The impact of financial technology on consumption function of the theory of absolute income hypothesis: a partial adjustment model approach (the Indonesian evidence)
Abstract
Households are economic actors that play a significant role in the economic condition. Thus, households’ consumption expenditures are a variable that deserves a through analysis in an economy. This study aims to identify the impact of financial technology on household consumption by using the theory of the absolute income hypothesis. We use the partial adjustment model (PAM) approach and the Chow test to detect the structural change on households’ consumption function in Indonesia with the observation period of 1990–2017. The results demonstrate that Indonesian households’consumption function exhibits structural change because of the development of financial technology 3.0 era that started in 2000. Besides, the partial adjustment model also suggests that financial technology positively affects Indonesian households’consumption in both short-run and long-run. The findings imply that on the one hand, the findings are a positive signal to rely on finteh as the factor that encourages economic growth in Indonesia. On the other hand, the results indicate that fintech motivates the public to be more consumptive that will potentially lead to higher inflation rates.
Keyword : household consumption, theory of absolute income hypothesis, financial technology, partial adjustment model, Chow test
How to Cite
Saraswati, B. D., Maski, G., Kaluge, D., & Sakti, R. K. (2022). The impact of financial technology on consumption function of the theory of absolute income hypothesis: a partial adjustment model approach (the Indonesian evidence). Business: Theory and Practice, 23(1), 109–116. https://doi.org/10.3846/btp.2022.10789
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Saksonova, S., & Merlino, I. K. (2017). Fintech as financial innovation – the possibilities and problems of implementation. European Research Studies Journal, XX(3), 1. https://doi.org/10.1021/ja00368a049
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Sekhampu, T. J. (2013). Analysis of the factors influencing household expenditure in A South African township. International Business & Economics Research Journal, 12(3), 279–283. https://doi.org/10.19030/iber.v12i3.7671
Tulai, H. I. (2015). Considerations regarding the evolution of incomes, expenditures and consumption of households in Romania. Procedia Economics and Finance, 32(15), 1469–1476. https://doi.org/10.1016/S2212-5671(15)01526-9
Verter, N., & Osakwe, C. N. (2014). A time series analysis of macroeconomic determinants of household spending in the era of cross-cultural dynamics: Czech Republic as a case study. Procedia Economics and Finance, 12(March), 733–742. https://doi.org/10.1016/S2212-5671(14)00400-6
Zafar, Z. (2016). A time series analysis of aggregate consumption function for Pakistan. In S3H Working Paper Series, 06, 243–255. https://doi.org/10.15611/aoe.2017.1.09
Agarwal, S., Ghosh, P., Li, J., & Ruan, T. (2019). Digital payments induce over-spending: Evidence from the 2016 demonetization in India. Working Paper. Asian Bureau of Finance and Economic Research. https://doi.org/10.2139/ssrn.3641508
Agarwal, S., Qian, W., Ren, Y., Tsai, H.-T., & Yeung, B. Y. (2020). The real impact of FinTech: Evidence from mobile payment technology. SSRN Electronic Journal, March. https://doi.org/10.2139/ssrn.3556340
Alimi, R. S. (2013). Keynes’ absolute income hypothesis and Kuznets paradox. Munich Personal RePEc Archive, 49310, 1–15.
Almasifard, M., & Saeedi, M. (2017). Financial development and consumption. In the Proceedings of the 2017 International Conference on Education, Economics and Management research (JCEEMR 2017). Atlantis Press. https://doi.org/10.2991/iceemr-17.2017.126
Arapova, E. (2018). Determinants of household final consumption expenditures in Asian countries: A panel model, 1991–2015. Applied Econometrics and International Development, 18(1), 121–140.
Arner, D. (2016). FinTech: Evolution and regulation (June 2016, 1–18). https://law.unimelb.edu.au/__data/assets/pdf_file/0011/1978256/D-Arner-FinTech-Evolution-Melbourne-June-2016.pdf
Arner, D. W., Barberis, J., & Buckley, R. P. (2016). 150 years of Fintech: An evolutionary analysis. Jassa The Finsia Journal of Applied Finance, 3, 22.
Arner, D. W., Barberis, J. N., & Buckley, R. P. (2015). The Evolution of Fintech: A new post-crisis paradigm? In University of Hing Kong Faculty of Law Research Paper No. 2015/047, UNSW Law Research Paper No. 2016-62. https://doi.org/10.2139/ssrn.2676553
Arioglu, E. (2011). Test of the absolute income hypothesis in USA and Europe. Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi, Cilt 20, Sayı 2, 2011, 299–316. https://doi.org/10.2139/ssrn.1760584
Aziz, N., & Athoillah. (2020). Fintech contribution to Indonesia’s economic growth. Munich Personal RePEc Archive, 97884(97884).
