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Field
Abstract
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Before
In low income countries, overweight and obesity are more widespread among rich individuals. In contexts where income information is limited, high body mass might be exploited as signal of wealth. In this project I study how individuals' body mass affects their chance of accessing credit via a survey experiment in Uganda. Respondents are loan officers from a random subsample of licensed money lending institutions from the metropolitan area of Kampala, the capital. Loan officers are a key step in the process of accessing credit: They screen prospective clients, verify their information and upon verification, determine whether applicants qualify for the selected loan.
In the survey experiment, loan officers evaluate multiple hypothetical loan applications. Following Kessler et al. (WP 2019), truthful answers are incentivised by providing real referrals. In the applications, I randomise body mass of hypothetical applicants, and evaluate how this affects loan officers' evaluations. My measure of access to credit are the loan officer’s 1) choice of meeting the hypothetical applicant; 2) likelihood of qualifying the loan application; 3) charged interest rate. Furthermore, to investigate the mechanism at play, I elicit 4) assessment of the applicant’s creditworthiness and 5) assessment of the applicants' ability to put the loan to productive use.
Loan officers evaluate in total 30 hypothetical applications, which are split into three treatment arms, which vary how much and in which way information on the applicant is presented (within-subject design). The three arms allow to pin down the mechanism at play, by allowing to understand at which point of the decision making process does the discrimination bites.
This set up allows to (1) test whether body mass affects perceived creditworthiness and access to credit, (2) test whether reducing asymmetric information on income changes the relevance of body mass in determining the decision, and (3) understand at which, if any, step of the decision making process does the discrimination bites.
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After
In low income countries, overweight and obesity are more widespread among rich individuals. In contexts where income information is limited, high body mass might be exploited as signal of wealth. In this project I study how individuals' body mass affects their chance of accessing credit via a survey experiment in Uganda. Respondents are loan officers from a random subsample of licensed money lending institutions from the metropolitan area of Kampala, the capital. Loan officers are a key step in the process of accessing credit: They screen prospective clients, verify their information and upon verification, determine whether applicants qualify for the selected loan.
In the survey experiment, loan officers evaluate multiple hypothetical loan applications. As in the IRR paradigm by Kessler et al. (WP 2019), truthful answers are incentivised by providing real referrals. In the applications, I randomise body mass of hypothetical applicants, and evaluate how this affects loan officers' evaluations. My measure of access to credit are the loan officer’s 1) choice of meeting the hypothetical applicant; 2) likelihood of qualifying the loan application; 3) charged interest rate. Furthermore, to investigate the mechanism at play, I elicit 4) assessment of the applicant’s creditworthiness and 5) assessment of the applicants' ability to put the loan to productive use.
Loan officers evaluate in total 30 hypothetical applications, which are split into three treatment arms, which vary how much and in which way information on the applicant is presented (within-subject design). The three arms allow to pin down the mechanism at play, by allowing to understand at which point of the decision making process does the discrimination bites.
This set up allows to (1) test whether body mass affects perceived creditworthiness and access to credit, (2) test whether reducing asymmetric information on income changes the relevance of body mass in determining the decision, and (3) understand at which, if any, step of the decision making process does the discrimination bites.
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Field
Planned Number of Clusters
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Before
minimum/expected 250 loan officers.
The sample size is obtained as follows. The set of institutions is obtained by randomly selecting 250 branches in Kampala, Mukono and Wakiso, stratifying by bank tier and location. Notably, commercial banks are excluded from the randomisation, as they are unlikely to lend as little as low as Ush. 1 million. Each selected branch is visited to ask whether they will be willing to participate to the study. If they agree, 1 to 2 loan officers are interviewed, until exhaustion of the list. The target loan officers number is 250 loan officers. If the 250 branches interview fail to reach the target number, we will perform a second randomisation among the remaining branches.
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After
minimum/expected 250 loan officers.
The sample size is obtained as follows. The set of institutions is obtained by randomly selecting 250 branches in Kampala, Mukono and Wakiso, stratifying by bank tier and location. Notably, commercial banks are excluded from the randomisation, as they are unlikely to lend as little as low as Ush. 1 million. Each selected branch is visited to ask whether they will be willing to participate to the study. If they agree, first it is verified that the institution offers both personal and business loans; second, it is verified that the institution offers as little as Ush. 1 million loans. If these conditions are met, 1 to 2 loan officers are interviewed depending on availability. The procedure continues until exhaustion of the list. The target loan officers number is 250 loan officers. If the 250 branches interview fail to reach the target number, we will perform a second randomisation among the remaining branches.
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