Households' Debts Among Rural and Agriculture-based Households in Indonesia

Abstract

Household debts reflect financial insecurity for households to maintain their standard of living because it reflects the financial commitment that must be paid to other parties. However, the share of debts among different household classes, especially among agriculture and rural households in Indonesia still needs to be discovered. This research investigates the distribution of households’ debts in rural areas in Indonesia by utilizing data from the Indonesian Family Life Survey (IFLS) Wave 5 (2014). This research shows that households in rural areas have lower average debts than those in urban areas. At the same time, households in rural areas outside Java Island have higher average debts than their counterparts in Java Island. Two significant contributors to households’ debts are household size and household head educational attainment, where both variables show a positive and significant effect. The government must focus on rural development, including agricultural-based households, creating small but financially strong households, and increasing food self-sufficiency.


Keywords: agriculture, debts, households, rural

References
[1] Otoritas Jasa Keuangan. “Survei Nasional Literasi dan Inklusi Keuangan (SNLIK),” 2019. [Online]. Available: https://www.ojk.go.id/id/berita-dankegiatan/ publikasi/Pages/Survei-Nasional-Literasi-dan-Inklusi-Keuangan-2019.aspx

[2] Hasan M, Noor T, Gao J, Usman M, Abedin MZ. Rural Consumers’ Financial Literacy and Access to FinTech Services. J Knowl Econ. 2022;:1–25.

[3] Oxford Policy Management L. “Understanding people’s use of financial services in Indonesia,” in “Survey on Financial Inclusion and Access,” 2017. [Online]. Available: file:///C:/Users/thoma/Downloads/SOFIA_Report_May_2017_low_res.pdf

[4] Eggertsson GB, Krugman P. Debt, deleveraging, and the liquidity trap: A Fisher- Minsky-Koo approach. Q J Econ. 2012;127(3):1469–513.

[5] Guerrieri V, Lorenzoni G, Prato M. Schumpeter Lecture 2019: Slow Household Deleveraging. J Eur Econ Assoc. 2020;18(6):2755–75.

[6] Samah BA, Shaffril HA, Hassan MS, Hassan MA, Ismail N. Contribution of information and communication technology in increasing agro-based entrepreneurs productivity in Malaysia. Journal of Agriculture and Social Sciences. 2009;5(3):93–8.

[7] Prinsloo JW. Household debt, wealth and saving. Quarterly Bulletin. 2002;63(78):290–6.

[8] Kumar Das A, Bezbaruah M. “Efficiency and imperfections of tilling machinery rental markets in the Brahmaputra Valley of eastern India,” Agricultural Economics Research Review, vol. 33, no. 347-2020-1413, 2020.

[9] Diagne A, Zeller M, Sharma M. “Empirical measurements of households’ access to credit and credit constraints in developing countries,” International Food Policy Research Institute. IFPRI; 2000.

[10] Mago S. Microfinance and poverty alleviation: an empirical reflection. The Journal of Asian Finance, Economics and Business. 2014;1(2):5–13.

[11] Nguyen HH, Nguyen NV. Factor affecting poverty and policy implication of poverty reduction: A case study for the Khmer ethnic people in Tra Vinh Province, Viet Nam. The Journal of Asian Finance, Economics and Business. 2019;6(1):315–9.

[12] Pienkhuntod A, Amornbunchornvei C, Nantharath P. Quantitative Analysis of Poverty Indicators: The Case of Khon Kaen Province, Thailand. The Journal of Asian Finance, Economics and Business. 2020;7(2):131–41.

[13] Senadjki A, Mohd S, Bahari Z, Hamat AF. Assets, risks and vulnerability to poverty traps: A study of Northern region of Malaysia. The Journal of Asian Finance, Economics and Business. 2017;4(4):5–15.

[14] Kumar A, Singh R, Jee S, Chand S, Tripathi G, Saroj S. “Dynamics of access to rural credit in India: patterns and determinants,” Agricultural Economics Research Review, vol. 28, no. 347-2016-17194, pp. 151-166, 2015.

[15] Pitt MM, Khandker SR. Credit programmes for the poor and seasonality in rural Bangladesh. J Dev Stud. 2002;39(2):1–24.

[16] F. Temesgen, H. Duguma, and C. Hailu, “Factors affecting credit use for rural farming at household level: evidence from small holder farmers’ of Toke-Kutaye district,” J Agric Econ Dev, vol. 7, no. 2, pp. 007-12, 2018.

[17] Santoso DB, Gan C. Microcredit accessibility in rural households: evidence from Indonesia. Economics and Finance in Indonesia. 2019;65(1):67–88.

[18] Morduch J. Between the state and the market: can informal insurance patch the safety net? World Bank Res Obs. 1999;14(2):187–207.

[19] Fanwell B. Determinant and characteristics of household demand for agricultural credit in Malawi. Journal of World Development. 2003;14:167–71.

