• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.153-166
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• 2022

The study estimates the Structured VAR and the Dynamic Stochastic General Equilibrium Model for the Vietnamese economy based on the new Keynesian model for small and open economies, with the output gap, inflation, policy interest rate, the Vietnamese exchange rate, and the inflation and interest rate in the United States. The paper aims to clarify the impulse response of the macro variables through their shocks. It offers to model the SVAR and DSGE processes, as well as describe why and how interest rate policy is important in the impulse response of macro variables like the output gap and inflation process. The study supports the central role of monetary policy by giving empirical evidence for the new Keynesian theory, according to which an interest rate shock causes the output gap to widen and inflation to decrease. Finally, the application of the DSGE model is becoming more and more popular in the State Bank of Viet Nam to improve its policy planning, analyzing, and forecasting policy towards sustainable and stable growth.

• 산업경영시스템학회지
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• 제22권52호
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• pp.141-153
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• 1999

The focus of marketing study on the strategic tools has shifted from traditional 4Ps'(product, price, place and promotion) to macro relationship marketing which places emphasis on interfirm relationships. The purpose of this study is to develope antecedent variables of relationship type which play the most important role of interfirm relationships, and the antecedent variables of relationship structure comprises three factors : 1) transactional relationship structure, 2) hierarchical relationship structure and 3) embedded relationship structure.

• 한국안전학회지
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• 제33권4호
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• pp.98-104
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• 2018

Macroscopic accident analyses have been conducted to incorporate transportation safety into long-term transportation planning. In macro-level accident prediction model, exposure variable(e.g. a settled population) have been used as fundamental explanatory variable under the concept that each trip will be subjected to a probable risk of accident. However, a settled population may be embedded error by exclusion of active population concept. The objective of this research study is to develop macro-level accident prediction model using floating population variable(concept of including a settled population and active population) collected from mobile phone data. The concept of accident prediction models is introduced utilizing exposure variable as explanatory variable in a generalized linear regression with assumption of a negative binomial error structure. The goodness of fit of model using floating population variable is compared with that of the each models using population and the number of household variables. Also, log transformation models are additionally developed to improve the goodness of fit. The results show that the log transformation model using floating population variable is useful for capturing the relationships between accident and exposure variable and generally perform better than the models using other existing exposure variables. The developed model using floating population variable can be used to guide transportation safety policy decision makers to allocate resources more efficiently for the regions(or zones) with higher risk and improve urban transportation safety in transportation planning step.

• 자원환경지질
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• 제55권6호
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• pp.617-632
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• 2022

In recent years, environmental pollution and determining the main factors causing this pollution have become an important issue. This study investigates the relationship between the agricultural sector and environmental pollution in Azerbaijan for 1992-2018. The dependent variable in the study is the agricultural greenhouse gas emissions (CO₂ equivalent). Eight variables were selected as explanatory variables: four agricultural inputs and four agricultural macro indicators. Unit root tests, ARDL boundary test, FMOLS, DOLS and CCR long-term estimators, Granger causality analysis, and variance decomposition analyses were used to investigate the effect of these variables on agricultural emissions. The results show that chemical fertilizer consumption, livestock number, and pesticide use positively and statistically significantly affect agricultural emissions from agricultural input variables. In contrast, agricultural energy consumption has a negative and significant effect. From agricultural macro indicator variables, it was found that the crop and animal production index had a positive and significant effect on agricultural emissions. According to the Granger causality test results, it was concluded that there are a causality relationship from chemical fertilizer consumption, livestock number, crop and livestock production index variables towards agricultural emissions. Considering all the results obtained, it is seen that the variables that have the most effect on the increase in agricultural emissions in Azerbaijan are the number of livestock, the consumption of chemical fertilizers, and the use of pesticides, respectively. The results from the research will contribute to the information on agricultural greenhouse gas emissions and will play an enlightening role for policymakers and the general public.

• 한국지리정보학회지
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• 제6권1호
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• pp.59-77
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• 2003

본 연구는 적지분석시 이용되는 자료 중 의사결정과 관련된 입지인자를 추출하고, 매크로 언어에 의한 입지인자 조정에 따른 의사결정과정상의 이해상충을 조정할 수 있는 활용가능성을 검증하였다. 연구의 대상지역으로는 부산광역시 기장군 내의 개발제한구역을 대상으로 환경친화적인 실버타운 개발적지를 분석하였고, 지리정보체계의 지도학적 모델링 기법과 매크로 언어(macro language)를 이용한 입지인자별 변수조정에 따라 보다 효과적이고 합리적인 적지선정을 목적으로 하였다. 대상지의 현황분석 및 적지분석을 위해 기장군의 지형도, 행정자료들을 바탕으로 도로현황도, 시설물현황도, 표고, 경사, 향 분석도와 수계도 등의 수치지도 데이터베이스를 구축하였으며, 구축된 데이터베이스를 이용하여 입지성에 따른 분석을 통해 1차 적지를 선정하였다. 선정된 몇개의 후보지들 중에서 순위를 결정하기 위해 2차 선정조건으로 접근성, 이용성, 환경성에 따른 가중치를 부여하여 2차 적지를 선정하였다. 또한 이들 모든 세부인자들과 분석과정을 매크로 언어를 도입하여 조정이 가능하도록 함으로서 발주자나 계획가의 선호 및 목적에 따라 입지인자별 변수를 조정함으로써 보다 쉽고 효과적으로 적지를 선정할 수 있도록 하여, 이와 관련된 이해상충의 조정이 가능하도록 하였다. 매크로 언어를 이용한 자동변수조정에 따른 적지분석은 기존의 적지 분석과 비교해 더 효과적이고 합리적인 방법으로 이용될 수 있을 것이다.

