44 research outputs found

    A Study on the Development Strategy of Ulsan Port Authority using SWOT/AHP Analysis

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ตญ๋‚ด์™ธ ํ™˜๊ฒฝ๋ณ€ํ™”์— ๋งž์ถฐ ์šธ์‚ฐํ•ญ๋งŒ๊ณต์‚ฌ๊ฐ€ ์–ด๋–ป๊ฒŒ ๊ฒฝ์Ÿ๋ ฅ์„ ํ™•๋ณดํ•˜๋ฉฐ, ์–ด๋–ค ๋ฐฉ๋ฒ•์œผ๋กœ ์ง€์†์ ์ธ ์„ฑ์žฅ์„ ์ถ”๊ตฌํ•  ๊ฒƒ์ด๋ฉฐ, ์ด๋ฅผ ์œ„ํ•ด ์–ด๋–ค ์ค‘์žฅ๊ธฐ ๋ฐœ์ „๋ฐฉ์•ˆ์„ ์ˆ˜๋ฆฝํ•ด์•ผ ํ•˜๋Š”์ง€๋ฅผ ๊ตฌ์ฒด์ ์œผ๋กœ ์ œ์‹œํ•˜์˜€๋‹ค. ์šธ์‚ฐํ•ญ๋งŒ๊ณต์‚ฌ์˜ ๋ฐœ์ „๋ฐฉ์•ˆ์„ ์‹คํ˜„ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, SWOT/AHP ๋ถ„์„์„ ์ด์šฉํ•˜์˜€์œผ๋ฉฐ, ์‹ค์ฆ๋ถ„์„์„ ๋ฐ”ํƒ•์œผ๋กœ ์šธ์‚ฐํ•ญ๋งŒ๊ณต์‚ฌ์˜ ์ „๋žต์  ๋ฐœ์ „๋ฐฉ์•ˆ์„ ์šฐ์„ ์ˆœ์œ„๋ณ„๋กœ S/O์ „๋žต, W/O์ „๋žต, S/T์ „๋žต, W/T์ „๋žต ์ˆœ์œผ๋กœ ์ˆ˜๋ฆฝํ•˜์—ฌ ์ œ์‹œํ•˜๊ณ , 4๋Œ€์ „๋žต๊ณผ 10๋Œ€ ์ถ”์ง„๊ณผ์ œ๋ฅผ ์„ค์ •ํ•˜๊ณ  2์ฐจ AHP ๋ถ„์„์„ ํ†ตํ•˜์—ฌ ์ถ”์ง„๊ณผ์ œ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. This paper aims to propose practical and effective research result which can contribute to fulfill the strategy od Ulsan Port Authority, ultimately proposing tasks and strategies of development plan to the policy maker to make the right decision. In order to find out the optimal strategies of Ulsan Port Authory, The paper offers a systematic approach and analytical means with a combination of SWOT/AHP that can enhance stakeholders' and decision makers' understanding of the problem and help in the definition of solution objectives and constraints.1. ์„œ๋ก  2. ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 3. SWOT/AHP ๋ชจํ˜•๊ตฌ์ถ• 4. ์šธ์‚ฐํ•ญ๋งŒ๊ณต์‚ฌ ํ˜„ํ™ฉ ๋ฐ SWOT/AHP ๋ถ„์„ 5. ์šธ์‚ฐํ•ญ๋งŒ๊ณต์‚ฌ ๋ฐœ์ „๋ฐฉ์•ˆ 6. ๊ฒฐ๋ก  ์ฐธ๊ณ ๋ฌธํ—Œ ๋ถ€

    ์–ธ๋ก  ์‚ฌ์„ค์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2022. 8. ์—„์„์ง„.๊ธฐํ›„๋ณ€ํ™”๋Š” ์ธ๋ฅ˜๊ฐ€ ์ง๋ฉดํ•œ ๊ฐ€์žฅ ํฐ ์œ„ํ˜‘์ด๋‹ค. ์ง€๊ตฌ์˜จ๋‚œํ™” 1.5โ„ƒ ํŠน๋ณ„๋ณด๊ณ ์„œ(IPCC)์— ๋”ฐ๋ฅด๋ฉด 2050๋…„๊นŒ์ง€ ํƒ„์†Œ๋ฐฐ์ถœ์„ 0๊นŒ์ง€ ์ค„์ด์ง€ ์•Š์œผ๋ฉด ์ง€๊ตฌ ํ‰๊ท ๊ธฐ์˜จ์ด ์ธ๋ฅ˜์˜ ์ƒ์กดํ•œ๊ณ„๋ฅผ ์œ„ํ˜‘ํ•˜๋Š” 1.5โ„ƒ๋ฅผ ๋„˜์–ด์„ค ๊ฒƒ์ด๋ผ๊ณ  ๊ฒฝ๊ณ ํ•œ๋‹ค. ์ด์— ์ „ ์„ธ๊ณ„๋Š” ๊ธฐํ›„๋ณ€ํ™” ๋Œ€์‘์ฒด์ œ์— ๋Œ์ž…ํ•˜์˜€๋‹ค. ์šฐ๋ฆฌ๋‚˜๋ผ๋„ ๊ฒฝ์ œ ์ „๋ฐ˜์˜ ๊ตฌ์กฐ์  ์ „ํ™˜์„ ์ˆ˜๋ฐ˜ํ•˜๋Š” ํƒ„์†Œ์ค‘๋ฆฝ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๋ฐœํ‘œํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์ •์ฑ…์€ ์žฅ๊ธฐ์ ์ธ ์‹œ๊ฐ์—์„œ ์ •์ฑ…ํ–‰์œ„์ž๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ๋‹ค์–‘ํ•œ ๊ด€์ ์—์„œ ์‚ดํŽด๋ณผ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‹ค์–‘ํ•œ ์ •์ฑ… ์•„์ด๋””์–ด๊ฐ€ ๋‚˜ํƒ€๋‚˜๋Š” ์–ธ๋ก  ์‚ฌ์„ค 1,063๊ฐœ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ…์ŠคํŠธ ๋ถ„์„์„ ์‹ค์‹œํ•˜์—ฌ ๊ธฐํ›„๋ณ€ํ™”์— ๋Œ€ํ•œ ์ •์ฑ… ํ”„๋ ˆ์ž„์„ ๋„์ถœํ•˜์˜€๋‹ค. ๋˜ํ•œ ์–ธ๋ก ์‚ฌ์˜ ์„ฑํ–ฅ์— ๋”ฐ๋ผ ๋ณด์ˆ˜์™€ ์ง„๋ณด ์–ธ๋ก ์œผ๋กœ ๋‚˜๋ˆ„๊ณ , ์‹œ๊ฐ„์˜ ํ๋ฆ„์— ๋”ฐ๋ผ ๋ฌธ์žฌ์ธ ์ •๋ถ€์™€ ๋ฐ•๊ทผํ˜œ ์ •๋ถ€๋กœ ๋‚˜๋ˆ„์–ด ๋ถ„์„ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋ณด์ˆ˜ ์–ธ๋ก ๊ณผ ์ง„๋ณด ์–ธ๋ก  ๊ฐ„, ๋ฌธ์žฌ์ธ ์ •๋ถ€์™€ ๋ฐ•๊ทผํ˜œ ์ •๋ถ€ ๊ฐ„์˜ ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ… ํ”„๋ ˆ์ž„์˜ ์ฐจ์ด๋ฅผ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ์ดˆ ํ†ต๊ณ„ ๋ถ„์„, ํ† ํ”ฝ ๋ชจ๋ธ๋ง, ์˜๋ฏธ ์—ฐ๊ฒฐ๋ง ๋ถ„์„ ๋“ฑ์˜ ํ…์ŠคํŠธ ๋งˆ์ด๋‹์„ ์‹ค์‹œํ•œ ํ›„ ์ด๋ฅผ ์ข…ํ•ฉํ•˜์—ฌ ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ… ํ”„๋ ˆ์ž„์„ ๋„์ถœํ•˜์˜€๋‹ค. ๋ฌธ์žฌ์ธ ์ •๋ถ€ ๋ณด์ˆ˜ ์–ธ๋ก ์—์„œ๋Š” โ€˜์›์ „์ค‘์‹ฌโ€™, โ€˜ํ˜„์ƒ๋ถ„์„โ€™, โ€˜ํ•ด๊ฒฐ๋ฐฉ๋ฒ•โ€™, โ€˜๊ฐ•๋Œ€๊ตญ์ฐธ์—ฌโ€™, โ€˜๊ธฐํ›„์ธ์‹โ€™ ํ”„๋ ˆ์ž„์ด ๋‚˜ํƒ€๋‚ฌ๊ณ , ์ง„๋ณด ์–ธ๋ก ์—์„œ๋Š” โ€˜์žฌ์ƒ์—๋„ˆ์ง€์ค‘์‹ฌโ€™, โ€˜์œ„๊ธฐ์ƒํ™ฉโ€™, โ€˜๊ธฐ์—…์ฐธ์—ฌโ€™, โ€˜๊ฒฝ์ œ์„ฑโ€™, โ€˜๊ธฐํ›„ํ–‰๋™โ€™ ํ”„๋ ˆ์ž„์ด ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ•๊ทผํ˜œ ์ •๋ถ€ ๋ณด์ˆ˜ ์–ธ๋ก ์—์„œ๋Š” โ€˜์›์ „์ค‘์‹ฌโ€™, โ€˜ํ˜„์ƒ๋ถ„์„โ€™, โ€˜๊ธฐ์—…์ค‘์‹ฌโ€™, โ€˜๋Œ€์ฑ…๋งˆ๋ จโ€™, โ€˜๊ทœ์ œ์™„ํ™”โ€™ ํ”„๋ ˆ์ž„์ด ๋‚˜ํƒ€๋‚ฌ๊ณ , ์ง„๋ณด ์–ธ๋ก ์—์„œ๋Š” โ€˜์žฌ์ƒ์—๋„ˆ์ง€์ค‘์‹ฌโ€™, โ€˜๊ธฐํ›„ํ–‰๋™โ€™, โ€˜์ง€๊ตฌ์ค‘์‹ฌโ€™, โ€˜์›์ธ๊ทœ๋ช…โ€™, โ€˜๊ทœ์ œ๊ฐ•ํ™”โ€™ ํ”„๋ ˆ์ž„์ด ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•œํŽธ, ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์—์„œ ๋ฌธ์žฌ์ธ ์ •๋ถ€๋กœ ์‹œ๊ฐ„ ํ๋ฆ„์— ๋”ฐ๋ผ ๋ณด์ˆ˜ ์–ธ๋ก ์˜ โ€˜์›์ „์ค‘์‹ฌโ€™, โ€˜ํ˜„์ƒ๋ถ„์„โ€™ ํ”„๋ ˆ์ž„๊ณผ ์ง„๋ณด ์–ธ๋ก ์˜ โ€˜์žฌ์ƒ์—๋„ˆ์ง€์ค‘์‹ฌโ€™, โ€˜๊ธฐํ›„ํ–‰๋™โ€™ ํ”„๋ ˆ์ž„์€ ๊ณ„์† ์œ ์ง€๋˜๋‚˜, ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ…์˜ ์—ญ์‚ฌ์ ์ธ ๋ณ€ํ™”๊ฐ€ ์ด๋ฃจ์–ด์ง์— ๋”ฐ๋ผ ๋‹ค๋ฅธ ํ”„๋ ˆ์ž„๋“ค์€ ์–ธ๋ก ์‚ฌ ํŠน์„ฑ์— ๋”ฐ๋ผ ๋ณ€๋™ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๊ธฐํ›„๋ณ€ํ™”์— ๋Œ€ํ•œ ์ •์ฑ… ํ”„๋ ˆ์ž„์„ ์–ธ๋ก ์‚ฌ์™€ ์ •๊ถŒ๋ณ„๋กœ ๋น„๊ต ๋ถ„์„ํ•จ์œผ๋กœ์จ, ์ •์ฑ… ์•„์ด๋””์–ด ์ธก๋ฉด์—์„œ ๋ณด์ˆ˜ ์–ธ๋ก ๊ณผ ์ง„๋ณด ์–ธ๋ก  ๊ฐ„์˜ ํ”„๋ ˆ์ž„ ์ฐจ์ด๊ฐ€ ์žˆ๊ณ , ์ •๊ถŒ๋ณ„๋กœ๋„ ๋ณด๋„๊ธฐ์‚ฌ์˜ ๋‚ด์šฉ์ด ๋‹ฌ๋ผ์กŒ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์™€ ๋ฌธ์žฌ์ธ ์ •๋ถ€์˜ ๊ฐ ์–ธ๋ก ์‚ฌ๋ฅผ ํ†ตํ•ด ๋‚˜ํƒ€๋‚˜๋Š” ๋‹ค์–‘ํ•œ ์ •์ฑ… ์•„์ด๋””์–ด์™€ ํ”„๋ ˆ์ž„์˜ ์ฐจ์ด๋ฅผ ์‚ดํŽด๋ณผ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ •์ฑ…์  ํ•จ์˜๋ฅผ ๊ฐ€์ง„๋‹ค. ์ด์— ์ƒˆ๋กœ์šด ์ •๋ถ€์˜ ์ฃผ์š” ๊ตญ์ •๊ณผ์ œ ์ค‘ ํ•˜๋‚˜์ธ ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ…์— ๋Œ€ํ•œ ์‹ค์ฆ์ ์ธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋กœ์จ ์˜์˜๋ฅผ ๊ฐ€์ง„๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ…์€ ๊ณ ๋น„์šฉ์œผ๋กœ ์žฅ๊ธฐ์ ์œผ๋กœ ์ถ”์ง„๋˜๋ฏ€๋กœ ์ฒซ ๋‹จ์ถ”๋ฅผ ์ž˜๋ชป ๊ฟฐ๋ฉด ์˜คํžˆ๋ ค ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ…์ด ํ‡ด๋ณดํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ •์ฑ… ์•„์ด๋””์–ด์— ๋”ฐ๋ฅธ ํ”„๋ ˆ์ž„ ์ฐจ์ด๋ฅผ ๊ณ ๋ คํ•œ ๋‹ค๊ฐ์ ์ธ ์ ‘๊ทผ์ด ํ•„์š”ํ•˜๋‹ค. ๋˜ํ•œ ์ •์น˜์ ์œผ๋กœ ํŽธํ–ฅ๋˜์ง€ ์•Š์€ ์—ฌ๋Ÿฌ ๋ถ„์•ผ์˜ ์ „๋ฌธ๊ฐ€๋“ค์ด ๋ชจ์—ฌ ๊ธฐํ›„๋ณ€ํ™”์— ๋Œ€ํ•œ ํ•ด๋‹ต์„ ์ฐพ๊ธฐ ์œ„ํ•œ ๊ทผ๋ณธ์ ์ธ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค.Climate change is the greatest threat facing mankind. According to the Special Report on Global Warming 1.5โ„ƒ (IPCC), if carbon emissions are not reduced to zero by 2050, the global average temperature will exceed 1.5โ„ƒ, which threatens the survival limit of mankind. Accordingly, the world has entered a climate change response system. Korea also announced a carbon-neutral scenario involving a structural transformation of the overall economy. These policies need to be examined from various perspectives, focusing on policy actors from a long-term perspective. In this study, a text analysis was conducted on 1,063 media editorials with various policy ideas to derive a policy frame for climate change. In addition, it was divided into conservative and progressive media according to the tendency of the media company, and analyzed by dividing it into the Moon Jae-In government and the Park Geun-Hye government over time. Through this, we tried to find out the difference in the climate change policy frame between the conservative and progressive media, and between the Moon Jae-In and Park Geun-Hye governments. In this study, text mining such as basic statistical analysis, topic modeling, and semantic network analysis was conducted, and then the climate change policy frame was derived by synthesizing them. Moon Jae-In In the conservative media of the government, frames of "nuclear power," "phenomenal analysis," "resolutions," "climate awareness," and "renewable energy," "crisis," "corporate participation," "economy," and "climate action" appeared in the liberal media. Park Geun-Hye In the conservative government media, "nuclear power plant-centered," "phenomenal analysis," "company-centered," "planning," and "deregulation" frames appeared, while in the liberal media, "renewable energy-centered," "climate action," "earth-centered," "cause-strengthening" frames appeared. Meanwhile, as the Park Geun-Hye government goes from the Park Geun-Hye government to the Moon Jae-In government, the conservative media's "nuclear power plant" and "phenomenal analysis" frames and the progressive media's "climate action" frames continue, but other frames change depending on the characteristics of the media. Through this study, by comparing and analyzing the policy frame on climate change by media and regime, it was confirmed that there was a frame difference between the conservative and liberal media in terms of policy ideas, and the contents of the press articles changed by regime. Therefore, it has a policy implication that it is possible to examine the differences in various policy ideas and frames that appear through each