2019
DOI: 10.1111/rode.12589
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Is the model “loans‐plus‐savings” better for microfinance in Eastern Europe and Central Asia? A propensity score matching comparison

Abstract: Microfinance institutions are gradually evolving into multiservice organizations offering not only loans but also savings, and other financial and nonfinancial services. We contribute to the literature aimed at identifying how combining credit with savings affects outreach and sustainability in microfinance institutions (MFIs). We apply the propensity score matching method as well as its augmented dose-response version to compare the performance of loans-plus-savings MFIs with that of lending-only in a sample … Show more

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Cited by 13 publications
(3 citation statements)
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“…When estimating the impact of a binary treatment variable on a count variable, researchers have used propensity score matching (PSM) (Caliendo and Kopeinig 2008 ; Abadie and Imbens 2016 ; Khachatryan et al 2019 ), the inverse-probability-weighted regression adjustment (IPWRA) estimator (Manda et al 2018 ; Liu et al 2019 ; Zheng and Ma 2021b ), Poisson regression with endogenous treatment effects (PRETE) (Miranda and Rabe-Hesketh 2006 ; Bratti and Miranda 2011 ), and endogenous switching regression for count-dependent variables (henceforth, ESC model) (Hasebe 2020 ). Among them, PSM and IPWRA are nonparametric approaches that address only the selection bias from observed factors.…”
Section: Econometric Modelmentioning
confidence: 99%
“…When estimating the impact of a binary treatment variable on a count variable, researchers have used propensity score matching (PSM) (Caliendo and Kopeinig 2008 ; Abadie and Imbens 2016 ; Khachatryan et al 2019 ), the inverse-probability-weighted regression adjustment (IPWRA) estimator (Manda et al 2018 ; Liu et al 2019 ; Zheng and Ma 2021b ), Poisson regression with endogenous treatment effects (PRETE) (Miranda and Rabe-Hesketh 2006 ; Bratti and Miranda 2011 ), and endogenous switching regression for count-dependent variables (henceforth, ESC model) (Hasebe 2020 ). Among them, PSM and IPWRA are nonparametric approaches that address only the selection bias from observed factors.…”
Section: Econometric Modelmentioning
confidence: 99%
“…So, results are coherent to basic theoretical frame and rejected but hypothesis is rejected as stated by literature and has supported its generic concept. Thus, results comprehended that as efficiency of a MFI rises the capital structure is positively affected and supports operational & financing activities of institutions [61], [62].…”
Section: Conclusion and Policy Implicationsmentioning
confidence: 87%
“…Finances created through savings are used for lending. Thus, microfinance helps to mobilize savings (Khachatryan and Vardan Baghdasaryan Valentina Hartarska, 2019).…”
Section: Introductionmentioning
confidence: 99%