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    ใƒŸใƒฃใƒณใƒžใƒผใซใŠใ‘ใ‚‹ๆ—ง็Ÿณๅ™จๆ™‚ไปฃ็Ÿณๅ™จใฎๅŽŸๆๆ–™ๅˆฉ็”จใƒปๆŠ€่ก“ใƒปๅž‹ๅผๅˆ†้กž : ็Ÿณๅ™จ่ฃฝไฝœๆŠ€่ก“ใฏๅœฐๅŸŸๆ€งใจ้–ขไฟ‚ใ™ใ‚‹ใ‹๏ผŸโ€•

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    ใ€€ใƒŸใƒฃใƒณใƒžใƒผใฎๆ—ง็Ÿณๅ™จๆ–‡ๅŒ–ใฏใใฎๅœฐ็†็š„ไฝ็ฝฎใซใ‚ˆใฃใฆไบŒใคใซๅŒบๅˆ†ใ•ใ‚Œใ‚‹ใ€‚้–‹ๅœฐ็š„ใช้บ่ทกใฏไฝŽๅœฐๅนณๅŽŸใซไฝ็ฝฎใ—ใ€ใใ“ใงๅ…ธๅž‹็š„ใชใ‚ขใƒ‹ใƒฃใƒ†ใ‚ฃใ‚ขใƒณๆ–‡ๅŒ–ใŒๆ›ดๆ–ฐไธ–ไธญๆœŸใ‹ใ‚‰ๅฎŒๆ–ฐไธ–ๅ‰ๆœŸใฎ้–“ใซ็››่กŒใ—ใŸใ‚‚ใฎใจๆ€ใ‚ใ‚Œใ‚‹ใ€‚ไธ€ๆ–นใ€้ซ˜ๅœฐใ‚ซใƒซใ‚นใƒˆๅœฐๅธฏใฎๆดž็ฉด้บ่ทกใฏ็คซๅ™จๆ–‡ๅŒ–ใ‚’ๅๆ˜ ใ—ใฆใŠใ‚Šใ€ใใฎๅนดไปฃใฏ11,000 BP ใ”ใ‚ไปฅ้™ใซๅง‹ใพใ‚‹ใ‹ใ‚‚ใ—ใ‚Œใชใ„ใ€‚ๆœฌ่ซ–ใฏใใ†ใ—ใŸไบŒใคใฎ็•ฐใชใฃใŸๆ–‡ๅŒ–ใฎ็‰นๅพดใ‚’ใพใจใ‚ใ‚‹ใจใจใ‚‚ใซใ€ๅœฐๆ–น็š„ใƒปๅœฐๅŸŸ็š„ไผ็ตฑใซใŠใ‘ใ‚‹ๆŠ€่ก“่ซ–็š„้–ข้€ฃใ‚’ๆ˜Žใ‚‰ใ‹ใซใ—ใ‚ˆใ†ใจใ™ใ‚‹ใ‚‚ใฎใงใ‚ใ‚‹

    Trade Competitions among the Top Exporting Partners in the ASEAN Market: Focusing on Agro-food Commodities

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†๊ฒฝ์ œ์‚ฌํšŒํ•™๋ถ€(๋†๊ฒฝ์ œํ•™์ „๊ณต), 2012. 8. ๊น€ํ•œํ˜ธ.ABSTRACT (in Korean) ๋™๋‚จ์•„์‹œ์•„๊ตญ๊ฐ€์—ฐํ•ฉ(ASEAN)์ด ๋™์•„์‹œ์•„ ์ง€์—ญ์—์„œ์˜ ์–‘์ž๋ฌด์—ญํ˜‘์ • ๋„คํŠธ์›Œํ‚น์— ์žˆ์–ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๊ธฐ ์‹œ์ž‘ํ•˜๋ฉด์„œ ์ž์œ ๋ฌด์—ญํ˜‘์ •(FTA)์ด ํ™œ๋ฐœํžˆ ๋งบ์–ด์ง€๊ณ  ์žˆ์œผ๋ฉฐ ๋™์‹œ์— ๋‹ค์ž๊ฐ„ ๋ฌด์—ญ ์‹œ์Šคํ…œ์˜ ํŠน์ง•๋„ ๊ธ‰์†ํžˆ ํ™•์žฅํ•˜๊ณ  ์žˆ๋‹ค. ๋™๋‚จ์•„์‹œ์•„๊ตญ๊ฐ€์—ฐํ•ฉ์€ ๋†์‚ฐ๋ฌผ๋ฌด์—ญ์— ์žˆ์–ด ์ˆœ ์ˆ˜์ถœ ์ง€์—ญ์ด์ง€๋งŒ, ์ตœ๊ทผ 1์ธ๋‹น ์†Œ๋“ ์ฆ๋Œ€, ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ๋ถ€๊ฐ€๊ฐ€์น˜์ œํ’ˆ์— ๋Œ€ํ•œ ์‹์Šต๊ด€ ๋ฐ ์„ ํ˜ธ, ๋†์ถ•์‹ํ’ˆ์‚ฐ์—…์˜ ์ง‘์ค‘๋„ ์ฆ๊ฐ€, ์„ธ๊ณ„ํ™” ๋ฐ ๊ฐœ๋ฐœ๋„์ƒ๊ตญ์—์„œ์˜ ํŒจ์ŠคํŠธํ‘ธ๋“œ์˜ ํ™•์‚ฐ ๋“ฑ์œผ๋กœ 2005๋…„~2009๋…„ ์‚ฌ์ด ๋†์‚ฐ๋ฌผ๊ณผ ๋น„๋†์‚ฐ๋ฌผ ์ˆ˜์ž…์‹œ์žฅ์ด ์ด์ˆ˜์ž…๊ธˆ์•ก 257,943 ๋ฐฑ๋งŒ๋‹ฌ๋Ÿฌ(US)๋กœ ์ปค์ง€๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋‹ค. ASEAN ์‹œ์žฅ์œผ๋กœ ๊ฐ€์žฅ ๋งŽ์ด ์ˆ˜์ถœํ•˜๋Š” ์ฃผ์š” 20๊ตญ ๊ฐ€์šด๋ฐ, ํŠนํžˆ ๋ฏธ๊ตญ, ์ค‘๊ตญ, ํ˜ธ์ฃผ, ์ธ๋„, ๊ทธ๋ฆฌ๊ณ  ์ผ๋ณธ์ด ์ˆ˜์ถœ 5๋Œ€๊ตญ๊ฐ€๋ฅผ ํ˜•์„ฑํ•˜๊ณ  ์žˆ๋‹ค. ๋น„์ค‘์‹ฌ์ƒ๊ด€๊ฑฐ๋ฆฌ์ ‘๊ทผ(The un-centered correlation distance approach)๊ณผ ๊ฒฝ์Ÿ์œ„ํ˜‘๋ชจํ˜•(competitive threat framework) ๊ฐœ๋…์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, ๋ฏธ๊ตญ, ์ผ๋ณธ, ํ˜ธ์ฃผ๋Š” ASEAN ์‹œ์žฅ์—์„œ ์ธ๋„๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ค‘๊ตญ๊ณผ ์‹ฌ๊ฐํ•œ ๊ฒฝ์Ÿ์„ ํ•˜๊ณ  ์žˆ๋‹ค. ์ผ๋ณธ์€ ๋˜ํ•œ ํ•œ๊ตญ๊ณผ์˜ ๊ฒฝ์Ÿ์— ์ง๋ฉดํ•ด ์žˆ๋‹ค. ์ค‘๊ตญ๊ณผ ์ธ๋„๋Š” ์ง€๋ฆฌ์  ์ ‘๊ทผ์˜ ์ƒ๋Œ€์  ์šฐ์›”์„ฑ ๋•Œ๋ฌธ์— ASEAN ์‹œ์žฅ์—์„œ ๋‹ค๋ฅธ ๋‚˜๋ผ๋ณด๋‹ค ๊ฒฝ์Ÿ์šฐ์œ„๋ฅผ ์ ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ธ๋‹ค. HS 4์ž๋ฆฌ ๊ธฐ์ค€ ์ด 323๊ฐœ์˜ ASEAN ์‹œ์žฅ ์ˆ˜์ž…ํ’ˆ์„ ๋‘๊ณ  ๋ฏธ๊ตญ(316๊ฐœ ํ’ˆ๋ชฉ), ์ผ๋ณธ(318๊ฐœ ํ’ˆ๋ชฉ), ํ˜ธ์ฃผ(304๊ฐœ ํ’ˆ๋ชฉ) ๋“ฑ์ด ๊ฒฝ์Ÿ์„ ํ•˜๊ณ  ์žˆ๋Š”๋ฐ, ์ตœ๊ทผ ์ค‘๊ตญ ์ˆ˜์ถœ๋กœ ์ธํ•ด ์œ„ํ˜‘์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์˜ํ–ฅ์„ ๋ฐ›๋Š” ํ’ˆ๋ชฉ๋“ค ์ค‘์—์„œ ๋ฏธ๊ตญ(63%), ์ผ๋ณธ(63%), ํ˜ธ์ฃผ(63%)์˜ ์ˆ˜์ถœ์ด ์ค‘๊ตญ ์ˆ˜์ถœ์˜ "์ง์ ‘์  ์œ„ํ˜‘๊ณผ ๋ถ€๋ถ„์  ์œ„ํ˜‘"์„ ๋ฐ›์•˜๋‹ค. HS 6์ž๋ฆฌ ํ’ˆ๋ชฉ์œผ๋กœ ์ข€ ๋” ์ž์„ธํ•œ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•œ ๊ฒฐ๊ณผ, ์ค‘๊ตญ์€ "์‹ ์„  ์‚ฌ๊ณผ", "์‹ ์„  ๋˜๋Š” ๊ฑด์กฐํ•œ ํฌ๋„", "์‹ ์„  ๋˜๋Š” ๊ฑด์กฐํ•œ ์˜ค๋ Œ์ง€", "์‹ ์„ ํ•œ ๋ฐฐ ๋ฐ ๋งˆ๋ฅด๋ฉœ๋กœ", "์‹ ์„ ํ•œ ๋งŒ๋‹ค๋ฆฐ, ํด๋ ˆ๋ฉ˜ํƒ€์ธ & ์‹œํŠธ๋ฆฌ์Šค" ๋“ฑ ์ฃผ์š” ์‹์šฉ ๊ณผ์ผ์— ๋Œ€ํ•ด ASEAN ์ˆ˜์ž… ์‹œ์žฅ์—์„œ ์ง์ ‘์ ์œผ๋กœ ๋ฏธ๊ตญ๊ณผ ํ˜ธ์ฃผ๋ฅผ ์œ„ํ˜‘ํ–ˆ๋‹ค. ๋ฏธ๊ตญ๊ณผ ์ผ๋ณธ์€ "์†Œ์Šค์™€ ์†Œ์Šค์šฉ ์กฐ์ œํ’ˆ, ํ˜ผํ•ฉ์กฐ๋ฏธ๋ฃŒ", "์ˆ˜ํ”„โ€ข๋ธŒ๋กœ๋“œ์™€ ์ˆ˜ํ”„โ€ข๋ธŒ๋กœ๋“œ์šฉ ์กฐ์ œํ’ˆ", "๊ท ์งˆํ™”ํ•œ ํ˜ผํ•ฉ์กฐ์ œ์‹๋ฃŒํ’ˆ", ๊ฒจ์ž์˜ ๋ถ„โ€ข์กฐ๋ถ„๊ณผ ์กฐ์ œํ•œ ๊ฒจ์ž", "๋”ฐ๋กœ ๋ถ„๋ฅ˜๋˜์ง€ ์•„๋‹ˆํ•œ ์กฐ์ œ์‹๋ฃŒํ’ˆ ๊ธฐํƒ€", "์žŽ๋‹ด๋ฐฐ"์™€ ๊ฐ™์€ ํ’ˆ๋ชฉ์—์„œ ์ค‘๊ตญ์˜ ์ง์ ‘์ ์ธ ์œ„ํ˜‘์„ ๊ฒช๊ณ  ์žˆ์—ˆ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€ ์ด๋“ค 3๊ตญ์€ "๋ฉด์ง๋ฌผ(๋ฉด์˜ ํ•จ์œ ๋Ÿ‰์ด ์ „ ์ค‘๋Ÿ‰์˜ 100๋ถ„์˜ 85 ์ด์ƒ์ธ ๊ฒƒ์œผ๋กœ์„œ 1์ œ๊ณฑ๋ฏธํ„ฐ ๋‹น ์ค‘๋Ÿ‰์ด 200๊ทธ๋žจ ์ดํ•˜์ธ ๊ฒƒ์— ํ•œํ•จ) ๊ธฐํƒ€์ž‘๋ฌผ", "๋ฉด์ง๋ฌผ(๋ฉด์˜ ํ•จ์œ ๋Ÿ‰์ด ์ „ ์ค‘๋Ÿ‰์˜ 100๋ถ„์˜ 85 ์ด์ƒ์ธ ๊ฒƒ์œผ๋กœ์„œ 1์ œ๊ณฑ๋ฏธํ„ฐ๋‹น ์ค‘๋Ÿ‰์ด 200๊ทธ๋žจ์„ ์ดˆ๊ณผํ•˜๋Š” ๊ฒƒ์— ํ•œํ•จ) ๊ธฐํƒ€์ง๋ฌผ", "๋ฉด์ง๋ฌผ ๊ธฐํƒ€ ์ง๋ฌผ์˜ ๊ฒƒ"์— ๋Œ€ํ•˜์—ฌ ์ค‘๊ตญ์˜ ์ง์ ‘์ ์ธ ์œ„ํ˜‘์„ ๋ฐ›์•˜๋‹ค. ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ์œ ์‚ฌ์„ฑ(similarity) ์ง€์ˆ˜๋กœ ๋ฏธ๊ตญ, ์ผ๋ณธ, ํ˜ธ์ฃผ๋Š” ์ค‘๊ตญ์˜ ์ˆ˜์ถœ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ธ๋„์˜ ์ˆ˜์ถœ๊ณผ๋„ ASEAN ์ˆ˜์ž… ์‹œ์žฅ์—์„œ ๊ฒฝ์Ÿํ•ด์•ผ ํ–ˆ๋‹ค. ์ผ๋ณธ์˜ 243๊ฐœ ์ˆ˜์ถœ ํ’ˆ๋ชฉ, ๋ฏธ๊ตญ์˜ 225๊ฐœ ์ˆ˜์ถœ ํ’ˆ๋ชฉ, ํ˜ธ์ฃผ์˜ 218๊ฐœ ์ˆ˜์ถœ ํ’ˆ๋ชฉ์€ ์ง์ ‘ ๋˜๋Š” ๋ถ€๋ถ„์ ์œผ๋กœ ์ธ๋„์˜ ์ˆ˜์ถœ์— ๋„์ „์„ ๋ฐ›์•˜๋‹ค. ์ง์ ‘์ ์œผ๋กœ ์ธ๋„์˜ ์ˆ˜์ถœ์— ์˜ํ–ฅ์„ ๋ฐ›์€ ๋ฏธ๊ตญ๊ณผ ํ˜ธ์ฃผ์˜ ์ฃผ์š” ๋†์‚ฐ๋ฌผ์€ "์˜ฅ์ˆ˜์ˆ˜ ๊ธฐํƒ€(์‚ฌ๋ฃŒ์šฉ, ํŒ์ฝ˜, ๊ธฐํƒ€)", "์˜ฅ์ˆ˜์ˆ˜ ์ข…์ž์šฉ", "๋ฐ€๋ฆฌํŠธ", "์นด๋‚˜๋ฆฌ์‹œ๋“œ", ๋‚™ํ™”์ƒ(๋ณถ๊ฑฐ๋‚˜ ๊ธฐํƒ€ ์กฐ๋ฆฌ๋ฅผ ํ•œ ๊ฒƒ์„ ์ œ์™ธํ•˜๋ฉฐ, ํƒˆ๊ฐ ๋˜๋Š” ํŒŒ์‡„ํ•œ ๊ฒƒ์ธ์ง€์˜ ์—ฌ๋ถ€๋ฅผ ๋ถˆ๋ฌธํ•œ๋‹ค), "์ฐธ๊นจ", "์ฃผ๋กœ ํ–ฅ๋ฃŒ์šฉใ†์˜๋ฃŒ์šฉใ†์‚ด์ถฉ์šฉใ†์‚ด๊ท ์šฉ ๊ธฐํƒ€ ์ด์™€ ์œ ์‚ฌํ•œ ์šฉ๋„์— ์ ํ•ฉํ•œ ์‹๋ฌผ ๋ฐ ๊ทธ ๋ถ€๋ถ„ ๊ธฐํƒ€", ์‚ฌ๋ฃŒ์šฉ ์‹๋ฌผ์˜ ์ข…์ž, ์ฑ„์†Œ ์ข…์ž, ์ฃผ๋กœ ์‹์šฉ์— ์ ํ•ฉํ•œ ๊ณผ์‹ค์˜ ํ•ต๊ณผ ๊ธฐํƒ€์˜ ์‹๋ฌผ์„ฑ ์ƒ์‚ฐํ’ˆ(๋ณถ์ง€ ์•„๋‹ˆํ•œ ์‹œ์ฝ”๋ฆฌ์—„ ์ธํ‹ฐ๋ถ€์Šค ์ƒˆํ‹ฐ๋ฒ” ๋ณ€์ข…์˜ ์น˜์ปค๋ฆฌ๋ฟŒ๋ฆฌ๋ฅผ ํฌํ•จํ•œ๋‹ค)์œผ๋กœ์„œ ๋”ฐ๋กœ ๋ถ„๋ฅ˜๋˜์ง€ ์•„๋‹ˆํ•œ ๊ฒƒ ๊ธฐํƒ€์™€ ๋ฉดโ€ข๋ฉด์‚ฌ๋ฉด์ง๋ฌผ์ด์—ˆ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€ ํ˜ธ์ฃผ์˜ ์œ ์ œํ’ˆ"๊ณผ ๋ฏธ๊ตญ์˜ "์กฐ์ œ์‚ฌ๋ฃŒ" ๋˜ํ•œ ์ธ๋„์˜ ์ˆ˜์ถœ๋กœ๋ถ€ํ„ฐ ์œ„ํ˜‘์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. "๊ฐ„์žฅ ๊ธฐํƒ€", "์ˆ˜ํ”„โ€ข๋ธŒ๋กœ๋“œ์™€ ์ˆ˜ํ”„โ€ข๋ธŒ๋กœ๋“œ์šฉ์กฐ์ œํ’ˆ", "๊ท ์งˆํ™”ํ•œ ํ˜ผํ•ฉ์กฐ์ œ์‹๋ฃŒํ’ˆ", "์ œ 3901ํ˜ธ ๋‚ด์ง€ ์ œ 3913ํ˜ธ์˜ ํ’€๋ฆฌ๋จธ ๋˜๋Š” ๊ณ ๋ฌด๋ฅผ ๊ธฐ์ œ๋กœ ํ•œ ์ ‘์ฐฉ์ œ", "๊ทœ์‚ฐ์—ผ์„ ๊ธฐ์ œ๋กœ ํ•œ ๊ธ€๋ฃจ", "ํšจ์†Œ ๋ฐ ๋”ฐ๋กœ ๋ถ„๋ฅ˜๋˜์ง€ ์•„๋‹ˆํ•œ ์กฐ์ œ ํšจ์†Œ", "๋ฑ์ŠคํŠธ๋ฆฐ๊ณผ ๊ธฐํƒ€ ๋ณ€์„ฑ์ „๋ถ„", " ๋ฉดโ€ข๋ฉด์‚ฌ๋ฉด์ง๋ฌผ"๊ณผ ๊ฐ™์€ ์ผ๋ณธ ์ฃผ์š” ์ƒ์‚ฐํ’ˆ์€ ์ธ๋„์˜ ์ˆ˜์ถœ ์ƒ์‚ฐํ’ˆ์œผ๋กœ ์ธํ•ด ์ง์ ‘์  ์œ„ํ˜‘์„ ๋ฐ›์•˜๋‹ค. ๋˜ํ•œ ํ•œ๊ตญ์— ์˜ํ•˜์—ฌ ์ง์ ‘์ ์œผ๋กœ ์œ„ํ˜‘ ๋ฐ›์€ ์ฃผ์š” ์ƒ์‚ฐํ’ˆ์€ ๋ถ„ ๋˜๋Š” ์„ค์œก์˜ ๋ถ„. ์กฐ๋ถ„. ํŽ ๋ฆฌํŠธ ๋ฐ ์ˆ˜์ง€๋ฐ•, ์–ด๋ฅ˜. ๊ฐ‘๊ฐ๋ฅ˜. ์—ฐ์ฒด๋™๋ฌผ ๋˜๋Š” ๊ธฐํƒ€ ์ˆ˜์ƒ๋ฌด์ฒ™์ถ”๋™๋ฌผ์˜ ๋ถ„. ์กฐ๋ถ„ ๋ฐ ํŽ ๋ฆฌํŠธ, ํ‰์ง๋ฌผ (1์ œ๊ณฑ๋ฏธํ„ฐ๋‹น ์ฃผ๋Ÿ‰์ด 100 ๊ทธ๋žจ ์ดํ•˜์ธ ๊ฒƒ์— ํ•œํ•œ๋‹ค), ํ‘œ๋ฐ•ํ•˜์ง€ ์•„๋‹ˆํ•œ ๊ฒƒ. ๊ธฐํƒ€ ์ง๋ฌผ์˜ ๊ฒƒ ๊ณผ ์—ผ์ƒ‰ํ•œ ๊ฒƒ. ๊ธฐํƒ€์ง๋ฌผ ์ด๋‹ค. ASEAN ์‹œ์žฅ์˜ ๋ฌด์—ญ๊ฒฝ์Ÿ์—์„œ ๋ฏธ๊ตญ, ์ผ๋ณธ, ํ˜ธ์ฃผ๋Š” "์ œ์ดˆ์ œ", "์‚ด์ถฉ์ œ", "์‚ด์ถฉ์ œ(๋†์•ฝ)", "์„ฌ์œ ๊ณต์—… ๋˜๋Š” ์ด์™€ ์œ ์‚ฌํ•œ ๊ณต์—…์šฉ์˜ ๊ฒƒ", "ํ™œ์„ฑํƒ„", "์กฐ์ œํ•œ ๊ณ ๋ฌด๊ฐ€ํ™ฉ์ด‰์ง„์ œ", "์ด์†Œ์‹œ์•„๋„ค์ดํŠธ", "์—ํ‹ธ๋ Œ", "ํ•ญ์ƒ๋ฌผ์งˆ", "์œ ๊ธฐ-ํ™ฉ ํ™”ํ•ฉ๋ฌผ", "๋†์•ฝ์›์ œ์˜ ๊ฒƒ", "ํŽ˜๋‹ˆ์‹ค๋ฆฐ๊ณผ ํŽ˜๋‹ˆ์‹ค๋ฆฐ ์‚ฐ"๊ณผ ๊ฐ™์€ ๋น„๋†์‚ฐ๋ฌผ ํ’ˆ๋ชฉ์—์„œ ๋ชจ๋“  ๋น„๊ต ๋Œ€์ƒ ๊ตญ๊ฐ€ ์ฆ‰, ์ค‘๊ตญ, ์ธ๋„, ํ•œ๊ตญ์œผ๋กœ๋ถ€ํ„ฐ ์ง์ ‘์ ์ธ ์œ„ํ˜‘์„ ๋ฐ›์•˜๋‹ค. ์ค‘๋ ฅ๋ชจํ˜•์„ ์ ์šฉํ•˜๋ฉด "์ˆ˜์ž…๊ตญ GDP", "1์ธ๋‹น ์ˆ˜์ž…๊ตญ GDP", "์ˆ˜์ถœ๊ตญ GDP"๋Š” ์–‘์˜ ๋ถ€ํ˜ธ๋ฅผ ๊ฐ€์ง€๋ฉฐ ๋†’์€ ํ†ต๊ณ„์  ์œ ์˜์„ฑ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด๊ฒƒ์€ ASEAN ์ˆ˜์ž… ์‹œ์žฅ์—์„œ ์ˆ˜์ž…๊ตญ์˜ GDP, ์ˆ˜์ž…๊ตญ์˜ 1์ธ๋‹น GDP, ์ˆ˜์ถœ๊ตญ์˜ GDP์™€ ํ•จ๊ป˜ ๋ฌด์—ญ๋Ÿ‰์ด ์ฆ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. FTA๋ฅผ ํ‘œ์‹œํ•˜๋Š” ๋”๋ฏธ๋ณ€์ˆ˜์˜ ์ถ”์ •์น˜๋Š” ์œ ์˜๋ฏธํ•œ ๊ณ„์ˆ˜(2.39)๋ฅผ ๋ณด์—ฌ์ฃผ๊ณ , ๋˜ํ•œ ASEAN ์—ญ๋‚ด ์ž์œ ๋ฌด์—ญํ˜‘์ •์€ ํšŒ์›๊ตญ๊ฐ„ ๋ฌด์—ญ์„ 991% ์ƒ์Šน์‹œ์ผฐ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ์ž์œ ๋ฌด์—ญ์€ ASEAN ์ˆ˜์ž… ์‹œ์žฅ ๋‚ด ์ฃผ์š”์ˆ˜์ถœ๊ตญ๊ฐ€๋“ค์˜ ๋ฌด์—ญ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜์˜€๋‹ค. ์ฃผ์š” ์ž‘๋ฌผ์˜ ์ˆ˜์ž…์€ ์–‘๊ณผ ๊ธˆ์•ก ๋ชจ๋‘ ์ƒ๋‹นํžˆ ์ฆ๊ฐ€ํ–ˆ๋Š”๋ฐ, ์ด ๊ฐ™์€ ์ˆ˜์ž… ์ฆ๊ฐ€๋Š” ASEAN ๊ตญ๊ฐ€๋“ค์˜ ๊ตญ๋‚ด ์ƒ์‚ฐ์—๋Š” ํฌ๊ฒŒ ์˜ํ–ฅ์„ ๋ผ์น˜์ง€ ์•Š์•˜๋‹ค. ์—ฌ๋Ÿฌ ํ’ˆ๋ชฉ์˜ ์ˆ˜์ž…์€ ๋ณด์™„์žฌ๋กœ์„œ ๊ตญ๋‚ด์—์„œ ์†Œ๋น„๋  ์ˆ˜ ์žˆ์—ˆ๊ณ  ๋˜ํ•œ ASEAN ๊ตญ๊ฐ€๋“ค์˜ ์ˆ˜์ถœ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ตญ๋‚ด ์†Œ๋น„๋ฅผ ์œ„ํ•œ ๋ถ€๊ฐ€๊ฐ€์น˜ ์‚ฐ์—…์˜ ์›์ž์žฌ๋กœ์„œ๋„ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ‚ค์›Œ๋“œ: ๋ฌด์—ญ ๊ฒฝ์Ÿ, ASEAN ์ˆ˜์ž… ์‹œ์žฅ, ์ž์œ ๋ฌด์—ญํ˜‘์ •(FTA), ์ค‘๋ ฅ๋ชจํ˜•, ๋†์‚ฐํ’ˆ ํ•™๋ฒˆ: 2009-31277ABSTRACT Since ASEAN is playing a significant role in the networking of bilateral trade agreements in the East Asia region, Free Trade Agreements (FTAs) become now the most prominent and rapidly expanding feature of the multilateral trading system. Although ASEAN is a net exporting region for agricultural trade, due to rising per capita income, the diets and preferences of consumers on the different kinds of value added products, the demands of an increasingly concentrated food industry, globalization and the spreading presence of the fast-food industry in developing countries, most of its agriculture and some non-agriculture imports become large and growing during these periods until the total import amount 257,943 million US$ from the world in 2005-2009 periods. Among the top 20 exporters to ASEAN market, USA, China, Australia, India and Japan were five largest trade partners in ASEAN import market. By using the un-centered correlation distance approach and the concept of competitive threat framework, the results show that USA, Japan and Australia were facing serious competition with China as well as India in ASEAN import market. Japan also faced trade competition with Korea. The relative geographic proximity of China and India to ASEAN markets seems to favor them several advantages in their competitions with other countries. Among total 323 four-digit HS commodities of ASEAN import, USAs exports (316 commodities), Japans exports (318 commodities) and Australias exports (304 commodities) were affected by Chinas export threat. Among those affected items, USA (63%), Japan (63%) and Australia (63%) were subjected to Direct threat and Partial threat of Chinas exports. After more detail analysis of six-digit items, China directly threatened