Application of Logistic Regression Analysis to Household Debt of Bangkok and Metropolitan Area of Thailand

Intarapak, Sukanya; Supapakorn, Thidaporn

doi:10.37394/23207.2020.17.65

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…In Thailand, Chounlakorn and Kittichotipanit (2016) reported that for civil servants specifically general officials, three common factors including number of family members, capability of making installed payments, and the cost of living affected household debt. Likewise, Intarapak and Supapakorn (2020) highlighted that for households in Bangkok and the surrounding metropolitan area, variables such as household size, number of people who get wages, remittance receiving, and loan for emergency influenced household debt.…”

Section: Discussionmentioning

confidence: 99%

“…Whilst Lerskullawat (2020) highlighted that social factors as well as economic factors including household income and household expenditure played a key role in determining the household debt burden. Similarly, Intarapak and Supapakorn (2020) found that household size, number of people earning wages, remittance receiving, and loan for emergency affected the level of household debt.…”

Section: Introductionmentioning

confidence: 94%

“…Furthermore, household size has also been found to have a positive effect on household debt levels with larger households demanding more debt (Giordana and Ziegelmeyer (2017); Haq et al (2018); Togba (2012)). For Thailand, Chounlakorn and Kittichotipanit (2016) and Intarapak and Supapakorn (2020) highlighted that multiple factors including number of family members affect the indebtedness level of the household. In addition, for household debt in the form of household mortgage, Xiao and Yao (2011) reported that married couples and families with children were more likely to have mortgages, car loans or credit card debt.…”

Section: Empirical Evidencementioning

confidence: 99%

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Household characteristics of indebted households with members working in the public and private sector

Niwatananun

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The research analyzed the influence of different household characteristics on household debt, including mortgage debt. Using data from Thailand's Household Socio-Economic Survey in 2019 and 2021, the study implemented a logit model to identify household characteristics with significant impact on household debt. By analyzing data from two different periods that varied in social and economic contexts, the study highlighted critical factors that influenced household debt demand. The datasets were divided into three categories according to household work status. The categories include households with at least one public sector worker, households with no public sector workers but at least one private sector worker, and all other households. The study found that, in 2019 and 2021, different household characteristics, such as work status, location, and education attainment, influenced the households' likelihood of having debt at varying levels of significance and direction. The household work status was a significant and positive factor regarding the probability of having household debt as well as household mortgage demand in all categories of household work statuses. When looking at other factors, the study discovered that households' location, number of children, average household compensation, government loan schemes, and medical welfare services significantly increased the probability of household debt in both years, while the highest household education attainment level significantly decreased the probability of household debt. At the same time, the study highlighted that number of children, average household compensation, and medical welfare services significantly increased household mortgage demand. However, households' location, highest household education attainment level, and government loan schemes decreased the likelihood of household mortgages significantly. In addition, household assets had a significant influence on the likelihood of household debt and household mortgage, but this differed by factor and year.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 94%

Section: Empirical Evidencementioning

confidence: 99%

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Household characteristics of indebted households with members working in the public and private sector

Niwatananun

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A Dynamic Evolutionary Game Model of Collaborative Innovation in Manufacturing Services Industry and Manufacturing Industry

Liu

2021

International Journal of Circuits, Systems and Signal Processing

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Collaborative innovation has a significant impact on the efficiency of manufacturing services and manufacturing innovation. In this paper, a collaborative innovation model of manufacturing services and manufacturing is constructed based on the two-dimensional asymmetric evolutionary game basic model. The stable evolution strategy of the model is to be found through the solutions to the replicator dynamic differential equation of both sides of the game. The results show that on the one hand, producer services can rely on the carrier of knowledge capital and human capital to link to the manufacturing process from front to back, and form the forward and backward spillover effect. On the other hand, the knowledge elements in producer services, especially tacit knowledge, are transmitted through the modern network under the common industrial culture atmosphere in the process of continuous industrial interaction and industrial integration, which can promote the sharing and transfer of knowledge, produce interactive innovation, and finally promote the innovation of value chain.

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An Entropy Weight Method of Collaborative Degree Model Between Producer Service Industry and Manufacturing Industry

Liu

2021

International Journal of Circuits, Systems and Signal Processing

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In order to study the coupling coordination relationship, the equipment manufacturing industry has been taken as the example to develop the evaluation index system of producer services and equipment manufacturing industry through employing the entropy weighting method. The relationship between them has been verified in the whole country. The research results show that there is a symbiotic relationship between the producer services and the equipment manufacturing industry. Both of them are mutually promoted and symbiotically developed. The unbalanced economic development in all regions of China is dominated by the synergy degree difference of both sides, which provides the guidance for the regional economic development in our country.

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Application of Logistic Regression Analysis to Household Debt of Bangkok and Metropolitan Area of Thailand

Cited by 5 publications

References 6 publications

Household characteristics of indebted households with members working in the public and private sector

Household characteristics of indebted households with members working in the public and private sector

A Dynamic Evolutionary Game Model of Collaborative Innovation in Manufacturing Services Industry and Manufacturing Industry

An Entropy Weight Method of Collaborative Degree Model Between Producer Service Industry and Manufacturing Industry

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