media company of the Park Geun-Hye government and the Moon Jae-In government. Therefore, it can be said that it is meaningful as an empirical research result on climate change policy, one of the main national tasks of the new government. These climate change policies are expensive and long-term, so if you take the wrong first step, climate change policies can regress. Therefore, a multifaceted approach is needed to consider the frame difference according to policy ideas. In addition, fundamental efforts are needed to find answers to climate change by gathering experts from various fields that are not politically biased.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  ๋ฐ ํ•„์š”์„ฑ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 4 1. ์—ฐ๊ตฌ ๋ฒ”์œ„ 4 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 4 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  6 ์ œ 1 ์ ˆ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 6 1. ์ •์ฑ… ์•„์ด๋””์–ด 6 2. ์ •์ฑ… ํ”„๋ ˆ์ž„ 10 3. ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ… 13 ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  17 1. ์ •์ฑ… ์•„์ด๋””์–ด ๊ด€๋ จ ์—ฐ๊ตฌ 17 2. ์ •์ฑ… ํ”„๋ ˆ์ž„ ๊ด€๋ จ ์—ฐ๊ตฌ 19 3. ๊ธฐํ›„๋ณ€ํ™” ์ •์ฑ… ๊ด€๋ จ ์—ฐ๊ตฌ(ํ…์ŠคํŠธ ๋ถ„์„ ์ค‘์‹ฌ) 21 ์ œ 3 ์ ˆ ๋น„ํŒ์  ๊ฒ€ํ†  ๋ฐ ์—ฐ๊ตฌ์ ์šฉ 25 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ์„ค๊ณ„ 26 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋Œ€์ƒ ๋ฐ ๋ฒ”์œ„ 26 1. ์—ฐ๊ตฌ ๋Œ€์ƒ 26 2. ์—ฐ๊ตฌ ๋ฒ”์œ„ 28 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 29 1. ์ž๋ฃŒ ์ˆ˜์ง‘ 29 2. ๋ถ„์„ ๋ฐฉ๋ฒ• 30 ์ œ 4 ์žฅ ๋ถ„์„ ๊ฒฐ๊ณผ 37 ์ œ 1 ์ ˆ ๊ธฐ์ดˆํ†ต๊ณ„ ๋ถ„์„ 35 1. ํ…์ŠคํŠธ ์ˆ˜์ง‘ ๋ฐ ๋ถ„๋ฅ˜ 37 2. ํ…์ŠคํŠธ ์ „์ฒ˜๋ฆฌ 39 3. ๋‹จ์–ด ๋นˆ๋„ ๋ถ„์„ 41 ์ œ 2 ์ ˆ ํ† ํ”ฝ ๋ชจ๋ธ๋ง 50 1. ๋ฌธ์žฌ์ธ ์ •๋ถ€์˜ ๋ณด์ˆ˜ ์–ธ๋ก  54 2. ๋ฌธ์žฌ์ธ ์ •๋ถ€์˜ ์ง„๋ณด ์–ธ๋ก  58 3. ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์˜ ๋ณด์ˆ˜ ์–ธ๋ก  62 4. ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์˜ ์ง„๋ณด ์–ธ๋ก  66 ์ œ 3 ์ ˆ ์˜๋ฏธ ์—ฐ๊ฒฐ๋ง ๋ถ„์„ 69 1. ๋ฌธ์žฌ์ธ ์ •๋ถ€์˜ ๋ณด์ˆ˜ ์–ธ๋ก  72 2. ๋ฌธ์žฌ์ธ ์ •๋ถ€์˜ ์ง„๋ณด ์–ธ๋ก  75 3. ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์˜ ๋ณด์ˆ˜ ์–ธ๋ก  78 4. ๋ฐ•๊ทผํ˜œ ์ •๋ถ€์˜ ์ง„๋ณด ์–ธ๋ก  81 ์ œ 4 ์ ˆ ์ •์ฑ… ํ”„๋ ˆ์ž„ ๋„์ถœ 84 1. ๋‹จ์–ด ๋นˆ๋„ ๋ถ„์„ 84 2. ํ† ํ”ฝ ๋ชจ๋ธ๋ง 86 3. ์˜๋ฏธ ์—ฐ๊ฒฐ๋ง ๋ถ„์„ 90 ์ œ 5 ์žฅ ๊ฒฐ๋ก  96 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์š”์•ฝ 96 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ์˜์˜ 99 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 101 ์ฐธ๊ณ ๋ฌธํ—Œ 104 Abtract 112์„

    ๊ทœ์ œํšŒํ”ผ ๋ฐ ์šฐํšŒํ˜„์ƒ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› : ํ–‰์ •ํ•™๊ณผ, 2014. 2. ์ตœ๋ณ‘์„ .๋ณธ ๋…ผ๋ฌธ์€ ํ›„์›ํšŒ, ์ •์น˜ํ›„์›๊ธˆ ๋ฐ ํšŒ๊ณ„๋ณด๊ณ ์— ๊ด€๋ จํ•œ ๊ทœ์ œ๊ฐ€ ๊ด‘ ๋ฒ”์œ„ํ•œ ๊ทœ์ œํšŒํ”ผ ๋ฐ ์šฐํšŒํ˜„์ƒ์„ ์•ผ๊ธฐํ•˜๊ณ  ์žˆ๋Š” ์›์ธ์„ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฐ ํ˜„์ƒ์˜ ์›์ธ์— ๋Œ€ํ•˜์—ฌ ํ”ํžˆ ๊ทœ์ œ์œ„๋ฐ˜ํ–‰์œ„์— ๋Œ€ํ•œ ์ฒ˜๋ฒŒ ๊ทœ์ •์ด ์•ฝํ•˜๋‹ค๊ฑฐ๋‚˜ ๊ทœ์ œ๊ธฐ์ค€์ด ๋„ˆ๋ฌด ๋‚ฎ๊ฒŒ ์„ค์ •๋˜์–ด ์žˆ์–ด์„œ๋ผ๋Š” ๋“ฑ ์˜ ์˜๊ฒฌ์„ ์ œ์‹œํ•˜๋ฉด์„œ ๊ทœ์ œ๋ฅผ ๋”์šฑ ๊ฐ•ํ™”ํ•˜๋Š” ๊ฒƒ์ด ํ•ด๊ฒฐ์ฑ…์ด ๋  ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋งํ•˜๋‚˜ ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ์— ๋น„์ถ”์–ด ๋ณผ ๋•Œ ์ด๋Š” ๋…ผ๋ฆฌ์  ํƒ€๋‹น ์„ฑ์ด ๋งค์šฐ ์•ฝํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ์ œ์‹œํ•˜๊ณ  ์žˆ๋Š” ๋‹ค์ข…๋‹ค์–‘ํ•œ ๊ทœ์ œํšŒํ”ผ ๋ฐ ์šฐํšŒ์‚ฌ๋ก€๋“ค์€ ๊ทœ์ œ๋Œ€์ƒ์ž์ธ ์ •์น˜์ธ๊ณผ ๊ตญ๋ฏผ๋“ค์ด ๊ณ ์˜๋‚˜ ๋ฌด์ง€๋กœ ๊ทœ์ œ๋ฅผ ๋ฌด์‹œํ•˜๊ณ  ์œ„๋ฐ˜ํ•œ๋‹ค๊ธฐ๋ณด๋‹ค๋Š” ์ž์‹ ์˜ ํ–‰๋™์ด ๊ทœ์ œ์œ„๋ฐ˜์— ํ•ด๋‹น๋  ์ˆ˜ ์žˆ์Œ์„ ์ž˜ ์•Œ๋ฉด์„œ๋„ ๊ทœ์ œ๊ฐ€ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์ •์น˜ํ˜„์‹ค๊ณผ ์ง€๋‚˜์น˜๊ฒŒ ์œ ๋ฆฌ๋˜์–ด ์žˆ๋Š” ์†์—์„œ, ๋˜ํ•œ ๋‹ค๋ฅธ ๊ทœ์ œ๋Œ€์ƒ์ž๋“ค๋„ ์ž๊ธฐ์™€ ๊ฐ™์€ ์ฒ˜์ง€์— ์žˆ๊ณ  ๋”ฐ๋ผ ์„œ ๋น„์Šทํ•œ ํ–‰๋™์„ ํ•˜๋ฆฌ๋ผ๋Š” ์ถฉ๋ถ„ํžˆ ๊ทผ๊ฑฐ ์žˆ๋Š” ์ถ”์ • ํ•˜์—์„œ ๋‚˜ํƒ€๋‚˜ ๊ณ  ์žˆ๋Š” ์ค„ํƒ€๊ธฐ ์‚ฌ๋ก€๋“ค์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด ์ ์€ ๋ณธ ์—ฐ๊ตฌ์˜ 2004๋…„ ์ •์น˜์ž๊ธˆ๋ฒ• ๊ฐœ์ • ๊ณผ์ •์— ๋Œ€ํ•œ ๊ณ ์ฐฐ์—์„œ๋„ ์ž˜ ๋“œ๋Ÿฌ๋‚˜๊ณ  ์žˆ ๋‹ค. ์ด๋ ‡๊ฒŒ ๋ณผ ๋•Œ ๊ทœ์ œํšŒํ”ผ ๋ฐ ์šฐํšŒํ˜„์ƒ์˜ ๋งŒ์—ฐ์€ ๊ทœ์ œ์˜ ๋น„ํ˜„์‹ค์„ฑ ์„ ๊ณ ๋ฐœํ•˜๋Š” ๊ฐ•๋ ฅํ•œ ์‹ ํ˜ธ๋กœ ๋ณผ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ทธ ๋Œ€์ฑ…์€ ๊ทœ์ œ๊ฐ•ํ™”๊ฐ€ ์•„๋‹ˆ๋ผ ๊ทœ์ œ์˜ ํ˜„์‹ค์ ํ•ฉ์„ฑ๊ณผ ํƒ€๋‹น์„ฑ์„ ๋†’์ด๋Š” ๋ฐ ์ฃผ์•ˆ์ ์„ ๋‘” ๊ทœ ์ œ์˜ ํ˜„์‹คํ™”์—์„œ ์ฐพ์•„์ ธ์•ผ ํ•จ์„ ์‹œ์‚ฌํ•˜๊ณ  ์žˆ๋‹ค.