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An Impact Estimator Using Propensity Score Matching: People’s Business Credit Program to Micro Entrepreneurs in Indonesia

Author

Listed:
  • Farida Farida

    (Faculty of Economics, Persada YAI University, Jakarta, Indonesia.)

  • Hermanto Siregar

    (Department of Economics, Bogor Agricultural University, Bogor, Indonesia.)

  • Nunung Nuryartono

    (Department of Economics, Bogor Agricultural University, Bogor, Indonesia)

  • Eka Intan K.P

    (Department of Resource and Enviromental Economics, Bogor Agricultural University, Bogor, Indonesia.)

Abstract

People’s business credit program (KUR) has been launched to alleviate poverty through provision of micro financing to micro entrepreneurs in Indonesia This study aims to estimate the impact of KUR program using cross-sectional data and propensity score matching technique (PSM). The survey was conducted on 332 household entrepreneurs, consisting of 155 KUR receivers and 177 non-KUR receivers. Results show that KUR has impacts on increasing profits, total revenues, number of employees, and asset ownerships. KUR program also has impacted on reduction of food spending share. As such, KUR can play an important role to alleviate poverty and unemployment.

Suggested Citation

  • Farida Farida & Hermanto Siregar & Nunung Nuryartono & Eka Intan K.P, 2016. "An Impact Estimator Using Propensity Score Matching: People’s Business Credit Program to Micro Entrepreneurs in Indonesia," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 20(4), pages 599-615, Autumn.
    • Handle: RePEc:eut:journl:v:20:y:2016:i:4:p:599
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    References listed on IDEAS

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    1. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    2. Shahidur R. Khandker, 2005. "Microfinance and Poverty: Evidence Using Panel Data from Bangladesh," The World Bank Economic Review, World Bank, vol. 19(2), pages 263-286.
    3. Berhane, Guush & Gardebroek, Cornelius, 2012. "Assessing the long-term impact of microcredit on rural poverty: Does the timing and length of participation matter?," ESSP working papers 43, International Food Policy Research Institute (IFPRI).
    4. Abhijit Banerjee & Esther Duflo & Rachel Glennerster & Cynthia Kinnan, 2015. "The Miracle of Microfinance? Evidence from a Randomized Evaluation," American Economic Journal: Applied Economics, American Economic Association, vol. 7(1), pages 22-53, January.
    5. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    6. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
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    Cited by:

    1. Iman Widhiyanto & Nunung Nuryartono & Harianto Harianto & Hermanto Siregar, 2018. "The Analysis of Farmers' Financial Literacy and its' Impact on Microcredit Accessibility with Interest Subsidy on Agricultural Sector," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 148-159.
    2. Ali Raza & Guangji Tong & Furqan Sikandar & Vasilii Erokhin & Zhang Tong, 2023. "Financial Literacy and Credit Accessibility of Rice Farmers in Pakistan: Analysis for Central Punjab and Khyber Pakhtunkhwa Regions," Sustainability, MDPI, vol. 15(4), pages 1-24, February.

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