Rational Herding toward the Poor: Evidence from Location Decisions of Microfinance Institutions within Pakistan
Analyzing the geographical location of almost all the microfinance institutions (MFIs) within Pakistan, this paper gives further evidence that microfinance activities do not reach the poorest rural areas. Especially, we explore how this result is driven by the uncertainty faced by MFIs in their loca...
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description | Analyzing the geographical location of almost all the microfinance institutions (MFIs) within Pakistan, this paper gives further evidence that microfinance activities do not reach the poorest rural areas. Especially, we explore how this result is driven by the uncertainty faced by MFIs in their location decision i.e., they can hardly predict accurately whether or not they will perform financially. Furthermore, we find that MFIs are spatially clustered and identify three main reasons for this: common attraction factors i.e., the characteristics of one area fits to the preferences of all MFIs so that they are all located in the same areas; payoff externalities to be collocated; and herd behavior, i.e., MFIs follow one another. Most importantly, we find that a significant part of this herding process is rational, i.e., early locations of MFIs convey information used by later ones such that it reverses or neutralizes the negative impact of uncertainty resulting then in more locations in needier areas. Since it allows them to be located in poorer areas, MFIs improve the achievement of their social goal. This latter result is rather good news for those who reckon that a better access to financial services enhances economic growth and fosters poverty alleviation. Indeed, rational herding constitutes an endogenous moderator effect to the big issue that financial services penetration is too weak in the poorest rural areas. |
doi_str_mv | 10.1016/j.worlddev.2016.02.004 |
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Especially, we explore how this result is driven by the uncertainty faced by MFIs in their location decision i.e., they can hardly predict accurately whether or not they will perform financially. Furthermore, we find that MFIs are spatially clustered and identify three main reasons for this: common attraction factors i.e., the characteristics of one area fits to the preferences of all MFIs so that they are all located in the same areas; payoff externalities to be collocated; and herd behavior, i.e., MFIs follow one another. Most importantly, we find that a significant part of this herding process is rational, i.e., early locations of MFIs convey information used by later ones such that it reverses or neutralizes the negative impact of uncertainty resulting then in more locations in needier areas. Since it allows them to be located in poorer areas, MFIs improve the achievement of their social goal. This latter result is rather good news for those who reckon that a better access to financial services enhances economic growth and fosters poverty alleviation. 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Especially, we explore how this result is driven by the uncertainty faced by MFIs in their location decision i.e., they can hardly predict accurately whether or not they will perform financially. Furthermore, we find that MFIs are spatially clustered and identify three main reasons for this: common attraction factors i.e., the characteristics of one area fits to the preferences of all MFIs so that they are all located in the same areas; payoff externalities to be collocated; and herd behavior, i.e., MFIs follow one another. Most importantly, we find that a significant part of this herding process is rational, i.e., early locations of MFIs convey information used by later ones such that it reverses or neutralizes the negative impact of uncertainty resulting then in more locations in needier areas. Since it allows them to be located in poorer areas, MFIs improve the achievement of their social goal. 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Indeed, rational herding constitutes an endogenous moderator effect to the big issue that financial services penetration is too weak in the poorest rural areas.</description><subject>Antipoverty programs</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Economic development</subject><subject>Economic growth</subject><subject>Economics and Finance</subject><subject>Externalities</subject><subject>Finance</subject><subject>Financial services</subject><subject>Geographical distribution</subject><subject>Geography</subject><subject>Herding</subject><subject>Humanities and Social Sciences</subject><subject>Location</subject><subject>Location analysis</subject><subject>location decisions</subject><subject>Low income groups</subject><subject>Microfinance</subject><subject>microfinance institutions</subject><subject>Neutrality</subject><subject>panel Poisson regression</subject><subject>Place preferences</subject><subject>Poverty</subject><subject>rational herding</subject><subject>Rural