nep-fle New Economics Papers
on Financial Literacy and Education
Issue of 2019‒10‒21
three papers chosen by

  1. Behind the success of dominated personal pension plans: sales force and financial literacy factors By Francesca Arnaboldi, Francesca Gioia
  2. Behind the success of dominated personal pension plans: sales force and financial literacy factors By Giuseppe Marotta
  3. Markovian model for granting credit in microfinance By Philibert Andriamanantena; Issouf Abdou; Mamy Raoul Ravelomanana; Rivo Rakotozafy

  1. By: Francesca Arnaboldi, Francesca Gioia
    Abstract: This paper analyzes the role of newborn gender in households’ investment decisions. The results indicate that newborn gender is a significant predictor of both the real-location of financial wealth across different types of financial assets and households’investment diversification. Parenting a new baby boy is associated with a higher real-location of wealth towards cash while the share of financial wealth allocated to risky assets decreases. A new baby boy also significantly reduces the magnitude of portfo-lio diversification. We find no evidence that the relationship between newborn gender and investment allocation is driven by third variables that simultaneously affect gender and financial decisions. The relationship between newborn gender and the financial decision is particularly relevant to disentangle unconscious gender bias in households’investment decisions.
    Keywords: Investment choice, Investment decision, Household savings, Gender, Newborns
    JEL: G11 D14
    Date: 2019–10
  2. By: Giuseppe Marotta
    Abstract: The revealed preference for dominated insurance-based personal pension plans in Italy is a decade-long puzzle. I surmise that a motivation from the supply side is a sales force factor deriving from the geographical distribution of financial providers, including the countrywide network of the state controlled Post Office. I provide supporting evidence using three biennial waves of the Bank of Italy’s survey on household finances from 2010 to 2014. The time interval includes a public pension system reform sharply raising the statutory age retirement, legislated in December 2011 to defuse a sovereign debt crisis. I show that the salience effect on the awareness of the benefits of supplementing lower perspective public pensions with personal pension plans strengthened the explanatory power of financial strength indicators. Exploiting a module in the 2010 wave I estimate a surprising decrease in the probability of subscription to personal pension plans in 2014 associated to the indicator for the highest financial literacy level.
    Keywords: Pensions, Private pension systems, Retail financial products distribution, Italy
    JEL: D91 E21 G11 H55
    Date: 2019–10
  3. 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

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