• Health Policy and Management
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• v.12 no.2
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• pp.43-75
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• 2002

This study focuses on the factors that make the financial structure of hospitals in Korea different, and on recommended courses of action that could be very helpful to hospitals in maintaining a sound financial structure. Data used in this study were collected from 132 hospitals with complete general data of present conditions as well as financial statements. They were chosen from the 174 hospitals that passed the standardization audit undertaken by the Korean Hospital Association from 1996 to 2000 for the purpose of accrediting training hospitals. The dependent variable in this study is financial structure. It consists of liabilities as against total assets (total liabilities to total assets, short-term liabilities to total assets, long-term liabilities to total assets, short-term borrowings to total assets, long-term borrowings to total assets). The independent variables are ownership type, hospital type, location, whether or not a representative is a director of the hospital, the possibility of changing a hospital director, bed size, period of establishment, asset structure, profitability, growth, tax shields, business risk, competition. The factors that appear to have the strongest impact on the liabilities to total assets of all the hospitals sampled are ownership type, hospital type, profitability, tax shields, and business risk. It was found that not-for-profit private hospitals and for-profit private hospitals have more liabilities than public hospitals, and tertiary medical institutions have less liabilities than the secondary general hospitals. Moreover, hospitals earning more at the expense of high business risk have a distinct tendency to lower liabilities. Concerning the current ratio, it was found that factors such as ownership type, hospital type, period of establishment, asset structure, and business risk are the more significant variables. The current ratio of public hospitals is higher than that of both not-for-profit private hospitals and for-profit private hospitals, and the current ratio of tertiary medical institutions is higher than that of general hospitals. As business risk is higher in hospitals compared to other businesses, the current ratio becomes higher; this is because it is assumed that for fear of bankruptcy, hospitals lessen liabilities to total assets. On the other hand, as hospitals become older, the fixed assets to total assets become lower. It is remarkable that in hospitals, the factors affecting liabilities to total assets have an opposite regression coefficient sign against factors affecting current ratio. It brings out the same results borne out by the old financial theories and researches, in which a lot of the liabilities of hospitals are considered as the cause of worsening liquidity. Therefore, it is very important for hospitals to maintain a sound financial structure in order to survive using the rational acquisition and maintenance of capital.

• Journal of Family Resource Management and Policy Review
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• v.3 no.1
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• pp.67-82
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• 1999

The purpose of this study were to examine assets investment behavior of urban households and find the factors affecting it. The data were obtained from 442 households living in Seoul. The statistical techniques used for this study included descriptive statistecs, logistic regression, multiple regression. The major findings were as follows: First, The ownership of houehold assets were affected by age, education, total income, total income, total asset, the number of income source, income stability, the financial expectations, past financial experiences and the job of houehold head. Second, amount of household assets was affected by husband’s age, education, unearned income, total asset, income stability, the expectiation of future, the past financial experiences and the job of household head. Third, ratios of household assets were affected by age, education, unearned income, family size, the number of income source and the job of household head. The findings of this study can be used by financial counseling and planning practioners and education.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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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.

• International Journal of Contents
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• v.5 no.1
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• pp.37-45
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• 2009

This paper empirically tests pecking order theory. Korean listed firms are used as the samples. On the whole we find supportive results for pecking order theory. The fixed effect model on the whole period shows that as pecking order theory suggests that debt ratio decreases as cash flow. ROA, physical assets, and firm size increase. Again, it is shown that corporate debt ratio significantly decreases as cash flow or ROA increases in every sub-sample, which coincides with the prediction of pecking order theory. Corporate debt ratio significantly decreases as physical assets or jinn size increases in case of the whole sample, pre-financial crisis period, and the sub-samples by q-ratio, which also supports the prediction of pecking order theory. Statistical significance of the coefficients of physical assets or firm size completely disappears after Korean financial crisis. Perhaps it is because the role of physical assets or firm size as a mitigator of information asymmetry significantly weakens after the financial crisis as Korean financial market becomes more transparent. For small firms only size variable is negatively and significantly related with debt to assets. It seems that size is an important factor for smaller firms in making financing decision.

• Journal of the Korean Home Economics Association
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• v.41 no.1
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• pp.39-58
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• 2003

This study investigated the effects of the householder's age as a proxy for the family life cycle stage variable and the householder's occupation on the household financial structures. Household financial structures are analyzed by the components of two financial statements(the income and expense statement and the balance sheet statement) and selected financial ratios. The data came from the 1998 Korean Household Panel Study. It was found that the age profiles of household finances such as household income, expenditure, savings and consumption rate, financial assets, real assets and home ownership, debt and net worth usually vary according the householder's occupation. The ratios of debt repayment and the liquidity ratios also vary in part as age changes for each occupational group.

