ENERGY-EFFICIENT RESIDENTIAL HOUSING LOAN: ECONOMIC AND ENVIRONMENTAL IMPACTS AND CURRENT FINANCING SITUATION IN MONGOLIA

Introduction: Energy-efficient residential housing plays a critical role in sustainable development, especially in countries with severe climates such as Mongolia. These buildings are designed to minimize energy consumption, improve indoor environmental quality, and reduce greenhouse gas emissions. Given that the global construction sector accounts for over 30% of energy use and a large share of emissions, transitioning to energy-efficient housing is crucial. Moreover, energy-efficient homes contribute directly to the achievement of several UN Sustainable Development Goals (SDGs), particularly Goal 7 (Affordable and Clean Energy), Goal 11 (Sustainable Cities and Communities), and Goal 13 (Climate Action). Despite its importance, the green housing sector in Mongolia faces significant financial and regulatory barriers that limit its growth and accessibility for low- and middle-income households. Methods: The study employs panel data analysis to investigate the relationship between macroeconomic indicators and the volume of residential housing loans issued by Mongolian commercial banks from 2017 to 2023. Correlation and linear regression techniques were applied to assess the impact of selected SDG-aligned indicators, including nominal GDP (GDPn), real GDP (GDPr), unemployment rate (UnIm), poverty rate (Pover), household energy consumption (EnConH), and construction sector energy use (EnConB). Data sources include the Bank of Mongolia and the national statistical database. Excel was used to conduct the statistical analyses and build regression models. Results: The correlation analysis revealed strong positive relationships between residential loan volumes and GDPn (0.96), GDPr (0.86), and household energy use (0.82). In contrast, unemployment and poverty rates showed negative correlations at –0.66 and –0.77, respectively. The regression analysis produced a high explanatory power: R² = 0.972 in Model 1. An improved Model 2, excluding weaker energy variables, achieved R² = 0.96 with lower standard error and higher statistical significance (F-statistic = 0.012). The final regression model is as follows: Loan Volume = 6495.5 + 0.043 × GDPn − 84.3 × UnIm + 234.2 × Pover. The coefficients suggest that a 1 billion MNT increase in nominal GDP results in a 43 million MNT increase in loan volume, a 1% rise in unemployment reduces loans by 84.3 billion MNT, and a 1% increase in poverty rate corresponds to a decrease of 234.2 billion MNT in loan issuance. Discussion: The findings confirm that Mongolia’s residential mortgage market is highly sensitive to macroeconomic stability. Economic growth boosts demand and accessibility for housing loans, while unemployment and poverty act as suppressors. Despite progress in expanding the green finance sector, green loans remain marginal, accounting for only 2.9% of total bank lending as of Q1 2025. Moreover, 61.8% of these loans are allocated to enterprises, not households, revealing a mismatch between financing availability and residential needs. Barriers include stringent borrower eligibility requirements, insufficient affordable energy-efficient housing stock, and limited data to assess alignment with SDG targets. To address these challenges, the paper recommends expanding access to green housing finance through subsidized interest rates, standardizing certification procedures, streamlining regulatory requirements, and promoting multi-stakeholder partnerships. Future research should explore regional disparities in mortgage access, examine the influence of household income levels, and evaluate the long-term return on investment of green buildings to support evidence-based policymaking.