한국 건설산업의 노동수요 결정요인 분석
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 유일선 | - |
dc.contributor.author | 이태희 | - |
dc.date.accessioned | 2019-12-16T02:45:57Z | - |
dc.date.available | 2019-12-16T02:45:57Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://repository.kmou.ac.kr/handle/2014.oak/11509 | - |
dc.identifier.uri | http://kmou.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002382116 | - |
dc.description.abstract | A lot of articles has pointed that recent polarization in Korean society is mainly attributed to wage discrepancy in labor market which contributes to income discrepancy between laborers and that it is quite related with segmentation of labor market. This kind of phenomenon has been expanded since Korean economic crisis which happened in 1998. Under this social background, this thesis aims to empirically analyze the determinants of labor demand in Korean construction industry, based on the human capital theory and the segmented labor market theory. First it was examined whether the labor market in Korean construction industry is substantially segmented. It is founded that due to the unique labor market structure of construction industry, such as subcontracting system in working, complexity of products, space-centered working system, the tendency of segmentation in labor market of the industry is more reinforced than that in other manufacturing industry, in terms of institution and market structure through the date issued by the National Statistical Office, Korea Construction Association. Second, based on these findings, I set up the model which is designed to make analysis of how and by which factors labor demands is determined in each segmented labor market. To do this, three factor-Cobb-Douglas production function which consists of capital, labor I(low-educated labor, unskilled labor and labor II, , is used. Labor I means labor demand from external labor market while labor II means that from internal labor market. The estimation equations which can make it possible to estimate the determinants of labor demand in each segmented labor market were derived by applying cost-minimizing principle to this production function, with the results that the labor demands in each labor market are determined by relative production factor price between three factors, the quantity of production and technical progress. The derived estimation equations are as follows. Based on the above estimation equations, in terms of estimation method was SUR(seemingly unrelated regression) method used, because ORS(ordinary least square) that assumes independent and identical disturbance terms cannot cover the simultaneous equation system with auto-correlated disturbance term. The purport of the estimation results are as follows. First, the labor demand of low-educated laborer in the whole labor market is not affected by the relative price of any production factor, while the quantity of production and technical progress have a positive effect on labor demand. But the substitutive relation between male and female laborers was founded Second, the labor demand of high-educated laborer in the whole labor market was increased only when technical progress takes place. Male laborers with high education year increase with increment of production quantity and technical progress while female laborers with high-education year increase when the relative price of capital() in terms of the price of high-educated labor rise. The labor demand of unskilled laborers increases when the relative price of the skilled laborer()rises. The rise of relative skilled laborer and technical progress increases labor demand of male unskilled laborer while female laborers are not affected by any