๋ชฉ ์ฐจ ์ œ 1 ์žฅ ์„œ ๋ก  ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฒ”์œ„ ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ์ œ 1 ์ ˆ ์ •์น˜ํ›„์›๊ธˆ ๊ทœ์ œ์˜ ์˜์˜์™€ ๋ถ„๋ฅ˜ 1. ์ •์น˜ํ›„์›๊ธˆ ๊ทœ์ œ์˜ ์˜์˜์™€ ํ•„์š”์„ฑ 2. ์ •์น˜ํ›„์›๊ธˆ ๊ทœ์ œ์˜ ๋ถ„๋ฅ˜ ์ œ 2 ์ ˆ ์ •์น˜ํ›„์›๊ธˆ ๊ทœ์ œ์˜ ์›์น™๊ณผ ์ˆ˜๋‹จ 1. ์ •์น˜ํ›„์›๊ธˆ ๊ด€๋ จ ์›์น™ ๋ฐ ์ œํ•œ 2. ํ›„์›๊ธˆ ๊ด€๋ จ ๊ทœ์ œ 3. ์ •์น˜ํ›„์›๊ธˆ ๊ด€๋ จ ๊ธฐ์ค€ ๋ฐ ํ•œ๋„ 4. ํšŒ๊ณ„๋ณด๊ณ  ์ œ 3 ์ ˆ ์ •์น˜ํ›„์›๊ธˆ ๊ทœ์ œํšŒํ”ผ ๋ฐ ์šฐํšŒํ˜„์ƒ์˜ ์›์ธ๊ณผ ์œ ํ˜• 1. ์›์ธ๊ณผ ์œ ํ˜• ๋ถ„๋ฅ˜์˜ ์˜์˜ 2. ๊ทœ์ œ์˜ ๋น„ํ˜„์‹ค์„ฑ 3. ์œ„๋ฐ˜ํ–‰์œ„ ์ ๋ฐœ์˜ ์–ด๋ ค์›€๊ณผ ํ•œ๊ณ„ 4. ์œ„๋ฐ˜ํ–‰์œ„ ์ฒ˜๋ฒŒ์˜ ๊ด€๋Œ€ํ•จ 5. ๋ˆ์„ ๊ฑฐ์˜ ์—ญํ•™์— ๋Œ€ํ•œ ์ธ์‹ 6. ๊ธฐํƒ€ ์›์ธ ์ œ 3 ์žฅ ๊ทœ์ œํšŒํ”ผ ๋ฐ ์šฐํšŒํ˜„์ƒ ์‚ฌ๋ก€์˜ ๋ถ„์„ ์ œ 1 ์ ˆ ๋ฒ•์ธ์˜ ์ •์น˜ํ›„์›๊ธˆ ๊ธฐ๋ถ€๊ธˆ์ง€ 1. ๊ทœ์ œ ์ˆ˜๋‹จ 2. ์‚ฌ๊ฑด์˜ ๊ฐœ์š” 3. ๊ทœ์ œํšŒํ”ผ ์›์ธ ๋ถ„์„ ์ œ 2 ์ ˆ ๋‹จ์ฒด์™€ ๊ด€๋ จ๋œ ์ •์น˜ํ›„์›๊ธˆ ๊ธฐ๋ถ€๊ธˆ์ง€ 1. ๊ทœ์ œ ์ˆ˜๋‹จ 2. ์‚ฌ๊ฑด์˜ ๊ฐœ์š” 3. ๊ทœ์ œํšŒํ”ผ ์›์ธ ๋ถ„์„ ์ œ 3 ์ ˆ ์ถœํŒ๊ธฐ๋…ํšŒ ์‚ฌ๋ก€ 1. ๊ทœ์ œ ์ˆ˜๋‹จ 2. ์‚ฌ๊ฑด์˜ ๊ฐœ์š” 3. ๊ทœ์ œํšŒํ”ผ ์›์ธ ๋ถ„์„ ์ œ 4 ์žฅ ๋น„ํ˜„์‹ค์  ๊ทœ์ œ์˜ ํ˜•์„ฑ๋ฐฐ๊ฒฝ๊ณผ ๊ณผ์ • ์ œ 1 ์ ˆ 2004๋…„ ์ •์น˜์ž๊ธˆ๋ฒ• ๊ฐœ์ •์˜ ๋ฐฐ๊ฒฝ๊ณผ ์ฃผ์š”๊ฒฝ๊ณผ 1. ๋ถˆ๋ฒ• ์ •์น˜์ž๊ธˆ ์‚ฌ๊ฑด์˜ ์ง€์†์  ๋ฐœ์ƒ 2. ๊ทœ์ œ ๊ฐ•ํ™” ํ•„์š”์„ฑ์— ๋Œ€ํ•œ ์ธ์‹ 3. ๋ฒ”๊ตญ๋ฏผ์ •์น˜๊ฐœํ˜ํ˜‘์˜ํšŒ์˜ ๊ทœ์ œ๊ฐœํ˜ ๋Œ€์•ˆ ์ œ์‹œ 4. ๊ตญํšŒ์˜ ๋ฌด๋น„ํŒ์  ์ˆ˜์šฉ ์ œ 2 ์ ˆ ์ฃผ์š” ํ–‰์œ„์ž์˜ ํƒœ๋„์™€ ๋Œ€์‘์–‘์ƒ 1. ๊ตญํšŒ์™€ ๊ตญํšŒ์˜์› 2. ์„ ๊ฑฐ๊ด€๋ฆฌ์œ„์›ํšŒ 3. ๊ตญํšŒ์˜์›๊ณผ ์ •์น˜์ธ ์ผ๋ฐ˜ 4. ์–ธ๋ก , ์‹œ๋ฏผ๋‹จ์ฒด ๋“ฑ ์ œ 5 ์žฅ ๊ฒฐ ๋ก  ์ œ 1 ์ ˆ ๋ณธ ์—ฐ๊ตฌ์˜ ์š”์•ฝ ์ œ 2 ์ ˆ ์ •์ฑ…์  ์‹œ์‚ฌ์  ์ฐธ๊ณ ๋ฌธํ—Œ AbstractMaste

    ํ•œ๊ตญ์˜ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€๋™ ์š”์ธ ๋ฐ ๊ฐ€๊ตฌ์˜ ํ›„์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ๊ฒฝ์ œํ•™๋ถ€,2019. 8. ํ™์žฌํ™”.๋ณธ ์—ฐ๊ตฌ๋Š” 2001๋…„๋ถ€ํ„ฐ 2016๋…„๊นŒ์ง€ ํ•œ๊ตญ์˜ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€ํ™”์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ๋“ค์˜ ์ƒ๋Œ€์  ๊ธฐ์—ฌ๋„๋ฅผ ์ˆ˜๋Ÿ‰์ ์œผ๋กœ ๋ฐํžˆ๊ณ , ์ฃผํƒ๋‹ด๋ณด์ธ์ •๋น„์œจ(LTV) ๊ทœ์ œ ๊ฐ•ํ™” ๋ฐ ํ–ฅํ›„ ์ผ์–ด๋‚  ์ˆ˜ ์žˆ๋Š” ๋ณด์œ ์„ธ ์ธ์ƒ๊ณผ ์ทจ๋“์„ธ ํ์ง€๊ฐ€ ์ฃผํƒ๊ฐ€๊ฒฉ, ์ž„์ฐจ๋ฃŒ ๋ฐ ๊ฐ€๊ตฌ์— ํ›„์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ๋ถ„์„ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋น„๋™์งˆ์  ๊ฐ€๊ตฌ(heterogeneous households)๋กœ ์ด๋ฃจ์–ด์ง„ ๊ท ํ˜•๊ฑฐ์‹œ๊ฒฝ์ œ ๋ชจํ˜•์„ ๊ตฌ์„ฑํ•œ๋‹ค. ๋ชจํ˜•๊ฒฝ์ œ๋Š” ์†Œ๋“, ์ฃผ๊ฑฐํ˜•ํƒœ, ์†Œ์œ ๋ฉด์ , ์ฃผ๊ฑฐ๋ฉด์ , ์ž์‚ฐ ๋ฐ ๋ถ€์ฑ„ ๊ทœ๋ชจ, ์†Œ๋น„์ˆ˜์ค€์˜ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ€๊ตฌ๋“ค๋กœ ๊ตฌ์„ฑ๋˜๋ฉฐ, ์ด๋“ค ๊ฐ€๊ตฌ์˜ ๊ฐœ๋ณ„ ์„ ํƒ์— ๋”ฐ๋ผ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ๊ฐ€ ๋‚ด์ƒ์ ์œผ๋กœ ๊ฒฐ์ •๋˜๋Š” ๋ชจํ˜•๊ฒฝ์ œ์˜ ์‹œ์žฅ๊ท ํ˜•์„ ์„ค์ •ํ•œ๋‹ค. ์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ์‹ค์งˆ๊ธˆ๋ฆฌํ•˜๋ฝ, ์‹ค์งˆ์†Œ๋“์ƒ์Šน, ์ฃผํƒ๊ณต๊ธ‰์˜ ์ฆ๊ฐ€, LTV ๋ฐ DTI์˜ ๋Œ€์ถœ๊ทœ์ œ ๊ฐ•ํ™”, ๋ณด์œ ์„ธ ์ธํ•˜์™€ ์ทจ๋“์„ธ ๋ณ€ํ™” ๋“ฑ์˜ ๊ฒฝ์ œํ™˜๊ฒฝ ๋ฐ ์ •์ฑ…์  ์š”์ธ์˜ ์™ธ์ƒ์ ์ธ ๋ณ€ํ™”๊ฐ€ ๋ชจํ˜•๊ฒฝ์ œ์˜ ๊ท ์ œ(steady state) ๊ท ํ˜•์—์„œ์˜ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ ๋ฐ ๊ด€๋ จ ๋ณ€์ˆ˜๋“ค์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ  ์ด๋ฅผ ์ž๋ฃŒ์˜ ๊ฒฐ๊ณผ์™€ ๋น„๊ตํ•˜์—ฌ ๋™๊ธฐ๊ฐ„ ๋™์•ˆ ๊ฐœ๋ณ„ ์š”์ธ์˜ ์ƒ๋Œ€์  ๊ธฐ์—ฌ๋„๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ถ”๊ฐ€์ ์œผ๋กœ ํ–ฅํ›„ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” LTV ๊ทœ์ œ ๊ฐ•ํ™”์™€ ์ถฉ๋ถ„ํ•œ ํฌ๊ธฐ์˜ ๋ณด์œ ์„ธ ์ธ์ƒ ๋ฐ ์ทจ๋“์„ธ ํ์ง€๋ฅผ ์ƒ์ •ํ•˜์—ฌ ๊ฐ๊ฐ์˜ ๊ฒฝ์šฐ ์ฃผํƒ๊ฐ€๊ฒฉ, ์ž„์ฐจ๋ฃŒ ๋ฐ ๊ฐ€๊ตฌ์˜ ํ›„์ƒ ๋ณ€ํ™”๋ฅผ ์•„์šธ๋Ÿฌ ์‚ดํŽด๋ณธ๋‹ค. 2001๋…„๋ถ€ํ„ฐ 2016๋…„๊นŒ์ง€ ํ˜„์‹ค์—์„œ ๋‹จ์œ„๋ฉด์ ๋‹น ์‹ค์งˆ์ฃผํƒ๊ฐ€๊ฒฉ์€ 27.6% ์ƒ์Šนํ•˜์˜€๊ณ , ๋‹จ์œ„๋ฉด์ ๋‹น ์‹ค์งˆ์ž„์ฐจ๋ฃŒ๋Š” 2.1% ํ•˜๋ฝํ•˜์˜€๋‹ค. ์‹ค์งˆ๊ธˆ๋ฆฌํ•˜๋ฝ, ์‹ค์งˆ์†Œ๋“์ƒ์Šน, ์ฃผํƒ๊ณต๊ธ‰์˜ ์ฆ๊ฐ€, LTV ๋ฐ DTI์˜ ๋Œ€์ถœ๊ทœ์ œ ๊ฐ•ํ™”, ๋ณด์œ ์„ธ ์ธํ•˜์™€ ์ทจ๋“์„ธ ๋ณ€ํ™”์˜ ์š”์ธ์˜ ํšจ๊ณผ๋ฅผ ์ข…ํ•ฉํ•œ ๋ชจํ˜•๊ฒฝ์ œ์—์„œ๋Š” ๋‹จ์œ„๋ฉด์ ๋‹น ์‹ค์งˆ์ฃผํƒ๊ฐ€๊ฒฉ์ด 34.8% ์ƒ์Šนํ•˜๊ณ , ๋‹จ์œ„๋ฉด์ ๋‹น ์‹ค์งˆ์ž„์ฐจ๋ฃŒ๋Š” 2.5% ํ•˜๋ฝํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚œ๋‹ค. ์ฆ‰ ๋ชจํ˜•๊ฒฝ์ œ๋Š” ํ˜„์‹ค๊ฒฝ์ œ์˜ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€ํ™”์— ๋Œ€ํ•ด์„œ ์ƒ๋‹น๋ถ€๋ถ„ ์ผ์น˜ํ•˜๋Š” ๊ฒฐ๊ณผ๋ฅผ ๋ณด์ธ๋‹ค. 2001๋…„์—์„œ 2016๋…„์˜ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€ํ™”๋Š” ๋Œ€๋ถ€๋ถ„ ์‹ค์งˆ๊ธˆ๋ฆฌํ•˜๋ฝ, ์‹ค์งˆ์†Œ๋“์ƒ์Šน, ์ฃผํƒ๊ณต๊ธ‰์˜ ์ฆ๊ฐ€๋กœ ์„ค๋ช…์ด ๋˜๊ณ , LTV ๋ฐ DTI์˜ ๋Œ€์ถœ๊ทœ์ œ ์ •์ฑ…์˜ ๋ณ€ํ™”์™€ ๋ณด์œ ์„ธ, ์ทจ๋“์„ธ์˜ ์ฃผํƒ๊ด€๋ จ์„ธ์ œ์˜ ๋ณ€ํ™”๊ฐ€ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€ํ™”์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋ฏธ๋ฏธํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. LTV ๊ทœ์ œ๋น„์œจ์ด 100%์—์„œ 70%๋กœ, 70%์—์„œ 40%๋กœ ๊ฐ•ํ™”๋  ๋•Œ ์žฅ๊ธฐ์ ์œผ๋กœ ์ฃผํƒ๊ฐ€๊ฒฉ์€ ๋น„๊ต์  ์ž‘์€ ํญ์œผ๋กœ ๊ฐ์†Œํ•˜์ง€๋งŒ, LTV ๊ทœ์ œ๋น„์œจ์ด 40%์—์„œ 0%๋กœ ๊ฐ์†Œํ•˜๊ฒŒ ๋  ๋•Œ๋Š” ์ฃผํƒ๊ฐ€๊ฒฉ์ด ํฐ ํญ์œผ๋กœ ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ๋ชจํ˜•๊ฒฝ์ œ์—์„œ ์ž๋ฃŒ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ LTV ๋น„์œจ์ด 40% ์ดํ•˜์ธ ๊ฐ€๊ตฌ์˜ ๋น„์ค‘์ด 90% ์ด์ƒ์ด๊ธฐ ๋•Œ๋ฌธ์— LTV ๊ทœ์ œํ•œ๋„๊ฐ€ ์ถฉ๋ถ„ํžˆ ์ปค์กŒ์„ ๋•Œ์— LTV ๊ทœ์ œํ•œ๋„ ๊ฐ•ํ™”์— ๋”ฐ๋ฅธ ์ฃผํƒ๊ฐ€๊ฒฉ ํ•˜๋ฝ์˜ ํญ์ด ํ™•๋Œ€๋œ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. LTV ๊ทœ์ œ ๊ฐ•ํ™”์— ๋”ฐ๋ผ ๊ฒฝ์ œ ์ „์ฒด์ ์œผ๋กœ ๊ฐ€๊ตฌ์˜ ํ›„์ƒ์ด ์ฆ๊ฐ€ํ•˜๊ณ , ํŠนํžˆ ์ด๋Ÿฌํ•œ ํ›„์ƒ ์ฆ๊ฐ€๋Š” ๊ณ ์†Œ๋“์ธต์— ์ง‘์ค‘๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. LTV ๊ทœ์ œ๊ฐ€ ์ถฉ๋ถ„ํžˆ ๊ฐ•ํ™”๋˜๋ฉด ์ €์†Œ๋“์ธต๋„ ๊ณ ์†Œ๋“์— ๋น„ํ•ด ์ž‘์€ ํญ์ด์ง€๋งŒ ํ›„์ƒ ์—ญ์‹œ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ–ฅํ›„ ๋ณด์œ ์„ธ์˜ ๊ณผ์„ธํ‘œ์ค€์ด ์‹ค๊ฑฐ๋ž˜๊ฐ€๋กœ ์ธ์ƒ๋˜๋Š” ๊ฒฝ์šฐ๋ฅผ ์ƒ์ •ํ•œ ์‹คํ—˜์—์„œ๋Š” ์žฅ๊ธฐ์ ์œผ๋กœ ์ฃผํƒ๊ฐ€๊ฒฉ์ด 9.3% ํ•˜๋ฝํ•˜๊ณ , ์ž„์ฐจ๋ฃŒ๋Š” 4.1% ํ•˜๋ฝํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ฐ€๊ตฌ๋Š” ํ‰๊ท ์ ์œผ๋กœ ๋งค๊ธฐ ์†Œ๋น„๊ฐ€ 0.7% ๊ฐ์†Œํ•˜๋Š” ํฌ๊ธฐ์˜ ํ›„์ƒ ๋ณ€ํ™”๋ฅผ ๋ณด์˜€๋‹ค. ํŠนํžˆ ๊ณ ์†Œ๋“์ธต์˜ ๊ฒฝ์šฐ ํ›„์ƒ ๊ฐ์†Œ ํญ์ด ๋”์šฑ ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ทจ๋“์„ธ๊ฐ€ ํ์ง€๋˜๋Š” ๊ฒฝ์šฐ๋ฅผ ์ƒ์ •ํ•œ ์‹คํ—˜์—์„œ๋Š” ์žฅ๊ธฐ์ ์œผ๋กœ ์ฃผํƒ๊ฐ€๊ฒฉ์ด 7.4% ์ƒ์Šนํ•˜๊ณ , ์ž„์ฐจ๋ฃŒ๋Š” 2.9% ์ƒ์Šนํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ธฐ์กด์˜ ํ†ต๋…๊ณผ๋Š” ๋‹ฌ๋ฆฌ ๊ฐ€๊ตฌ๋Š” ํ‰๊ท ์ ์œผ๋กœ ๋งค๊ธฐ ์†Œ๋น„๊ฐ€ 0.1% ๊ฐ์†Œํ•˜๋Š” ์ •๋„์˜ ํ›„์ƒ ๋ณ€ํ™”๋ฅผ ๋ณด์˜€๊ณ , ๊ณ ์†Œ๋“์ธต์ผ์ˆ˜๋ก ํ›„์ƒ ๊ฐ์†Œ์˜ ํญ์ด ๋”์šฑ ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ทจ๋“์„ธ๊ฐ€ ํ์ง€๋˜๋Š” ๊ฒฝ์šฐ ์ฃผํƒ๊ฐ€๊ฒฉ์ด ์ƒ์Šนํ•˜๋ฉด์„œ ๊ธฐ์กด์˜ ์ฃผํƒ๋ณด์œ ๊ฐ€๊ตฌ ์ค‘ ๋Œ€์ถœ๋น„์ค‘์ด ํฐ ๊ฐ€๊ตฌ๋Š” LTV ๊ทœ์ œํ•œ๋„๋กœ ์ธํ•ด ์ฃผํƒ์˜ ํฌ๊ธฐ๋ฅผ ์ค„์ด๊ฑฐ๋‚˜ ์ž„์ฐจ๊ฐ€๊ตฌ๋กœ ์ „ํ™˜ํ•˜๊ฒŒ ๋˜์–ด ์ด๋“ค ๊ณ„์ธต์˜ ํ›„์ƒ ๊ฐ์†Œ๋กœ ์ธํ•ด ๊ฒฝ์ œ ์ „์ฒด๋กœ๋Š” ๋น„๋ก ์ž‘์€ ํฌ๊ธฐ์ด์ง€๋งŒ ํ›„์ƒ ๊ฐ์†Œ๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค.This paper quantitatively evaluates the relative contribution of macroeconomic fundamentals and housing-related policies to the changes in real house prices, rents, and household welfare in Korea. We show that the observed changes in real house prices and rents in 2001-2016 are mainly attributed to a decrease in the real interest rate, an increase in real income, and an increase in aggregate house supply. However, housing-related policies turn out to have little impact on the price changes in contrast to the common belief that those policies greatly affected the housing market over the period. We also find that the welfare implications of fundamentals and housing-related policies vary by household income. This study also finds that if LTV regulation is tightened further to less than 40%, the effects on housing prices start to increase disproportionately because more than 90% of the households LTV ratio is less than 40%. In addition, tighter LTV regulations lead to higher household welfare on average, although larger portions of welfare gains fall to high income groups. If the tax base of property holding tax is expanded to the prevailing prices, the housing prices decrease by 9.3% and the rents decrease by 4.1% in the long run. The welfare decreases by 0.7% in terms of CEV on average and higher income groups get worse off more. If the acquisition tax is abolished, the housing prices increase by 7.4% and the rents increase by 2.9% in the long run. The welfare decreases by 0.1% in terms of CEV on average and higher income groups get worse off more due to interactions of the LTV regulation and the higher housing prices.