• 융합경영연구
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• 제5권1호
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• pp.27-37
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• 2017

Domestic government debt securities is one of the steps which is taken by the government of Indonesia as a major source of financial budget, covering for the budget deficit, debt payments and interest debt. The purposes of this research are to know the development of budget deficits, government debt and impact of domestic government debt securities against economic growth in Indonesia. Method of analysis used Ordinary Least Squares (OLS) analyzing the impact of the domestic debt against economic growth in Indonesia. This research uses time series data from 1997 to 2014. Total government debt and domestic government debt securities in Indonesia increased during the last five years. The average of domestic government securities was above 50 percent of the total government debt. Estimated results showed domestic government debt securities has a positive and significant effect to economic growth. Official development assistance (ODA) has a negative effect to economic growth. Other variables such as the gross fixed capital formation and receipt of remittance have positive and significant effect, total imports and government expenditure have negative and significant effect against economic growth.

• 디지털융복합연구
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• 제14권5호
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• pp.177-183
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• 2016

본 연구의 목적은 부채보유 가계를 대상으로 가계부채에 미치는 결정요인에 대하여 분석하고자 한 연구이다. 분석 방법으로는 SPSS 22.0을 사용하였다. 연구결과는 다음과 같다. 첫째, 부채보유 가계를 대상으로 검증한 결과, 인구통계학적 특성으로는 학력이 낮을수록, 나이가 많을수록, 직업은 농림 및 어업에서 그리고 가구원 수가 많을수록, 성별에 있어서는 여성들이 더 많은 심리적 부채부담을 갖는 것으로 나타났다. 둘째, 부채보유가계 중 월평균 부채상환액과 총자산에 대한 부채부담특성이 심리적 부채부담에 영향을 미치는 것으로 나타났다. 이는 취약계층을 위하여 부채부담을 낮출 수 있도록 부채 금리를 낮추고, 가계부채자에 대한 이해도를 높이는 것이 필요하며, 그에 적합한 금융교육과 컨설팅이 필요하다는 것을 시사한다. 셋째, 부채보유 가계 중 심리적 부채 부담에 영향을 미치는 요인으로 나이가 많을수록, 소득에 비해 월평균 지급이자 및 상환액이 높을수록, 총자산에 비해 총부채가 많을수록 심리적 부채부담에 영향을 미치는 것으로 나타났다. 가계부채에 영향을 주는 다른 요인은 후속연구에서 다루어질 것이다.

• 산경연구논집
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• 제12권2호
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• 가정과삶의질연구
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• 제26권3호
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• pp.169-189
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• 2008

There are few studies on the characteristics of defaulters, though research in this field is needed. The purpose of this study was to find out social, economic and psychological characteristics of defaulters who are married and in their thirties. For this study, an in-depth interview was used. The major findings were as follows. The focus of this study is defaulters who are married, in their thirties, have managed small businesses by themselves or with their spouses and have experienced job fluctuation. There were a lot of reasons for their becoming defaulters. Most of all, a slump in business with the occurrence of individual events caused them to be enrolled as defaulters. The monthly mean income of defaulters was $1,800,000{\sim}5,000,000$ won, yet it was irregular. Moreover, they were dependent upon labor income or business income. The monthly mean expenditure of defaulters was $1,000,000{\sim}2,300,000$ won, which constituted about $26%{\sim}57.5%$ of their monthly mean income. The defaulters needed to budget a number of expenditures such as food and private education. Defaulters had $25,000,000{\sim}128,000,000$ won in debts and $300,000{\sim}3,000,000$ won per month in debt payments. Most of them didn't have any emergency funds, monetary assets or fixed assets. Interestingly, they showed high tendency to use debt and low skill for their money management. Defaulters had short time horizons and were likely to buy something on the spur of the moment.

• The Journal of Asian Finance, Economics and Business
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• 제4권1호
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• pp.5-18
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• 2017

Total debt in the People's Republic of China surged to nearly 290% as a ratio to GDP by the second quarter of 2016, mostly on account of non-financial corporate debt. The outpouring of credit to stem the impact of the global financial crisis accentuated industrial overcapacity in traditional sectors, such as steel, cement, and energy, while feeding asset bubbles in the property, equity and bond markets. At the Chinese corporate level, this has translated into weakened fundamentals and a fall in industrial profits, particularly of SOEs. As debtors struggle to service interest payments, non-performing loans (NPLs) have been on the rise. This paper assesses the financial fragility of the Chinese economy by looking at risk factors in the non-financial sector. We apply quantile regressions to a dataset containing all Chinese listed companies in Standard & Poor's IQ Capital database. We find higher sensitivity over time of corporate leverage to some of its key determinants, particularly for firms at the upper margin of the distribution. In particular, profitability increasingly acts as a curb on corporate leverage. At a time of falling profitability across the Chinese non-financial corporate sector, this eases the brake on leverage and may contribute to its continuing increase.

