๊ต์œก, ๊ตญ๋‚ด ์ž…๊ตญํ•œ ์™ธ๊ตญ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ ๋ฐ ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ(ํ•œ๊ตญ์–ด์™€ ํ•œ๊ตญ์‚ฌํšŒ์ดํ•ด)์œผ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋ฏผ์ •์ฑ…์˜ ๊ฐœ๋…๊ณผ ๊ทธ ๊ตฌ์„ฑ์š”์†Œ(์ธ๊ตฌ์œ ์ž…์˜ ๊ทœ๋ชจ์™€ ์งˆ ์กฐ์ ˆ, ์™ธ๊ตญ์ธ๋ ฅ ๊ณ ์šฉ?ํ™œ์šฉ, ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ)๋ฅผ ์ด๋ก ์ ์œผ๋กœ ์ •๋ฆฝํ•˜๋Š” ๊ฒƒ์„ ์ƒˆ๋กœ์ด ์‹œ๋„ํ–ˆ๋‹ค. ์šฐ๋ฆฌ๋‚˜๋ผ ์ด๋ฏผ์ •์ฑ…์˜ ์‹œ๋Œ€์  ๊ตฌ๋ถ„๊ณผ ์ •์ฑ…์ด๋…์„ ์‚ดํŽด๋ณด์•˜๊ณ , ์ด๋ฅผ ๋‹ค๋ฌธํ™”์ •์ฑ…๊ณผ ๋น„๊ต ๋ถ„์„ํ–ˆ๋‹ค. ์ด๋ฏผ์ •์ฑ…(์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ)๊ณผ ์ธ์ข…์  ๋‹ค๋ฌธํ™”์ •์ฑ…์€ ๋‘˜ ๋‹ค ์™ธ๊ตญ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ๋ฌธํ™”์  ๋‹ค์–‘์„ฑ์„ ์ง€ํ–ฅํ•˜๋Š” ์œ ์‚ฌํ•œ ์ •์ฑ…์ด์ง€๋งŒ, ์ •์ฑ…์  ๊ด€์ ๊ณผ ์‹ ๋…์ฒด๊ณ„์˜ ์ฐจ์ด๋กœ ์ธํ•ด ๊ฐ๊ฐ ์ž‘๋™์›๋ฆฌ์™€ ๋„๊ตฌ์  ์ •์ฑ…์‹ ๋…์ด ์ƒ์ดํ•จ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์€ ๊ตญ๊ฐ€์ด์ต๊ณผ ์‚ฌํšŒ์งˆ์„œ ์œ ์ง€๋ผ๋Š” ์‹ ๋…์ฒด๊ณ„๋ฅผ ๋ณด์œ ํ–ˆ๊ณ , ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์€ ๊ฐ€์กฑ๋ณต์ง€์™€ ์–‘์„ฑํ‰๋“ฑ์ด๋ผ๋Š” ์‹ ๋…์ฒด๊ณ„๋ฅผ ๋ณด์œ ํ–ˆ์Œ์„ ๋น„๊ต ๋ถ„์„ํ–ˆ๊ณ , ๊ฐˆ๋“ฑ๊ด€๊ณ„์— ์žˆ๋Š” ๋‘ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์ด ๊ตํ™˜์  ์ •์ฑ…์‹ ๋…๊ณผ ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๋ณ€ํ™”, ์ดˆ์ ์‚ฌ๊ฑด ๋“ฑ์„ ํ†ตํ•ด ์ •์ฑ…์ง€ํ–ฅํ•™์Šต๊ณผ ๋„๊ตฌ์  ์ •์ฑ…์‹ ๋…์˜ ๋ณ€ํ™”๊ฐ€ ์žˆ์—ˆ์Œ์„ ๋ถ„์„ํ–ˆ๋‹ค. ๋…ธ๋ฌดํ˜„ ์ •๋ถ€์‹œ๊ธฐ์—์„œ๋Š” ๊ฒฐํ˜ผ์ด๋ฏผ์ž์— ๋Œ€ํ•ด ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ์„ ์˜๋ฌด์ ์œผ๋กœ ์‹œํ–‰ํ•˜๋„๋ก ์ •์ฑ…๊ฒฐ์ •์ด ์ด๋ฃจ์–ด์กŒ์œผ๋‚˜, ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€์™€ ์ด์ฃผ์—ฌ์„ฑ ์ธ๊ถŒ๋‹จ์ฒด ๋“ฑ ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์˜ ๋ฐ˜๋Œ€ ๋ฐ ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์˜ ์„ธ๋ ฅ ๋ฏธ๋น„๋กœ ๊ทธ ์‹œํ–‰์ด ์‹คํŒจํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋ช…๋ฐ• ์ •๋ถ€์‹œ๊ธฐ์—์„œ๋Š” ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ํ‘œ์ค€ํ™”๊ฐ€ ๊ตญ์ •๊ณผ์ œ๋กœ ์ฑ„ํƒ๋˜์—ˆ๊ณ  ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€ ๋“ฑ 4๊ฐœ ๋ถ€์ฒ˜๊ฐ€ ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ์„ ํ‘œ์ค€ํ™”ํ•˜๊ธฐ๋กœ ํ˜‘์•ฝ์„œ๋ฅผ ์ฒด๊ฒฐํ–ˆ์Œ์—๋„, ๋‹ค๋ฌธํ™”๊ฐ€์กฑ์ง€์›์„ผํ„ฐ ๋“ฑ ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์˜ ๋ฐ˜๋Œ€๋กœ ํ‘œ์ค€ํ™” ์ดํ–‰์ด ์‹คํŒจํ•˜์˜€๋‹ค. ๋‘ ์ •๋ถ€์‹œ๊ธฐ์—์„œ๋Š” ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ์˜๋ฌดํ™”๋ผ๋Š” ์ •์ฑ…์˜์ œ์„ค์ •์€ ์ •๋ถ€ ์™ธ๋ถ€์— ์žˆ๋Š” ์„ธ๋ ฅ์— ์˜ํ•ด ์˜ํ–ฅ์„ ๋ฐ›์•˜๊ณ , ์ •๋ถ€ ์™ธ๋ถ€์˜ ๋ฏผ๊ฐ„์ง‘๋‹จ(์™ธ๋ถ€์ฃผ๋„ํ˜•)์€ ํ‘œ์ค€ํ™”๊ฐ€ ์ง‘ํ–‰๋‹จ๊ณ„์—์„œ ์ขŒ์ ˆ๋˜๋„๋ก ํ•˜๋Š” ๋ฌด์˜์‚ฌ๊ฒฐ์ •(non-decision making)์„ ์ฃผ๋„ํ–ˆ๋‹ค. ๋ฐ˜๋ฉด์— ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ์—์„œ๋Š” ์™ธ๊ตญ์ธ์˜ ์ˆ˜๊ฐ€ 200๋งŒ ๋ช… ์ž„๋ฐ•, ๋ถ€์ ์‘๊ณผ ๊ฐ•๋ ฅ๋ฒ”์ฃ„ ์ฆ๊ฐ€ ๋“ฑ ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๋ณ€ํ™”๊ฐ€ ๋‘๋“œ๋Ÿฌ์กŒ๊ณ  ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์€ ๊ตฌ์„ฑ์›์„ ํ™•๋Œ€ํ•˜๊ณ  ๊ทธ ๊ฒฐ์†๋ ฅ์„ ๊ฐ•ํ™”ํ–ˆ๋‹ค. ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๊ณผ ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ ๋ชจ๋‘๊ฐ€ ์ •์ฑ…์ง€ํ–ฅํ•™์Šต์„ ๊ฑฐ์ณ ๋„๊ตฌ์  ์‹ ๋…์ฒด๊ณ„์˜ ๋ณ€ํ™”๋ฅผ ๊ฒฝํ—˜ํ–ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐฐ๊ฒฝ์—์„œ ๋Œ€ํ†ต๋ น, ๋ฒ•๋ฌด๋ถ€์žฅ๊ด€์€ ์ •์ฑ…๊ธฐ์—…๊ฐ€๋กœ์„œ ์—ญํ• ์„ ๋ฐœํœ˜ํ•˜์—ฌ ์ •์ฑ…ํ๋ฆ„์ด ๋งŒ๋‚˜ ์ •์ฑ…์˜ ์ฐฝ์ด ์—ด๋ ธ๊ณ  ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก ์ค‘์˜ ์ผ๋ถ€ ๊ณผ์ •์ด ํ‘œ์ค€ํ™”์™€ ์˜๋ฌดํ™”๋˜์—ˆ๋‹ค. ํ‘œ์ค€ํ™”์™€ ์˜๋ฌดํ™”๋Š” ๋Œ€ํ†ต๋ น, ์žฅ๊ด€ ๋“ฑ ํ–‰์ •๊ด€๋ฃŒ๋“ค์— ์˜ํ•ด ์ •๋ถ€์˜์ œ๋กœ ์ฑ„ํƒ๋˜๊ฑฐ๋‚˜(๋™์›ํ˜•), ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก๊ธฐ๊ด€, ๋‹ค๋ฌธํ™”๊ฐ€์กฑ์ง€์›์„ผํ„ฐ ๋“ฑ ์™ธ๋ถ€์ง‘๋‹จ์— ์˜ํ•ด ์ •๋ถ€์˜์ œ๋กœ ๋˜๊ธฐ๋„ ํ•˜์˜€๋‹ค(๋‚ด๋ถ€์ ‘๊ทผํ˜•). ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์˜ ์‹œ์‚ฌ์ ์€ ํ–ฅํ›„ ์™ธ๊ตญ์ธ์˜ ๊ธ‰์ฆ์— ๋Œ€๋น„ํ•˜์—ฌ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์ด ํ‘œ์ค€ํ™”๋˜๊ฑฐ๋‚˜ ์˜๋ฌดํ™”๋  ์ˆ˜ ์žˆ๊ธฐ ์œ„ํ•ด์„œ๋Š” ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๋ณ€ํ™”์™€ ์ดˆ์ ์‚ฌ๊ฑด ์ด์™ธ์—, ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๊ณผ ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์ด ์ •์ฑ…์ง€ํ–ฅํ•™์Šต์„ ํ†ตํ•ด ์„œ๋กœ๋ฅผ ์ดํ•ดํ•˜์—ฌ ๊ฒฐ์†๋ ฅ์„ ๊ฐ•ํ™”ํ•˜๊ณ , ๋‘ ์—ฐํ•ฉ์˜ ์‹ ๋…์ฒด๊ณ„๊ฐ€ ๋ณ€ํ™”๋˜์–ด์•ผ๋งŒ ์ •์ฑ…๊ธฐ์—…๊ฐ€์˜ ์กด์žฌ์™€ ์—ญํ• ์ด ํ™œ์„ฑํ™”๋˜์–ด ์ •์ฑ…์˜ ์ฐฝ์ด ์‰ฝ๊ฒŒ ์—ด๋ฆด ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ด์—ˆ๋‹ค.์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ๊ณผ ํ•„์š”์„ฑ 1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ?๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 4 ์ œ3์ ˆ ์„ ํ–‰์—ฐ๊ตฌ์˜ ๊ฒ€ํ†  8 ์ œ4์ ˆ ์„ ํ–‰์—ฐ๊ตฌ์™€์˜ ์ฐจ๋ณ„์„ฑ 15 ์ œ2์žฅ ์—ฐ๊ตฌ ๋ถ„์„ํ‹€์„ ์œ„ํ•œ ์ด๋ก ์  ๋…ผ์˜ 17 ์ œ1์ ˆ ์ด๋ฏผ์ •์ฑ…์— ๊ด€ํ•œ ์ด๋ก ์  ๋…ผ์˜ 17 1. ์˜์˜ 17 2. ์ด๋ฏผ์ •์ฑ… 17 3. ์ด๋ฏผ์ •์ฑ…์˜ ํ•™๋ฌธ์  ๋ฒ”์ฃผ 20 (1) ์ด๋ฏผ ํ˜„์ƒ์— ๋Œ€ํ•œ ์ธ๋ฌธํ•™์  ์ดํ•ด 20 (2) ์ด๋ฏผ ํ˜„์ƒ์— ๋Œ€ํ•œ ํ–‰์ •ํ•™?์ •์ฑ…ํ•™์  ์ดํ•ด 22 4. ์ด๋ฏผ์ •์ฑ…์˜ ํ•˜์œ„ ๊ตฌ์„ฑ์š”์†Œ 24 (1) ์ธ๊ตฌ์œ ์ž…์˜ ๊ทœ๋ชจ์™€ ์งˆ ์กฐ์ ˆ(๊ตญ๊ฒฝ๊ด€๋ฆฌ, ์ถœ์ž…๊ตญ๊ด€๋ฆฌ์ •์ฑ…) 24 (2) ์™ธ๊ตญ์ธ๋ ฅ ๊ณ ์šฉ?ํ™œ์šฉ 25 (3) ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ 26 ์ œ2์ ˆ ์ •์ฑ…๋ณ€๋™์— ๊ด€ํ•œ ์ด๋ก ์  ๋…ผ์˜ 29 1. ์ •์ฑ…๋ณ€๋™ 29 2. ์ •์ฑ…์˜์ œ์„ค์ •์˜ ์ฃผ๋„๊ถŒ ๋ฌธ์ œ 30 3. ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•๊ณผ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋ชจํ˜•์˜ ๊ฒฐํ•ฉ๋ชจํ˜• 31 (1) ๊ฒฐํ•ฉ๋ชจํ˜•์˜ ์œ ์šฉ์„ฑ 31 (2) ์ •์ฑ…ํ๋ฆ„๋ชจํ˜• 33 (3) ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋ชจํ˜• 35 (4) ์žฌ์„ค๊ณ„๋œ ์ •์ฑ…ํ๋ฆ„๋ชจํ˜• : ๊ฒฐํ•ฉ๋ชจํ˜• 37 ์ œ3์ ˆ ์—ฐ๊ตฌ ๋ฌธ์ œ 43 ์ œ4์ ˆ ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 44 ์ œ3์žฅ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์ด๋ฏผ์ •์ฑ…๊ณผ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก 46 ์ œ1์ ˆ ์ด๋ฏผ์ •์ฑ… 46 1. ์˜์˜ 46 2. ์ด๋ฏผ์ •์ฑ…์˜ ์‹œ๋Œ€์  ๊ตฌ๋ถ„ 47 3. ์ด๋ฏผ์ •์ฑ…์˜ ์ด๋… 49 4. ๋‹ค๋ฌธํ™”์ •์ฑ…๊ณผ์˜ ๊ด€๊ณ„ 50 ์ œ2์ ˆ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก 56 1. ์˜์˜ 56 2. ์œ ํ˜• 57 3. ์ž…๊ตญ ์ „(ๅ‰)์˜ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก 59 (1) ๊ฒฐํ˜ผ์ด๋ฏผ์ž๋ฅผ ์œ„ํ•œ ํ•œ๊ตญ์–ด๊ต์œก 59 4. ์ž…๊ตญ ํ›„(ๅพŒ)์˜ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก 61 (1) ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ 61 (2) ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ(์™ธ๊ตญ๊ตญ์ ๋™ํฌ ๊ธฐ์ดˆ๋ฒ•์ œ๋„) 64 (3) ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ 65 ์ œ4์žฅ ์žฌ์„ค๊ณ„๋œ ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•์„ ํ™œ์šฉํ•œ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์— ๋Œ€ํ•œ ์ •์ฑ…๋ณ€๋™ ์—ฐ๊ตฌ 68 ์ œ1์ ˆ ๋…ธ๋ฌดํ˜„ ์ •๋ถ€์‹œ๊ธฐ (2005๋…„ ~ 2008๋…„ 2์›”) 68 1. ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๋ณ€ํ™” 68 2. ์ •์ฑ…์˜ ํ๋ฆ„ 70 (1) ์ •์ฑ…๋Œ€์•ˆ์˜ ํ๋ฆ„ 70 (2) ์ •์น˜์˜ ํ๋ฆ„ 73 1) ๋Œ€ํ†ต๋ น์˜ ๊ด€์—ฌ 73 2) ๋ฒ•๋ฌด๋ถ€์žฅ๊ด€์˜ ๊ด€์—ฌ 74 3) ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€์žฅ๊ด€์˜ ๊ด€์—ฌ : ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ์˜๋ฌดํ™” ๋ฐ˜๋Œ€ 76 4) ์ด์ฃผ์—ฌ์„ฑ ์ธ๊ถŒ๋‹จ์ฒด์˜ ๊ด€์—ฌ : ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ์˜๋ฌดํ™” ๋ฐ˜๋Œ€ 77 5) ์—ฌ๋ก ์˜ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก ์ง€์ง€ 78 3. ์ •์ฑ…ํ•˜์œ„์ฒด๊ณ„ 78 (1) ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ 78 (2) ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ 79 (3) ์ •๋ถ€์˜์ œ์„ค์ •์˜ ์ฃผ๋„๊ถŒ ๋ฌธ์ œ 80 4. ์ดˆ์ ์‚ฌ๊ฑด 80 5. ์ •์ฑ…๊ธฐ์—…๊ฐ€์˜ ๋ถ€์กด์žฌ, ์ •์ฑ…์˜ ์ฐฝ ๋‹ซํž˜ 83 ์ œ2์ ˆ ์ด๋ช…๋ฐ• ์ •๋ถ€์‹œ๊ธฐ (2008๋…„ 2์›” ~ 2013๋…„ 2์›”) 85 1. ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๋ณ€ํ™” 85 2. ์ •์ฑ…์˜ ํ๋ฆ„ 89 (1) ์ •์ฑ…๋Œ€์•ˆ์˜ ํ๋ฆ„ 89 (2) ์ •์น˜์˜ ํ๋ฆ„ 92 1) ๋ฒ•๋ฌด๋ถ€์žฅ๊ด€์˜ ๊ด€์—ฌ 92 2) ๊ด€๋ จ ๋ถ€์ฒ˜์˜ ๊ด€์—ฌ : ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ํ‘œ์ค€ํ™” ํ•ฉ์˜ 95 3) ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€์žฅ๊ด€, ๋‹ค๋ฌธํ™”๊ฐ€์กฑ์ง€์›์„ผํ„ฐ ๋“ฑ์˜ ๊ด€์—ฌ : ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ํ‘œ์ค€ํ™” ๋ฐ˜๋Œ€ 96 4) ์—ฌ๋ก ์˜ ์ƒ๋ฐ˜๋œ ๋ฐ˜์‘ 99 3. ์ •์ฑ…ํ•˜์œ„์ฒด๊ณ„ 100 (1) ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ 100 (2) ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ 101 (3) ์ •๋ถ€์˜์ œ์„ค์ •์˜ ์ฃผ๋„๊ถŒ ๋ฌธ์ œ 102 4. ์ดˆ์ ์‚ฌ๊ฑด 102 5. ์ •์ฑ…๊ธฐ์—…๊ฐ€์˜ ๋ถ€์กด์žฌ, ์ •์ฑ…์˜ ์ฐฝ ๋‹ซํž˜ 106 ์ œ3์ ˆ ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ (2013๋…„ 2์›” ~ 2015๋…„ 5์›” ํ˜„์žฌ) 110 1. ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๋ณ€ํ™” 110 2. ์ •์ฑ…์˜ ํ๋ฆ„ 114 (1) ์ •์ฑ…๋Œ€์•ˆ์˜ ํ๋ฆ„ 114 (2) ์ •์น˜์˜ ํ๋ฆ„ 118 1) ๋Œ€ํ†ต๋ น์˜ ๊ด€์—ฌ 118 2) ์ฒญ์™€๋Œ€ ๊ตญ์ •๊ณผ์ œ๋น„์„œ๊ด€ ๋ฐ ๊ต์œก๋ฌธํ™”์ˆ˜์„์˜ ๊ด€์—ฌ 120 3) ๋ฒ•๋ฌด๋ถ€์žฅ๊ด€์˜ ๊ด€์—ฌ 122 4) ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€์žฅ๊ด€, ๋‹ค๋ฌธํ™”๊ฐ€์กฑ์ง€์›์„ผํ„ฐ์˜ ๊ด€์—ฌ : ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก ์ง€์ง€ 125 5) ์ด์ฃผ์—ฌ์„ฑ ์ธ๊ถŒ๋‹จ์ฒด์˜ ๊ด€์—ฌ : ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก ์†Œ๊ทน์  ๋ฐ˜๋Œ€ 126 6) ์—ฌ๋ก ์˜ ๋ณ€ํ™” 127 3. ์ •์ฑ…ํ•˜์œ„์ฒด๊ณ„ 131 (1) ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ 131 (2) ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ 132 (3) ์ •๋ถ€์˜์ œ์„ค์ •์˜ ์ฃผ๋„๊ถŒ ๋ฌธ์ œ 133 4. ์ดˆ์ ์‚ฌ๊ฑด 134 5. ์ •์ฑ…๊ธฐ์—…๊ฐ€์˜ ์กด์žฌ, ์ •์ฑ…์˜ ์ฐฝ ์—ด๋ฆผ 138 6. ์ •์ฑ…์‚ฐ์ถœ๊ณผ ์ •์ฑ…๋ณ€๋™ 139 (1) ์ž…๊ตญ ์ „(ๅ‰) ๊ฒฐํ˜ผ์ด๋ฏผ์ž์˜ ํ•œ๊ตญ์–ด ๊ต์œก ์˜๋ฌดํ™” 139 (2) ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ์˜ ํ‘œ์ค€ํ™” 140 (3) ๊ตญ๋‚ด ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ์ผ๋ถ€ ์˜๋ฌดํ™” 140 ์ œ5์žฅ ๊ฒฐ๋ก  143 ์ œ1์ ˆ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 143 ์ œ2์ ˆ ์ด๋ก ์ ?์ •์ฑ…์  ์‹œ์‚ฌ์  151 ์ œ3์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 156 ์ฐธ๊ณ ๋ฌธํ—Œ 159 ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ์˜ ๊ต์œก๋‚ด์šฉ 164 Abstract 168 ํ‘œ ๋ชฉ ์ฐจ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์— ๋Œ€ํ•œ ์‹ ๋…์ฒด๊ณ„์˜ ๋ถ„๋ฅ˜ 5 ์—ฐ๊ตฌ์˜ ์‹œ๊ฐ„์  ๋ฒ”์œ„ 7 DDC 23ํŒ์— ๋‚˜ํƒ€๋‚œ ์ด๋ฏผ์˜ ํ•™๋ฌธ์  ๋ฒ”์ฃผ 23 ๊ธฐ์กด ๋ชจํ˜•์˜ ์žฅ๋‹จ์  ๋ฐ ๊ฒฐํ•ฉ๋ชจํ˜•์˜ ์žฅ์  32 ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ๊ตฌ์„ฑ์š”์†Œ ๋ฐ ๋‚ด์šฉ 38 ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 45 ๋‹ค๋ฌธํ™”์ •์ฑ…์˜ ์œ ํ˜• 53 ์ด๋ฏผ์ •์ฑ…๊ณผ (์ธ์ข…์ ) ๋‹ค๋ฌธํ™”์ •์ฑ…์˜ ๊ด€๊ณ„ ๋น„๊ต 56 ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์˜ ์œ ํ˜• 59 ์—ฐ๋„๋ณ„ ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ ์ฐธ์—ฌ์ž 62 ์กฐ๊ธฐ์ ์‘ํ”„๋กœ๊ทธ๋žจ์˜ ๊ต์œก ๋Œ€์ƒ์ž 64 ์—ฐ๋„๋ณ„ ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ์ฐธ์—ฌ์ž 66 ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ๊ต์œก ๊ณผ์ •ํ‘œ 67 ์™ธ๊ตญ์ธ๊ณผ์˜ ๊ตญ์ œ๊ฒฐํ˜ผ ์ถ”์ด 68 ๊ฒฐํ˜ผ์ด๋ฏผ์ž๊ฐ€ ํ•œ๊ตญ์—์„œ ์ƒํ™œํ•˜๋ฉด์„œ ๊ฐ€์žฅ ํž˜๋“  ์  69 ์‚ฌํšŒํ†ตํ•ฉํ”„๋กœ๊ทธ๋žจ ์˜๋ฌดํ™”๋ฅผ ์œ„ํ•œ ์˜๊ฒฌ์ˆ˜๋ ด ๊ณผ์ • 76 ๋…ธ๋ฌดํ˜„ ์ •๋ถ€์‹œ๊ธฐ์—์„œ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋“ค์˜ ์‹ ๋…์ฒด๊ณ„ 80 ๊ฒฐํ˜ผ์ „ ํ•œ๊ตญ์ธ ๋ฐฐ์šฐ์ž(๋‚จํŽธ)์— ๋Œ€ํ•ด ๋“ค์€ ์ด์•ผ๊ธฐ ์‚ฌ์‹ค์—ฌ๋ถ€ 82 ์œ„์žฅ๊ฒฐํ˜ผ ๋‹จ์† ์‹ค์  82 ํ•œ๊ตญ์ธ๊ณผ ์™ธ๊ตญ์ธ ๋ถ€๋ถ€์˜ ์ดํ˜ผ ํ˜„ํ™ฉ 83 ๋…ธ๋ฌดํ˜„ ์ •๋ถ€์‹œ๊ธฐ์˜ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์— ๋Œ€ํ•œ ์ •์ฑ…๊ณผ์ • 84 ์™ธ๊ตญ์ธ์˜ ์œ ํ˜•๋ณ„ ํ†ต๊ณ„ 86 ๋ถˆ๋ฒ•์ฒด๋ฅ˜์ž ์ˆ˜(2009๋…„~2012๋…„) 88 ์œ ํ˜•๋ณ„ ์™ธ๊ตญ์ธ์˜ ์ฆ๊ฐ€์— ๋Œ€ํ•œ ๊ตญ๋ฏผ์˜ ํƒœ๋„ 100 ์ด๋ช…๋ฐ• ์ •๋ถ€์‹œ๊ธฐ์—์„œ ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋“ค์˜ ์‹ ๋…์ฒด๊ณ„ 102 ๊ตญ๋ฏผ?์™ธ๊ตญ์ธ ๋ฒ”์ฃ„ ์œ ํ˜•๋ณ„ ์ธ๊ตฌ 10๋งŒ๋ช…๋‹น ๊ฒ€๊ฑฐ์ธ์›์ง€์ˆ˜ ๋น„๊ต 105 ์ด๋ช…๋ฐ• ์ •๋ถ€์‹œ๊ธฐ์˜ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์— ๋Œ€ํ•œ ์ •์ฑ…๊ณผ์ • 109 ๋‹ค๋ฌธํ™”๊ฐ€์กฑ์˜ ์ฆ๊ฐ€๊ฐ€ ํ•œ๊ตญ ์‚ฌํšŒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ํ•œ๊ตญ์ธ์˜ ์ธ์‹๋ณ€ํ™” 129 ์™ธ๊ตญ์ธ๋…ธ๋™์ž์— ๋Œ€ํ•œ ํ•œ๊ตญ์ธ์˜ ์ธ์‹ 129 ๋‹ค๋ฌธํ™”๊ฐ€์กฑ ์ฆ๊ฐ€๊ฐ€ ํ•œ๊ตญ ์‚ฌํšŒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ์ธ์‹ 130 ์ˆ˜์›์‹œ ๊ตญ๋ฏผ?์™ธ๊ตญ์ธ ๋ฒ”์ฃ„์ž ์ธ๊ตฌ 10๋งŒ๋ช…๋‹น ๊ฒ€๊ฑฐ์ธ์›์ง€์ˆ˜ ๋น„๊ต 138 ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ์˜ ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก์— ๋Œ€ํ•œ ์ •์ฑ…๊ณผ์ • 141 ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ๊ต์œก ์˜๋ฌดํ™” ์ •์ฑ…๊ณผ์ • ๋ฐ ์ •๋ถ€์‹œ๊ธฐ๋ณ„ ๋น„๊ต 142 ๊ทธ ๋ฆผ ๋ชฉ ์ฐจ ์ฒด๋ฅ˜์™ธ๊ตญ์ธ ์ฆ๊ฐ€ ๋ฐ ์ด์ธ๊ตฌ ๋Œ€๋น„ ์™ธ๊ตญ์ธ ๋น„์œจ(์ถ”์ •) 2 ์™ธ๊ตญ์ธ ์‚ฌํšŒํ†ตํ•ฉ์ •์ฑ…์˜ ์ •์ฑ…์ˆ˜๋‹จ๊ณผ ๋ชฉํ‘œ 27 ์ด๋ฏผ์ •์ฑ…์˜ ํ•˜์œ„ ๊ตฌ์„ฑ์š”์†Œ 29 ์™ธ๊ตญ์ธ ์œ ํ˜• ๋ฐ ์ด๋ฏผ์ •์ฑ… ์œ ํ˜• 29 ์ •์ฑ…ํ๋ฆ„๋ชจํ˜•์˜ ๊ตฌ์กฐ ๋ฐ ์„ค๋ช…๋ณ€์ˆ˜ 35 ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ๋ชจํ˜•์˜ ๊ตฌ์กฐ ๋ฐ ์„ค๋ช…๋ณ€์ˆ˜(์—ฐ๊ตฌํ•  ๋‚ด์šฉ ์ ์šฉ) 36 ์žฌ์„ค๊ณ„๋œ ์ •์ฑ…ํ๋ฆ„๋ชจํ˜• 37 ๋…ธ๋ฌดํ˜„, ์ด๋ช…๋ฐ• ์ •๋ถ€์‹œ๊ธฐ ๋ฐ ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ ๋น„๊ต 43 ์ฃผ์š”๊ตญ๊ฐ€์˜ ์ด๋ฏผ์ •์ฑ… ์‚ฌ๋ก€ 85 2008๋…„์ดˆ ๋ถˆ๋ฒ•์ฒด๋ฅ˜์ž ์ฃผ์š” ๋ฐ€์ง‘์ง€์—ญ ๋ถ„ํฌ๋„ 103 ์ค‘๋„์ž…๊ตญ์ž๋…€์˜ ์ทจํ•™ ํ˜„ํ™ฉ 113 ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ์—์„œ ์ด๋ฏผ์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์˜ ์ •์ฑ…์ง€ํ–ฅํ•™์Šต ๊ณผ์ • 132 ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์‹œ๊ธฐ์—์„œ ๋‹ค๋ฌธํ™”์ •์ฑ…์˜นํ˜ธ์—ฐํ•ฉ์˜ ์ •์ฑ…์ง€ํ–ฅํ•™์Šต ๊ณผ์ • 133Maste

    (A) comparison of the scapulothoracic muscle activities according to the type of quadruped position

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    ์ธ๊ฐ„๊ณตํ•™์น˜๋ฃŒํ•™์ „๊ณต/์„์‚ฌ[ํ•œ๊ธ€] ์ตœ๊ทผ ๊ฒฌ๊ฐ‘๊ณจ์ด ์ •์ƒ๊ธฐ๋Šฅ์„ ํ•˜๋Š”๋ฐ ํ•„์ˆ˜์ ์ธ ์ „๊ฑฐ๊ทผ์˜ ๊ทผ๋ ฅ์ฆ์ง„ ์šด๋™๋ฐฉ๋ฒ•๊ณผ ์šด๋™ ํšจ๊ณผ์— ๋Œ€ํ•œ ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ๋„ค๋ฐœ๊ธฐ๊ธฐ์ž์„ธ, ๋‹ค์–‘ํ•œ ํ‘ธ์‹œ์—… ํ”Œ๋Ÿฌ์Šค ์šด๋™ ๊ทธ๋ฆฌ๊ณ  ๊ธฐ๊ตฌ๋ฅผ ์ด์šฉํ•œ ์šด๋™๋“ค์ด ์ „๊ฑฐ๊ทผ ๊ทผ๋ ฅ์ฆ์ง„ ์šด๋™์œผ๋กœ ์ž์ฃผ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๊ฒฌ๊ฐ‘๊ณจ ์ต์ƒ๊ตฐ๊ณผ ์ •์ƒ ๋Œ€์กฐ๊ตฐ์„ ๋Œ€์ƒ์œผ๋กœ ๋„ค๋ฐœ๊ธฐ๊ธฐ ์ž์„ธ์˜ ์„ธ ๊ฐ€์ง€ ์œ ํ˜•์— ๋”ฐ๋ฅธ ์ „๊ฑฐ๊ทผ, ์ค‘์Šน๋ชจ๊ทผ, ํ•˜์Šน๋ชจ๊ทผ, ๋Šฅํ˜•๊ทผ, ๊ทธ๋ฆฌ๊ณ  ๋Œ€ํ‰๊ทผ์˜ ๊ทผํ™œ์„ฑ๋„์— ์–ด๋–ค ์ฐจ์ด๊ฐ€ ์žˆ๋Š”์ง€ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•˜์—ฌ ์‹ค์‹œํ•˜์˜€๋‹ค. ์–ด๊นจ ํ†ต์ฆ๊ณผ ์ „๊ฑฐ๊ทผ ์•ฝํ™”๊ฐ€ ์—†๋Š” ๊ฑด๊ฐ•ํ•œ ์„ฑ์ธ 10๋ช…๊ณผ ๊ฒฌ๊ฐ‘๊ณจ ์ต์ƒ๊ตฐ 10๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ๋„ค๋ฐœ๊ธฐ๊ธฐ ์ž์„ธ์˜ ์ผ๋ถ€ ์œ ํ˜•์ธ ํ›„๋ฐฉ๋ฝํ‚น ์ž์„ธ, ์ค‘๋ฆฝ ์ž์„ธ, ์ „๋ฐฉ๋ฝํ‚น ์ž์„ธ๋ฅผ ์œ ์ง€ํ•˜์˜€์„ ๋•Œ ์ „๊ฑฐ๊ทผ, ์ค‘์Šน๋ชจ๊ทผ, ํ•˜์Šน๋ชจ๊ทผ, ๋Šฅํ˜•๊ทผ, ๋Œ€ํ‰๊ทผ์˜ ๊ทผํ™œ์„ฑ๋„๋ฅผ ํ‘œ๋ฉด ๊ทผ์ „๋„ ๋ถ„์„ ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ์ธก์ •ํ•˜์˜€๋‹ค. ์ •๋Ÿ‰ํ™”๋œ ๊ฐ ๊ทผ์œก์˜ ๊ทผํ™œ์„ฑ๋„๋ฅผ ๋ฐ˜๋ณต ์ธก์ •๋œ ์ด์š”์ธ ๋ถ„์‚ฐ๋ถ„์„(two-way repeated ANOVA)์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ ๊ทผ์œก์˜ ์ต์ƒ์˜ ์œ ๋ฌด์— ๋”ฐ๋ฅธ ์ง‘๋‹จ๊ฐ„์˜ ๋น„๊ต์™€ ๋„ค๋ฐœ๊ธฐ๊ธฐ ์ž์„ธ์˜ ์„ธ ๊ฐ€์ง€ ์œ ํ˜•์— ๋”ฐ๋ฅธ ๊ทผํ™œ์„ฑ๋„๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์ง‘๋‹จ๊ณผ ๋„ค๋ฐœ๊ธฐ๊ธฐ ์ž์„ธ ์œ ํ˜• ์‚ฌ์ด์˜ ์ƒํ˜ธ์ž‘์šฉ์€ ์—†์—ˆ๋‹ค. ์ „๊ฑฐ๊ทผ, ๋Šฅํ˜•๊ทผ, ์ค‘์Šน๋ชจ๊ทผ์˜ ๊ทผํ™œ์„ฑ๋„๋Š” ์ž์„ธ ๊ฐ„ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๊ณ (p0.05). ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ๋„ค๋ฐœ๊ธฐ๊ธฐ ์ž์„ธ์—์„œ ๊ฒฌํ‰๊ฐ‘ ๊ทผ์œก์˜ ๊ทผ๋ ฅ์ฆ์ง„ ์šด๋™ ์‹œ ์šด๋™๋ถ€ํ•˜๋ฅผ ๊ฒฐ์ •ํ•˜๋Š”๋ฐ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค [์˜๋ฌธ]Many researchers have recently studied the effects of exercise programs for the scapulothoracic muscles. In particular, strengthening exercise methods for the serratus anterior muscle have been extensively studied, because the muscle is essential for the proper movement patterns of the scapula. A variety of strengthening exercises in the quadruped position, various push-up plus exercises, and the use of exercise equipment have been employed to strengthen the muscle. The purpose of this study was to evaluate the effects of three modified quadruped positions on scapulothoracic muscle activities in subjects with and without winged scapulae. 10 healthy adults without musculoskeletal disease and 10 subjects with winged scapular participated in this study. Surface electromyographic (EMG) activities of the serratus anterior, middle trapezius, lower trapezius, rhomboid, and the pectoralis major muscles were measured in the backward rocking, the neutral, and the forward rocking positions. The EMG activities of each muscle were compared using a two-way (group ร— positions) repeated ANOVA. In the result of the study, no significant interaction was found between the groups and the three variations of quadruped position. The EMG activities of the serratus anterior, rhomboid, and middle trapezius muscles in both groups significantly decreased in the order of forward rocking, neural position, and backward rocking position (p0.05). The results of this study suggest progressive use of exercises in quadruped positions from the backward rocking position which requires relatively low scapulothoracic activities to the neural and the forward rocking positions. As a conclusion, the various quadruped positions must be selectively used to control the amount of load to the scapulothoracic muscles for the effective strengthening exercise according to the status of patientsope

    The Effect of ฮด-Ferrite on the Corrosion Resistance of STS 316L

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    Maste

    - ๊ณต๊ฐ„ ๊ด€๊ณ„ ๋ถ„์„๊ณผ SUR ๋ชจํ˜•์„ ์ค‘์‹ฌ์œผ๋กœ -

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(์ •์ฑ…ํ•™์ „๊ณต), 2022.2. ์ž„๋„๋นˆ.์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ง€์—ญ์—์„œ ์ƒˆ๋กœ์šด ํ–‰์œ„์ž๋กœ ๋“ฑ์žฅํ•˜๋ฉด์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ฑฐ์ฃผ ๋ถ„ํฌ์™€ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€๋„ ์ฆ๊ฐ€ํ•˜๋Š” ์ถ”์„ธ์ด๋‹ค. ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€์€ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ(%) ๋˜๋Š” ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๋กœ ์ธก์ •๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์ด ์ง€์—ญ๊ฒฝ์ œ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ์—์„œ ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€์— ๋”ฐ๋ผ ๊ทธ ํšจ๊ณผ์— ์–ด๋–ค ๋ณ€ํ™”๊ฐ€ ๋ฐœ์ƒํ•˜๋Š”์ง€๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์™ธ๊ตญ์ธ ์ด์›ƒ์˜ ์™ธ๋ถ€ํšจ๊ณผ์— ๋Œ€ํ•ด ์ด๋ก ์  ๋…ผ์Ÿ์ด ์žˆ์Œ์„ ์„ค๋ช…ํ•œ๋‹ค. ์ง€์—ญ์˜ ๊ฒฝ์ œ์„ฑ์žฅ์€ ์ƒ์‚ฐ์š”์†Œ(์ธ๋ ฅ)์˜ ๊ณต๊ธ‰์— ๋”ฐ๋ผ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค๋Š” ๊ณต๊ธ‰์ค‘์‹œ์ด๋ก ์„ ํ™œ์šฉํ•˜๊ณ , ๋…ธ๋™์‹œ์žฅ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ๋Š” ๋…ธ๋™์ด๋Ÿ‰์„ค๊ณผ ๋Œ€์ฒด์žฌ ๋˜๋Š” ๋ณด์™„์žฌ ๊ด€๊ณ„์— ๋”ฐ๋ผ ์„œ๋กœ ๋Œ€๋ฆฝํ•˜๋Š” ๋…ผ์Ÿ์„ ํ™œ์šฉํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ด๋ฏผ์˜ ๊ณต๊ฐ„์  ํšจ๊ณผ๋ฅผ ๋ฐ˜์˜ํ•˜๊ธฐ ์œ„ํ•ด ๊ณต๊ฐ„๋ถ„์„์„ ์‹œํ–‰ํ•˜๊ณ , ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅโ€ค์‹ค์—…โ€ค๊ณ ์šฉ์— ๋Œ€ํ•ด ๋™์‹œ์— ํ•œ๊บผ๋ฒˆ์— ๋ถ„์„ํ•˜๋Š” ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•จ์œผ๋กœ์จ ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ์ ์‹ค์„ฑ์„ ๋†’์ด๊ณ ์ž ํ•œ๋‹ค. ๋ถ„์„์ง€์—ญ์€ ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ, ์ˆ˜๋„๊ถŒ, ๋น„์ˆ˜๋„๊ถŒ, ๋†์ดŒ์˜ 4๊ฐ€์ง€๋กœ ๊ตฌ๋ถ„ํ•œ๋‹ค. ๋…๋ฆฝ๋ณ€์ˆ˜๋Š” ๋“ฑ๋ก์™ธ๊ตญ์ธ๊ณผ ๋™ํฌ(F4)๋ฅผ ํ•ฉํ•œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ฑ„ํƒ๋œ๋‹ค. โ€˜๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌโ€™๋Š” ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋กœ๋ถ€ํ„ฐ ์ถ”์ •๋˜๊ณ , OECD ๊ธฐ์ค€์— ๋”ฐ๋ผ ์˜๊ตฌโ€ค์ค€์˜๊ตฌ์  ๋ฐ ํ•œ์‹œ์  ์™ธ๊ตญ์ธ์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜๊ณ , ์ „๋ฌธ์ธ๋ ฅ ๋ฐ ๋น„์ „๋ฌธ์ธ๋ ฅ ์™ธ๊ตญ์ธ์œผ๋กœ ๋ถ„๋ฅ˜ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋ณด๋ฉด, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž… ๋ฐ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€๋Š” ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ, ์‹ค์—…, ๊ณ ์šฉ์— ํšจ๊ณผ๋ฅผ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ณ„๋Ÿ‰ํ†ต๊ณ„ ๋ถ„์„์„ ํ†ตํ•ด ๋ฐํžˆ์ง€ ๋ชปํ•˜๋Š” โ€˜์ด๋ฏผ์˜ ๊ณต๊ฐ„์  ํšจ๊ณผโ€™๊ฐ€ ์žˆ์Œ์ด ๋ถ„์„๋˜์—ˆ๋‹ค. ๋‹ค๋งŒ, ์ง€์—ญ ๊ตฌ๋ถ„์— ๋”ฐ๋ผ ์ƒ์ดํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚œ ์ ์€ ์ฃผ๋ชฉํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ํด๋Ÿฌ์ŠคํŠธ ์ง€๋„ ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ฐ ๊ตฌ๋ถ„, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๋Š” ๋†’์€ ์ˆ˜์ค€์œผ๋กœ ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ๊ณผ ๊ณต๊ฐ„ ๊ตฐ์ง‘์ด ํ˜•์„ฑ๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ๋†์ดŒ์—์„œ๋Š” ์ˆ˜๋„๊ถŒ, ๋น„์ˆ˜๋„๊ถŒ์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ๋†’๊ฒŒ ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ์ด ์ธก์ •๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ๊ณ„๋Ÿ‰ํ†ต๊ณ„ ๋ถ„์„์— ์˜ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด๋ฉด, ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ ๋ฐ 65์„ธ ์ด์ƒ ์ทจ์—…์ž, ์™ธ๊ตญ์ธ ์ธ๊ตฌ ๋ฐ ๋†์—…์ž„์—…์–ด์—… ์ทจ์—…์ž ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์—†๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์œผ๋กœ ์ธํ•ด ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ(GRDP)์ด ์ฆ๊ฐ€ํ•œ๋‹ค. ํŠนํžˆ ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์™€ ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ ๊ฐ„ ์ƒ๊ด€๊ณ„์ˆ˜๋Š” 0.916์œผ๋กœ ๋งค์šฐ ๋†’๊ณ , ๊ณต๊ฐ„์  ์ƒ๊ด€์„ฑ๋„ ๋งค์šฐ ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ํŒจ๋„ ํ™•๋ฅ ํšจ๊ณผ SUR ๋ถ„์„(์กฐ์ ˆ๋ณ€์ˆ˜)์— ๋”ฐ๋ฅด๋ฉด, ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€(์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ ๋˜๋Š” ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ)์ด ๋†’์„์ˆ˜๋ก ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ ์ฆ๊ฐ€๊ฐ€ ๊ฐ•ํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋น„์ˆ˜๋„๊ถŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ•ํ™”ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋†์ดŒ์—์„œ ํšก๋‹จ๋ฉด SUR ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์„์ˆ˜๋ก ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ•ํ™”ํ•˜๋Š” ์กฐ์ ˆํšจ๊ณผ๊ฐ€ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋‹ค๋งŒ, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๋Š” โ€˜์ด์›ƒ์˜ ๋ถ€์ •์  ์™ธ๋ถ€ํšจ๊ณผโ€™๊ฐ€ ๋ฐœ์ƒํ•  ์—ฌ์ง€๊ฐ€ ์žˆ๋‹ค. