•  
  •  
 

Abstract

Investigating household wealth should also include spatial analysis to capture the influence of location on the households’ net wealth and to avoid underestimation of the effect of the change of variables due to estimation that ignores spatial aspects. This paper examines factors influencing household net wealth in Indonesia with the influence of spatial lag using data from the Indonesian Family Life Survey (IFLS) for 1993–2014. The article relies on the Spatial Durbin Model (SDM) to analyze the data. Results show that household net wealth in Indonesia is spatially related to each other, and the spillover effect makes the change of household net wealth in Indonesia dominated by the change of variables in neighbouring regions. Furthermore, considering the time component, there is a positive effect of households’ size on households’ net wealth due to the time component concerning the spatial lag of the dependent and independent variables.

References

[1] Anselin, L 2001, ‘Spatial econometrics’, in BH Baltagi (ed.), A companion to theoretical econometrics (pp. 310-330), Blackwell Publishing Ltd. doi: https://doi.org/10.1002/9780470996249.ch15.

[2] Anselin, L, & Bera, AK 1998, ‘Spatial dependence in linear regression models with an introduction to spatial econometrics’, in A Ullah & DEA Giles (Eds.), Handbook of Applied Economic Statistics (pp. 237-290), CRC Press.

[3] Badan Pusat Statistik 1994–2015, Statistik Indonesia 1994, 1997, 2000, 2007, 2014.

[4] Baltagi, BH 2008, Econometric analysis of panel data, John Wiley & Sons.

[5] Belotti, F, Hughes, G, & Mortari, AP 2017, ‘Spatial panel-data models using Stata’, The Stata Journal, vol. 17, no. 1, pp. 139-180. doi: https://doi.org/10.1177/1536867X1701700109.

[6] Birdsall, N 2010, ‘The (indispensable) middle class in developing countries; or, the rich and the rest, not the poor and the rest’, Center for Global Development Working Paper, 207, Center for Global Development, viewed 3 December 2020 .

[7] Brown, S, & Gray, D 2014, ‘Household finances and well-being: an empirical analysis of comparison effects’, IZA Discussion Paper, 8530, Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor (IZA), viewed 3 December 2020 .

[8] Case, AC 1991, ‘Spatial patterns in household demand’, Econometrica: Journal of the Econometric Society, vol. 59, no. 4, pp. 953-965. doi: https://doi.org/10.2307/2938168.

[9] Clementi, F, Dabalen, AL, Molini, V, & Schettino, F 2020, ‘We forgot the middle class! Inequality underestimation in a changing Sub-Saharan Africa’, The Journal of Economic Inequality, vol. 18, no. 1, pp. 45-70. doi: https://doi.org/10.1007/s10888-019-09432-8.

[10] Cliff, AD, & Ord, JK 1981, Spatial processes: models and applications, Pion.

[11] Cox, NJ 2011, ‘Stata tip 96: Cube roots’, The Stata Journal, vol. 11, no. 1, pp. 149-154. doi: https://doi.org/10.1177/1536867X1101100112.

[12] Elhorst, JP 2009, ‘Spatial panel data models’, in M Fischer & A Getis (eds), Handbook of applied spatial analysis, (pp. 377-407), Springer. doi: https://doi.org/10.1007/978-3-642- 03647-7_19.

[13] Elhorst, JP 2010, ‘Applied spatial econometrics: raising the bar’, Spatial Economic Analysis, vol. 5, no. 1, pp. 9-28. doi: https://doi.org/10.1080/17421770903541772.

[14] Elhorst, JP, & Fréret, S 2009, ‘Evidence of political yardstick competition in France using a two-regime spatial Durbin model with fixed effects’, Journal of Regional Science, vol. 49, no. 5, pp. 931-951. doi: https://doi.org/10.1111/j.1467- 9787.2009.00613.x.

[15] Filmer, D, & Pritchett, LH 2001, ‘Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India’, Demography, vol. 38, no. 1, pp. 115-132. doi: https://doi.org/10.1353/dem.2001.0003.

[16] Fitzsimmons, V, & Leach, LJ 1994, ‘Net worth change: beginning and expanding life cycle stages’, Journal of Financial Counseling and Planning, vol. 5, no. 1, pp. 65-82.

[17] Friedman, M 1957, A theory of the consumption function, Princeton University Press.

[18] Gani, I 2021, ‘Poverty of women and the Covid-19 pandemic in Indonesia’, Budapest International Research and Critics Institute-Journal (BIRCI-Journal), vol. 4, no. 1, pp. 1034-1041. doi: https://doi.org/10.33258/birci.v4i1.1710.

[19] Gibson, L 2017, ‘Towards a More Equal Indonesia: How the government can take action to close the gap between the richest and the rest’, Oxfam Briefing Paper, viewed 3 December 2020 .

[20] Hao, L 1996, ‘Family structure, private transfers, and the economic well-being of families with children’, Social Forces, vol. 75, no. 1, pp. 269-292. doi: https://doi.org/10.1093/sf/75.1.269.

[21] Haryono, TJS 1999, ‘Dampak urbanisasi terhadap masyarakat di daerah asal’, Masyarakat, Kebudayaan dan Politik, vol. 12, no. 4, pp. 67-78.

[22] Keister, LA 2003, ‘Sharing the wealth: the effect of siblings on adults’ wealth ownership’, Demography, vol. 40, no. 3, pp. 521-542. doi: https://doi.org/10.1353/dem.2003.0026.

[23] Keister, LA 2004, ‘Race, family structure, and wealth: The effect of childhood family on adult asset ownership’, Sociological Perspectives, vol. 47, no. 2, pp. 161-187. doi: https://doi.org/10.1525/sop.2004.47.2.161.

