We combine administrative data with a life cycle structural model that exploits the unique features of the U.K. mortgage market to analyze the sources of inaction and to estimate borrowers’ nonpecuniary remortgaging costs. The utility costs needed to generate a given level of inaction depend on monetary gains from remortgaging and on the importance of those monetary gains for agents, which in turn depend on the (endogenously determined) marginal utility of consumption. The model results reveal significant nonpecuniary costs of action that, when measured as a proportion of borrower income, are larger for the young and for lower-income households.

We exploit a U.K. government-sponsored product and provide evidence on shared equity mortgages. The analysis shows how the interaction of house price growth and leverage regulation promotes product adoption. Following an increase in the equity limit, households use the additional financing to buy more expensive properties rather than reduce leverage. Equity used as a complement to debt is likely less beneficial for financial stability than when used as a substitute. Equity borrowers are less likely to change lenders when refinancing their senior debt. Finally, we measure the equity provider returns, which are affected by selection and undervaluation at repayment.

Using data on the universe of housing transactions in England and Wales over a 20-year period, we document that sale prices and selling propensities are affected by house prices prevailing in the period in which properties were previously bought. Using administrative data on mortgages, we show that cognitive frictions explain most of the history dependence in sale prices, whereas credit frictions are more relevant for selling propensities. We corroborate our analysis with data on online house listings, and we estimate the impact of history dependence on the collapse and slow recovery of housing market activity in the postcrisis period. (JEL E32, R21, R31)

I combine housing sales from the England and Wales Land Registry with online rental listings from property portal Zoopla to identify buy-to-rent transactions-known as buy-to-let (BTL) in the UK. These sales are procyclical, concentrated in areas where the housing market is performing well, and more common for small dwellings. Comparing these transactions against all other housing sales in 2009-2014, I show that BTL investors pay less than other buyers for the same properties. The heterogeneity of discounts across regions and property types is consistent with a simple theoretical framework that emphasizes the drivers of investors' and homeowners' demand for houses.

We propose a framework for addressing the ‘black box’ problem present in some Machine Learning (ML) applications. We implement our approach by using the Quantitative Input Influence (QII) method of Datta et al (2016) in a real‑world example: a ML model to predict mortgage defaults. This method investigates the inputs and outputs of the model, but not its inner workings. It measures feature influences by intervening on inputs and estimating their Shapley values, representing the features’ average marginal contributions over all possible feature combinations. This method estimates key drivers of mortgage defaults such as the loan‑to‑value ratio and current interest rate, which are in line with the findings of the economics and finance literature. However, given the non‑linearity of ML model, explanations vary significantly for different groups of loans. We use clustering methods to arrive at groups of explanations for different areas of the input space. Finally, we conduct simulations on data that the model has not been trained or tested on. Our main contribution is to develop a systematic analytical framework that could be used for approaching explainability questions in real world financial applications. We conclude though that notable model uncertainties do remain which stakeholders ought to be aware of.

Academics have proposed hybrid products with equity features for the financing of housing. In spite of their risk-sharing benefits these products have not become mainstream. This paper studies an important exception, a UK government scheme which in the five years since its inception has provided almost £10 billion of equity financing. The analysis of the origination and prepayment behavior of households who have used the scheme highlights housing affordability constraints. A difference-in-difference analysis of an increase in the maximum government equity limit shows that households took advantage of the increase to buy more expensive properties, and not to reduce their mortgage debt and house price risk exposure. A counterfactual study of homebuyers who, instead of using the equity available, relied on high loan-to-value mortgages shows that their financing choices can be rationalized by an expected rate of house price appreciation of 7.7% per year. We draw general implications for how households approach their house purchase and financing decisions, taking advantage of the fact that the shared equity mortgages that we study allow the separation of the consumption and investment dimensions of housing.

We study the link between mortgage debt and entrepreneurship using a model of occupational choice and housing tenure in a setting where loans are recourse—like in the UK and several US states. Our model shows that as long as the mortgage interest rate exceeds the risk-free rate: (i) mortgage debt diminishes the likelihood of entrepreneurship by amplifying risk aversion; and (ii) the negative relation between mortgage debt and entrepreneurship increases with income volatility. Our model also shows that the link between housing equity and entrepreneurship is ambiguously signed because of competing portfolio and wealth effects. We use the British Household Panel Survey to test and confirm the model predictions, and deal with unobservable heterogeneity employing three research designs—individual fixed effects, housing-spell fixed effects, and instrumental variables. A one standard deviation increase in leverage reduces the probability of entrepreneurship by 10–20 percent.

