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This study investigates the effects of housing futures trading on housing demand, house price volatility and housing bubbles in a theoretical framework. The baseline model is an application of the De long, Shleifer, Summers and Waldman (1990) model of noise traders to the housing market, when the risky asset is housing. This adds new features to the model as households receive utility from housing services and cannot short-sell houses. The existence of noise traders in the housing market creates uncertainty about house prices, causes prices to deviate away from their fundamental values, and leads to a distortion in housing consumption. To investigate the impact of housing derivatives trading on the housing market, a new financial instrument, housing futures, is introduced into the baseline model. Housing futures trading affects house price stability through three channels: by (i) enabling households to disentangle their housing consumption decisions from investment decisions; (ii) allowing short-selling; and (iii) attracting an additional set of traders (pure speculators) looking for portfolio diversification opportunities. The results show that, for a large set of admissible parameter values, housing futures trading decreases the volatility of house prices and increases the welfare of households and investors.

In 2010, the Basel Committee on Banking Supervision published an assessment of the long-term economic impact (LEI) of stronger capital and liquidity requirements. This paper considers this assessment in light of estimates from later studies of the macroeconomic benefits and costs of higher capital requirements. Consistent with the Basel Committee's original assessment, this paper finds that the net macroeconomic benefits of capital requirements are positive over a wide range of capital levels. Under certain assumptions, the literature finds that the net benefits of higher capital requirements may have been understated in the original committee assessment. Put differently, the range of estimates for the theoretically optimal level of capital requirements-where marginal benefits equal marginal costs-is likely either similar to, or higher than was originally estimated by the Basel Committee. The above conclusion is however subject to a number of important considerations. First, estimates of optimal capital are sensitive to a number of assumptions and design choices. For example, the literature differs in judgments made about the permanence of crisis effects as well as assumptions about the efficacy of post crisis reforms, such as liquidity regulations and bank resolution regimes, in reducing the probability and costs of future banking crisis. In some cases, these judgements can offset the upward tendency in the range of optimal capital. Second, differences in (net) benefit estimates can reflect different conditioning assumptions such as starting levels of capital or default thresholds (the capital ratio at which firms are assumed to fail) when estimating the impact of capital in reducing crisis probabilities. Finally, the estimates are based on capital ratios that are measured in different units. For example, some studies provide optimal capital estimates in risk-weighted ratios, others in leverage ratios. And, across the risk-weighted ratio estimates, the definition of capital and risk-weighted assets (RWAs) can also differ (e.g., tangible common equity (TCE) or Tier 1 or common equity tier 1 (CET1) capital; Basel II RWAs vs. Basel III measures of RWAs). A full standardisation of the different estimates across studies to allow for all of these considerations is not possible on the basis of the information available and lies beyond the scope of this paper. This paper also suggests a set of issues which warrant further monitoring and research. This includes the link between capital and the cost and probability of crises, accounting for the effects of liquidity regulations, resolution regimes and counter-cyclical capital buffers, and the impact of regulation on loan quantities.

Every year since 2004, the Bank of England has commissioned NMG Consulting to carry out a survey on household finances. This paper describes the NMG Survey, its methodology, and its advantages and disadvantages relative to other surveys. The NMG Survey is useful in providing a timelier guide to developments in the distribution of household balance sheets than other surveys, it appears better at measuring financial distress, and it includes questions on topical policy issues that are often not available in other surveys. A drawback of the NMG Survey is that there may be a greater risk of selection into the survey based on unobservable characteristics than is the case for some other household surveys.

We study the effect of changes to bank-specific capital requirements on mortgage loan supply with a new loan-level dataset containing all mortgages issued in the UK between 2005Q2 and 2007Q2. We find that a rise of a 100 basis points in capital requirements leads to a 5.4% decline in individual loan size by bank. Loans issued by competing banks rise by roughly the same amount, which is indicative of credit substitution. Borrowers with an impaired credit history (verified income) are not (most) affected. This is consistent with origination of riskier loans to grow capital by raising retained earnings. No evidence for credit substitution of non-bank finance companies is found. JEL Classification: G21, G28

We develop an agent-based model of the UK housing market to study the impact of macroprudential policy experiments on key housing market indicators. The heterogeneous nature of this model enables us to assess the effects of such experiments on the housing, rental and mortgage markets not only in the aggregate, but also at the level of individual households and sub-segments, such as first-time buyers, homeowners, buy-to-let investors, and renters. This approach can therefore offer a broad picture of the disaggregated effects of financial stability policies. The model is calibrated using a large selection of micro-data, including data from a leading UK real estate online search engine as well as loan-level regulatory data. With a series of comparative statics exercises, we investigate the impact of: i) a hard loan-to-value limit, and ii) a soft loan-to-income limit, allowing for a limited share of unconstrained new mortgages. We find that, first, these experiments tend to mitigate the house price cycle by reducing credit availability and therefore leverage. Second, an experiment targeting a specific risk measure may also affect other risk metrics, thus necessitating a careful calibration of the policy to achieve a given reduction in risk. Third, experiments targeting the owner-occupier housing market can spill over to the rental sector, as a compositional shift in home ownership from owner-occupiers to buy-to-let investors affects both the supply of and demand for rental properties.

