What determine the interest rates in China’s informal market?

Yuan, Ying; Xu, Lihe

doi:10.1080/14765284.2013.814459

Cited by 9 publications

(5 citation statements)

References 13 publications

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“…Households apply for loans from informal sources because they either fear rejection by the bank considering their request or their loan applications have been rejected by formal credit sources [6]. This finding is consistent with the studies of Turvey et al [32], Yuan and Xu [14,55], higher rates of informal borrowing is a consequence of credit rationing from formal credit sources. As a consequence, informal credit is likely to be more active in the regions where the formal credit market is less developed, such as in rural areas [14,32].…”

Section: Determinants Of Informal Borrowingsupporting

confidence: 82%

Credit Constraints on Farm Household Welfare in Rural China: Evidence from Fujian Province

et al. 2019

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This study investigates the effect of demographic factors on formal and informal borrowing households in rural Fujian Province. The study tests whether credit constraint affects rural farmers’ welfare in the studied region, using a probit regression and endogenous switching regression model to analyse data collected in 2017 from 960 farm households. Analysis shows that age, poverty, household size, and farmland size operate to constrain credit in formal borrowing. Results also indicate that level of education, farm land size and age have significant impacts on rural household borrowing from informal sources. The results from the endogenous switching model approach suggest that credit constraint does have a significant impact on rural farmers’ consumption and welfare in Fujian province.

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Section: Determinants Of Informal Borrowingsupporting

confidence: 82%

Credit Constraints on Farm Household Welfare in Rural China: Evidence from Fujian Province

et al. 2019

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“…The probability of a household being credit constrained in the formal credit sector has a positive impact on the household's access to informal credit. This can be construed as an indication that the informal credit sector provides a substitute for formal credit [39,40].…”

Section: Factors Affecting Credit Constraint From Formal Credit Sourcesmentioning

confidence: 99%

Rural Credit Constraint and Informal Rural Credit Accessibility in China

et al. 2019

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This paper investigates the effects of rural households’ demographic characteristics on formal credit constraint, and explores the relationship between informal and formal lending in rural China. Using 2013 China’s Household Finance survey data, the authors apply probit regression models to investigate the effects of demographic factors on formal credit constraint and the household’s decision to borrow from informal credit sources. In addition, the endogenous switching regression model is applied to evaluate the impact of credit constraint on the welfare of rural farm households. The empirical evidence confirms that age, family size, annual household nonagricultural income, level of education, and history of informal borrowing have significant influence over credit constraint. Moreover, annual household nonagricultural income, the presence of children, borrowing from social networks and monthly communication expenses significantly impact rural households’ decision to utilise informal borrowing. Results from the endogenous switching regression model suggest that credit constraint by formal credit sources has no impact on household consumption.

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“…The familiarity between a lender and his borrower, at high and medium levels, is shown to negatively affects the rates, which is consistent with Yuan and Xu (2013).…”

Section: Resultssupporting

confidence: 79%

“…Our dependent variable is the informal interest rates, while the key independent variables consist of the influence level of a lender, debt-to-income ratio (DTI), income level, stable income, and familiarity level. Our specific control variables are defined as in previous studies, such as Yuan and Xu (2013), and Siamwalla et al (1990).…”

Section: Data and Summary Statisticsmentioning

confidence: 99%

A Study Of Informal Loan In The Greater Bangkok Area: Fators Affecting Loan Decision And Interest Rate From The Demand Side

Tanomchat

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This thesis examines the likelihood of borrowing money from the informal credit market, the significant factors influencing the informal interest rates, and the factors which affect people?s decision on going back to rely on informal credit of individuals over 20+ years of age in four provinces, including Bangkok and Greater Bangkok, in Thailand. The survey uses a multi-stage stratified random sampling method by the weight of populations in each province for analysis with a quota sampling technique. The data used in the study is collected from 1,494 respondents by questionnaires. The results suggest that (i) luxury spending behavior, income levels, debt-to-income ratio, net monthly income, saving discipline, and the presence of monthly income and expense accounts are consistent with favorable decision-making for a loan from the informal credit market, (ii)? the study of correlation between the characteristics of the informal borrowers and the rates shows that the level of the lender?s influence and high levels of familiarity between the informal lenders and borrowers were found to be highly correlated with the interest rates. Moreover, the debt-to-income ratio also affects the rates, (iii) consistent saving, net monthly income, income payment on daily and weekly basis, installments, materialism, and impulsive buying behavior affect the likelihood of making repeated informal loans.

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What determine the interest rates in China’s informal market?

Cited by 9 publications

References 13 publications

Credit Constraints on Farm Household Welfare in Rural China: Evidence from Fujian Province

Credit Constraints on Farm Household Welfare in Rural China: Evidence from Fujian Province

Rural Credit Constraint and Informal Rural Credit Accessibility in China

A Study Of Informal Loan In The Greater Bangkok Area: Fators Affecting Loan Decision And Interest Rate From The Demand Side

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