• 아태비즈니스연구
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• 제11권2호
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• pp.159-172
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• 2020

Purpose - The purpose of this study is to investigate economic variables which have impact on the prices and returns of preferred stocks and to provide investors, underwriters, and policy makers with information regarding correlations and causal relations between them. Design/methodology/approach - This study collected 98 monthly data from Korea Exchange and Bank of Korea. The Granger causal relation analysis, unit-root test and the multiple regression analysis were hired in order to analyze the data. Findings - First, our study derives the economic variables affecting the prices and returns of preferred stocks and their implications, while previous studies focused mainly on the differential characteristics and related economic factors between common and preferred stocks. Empirical results show that the significant variables influencing the prices and returns of preffered stocks are consumer sentiment index, consumer price index, industrial production index, KOSPI volatility index, and exchange rate between Korean won and US dollar. Second, consumer sentiment index, consumer price index, and industrial production index have significant casual relations with the returns of preferred stocks, providing market participants with important information regarding investment in preferred stocks. Research implications or Originality - This study is different from previous studies in that preferred stocks themselves are investigated rather than the gap between common stocks and preferred stocks. In addition, we derive the major macro variables affecting the prices and returns of preferred stocks and find some useful causal relations between the macro variables and returns of preferred stocks. These findings give important implications to market participants, including stock investors, underwriters, and policy makers.

• 대한안전경영과학회지
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• 제11권1호
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• pp.121-130
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• 2009

This paper considers a six sigma project for reducing the cost copper of the cable materials in a electric wire company. The project follows a disciplined process of five macro phases: define, measure, analyze, improve, and control (DMAIC). A process map is used to identify process input variables. Three key process input variables are selected by using an input variables are selected by using an input variable evaluation table: large cable, plating, and a twisted pair. DOE is utilized for finding the optimal process conditions of the three key process input variables. The implementing result of this six sigma project is enable for reducing of the 2.8% copper materials.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.909-917
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• 2020

The research aims to analyze the firm-specific and macroeconomic factors that affect insurance company's financial performance. The research explores the variables that influence the financial performance of the United Arab Emirates (UAE)' insurance companies. The analysis for determining financial performance considers the following variables: the firm's age, retention ratio, capital adequacy, underwriting risk/loss ratio, financial-leverage, reinsurance dependency, and macro-economic factors such as GDP per capita, inflation rate considered as independent factors. The return-on-asset (ROA) is the key measuring indicator; it is regarded as the dependent variable for financial performance measures. The research focuses on secondary information obtained from insurance companies' financial statements. The researcher targeted 18 insurance companies listed on the UAE stock exchanges for study purposes. The research examines the overall factors that influence the financial performance of an insurance company. For analysis of data, software package of social sciences (SPSS version 20) is used. The studies used correlation and multiple linear regression analysis to determine financial performance and their effects. The analysis suggests that there are important and constructive relationships between the size, capital adequacy, and reinsurance dependency, while loss ratio, retention ratio, and financial leverage indicate a major negative relationship. And there's no link between GDP per capita and inflation.

• 통상정보연구
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• 제12권4호
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• pp.171-192
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• 2010

In general, a stock index and its individual stocks are assumed to follow a random walk. A stock index is an important source of information and one that is seen by people everyday, regardless of their investment intentions. This paper examines the correlation between the KOSPI-the index that best reflects the Korean stock market and the macro - economic variables that have been found to influence the index by previous studies. The sample period considers the years after 2000 when the Korean stock market matured as restrictions on foreign investors were removed. For this purpose, a Vector Error Correction Model (VECM) and KOSPI equation with a general pacific approach were used. This paper aims at verifying the factors that determined the KOSPI after 2000 and at examining whether there was structural change in the investment environment. It also investigates changes in the factors determining the KOSPI's performance as a result of structural changes in the investment environment. The V AR (Vector Autoregressive) model including the nine variables was selected as a baseline model whose stability was tested using the unit root test. The results from the VECM and the structural changes in the investment environment can be summarized by the following Inner story points.

• 품질경영학회지
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• 제29권3호
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• pp.166-176
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• 2001

This paper considers a six sigma project for reducing the color variation of the monitor materials in a chemical plant. The project follows a disciplined process of five macro phases: define, measure, analyze, improve, and control (DMAIC). A process map is used to identify process input variables. Three key process input variables are selected by using an input variable evaluation table; a melting pressure, a coloring agent, and a DP color variation. DOE is utilized for finding the optimal process conditions of the three key process input variables. The sigma level of defects rate becomes a 4.58 from a 2.0 at the beginning of the project.