Dynamic Response of the Residential Trade Price Index to Changes in Microeconomic Variables in Indonesia


International Research Journal of Economics and Management Studies
© 2024 by IRJEMS
Volume 3  Issue 9
Year of Publication : 2024
Authors : Mezaluna Firdausyah Giartasari, Ghozali Maski, Amilatus Solihah
irjems doi : 10.56472/25835238/IRJEMS-V3I9P106

Citation:

Mezaluna Firdausyah Giartasari, Ghozali Maski, Amilatus Solihah. "Dynamic Response of the Residential Trade Price Index to Changes in Microeconomic Variables in Indonesia" International Research Journal of Economics and Management Studies, Vol. 3, No. 9, pp. 40-50, 2024.

Abstract:

Residential areas have a very important role for a household, so the demand for them has increased over time along with the increase in population. This causes price fluctuations to become one of the main risks faced by households. Residential prices are not only influenced by a country's fundamental economic factors, but the dynamics that occur in supply and demand in the local residential market also influence house prices. This research aims to analyze how the dynamic response of residential prices is when microeconomic variables, namely the variables that form the cost of goods sold for a residential house, experience changes and economic factors interact and influence house prices in Indonesia. In addition, explores information regarding the factors that shape housing price trends and their impact on economic stability in the short and long term. The dependent variable in this research is the residential property price index. Meanwhile, the independent variables used are the construction wholesale trade price index, interest rate on company credit in the housing sector, and gross domestic product. The research analysis method is inductive statistics using the Ordinary Least Square method, which is implemented in an autoregressive model, namely the Partial Adjustment Model. The data used is time series data from 2013 Quarter 3 – 2023 Quarter 3. The research results show that all independent variables do not have a significant effect, either short-term or long-term, except for the interest rates on the company credit predictor. This shows that the interest rates on company credit are no longer an obstacle in the housing sector. It is proven that in the property sector, there are almost no bad loans because most developers' sales systems to consumers use the public housing credit model, so developer receipts are relatively smooth. Interest rates on company credit payments are also smooth.

References:

[1] Afika, Y. A., & Ariusni, A. (2019). FAKTOR - FAKTOR YANG MEMPENGARUHI PERMINTAAN RUMAH DI INDONESIA. Jurnal Kajian Ekonomi Dan Pembangunan, 1(2), 497. https://doi.org/10.24036/jkep.v1i2.6259
[2] Angipora, M. (2002). Dasar-dasar Pemasaran. Jakarta RajaGrafindo Persada. http://kin.perpusnas.go.id/DisplayData.aspx?pId=3229&pRegionCode=UNTAGSBY&pClientId=712
[3] Arve, M. R. (2022). Securitization Summit 2022, DirjenKN Jelaskan Pertumbuhan Sektor Perumahan Berikan Multiplier Effect Pada Sektor Lain. https://www.djkn.kemenkeu.go.id/berita/baca/28893/Securitization-Summit-2022-DirjenKN-Jelaskan-Pertumbuhan-Sektor-Perumahan-BerikanMultiplier-Effect-Pada-Sektor-Lain.html
[4] Boediono. (2014). Ekonomi Makro. In BPFE.
[5] Buhaerah, P. (2019). Pengaruh kredit pemilikan rumah terhadap keterjangkauan harga properti residensial. Kajian Ekonomi Keuangan, 3(3), 182–197. http://dx.doi.org/10.31685/kek.V3i1.527
[6] Chen, M.-C., & Patel, K. (1998). House Price Dynamics and Granger Causality: An Analysis of Taipei New Dwelling Market. In JOURNAL of the ASIAN REAL ESTATE SOCIETY (Vol. 1, Issue 1).
[7] Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In Modern methods for business research. (pp. 295–336). Lawrence Erlbaum Associates Publishers.
[8] CNN Indonesia. (2022). Sri Mulyani Sebut Milenial Sulit Beli Rumah, Apa Peran Pemerintah? https://www.cnnindonesia.com/ekonomi/20220713182830- 92-821146/sri-mulyani-sebut-milenial-sulit-beli-rumah-apa-peran-pemerintah
[9] Duja, B., & Supriyanto, H. (2019). THE INFLUENCE OF GDP, INTEREST RATE, WAGE, INFLATION AND EXCHANGE RATE ON RESIDENTIAL PROPERTY PRICE IN INDONESIA. In Journal of the Malaysian Institute of Planners VOLUME (Vol. 17).
[10] Fauzia, L. R. (2019). DETERMINAN HARGA RUMAH DI INDONESIA. In Jurnal Ekonomi Pembangunan (Vol. 11, Issue 1).
[11] Kotler, P. (2011). Manajemen Pemasaran Edisi 13 Jilid 1 dan 2. In Jakarta: Erlangga.
[12] Lipsey, R. G. (1993). Economics. In The HarperCollins series in economics.
[13] Rahmawati, O., & Sasongko. (2015). Analisis Determinan Harga Properti Residensial di Indonesia.
[14] Rostiana, E. (2011). Keterjangkauan Perumahan di Indonesia. Trikonomika, 10(2), 162–175.
[15] Scotland, S. (2015). The economic impact of investment in affordable housing. Shelter Scotland, 1–13.
[16] Shi, S., Jou, J. B., & Tripe, D. (2014). Can interest rates really control house prices? Effectiveness and implications for macroprudential policy. Journal of Banking and Finance, 47(1), 15–28. https://doi.org/10.1016/j.jbankfin.2014.06.012
[17] Sukirno, S. (2003). Pengantar Teori Mikroekonomi. In Computer.
[18] Tsatsaronis, K., & Zhu, H. (2004). What drives housing price dynamic: cross-country. March, 65–78.
[19] Wicaksono, A. H. (2021). Analisis Respon Harga Perumahan Terhadap Perubahan Suku Bunga, Tingkat Populasi, Pendapatan Dan Harga Minyak Dunia. Jurnal Ilmiah Mahasiswa FEB, 10(1), 1–31.
[20] Wijaya, D. D., & Anastasia, N. (2021). Pertimbangan Generasi Milenial Pada Kepemillikan Rumah dan Kendala Finansial. Jurnal Manajemen Aset Dan Penilaian, 1(2), 11–20.
[21] Zamillaili, M., & Qoyum, A. (2022). Determinasi Harga Perumahan di Indonesia dan Malaysia.

Keywords:

Dynamic response, Partial Adjustment Model, Property, Residential.