[논문]DID와 PSM 분석을 통한 건설업 클린사업장 대상 재정지원사업 평가

장성은; 유성열; 김화일

doi:10.15269/jksoeh.2022.32.1.31

DID와 PSM 분석을 통한 건설업 클린사업장 대상 재정지원사업 평가
Evaluation of Accident Prevention Financial Support Projects in the Construction Industry Using DID and PSM 원문보기

한국산업보건학회지 = Journal of Korean Society of Occupational and Environmental Hygiene, v.32 no.1, 2022년, pp.31 - 40

장성은 (부산가톨릭대학교 안전보건학과) , 유성열 (부산가톨릭대학교 경영정보학과) , 김화일 (부산가톨릭대학교 안전보건학과)

Abstract ▼ AI-Helper

Objectives: The purpose of this study is to understand the impact on accident reduction by analyzing the policy effectiveness of an industrial accident prevention clean workplace support project targeting the construction industry. Methods: In this study, DID and PSM models were used to analyze workplaces receiving and not receiving financial support based on the status of industrial accidents in recent years and the status of the workplaces by year. Results: The research results show that meaningful effects continued to occur in terms of reducing accidents and increasing employment. Conclusions: In this study, we show the effectiveness of the clean workplace support project, one of the South Korean government's financial support projects in the field of occupational safety and health focusing on the construction industry. Financial support projects such as clean projects should be further expanded based on the results of this study.

주제어

표/그림 (13)

표 Table 1. Number of business sites supporting clean business in the construction industry
표 Table 2. Status of accidents at worksites supporting clean projects in the construction industry
표 Table 3. Comparison of characteristics of supported and unsupported work places
표 Table 4. Calculation of the effect on the supported work places.
그림 Figure 1. Concept of the DID analysis model
그림 Figure 2. Structure of analysis data
그림 Figure 3. Distribution of propensity scores before and after matching between supported and unsupported workplaces (2013)
그림 Figure 4. Distribution of propensity scores before and after matching between supported and unsupported workplaces (2014)
표 Table 5. Comparison of characteristics of supported and unsupported work places (matching data)
그림 Figure 5. Distribution of propensity scores before and after matching between supported and unsupported workplaces (2015)
그림 Figure 6. Distribution of propensity scores before and after matching between supported and unsupported workplaces (2016)
표 Table 6. Regression coefficient for the effect of clean project support
표 Table 7. Regression coefficient for the effect of clean project support

참고문헌 (8)

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Korea Environment Information Service(KEIS). Study on the methodology for predicting the employment effect of economic and industrial policy and major financial projects. MOEL; 2010. p. 10
Korea Occupational Safety&Health Agency(KOSHA). Intensive inspection data for prevention of fall accidents at small and medium-sized construction sites. KOSHA; 2020. P.1-2. Available from: https://www.kosha.or.kr/kosha/report/pressreleases.do?modeview&boardNo507&articleNo418861&attachNo
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