์ œ1์žฅ ํ•œ๊ตญ์˜ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€๋™ ์š”์ธ ๋ถ„์„ ...... 1 ์ œ1์ ˆ ์„œ๋ก  ....................................................................... 1 ์ œ2์ ˆ ๋ชจํ˜•๊ฒฝ์ œ ................................................................. 4 1. ๊ฐ€๊ตฌ์˜ ์„ ํ˜ธ ๋ฐ ์ฃผ๊ฑฐ ......................................................... 5 2. ๊ฐ€๊ตฌ์˜ ์†Œ๋“ ..................................................................... 7 3. ๊ฐ€๊ตฌ์˜ ์ž์‚ฐ ๋ฐ ๋Œ€์ถœ๊ทœ์ œ ................................................... 7 4. ์ •๋ถ€ ๋ฐ ๊ฑฐ๋ž˜๋น„์šฉ .............................................................. 8 5. ๊ฐ€๊ตฌ์˜ ๋ฌธ์ œ ๋ฐ ๊ท ์ œ๊ท ํ˜• ................................................... 10 ์ œ3์ ˆ ๋ชจ์ˆ˜์„ค์ • ................................................................ 11 1. ๊ฒฝ์ œํ™˜๊ฒฝ ๋ฐ ์ •์ฑ…์„ ๋ฐ˜์˜ํ•œ ๋ชจ์ˆ˜ ........................................ 11 2. ์™ธ๋ถ€์  ๋ชจ์ˆ˜ ..................................................................... 20 3. ๋‚ด๋ถ€์  ๋ชจ์ˆ˜ ..................................................................... 23 4. 2016๋…„ ๋ชจํ˜•๊ฒฝ์ œ์˜ ๊ท ์ œ์ƒํƒœ ๋ถ„์„ ...................................... 25 ์ œ4์ ˆ ์ฃผํƒ๊ฐ€๊ฒฉ๊ณผ ์ž„์ฐจ๋ฃŒ์˜ ๋ณ€ํ™”์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ ๋ถ„์„ ... 30 1. ๋ชจํ˜•๊ฒฝ์ œ์˜ ๋ณ€ํ™”์™€ ์ž๋ฃŒ์˜ ๋ณ€ํ™” ๋น„๊ต ๋ถ„์„ .......................... 31 2. ๊ฐœ๋ณ„์š”์ธ์˜ ํšจ๊ณผ ๋ถ„์„ ....................................................... 36 ์ œ5์ ˆ ๊ฒฐ๋ก  ......................................................................... 49 ์ œ2์žฅ ์ฃผํƒ๋‹ด๋ณด์ธ์ •๋น„์œจ(LTV)์˜ ๋ณ€ํ™”๊ฐ€ ์ฃผํƒ๊ฐ€๊ฒฉ, ์ž„์ฐจ๋ฃŒ ๋ฐ ๊ฐ€๊ตฌ์˜ ํ›„์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ๋ถ„์„ .............. 51 ์ œ1์ ˆ ์„œ๋ก  ..................................................................... 51 ์ œ2์ ˆ ์ฃผํƒ๋‹ด๋ณด์ธ์ •๋น„์œจ ๋ณ€ํ™”์˜ ํšจ๊ณผ ................................ 52 ์ œ3์ ˆ ๊ฒฐ๋ก  ..................................................................... 55 ์ œ3์žฅ ๋ณด์œ ์„ธ ์ธ์ƒ๊ณผ ์ทจ๋“์„ธ ํ์ง€๊ฐ€ ์ฃผํƒ๊ฐ€๊ฒฉ, ์ž„์ฐจ๋ฃŒ ๋ฐ ๊ฐ€๊ตฌ์˜ ํ›„์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ๋ถ„์„ ................... 58 ์ œ1์ ˆ ์„œ๋ก  ..................................................................... 58 ์ œ2์ ˆ ๋ณด์œ ์„ธ์˜ ๊ณผ์„ธํ‘œ์ค€์ด ์‹ค๊ฑฐ๋ž˜๊ฐ€๋กœ ์ธ์ƒ๋˜๋Š” ๊ฒฝ์šฐ ........ 59 ์ œ3์ ˆ ์ทจ๋“์„ธ๊ฐ€ ํ์ง€๋˜๋Š” ๊ฒฝ์šฐ .......................................... 63 ์ œ4์ ˆ ๊ฒฐ๋ก  ..................................................................... 67 ์ฐธ๊ณ ๋ฌธํ—Œ ............................................................... 69 Abstract .............................................................. 71Docto

    ์ค‘์žฅ๊ธฐ SOC ํˆฌ์ž์ „๋žต์— ๊ด€ํ•œ ์—ฐ๊ตฌ(The middle and long term investment strategies of transporation social overhead capitals)

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    ๋…ธํŠธ : ์ด ์—ฐ๊ตฌ๋ณด๊ณ ์„œ์˜ ๋‚ด์šฉ์€ ๊ตญํ† ์—ฐ๊ตฌ์›์˜ ์ž์ฒด ์—ฐ๊ตฌ๋ฌผ๋กœ์„œ ์ •๋ถ€์˜ ์ •์ฑ…์ด๋‚˜ ๊ฒฌํ•ด์™€๋Š” ์ƒ๊ด€์—†์Šต๋‹ˆ๋‹ค

    ์ˆ˜๋„๊ถŒ ์ง€์—ญ์„ ์ค‘์‹ฌ์œผ๋กœ (2017~2020)

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™˜๊ฒฝ๋Œ€ํ•™์› ํ™˜๊ฒฝ๊ณ„ํšํ•™๊ณผ, 2021. 2. ๊น€๊ฒฝ๋ฏผ.ํ˜„ ์ •๋ถ€์—์„œ ์ฃผํƒ์‹œ์žฅ ์•ˆ์ •ํ™”๋ฅผ ๋ช…๋ถ„์œผ๋กœ ์กฐ์„ธ์™€ ์ฃผํƒ๊ธˆ์œต์— ๋Œ€ํ•œ ํŒจ๋„ํ‹ฐ๋ฅผ ๊ฐ•ํ™”ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ฐœ์ธ๊ณผ ๋ฒ•์ธ ๊ฐ„ ๊ทœ์ œ์˜ ํ˜•ํ‰์„ฑ์ด ์ถฉ๋ถ„ํžˆ ๊ณ ๋ ค๋˜์ง€ ๋ชปํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์ฃผํƒ์ˆ˜์š”์ž์ธ ๊ฐœ์ธ์—๊ฒŒ ๋ถ€๊ณผ๋˜๋Š” ์กฐ์„ธ๋ถ€๋‹ด๊ณผ ๋Œ€์ถœ๊ทœ์ œ๋ฅผ ์šฐํšŒํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ๋ฒ•์ธ์„ ํ†ตํ•˜์—ฌ ์ฃผํƒ์‹œ์žฅ์— ์ฐธ์—ฌํ•˜๋Š” ๊ฒฐ๊ณผ๋ฅผ ์ดˆ๋ž˜ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ˜„์ƒ์ด ์ฃผ์š” ์ฃผํƒ์‹œ์žฅ์ธ ์ˆ˜๋„๊ถŒ์—์„œ ์ง€์—ญ์ ์œผ๋กœ ์–ด๋–ป๊ฒŒ ์ฐจ๋ณ„ํ™”๋˜์–ด ๋‚˜ํƒ€๋‚˜๋Š”์ง€๋ฅผ ๊ณ ์ฐฐํ•˜๊ธฐ ์œ„ํ•ด ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐœ์ธ์— ๋Œ€ํ•œ ์ฃผํƒ๊ทœ์ œ์ •์ฑ…์ด ๋ฒ•์ธ ๋ช…์˜์˜ ์•„ํŒŒํŠธ ๊ฑฐ๋ž˜์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์ˆ˜๋„๊ถŒ ์‹œ๊ตฐ๊ตฌ 76๊ฐœ ์ง€์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฒ•์ธ์˜ ์•„ํŒŒํŠธ ๊ฑฐ๋ž˜์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๊ณ„๋Ÿ‰์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ 2017๋…„ 7์›”์—์„œ 2020๋…„ 7์›”๊นŒ์ง€ ์ด 37๊ฐœ์›” ๋™์•ˆ ์›”๋ณ„๋กœ ๋ฐœํ‘œ๋œ ์ฃผํƒ์ •์ฑ…์„ ์ •์ฑ…์ˆ˜๋‹จ ๋ฐ ์ •์ฑ…๋Œ€์ƒ์— ๋”ฐ๋ผ 2์ข…๋ฅ˜๋กœ ๋ถ„๋ฅ˜ํ•˜์—ฌ ์ง€์ˆ˜ํ™”ํ•˜์˜€๋‹ค. ์ดํ›„ ๋ฒ•์ธ์ด ๋งค์ˆ˜ํ•œ ๋ถ€๋™์‚ฐ ๊ฑฐ๋ž˜๋Ÿ‰์„ ์ข…์†๋ณ€์ˆ˜๋กœ, ์„œ์šธ์‹œ์•„ํŒŒํŠธ๊ฐ€๊ฒฉ์ง€์ˆ˜, ์‹œ๊ตฐ๊ตฌ ์ฃผ๋ฏผ๋“ฑ๋ก์„ธ๋Œ€์ˆ˜ ์ฆ๊ฐ€์œจ, ์ด์ž์œจ, ์ฝ”์Šคํ”ผ์ง€์ˆ˜ ๋“ฑ ์ฃผํƒ์‹œ์žฅ๊ณผ ๊ธฐํƒ€ ๊ฑฐ์‹œ๊ฒฝ์ œ๋ณ€์ˆ˜๋ฅผ ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ ํ•˜์—ฌ ํŒจ๋„๋ฐ์ดํ„ฐ๋ฅผ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๋ถ„์„ ๋ชจํ˜•์œผ๋กœ๋Š” ํŒจ๋„ ๋‹จ์œ„๊ทผ ๊ฒ€์ •๊ณผ ํŒจ๋„ ๊ณต์ ๋ถ„ ๊ฒ€์ •์„ ํ†ตํ•˜์—ฌ ๋‹จ์œ„๊ทผ๊ณผ ์‹œ๊ณ„์—ด์  ์ˆ˜๋ ดํ˜„์ƒ์„ ๊ฒ€์ •ํ•œ ์ดํ›„, ํŒจ๋„ ๋ฐ์ดํ„ฐ ๋ถ„์„์„ ์œ„ํ•œ ๊ณ ์ •ํšจ๊ณผ ๋ชจํ˜•๊ณผ ํ™•๋ฅ ํšจ๊ณผ ๋ชจํ˜•์„ ํ†ตํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๊ณ , ๋ถ„์„ ์ด์ „์— ํ•˜์šฐ์Šค๋งŒ ๊ฒ€์ •์„ ํ†ตํ•˜์—ฌ ๊ณ ์ •ํšจ๊ณผ ๋ชจํ˜•๊ณผ ํ™•๋ฅ ํšจ๊ณผ ๋ชจํ˜• ์ค‘ ์ ์ •ํ•œ ๋ชจํ˜•์„ ์„ ํƒํ•˜์˜€๋‹ค. ๋˜ํ•œ 1๊ณ„ ์ž๊ธฐ์ƒ๊ด€ ๊ฒ€์ •์„ ํ†ตํ•˜์—ฌ ์˜ค์ฐจํ•ญ์˜ ์‹œ๊ณ„์—ด์  ์ž๊ธฐ์ƒ๊ด€์„ฑ์„ ๊ฒ€์ •ํ•˜๊ณ  ์ด๋ฅผ ํ†ต์ œํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ง€์—ญ์ ์œผ๋กœ ๋ฒ•์ธ์˜ ์•„ํŒŒํŠธ๋งค์ˆ˜๋Ÿ‰ ๋ฐ ๊ทœ์ œ์˜ ๊ฐ•๋„๊ฐ€ ํฌ๊ฒŒ ์ฐจ์ด ๋‚˜๋ฏ€๋กœ ์ˆ˜๋„๊ถŒ ์ „์ฒด(๋ชจ๋ธ1), ์„œ์šธ ์™ธ ์ˆ˜๋„๊ถŒ(๋ชจ๋ธ2), ์„œ์šธ(๋ชจ๋ธ3)๋กœ ๋‚˜๋ˆ„์–ด ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ชจ๋ธ 1(์ˆ˜๋„๊ถŒ ์ „์ฒด) ๋ฐ ๋ชจ๋ธ 2(์„œ์šธ ์™ธ ์ˆ˜๋„๊ถŒ)์˜ ๊ฒฝ์šฐ ๋ถ€๋™์‚ฐ ๊ทœ์ œ ์ง€์ˆ˜๋Š” ์–‘์˜ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ๊ธˆ๋ฆฌ์™€๋Š” ์Œ์˜ ์ƒ๊ด€๊ด€๊ณ„, ์„œ์šธ์‹œ ์•„ํŒŒํŠธ ๊ฐ€๊ฒฉ ์ง€์ˆ˜์™€ ์ฝ”์Šคํ”ผ ์ง€์ˆ˜์™€๋Š” ์–‘์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด์™€ ๋‹ฌ๋ฆฌ ๋ชจ๋ธ3(์„œ์šธ)์€ ์„ธ๋Œ€์ˆ˜ ์ฆ๊ฐ€์œจ, ์ด์ž์œจ, ์„œ์šธ์‹œ ์•„ํŒŒํŠธ ๋งค๋งค๊ฐ€๊ฒฉ ์ง€์ˆ˜๋งŒ์ด ์œ ์˜ํ•œ ์˜ํ–ฅ๋ ฅ์ด ์žˆ์—ˆ๊ณ , ์ฃผํƒ๊ทœ์ œ์ง€์ˆ˜๋Š” ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ์ฃผ์ง€ ๋ชปํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์œ„ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•˜๋ฉด ์กฐ์„ธ์™€ ๊ธˆ์œต ํŒจ๋„ํ‹ฐ๋ฅผ ํ†ตํ•œ ๊ฐœ์ธ์˜ ์ฃผํƒ๊ฑฐ๋ž˜์— ๋Œ€ํ•œ ์ •๋ถ€์˜ ์ง€์†์ ์ธ ๊ฐœ์ž…์€ ๋ฒ•์ธ์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ๊ฑฐ๋ž˜ ์ฃผ์ฒด๋ฅผ ์ฃผํƒ์‹œ์žฅ์— ์ฐธ์—ฌ์‹œํ‚ค๊ณ , ์ด๋“ค์€ ์„ธ๋Œ€์ˆ˜ ์ฆ๊ฐ€ ๋“ฑ ์‹ค์ˆ˜์š”์ธก๋ฉด๋ณด๋‹ค๋Š” ๋ถ€๋™์‚ฐ ๊ทœ์ œ, ์ฝ”์Šคํ”ผ์ง€์ˆ˜, ๊ธˆ๋ฆฌ ๋“ฑ ํˆฌ์ž์˜ ์ธก๋ฉด์—์„œ ์•„ํŒŒํŠธ ์‹œ์žฅ์— ์ฐธ์—ฌํ•œ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ๊ฒฝํ–ฅ์„ฑ์€ ์„œ์šธ๋ณด๋‹ค๋Š” ์„œ์šธ ์™ธ ์ˆ˜๋„๊ถŒ์—์„œ ๊ฐ•ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚œ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ํ–ฅํ›„ ๋ถ€๋™์‚ฐ ๊ทœ์ œ ์‹œ ๊ฐœ์ธ๊ณผ ๋ฒ•์ธ๊ณผ์˜ ํ˜•ํ‰์„ฑ ๋ฐ ์ง€์—ญ ๋ถ€๋™์‚ฐ ์‹œ์žฅ์˜ ๊ฑฐ๋ž˜ ์›์ธ ๋ฐ ํŠน์„ฑ์„ ์ถฉ๋ถ„ํžˆ ๊ณ ๋ คํ•œ ๋Œ€์ฑ… ์ˆ˜๋ฆฝ์ด ํ•„์š”ํ•˜๋‹ค.Although the current government is strengthening penalties for tax and housing finance in the name of stabilizing the housing market, it has resulted in a new economic entity called corporations participating in the housing market. As the cause of this phenomenon needs to be analyzed, this study conducted a study on 76 areas of metropolitan city, county and district to see how the housing regulation policy for individuals affects apartment transactions under the corporate name. In order to quantitatively analyze the impact of corporations on apartment transactions, this study is based on the housing policies published monthly for a total of 37 months from July 2017 to July 2020 according to the policy instruments and policy targets (taxation for individuals). And housing finance incentives/penalties and corporate taxes and housing finance incentives/penalties). After that, the panel data was constructed using the real estate transaction volume purchased by the corporation as the dependent variable, and the housing market and other macroeconomic variables such as the Seoul apartment price index, the increase rate of the number of resident registration households in the city, county and