• Title, Summary, Keyword: Proxy variables

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Analysis of Climate Characteristics Observed over the Korean Peninsula for the Estimation of Climate Change Vulnerability Index (기후변화 취약성 지수 산출을 위한 한반도 관측 기후 특성 분석)

  • Nam, Ki-Pyo;Kang, Jeong-Eon;Kim, Cheol-Hee
    • Journal of Environmental Impact Assessment
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    • v.20 no.6
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    • pp.891-905
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    • 2011
  • Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

A Study on the Vulnerability Assessment for Agricultural Infrastructure using Principal Component Analysis (주성분 분석을 이용한 농업생산기반의 재해 취약성 평가에 관한 연구)

  • Kim, Sung Jae;Kim, Sung Min;Kim, Sang Min
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.1
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    • pp.31-38
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    • 2013
  • The purpose of this study was to evaluate climate change vulnerability over the agricultural infrastructure in terms of flood and drought using principal component analysis. Vulnerability was assessed using vulnerability resilience index (VRI) which combines climate exposure, sensitivity, and adaptive capacity. Ten flood proxy variables and six drought proxy variables for the vulnerability assessment were selected by opinions of researchers and experts. The statistical data on 16 proxy variables for the local governments (Si, Do) were collected. To identify major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted. The result of PCA showed that the first 3 principal components explained approximately 83 % and 89 % of the total variance for the flood and drought, respectively. VRI assessment for the local governments based on the PCA results indicated that provinces where having the relatively large cultivation areas were categorized as vulnerable to climate change.

상태공간모형을 이용한 이자율 확률과정의 추정

  • 전덕빈;정우철
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • pp.11-14
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    • 2003
  • The dynamics of unobservable short rate are frequently estimated directly by using a proxy. We estimate the biases resulting from this practice ("proxy problem"). To solve this problem, State-Space models have been proposed by many researchers. State-Space models have been used to estimate the unobservable variables from the observable variables in econometrics. However, applications of State-Space models often result in a misleading interpretation of the underlying processes especially when the absorbability of the State-Space model and the assumption of noise processes in the state vector are not properly considered. In this study, we propose the exact State-Space model that properly considers the faults of previous researchers to solve the proxy problem.

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Effects of Poverty Status on Socio-Emotional Development in Childhood : Focused on Comparing the Effects of Proxy Variables and Poverty-Co-Factors (빈곤지위가 아동의 사회·정서발달에 미치는 영향 :빈곤대리변수와 빈곤동반 위험요소와의 비교를 중심으로)

  • Park, Hyun-sun
    • Journal of the Korean Society of Child Welfare
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    • no.26
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    • pp.113-137
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    • 2008
  • Present study investigated the effects of poverty and poverty-co-factors in childhood. The effect of poverty status was measured by needs-income ratio. It compared its effect on children's socio-emotional development with that of poverty proxy variables such as recipient of public assistance, financial stress, subjective perception about social class, residence in public housing. It also examined the effects of poverty-co-factors after poverty status were controlled. Results show that poverty status has a more consistent negative relationship with socio-emotional development than other proxy variables. However, the relationship between them disappeared after poverty-co-factors were controlled. Findings from the present study suggest that targeted efforts for decreasing poverty-co-factor risks should be made along with financial support.

Stock Price Predictability of Financial Ratios and Macroeconomic Variables: A Regulatory Perspective

  • Kwag, Seung Woog;Kim, Yong Seog
    • Industrial Engineering and Management Systems
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    • v.12 no.4
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    • pp.406-415
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    • 2013
  • The present study examines a set of financial ratios in predicting the up or down movements of stock prices in the context of a securities law, the Sarbanes-Oxley Act of 2002 (SOA), controlling for macroeconomic variables. Using the logistic regression with proxy betas to alleviate the incompatibility problem between the firm-specific financial ratios and macroeconomic indicators, we report evidence that financial ratios are meaningful predictors of stock price changes, which subdue the influence of macroeconomic indicators on stock returns, and more importantly that the SOA truly improves the stock price predictability of financial ratios for the markup sample. The empirical results further suggest that industry and time effects exist and that for the markdown sample the SOA actually deteriorates the predictive power of financial ratios.

A Simultaneous Analysis on the Relationship Between Household Productivity and Market Productivity (가정생산성과 시장생산성의 관계분석을 통한 경제위기 대응력 증진을 위한 연구)

  • 정순희;최혜경
    • Journal of Korean Home Management Association
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    • v.18 no.2
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    • pp.45-60
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    • 2000
  • The purpose of this study was to examine the relationship between household productivity and market productivity of the married men in their early adulthood. Proxy variables of the household productivity were housework time, family cohesion·adaptability and family economic resource. Also proxy variables of the market productivity were job performance, job satisfaction and wage. The main result were as follows: First, men's housework time is insignificantly related to men's job performance, job satisfaction, and wage. But men's housework time is reduced as men's wage. Second, family cohesion·adaptability is significantly and positively related to the married men's job performance. The married men's job performance is significantly and positively related to the family cohesion·adaptability.

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Priority survey between indicators and analytic hierarchy process analysis for green chemistry technology assessment

  • Kim, Sungjune;Hong, Seokpyo;Ahn, Kilsoo;Gong, Sungyong
    • Environmental health and toxicology
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    • v.30 no.sup
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    • pp.3.1-3.11
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    • 2015
  • Objectives This study presents the indicators and proxy variables for the quantitative assessment of green chemistry technologies and evaluates the relative importance of each assessment element by consulting experts from the fields of ecology, chemistry, safety, and public health. Methods The results collected were subjected to an analytic hierarchy process to obtain the weights of the indicators and the proxy variables. Results These weights may prove useful in avoiding having to resort to qualitative means in absence of weights between indicators when integrating the results of quantitative assessment by indicator. Conclusions This study points to the limitations of current quantitative assessment techniques for green chemistry technologies and seeks to present the future direction for quantitative assessment of green chemistry technologies.

