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Abstract
This study investigates whether online search trends can act as early indicators of mortgage loan distribution and housing price dynamics in Indonesia. Adopting insights from previous studies on internet search data, it combines cross-correlation and time-series econometric analyses to assess the link between public interest in housing-related keywords, especially mortgage, and subsequent changes in housing market indicators. Using the ARDL model for the 2014Q1–2024Q4 period, the study finds that GDP growth boosts mortgage demand, while inflation and strict LTV ratios hinder it. A negative long-run relationship is shown by Google Trends, implying that heightened online searches may signal uncertainty or speculation rather than actual demand. In the short term, increasing housing prices and interest rates stimulate mortgage issuance, reflecting anticipatory behavior. Overall, the results enrich digital economics research and provide valuable insights for policymakers and financial institutions in managing real estate dynamics amid evolving post-pandemic consumer behavior
