Data and Code for: Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment

Principal Investigator(s): View help for Principal Investigator(s) Gharad Bryan, London School of Economics; Dean Karlan, Northwestern University; Adam Osman, University of Illinois

Version: View help for Version V1

Name	File Type	Size	Last Modified
Clean Data			05/24/2024 05:48:PM
Do Files			05/24/2024 05:49:PM
Output			05/24/2024 05:31:PM
Raw Data			05/24/2024 05:58:PM
Surveys			05/24/2024 05:59:PM
AER_READ ME.pdf	application/pdf	201.8 KB	05/24/2024 01:31:PM

Project Description

Summary: We experimentally study the impact of relatively large enterprise loans in Egypt. Larger loans generate small average impacts, but machine learning using psychometric data reveals that "top-performers" (those with the highest predicted treatment effects) substantially increase profits, while profits drop for poor-performers. The large differences imply that lender credit allocation decisions matter for aggregate income, yet we find that existing practice leads to substantial misallocation. We argue that some entrepreneurs are over-optimistic and squander the opportunities presented by larger loans by taking on too much risk, and show the promise of allocations based on entrepreneurial type relative to firm characteristics.

Scope of Project

Subject Terms: Randomized Experiment

JEL Classification:
      C93 Field Experiments
      D22 Firm Behavior: Empirical Analysis
      G32 Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
      L26 Entrepreneurship
      O12 Microeconomic Analyses of Economic Development

Geographic Coverage: Egypt

Universe: Approved loan applicants to "Tamouh" program at Alexandria Business Association

Data Type(s): administrative records data; experimental data; survey data

Collection Notes: Data collection received CAPMAS approval from government of Egypt.

Methodology

Response Rate: Overall response rate was 96%

Sampling: Applicants to a microfinance organization

Data Source: Collected by researchers, and lender administrative data

Collection Mode(s): face-to-face interview; other

Unit(s) of Observation: Individuals

Related Publications

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Published Versions

V1 [2024-07-30]

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DDI 2.5

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