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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 王泓仁(Hung-Jen Wang),陳南光(Nan-Kuang Chen) | |
dc.contributor.author | Clifford Tan Kuan Lu | en |
dc.contributor.author | 陳冠儒 | zh_TW |
dc.date.accessioned | 2021-05-19T17:51:37Z | - |
dc.date.available | 2027-12-31 | |
dc.date.available | 2021-05-19T17:51:37Z | - |
dc.date.copyright | 2017-08-08 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-08-07 | |
dc.identifier.citation | 1. Banerjee, A., Karlan, D., & Zinman, J. (2015). Six randomized evaluations of microcredit: Introduction and further steps. American Economic Journal: Applied Economics, 7(1), 1-21.
2. Banerjee, A. V., & Newman, A. F. (1993). Occupational choice and the process of development. Journal of Political Economy, 101(2), 274-298. 3. Chemin, M. (2008). The benefits and costs of microfinance: evidence from Bangladesh. The Journal of Development Studies, 44(4), 463-484. 4. Coleman, B. E. (1999). The impact of group lending in Northeast Thailand. Journal of Development Economics, 60(1), 105-141. 5. Coleman, B. E. (2006). Microfinance in Northeast Thailand: Who benefits and how much?. World Development, 34(9), 1612-1638. 6. Deaton, A. (2010). Instruments, Randomization, and Learning about Development. Journal of Economic Literature, 48, 424-455. 7. Duvendack, M., & Palmer-Jones, R. (2012). High noon for microfinance impact evaluations: re-investigating the evidence from Bangladesh. The Journal of Development Studies, 48(12), 1864-1880. 8. Heckmann, J., Ichimura, H., & Todd, P. (1997). Matching as an econometric evaluation estimator. Review of Economic Studies, 65(2), 261-294. 9. Imai, K. S., Gaiha, R., Thapa, G., & Annim, S. K. (2012). Microfinance and poverty—a macro perspective. World Development, 40(8), 1675-1689. 10. Islam, A. (2011). Medium-and long-term participation in microcredit: An evaluation using a new panel dataset from Bangladesh. American Journal of Agricultural Economics, 93(3), 847-866. 11. Kaboski, J. P., & Townsend, R. M. (2012). The impact of credit on village economies. American Economic Journal: Applied Economics, 4(2), 98-133. 12. Karlan, D., & Zinman, J. (2010). Expanding microenterprise credit access: Using randomized supply decisions to estimate the impacts in Manila. Innovations for Poverty Action working paper. 13. Khandker, S. R. (2005). Microfinance and poverty: Evidence using panel data from Bangladesh. The World Bank Economic Review, 19(2), 263-286. 14. Khandker, S. R., & Samad, H. A. (2013). Microfinance Growth and Poverty Reduction in Bangladesh: What Does the Longitudinal Data Say?. 15. Khandker, S. R., & Samad, H. A. (2016). Bangladesh’s Achievement in Poverty Reduction: The Role of Microfinance Revisited. 16. Duvendack, M., & Palmer-Jones, R. (2012). High noon for microfinance impact evaluations: re-investigating the evidence from Bangladesh. The Journal of Development Studies, 48(12), 1864-1880. 17. McKenzie, D., & Woodruff, C. (2008). Experimental evidence on returns to capital and access to finance in Mexico. The World Bank Economic Review, 22(3), 457-482. 18. Morduch, J. (1998). Does microfinance really help the poor? New evidence from flagship programmes in Bangladesh. Unpublished mimeo. 19. Morduch, J. (1999). The microfinance promise. Journal of Economic Literature, 37(4), 1569-1614. 20. Mushtaq, S., & Siddiqui, D. A. (2016). Effect of interest rate on economic performance: evidence from Islamic and non-Islamic economies. Financial Innovation, 2(1), 9. 21. Pitt, M. M., & Khandker, S. R. (1998). The impact of group-based credit programs on poor households in Bangladesh: Does the gender of participants matter?. Journal of Political Economy, 106(5), 958-996. 22. Porter, M. (2016). Effects of microcredit and other loans on female empowerment in Bangladesh: the borrower's gender influences intra‐household resource allocation. Agricultural Economics, 47(2), 235-245. 23. Roodman, D. (2012). Latest Impact Research: Inching Towards Generalization. CGAP blog, April, 11, 2012. 24. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. 25. Ting, H. L., Ao, C. K., & Lin, M. J. (2014). Television on women’s empowerment in India. The Journal of Development Studies, 50(11), 1523-1537. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7731 | - |
