Uswatun Khasanah
Faculty of Economics and Business, Ahmad Dahlan University

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Determinant of Property Price Through The Monetary Variables: An ARDL Approach Mahrus Lutfi Adi Kurniawan; Uswatun Khasanah; Siti 'Aisyah Baharudin
Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Vol 24, No 1 (2023): JEP 2023
Publisher : Muhammadiyah University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jep.v24i1.20588

Abstract

The 2008 financial crisis demonstrates that studies on property price volatility are important because it impacts domestic economic conditions. This study identifies the volatility of property prices through monetary variables. This current study employs the ARDL method to determine the effect of monetary variables in the short and long term. The study results show that GDP as a proxy for income negatively affects residential property prices in Indonesia, and inflation positively affects property prices. There is a difference in the effect of domestic interest rates on property prices where there is a direct effect on domestic interest rates followed by the COVID-19 crisis. Meanwhile, foreign interest rates have a negative effect in the short term and a positive effect in the long term. This study implies that strong monetary operation through interest rates can maintain public expectations of prices, especially property prices.
Unveiling Regional Growth Patterns Spatial Heterogeneity and Infrastructure Quality under a Bayesian Framework in Central Java Suripto Suripto; Agus Salim; Mahrus Lutfi Adi Kurniawan; Uswatun Khasanah; Azkal Azkiya Athfal
Eko-Regional: Jurnal Pembangunan Ekonomi Wilayah Vol 20 No 2 (2025): September 2025
Publisher : Faculty of Economics and Business Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32424/er.v20i2.17670

Abstract

: This study investigates the impact of infrastructure quality, encompassing roads, clean water distribution, and electricity consumption, on regional economic growth in Central Java from 2018 to 2024. A Bayesian Panel Data Regression model with a hierarchical structure was estimated using the Markov Chain Monte Carlo (MCMC) method, assisted by Python programming, to address spatial heterogeneity, lag effects, and parameter uncertainty. Model validation employed Posterior Predictive Checks (PPC), Bayesian R², R-hat statistics, and Effective Sample Size (ESS). The findings reveal that past GRDP significantly influences current regional economic growth, while the direct effects of infrastructure variables are statistically insignificant. This outcome highlights that infrastructure quality is more important than quantity in promoting development. The study advances empirical methodologies by integrating full posterior inference with predictive validation, representing a state-of-the-art approach in regional economic analysis. The results provide strong evidence in support of formulating infrastructure policies that focus on long-term, sustainable Growth.