• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.291-301
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• 2020

Purpose - The purpose of this study was to investigate several household characteristics related to panel attrition, examining how they may have conditioned the panel data in the Korea Welfare Panel Study (KOWEPS). Design/methodology/approach - We studied the cause of the differences in household income between the original panel and the new panel in KOWEPS. Findings - To summarize our findings, whereas it is highly likely that a low-income household or a household without health insurance will remain in the panel, it is highly likely that a high-income household or a household of more than three members will be taken off the panel. Research implications or Originality - The proportion of low-income household tends to decrease over the years, which appears to result from an overall increase in household income. Such changes are reflected in the pattern in which older panels have higher estimates of household income than newer panels.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.769-782
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• 2020

Interest in fruit and vegetables has increased due to changes in consumer consumption patterns, socioeconomic status, and family structure. This study determined the factors influencing the demand for fruit and vegetables (strawberries, paprika, tomatoes and cherry tomatoes) using a panel of Rural Development Administration household-level purchases from 2010 to 2018 and compared the ability to the prediction performance. An artificial neural network model was constructed, linking household characteristics with final food expenditure. Comparing the analysis results of the artificial neural network with the results of the panel model showed that the artificial neural network accurately predicted the pattern of the consumer panel data rather than the fixed effect model. In addition, the prediction for strawberries was found to be heavily affected by the number of families, retail places and income, while the prediction for paprika was largely affected by income, age and retail conditions. In the case of the prediction for tomatoes, they were greatly affected by age, income and place of purchase, and the prediction for cherry tomatoes was found to be affected by age, number of families and retail conditions. Therefore, a more accurate analysis of the consumer consumption pattern was possible through the artificial neural network model, which could be used as basic data for decision making.

• Korean Journal of Organic Agriculture
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• v.22 no.4
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• pp.611-628
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• 2014

This study probed into some characteristics of the urban household such as household income, number of the household, age distribution of the family members, their characteristics of shopping behavior such as the shopping place, types of the packaging and the characteristics of the time series, using consumer panel data of the Rural Development Administration (RDA). It further examined how the above factors affect fruit purchasing prices and then estimates the degree of the influence by each factor. The study looked at the purchase of apples, pears, tangerines, and oranges - the most favorite fruits in Korea. The results of this study can be utilized as the basic information for marketing strategies and/or for the establishment of future policy plans related to fruits consumption.

• Journal of Families and Better Life
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• v.17 no.4
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• pp.193-206
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• 1999

This study analyzed the household portfolio according to wealth levels using a survey data of 1997 Korea Household Panel Study. The major findings of this study are as follows: (1) A household in high wealth level has invested relatively large proportion of his asset into real estate (2) A household in middle wealth level has invested relatively large proportion of his asset into risky financial asset(3) A household in low wealth level has invested relatively large proportion of his asset into secure financial asset. These findings accorded with risky pyramid model.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.7-20
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• 2012

The objective of this paper is to construct pseudo-panel data set and estimate price and income elasticities of car travel demand, using 1995-2007 household income and expenditure survey data, in order to provide quantitative information for analyzing related policy effects in the transport sector. We categorized household survey data into 14 cohorts based on the birth year of the household head. As the result, a total of 133 pseudo-panel data sets was created for estimating price and income elasticities of car travel demand. Especially, price and income elasticities of car travel demand were separately estimated both short-term and long-term. We analyzed the panel model considering fixed effect within cohorts, using explanatory variables such as previous year's fuel consumption, real household income after tax, education level of the household head, the number of children under five, and the share of household type averaged by cohorts. As results, the short-term and long-term price elasticities of car travel demand were calculated as 0.2974-0.4280 and 0.4087-0.6275, respectively. Similarly, the short-term and long-term income elasticities were calculated as 0.3364-0.6281 and 0.7098, respectively.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.3
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• pp.149-156
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• 2004

This paper deals with the effective protection method for the household electric appliances against lightning surges invading from the Power lines. Direct or induced lightning is the main cause of the breakdown of household electric appliance. The most effective protection method is to install SPDs(surge protective devices) at household electric appliances. If SPDs were not installed at most household electric appliances, it is necessary to install SPDs on the mains. Therefore the propagation aspect and protection methods of lighting surges coming into household electric appliances through the mains was experimentally investigated. The in actual-sized test circuits results of protection method for 8 household electric appliances including computer monitors and TV set could be summarized as follows: The breakdown characteristics of household electric appliances from lightning surges were significantly changed with the their input impedance. Namely, the types of input impedance are classified into infinite, resistive or inductive impedances. Especially, the monitor for computer with inductive input impedance from lightning surges was relatively weak against lightning surges. It was confirmed that the self inductance of branch circuits on the mains have protection effect for household electric appliances against lightning surges invading from the power lines. Also the varistors installed at cabinet panel or circuit-breaker were more effective than multi-tap outlet with varistors. When installed varistors in cabinet panel and multi-tap outlet together, the surge protection effect is much more excellent in technical and economical aspects.

• Journal of the Korean Home Economics Association
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• v.38 no.2
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• pp.65-77
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• 2000

This study investigated the effect of socio-demographic variables and the ownership of asset and the other types of debts on the use of a specific type of household debt. Household debts were categorized into six types according to borrowing sources: debts from banks, other financial institutes, employers, private sources, Gye, and retailers. The 1996 Korean Household Panel Study were analyzed using logistic model. It was found that socio-demographic factors influenced differently on the probabilities of debt holdings according to the types of debt. There were interrelationships among the ownerships of a specific type of debt and other types of debt and asset.

• Survey Research
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• v.12 no.2
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• pp.89-112
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• 2011

This study shows the results of constructing panel data using Farm Household survey and presents some examples of empirical application. This study shows that ex post constructed panel data using repeated cross-sectional survey can be used in various dynamic analyses. This paper also shows that the well known difficult problem of longitudinal weights can be easily solved by using the existing cross-sectional weights in original cross-section data. Based on these results, we propose that the National Statistical Office not only try to construct panel data, but also construct panel data by using existing repeated cross-section data. The benefits of this approach seems to be very big in establishment survey.

• Korean Journal of Social Welfare
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• v.62 no.1
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• pp.109-132
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• 2010

This study examined the effects of depression by household's economic factors with income levels using the wave 1, 2 of Korean Welfare Panel Study. As a result, changes in income satisfaction have significant effects on depression levels. In non-poor households, the income and comsumption expenditure have effects on depression levels. But poor households do not have any effects. Among the control variables, age, marital status, and education level are influential factors on the depression levels. Based on the results, the author was able to recognize the economic factors in household that influnce the depression levels. and The policy directios for household's economic support were discussed.

• Journal of Families and Better Life
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• v.22 no.2
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• pp.85-95
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• 2004

The purpose of this study was to classify the household financial strategies and find out variables affecting the type of the household financial strategies. The data of 3994 households from Korean Labor and Income Panel Study(1999-2000) were used. The major findings were as follows: (1) the household financial strategies were Residual Saver Type(44.6%), Unformal Institute Saver Type(13.3%), Financial asset Saver Type(16.7%), Real estate Saver Type(13.4%) and Diversities(12.0%). (2) The household financial strategy types were changed rapidly during short term. (3) In 3994 households, the variables which influence on the change of the household financial strategies were education, job, numbers of children, place of residence, home ownership. Similarly, in each type, the change of household financial strategies was significantly different according to the household characteristics variables.