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ๋”๋ฏธ๋ณ€์ˆ˜ ๋ถ„์„์— ์˜ํ•  ๋•Œ ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ์˜ ์ˆ˜์ค€์ด ๋†’์€ ์ง€์—ญ์€ ๋‚ฎ์€ ์ง€์—ญ์— ๋น„ํ•ด ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ์ด ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์€ ์‹ค์—…์— ๋ถ€์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ์ง€๋งŒ, 65์„ธ ์ด์ƒ ์ทจ์—…์ž ์ฆ๊ฐ€ ๋ฐ ๊ฑด์„ค์—…, ๊ด‘์ œ์กฐ์—…, ๋†์—…์ž„์—…์–ด์—… ์ทจ์—…์ž ์ฆ๊ฐ€์— ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰ ์ƒ์‚ฐ์š”์†Œ์™€ ์†Œ๋น„์ž ์—ญํ• ์„ ๊ฒธํ•˜๋Š” ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์œ ์ž…๋˜์–ด ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ์€ ์ฆ๊ฐ€ํ•˜๊ณ , ์‹ค์—…๊ณผ ๊ณ ์šฉ์€ ์„œ๋กœ ์ƒ์‡„ํ•˜๋Š” ์ธก๋ฉด์ด ์žˆ๋‹ค. ํŒจ๋„ ํ™•๋ฅ ํšจ๊ณผ SUR ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ ๋‚ฎ์€ ์ง€์—ญ์— ๋น„ํ•ด ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ์‹ค์—…์ด ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๊ฑด์„ค์—… ์ทจ์—…์ž ์ฆ๊ฐ€๊ฐ€ ๊ฐ•ํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋ฉด์—, ๋น„์ˆ˜๋„๊ถŒ์—์„œ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” 65์„ธ ์ด์ƒ ์ทจ์—…์ž ์ฆ๊ฐ€์— ๋Œ€ํ•ด ๋ถ€์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ง€์—ญ์„ ๊ตฌ๋ถ„ํ•œ ๋”๋ฏธ๋ณ€์ˆ˜ ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ์ˆ˜๋„๊ถŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ 65์„ธ ์ด์ƒ ์ทจ์—…์ž์™€ ๊ด‘์ œ์กฐ์—… ์ทจ์—…์ž๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋” ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ฐ ๊ตฌ๋ถ„ ๋ชจ๋‘๋Š” ์ง€์—ญ๊ฒฝ์ œ์— ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ๊ณผ ๊ณต๊ฐ„ ๊ตฐ์ง‘์ด ํ˜•์„ฑ๋œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ํŠนํžˆ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ, ์‹ค์—…, ๊ณ ์šฉ์— ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ๋น„(้ž)์ „๋ฌธ์ธ๋ ฅ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” ์ „๋ฌธ์ธ๋ ฅ๋ณด๋‹ค ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ(GRDP)์— ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ํฐ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ๊ด‘์ œ์กฐ์—… ์ทจ์—…์ž ์ฆ๊ฐ€์— ๋ฏธ์น˜๋Š” ๊ธ์ •์  ํšจ๊ณผ๋Š” ๊ฑด์„ค์—… ์ทจ์—…์ž ์ฆ๊ฐ€์— ๋ฏธ์น˜๋Š” ๊ธ์ •์  ํšจ๊ณผ๋ณด๋‹ค ํฐ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ํŠนํžˆ ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” 65์„ธ ์ด์ƒ ์ทจ์—…์ž ๋ฐ ๋†์—…์ž„์—…์–ด์—… ์ทจ์—…์ž์— ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋†์ดŒ์—์„œ ์˜ˆ์ƒ ๋ฐ–์˜ ๋ถ„์„ ๊ฒฐ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚œ ์›์ธ์˜ ํ•˜๋‚˜๋Š” ์ธ๊ตฌ ๊ณ ๋ นํ™” ๋ฐ ๋‚ด๊ตญ์ธ์ด ๋†์—…์ž„์—…์–ด์—…์— ์ข…์‚ฌ๋ฅผ ๊ธฐํ”ผ ํ•˜๋Š” ํ˜„์ƒ์œผ๋กœ ์ธํ•ด ๋†์–ด์ดŒ์—์„œ ํ•„์š”ํ•œ ์ธ๋ ฅ์ด ์™ธ๊ตญ์ธ ์ธ๊ตฌ์— ํฌ๊ฒŒ ์˜์กดํ•˜๊ณ  ์žˆ๋Š” ํ˜„์‹ค์ด ๋ฐ˜์˜๋œ ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ๊ฐ€์ง„ ์ •์ฑ…์  ํ•จ์˜๋Š” ์šฐ์„ , ์ง€์—ญ ๊ตฌ๋ถ„์— ๋”ฐ๋ผ ์™ธ๊ตญ์ธ ์œ ์ž…์ •์ฑ…์ด ๋‹ฌ๋ฆฌ ์ˆ˜๋ฆฝ๋  ํ•„์š”๊ฐ€ ์žˆ๋‹ค๋Š” ๋ฐ์ดํ„ฐ์— ๊ธฐ๋ฐ˜ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ˆ˜๋„๊ถŒ์˜ ๊ฒฝ์šฐ โ€˜๋™์‹ฌ์› ๊ตฌ์—ญ ๋ชจํ˜•โ€™์ด ์ ์šฉ๋˜๋ฏ€๋กœ ์ˆ˜๋„๊ถŒ์„ ํ•˜๋‚˜์˜ ์˜์—ญ์œผ๋กœ ๋ณด์•„ ์™ธ๊ตญ์ธ ์œ ์ž…์ •์ฑ… ๋ถ„์„์— ๋ฐ˜์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋†์ดŒ์˜ ๊ฒฝ์šฐ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์œผ๋กœ ์ธํ•œ ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋ฏ€๋กœ ์ •๋ถ€์˜ ์ •์ฑ…๋„ ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๋ฅผ ๋ฐ˜์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ, ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€์€ ์กฐ์ ˆํšจ๊ณผ๊ฐ€ ์กด์žฌํ•œ๋‹ค๋Š” ์‹ค์ฆ์  ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์€ โ€˜์ด์›ƒ์˜ ๊ธ์ •์  ์™ธ๋ถ€ํšจ๊ณผโ€™๊ฐ€ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋‹ค. ๋‹ค๋งŒ, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ์˜ ํšจ๊ณผ๋Š” ๊ฒฝ์ œ์  ์ธก๋ฉด์—์„œ ์ผ๋ถ€ ๊ธ์ •์ ์ธ ๋ฉด๋„ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ํšก๋‹จ๋ฉด SUR ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๊ฐ€ ๋†’์€ ์ง€์—ญ์€ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ๋Š˜์ˆ˜๋ก ์ฃผ๋ฏผ์˜ ์‹ค์—…์ด ์ค„์–ด๋“œ๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋œ๋‹ค. ์ด๊ฒƒ์€ ๋„์‹œ์ƒํƒœํ•™โ€ค๊ฒฝ์ œ์ƒํƒœํ•™์  ๊ด€์ , ์ข‹์€ ๋ถ„๋ฆฌ ๋˜๋Š” ๋‚˜์œ ๋ถ„๋ฆฌ์˜ ๊ด€์ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์†Œ์ˆ˜๋ฏผ์กฑ ์ธํด๋ ˆ์ด๋ธŒ ๊ฒฝ์ œ๋กœ ๋ฐœ์ „๋  ๊ฐ€๋Šฅ์„ฑ์ด ๋ฐฐ์ œํ•  ์ˆ˜ ์—†์–ด ์™ธ๊ตญ์ธ๊ทผ๋กœ์ž์˜ ์‚ฌ์—…์žฅ ์ด๋™ ์ œํ•œ ํ์ง€ ๋“ฑ ํ–ฅํ›„ ๊ฒฝ์ œโ€ค์‚ฌํšŒ์ ์ธ ์ข…ํ•ฉ ๋ถ„์„์ด ํ•„์š”ํ•˜๋‹ค.The distribution of residences of the foreign population is spreading across the country, and the number of ethnic agglomerate is increasing. Therefore, the background of starting this research is the curiosity about what effects are caused by ethnic agglomerate on the local economy. Most of the previous researches on ethnic agglomerate tend to focus mainly on mutual aid for foreigners and ethnic businesses. On the other hand, this research intends to prove that immigration or ethnic agglomerate is an important variable that affects the local economy and the labor market of residents. The level of ethnic agglomerate is measured as a percentage of the foreign population or residential segregation. Therefore, in the effect of the influx of foreign population on the local economy, what kind of change occurs in the effect depending on the level of ethnic agglomerate is analyzed. This research explains that there are theoretical debates about the externalities of foreign neighbors. The supply-oriented theory is used, which states that regional economic growth is affected by the supply of production factors (manpower). As for the effect on the labor market, conflicting arguments are used depending on the Lump of labor theory and the relationship between substitutes or complements. Through this, we are examining the effect of the influx of immigrants on the local economy. In order to reflect the spatial effect in the relationship of immigration on the local economy, spatial relationship and spatial cluster analysis are conducted. In addition, by applying a research method that analyzes at the same time through the simultaneous correlation of three variables of regional economic growth, unemployment, and employment, it is intended to increase the relevance of the analysis results. The independent variable is the foreign population, which is the sum of registered foreigners and foreign nationals who have been issued F4, measured on a regional basis. โ€˜Economically active foreign populationโ€™ is estimated from the foreign population, classified as permanent and temporary foreigners according to OECD standards, and classified as professional and non-professional foreigners. The analysis area is divided into four categories: nationwide, metropolitan area, non-metropolitan area, and rural area. According to the analysis results of this research, it has been proved that the foreign population intensively resides in a specific area, which has an effect on the economic growth and labor market of that area. It is analyzed that the inflow of the foreign population and ethnic agglomerate have an effect on the GRDP, unemployment, and employment. It is analyzed that there is a โ€˜spatial effect of immigrationโ€™ that cannot be revealed through econometric analysis. However, it is worth noting that the analysis results differ depending on the region. The main meaningful analysis