We develop an agent-based model of the UK housing market to study the impact of macroprudential policy experiments on key housing market indicators. The heterogeneous nature of this model enables us to assess the effects of such experiments on the housing, rental and mortgage markets not only in the aggregate, but also at the level of individual households and sub-segments, such as first-time buyers, homeowners, buy-to-let investors, and renters. This approach can therefore offer a broad picture of the disaggregated effects of financial stability policies. The model is calibrated using a large selection of micro-data, including data from a leading UK real estate online search engine as well as loan-level regulatory data. With a series of comparative statics exercises, we investigate the impact of (i) a hard loan-to-value limit, and (ii) a soft loan-to-income limit, allowing for a limited share of unconstrained new mortgages. We find that, first, these experiments tend to mitigate the house price cycle by reducing credit availability and therefore leverage. Second, an experiment targeting a specific risk measure may also affect other risk metrics, thus necessitating a careful calibration of the policy to achieve a given reduction in risk. Third, experiments targeting the owner-occupier housing market can spill over to the rental sector, as a compositional shift in home ownership from owner-occupiers to buy-to-let investors affects both the supply of and demand for rental properties.

We develop an agent-based model of the UK housing market to study the impact of macroprudential policy experiments on key housing market indicators. The heterogeneous nature of this model enables us to assess the effects of such experiments on the housing, rental and mortgage markets not only in the aggregate, but also at the level of individual households and sub-segments, such as first-time buyers, homeowners, buy-to-let investors, and renters. This approach can therefore offer a broad picture of the disaggregated effects of financial stability policies. The model is calibrated using a large selection of micro-data, including data from a leading UK real estate online search engine as well as loan-level regulatory data. With a series of comparative statics exercises, we investigate the impact of (i) a hard loan-to-value limit, and (ii) a soft loan-to-income limit, allowing for a limited share of unconstrained new mortgages. We find that, first, these experiments tend to mitigate the house price cycle by reducing credit availability and therefore leverage. Second, an experiment targeting a specific risk measure may also affect other risk metrics, thus necessitating a careful calibration of the policy to achieve a given reduction in risk. Third, experiments targeting the owner-occupier housing market can spill over to the rental sector, as a compositional shift in home ownership from owner-occupiers to buy-to-let investors affects both the supply of and demand for rental properties.

We study the effect of changes to bank-specific capital requirements on mortgage loan supply with a new loan-level data set containing all mortgages issued in the United Kingdom between 2005 Q2 and 2007 Q2. We find that a rise of a 100 basis points in capital requirements leads to a 5.4% decline in individual loan size by bank. Loans issued by competing banks rise by roughly the same amount, which is indicative of credit substitution. Borrowers with an impaired credit history (verified income) are not (most) affected. This is consistent with origination of riskier loans to grow capital by raising retained earnings. No evidence for credit substitution of non-bank finance companies is found.

Macroprudential regulators worldwide have introduced regulations to limit household leverage in light of existing evidence which suggests that high leverage is associated with household distress during crisis. We analyse the distributional effects of such a macroprudential policy on mortgage and house price cycles. For identification, we exploit the universe of UK mortgages and a 15%-limit imposed in 2014 on lenders—not households—for high loan-to-income ratio (LTI) mortgages. Despite some regulatory arbitrage (e.g. increases in LTV and average loan size), more-constrained lenders issue fewer high-LTI mortgages. Partial substitution by less-constrained lenders leads to overall credit contraction to low-income borrowers in local-areas more exposed to constrained-lenders, lowering house price growth. Following the Brexit referendum (which led to house-price correction), the 2014-policy strongly implies—via lower pre-correction debt—better house prices and mortgage defaults during an episode of house price correction.

Macroprudential regulators worldwide have introduced regulations to limit household leverage in light of existing evidence which suggests that high leverage is associated with household distress during crisis. We analyse the distributional effects of such a macroprudential policy on mortgage and house price cycles. For identification, we exploit the universe of UK mortgages and a 15%-limit imposed in 2014 on lenders—not households—for high loan-to-income ratio (LTI) mortgages. Despite some regulatory arbitrage (e.g. increases in LTV and average loan size), more-constrained lenders issue fewer high-LTI mortgages. Partial substitution by less-constrained lenders leads to overall credit contraction to low-income borrowers in local-areas more exposed to constrained-lenders, lowering house price growth. Following the Brexit referendum (which led to house-price correction), the 2014-policy strongly implies—via lower pre-correction debt—better house prices and mortgage defaults during an episode of house price correction.