to USA and Australia in major edible fruits such as fresh apples, fresh and dried grapes, fresh or dried oranges, fresh pears and quinces, and fresh mandarin, clementine & citrus in ASEAN market. USA and Japan were suffering Chinas direct threat in some items like Sauces nes, mixed condiment, mixed seasoning, Soups and broths and preparations thereof, Homogenised composite food preparations, Mustard flour or meal and prepared mustard, Food preparation nes and Tobacco, unmanufactured, stemmed or stripped. Moreover these three countries were subjected to China direct threat in Woven cotton nes, >85% 85% >200g/m2, dyed, nes, and Woven cotton nes, >85% <200g/m2, unbleached. With the relatively higher similarity index, exports of USA, Japan and Australia were subjected to compete with not only Chinas exports but also Indias exports in ASEAN import market. Japans exports 243 items, USAs export 225 items and Australias exports 218 items were directly or partially challenged by Indias exports. The major agriculture export commodities directly affected by Indias export were Maize except seed corn, Maize (corn) seed, Millet, Canary seed, Ground-nuts shelled, not roasted or cooked, Sesamum seeds, Plants & parts, pharmacy, perfume, insecticide use nes, Seed, fruits and spores for sowing, nes, Seed, forage plants, for sowing nes, Seed, vegetable, nes for sowing, Vegetable products nes for human consumption and different kinds of Cotton for both USA and Australia. Moreover Australias Dairy products and USAs Residues and waste from the food industries were also threatened by Indias exports. Japans major products like Sauces nes, mixed condiments, mixed seasoning, Soups and broths and preparations thereof, Homogenised composite food preparations, Adhesives based on rubber or plastic, package >1 kg, Glues or adhesives, prepared nes, package > 1kg, Enzymes nes, prepared enzymes nes, except rennet, Dextrins and other modified starches and major cotton products were subjected to Direct Threat by Indias export products. In addition to, Japans major products directly threatened by Korea were Flour or meal, pellet, fish, etc., for animal feed, Animal feed preparations nes, Plain weave cotton, >85% >200g/m2, unbleached, Woven cotton nes, >85% 85% <200g/m2, dyed and other different kinds of cotton in ASEAN import market. For non-agriculture products, Herbicides, Insecticides, Pesticides, Finishing