district, interest rate, and KOSPI index as independent variables. As an analysis model, unit root and time series convergence was tested through unit root test and cointegration test, and then analyzed through fixed effect model and probability effect model for panel data analysis. The appropriate model was selected among the and probability effects models. In addition, the time-series autocorrelation of the error term was tested and controlled through a first-order autocorrelation test. In addition, since the amount of apartment purchases by corporations and the intensity of regulation differ greatly in regions, the analysis was divided into the entire metropolitan area (model 1), Seoul (model 2), and the metropolitan area outside Seoul (model 3). In the case of Model 1 (the entire metropolitan area) and Model 2 (the metropolitan area other than Seoul), the real estate regulation index had a positive correlation. It also showed a negative correlation with interest rates and a positive correlation with the Seoul apartment price index and the KOSPI index. Unlike this, however, Model 3 (Seoul) showed that only the household growth rate, the interest rate, and the Seoul apartment sale price index had a significant influence, and the housing regulation index did not have a significant effect. Summarizing the results of the above study, the government's continuous intervention in individual housing transactions through tax and financial penalties will involve a new entity called a corporation in the housing market. In terms of investment, it can be seen that it participates in the apartment market. And this tendency can be seen to be stronger in the metropolitan area outside Seoul than in Seoul. Therefore, it is necessary to establish measures that fully consider the causes and characteristics of transactions in the local real estate market and equity between individuals and corporations when regulating real estate in the future.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  2 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ๋ฒ”์œ„ 3 ์ œ 4 ์ ˆ ์—ฐ๊ตฌ์˜ ํ๋ฆ„ 4 ์ œ 2 ์žฅ ์„ ํ–‰์—ฐ๊ตฌ 5 ์ œ 1 ์ ˆ ๋ถ€๋™์‚ฐ ๊ทœ์ œ์™€ ์ฃผํƒ์‹œ์žฅ 5 1. ์กฐ์„ธ์ •์ฑ…๊ณผ ์ฃผํƒ์‹œ์žฅ 5 2. ์ฃผํƒ๊ธˆ์œต๊ณผ ์ฃผํƒ์‹œ์žฅ 7 3. ๋ถ€๋™์‚ฐ๊ทœ์ œ์ง€์ˆ˜๋ฅผ ํ™œ์šฉํ•œ ์—ฐ๊ตฌ 7 4. ๋ฒ•์ธ ๋ฐ ์ž„๋Œ€์‚ฌ์—…์ž์˜ ์ฃผํƒ์‹œ์žฅ ์ฐธ์—ฌ์š”์ธ 8 ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ์˜ ์ข…ํ•ฉ 9 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก  12 ์ œ 1 ์ ˆ ํŒจ๋„๋ฐ์ดํ„ฐ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 12 1. ํŒจ๋„ ๋‹จ์œ„๊ทผ ๊ฒ€์ • ๋ฐ ํŒจ๋„ ๊ณต์ ๋ถ„ ๊ฒ€์ • 12 2. ํŒจ๋„ ๋ฐ์ดํ„ฐ ๋ถ„์„ 15 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ์ž๋ฃŒ ์„ ์ • 19 1. ๊ฑฐ๋ž˜์ฃผ์ฒด๋ณ„ ์•„ํŒŒํŠธ ๊ฑฐ๋ž˜ (๊ตญํ† ๊ตํ†ต๋ถ€ ์‹ค๊ฑฐ๋ž˜ ๋ฐ์ดํ„ฐ) 19 2. ๋ถ€๋™์‚ฐ ๊ทœ์ œ ์ง€์ˆ˜ 20 3. ๊ธฐํƒ€ ๋ณ€์ˆ˜ 22 ์ œ 3 ์ ˆ ์‹ค์ฆ๋ถ„์„์„ ์œ„ํ•œ ๋ชจํ˜• ์„ค์ • 23 ์ œ 4 ์žฅ ์‹ค์ฆ ๋ถ„์„ 26 ์ œ 1 ์ ˆ ๋ถ„์„์ž๋ฃŒ ๊ฐœ์š” 26 ์ œ 2 ์ ˆ ์ž๋ฃŒ ๊ธฐ์ดˆ๋ถ„์„ 27 1. ๋ณ€์ˆ˜ ์ „์ฒด ๊ธฐ์ดˆ ํ†ต๊ณ„๋Ÿ‰ 27 2. ์ง€์—ญ๋ณ„ ๋ฒ•์ธ ๋ช…์˜ ์•„ํŒŒํŠธ ๋งค์ˆ˜๋Ÿ‰ 28 3. ๋ถ€๋™์‚ฐ ๊ทœ์ œ ์ง€์ˆ˜ ๋ฐ ๊ฐœ์ธ๊ณผ ๋ฒ•์ธ ๊ฐ„ ๊ทœ์ œ ์ฐจ์ด 29 4. ์„ธ๋Œ€์ˆ˜ ์ฆ๊ฐ€์œจ๊ณผ ์•„ํŒŒํŠธ๋งค๋งค๊ฐ€๊ฒฉ์ง€์ˆ˜ 30 5. ๊ฑฐ์‹œ ๊ฒฝ์ œ ์ง€ํ‘œ 32 ์ œ 3 ์ ˆ ํŒจ๋„ ๋‹จ์œ„๊ทผ ๋ฐ ๊ณต์ ๋ถ„ ๊ฒ€์ • ๊ฒฐ๊ณผ 33 1. ํŒจ๋„ ๋‹จ์œ„๊ทผ ๊ฒ€์ • ๊ฒฐ๊ณผ 33 2. ํŒจ๋„ ๊ณต์ ๋ถ„ ๊ฒ€์ • ๊ฒฐ๊ณผ 35 ์ œ 4 ์ ˆ ํŒจ๋„ ๊ฒ€์ • ๊ฒฐ๊ณผ 36 1. ํ•˜์šฐ์Šค๋งŒ ๊ฒ€์ • ๊ฒฐ๊ณผ 36 2. 1๊ณ„ ์ž๊ธฐ์ƒ๊ด€ ๊ฒ€์ • ๊ฒฐ๊ณผ 36 3. ๊ทœ์ œ์ง€์ˆ˜์™€ ๋ฒ•์ธ์˜ ์•„ํŒŒํŠธ ๋งค์ˆ˜๋Ÿ‰๊ฐ„์˜ ๊ด€๊ณ„ : ์ˆ˜๋„๊ถŒ 37 4. ๊ทœ์ œ์ง€์ˆ˜์™€ ๋ฒ•์ธ์˜ ์•„ํŒŒํŠธ ๋งค์ˆ˜๋Ÿ‰๊ฐ„์˜ ๊ด€๊ณ„ : ์„œ์šธ ์™ธ 38 5. ๊ทœ์ œ์ง€์ˆ˜์™€ ๋ฒ•์ธ์˜ ์•„ํŒŒํŠธ ๋งค์ˆ˜๋Ÿ‰๊ฐ„์˜ ๊ด€๊ณ„ : ์„œ์šธ 40 ์ œ 5 ์žฅ ๊ฒฐ ๋ก  41 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ์š”์•ฝ 41 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ๋ฐ ์‹œ์‚ฌ์  42 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ์˜์˜ ๋ฐ ํ•œ๊ณ„ 43 ์ฐธ๊ณ ๋ฌธํ—Œ 45 ์˜๋ฌธ์ดˆ๋ก 48Maste

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    ๋…ธํŠธ : ์ด ์—ฐ๊ตฌ๋ณด๊ณ ์„œ์˜ ๋‚ด์šฉ์€ ๊ตญํ† ์—ฐ๊ตฌ์›์˜ ์ž์ฒด ์—ฐ๊ตฌ๋ฌผ๋กœ์„œ ์ •๋ถ€์˜ ์ •์ฑ…์ด๋‚˜ ๊ฒฌํ•ด์™€๋Š” ์ƒ๊ด€์—†์Šต๋‹ˆ๋‹ค
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