Bäckman, C., & Khorunzhina, N. (2017). Financial Innovation, House Prices and Consumption. In KNUT Wicksell Working Paper 2017:4. https://www.nek.lu.se/media/kwc/working-papers/2017/Web%20wp%202017_4.pdf
Bank Indonesia. (2018a). Mengenal Financial Teknologi. https://www.bi.go.id/id/edukasi/Pages/mengenal-Financial-Teknologi.aspx
Bank Indonesia. (2018b). Statistik Bank Indonesia. https://www.bi.go.id/id/statistik/Default.aspx
Becker, G. (2017). Does FinTech affect household saving behavior? Findings from a Natural Field Experiment. In Federal Reserve Bank of Philadelphia Working Paper 2017, 1–47.
Caglayan, E., & Astar, M. (2012). A microeconometric analysis of household consumption expenditure determinants for both rural and urban areas in Turkey. American International Journal of Contemporary Research, 2(2), 27–34.
DailySocial. (2018). Fintech Report 2018 – Daily Social. Association with Otoritas Jasa Keungan and JAKPAT. https://dailysocial.id/research/fintech-report-2018
Deng, X., Huang, Z., & Cheng, X. (2019). FinTech and sustainable development: Evidence from China based on P2P data. Sustainability (Switzerland), 11(22), 6434. https://doi.org/10.3390/su11226434
Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018). On the Fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), 220–265. https://doi.org/10.1080/07421222.2018.1440766
Gounder, N. (2012). The determinants of household consumption and poverty in Fiji. In Griffith Bussines School Discussion Paper Economics No. 2012-05.
Gujarati, D. N. (2003). Basic econometrics (4th ed.). McGraw Hill.
Hendayana, R. (2005). Penggunaan “Partial Adjustment Model” Sebagai Alternatif Alat Analisis Daya Saing Komoditas Pertanian Dalam Perdagangan Internasional. SOCA: Socioeconomics of Agriculture and Agribusiness, 5(2), 1–18.
Ibbih, J. M., & Peter, S. (2017). Analysis of the determinants of banks distress in Nigeria: An Autoregressive Distributed Lag Model Approach. IOSR Journal of Economics and Finance, 08(02), 67–73. https://doi.org/10.9790/5933-0802036773
Li, J., Wu, Y., & Xiao, J. J. (2020). The impact of digital finance on household consumption: Evidence from China. Economic Modelling, 86(April), 317–326. https://doi.org/10.1016/j.econmod.2019.09.027
Mankiw, N. G. (2016). MacroEconomics (9th ed.). Worth Publishers.
Ofwona, A. C. (2013). An estimation of the consumption function for Kenya Using Keynes’ absolute income hypothesis for the period 1992–2011. Journal of Emerging Trends in Economics and Management Sciences, 4(1), 103–105.
Otoritas Jasa Keuangan. (2019). Perkembangan Fintech Lending 2019. https://www.ojk.go.id/id/kanal/iknb/data-dan-statistik/fintech/Pages/Statistik-Fintech-Lending-Periode-Agustus-2019.aspx
Phimolsathien, T. (2021). Determinants of the use of financial technology (Fintech) in Generation Y. Utopía Y Praxis Latinoamericana. Año: 26, n. o extra interlocuciones 2, 2021, 27–35.
Pindyck, R. S., & Rubinfeld, D. L. (1997). Econometric models and economic forecasts. McGraw Hill.
Saksonova, S., & Merlino, I. K. (2017). Fintech as financial innovation – the possibilities and problems of implementation. European Research Studies Journal, XX(3), 1. https://doi.org/10.1021/ja00368a049
Saraswati, B. D., Maski, G., Kaluge, D., & Sakti, R. K. (2020). The effect of financial inclusion and financial technology on effectiveness of the Indonesian monetary policy. Business: Theory and Practice, 21(1), 230–243. https://doi.org/10.3846/btp.2020.10396
Sekhampu, T. J. (2013). Analysis of the factors influencing household expenditure in A South African township. International Business & Economics Research Journal, 12(3), 279–283. https://doi.org/10.19030/iber.v12i3.7671
Tulai, H. I. (2015). Considerations regarding the evolution of incomes, expenditures and consumption of households in Romania. Procedia Economics and Finance, 32(15), 1469–1476. https://doi.org/10.1016/S2212-5671(15)01526-9
Verter, N., & Osakwe, C. N. (2014). A time series analysis of macroeconomic determinants of household spending in the era of cross-cultural dynamics: Czech Republic as a case study. Procedia Economics and Finance, 12(March), 733–742. https://doi.org/10.1016/S2212-5671(14)00400-6
Zafar, Z. (2016). A time series analysis of aggregate consumption function for Pakistan. In S3H Working Paper Series, 06, 243–255. https://doi.org/10.15611/aoe.2017.1.09