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Lithuanian loan market evaluation

Grigaite, Kristina and Bezhanishvili, Tamar (2008)
Department of Economics
Abstract
We think much of a current consumption is strongly based on various types of loans every person should have an idea about how the loan approval mechanism works. Because everybody wants to know if they have a possibility of getting a loan approval, almost all banks’ web pages have a maximum loan calculator, which gives a client a maximum loan amount he/she could borrow at a current date given certain factors (e.g. income, age, place of living, etc.). However this calculator does not give an idea if the loan will be approved or not. We believe that this research will help a client get a better idea whether his/her loan will to be approved or not. To get a better picture of the bank lending decision process the client could make use of... (More)
We think much of a current consumption is strongly based on various types of loans every person should have an idea about how the loan approval mechanism works. Because everybody wants to know if they have a possibility of getting a loan approval, almost all banks’ web pages have a maximum loan calculator, which gives a client a maximum loan amount he/she could borrow at a current date given certain factors (e.g. income, age, place of living, etc.). However this calculator does not give an idea if the loan will be approved or not. We believe that this research will help a client get a better idea whether his/her loan will to be approved or not. To get a better picture of the bank lending decision process the client could make use of academic research. Unfortunately, empirical research of this type is quite rare. The main reason being that data are usually very difficult to obtain, as it contains personal information and the banks are not normally willing to disclose it
There are other studies that address this issue, Munnell A. H. et al (1996) wrote a paper about mortgage lending in Boston and studied whether belonging to a particular race affected a bank’s decision about loan approval. Ross L.S. (1996) analyzed the use of racial differences in loan default to test for mortgage loan discrimination. Stengel M. and Glennon D. (1999) tried to develop a bank specific model to study the mortgage lending discrimination. Black (1978), King (1980), Schafter and Ladd (1980) cited by Munnel (1996) have studied the probabilities of getting a mortgage loan if an applicant belonged to a certain minority. The problem is that these studies are concerned with the US, and they are concentrated on exploring the degree to which race, gender, age, religion or education level affects the possibility to get loan. We believe that these analyses are overly specific and are not relevant for Lithuanian society as the population in the country is mainly the same race and religion.
The objective of this paper is to determine what the main drivers of the decision about the loan approval are in Lithuanian banks. How do the Political, Economical, Social and Technological factors, i.e. the general environment of the country affect the decisions of the banks. (Less)
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author
Grigaite, Kristina and Bezhanishvili, Tamar
supervisor
organization
year
type
H1 - Master's Degree (One Year)
subject
keywords
evaluation, Lithuania, loan market, binary, pest, Economics, econometrics, economic theory, economic systems, economic policy, Nationalekonomi, ekonometri, ekonomisk teori, ekonomiska system, ekonomisk politik
language
English
id
1334619
date added to LUP
2008-06-07
date last changed
2010-08-03 10:51:46
@misc{1334619,
  abstract     = {We think much of a current consumption is strongly based on various types of loans every person should have an idea about how the loan approval mechanism works. Because everybody wants to know if they have a possibility of getting a loan approval, almost all banks’ web pages have a maximum loan calculator, which gives a client a maximum loan amount he/she could borrow at a current date given certain factors (e.g. income, age, place of living, etc.). However this calculator does not give an idea if the loan will be approved or not. We believe that this research will help a client get a better idea whether his/her loan will to be approved or not. To get a better picture of the bank lending decision process the client could make use of academic research. Unfortunately, empirical research of this type is quite rare. The main reason being that data are usually very difficult to obtain, as it contains personal information and the banks are not normally willing to disclose it
There are other studies that address this issue, Munnell A. H. et al (1996) wrote a paper about mortgage lending in Boston and studied whether belonging to a particular race affected a bank’s decision about loan approval. Ross L.S. (1996) analyzed the use of racial differences in loan default to test for mortgage loan discrimination. Stengel M. and Glennon D. (1999) tried to develop a bank specific model to study the mortgage lending discrimination. Black (1978), King (1980), Schafter and Ladd (1980) cited by Munnel (1996) have studied the probabilities of getting a mortgage loan if an applicant belonged to a certain minority. The problem is that these studies are concerned with the US, and they are concentrated on exploring the degree to which race, gender, age, religion or education level affects the possibility to get loan. We believe that these analyses are overly specific and are not relevant for Lithuanian society as the population in the country is mainly the same race and religion.
The objective of this paper is to determine what the main drivers of the decision about the loan approval are in Lithuanian banks. How do the Political, Economical, Social and Technological factors, i.e. the general environment of the country affect the decisions of the banks.},
  author       = {Grigaite, Kristina and Bezhanishvili, Tamar},
  keyword      = {evaluation,Lithuania,loan market,binary,pest,Economics, econometrics, economic theory, economic systems, economic policy,Nationalekonomi, ekonometri, ekonomisk teori, ekonomiska system, ekonomisk politik},
  language     = {eng},
  note         = {Student Paper},
  title        = {Lithuanian loan market evaluation},
  year         = {2008},
}