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| Asset Prices and Bank Credit Allocation |
| JIANG Kexin, TAN Xiaofen, ZHU Feifei
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School of Economics, Beijing International Studies University;
School of Economics and Management, Beihang University;
School of Finance, Central University of Finance and Economics |
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Abstract China has a bank-dominated financial system. As the primary force in financial resource allocation, the banking sector must promote high-quality development of the real economy through its own advancement while simultaneously balancing development and security to firmly guard against systemic financial risks. As one of the most significant asset prices, to what extent do fluctuations in real estate prices affect bank credit allocation？ In the context of China's pursuit of high-quality economic development, investigating whether and how asset price fluctuations influence bank credit allocation holds significant importance for enhancing the effectiveness of financial services to the real economy and preventing systemic risks.
However, research on whether and how asset price fluctuations affect bank credit allocation remains limited in China. First, given China's bank-dominated financial system, localized empirical evidence is urgently needed to understand how banks' excessive reliance on real estate collateral, admist housing price volatility, impacts credit allocation. Second, existing literature primarily examines the indirect effects of housing price changes on non-financial enterprise investment through collateral and crowding-out channels from the firm perspective, lacking direct evidence from the banking perspective. Third, China is currently in a critical phase of transitioning toward high-quality development, where the stable operation of the banking sector is essential for coordinating development and security. Against this backdrop, a systematic analysis of housing price fluctuations' impact on bank credit allocation and their transmission mechanisms carries substantial value for preemptively predicting, analyzing, and addressing financial risk exposures arising from downward pressure on housing prices.
Based on loan-level data from a joint-stock commercial bank in China covering 2010-2021, this study finds that rising housing prices significantly increase bank lending, with the collateral channel playing a key role. However, unlike empirical evidence from advanced economies, no direct evidence was found at the data level showing that loans to real estate enterprises significantly crowd out lending to non-real estate enterprises during periods of rising house prices. The reasons are twofold: (1) Within China's shadow banking system, non-real estate enterprises often act as intermediaries for real estate enterprises to access credit. (2) During periods of real estate market boom, non-real estate enterprises actively engage in the real estate market by investing in land and properties, accumulating collateral that enhances their ability to secure bank loans. Heterogeneity analysis reveals that the effect of housing price changes on bank credit allocation varies significantly with enterprises' financial strength, regional economic institutions, market environments, and credit policy cycles.
This paper's main contributions are threefold. First, distinct from research based on Western data, it identifies no significant crowding-out effect of rising house prices within China's institutional settings. Second, differing from firm-level studies, this paper utilizes bank loan data to provide the first direct evidence from the bank's perspective, identifying that housing price fluctuations affect credit allocation via the collateral channel. Third, this research holds substantial practical relevance. Against the backdrop of recent housing price corrections, banks are becoming more cautious when lending to firms dependent on collateral, forming a “falling asset prices-credit contraction” feedback mechanism. The credit allocation mechanisms and collateral dependency paths revealed in this study provide valuable insights into understanding related credit allocation dynamics, financial risk exposures, and policy design.
The research yields the following policy implications: First, commercial banks must accelerate their transformation by reducing reliance on traditional collateral and expanding the scope of new types of pledged assets such as intellectual property rights, data assets, and carbon emission rights. They should also establish dynamic collateral stress-testing mechanisms with differentiated loan-to-value (LTV) thresholds to mitigate cascading risks caused by declining valuations. Second, enhanced penetrative regulation is needed to prevent the spread of financial risks. Given the hidden and contagious nature of financial risks in highly leveraged sectors, regulators must adopt targeted and penetrative supervisory measures. Third, legal and institutional reforms should be advanced to strengthen property rights protection and credit risk prevention mechanisms. This includes improving property rights protection and default recovery mechanisms by refining systems for property registration, bankruptcy liquidation, and information disclosure to enhance assets' legal protection. Additionally, corporate credit assessment systems should be refined, and early warning mechanisms for credit risks should be enhanced to reduce adverse selection problems stemming from inadequate legal protection.
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Received: 30 December 2024
Published: 13 October 2025
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