• Journal of Family Resource Management and Policy Review
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• v.16 no.4
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• pp.45-68
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• 2012

This study performed an analysis to determine if an individual can maintain the current consumption, in the case of a single retired elderly person's household using the accumulated assets. Assets are divided into three types, based on the behavioral economics life cycle hypothesis : financial assets, real assets excepting residential assets, and residential assets, and it is assumed that these assets were used on a step-by-step basis. Also, if the assets were sufficient, the maximum withdrawal amount was calculated. The results of the analysis are as follows. First, the monetary assets were sufficient to cover the cost of living for 2.7 years, 6.4 years by using the real assets of the non-occupied housing, and 26.3 years in the case of residential property. Second, in the case of preferentially using the financial assets, 4.4% of the sample households were able to cover the cost of living. Households that were not able to cover the cost of living used the next-stage assets, real assets of the non-occupied housing. Households that were not able to cover the cost of living by financial assets liquidated the real assets with the exception of residential assets and used these to cover the cost of living. A total of 4.8% of the households were able to maintain the current cost of living through the second stage and 25.5% supplemented their funds by using residential assets. That is to say, 35% of the sample households were able to maintain the current level of living by using their assets.

• Journal of Families and Better Life
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• v.22 no.6 s.72
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• pp.165-175
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• 2004

The purpose of this study was to classify the household financial strategies and investigate major determinants of the household financial strategies and financial performance. The data of 3,994 households is from the Korean Labor and Income Panel Stud?. The major findings were as follows. (1) The classified household financial strategies types were Residual ($44.6\%$), Informal Institutional ($13.3\%$), Financial Assets ($16.7\%$), Real Estate ($13.4\%$), and Diversified Portfolio ($12.0\%$). (2) The criteria of classification of the household financial strategies were relative, not absolute. (3) The household financial strategy types changed largely during a short period(1999-2000). (4) In all households, the variables that affected changes in household financial strategies were education, occupation, number of children, residential location and home ownership. (5) Households that employed a diversified portfolio strategy had the greatest financial performance (2,316,000 won net gain). (6) In all households, the variables that had the greatest influence on financial performance were the number of children, assets and debts. 1'he financial performance was significantly different according to changes in the household financial strategy.

• The Korean Journal of Financial Studies
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• v.3 no.2
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• pp.235-256
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• 1996

This paper studies evaluation of illiquid assets by using a consumption and investment model. In particular, the paper defines the marginal values of illiquid assets and shows how optimal consumption and investment policies are related to the marginal values. The general results are illustrated by two concrete examples.

• Journal of Family Resource Management and Policy Review
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• v.16 no.3
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• pp.153-176
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• 2012

This study gives an account of the state of baby-boomer households in regard to assets and liabilities utilizing the 2006 Household Asset Survey and the 2011 Survey of Household Finances. Using the data gathered from each year, this study examined the proportion of households who had each type of asset and liability, and the amount of them. This study also compared the amount of assets and liabilities of baby-boomer households with those of non baby-boomer households in 2006 and 2011 respectively. Finally, this study examined the amount of change and composition ratio of assets and liabilities of baby-boomer households between 2006 and 2011. Selected financial ratios were also presented for both years. Major findings are as follows. The average asset amount for baby-boomer households was approximately 296 million in 2006 and 392 million in 2011. Of total assets, 78% and 76.5% were real assets in 2006 and 2011 respectively. The average financial assets of 2006 baby-boomer households were approximately 66 thousand and the average amount of debt was 42 thousand. For 2011 baby-boomer households, the average amount of financial assets was 92 thousand and the average amount of debt was 73 thousand. Results from the 2011 survey showed that baby-boomer households had a significantly higher proportion of total assets, total debt, and net worth than non baby-boomer households. The proportion of savings, saving insurance, stocks, and mutual funds were significantly higher for baby-boomer households than non baby-boomer households in 2011. In regard to financial ratios, the emergency fund index and debt burden index were appropriate to the guidelines of asset quality, although the propensity to investment indexes were not.

• Journal of the Korean Home Economics Association
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• v.34 no.2
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• pp.201-215
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• 1996

The purpose of the study was to examine the effects of household characteristics to family savings. Family savings were defined in four ways such as monthly savings, average propensity to save, financial assets, and net financial assets. The household characteristics dealt with were family income, household size, number of earners, age, occupation, education, housing tenure, and urbanization. The data used in the study was Survey of Family Finance 1990. The main statistical method was multiple regression. Family income was found to the most important variable to determine four family saving variables holding other characteristics constant. Also, household size had significant negative effects on family savings. Two-earner households were found to have higher average propensity to save and less financial assets compared to single-earner households. Fro monthly savings and average propensity to save, the households with forties andfifties household head tended to be less than others, while financial assets tended to increase with the age of household head. Compared to salary earner households, blue-colored households had significantly lower average propensity to save, and the households with professionals had significantly higher financial assets. The college-graduated households tended to have less monthly savings than the elementary-graduated households. Also, the housing renters were found to have more monthly savings and higher average propensity to save, compared to the housing owners.