|
on Microfinance |
| By: | Renaud Bourlès (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, IUF - Institut Universitaire de France - M.E.N.E.S.R. - Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche); Anastasia Cozarenco (CERMi - Centre for European Research in Microfinance, MRM - Montpellier Research in Management - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier); Dominique Henriet (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique); Xavier Joutard (LEST - Laboratoire d'économie et de sociologie du travail - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique, OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po) |
| Abstract: | In the microfinance sector, experienced lenders enjoy an information advantage over first-time entrepreneurs. Our study proposes an analysis of the business training provided on a par with microloans and its potential effect on borrowers'behavior. First, we present a simple theoretical mechanism showing that an information advantage concerning borrower risk can lead to a non-monotonic relationship between risk and business training provision. Second, using a hand-collected data set of loan applications to a French MFI, we empirically examine the relationship between business training provision and borrower risk, controlling for selection bias and endogeneity. The collected evidence supports the existence of a non-monotonic relationship and shows that business training significantly increases the survival time of loans. Our results are robust to alternative econometric models. |
| Keywords: | Business training, Microcredit, Informed lender |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-03934370&r=mfd |
| By: | Yuehao Bai; Liang Jiang; Joseph P. Romano; Azeem M. Shaikh; Yichong Zhang |
| Abstract: | This paper studies inference on the average treatment effect in experiments in which treatment status is determined according to "matched pairs" and it is additionally desired to adjust for observed, baseline covariates to gain further precision. By a "matched pairs" design, we mean that units are sampled i.i.d. from the population of interest, paired according to observed, baseline covariates and finally, within each pair, one unit is selected at random for treatment. Importantly, we presume that not all observed, baseline covariates are used in determining treatment assignment. We study a broad class of estimators based on a "doubly robust" moment condition that permits us to study estimators with both finite-dimensional and high-dimensional forms of covariate adjustment. We find that estimators with finite-dimensional, linear adjustments need not lead to improvements in precision relative to the unadjusted difference-in-means estimator. This phenomenon persists even if the adjustments are interacted with treatment; in fact, doing so leads to no changes in precision. However, gains in precision can be ensured by including fixed effects for each of the pairs. Indeed, we show that this adjustment is the "optimal" finite-dimensional, linear adjustment. We additionally study two estimators with high-dimensional forms of covariate adjustment based on the LASSO. For each such estimator, we show that it leads to improvements in precision relative to the unadjusted difference-in-means estimator and also provide conditions under which it leads to the "optimal" nonparametric, covariate adjustment. A simulation study confirms the practical relevance of our theoretical analysis, and the methods are employed to reanalyze data from an experiment using a "matched pairs" design to study the effect of macroinsurance on microenterprise. |
| Date: | 2023–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2302.04380&r=mfd |
| By: | Meg Adachi-Sato (Research Institute for Economics & Business Administration, Kobe University Faculty of Business Administration, JAPAN and Accountancy, Khon Kaen University, THAILAND); Osamu Sato (Department of Management, Tokyo University of Science, JAPAN) |
| Abstract: | This study examines how for-profit firms finance capital from investors through environmental, social, and governance (ESG) efforts. We examine a situation with two types of investors: socially responsible and for-profit investors. In this scenario, firms outnumber all investors in the market, and they must attract socially responsible investors to successfully obtain the capital they require. We show that when a firm makes a positive ESG investment, regulators aiming to promote ESG should encourage investors to prioritize ESG performance in their investment choices. Meanwhile, strengthening shareholders' rights or promoting corporate governance reform may not necessarily be ideal for them. |
| Keywords: | ESG; Matching intensity; Search; Social impact; Socially responsible investors |
| JEL: | D83 G23 G32 M14 |
| Date: | 2023–02 |
| URL: | http://d.repec.org/n?u=RePEc:kob:dpaper:dp2023-03&r=mfd |