agents, dye carriers , Activated carbon, prepared rubber accelerators, Isocyanates, Ethylene, Antibiotics, Organo-sulphur compounds, Heterocyclic compounds, and Penicillins and their derivatives of USA, Japan and Australia were subjected to Direct Threat of each reference country in all trade competitions in ASEAN market. By applying gravity model, the effect of the importers GDP, the importers GDP per capita and exporters GDP shows positive and highly significant. It means that trade rises with GDP of importers, GDP per capita of importers and GDP of exporters in ASEAN import market. The significant coefficient of dummy variable, FTAijt is (2.39) and the intra-ASEAN Free Trade Agreement increased trade between its members by 991%. Therefore, Free Trade Agreements play an important role in the trade of top exporters in ASEAN import market. Even import amounts and value of the major crops increased significantly, increasing of import did not effect on their domestic productions of ASEAN countries. Importing products or commodities could be used for domestic consumption as complementary goods and could be also used as raw materials from value-added industries for domestic consumption as well as export in ASEAN countries. Key words: trade competition, ASEAN import market, Free Trade Agreement (FTA), gravity model, agriculture products Student ID number: 2009-31277Contents Abstract i List of Tables (in the body of text) ix List of Figures (in the body of text) xiii List of the Acronyms xvi I. INTRODUCTION 1 1.1 Background of the study 1 1.2 Significance of the study 5 1.3 Objectives of the study 12 1.4 Organization of the study 13 II. LITERATURE REVIEWS 14 2.1 ASEAN Regional Trade 14 2.2 ASEAN Free Trade Agreements 16 2.3 Trade Competitions 20 2.3.1 Trade Competition between China and USA 20 2.3.2 Trade Competition between China and India 24 2.3.3 Trade Competition between China and Japan 26 2.3.4 Trade Competition between India and USA 30 2.3.5 Trade Competition between Korea and Japan 31 III. DESCRIPTION OF THE STUDY AREA 33 3.1 Association of South East Asian Nations (ASEAN) 33 3.2 Economic Situation of ASEAN 49 3.3 ASEAN Free Trade Agreements 52 3.4 ASEAN Relation with Top Trading Partners 55 3.4.1 ASEAN relation with USA 55 3.4.2 ASEAN relation with China 58 3.4.3 ASEAN relation with Japan 64 3.4.4 ASEAN relation with India 66 3.4.5 ASEAN relation with Australia 69 3.4.6 ASEAN relation