The Proxy Variables Selection of Vulnerability Assessment for Agricultural Infrastructure According to Climate Change (논문 - 기후변화에 따른 농업생산기반 재해 취약성 평가를 위한 대리변수 선정)

  • Kim, Sung-Jae;Park, Tae-Yang;Kim, Sung-Min;Kim, Sang-Min
    • KCID journal
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    • v.18 no.2
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    • pp.33-42
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    • 2011
  • Climate change has impacts on not only the average temperature rise but also the intensity and frequency of extreme events such as flood and drought. It is also expected that the damages on agricultural infrastructure will be increased resulting from increased rainfall intensity and frequency caused by climate change. To strengthen the climate change adaptation capacity, it is necessary to identify the vulnerability of a given society's physical infrastructures and to develop appropriate adaptation strategies with infrastructure management because generally facilities related to human settlements are vulnerable to climate changes and establishing an adaptive public infrastructure would reduce the damages and the repair cost. Therefore, development of mitigation strategies for agricultural infrastructure against climatic hazard is very important, but there are few studies on agricultural infrastructure vulnerability assessment and adaptation strategies. The concept of vulnerability, however, is difficult to functionally define due to the fact that vulnerability itself includes many aspects (biological, socioeconomic, etc.) in various sectors. As such, much research on vulnerability has used indicators which are useful for standardization and aggregation. In this study, for the vulnerability assessment for agricultural infrastructure, 3 categories of climate exposure, sensitivity, and adaptation capacity were defined which are composed of 16 sub-categories and 49 proxy variables. Database for each proxy variables was established based on local administrative province. Future studies are required to define the weighting factor and standardization method to calculate the vulnerability indicator for agricultural infrastructure against climate change.

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Study on Sensitivity of different Standardization Methods to Climate Change Vulnerability Index (표준화 방법에 따른 기후변화 취약성 지수의 민감성 연구)

  • Nam, Ki-Pyo;Kim, Cheol-Hee
    • Journal of Environmental Impact Assessment
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    • v.22 no.6
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    • pp.677-693
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    • 2013
  • IPCC showed that calculation of climate vulnerability index requires standardization process of various proxy variables for the estimation of climate exposure, sensitivity, and adaptive capacity. In this study, four different methodologies of standardization methods: Z-score, Rescaling, Ranking, and Distance to the reference country, are employed to evaluate climate vulnerability-VRI (Vulnerability-Resilience Indicator) over Korean peninsula, and the error ranges of VRI, arising from employing the different standardization are estimated. All of proxy variables are provided by CCGIS (Climate Change adaptation toolkit based on GIS) which hosts information on both past and current socio-economic data and climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the decades of 2000s, 2020s, 2050s, and 2100s. The results showed that Z-score and Rescaling methods showed statistically undistinguishable results with minor differences of spatial distribution, while Ranking and Distance to the reference country methods showed some possibility to lead the different ranking of VRI among South Korean provinces, depending on the local characteristics and reference province. The resultant VRIs calculated from different standardization methods showed Cronbach's alpha of more than 0.84, indicating that all of different methodologies were overall consistent. Similar horizontal distributions were shown with the same trends: VRI increases as province is close to the coastal region and/or it close toward lower latitude, and decreases as it is close to urbanization area. Other characteristics of the four different standardization are discussed in this study.

Vulnerability Assessment of Human Health Sector due to Climate Change: Focus on Ozone (기후변화에 따른 보건 분야의 취약성 평가: O3을 중심으로)

  • Lee, Jae-Bum;Lee, Hyun-Ju;Moon, Kyung-Jung;Hong, Sung-Chul;Kim, Deok-Rae;Song, Chang-Keun;Hong, You-Deog
    • Journal of Korean Society for Atmospheric Environment
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    • v.28 no.1
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    • pp.22-38
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    • 2012
  • Adaptation of climate change is necessary to avoid unexpected impacts of climate change caused by human activities. Vulnerability refers to the degree to which system cannot cope with impacts of climate change, encompassing physical, social and economic aspects. Therefore the quantification of climate change impacts and its vulnerability is needed to identify vulnerable regions and to setup the proper strategies for adaptation. In this study, climate change vulnerability is defined as a function of climate exposure, sensitivity, and adaptive capacity. Also, we identified regions vulnerable to ozone due to climate change in Korea using developed proxy variables of vulnerability of regional level. 18 proxy variables are selected through delphi survey to assess vulnerability over human health sector for ozone concentration change due to climate change. Also, we estimate the weighting score of proxy variables from delphi survey. The results showed that the local regions with higher vulnerability index in the sector of human health are Seoul and Daegu, whereas regions with lower one are Jeollanam-do, Gyeonggi-do, Gwangju, Busan, Daejeon, and Gangwon-do. The regions of high level vulnerability are mainly caused by their high ozone exposure. We also assessed future vulnerability according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1FI, A1T, A1B, B2, and B1 scenarios in 2020s, 2050s and 2100s. The results showed that vulnerability increased in all scenarios due to increased ozone concentrations. Especially vulnerability index is increased by approximately 2 times in A1FI scenarios in the 2020s. This study could support regionally adjusted adaptation polices and the quantitative background of policy priority as providing the information on the regional vulnerability of ozone due to climate change in Korea.