• 경영정보학연구
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• 제23권1호
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• pp.69-91
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• 2021

국내 개인신용평가회사들은 과거와 현재 시점의 다양한 금융거래 정보를 활용하여 개인의 신용을 평가하고 있는데, 이 중 과거에 대출을 실행하여 이를 상환 또는 연체한 이력에 대한 정보를 의미하는 '상환이력정보'는 신용평가에 활용되는 다른 항목들에 비해 상대적으로 활용 비중이 높은 항목이다. 그러나 개인이 연체된 채무를 모두 변제하여 현재 연체중인 상태가 아닌 경우에도 과거의 연체 이력이 부정적인 요인으로 최장 5년간 평가에 반영되고 있어 금융소비자에게 과도한 불이익을 준다는 지적이 지속적으로 있어 왔다. 실제로 연체 이력이 있는 개인의 경우, 연체된 채무를 성실하게 변제한 개인(정상변제)과 그렇지 않은 개인(비정상변제)으로 구분할 수 있는데, 이들 간에는 신용도의 차이가 존재하므로 '정상변제'하는 개인의 특징을 확인하여 이들에게 '상환이력정보'의 활용기간을 단축시켜 주는 등의 혜택을 제공하는 것이 바람직하다고 판단된다. 본 연구는 이러한 문제의식에서 출발하여 한국신용정보원에서 보유하고 있는 2019년 12월 말 기준, 개인의 대출·연체·변제 정보에 기반하여 국내 연체경험자의 정상변제 요인을 분석하였다. 방법론은 개인신용평가모형에서 주로 사용하는 로지스틱 회귀모형을 기본으로 하여 의사결정나무, 신경망 모형 등의 머신러닝 방법론을 추가로 활용하였으며, 각 방법론별 성능을 비교해보았다. 실증분석 결과, 연체건수, 대출·연체유형 등이 정상변제 여부에 영향을 미치는 유의한 변수들로 확인되었으며 방법론 중에는 신경망 모형의 성능이 가장 높은 것으로 나타났다. 이러한 연구결과는 연체된 개인 차주의 정상변제 여부에 영향을 미치는 요인을 확인하여 개인신용평가모형을 고도화하는데 도움이 될 수 있을 것으로 보이며 연체 후 성실하게 변제하는 개인을 정책적으로 지원하기 위한 기초자료로도 활용될 수 있을 것으로 보인다. 향후에는 정상변제 요인을 추가 발굴하여 금융업권별 정상변제 요인의 세부적인 차이를 확인하고 이를 실제 모형에 반영하는 연구가 필요할 것이다.

• 한국지역사회생활과학회지
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• 제12권2호
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• pp.47-59
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• 2001

The purpose of this study was to examine the factors affecting financial satisfaction of rural housewives. Data for this study were collected from 202 households living in 8 provinces. The results were as follows; 1) The most frequent financial problems experienced from expenditures on clothes(82.1%), lack of expense for social intercourse (61.47), and difficulty in purchasing durable goods(60.1%) in the order. 2) 44.6% of the respondents said they were satisfied with their net worth, and 21.6% of them confessed they had difficulties in debt redemption while 52.5% of them said they felt pressure about monthly payments of installments, which reveals that farm households find it hard to pay back short-term debt. 3) The path analysis was adopted to see the causal relations among the variables influenced the financial satisfaction. The variables of experiences of economic problems, educational background(graduated from middle school), saving, income, and age appeared to be important in the order of effectiveness. Among them, the variables of saying and experiences of economic problems showed a direct effect, and those of age and saving displayed an indirect effect with the experiences of economic problems as the parameter. From this findings, it is suggested that rural extension workers and educators should emphasize the importance of the financial plan in their educational programs.

• Journal of Information Technology Applications and Management
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• 제14권2호
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• pp.151-168
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• 2007

The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

• 한국주거학회논문집
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• 제10권3호
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• pp.221-229
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• 1999

The purpose of this study is to investigate the housing affordability of multi-family dwelling in Seoul and to systemize the housing expenditure patterns and housing affordability according to household and housing characteristics. Housing expenditures are basically composed of the payments of four major items. including utilities. home alteration and interior furnishing. home mortgage debt. and monthly rent. Housing affordability index as operationally defined in this study is Housing Expenditure-to-Income Ratio (HEIR). The ratios were computed for each of the four housing expenditure items. Data for 465 multi-family dwellers were gathered from the structured questionnaire. The results showed the differences between household and housing characteristics on housing expenditure levels and HEIR. In addition. this differences had influence on future housing choice behavior. The analysis on the variables of housing choice behavior showed the result that user cost considering capital gains were less important. comparing those of early 1990's.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.