• Journal of Families and Better Life
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• v.24 no.5 s.83
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• pp.251-270
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• 2006

This study examined how the households used and combined financing sources to pay for college education. It compared the probability of using each source (current incomes, saving, education loans and grants) by households' socio-economic characteristics and analyzed which factors influence the decision to use each source and the amounts from each source for financing college education. Data for this study were from a questionnaire completed by 4-year college students (n=623) and were analyzed by t-tests, ANOVA and Heckman's two-step estimation models. The findings of this study were as follows: First, the most frequent source for college education was parents' savings and the second one was parents' incomes. Also, the most frequent combination of sources was saving and current incomes and the second was combination of three sources, saving, incomes and education loans. Second, the probability of using incomes was higher for younger students than for older students. The number of siblings showed significant differences among income, savings and education loans. Those who had higher incomes were more likely to use current incomes, saving, but less likely to borrow for financing college education. Middle-class income groups were more likely to borrow for education. Third, household incomes and asset holdings had generally positive impacts on the probability of using incomes and savings for college education, while total debt burden decreased both the probability and amounts of income and saving sources. The college costs had significantly positive effects on both the probability and the amounts of all of financing sources. Total grants received significantly decreased the amounts from incomes, savings and borrowing sources.

• Journal of Preventive Medicine and Public Health
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• v.50 no.2
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• pp.91-99
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• 2017

Objectives: As in many low-income and middle-income countries, out-of-pocket (OOP) payments by patients or their families are a key healthcare financing mechanism in Bangladesh that leads to economic burdens for households. The objective of this study was to identify whether and to what extent socioeconomic, demographic, and behavioral factors of the population had an impact on OOP expenditures in Bangladesh. Methods: A total of 12 400 patients who had paid to receive any type of healthcare services within the previous 30 days were analyzed from the Bangladesh Household Income and Expenditure Survey data, 2010. We employed regression analysis for identify factors influencing OOP health expenditures using the ordinary least square method. Results: The mean total OOP healthcare expenditures was US dollar (USD) 27.66; while, the cost of medicines (USD 16.98) was the highest cost driver (61% of total OOP healthcare expenditure). In addition, this study identified age, sex, marital status, place of residence, and family wealth as significant factors associated with higher OOP healthcare expenditures. In contrary, unemployment and not receiving financial social benefits were inversely associated with OOP expenditures. Conclusions: The findings of this study can help decision-makers by clarifying the determinants of OOP, discussing the mechanisms driving these determinants, and there by underscoring the need to develop policy options for building stronger financial protection mechanisms. The government should consider devoting more resources to providing free or subsidized care. In parallel with government action, the development of other prudential and sustainable risk-pooling mechanisms may help attract enthusiastic subscribers to community-based health insurance schemes.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.206-222
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• 1997

The conventional analysis with which justifies government intervention of the private sector's innovation activities is the market failure approach. According to such analysis, fund allocation through autonomous market mechanisms is not optimal in technology financing because of the disparity between the desirable level of investment for society as a whole and that for private firms. To optimize the fund allocation, public policies such as subsidy, preferencial loan and venture capital investment programs are designed for technology development projects performed by private firms. They, however, have not been effective in increasing private investment for such projects. In most cases, it was found that little considerations given to the relationship between uncertainty embodied in technology development projects and each types of financing. With respect to optimizing fund allocation, technology development projects should be financed by different means according to their probability of success and the expected value of technology. Employing various theoretical models on financing decision-making we verify here that technology development projects to be supported by commercial banks or venture capital institutions is limited contingent upon levels of uncertainty adn expected value. Under the assumption that financial institutions are risk averse, loan or investment can be available only if the probability of success of the project is higher than the probability premium and the current market rate of interest. Therefore, the projects that have lower probability of success and/or small expected return are excluded from commercial loan or investment programs. However, the remaining projects, whose probability of success is low but with high expected return, may be applied under government subsidy programs. To achieve optimality of fund allocation and to activate technology financing, we conclude that there should be a systematic division of role among financial institutions including government commercial banks, and venture capital institutions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.151-157
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• 2021

This paper deals with financing an early retirement scheme problem(FERSP) with minimum initial cash and filling up maximum financial interest. For this problem, Guéret et al. programming the Mosel, and Edvall merely realize the CPLEX Branch-and-Cut MIP Solver program to get the optimal solution. But there is no clear rule to finding the solution. This paper suggests calculation formula of bond number decision-making that the reverse from long arrival due date to short. Then we optimize and confirm the bonds number in accordance with continuative effect of the arrival due date. The shortage prepare with the principal and interest of one year deposit(saving) reversely calculation formula.

