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Access to Formal Credit and Gender Income Gap: The Case of Farmers in Cambodia

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  • SAM, Vichet

Abstract

This article analyzes the factors that drive the gender income difference among farmers in Cambodia with a focus on the access to formal credit, using the FinScope survey data. First, an Ordinary Least Square regression (OLS) is used to investigate the main determinants of farmers’ income, while an instrumental variable approach (IV) is estimated to check the causal effect of the access to formal credit on earnings. Next, the Blinder-Oaxaca technique is employed to decompose the gender earnings gap. Results from OLS regression show that individual education and health, farm size and other inputs, irrigation system and weather conditions, access to market and formal credit are strongly associated with farmers’ earnings, while the positive impact of access to formal credit is also confirmed by the IV regression at 5% significant level. These results suggest that improving infrastructure and formal credit access in the rural areas play a critical role in increasing farmers’ income. Then, based on the Blinder-Oaxaca decomposition technique, most of gender earnings difference is due to the endowment effect in favor of male farmers such as education, farm size and volume of work hours. Access to formal credit also contributes to the gender earnings gap, yet not in terms of endowment but coefficient effect, as a higher return to credit access for male farmers is observed. This could be due to the levels of education and financial literacy that are higher for men, allowing them to use the formal credit better. Closing the gap in education and financial literacy would therefore reduce their earnings gap. Discrimination against female farmers, not in terms of credit access, but in loan amount should be worth to consider as well, as the median of loan amounts of male farmers is higher than those of female. If such discrimination exists, it could also limit the women’s capacity to manage and invest in their farms effectively, and thus, the return to credit access must be lower for female farmers.

Suggested Citation

  • SAM, Vichet, 2019. "Access to Formal Credit and Gender Income Gap: The Case of Farmers in Cambodia," MPRA Paper 97052, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:97052
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    References listed on IDEAS

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    1. Fletschner, Diana, 2009. "Rural Women's Access to Credit: Market Imperfections and Intrahousehold Dynamics," World Development, Elsevier, vol. 37(3), pages 618-631, March.
    2. Donna Gilleskie & Denise Hoffman, 2014. "Health Capital and Human Capital as Explanations for Health-Related Wage Disparities," Journal of Human Capital, University of Chicago Press, vol. 8(3), pages 235-279.
    3. SAM, Vichet, 2019. "Formal Financial Inclusion in Cambodia: What are the Key Barriers and Determinants?," MPRA Paper 94000, University Library of Munich, Germany.
    4. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    5. Doris Weichselbaumer & Rudolf Winter‐Ebmer, 2005. "A Meta‐Analysis of the International Gender Wage Gap," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 479-511, July.
    6. Seema Jayachandran, 2015. "The Roots of Gender Inequality in Developing Countries," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 63-88, August.
    7. Ali, Daniel & Bowen, Derick & Deininger, Klaus & Duponchel, Marguerite, 2016. "Investigating the Gender Gap in Agricultural Productivity: Evidence from Uganda," World Development, Elsevier, vol. 87(C), pages 152-170.
    8. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    9. Chun, Hyunbae & Lee, Injae, 2001. "Why Do Married Men Earn More: Productivity or Marriage Selection?," Economic Inquiry, Western Economic Association International, vol. 39(2), pages 307-319, April.
    10. Huynh, Phu., 2016. "Assessing the gender pay gap in Asia's garment sector," ILO Working Papers 994904713402676, International Labour Organization.
    11. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    12. Sara Horrell & Pramila Krishnan, 2007. "Poverty and productivity in female-headed households in Zimbabwe," Journal of Development Studies, Taylor & Francis Journals, vol. 43(8), pages 1351-1380.
    13. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    14. Akter, Sonia & Rutsaert, Pieter & Luis, Joyce & Htwe, Nyo Me & San, Su Su & Raharjo, Budi & Pustika, Arlyna, 2017. "Women’s empowerment and gender equity in agriculture: A different perspective from Southeast Asia," Food Policy, Elsevier, vol. 69(C), pages 270-279.
    15. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    16. Fengxia Dong & Jing Lu & Allen M. Featherstone, 2012. "Effects of credit constraints on household productivity in rural China," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(3), pages 402-415, November.
    17. Florent Kinkingninhoun-Mêdagbé & Aliou Diagne & Franklin Simtowe & Afiavi Agboh-Noameshie & Patrice Adégbola, 2010. "Gender discrimination and its impact on income, productivity, and technical efficiency: evidence from Benin," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 27(1), pages 57-69, March.
    18. Adams, Renée & Almeida, Heitor & Ferreira, Daniel, 2009. "Understanding the relationship between founder-CEOs and firm performance," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 136-150, January.
    19. Diagne, Aliou & Zeller, Manfred, 2001. "Access to credit and its impact on welfare in Malawi:," Research reports 116, International Food Policy Research Institute (IFPRI).
    20. Un, B. & Pech, S. & Baran, E., 2015. "Aquatic agricultural systems in Cambodia: National situation analysis," Monographs, The WorldFish Center, number 40548, April.
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    Cited by:

    1. Punlork Men & Lyda Hok & Panchit Seeniang & B. Jan Middendorf & Rapee Dokmaithes, 2024. "Identifying Credit Accessibility Mechanisms for Conservation Agriculture Farmers in Cambodia," Agriculture, MDPI, vol. 14(6), pages 1-26, June.

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    More about this item

    Keywords

    J16; J31; J43; J71;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J43 - Labor and Demographic Economics - - Particular Labor Markets - - - Agricultural Labor Markets
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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