[20] Rweyemamu D, Kimaro M. “Assessing micro-finance services in agricultural sector development,” International Food Policy Research Institute, 2015. [Online]. Available: https://agris.fao.org/agris-search/search.do?recordID=QB2015104151

[21] Gitaharie BY, Soelistianingsih L, Djutaharta T. Financial inclusion: Household access to credit in Indonesia. Competition and Cooperation in Economics and Business; 2018. pp. 309–19.

[22] Ha NT. An analysis of informal versus formal microfinance for the poor in Vietnam. The Vietnamese–Netherlands Master’s program in development economics. Volume 6. Class; 1999.

[23] Ha VT. “Determinants of Rural Households’ Borrowing from the Formal Financial Sector: A study of the rural credit market in Red river delta region,” Master of Arts in Economics of Development. Hanoi: Vietnam–Netherlands Project; 2001.

[24] Sierminska and T. J. L. I. S. L. Smeeding, “Measurement issues: equivalence scales, accounting framework and reference unit,” 2005.

[25] Atkinson AB, Rainwater L, Smeeding T. “Income Distribution in OECD Countries: The Evidence from the Luxembourg Income Study,” ed: Paris: OECD. Reprinted Atkinson, 1995.

[26] Clementi F, Gallegati M, Kaniadakis G. A generalized statistical model for the size distribution of wealth. J Stat Mech. 2012;2012(12):1–25.

[27] Abrevaya J, Dahl CM. The effects of birth inputs on birthweight: evidence from quantile estimation on panel data. J Bus Econ Stat. 2008;26(4):379–97.

[28] Coad A, Rao R. The firm-level employment effects of innovations in high-tech US manufacturing industries. J Evol Econ. 2011;21(2):255–83.

[29] Koenker R, Bassett G Jr. Regression quantiles. Econometrica. 1978;46(1):33–50.

[30] Soseco T. “Lessons from COVID-19: Small and Financially Strong Family,” Jurnal Kependudukan Indonesia, vol. Edisi Khusus Demografi dan COVID-19, Juli 2019, pp. 49-52, 2020, doi: https://doi.org/10.14203/jki.v0i0.577.

[31] Soseco T. Household Size, Education, and Household Wealth in Indonesia: Evidence from Quantile Regression. Jurnal Ekonomi Indonesia. 2021;10(3):281–97.

[32] Van Winkle Z, Monden C. Family Size and Parental Wealth: The Role of Family Transfers in Europe. Eur J Popul. 2022 Mar;38(3):401–28.

[33] S. Magri, “Italian households’ debt: determinants of demand and supply,” Bank of Italy, Economic Research and International Relations Area, 2002.

[34] Setargie S. Credit default risk and its determinants of microfinance industry in Ethiopia. Ethiopian Journal of Business and Economics (The). 2013;3(1):1–21.

[35] Nguyen HT, Nguyen HM, Troege M, Nguyen AT. Debt aversion, education, and credit self-rationing in SMEs. Small Bus Econ. 2021;57(3):1125–43.

[36] Haq W, Ismail NA, Satar NM. Household debt in different age cohorts: A multilevel study. Cogent Econ Finance. 2018;6(1):1455406.

[37] Soseco T, Hidayah I, Rini AD. “Gender Determinant on Multidimensional Poverty Index: Evidence from Indonesia,” Jurnal Ilmu Sosial dan Ilmu Politik, vol. 26, no. 2, pp. 137-151, 2022, https://doi.org/10.22146/jsp.69320.

[38] Soseco T. “Household Size and Household Wealth in Indonesia with the Influence of Spatial Aspects,” Economics and Finance in Indonesia, vol. 68, no. 2, pp. 75-86, 2022. [Online]. Available: https://scholarhub.ui.ac.id/efi/vol68/iss2/1

[39] Goode J. Brothers are doing it for themselves?: men’s experiences of getting into and getting out of debt. J Socio-Economics. 2012;41(3):327–35.

[40] Thorne D. Extreme financial strain: emergent chores, gender inequality and emotional distress. J Fam Econ Issues. 2010;31(2):185–97.

[41] Callegari J, Liedgren P, Kullberg C. Gendered debt–a scoping study review of research on debt acquisition and management in single and couple households. Eur J Soc Work. 2020;23(5):742–54.

[42] Nord M. Does it cost less to live in rural areas? Evidence from new data on food security and hunger. Rural Sociol. 2000;65(1):104–25.

[43] Aghion P, Caroli E, Garcia-Penalosa C. Inequality and economic growth: the perspective of the new growth theories. J Econ Lit. 1999;37(4):1615–60.

[44] Jia X, Heidhues F, Zeller M. Credit rationing of rural households in China. Agr Financ Rev. 2010;70(1):37–54.

[45] Warr PG. (2011). Food security vs. food self-sufficiency: The Indonesian case. Crawford School Research Paper, (2011/04).

[46] Mears LA. Rice and food self-sufficiency in Indonesia. Bull Indones Econ Stud. 1984;20(2):122–38.