Marc Diener
Laboratoire Jean Dieudonné, Nice, France
Abstract:
Microcredit has been invented in the Indian subcontinent and is still getting more and more popular, even if facing a lot of critisism. I will explain how, in Nice, we understand this still unusual financial activity and the kind of elementary mathematical research we perform. We will begin with an example given by M. Yunus that shows that the expected interest rate in this example is 3% less than the admitted 20%. Then we will come up with a Markov chain model directly inspired by G. Tedeschi that can explain why a borrower prefers to pay what she owes. O. Khodr could then adress the question of modelling joint-lending. We will improve this model into Nahla Dhib’s model for improving the microcredit activity into a path to Inclusion (into the regular banking system). We will also present the result of P. Mauk’s research on Ahlin and Townsend’s data from Thailand on selecting parsimoniously variables for estimating the probability of default of a borrower that can’t produce a credit-history. If time allows we will describe Tedeschi’s statistical approach of impact assessment
Date: October 10, 2017
Time: 03:30 P.M.
Venue:
Conference Hall,
Indian Statistical Institute Delhi Centre,
7, S. J. S. Sansanwal Marg,
New Delhi-110016 (INDIA)
Location:
View Larger Map
Laboratoire Jean Dieudonné, Nice, France
Abstract:
Microcredit has been invented in the Indian subcontinent and is still getting more and more popular, even if facing a lot of critisism. I will explain how, in Nice, we understand this still unusual financial activity and the kind of elementary mathematical research we perform. We will begin with an example given by M. Yunus that shows that the expected interest rate in this example is 3% less than the admitted 20%. Then we will come up with a Markov chain model directly inspired by G. Tedeschi that can explain why a borrower prefers to pay what she owes. O. Khodr could then adress the question of modelling joint-lending. We will improve this model into Nahla Dhib’s model for improving the microcredit activity into a path to Inclusion (into the regular banking system). We will also present the result of P. Mauk’s research on Ahlin and Townsend’s data from Thailand on selecting parsimoniously variables for estimating the probability of default of a borrower that can’t produce a credit-history. If time allows we will describe Tedeschi’s statistical approach of impact assessment
Date: October 10, 2017
Time: 03:30 P.M.
Venue:
Conference Hall,
Indian Statistical Institute Delhi Centre,
7, S. J. S. Sansanwal Marg,
New Delhi-110016 (INDIA)
Location:
View Larger Map
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