[24] Keisuke, K 2016, ‘Introduction to spatial econometric analysis: creating spatially lagged variables in Stata’, RIETI Technical Paper Series 16-T-001, Research Institute of Economy, Trade and Industry (RIETI), viewed 3 December 2020 .

[25] Kondo, K 2018, Testing for global spatial autocorrelation in Stata, viewed 3 December 2020 .

[26] Kusumaningrum, S, Siagian, C, & Beazley, H 2022, ‘Children during the COVID-19 pandemic: children and young people’s vulnerability and wellbeing in Indonesia’, Children’s Geographies, vol. 20, no. 4, pp. 437-447. doi: https://doi.org/10.1080/14733285.2021.1900544.

[27] LeSage, JP 2008, ‘An introduction to spatial econometrics’, Revue d’économie industrielle, vol. 123, no. 3, pp. 19-44. doi: https://doi.org/10.4000/rei.3887.

[28] LeSage, J, & Pace, RK 2009, Introduction to spatial econometrics, Chapman and Hall/CRC.

[29] Mauleny, AT 2016, ‘Aglomerasi, perubahan sosial ekonomi, dan kebijakan pembangunan Jakarta’, Jurnal Ekonomi & Kebijakan Publik, vol. 6, no. 2, pp. 147-162. doi: http://dx.doi.org/10.22212/jekp.v6i2.351.

[30] Munandar, Y 2020, ‘Overcoming severe food insecurity in Central Java Province of Indonesia amidst Covid-19 pandemic’, Eko-Regional: Jurnal Pembangunan Ekonomi Wilayah, vol. 15, no. 2, pp. 87-92. doi: https://doi.org/10.20884/1.erjpe.2020.15.2.1579.

[31] Mustajab, M 2009, Infrastructure investment in Indonesia: Process and impact (Doctor of Philosophy, University of Groningen).

[32] Oliver, ML, & Shapiro, TM 1990, ‘Wealth of a nation: A reassessment of asset inequality in America shows at least one third of households are asset-poor’, American Journal of Economics and Sociology, vol. 49, no. 2, pp. 129-151. doi: https://doi.org/10.1111/j.1536-7150.1990.tb02268.x.

[33] Pisati, M 2001, ‘sg162: Tools for spatial data analysis’, Stata Technical Bulletin, vol. 60, pp. 21-37.

[34] Pramono, G, & Marsisno, W 2018, ‘Availability of infrastructure for poverty reduction in Indonesia: spatial panel data analysis’, Economics and Finance in Indonesia, vol. 64, no. 2, pp. 157-180.

[35] Rahiem, MDH 2021, ‘COVID-19 and the surge of child marriages: A phenomenon in Nusa Tenggara Barat, Indonesia’, Child Abuse & Neglect, vol. 118, p. 105168. doi: https://doi.org/10.1016/j.chiabu.2021.105168.

[36] RAND 2014, RAND IFLS-5 Survey Description, viewed 3 December 2020 .

[37] Réquia Jr, WJ, Koutrakis, P, & Roig, HL 2015, ‘Spatial distribution of vehicle emission inventories in the Federal District, Brazil’, Atmospheric Environment, vol. 112, pp. 32- 39. doi: https://doi.org/10.1016/j.atmosenv.2015.04.029.

[38] Sikoki, B, Witoelar, F, Strauss, J, Meijer, E, & Suriastini, W 2013, IFLS east user’s guide and field report, SurveyMETER and University of Southern California, viewed 3 Desember 2020. .

[39] Sokal, RR, Oden, NL, & Thomson, BA 1998, ‘Local spatial autocorrelation in a biological model’, Geographical Analysis, vol. 30, no. 4, pp. 331-354. doi: https://doi.org/10.1111/j.1538-4632.1998.tb00406.x.

[40] Soseco, T 2020, ‘Lessons from COVID-19: Small and financially strong family’, Jurnal Kependudukan Indonesia, Edisi Khusus Demografi dan Covid-19, pp. 49-52. doi: https://doi.org/10.14203/jki.v0i0.577.

[41] Soseco, T 2021, ‘Household size, education, and household wealth in Indonesia: Evidence from quantile regression’, Jurnal Ekonomi Indonesia, vol. 10, no. 3, pp. 281-297. doi: https://doi.org/10.52813/jei.v10i3.72.

[42] Vidyattama, Y 2014, ‘Issues in applying spatial autocorrelation on Indonesia’s provincial income growth analysis’, Australasian Journal of Regional Studies, vol. 20, no. 2, pp. 375-402.

[43] Wakita, S, Fitzsimmons, VS, & Liao, TF 2000, ‘Wealth: Determinants of savings net worth and housing net worth of pre-retired households’, Journal of Family and Economic Issues, vol. 21, no. 4, pp. 387-418. doi: https://doi.org/10.1023/A:1026432705410.

[44] Ward, P 2014, ‘Measuring the level and inequality of wealth: An application to China’, Review of Income and Wealth, vol. 60, no. 4, pp. 613-635. doi: https://doi.org/10.1111/roiw.12063.

[45] Williams, FL, & Manning, SL 1972, ‘Net worth change of selected families’, Family and Consumer Sciences Research Journal, vol. 1, no. 2, pp. 104-113. doi: https://doi.org/10.1177/1077727X7200100205.

[46] Yu, J, De Jong, R, & Lee, LF 2008, ‘Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large’, Journal of Econometrics, vol. 146, no. 1, pp. 118-134. doi: https://doi.org/10.1016/j.jeconom.2008.08.002.

Download

Share

COinS