with Korea 71 IV. RESEARCH METHODOLOGY 73 4.1 Trade Competitions in ASEAN import market 73 4.1.1 Data and Sampling 73 4.1.2 Analytical Framework 75 4.2 Effect of Free Trade Agreement (FTA) in ASEAN import market 80 4.2.1 The Gravity Model 80 4.2.2 Data and Methodology 82 V. RESULTS AND DISCUSSIONS 84 5.1 ASEAN agriculture and non-agriculture trade with the top partners 84 5.2 ASEAN agriculture and non-agriculture trade with United States 96 5.2.1 USA agriculture and non-agriculture exports to world 96 5.2.2 USA agriculture and non-agriculture exports to ASEAN 98 5.3 ASEAN agriculture and non-agriculture trade with China 101 5.3.1 China agriculture and non-agriculture exports to world 101 5.3.2 China agriculture and non-agriculture exports to ASEAN 105 5.4 ASEAN agriculture and non-agriculture trade with Japan 109 5.4.1 Japan agriculture and non-agriculture exports to world 109 5.4.2 Japan agriculture and non-agriculture exports to ASEAN 112 5.5 ASEAN agriculture and non-agriculture trade with India 115 5.5.1 India agriculture and non-agriculture exports to world 115 5.5.2 India agriculture and non-agriculture exports to ASEAN 119 5.6 ASEAN agriculture and non-agriculture trade with Australia 122 5.6.1 Australia agriculture and non-agriculture exports to world 122 5.6.2 Australia agriculture and non-agriculture exports to ASEAN 126 5.7 ASEAN agriculture and non-agriculture trade with Korea 129 5.7.1 Korea agriculture and non-agriculture exports to world 129 5.7.2 Korea agriculture and non-agriculture exports to ASEAN 132 5.8 Trade competitions among the emerging markets and declining markets136 5.8.1 Trade competition between China and United States 137 5.8.2 Trade competition between China and Japan 154 5.8.3 Trade competition between China and Australia 159 5.8.4 Trade competition between India and United States 165 5.8.5 Trade competition between India and Japan 175 5.8.6 Trade competition between India and Australia 180 5.8.7 Trade competition between Korea and Japan 185 5.9 Effect of Free Trade Agreement (FTA) 195 5.10 Production, export and import of some major crops in ASEAN 198 VI. CONCLUSIONS AND POLICY IMPLICATIONS 208 6.1 Conclusions 208 6.2 Policy implications 218 REFERENCES 225 APPENDICES 236 ABSTRACT (in Korean) 247 ACKNOWLEDGEMENT 250Docto

    Rural and urban disparities in health-seeking for fever in Myanmar: findings from a probability-based household survey.

