2011
DOI: 10.1016/j.asieco.2011.01.004
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Accessibility to microcredit by Chinese rural households

Abstract: This paper examines key factors influencing the accessibility of microcredit by rural households in China. The empirical approach is built upon logistic regression and data are collected through a household survey. A total of twelve household-level factors are identified as determinants in households' access to microcredit and the results indicate that households' accessibility to microcredit can also be impaired by the supply-side factors. The paper concludes that households should increase credit demand to e… Show more

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Cited by 100 publications
(125 citation statements)
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“…These results are in line with those of previous studies. The fact that credit targets the poorest has not previously been described in a number of published studies (Amin et al, 2003;Coleman, 2006;Ghalib, 2011;Li et al, 2011;Milan, 2012). Also, evidence of Dufhues and Buchenrieder (2005) indicated that the poorest are seldom clients of credit.…”
Section: Poverty Targeting Of Microcreditmentioning
confidence: 98%
See 1 more Smart Citation
“…These results are in line with those of previous studies. The fact that credit targets the poorest has not previously been described in a number of published studies (Amin et al, 2003;Coleman, 2006;Ghalib, 2011;Li et al, 2011;Milan, 2012). Also, evidence of Dufhues and Buchenrieder (2005) indicated that the poorest are seldom clients of credit.…”
Section: Poverty Targeting Of Microcreditmentioning
confidence: 98%
“…Among welfare indicators, household income and expenditure seem to be the most appropriate indicators (Li et al, 2011;Wetterberg, 2007). Obviously, household outcome is not only influenced by credit access but also by other endowments.…”
Section: Impact Of Microcredit On Household Income and Expenditurementioning
confidence: 99%
“…In addition to credit variable, the explanatory variables used for predicting borrowing status or calculating propensity score are presented in the upper part of Table 1. These variables are selected on the basis of previous empirical studies (Yinger, 1998;Duong and Izumida, 2002;Li et al, 2011;Khoi et al, 2013;Duong and Thanh, 2015). The outcome variables arealso shown in the bottom part of Table 1.…”
Section: Selection Of Variablesmentioning
confidence: 99%
“…From this equation, we can estimate the probability of access to credit or propensity score of each household. Based on the previous empirical studies by Yinger (1998;Duong and Izumida, 2002;Li et al, 2011;Khoi et al, 2013), this research includes in the model the factors presented in Table 1.…”
Section: Estimation Strategymentioning
confidence: 99%
“…The chemical composition, morphology, mineralogy, organic carbon, heavy metal content were determined using XRF (Kanadasan & Abdul Razak 2015), FESEM (Karim et al 2017), XRD (Karim et al 2016), TOC analyzer (Karim et al 2017) and ICP-MS (Singh & Kalamdhad 2013), respectively, in previous studies. Heavy metals mobility and bioavailability depend strongly on their chemical composition and mineralogical form (Li et al 2011). The leach ability of heavy metals from POC depend on the bonding force of trace element in its matrix.…”
Section: Introductionmentioning
confidence: 99%