factors. Fourth, only technical progress increases employment of skilled laborers. The same results appear in case of male and female laborers. But it has a larger effect on female skilled laborers than male skilled ones. Fifth, technical progress decreases the labor demand of irregular laborers Sixth, technical progress increases the labor demand of regular laborers and technical employees. Seventh, the relative price of capital() increases female labor demand. The labor demand of high-educated female laborers are the same case, while that of low-educated female labores are not affected by any factors. Eighth, technical progress increases labor demand of male labores. The labor demand of high-educated male laborers are the same case, while that of low-educated male labores are increased by increment of production quantity. Based on these findings, two things can be shown as implication of policy. First, the clearest result is that technical progress causes the unemployment of irregular laborers. Second, it is found that there are generally the substitutive relation between two labors and the complimentary relation between physical capital and two labors. Therefore, government should prepare the labor policy considering this point. | - |
dc.description.tableofcontents | Abstract ⅷ 제 1 장 서 론 1 제 1 절 연구의 배경 및 목적 1 제 2 절 연구의 범위와 방법 4 2. 1 연구방법 4 2. 2 연구범위 5 제 3 절 연구의 구성 6 제 2 장 노동시장의 이론적 검토 9 제 1 절 노동시장구조 이론 9 1. 1 경쟁노동시장론 9 1. 2 분절노동시장론 12 1. 3 소 결 18 제 3 장 한국 건설산업의 노동시장 구조 19 제 1 절 건설산업의 현황 20 1. 1 건설산업의 발전과 의의 20 1.1.1 건설산업의 비중 23 1.1.2 건설산업의 파급효과 30 1. 2 건설산업의 특징 31 제 2 절 건설산업의 노동시장현황 36 2. 1 건설산업의 노동형태 36 2. 2 건설산업의 임금구조 38 2.2.1 건설산업의 임금 결정 메카니즘 39 2.2.2 건설산업 임금현황 40 (1) 명목임금 41 (2) 실질임금 43 (3) 학력별 임금격차 46 1) 학력별 임금조정 46 2) 전체 노동자 학력별 임금 47 3) 남자 노동자 학력별 임금 49 4) 여자 노동자 학력별 임금 51 (4) 숙련별 임금 54 1) 숙련과 미숙련 구분 54 2) 숙련과 미숙련 노동 임금현황 55 (5) 직종별 임금 58 (6) 성별 임금격차 62 2.2.3 고용현황 65 (1) 고용구조의 특징 65 (2) 학력별 고용 65 1) 전체학력별 노동자수 65 2) 남자학력별 노동자수 67 3) 여자학력별 노동자수 69 (3) 숙련별 고용 72 (4) 직종별 고용 74 (5) 성별 고용 76 제 4 장 실증분석 모형 설정 78 제 1 절 추정모형 설정 78 제 2 절 통계자료 80 2. 1 건설산업 종사자의 임금 및 노동자수 80 2. 2 학력별 노동수요와 임금 80 2. 3 직종별 임금 및 노동자수 81 2. 4 시장이자율과 금융비용 82 2. 5 매출액 82 2. 6 소비자 물가지수 83 제 3 절 변수관련 설명 83 3. 1 종속변수 83 3. 2 독립변수 85 3.2.1 상대 자본가격 86 3.2.2 상대 임금가격 86 3.2.3 매출액과 부가가치액 87 3.2.4 기술진보 88 제 4 절 통계분석 방법 88 4. 1 단위근 검정(Unit Root Test) 88 4. 2 공적분 검정(Cointegration Test) 89 4. 3 추정방법:SUR(Seemingly Unrelated Regression) 추정법 90 제 5 장 추정결과 및 해석 92 제 1 절 추정결과 92 5. 1 단위근 검정결과 92 1) 학력별 단위근 검정결과 92 2) 숙련도별 단위근 검정결과 93 3) 직종별 단위근 검정결과 94 4) 성별 단위근 검정결과 95 5. 2 공적분 검증결과 97 1) 학력별 공적분 검증결과 97 2) 숙련도별 공적분 검증결과 98 3) 직종별 공적분 검증결과 99 4) 성별 공적분 검증결과 100 5. 3 SUR(Seemingly Unrelated Regression) 추정 결과 100 1) 학력별 SUR 추정결과 101 2) 숙련도별 SUR 추정결과 109 3) 직종별 SUR 추정결과 112 4) 성별 SUR 추정결과 116 가. 남녀 학력별 SUR 추정결과 116 나. 남녀 숙련도별 SUR 추정결과 120 제 6 장 요약 및 결론 123 참 고 문 헌 130 <부 록 1> 단위근 검정 결과표 138 <부 록 2> 공적분 검정 결과표 142 | - |
dc.format.extent | xi, 145 p. | - |
dc.language | kor | - |
dc.publisher | 한국해양대학교 대학원 | - |
dc.rights | 한국해양대학교 논문은 저작권에 의해 보호받습니다. | - |
dc.title | 한국 건설산업의 노동수요 결정요인 분석 | - |
dc.type | Dissertation | - |
dc.date.awarded | 2017-08 | - |
dc.contributor.alternativeName | TAE HEE LEE | - |
dc.contributor.department | 대학원 경제산업학과 | - |
dc.description.degree | Doctor | - |
dc.subject.keyword | Construction Industry, Labor Demand, Segmented Labor Market, Wage Discrepancy, Technical Progress, SUR(Seemingly Unrelated Regression) Method | - |
dc.title.translated | An Analysis on the Determinants of Labor Demand in Korean Construction Industry | - |
dc.contributor.specialty | 경제학 | - |
dc.identifier.holdings | 000000001979▲000000007040▲000002382116▲ | - |
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