International Monetary Fund. Monetary and Capital Markets Department
The institutional framework for Macroprudential Policies (MaPP) in the Hong Kong Special Administrative Region (the Hong Kong SAR) is well established. According to the Basic Law, the Government of the Hong Kong SAR shall on its own formulate monetary and financial policies. The Financial Secretary (FS) and the Secretary for Financial Services and the Treasury (SFST) are responsible for policies for maintaining the stability and integrity of the financial system of the Hong Kong SAR. The Hong Kong SAR has a sector-based regulatory structure and the responsibilities and tools for safeguarding financial stability are spread across the Financial Services and the Treasury Bureau (FSTB) and three regulators (namely, the Hong Kong Monetary Authority (HKMA), Securities and Futures Commission (SFC) and Insurance Authority (IA)). There are good and well-structured interagency coordination and consultation mechanisms, through the Council of Financial Regulators (CFR) and the Financial Stability Committee (FSC), chaired by the FS and the SFST, respectively. Broad coordination between the CFR and government agencies on taxation and housing supply-side policies has also worked well. MaPP and risk assessment are communicated to the public openly and frequently through speeches, press releases and regular publications, including the Half-Yearly Monetary and Financial Stability Report of the HKMA and the Half-yearly Review Report of the Global and Local Securities Markets of the SFC.
We present a semi-structural model of default risk, which is a function of loan and borrower characteristics, economic conditions, and the regulatory environment. We use this model to simulate bank credit losses for stress-testing purposes and to calibrate borrower-based macroprudential tools. The proposed approach is very flexible and is particularly useful when there is limited history of crisis episodes, when crises bring unanticipated shocks where past tail events offer little guidance and when structural shocks or changes in financial regulations have altered the loan default process. We apply the model to quantify mortgage lending risk in two distinct mortgage markets. For each application, we show a range of modeling adjustments that can be made to capture country-specific institutional features. The model uses bank portfolio data broken down by risk bucket and vintage, which enables us to take explicit account of the loan life cycle and to incorporate the housing and economic cycles. This feature facilitates a timely assessment of banks’ loss-absorbing capacity and the buildup of systemic risk conditional on policy. It also enables counterfactual analysis and the evaluation of macroprudential policy interventions.
We augment a linearized dynamic stochastic general equilibrium (DSGE) model with a tractable endogenous risk mechanism, to support the joint analysis of monetary and macroprudential policy. This state dependent conditional heteroskedasticity mechanism specifies the conditional variances of structural shocks as functions of the business or financial cycle. The resultant heteroskedastic linearized DSGE model preserves the satisfactory simulation and forecasting performance of its nested homoskedastic counterpart for the conditional means of endogenous variables, while substantially improving its goodness of fit to their conditional distributions. In particular, the model matches the key stylized facts of growth at risk. Accounting for state dependent conditional heteroskedasticity makes it optimal for monetary policy to respond more aggressively to the business cycle, and for macroprudential policy to manage the resilience of the banking sector more actively over the financial cycle.
Giancarlo Corsetti, Joao B. Duarte, and Samuel Mann
We study the transmission of monetary shocks across euro-area countries using a dynamic factor model and high-frequency identification. We develop a methodology to assess the degree of heterogeneity, which we find to be low in financial variables and output, but significant in consumption, consumer prices, and variables related to local housing and labor markets. Building a small open economy model featuring a housing sector and calibrating it to Spain, we show that varying the share of adjustable-rate mortgages and loan-to-value ratios explains up to one-third of the cross-country heterogeneity in the responses of output and private consumption.
Juliana Dutra Araujo, Manasa Patnam, Ms. Adina Popescu, Mr. Fabian Valencia, and Weijia Yao
This paper builds a novel database on the effects of macroprudential policy drawing from 58 empirical studies, comprising over 6,000 results on a wide range of instruments and outcome variables. It encompasses information on statistical significance, standardized magnitudes, and other characteristics of the estimates. Using meta-analysis techniques, the paper estimates average effects to find i) statistically significant effects on credit, but with considerable heterogeneity across instruments; ii) weaker and more imprecise effects on house prices; iii) quantitatively stronger effects in emerging markets and among studies using micro-level data; and iii) statistically significant evidence of leakages and spillovers. Other findings include relatively stronger impacts for tightening than loosening actions and negative effects on economic activity in the near term.
Viral V. Acharya, Katharina Bergant, Matteo Crosignani, Tim Eisert, and Fergal McCann
We analyze how regulatory constraints on household leverage—in the form of loan-to-income and loan-to-value limits—a?ect residential mortgage credit and house prices as well as other asset classes not directly targeted by the limits. Supervisory loan level data suggest that mortgage credit is reallocated from low-to high-income borrowers and from urban to rural counties. This reallocation weakens the feedback loop between credit and house prices and slows down house price growth in “hot” housing markets. Consistent with constrained lenders adjusting their portfolio choice, more-a?ected banks drive this reallocation and substitute their risk-taking into holdings of securities and corporate credit.