results are as follows. According to the cluster map analysis, the foreign population, the proportion of the foreign population, and the residential segregation show a high level of spatial correlation and spatial clustering. In particular, in rural areas, spatial correlation is measured relatively high compared to metropolitan and non-metropolitan areas. In addition, according to the correlation based on econometric analysis in rural areas, it is analyzed that there is no correlation between the foreign population and the employed over 65 years old, the foreign population and the agricultural, forestry and fishery workers. The influx of foreign populations increases the GRDP. In particular, in rural areas, the correlation coefficient between the foreign population and the GRDP is 0.916, which is very high, and the spatial correlation is also very high. According to the panel random effect SUR analysis nationwide, it is analyzed that the higher the level of ethnic agglomerate(proportion of foreign population or residential segregation), the higher the GRDP. In non-metropolitan regions, it is analyzed that the regions with a high proportion of foreign population reinforce the effect of economically active foreign population increasing the GRDP. According to the cross-sectional SUR analysis in rural areas, the higher the proportion of the foreign population, the more the moderating effect of economically active foreign population is to increase the GRDP. Although the inflow of the foreign population has an effect on increasing unemployment, it appears that it has a positive effect on the increase in the number of employed people aged 65 and over and the increase in employment in the construction, manufacturing, agricultural, forestry, and fishery industries. In other words, the influx of foreign populations who serve both as factors of production and consumers increases regional economic growth. Unemployment and employment are mutually exclusive. According to the panel random effect SUR analysis in rural areas, the unemployment rate decreases as the foreign population increases in regions with a high proportion of foreigners compared to regions with a low proportion. In regions with a high proportion of foreign population in the country, the increase in the number of economically active foreign population intensifies the increase in the number of people employed in the construction industry. On the other hand, the economically active foreign population in non-metropolitan areas appears to have a negative effect on the increase in the number of employed people aged 65 and over. According to the analysis of dummy variables divided by region, in the metropolitan area, in regions with a high proportion of foreign population, those aged 65 and over and those employed in manufacturing are relatively higher. It is analyzed that spatial correlations and spatial clusters are formed in the local economy for each division of the foreign population. In particular, the economically active foreign population has a relatively high effect on GRDP, unemployment, and employment. It is analyzed that the non-professional foreign population has a greater positive effect on GRDP than the professional foreign population. The positive effect of the foreign population on the increase of employment in the manufacturing industry is analyzed to be greater than the effect on the increase in employment of the construction industry. In particular, the foreign population in rural areas appears to have a positive effect on those aged 65 and over and those employed in agriculture, forestry and fisheries. One of the reasons for the unexpected analysis results in rural areas is the fact that the labor force required in rural areas is highly dependent on the foreign population due to the aging of the population and the phenomenon of Koreans avoiding engaging in agricultural, forestry and fishery. The policy implications of this research are as follows. First, the results of analysis based on data suggesting that different policies for influx of foreigners need to be established according to regional classification are presented. In the case of the metropolitan area, the โ€˜Concentric Zone Modelโ€™ is applied, so it is necessary to consider the metropolitan area as one area and reflect it in the analysis of the foreign population inflow policy. In the case of rural areas, the influx of foreigners has positive effects, so the government's policies need to reflect these changes. In addition, the empirical analysis results suggest that the level of ethnic agglomerate has a moderating effect. As for the proportion of the foreign population, โ€˜positive externalities of neighborsโ€™ exist. However, the effect of residential segregation sometimes has some positive aspects from an economic point of view. For example, according to a cross-sectional SUR analysis across the country, it is analyzed that unemployment decreases as the number of economically active foreign population increases in regions with high residential segregation. This is not only a social point of view of good segregation or bad segregation, but also the possibility of developing into an ethnic enclave economy, so a comprehensive economic and social analysis is needed in the future.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ ๋ฐ ๋ฒ”์œ„ 9 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• 11 ์ œ 2 ์žฅ ์ด๋ก  ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  14 ์ œ 1 ์ ˆ ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€์—ญ 14 1. ๋ถ„์„์ง€์—ญ์œผ๋กœ์„œ ๋„์‹œโ€ค๋†์ดŒ 14 2. ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ 18 1) ์˜์˜ 18 2) ์™ธ๊ตญ์ธ ์œ ์ž…์˜ ์š”์ธ 20 3) ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€์—ญ: ์ •์˜, ํšจ๊ณผ 25 4) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ณต๊ฐ„์  ๋ถ„ํฌ 28 5) ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ํšจ๊ณผ(๋…ผ๋ณ€ ๋Œ€๋ฆฝ ๊ตฌ์กฐ) 31 (1) ์™ธ๊ตญ์ธ ์ด์›ƒ์˜ ์™ธ๋ถ€ํšจ๊ณผ 31 (2) ๊ธ์ •์  ์™ธ๋ถ€ํšจ๊ณผ 32 (3) ๋ถ€์ •์  ์™ธ๋ถ€ํšจ๊ณผ 38 ์ œ 2 ์ ˆ ์ด๋ฏผ๊ณผ ์ง€์—ญ๊ฒฝ์ œ์˜ ๊ด€๊ณ„ 44 1. ๊ฒฝ์ œ์„ฑ์žฅ 44 1) ๊ฒฝ์ œ์„ฑ์žฅ์„ ์ด๋ฃจ๋Š” ์š”์ธ๋“ค 44 2) ๊ฒฝ์ œ์„ฑ์žฅ ์„ค๋ช… ์ด๋ก (๋…ผ๋ณ€ ๋Œ€๋ฆฝ ๊ตฌ์กฐ) 47 (1) ๋…ธ๋™๊ณผ ์ธ์ ์ž๋ณธ ๊ณต๊ธ‰์œผ๋กœ ์ธํ•œ ๊ฒฝ์ œ์„ฑ์žฅ 47 (2) ๋ฐ˜๋ก  55 2. ๋…ธ๋™์‹œ์žฅ 57 1) ์˜์˜ 57 2) ์‹ค์—…โ€ค๊ณ ์šฉ ์„ค๋ช… ์ด๋ก (๋…ผ๋ณ€ ๋Œ€๋ฆฝ ๊ตฌ์กฐ) 58 (1) ๋Œ€์ฒด์žฌ์™€ ๋…ธ๋™์ด๋Ÿ‰์„ค 58 (2) ๋…ธ๋™์‹œ์žฅ ๋ถ„์ ˆํ™” ๋˜๋Š” ๋ณด์™„์žฌ 64 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ์ฐจ๋ณ„์„ฑ 70 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ์„ค๊ณ„ 74 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ชจํ˜• ๋ฐ ๋ถ„์„ ํ‹€ 74 1. ๋ฌธ์ œ์˜ ์ œ๊ธฐ 74 2. ์—ฐ๊ตฌ์˜ ๋‹จ๊ณ„ ๋ฐ ๋ชจํ˜• 75 3. ๋ถ„์„ ํ‹€ 77 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๊ฐ€์„ค 82 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ์ž๋ฃŒ 88 1. ์ข…์†๋ณ€์ˆ˜ 88 1) ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ: ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ 88 2) ์ง€์—ญ ์‹ค์—…: ์‹ค์—…๊ธ‰์—ฌ์ž 92 3) ์ง€์—ญ ๊ณ ์šฉ: ์ทจ์—…์ž 96 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 103 1) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ตฌ๋ถ„ 103 2) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ํ™•์‚ฐ๊ณผ ์ง€์—ญ์  ๋ถ„ํฌ 115 3. ์กฐ์ ˆ๋ณ€์ˆ˜ 131 1) ์˜์˜ 131 2) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ 132 3) ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ 135 4) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ ๋ฐ ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ ๊ฐ„ ๊ด€๊ณ„ 142 4. ํ†ต์ œ๋ณ€์ˆ˜ 149 ์ œ 4 ์ ˆ ๋ถ„์„ ๋ฐฉ๋ฒ• 153 ์ œ 4 ์žฅ ์‹ค์ฆ๋ถ„์„ ๊ฒฐ๊ณผ 160 ์ œ 1 ์ ˆ ์ž๋ฃŒ์˜ ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ 160 1. ๋ถ„์„์— ํ™œ์šฉ๋œ ๋ณ€์ˆ˜๋“ค ๊ฐœ๊ด€ 160 2. ๊ธฐ์ดˆํ†ต๊ณ„๋Ÿ‰ ๋ฐ ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 162 3. ๊ณต๊ฐ„๋ถ„์„ ์ผ๋ณ€๋Ÿ‰ 183 ์ œ 2 ์ ˆ ๊ณต๊ฐ„ ๊ด€๊ณ„ ๋ถ„์„ 210 1. ์ด๋ฏผ๊ณผ ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ 210 1) ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ 210 2) ์ˆ˜๋„๊ถŒ 218 3) ๋น„์ˆ˜๋„๊ถŒ 228 4) ๋†์ดŒ 238 2. ์ด๋ฏผ๊ณผ ์ง€์—ญ ๋…ธ๋™์‹œ์žฅ 246 1) ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ 246 2) ์ˆ˜๋„๊ถŒ 274 3) ๋น„์ˆ˜๋„๊ถŒ 283 4) ๋†์ดŒ 291 ์ œ 3 ์ ˆ ์ด๋ฏผ๊ณผ ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ, ์‹ค์—…, ๊ณ ์šฉ์˜ SUR ๋ถ„์„ 302 1. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ 302 2. ์ˆ˜๋„๊ถŒ 333 3. ๋น„์ˆ˜๋„๊ถŒ 355 4. ๋†์ดŒ 381 ์ œ 5 ์žฅ ๊ฒฐ๋ก  396 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์š”์•ฝ 396 ์ œ 2 ์ ˆ ์‹œ์‚ฌ์  ๋ฐ ์ •์ฑ…์  ํ•จ์˜ 403 ์ฐธ๊ณ ๋ฌธํ—Œ 407 Abstract 417๋ฐ•

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    ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ง€์—ญ์—์„œ ์ƒˆ๋กœ์šด ํ–‰์œ„์ž๋กœ ๋“ฑ์žฅํ•˜๋ฉด์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ฑฐ์ฃผ ๋ถ„ํฌ์™€ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€๋„ ์ฆ๊ฐ€ํ•˜๋Š” ์ถ”์„ธ์ด๋‹ค. ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€์€ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ(%) ๋˜๋Š” ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๋กœ ์ธก์ •๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์ด ์ง€์—ญ๊ฒฝ์ œ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ์—์„œ ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€์— ๋”ฐ๋ผ ๊ทธ ํšจ๊ณผ์— ์–ด๋–ค ๋ณ€ํ™”๊ฐ€ ๋ฐœ์ƒํ•˜๋Š”์ง€๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์™ธ๊ตญ์ธ ์ด์›ƒ์˜ ์™ธ๋ถ€ํšจ๊ณผ์— ๋Œ€ํ•ด ์ด๋ก ์  ๋…ผ์Ÿ์ด ์žˆ์Œ์„ ์„ค๋ช…ํ•œ๋‹ค. ์ง€์—ญ์˜ ๊ฒฝ์ œ์„ฑ์žฅ์€ ์ƒ์‚ฐ์š”์†Œ(์ธ๋ ฅ)์˜ ๊ณต๊ธ‰์— ๋”ฐ๋ผ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค๋Š” ๊ณต๊ธ‰์ค‘์‹œ์ด๋ก ์„ ํ™œ์šฉํ•˜๊ณ , ๋…ธ๋™์‹œ์žฅ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ๋Š” ๋…ธ๋™์ด๋Ÿ‰์„ค๊ณผ ๋Œ€์ฒด์žฌ ๋˜๋Š” ๋ณด์™„์žฌ ๊ด€๊ณ„์— ๋”ฐ๋ผ ์„œ๋กœ ๋Œ€๋ฆฝํ•˜๋Š” ๋…ผ์Ÿ์„ ํ™œ์šฉํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ด๋ฏผ์˜ ๊ณต๊ฐ„์  ํšจ๊ณผ๋ฅผ ๋ฐ˜์˜ํ•˜๊ธฐ ์œ„ํ•ด ๊ณต๊ฐ„๋ถ„์„์„ ์‹œํ–‰ํ•˜๊ณ , ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅโ€ค์‹ค์—…โ€ค๊ณ ์šฉ์— ๋Œ€ํ•ด ๋™์‹œ์— ํ•œ๊บผ๋ฒˆ์— ๋ถ„์„ํ•˜๋Š” ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•จ์œผ๋กœ์จ ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ์ ์‹ค์„ฑ์„ ๋†’์ด๊ณ ์ž ํ•œ๋‹ค. ๋ถ„์„์ง€์—ญ์€ ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ, ์ˆ˜๋„๊ถŒ, ๋น„์ˆ˜๋„๊ถŒ, ๋†์ดŒ์˜ 4๊ฐ€์ง€๋กœ ๊ตฌ๋ถ„ํ•œ๋‹ค. ๋…๋ฆฝ๋ณ€์ˆ˜๋Š” ๋“ฑ๋ก์™ธ๊ตญ์ธ๊ณผ ๋™ํฌ(F4)๋ฅผ ํ•ฉํ•œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ฑ„ํƒ๋œ๋‹ค. โ€˜๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌโ€™๋Š” ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋กœ๋ถ€ํ„ฐ ์ถ”์ •๋˜๊ณ , OECD ๊ธฐ์ค€์— ๋”ฐ๋ผ ์˜๊ตฌโ€ค์ค€์˜๊ตฌ์  ๋ฐ ํ•œ์‹œ์  ์™ธ๊ตญ์ธ์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜๊ณ , ์ „๋ฌธ์ธ๋ ฅ ๋ฐ ๋น„์ „๋ฌธ์ธ๋ ฅ ์™ธ๊ตญ์ธ์œผ๋กœ ๋ถ„๋ฅ˜ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋ณด๋ฉด, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž… ๋ฐ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€๋Š” ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ, ์‹ค์—…, ๊ณ ์šฉ์— ํšจ๊ณผ๋ฅผ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ณ„๋Ÿ‰ํ†ต๊ณ„ ๋ถ„์„์„ ํ†ตํ•ด ๋ฐํžˆ์ง€ ๋ชปํ•˜๋Š” โ€˜์ด๋ฏผ์˜ ๊ณต๊ฐ„์  ํšจ๊ณผโ€™๊ฐ€ ์žˆ์Œ์ด ๋ถ„์„๋˜์—ˆ๋‹ค. ๋‹ค๋งŒ, ์ง€์—ญ ๊ตฌ๋ถ„์— ๋”ฐ๋ผ ์ƒ์ดํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚œ ์ ์€ ์ฃผ๋ชฉํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ํด๋Ÿฌ์ŠคํŠธ ์ง€๋„ ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ฐ ๊ตฌ๋ถ„, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๋Š” ๋†’์€ ์ˆ˜์ค€์œผ๋กœ ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ๊ณผ ๊ณต๊ฐ„ ๊ตฐ์ง‘์ด ํ˜•์„ฑ๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ๋†์ดŒ์—์„œ๋Š” ์ˆ˜๋„๊ถŒ, ๋น„์ˆ˜๋„๊ถŒ์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ๋†’๊ฒŒ ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ์ด ์ธก์ •๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ๊ณ„๋Ÿ‰ํ†ต๊ณ„ ๋ถ„์„์— ์˜ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด๋ฉด, ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ ๋ฐ 65์„ธ ์ด์ƒ ์ทจ์—…์ž, ์™ธ๊ตญ์ธ ์ธ๊ตฌ ๋ฐ ๋†์—…์ž„์—…์–ด์—… ์ทจ์—…์ž ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์—†๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์œผ๋กœ ์ธํ•ด ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ(GRDP)์ด ์ฆ๊ฐ€ํ•œ๋‹ค. ํŠนํžˆ ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์™€ ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ ๊ฐ„ ์ƒ๊ด€๊ณ„์ˆ˜๋Š” 0.916์œผ๋กœ ๋งค์šฐ ๋†’๊ณ , ๊ณต๊ฐ„์  ์ƒ๊ด€์„ฑ๋„ ๋งค์šฐ ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ํŒจ๋„ ํ™•๋ฅ ํšจ๊ณผ SUR ๋ถ„์„(์กฐ์ ˆ๋ณ€์ˆ˜)์— ๋”ฐ๋ฅด๋ฉด, ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€(์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ ๋˜๋Š” ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ)์ด ๋†’์„์ˆ˜๋ก ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ ์ฆ๊ฐ€๊ฐ€ ๊ฐ•ํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋น„์ˆ˜๋„๊ถŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ•ํ™”ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋†์ดŒ์—์„œ ํšก๋‹จ๋ฉด SUR ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์„์ˆ˜๋ก ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ•ํ™”ํ•˜๋Š” ์กฐ์ ˆํšจ๊ณผ๊ฐ€ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋‹ค๋งŒ, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๋Š” โ€˜์ด์›ƒ์˜ ๋ถ€์ •์  ์™ธ๋ถ€ํšจ๊ณผโ€™๊ฐ€ ๋ฐœ์ƒํ•  ์—ฌ์ง€๊ฐ€ ์žˆ๋‹ค. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ๋”๋ฏธ๋ณ€์ˆ˜ ๋ถ„์„์— ์˜ํ•  ๋•Œ ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ์˜ ์ˆ˜์ค€์ด ๋†’์€ ์ง€์—ญ์€ ๋‚ฎ์€ ์ง€์—ญ์— ๋น„ํ•ด ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ์ด ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์€ ์‹ค์—…์— ๋ถ€์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ์ง€๋งŒ, 65์„ธ ์ด์ƒ ์ทจ์—…์ž ์ฆ๊ฐ€ ๋ฐ ๊ฑด์„ค์—…, ๊ด‘์ œ์กฐ์—…, ๋†์—…์ž„์—…์–ด์—… ์ทจ์—…์ž ์ฆ๊ฐ€์— ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰ ์ƒ์‚ฐ์š”์†Œ์™€ ์†Œ๋น„์ž ์—ญํ• ์„ ๊ฒธํ•˜๋Š” ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์œ ์ž…๋˜์–ด ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ์€ ์ฆ๊ฐ€ํ•˜๊ณ , ์‹ค์—…๊ณผ ๊ณ ์šฉ์€ ์„œ๋กœ ์ƒ์‡„ํ•˜๋Š” ์ธก๋ฉด์ด ์žˆ๋‹ค. ํŒจ๋„ ํ™•๋ฅ ํšจ๊ณผ SUR ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ ๋‚ฎ์€ ์ง€์—ญ์— ๋น„ํ•ด ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ์‹ค์—…์ด ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๊ฑด์„ค์—… ์ทจ์—…์ž ์ฆ๊ฐ€๊ฐ€ ๊ฐ•ํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋ฉด์—, ๋น„์ˆ˜๋„๊ถŒ์—์„œ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” 65์„ธ ์ด์ƒ ์ทจ์—…์ž ์ฆ๊ฐ€์— ๋Œ€ํ•ด ๋ถ€์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ง€์—ญ์„ ๊ตฌ๋ถ„ํ•œ ๋”๋ฏธ๋ณ€์ˆ˜ ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ์ˆ˜๋„๊ถŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์ด ๋†’์€ ์ง€์—ญ์€ 65์„ธ ์ด์ƒ ์ทจ์—…์ž์™€ ๊ด‘์ œ์กฐ์—… ์ทจ์—…์ž๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋” ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ฐ ๊ตฌ๋ถ„ ๋ชจ๋‘๋Š” ์ง€์—ญ๊ฒฝ์ œ์— ๊ณต๊ฐ„์  ์—ฐ๊ด€์„ฑ๊ณผ ๊ณต๊ฐ„ ๊ตฐ์ง‘์ด ํ˜•์„ฑ๋œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ํŠนํžˆ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ, ์‹ค์—…, ๊ณ ์šฉ์— ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ๋น„(้ž)์ „๋ฌธ์ธ๋ ฅ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” ์ „๋ฌธ์ธ๋ ฅ๋ณด๋‹ค ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ(GRDP)์— ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ํฐ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ๊ด‘์ œ์กฐ์—… ์ทจ์—…์ž ์ฆ๊ฐ€์— ๋ฏธ์น˜๋Š” ๊ธ์ •์  ํšจ๊ณผ๋Š” ๊ฑด์„ค์—… ์ทจ์—…์ž ์ฆ๊ฐ€์— ๋ฏธ์น˜๋Š” ๊ธ์ •์  ํšจ๊ณผ๋ณด๋‹ค ํฐ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ํŠนํžˆ ๋†์ดŒ์—์„œ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๋Š” 65์„ธ ์ด์ƒ ์ทจ์—…์ž ๋ฐ ๋†์—…์ž„์—…์–ด์—… ์ทจ์—…์ž์— ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋†์ดŒ์—์„œ ์˜ˆ์ƒ ๋ฐ–์˜ ๋ถ„์„ ๊ฒฐ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚œ ์›์ธ์˜ ํ•˜๋‚˜๋Š” ์ธ๊ตฌ ๊ณ ๋ นํ™” ๋ฐ ๋‚ด๊ตญ์ธ์ด ๋†์—…์ž„์—…์–ด์—…์— ์ข…์‚ฌ๋ฅผ ๊ธฐํ”ผ ํ•˜๋Š” ํ˜„์ƒ์œผ๋กœ ์ธํ•ด ๋†์–ด์ดŒ์—์„œ ํ•„์š”ํ•œ ์ธ๋ ฅ์ด ์™ธ๊ตญ์ธ ์ธ๊ตฌ์— ํฌ๊ฒŒ ์˜์กดํ•˜๊ณ  ์žˆ๋Š” ํ˜„์‹ค์ด ๋ฐ˜์˜๋œ ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ๊ฐ€์ง„ ์ •์ฑ…์  ํ•จ์˜๋Š” ์šฐ์„ , ์ง€์—ญ ๊ตฌ๋ถ„์— ๋”ฐ๋ผ ์™ธ๊ตญ์ธ ์œ ์ž…์ •์ฑ…์ด ๋‹ฌ๋ฆฌ ์ˆ˜๋ฆฝ๋  ํ•„์š”๊ฐ€ ์žˆ๋‹ค๋Š” ๋ฐ์ดํ„ฐ์— ๊ธฐ๋ฐ˜ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ˆ˜๋„๊ถŒ์˜ ๊ฒฝ์šฐ โ€˜๋™์‹ฌ์› ๊ตฌ์—ญ ๋ชจํ˜•โ€™์ด ์ ์šฉ๋˜๋ฏ€๋กœ ์ˆ˜๋„๊ถŒ์„ ํ•˜๋‚˜์˜ ์˜์—ญ์œผ๋กœ ๋ณด์•„ ์™ธ๊ตญ์ธ ์œ ์ž…์ •์ฑ… ๋ถ„์„์— ๋ฐ˜์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋†์ดŒ์˜ ๊ฒฝ์šฐ ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ์œ ์ž…์œผ๋กœ ์ธํ•œ ๊ธ์ •์  ํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋ฏ€๋กœ ์ •๋ถ€์˜ ์ •์ฑ…๋„ ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๋ฅผ ๋ฐ˜์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ, ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ์ˆ˜์ค€์€ ์กฐ์ ˆํšจ๊ณผ๊ฐ€ ์กด์žฌํ•œ๋‹ค๋Š” ์‹ค์ฆ์  ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ์€ โ€˜์ด์›ƒ์˜ ๊ธ์ •์  ์™ธ๋ถ€ํšจ๊ณผโ€™๊ฐ€ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋‹ค. ๋‹ค๋งŒ, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ์˜ ํšจ๊ณผ๋Š” ๊ฒฝ์ œ์  ์ธก๋ฉด์—์„œ ์ผ๋ถ€ ๊ธ์ •์ ์ธ ๋ฉด๋„ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ์—์„œ ํšก๋‹จ๋ฉด SUR ๋ถ„์„์— ๋”ฐ๋ฅด๋ฉด, ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ๊ฐ€ ๋†’์€ ์ง€์—ญ์€ ๊ฒฝ์ œํ™œ๋™ ์™ธ๊ตญ์ธ ์ธ๊ตฌ๊ฐ€ ๋Š˜์ˆ˜๋ก ์ฃผ๋ฏผ์˜ ์‹ค์—…์ด ์ค„์–ด๋“œ๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋œ๋‹ค. ์ด๊ฒƒ์€ ๋„์‹œ์ƒํƒœํ•™โ€ค๊ฒฝ์ œ์ƒํƒœํ•™์  ๊ด€์ , ์ข‹์€ ๋ถ„๋ฆฌ ๋˜๋Š” ๋‚˜์œ ๋ถ„๋ฆฌ์˜ ๊ด€์ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์†Œ์ˆ˜๋ฏผ์กฑ ์ธํด๋ ˆ์ด๋ธŒ ๊ฒฝ์ œ๋กœ ๋ฐœ์ „๋  ๊ฐ€๋Šฅ์„ฑ์ด ๋ฐฐ์ œํ•  ์ˆ˜ ์—†์–ด ์™ธ๊ตญ์ธ๊ทผ๋กœ์ž์˜ ์‚ฌ์—…์žฅ ์ด๋™ ์ œํ•œ ํ์ง€ ๋“ฑ ํ–ฅํ›„ ๊ฒฝ์ œโ€ค์‚ฌํšŒ์ ์ธ ์ข…ํ•ฉ ๋ถ„์„์ด ํ•„์š”ํ•˜๋‹ค.The distribution of residences of the foreign population is spreading across the country, and the number of ethnic agglomerate is increasing. Therefore, the background of starting this research is the curiosity about what effects are caused by ethnic agglomerate on the local economy. Most of the previous researches on ethnic agglomerate tend to focus mainly on mutual aid for foreigners and ethnic businesses. On the other hand, this research intends to prove that immigration or ethnic agglomerate is an important variable that affects the local economy and the labor market of residents. The level of ethnic agglomerate is measured as a percentage of the foreign population or residential segregation. Therefore, in the effect of the influx of foreign population on the local economy, what kind of change occurs in the effect depending on the level of ethnic agglomerate is analyzed. This research explains that there are theoretical debates about the externalities of foreign neighbors. The supply-oriented theory is used, which states that regional economic growth is affected by the supply of production factors (manpower). As for the effect on the labor market, conflicting arguments are used depending on the Lump of labor theory and the relationship between substitutes or complements. Through this, we are examining the effect of the influx of immigrants on the local economy. In order to reflect the spatial effect in the relationship of immigration on the local economy, spatial relationship and spatial cluster analysis are conducted. In addition, by applying a research method that analyzes at the same time through the simultaneous correlation of three variables of regional economic growth, unemployment, and employment, it is intended to increase the relevance of the analysis results. The independent variable is the foreign population, which is the sum of registered foreigners and foreign nationals who have been issued F4, measured on a regional basis. โ€˜Economically active foreign populationโ€™ is estimated from the foreign population, classified as permanent and temporary foreigners according to OECD standards, and classified as professional and non-professional foreigners. The analysis area is divided into four categories: nationwide, metropolitan area, non-metropolitan area, and rural area. According to the analysis results of this research, it has been proved that the foreign population intensively resides in a specific area, which has an effect on the economic growth and labor market of that area. It is analyzed that the inflow of the foreign population and ethnic agglomerate have an effect on the GRDP, unemployment, and employment. It is analyzed that there is a โ€˜spatial effect of immigrationโ€™ that cannot be revealed through econometric analysis. However, it is worth noting that the analysis results differ depending on the region. The main meaningful analysis results are as follows. According to the cluster map analysis, the foreign population, the proportion of the foreign population, and the residential segregation show a high level of spatial correlation and spatial clustering. In particular, in rural areas, spatial correlation is measured relatively high compared to metropolitan and non-metropolitan areas. In addition, according to the correlation based on econometric analysis in rural areas, it is analyzed that there is no correlation between the foreign population and the employed over 65 years old, the foreign population and the agricultural, forestry and fishery workers. The influx of foreign populations increases the GRDP. In particular, in rural areas, the correlation coefficient between the foreign population and the GRDP is 0.916, which is very high, and the spatial correlation is also very high. According to the panel random effect SUR analysis nationwide, it is analyzed that the higher the level of ethnic agglomerate(proportion of foreign population or residential segregation), the higher the GRDP. In non-metropolitan regions, it is analyzed that the regions with a high proportion of foreign population