nep-mfd New Economics Papers
on Microfinance
Issue of 2019‒10‒21
two papers chosen by
Olivier Dagnelie
Université de Caen

  1. Markovian model for granting credit in microfinance By Philibert Andriamanantena; Issouf Abdou; Mamy Raoul Ravelomanana; Rivo Rakotozafy
  2. Technology Adoption and Access to Credit via Mobile Phones By Gupta, Apoorv; Ponticelli, Jacopo; Tesei, Andrea

  1. By: Philibert Andriamanantena (Université de Fianarantsoa [Fianarantsoa]); Issouf Abdou (Université des Comores); Mamy Raoul Ravelomanana (Faculté des Sciences - Université d'Antananarivo - Université d'Antananarivo); Rivo Rakotozafy (Université de Fianarantsoa [Fianarantsoa])
    Abstract: ABSTRACT. Starting from the generalized model of Osman Khodr and Francine Diener [1], we present a new model that meets the expectations of the microfinance institution (MFI) and that of the borrowers and that incorporates all the characteristics of the poor, namely tolerance in case of partial default and the possibility of having a progressive loan automatically. This model will provide microfinance institutions with a decision support tool that is better adapted to the reality of microfinance. Our Markov chain consists of several statements associated with the economic status of the borrower including three types of recipients B 1 (state of being beneficiary at a time t = 0), B 2 (state to be beneficiary at a time t = 1) and I (state of financial inclusion: permanent beneficiary), an applicant state A 1 and A T −1 ((T − 1) excluded states). We modeled a borrower's behavior by a λ parameter that depends on the borrower's α probability of success. At the initial time, λ = 1+α 1−α , this quantity changes as soon as the borrower moves from one state to another with a probability of success different from α. The agency's decision to grant a credit depends entirely on the λ parameter which is compared to the set subjective threshold-values. The chance γ to have a loan (γ: probability of credit request granted) for a borrower depends on the parameter λ, with γ = 1 − 1 λ. keywords: Microfinance, Credit Grant Decision, Markov Chain, Individual Loan, Dynamic Incentive, Updated Expected Profit
    Abstract: En partant du modèle généralisé de Osman Khodr et Francine Diener [1], nous présentons un nouveau modèle qui répond aux attentes de l'institution de microfinance (IMF) et celle des emprunteurs et qui incorpore toutes les caracté-ristiques des populations pauvres, à savoir la tolérance en cas de défaut partiel et la possibilité d'avoir un prêt progressif de façon automatique. Ce modèle offrira aux institutions de microfinance un outil d'aide à la décision plus adapté à la réalité de la microfinance. Notre chaîne de Markov comprend plusieurs états associés à la situation économique de l'emprunteur dont trois types de bénéficiaires B 1 (état d'être bénéficiaire au temps t = 0), B 2 (état d'être bénéficiaire au temps t = 1) et I (état d'inclusion financière: bénéficiaire permanent), un état de demandeur A 1 et A T −1 ((T − 1) états d'exclus). Nous avons modélisé le comportement d'un emprunteur par un paramètre λ qui dépend de la probabilité α de réussite de l'emprunteur. A l'instant initial, λ = 1+α 1−α , cette quantité change dès que l'emprunteur passe d'un état à un autre avec une probabilité de réussite différente de α. La décision de l'agence d'accorder un crédit dépend entièrement du paramètre λ qui est comparé aux valeurs-seuils subjectives fixées. La chance γ d'avoir un prêt (γ: probabilité de demande de crédit accordée) pour un emprunteur est fonction du paramètre λ, avec γ = 1 − 1 λ. MOTS-CLÉS : Microfinance, Décision d'octroi de crédit, chaîne de Markov, Prêt individuel, Incitation dynamique, Profit espéré actualisé
    Date: 2019–10–01
  2. By: Gupta, Apoorv; Ponticelli, Jacopo; Tesei, Andrea
    Abstract: Farmers in developing countries often lack access to timely and reliable information about modern technologies that are essential to improve agricultural productivity. The recent diffusion of mobile phones has the potential to overcome these barriers by making information available to those previously unconnected. In this paper we study the effect of mobile phone network expansion in rural India on adoption of high yielding variety seeds and chemical fertilizers. Our empirical strategy exploits geographical variation in the construction of mobile phone towers under a large government program targeting areas without existing coverage. To explore the role of mobile phones in mitigating information frictions we analyze the content of 1.4 million phone calls made by farmers to a major call center for agricultural advice. Farmers seek advice on which seed varieties and fertilizers better meet their needs and how to use them. We find that areas receiving mobile phone coverage experience higher adoption of these technologies. We also observe that farmers are often unaware of the eligibility criteria and loan terms offered by subsidized credit programs. Consistently, we find that areas receiving mobile phone coverage experience higher take-up of agricultural credit.
    Keywords: agriculture; Credit Card; HYV Seeds; India
    JEL: E51 G21 Q16
    Date: 2019–08

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