areas</subject><subject>Studies</subject><subject>Uncertainty</subject><issn>0305-750X</issn><issn>1873-5991</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNqFkUtvEzEUhS0EEqHwF5AlNrCY4fo1zrCiKoVUCqJCVOrOcvwgDpNxazuJ-Pd4EtoFG1a2r79zdHUOQq8JtARI937THmIarHX7ltZ3C7QF4E_QjMwla0Tfk6doBgxEIwXcPkcvct4AgGC9nKH4XZcQRz3ghUs2jD9xiQedLC5rh69jTB_w5T5YNxqHfYpbvIzmqMCfnAm5XjKOHn8NJkUfRj1xV2MuoezK8fMQyjqM-Fr_Crno8SV65vWQ3au_5xm6-Xz542LRLL99ubo4XzZGkL40K9mvVt4ww9ncdwDM6Z4LL7q5F9quhHVMUi4IeE4loVJw0VHjjNfUWN05dobenXzXelB3KWx1-q2iDmpxvlTTDAjrKAW6J5V9e2LvUrzfuVzUNmTjhkGPLu6yIrKHvpOc04q--QfdxF2q8R0pwsScS1ap7kTVUHJOzj9uQEBNnamNeuhMTZ0poKp2VoUfT0JXo9kHl1Q2YcrehuRMUTaG_1n8AQWso-I</recordid><startdate>20160801</startdate><enddate>20160801</enddate><creator>Monne, Jérôme</creator><creator>Louche, Céline</creator><creator>Villa, Christophe</creator><general>Elsevier Ltd</general><general>Pergamon Press Inc</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TQ</scope><scope>7U6</scope><scope>8BJ</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>SOI</scope><scope>1XC</scope><scope>BXJBU</scope><scope>IHQJB</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-6500-1862</orcidid></search><sort><creationdate>20160801</creationdate><title>Rational Herding toward the Poor: Evidence from Location Decisions of Microfinance Institutions within Pakistan</title><author>Monne, Jérôme ; Louche, Céline ; Villa, Christophe</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c519t-b79bbfc3c438f6003ea945f568f5adb5de3724510f42712754562cecfa2cda6e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Antipoverty programs</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Economic development</topic><topic>Economic growth</topic><topic>Economics and Finance</topic><topic>Externalities</topic><topic>Finance</topic><topic>Financial services</topic><topic>Geographical distribution</topic><topic>Geography</topic><topic>Herding</topic><topic>Humanities and Social Sciences</topic><topic>Location</topic><topic>Location analysis</topic><topic>location decisions</topic><topic>Low income groups</topic><topic>Microfinance</topic><topic>microfinance institutions</topic><topic>Neutrality</topic><topic>panel Poisson regression</topic><topic>Place preferences</topic><topic>Poverty</topic><topic>rational herding</topic><topic>Rural areas</topic><topic>Studies</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Monne, Jérôme</creatorcontrib><creatorcontrib>Louche, Céline</creatorcontrib><creatorcontrib>Villa, Christophe</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>PAIS Index</collection><collection>Sustainability Science Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Environment Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>HAL-SHS: Archive ouverte en Sciences de l'Homme et de la Société</collection><collection>HAL-SHS: Archive ouverte en Sciences de l'Homme et de la Société (Open Access)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>World development</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Monne, Jérôme</au><au>Louche, Céline</au><au>Villa, Christophe</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rational Herding toward the Poor: Evidence from Location Decisions of Microfinance Institutions within Pakistan</atitle><jtitle>World development</jtitle><date>2016-08-01</date><risdate>2016</risdate><volume>84</volume><spage>266</spage><epage>281</epage><pages>266-281</pages><issn>0305-750X</issn><eissn>1873-5991</eissn><coden>WODEDW</coden><abstract>Analyzing the geographical location of almost all the microfinance institutions (MFIs) within Pakistan, this paper gives further evidence that microfinance activities do not reach the poorest rural areas. Especially, we explore how this result is driven by the uncertainty faced by MFIs in their location decision i.e., they can hardly predict accurately whether or not they will perform financially. Furthermore, we find that MFIs are spatially clustered and identify three main reasons for this: common attraction factors i.e., the characteristics of one area fits to the preferences of all MFIs so that they are all located in the same areas; payoff externalities to be collocated; and herd behavior, i.e., MFIs follow one another. Most importantly, we find that a significant part of this herding process is rational, i.e., early locations of MFIs convey information used by later ones such that it reverses or neutralizes the negative impact of uncertainty resulting then in more locations in needier areas. Since it allows them to be located in poorer areas, MFIs improve the achievement of their social goal. 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subjects | Antipoverty programs Decision analysis Decision making Economic development Economic growth Economics and Finance Externalities Finance Financial services Geographical distribution Geography Herding Humanities and Social Sciences Location Location analysis location decisions Low income groups Microfinance microfinance institutions Neutrality panel Poisson regression Place preferences Poverty rational herding Rural areas Studies Uncertainty |
title | Rational Herding toward the Poor: Evidence from Location Decisions of Microfinance Institutions within Pakistan |
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