dc.description.abstract | 本研究探討孟加拉微型金融機構的農業貸款對農業家庭的影響。農業貸款理應用在農業用途,而使得農業家庭的生活品質由此提高。因此 ,農業貸款的效果分析至關重要。
我們以四種傾向評分匹配 (Propensity Score Matching) 技術進行實證分析,結果顯示,農業貸款有被善加利用在農業用途上。有農業貸款的農業家庭的勞動生產率、家庭人均農業自雇收入、家庭人均消費都有顯著提高。而有農業貸款的農業家庭的農業工資收入則下降。這顯示農業貸款也有助於鼓勵農業家庭自主創業,成為自僱農民。 | zh_TW |
dc.description.abstract | In this paper, we assess the effectiveness of micro-agri loans on agricultural outcomes of agricultural households in Bangladesh. Micro-agri loans refer to agricultural loans provided by microfinance institutions and they are supposed to be used for agricultural purposes. It is therefore vital to see whether these micro-agri loans have benefited agricultural households.
With the four different types of propensity score matching (PSM) techniques, our empirical results show that these agricultural loans are put into good use to improve agricultural outcomes of agricultural households. As a result of borrowing micro-agri loans, agricultural households enjoy higher total production value of crops, higher labor productivity, higher consumption expenditure per capita, higher agricultural self-employed income per capita, but lower agricultural employment income per capita. This shows that micro-agri loans also encourage agricultural households to be more self-employed in their agricultural production activities. | en |
dc.description.provenance | Made available in DSpace on 2021-05-19T17:51:37Z (GMT). No. of bitstreams: 1 ntu-106-R03323055-1.pdf: 1949624 bytes, checksum: b93596d6e813b3311b02237d0838fb8c (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | Contents
口試委員會審定書..............................................i 謝辭.........................................................ii 摘要........................................................iii Abstract.....................................................iv 1. Introduction..........................................1 2. Literature Review.....................................4 3. Data and Variables....................................7 4. Methodology: OLS and Propensity Score Matching.......17 5. OLS estimation results...............................20 6. PSM estimation Results...............................26 7. Conclusion...........................................33 References...................................................34 Appendix 1...................................................38 Appendix 2...................................................42 Appendix 3...................................................47 List of Figure and Tables Figure 1: Propensity score of both treated (borrow micro-agri loans) households and untreated (did not borrow any micro-agri loans) households............................................29 Table 1: Summary statistics of quantity of land owned by eligible and ineligible households...........................10 Table 2: Summary statistics of the six dependent variables...14 Table 3: Summary statistics of household’s control variables....................................................16 Table 4: OLS estimates of the impact of microagloan..........22 Table 5: OLS estimates of the impact of microagloa...........25 Table 6: Propensity score estimates: determinants of the probability of borrowing agricultural loans from microfinance institutions using logistic regression.......................27 Table 7: Comparison of OLS and PSM estimation results........31 | |
dc.language.iso | en | |
dc.title | 微型金融機構的農業貸款的效果分析–以孟加拉為例 | zh_TW |
dc.title | Assessment of the benefits of micro-agri loans: evidence from Bangladesh | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 張勝凱(Sheng-Kai Chang) | |
dc.subject.keyword | 微型金融,孟加拉,農作物總產值,勞動生產率,傾向評分匹配, | zh_TW |
dc.subject.keyword | Microfinance,Bangladesh,Total Production Value of Crops,Labor productivity,Propensity Score Matching, | en |
dc.relation.page | 47 | |
dc.identifier.doi | 10.6342/NTU201702598 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2017-08-07 | |
dc.contributor.author-college | 社會科學院 | zh_TW |
dc.contributor.author-dept | 經濟學研究所 | zh_TW |
dc.date.embargo-lift | 2027-12-31 | - |
顯示於系所單位: | 經濟學系 |
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