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          <name>Title</name>
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              <text>Impact of Mahatma Gandhi National Rural Employment Guarantee Act on Rural Credit System in India: A Standard Logit Difference in Difference Approach</text>
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              <text>Credit structure; Difference in difference; Formal and informal loan; MGNREGA; Panel data</text>
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              <text>The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) of India is one of the most extensive social safety nets programs in the developing world. The initiative attempts to enhance rural livelihoods in India by lowering rural poor vulnerability and misery. The programs nature and extent of execution vary from state to state. Using panel data sets from the Indian Human Development Survey (IHDS), which covering India for two waves, 200405 and 201112. We used a quasi-experimental approach, such as the difference-in-difference technique of effect evaluation, to quantify the programs influence on rural families credit and debt structures. The empirical analysis shows evidence of changing the behavior of taking loans from formal sources among non-poor households actively participating in the MGNREGA program. But the difference-in-difference results shows that among poor households participating in the MGNREGA scheme, the tendency to depend on formal sources to take loans is still insignificant. That means informal lending sources are still more prevalent among poor people. This tendency has not changed even after the initiation of this program. The article finishes with policy recommendations for successfully targeting the program, notably the social safety net benefits to disadvantaged households in India.  2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.</text>
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              <text>Kumar N.; Maya K.</text>
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              <text>Global Social Welfare</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/s40609-023-00282-x" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s40609-023-00282-x&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158926228&amp;amp;doi=10.1007%2Fs40609-023-00282-x&amp;amp;partnerID=40&amp;amp;md5=86fab323ca151122701e620232ceb014" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158926228&amp;amp;doi=10.1007%2fs40609-023-00282-x&amp;amp;partnerID=40&amp;amp;md5=86fab323ca151122701e620232ceb014&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 21968799</text>
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              <text>Online</text>
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              <text>Kumar N., Department of Econometrics, University of Madras, Tamil Nadu, Chennai, 600005, India; Maya K., Department of Economics, Christ (Deemed to Be) University, Karnataka, Bengaluru, 560076, India</text>
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