• Korean Journal of Social Welfare
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• v.57 no.1
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• pp.5-30
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• 2005

This article attempts to restructurize the current arguments on how to change the method of financing child care programme, which is currently under discussion in Korea. There has been a series of changes in Korean child care policy, such as the amendment of Child Care Act, the transition of its responsible administrations, adoption the child care policy as a national agenda. In these changes, new needs for child care financing method comes out with a new direction of child care policy and a plan of expansion of finances. That's the transition from 'facility-centered subsidy' to 'child-centered subsidy'. This article redefine it as the arguments about 'supply-side subsidy' vs. 'demand-side subsidy'. To analyse the different traits of two branches of arguments, this article reviews the social welfare models, and has come to the conclusion that the Burchardt's model is appropriate to explain the financing debates. Thus, the analysis the traits of the two perspectives is based on three dimensions i. e. service provision, financing and decision making according to the Burchardt's model. This also examines how the two sides is connected to the discussion of publicity and quality improvement of child care service. Through this approaches and analysis, this helps us restructurize the debates on the method of financing from the present superficial arguments.

• Journal of Preventive Medicine and Public Health
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• v.51 no.2
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• pp.83-91
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• 2018

Objectives: One of the main objectives of the Targeted Subsidies Law (TSL) in Iran was to improve equity in healthcare financing. This study aimed at measuring the effects of the TSL, which was implemented in Iran in 2010, on equity in healthcare financing. Methods: Segmented regression analysis was applied to assess the effects of TSL implementation on the Gini and Kakwani indices of outcome variables in Iranian households. Data for the years 1977-2014 were retrieved from formal databases. Changes in the levels and trends of the outcome variables before and after TSL implementation were assessed using Stata version 13. Results: In the 33 years before the implementation of the TSL, the Gini index decreased from 0.401 to 0.381. The Gini index and its intercept significantly decreased to 0.362 (p<0.001) 5 years after the implementation of the TSL. There was no statistically significant change in the gross domestic product or inflation rate after TSL implementation. The Kakwani index significantly increased from -0.020 to 0.007 (p<0.001) before the implementation of the TSL, while we observed no statistically significant change (p=0.81) in the Kakwani index after TSL implementation. Conclusions: The TSL reform, which was introduced as part of an economic development plan in Iran in 2010, led to a significant reduction in households' income inequality. However, the TSL did not significantly affect equity in healthcare financing. Hence, while measuring the long-term impact of TSL is paramount, healthcare decision-makers need to consider the efficacy of the TSL in order to develop plans for achieving the desired equity in healthcare financing.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.825-836
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• 2003

Based on customer information and financing processes in capital market, we derived individual models by applying multi-layered perceptrons, MDA, and decision tree. Further, the results from the existing single models were compared with the results from the integrated model that was developed using genetic algorithm. This study contributes not only to verifying the existing individual models and but also to overcoming the limitations of the existing approaches. We have depended upon the approaches that compare individual models and search for the best-fit model. However, this study presents a methodology to build an integrated data mining model using genetic algorithm.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.127-137
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• 2014

Project Financing (PF) development project is the type which influences national economy and building industry largely because it is exerted by using borrowed money from many kinds of investors and huge amount of financial raising. Many domestic PF projects are focused mainly on the profit maximization lacking in a sufficient feasibility study. Nowadays many projects are suspending due to the global finance debacle and stagnation of real estate industry. Therefore, in this paper, risk factors of PF project are deducted and Key Success Factors (KSFs) are derived through Factor-Analysis and qualified using Fuzzy-AHP method. And through the evaluation of the derived success factors in real projects, a strong correlationship has been identified between the score of each PF success factor and the level of success and/or expected rate of return (ROR). So, the result of this paper can help decision makers of the PF projects make a better decision and give a meaningful guidance in achieving successful PF projects.

• Journal of Technology Innovation
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• v.28 no.1
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• pp.31-52
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• 2020

This study was started to verify the preliminary(Ex-ante) discrimination power of the firm's high-activity using the 'Forward-looking' oriented technology appraisal model used in technology financing. The analytical firms are classified into the industry (manufacturing / non-manufacturing) and the age of company (initial / non-initial). High-activity SMEs are defined as those that achieve at least twice the average asset turnover ratio of the cluster. As a result of the discriminant model by applying C5.0 method, which is one of decision tree models, classification accuracy is more than 99% in all industries and the age of company, and it is confirmed that the discriminant power of the model is stable. As a result, the management expertise, capital involvement and funding capacity items were identified as a critical variable for the high-activity SMEs. In addition, the technology management capability and technology life cycle were also confirmed to be the items to determine high-activity SMEs in the manufacturing industry. Through this, it was possible to confirm some possibility of prior discrimination and policy utilization of high-activity SMEs by using technology appraisal items.

• Korean Journal of Construction Engineering and Management
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• v.7 no.1 s.29
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• pp.100-109
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• 2006

Feasibility analysis is a crucial key to success or failure of housing project. Existing feasibility analysis in construction company is based on intuitive approach rather than systematic approach. Usually feasibility analysis in a narrow sense is a financial analysis of project. Feasibility analysis focused in this study is confined to the matter of finance. So, the purpose of this study is to analyze the sensitivity of financial analysis item about profit rate by means of monte carlo simulation and this will improve accuracy of feasibility analysis and decision making.