reinforce the effect of economically active foreign population increasing the GRDP. According to the cross-sectional SUR analysis in rural areas, the higher the proportion of the foreign population, the more the moderating effect of economically active foreign population is to increase the GRDP. Although the inflow of the foreign population has an effect on increasing unemployment, it appears that it has a positive effect on the increase in the number of employed people aged 65 and over and the increase in employment in the construction, manufacturing, agricultural, forestry, and fishery industries. In other words, the influx of foreign populations who serve both as factors of production and consumers increases regional economic growth. Unemployment and employment are mutually exclusive. According to the panel random effect SUR analysis in rural areas, the unemployment rate decreases as the foreign population increases in regions with a high proportion of foreigners compared to regions with a low proportion. In regions with a high proportion of foreign population in the country, the increase in the number of economically active foreign population intensifies the increase in the number of people employed in the construction industry. On the other hand, the economically active foreign population in non-metropolitan areas appears to have a negative effect on the increase in the number of employed people aged 65 and over. According to the analysis of dummy variables divided by region, in the metropolitan area, in regions with a high proportion of foreign population, those aged 65 and over and those employed in manufacturing are relatively higher. It is analyzed that spatial correlations and spatial clusters are formed in the local economy for each division of the foreign population. In particular, the economically active foreign population has a relatively high effect on GRDP, unemployment, and employment. It is analyzed that the non-professional foreign population has a greater positive effect on GRDP than the professional foreign population. The positive effect of the foreign population on the increase of employment in the manufacturing industry is analyzed to be greater than the effect on the increase in employment of the construction industry. In particular, the foreign population in rural areas appears to have a positive effect on those aged 65 and over and those employed in agriculture, forestry and fisheries. One of the reasons for the unexpected analysis results in rural areas is the fact that the labor force required in rural areas is highly dependent on the foreign population due to the aging of the population and the phenomenon of Koreans avoiding engaging in agricultural, forestry and fishery. The policy implications of this research are as follows. First, the results of analysis based on data suggesting that different policies for influx of foreigners need to be established according to regional classification are presented. In the case of the metropolitan area, the โ€˜Concentric Zone Modelโ€™ is applied, so it is necessary to consider the metropolitan area as one area and reflect it in the analysis of the foreign population inflow policy. In the case of rural areas, the influx of foreigners has positive effects, so the government's policies need to reflect these changes. In addition, the empirical analysis results suggest that the level of ethnic agglomerate has a moderating effect. As for the proportion of the foreign population, โ€˜positive externalities of neighborsโ€™ exist. However, the effect of residential segregation sometimes has some positive aspects from an economic point of view. For example, according to a cross-sectional SUR analysis across the country, it is analyzed that unemployment decreases as the number of economically active foreign population increases in regions with high residential segregation. This is not only a social point of view of good segregation or bad segregation, but also the possibility of developing into an ethnic enclave economy, so a comprehensive economic and social analysis is needed in the future.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ ๋ฐ ๋ฒ”์œ„ 9 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• 11 ์ œ 2 ์žฅ ์ด๋ก  ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  14 ์ œ 1 ์ ˆ ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€์—ญ 14 1. ๋ถ„์„์ง€์—ญ์œผ๋กœ์„œ ๋„์‹œโ€ค๋†์ดŒ 14 2. ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ 18 1) ์˜์˜ 18 2) ์™ธ๊ตญ์ธ ์œ ์ž…์˜ ์š”์ธ 20 3) ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์ง€์—ญ: ์ •์˜, ํšจ๊ณผ 25 4) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ณต๊ฐ„์  ๋ถ„ํฌ 28 5) ์™ธ๊ตญ์ธ ๋ฐ€์ง‘ ๊ฑฐ์ฃผ์˜ ํšจ๊ณผ(๋…ผ๋ณ€ ๋Œ€๋ฆฝ ๊ตฌ์กฐ) 31 (1) ์™ธ๊ตญ์ธ ์ด์›ƒ์˜ ์™ธ๋ถ€ํšจ๊ณผ 31 (2) ๊ธ์ •์  ์™ธ๋ถ€ํšจ๊ณผ 32 (3) ๋ถ€์ •์  ์™ธ๋ถ€ํšจ๊ณผ 38 ์ œ 2 ์ ˆ ์ด๋ฏผ๊ณผ ์ง€์—ญ๊ฒฝ์ œ์˜ ๊ด€๊ณ„ 44 1. ๊ฒฝ์ œ์„ฑ์žฅ 44 1) ๊ฒฝ์ œ์„ฑ์žฅ์„ ์ด๋ฃจ๋Š” ์š”์ธ๋“ค 44 2) ๊ฒฝ์ œ์„ฑ์žฅ ์„ค๋ช… ์ด๋ก (๋…ผ๋ณ€ ๋Œ€๋ฆฝ ๊ตฌ์กฐ) 47 (1) ๋…ธ๋™๊ณผ ์ธ์ ์ž๋ณธ ๊ณต๊ธ‰์œผ๋กœ ์ธํ•œ ๊ฒฝ์ œ์„ฑ์žฅ 47 (2) ๋ฐ˜๋ก  55 2. ๋…ธ๋™์‹œ์žฅ 57 1) ์˜์˜ 57 2) ์‹ค์—…โ€ค๊ณ ์šฉ ์„ค๋ช… ์ด๋ก (๋…ผ๋ณ€ ๋Œ€๋ฆฝ ๊ตฌ์กฐ) 58 (1) ๋Œ€์ฒด์žฌ์™€ ๋…ธ๋™์ด๋Ÿ‰์„ค 58 (2) ๋…ธ๋™์‹œ์žฅ ๋ถ„์ ˆํ™” ๋˜๋Š” ๋ณด์™„์žฌ 64 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ์ฐจ๋ณ„์„ฑ 70 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ์„ค๊ณ„ 74 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ชจํ˜• ๋ฐ ๋ถ„์„ ํ‹€ 74 1. ๋ฌธ์ œ์˜ ์ œ๊ธฐ 74 2. ์—ฐ๊ตฌ์˜ ๋‹จ๊ณ„ ๋ฐ ๋ชจํ˜• 75 3. ๋ถ„์„ ํ‹€ 77 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๊ฐ€์„ค 82 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ์ž๋ฃŒ 88 1. ์ข…์†๋ณ€์ˆ˜ 88 1) ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ: ์ง€์—ญ๋‚ด์ด์ƒ์‚ฐ 88 2) ์ง€์—ญ ์‹ค์—…: ์‹ค์—…๊ธ‰์—ฌ์ž 92 3) ์ง€์—ญ ๊ณ ์šฉ: ์ทจ์—…์ž 96 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 103 1) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๊ตฌ๋ถ„ 103 2) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ํ™•์‚ฐ๊ณผ ์ง€์—ญ์  ๋ถ„ํฌ 115 3. ์กฐ์ ˆ๋ณ€์ˆ˜ 131 1) ์˜์˜ 131 2) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ 132 3) ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ 135 4) ์™ธ๊ตญ์ธ ์ธ๊ตฌ์˜ ๋น„์œจ ๋ฐ ๊ฑฐ์ฃผ ๋ถ„๋ฆฌ ๊ฐ„ ๊ด€๊ณ„ 142 4. ํ†ต์ œ๋ณ€์ˆ˜ 149 ์ œ 4 ์ ˆ ๋ถ„์„ ๋ฐฉ๋ฒ• 153 ์ œ 4 ์žฅ ์‹ค์ฆ๋ถ„์„ ๊ฒฐ๊ณผ 160 ์ œ 1 ์ ˆ ์ž๋ฃŒ์˜ ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ 160 1. ๋ถ„์„์— ํ™œ์šฉ๋œ ๋ณ€์ˆ˜๋“ค ๊ฐœ๊ด€ 160 2. ๊ธฐ์ดˆํ†ต๊ณ„๋Ÿ‰ ๋ฐ ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 162 3. ๊ณต๊ฐ„๋ถ„์„ ์ผ๋ณ€๋Ÿ‰ 183 ์ œ 2 ์ ˆ ๊ณต๊ฐ„ ๊ด€๊ณ„ ๋ถ„์„ 210 1. ์ด๋ฏผ๊ณผ ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ 210 1) ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ 210 2) ์ˆ˜๋„๊ถŒ 218 3) ๋น„์ˆ˜๋„๊ถŒ 228 4) ๋†์ดŒ 238 2. ์ด๋ฏผ๊ณผ ์ง€์—ญ ๋…ธ๋™์‹œ์žฅ 246 1) ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ 246 2) ์ˆ˜๋„๊ถŒ 274 3) ๋น„์ˆ˜๋„๊ถŒ 283 4) ๋†์ดŒ 291 ์ œ 3 ์ ˆ ์ด๋ฏผ๊ณผ ์ง€์—ญ ๊ฒฝ์ œ์„ฑ์žฅ, ์‹ค์—…, ๊ณ ์šฉ์˜ SUR ๋ถ„์„ 302 1. ์ „๊ตญ ์‹œ๊ตฐ๊ตฌ 302 2. ์ˆ˜๋„๊ถŒ 333 3. ๋น„์ˆ˜๋„๊ถŒ 355 4. ๋†์ดŒ 381 ์ œ 5 ์žฅ ๊ฒฐ๋ก  396 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์š”์•ฝ 396 ์ œ 2 ์ ˆ ์‹œ์‚ฌ์  ๋ฐ ์ •์ฑ…์  ํ•จ์˜ 403 ์ฐธ๊ณ ๋ฌธํ—Œ 407 Abstract 417๋ฐ•
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