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    BackgroundThe World Health Organization (WHO) recognizes Myanmar as having the highest burden of malaria in the Greater Mekong Sub-region (GMS). Early diagnosis and proper treatment are critical in containing malaria. The objective of this study was to assess determinants of seeking treatment for fever from trained providers across rural and urban areas in Eastern Myanmar.MethodsA cross-sectional survey was conducted during the high malaria seasons in the eastern part Myanmar between August and September 2014. Multi-staged cluster sampling was used to sample households. A series of questions related to treatment-seeking for fever were asked. Bivariate and multivariate logistic regressions were conducted to identify independent correlates of seeking treatment for fever from trained providers.ResultsThe analysis was restricted to 637 participants who reported either themselves or their family members having had fever 2ย weeks prior to the interview. In the multivariate analysis, rural residents were less likely to have sought treatment from trained providers (AORย =ย 0.60, 95ย % CI 0.42-0.88; pย =ย 0.01) while residents who had fever patients between the ages of 5 and 14ย years (AORย =ย 1.60, 95ย % CI 0.90-2.53; pย =ย 0.05); and those who knew that sleeping under bed nets can prevent malaria (AORย =ย 2.08, 95ย % CI 1.00-4.30; pย =ย 0.05); were borderline more likely to have sought treatment.ConclusionThis study suggests that rural populations need improved access to trained providers. Additionally, future programmes should focus on increasing knowledge around malaria prevention and treatment

    Effect of leucaena forage and silage substitution in concentrates on digestibility, nitrogen utilization and milk yield in dairy cows

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    This experiment was conducted to determine the effect of feeding leucaena forage and silage substitution in concentrate on the performances of dairy cows. Nine cross-bred Holstein Friesian cows (410ยฑ12kg) in the 12th week of lactation were randomly allocated to one of three treatment groups with three replicates/treatments in a completely randomized design. The three treatments were control diet without substitution of leucaena forage and silage (DLFS0), diet with substitution of leucaena forage 10% (DLF10) and diet with substitution of leucaena silage 10% (DLS10). Cows were fed treatments for 60 days. Although nutrient intakes were not significantly different (p&gt;0.05) each other, digestibility of DLFS0 was significantly higher (p&lt;0.05) than others. Conversely, nitrogen utilization and average milk yield of cows offered DLFS0 were significantly lower (p&lt;0.05) than those of cows fed on DLF10 and DLS10. The highest feed cost (p&lt;0.05) per kg of milk was found in DLFS0 and the lowest cost was observed in DLF10. Therefore, although the leucana forage and silage could be substitute up to 10% of concentrates without adverse effects on the performances of dairy cows, the substitution of leucaena forage gave the better performances than that of leucaena silage

    Who continues to stock oral artemisinin monotherapy? Results of a provider survey in Myanmar.

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    BackgroundArtemisinin-based combination therapy (ACT) is a key strategy for global malaria elimination efforts. However, the development of artemisinin-resistant malaria parasites threatens progress and continued usage of oral artemisinin monotherapies (AMT) predisposes the selection of drug resistant strains. This is particularly a problem along the Myanmar/Thailand border. The artemisinin monotherapy replacement programme (AMTR) was established in 2012 to remove oral AMT from stocks in Myanmar, specifically by replacing oral AMT with quality-assured ACT and conducting behavioural change communication activities to the outlets dispensing anti-malarial medications. This study attempts to quantify the characteristics of outlet providers who continue to stock oral AMT despite these concerted efforts.MethodsA cross-sectional survey of all types of private sector outlets that were stocking anti-malarial drugs in 13 townships of Eastern Myanmar was implemented from July to August 2014. A total of 573 outlets were included. Bivariate and multivariable logistic regressions were conducted to assess outlet and provider-level characteristics associated with stocking oral AMT.ResultsIn total, 2939 outlets in Eastern Myanmar were screened for presence of any anti-malarial drugs in August 2014. The study found that 573 (19.5ย %) had some kind of oral anti-malarial drug in stock at the time of survey and among them, 96 (16.8ย %) stocked oral AMT. In bivariate analyses, compared to health care facilities, itinerant drug vendors, retailers and health workers were less likely to stock oral AMT (33.3 vs 12.9, 10.0, 8.1ย %, ORย =ย 0.30, 0.22, 0.18, respectively). Providers who cut blister pack or sell partial courses (40.6 vs 11.7ย %, OR 5.18, CI 3.18-8.44) and those who based their stock decision on consumer demand (32.8 vs 12.1ย %, OR 3.54, CI 2.21-5.63) were more likely to stock oAMT. Multivariate logistic regressions produced similar significant associations.ConclusionPrivate healthcare facilities and drug shops and providers who prioritize consumers' demand instead of recommended practices were more likely to stock oral AMT. Malaria elimination strategies should include targeted interventions to effectively reach those outlets

    Bioactive secondary metabolites from the culture of the marine sponge-associated fungus Neosartorya fennelliae KUFA 0811

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    Mango Andrew. Alexandre Jevakhoff Kemal Atatรผrk : Les chemins de l'Occident, 1989. In: CEMOTI, nยฐ20, 1995. Mรฉdias d'Iran et d'Asie Centrale. pp. 415-418
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