Most London housing transactions involve trading long leases of varying lengths. We exploit this to estimate the time value of housing — the relationship between the price of a property and the term of ownership — over a hundred years and derive implied discount rates. For our empirical analysis, we compile a unique historical data set (1987 to 1992) to abstract from the right to extend leases currently enjoyed by tenants. Across a variety of specifications and samples we find that leasehold prices are consistent with a time declining schedule and low long-term discount rates in housing markets.

We present new evidence that lenders use down payment size to price unobservable borrower risk. We exploit the contractual features of a UK scheme that helps home buyers top up their down payments with equity loans. We find that a 20 percentage point smaller down payment is associated with a 22 basis point higher interest rate at origination, and a higher ex-post default rate. Lenders see down payment as a signal for unobservable risk, but the relative importance of this signal is limited, as it accounts for only 10% of the difference in mortgage rates between loans with 75% and 95% loan to value ratio.

Academics have proposed hybrid products with equity features for the financing of housing. In spite of their risk-sharing benefits these products have not become mainstream. This paper studies an important exception, a UK government scheme which over the last four years has provided £6.72 billion of equity financing. The analysis of the origination and prepayment behaviour of households who have used the scheme highlights housing affordability constraints. A counterfactual study of homebuyers who instead of using the equity available relied on high loan to value mortgages shows that their behavior can be rationalized by a large expected rate of house price appreciation (of over 9% per year). The analysis contributes to the understanding of the roles of affordability and house price expectations in housing finance. ∗We would like to thank Francisco Gomes, Henri Servaes, Rui Silva and seminar participants at the Bank of England, Birkbeck, IE, London Business School and NIESR for comments. We would also like to thank Scott Dennison and Marcus Spray at the Ministry of Housing, Communities and Local Government for providing data on the Help To Buy Equity Loan scheme. ¶Department of Economics, London School of Economics. Houghton Street, London WC2A 2AE, United Kingdom. Email: m.benetton1@lse.ac.uk. ‖Structural Economic Analysis, Bank of England. Threadneedle St, London EC2R 8AH, United Kingdom. Email: Philippe.Bracke@bankofengland.gsi.gov.uk. §Department of Finance, London Business School, Regent’s Park, London NW1 4SA, United Kingdom. Email: jcocco@london.edu. ‡Policy Strategy & Implementation, Bank of England. Threadneedle St, London EC2R 8AH, United Kingdom. Email: Nicola.Garbarino@bankofengland.gsi.gov.uk.

At its November 2017 meeting, the Bank of England’s Monetary Policy Committee (MPC) voted to increase Bank Rate for the first time since July 2007. The September 2017 NMG Consulting survey of households, whose results were shown to the MPC prior to their November policy decision, sheds light on the conditions of households’ balance sheets just before this change in monetary policy. Since the financial crisis, household balance sheet positions have improved significantly. The latest survey points to a slight deterioration in household balance sheet metrics over the past year, but these measures remain some way from previous peaks. For example, the share of households with a mortgage debt-servicing ratio (DSR) above 40% of income, — a DSR often associated with a higher risk of repayment difficulties — has risen over the past year. But that share remains around a historically low level. Changes in Bank Rate can influence household spending through a number of channels. To the extent that increases in Bank Rate feed through to retail interest rates, they affect household disposable income by raising payments on existing debts and deposits. The NMG survey provides evidence on this cash-flow effect and suggests that only around 2½% of households with a mortgage will need to take action (for instance by spending less or working more hours) following the rate increase. The decision to leave the European Union in the June 2016 referendum is still influencing households’ economic outlook. Views on both the general economy and households’ own finances have become slightly more pessimistic over the past twelve months. Expectations about nominal income growth, however, have reverted back to pre-referendum levels.

In 2013 buy-to-rent investors — referred to as buy-to-let (BTL) in the United Kingdom — accounted for 13% of all UK mortgage-funded housing transactions and for an even greater fraction of non-mortgage sales. This paper studies the behaviour of BTL investors using 2009–14 micro data. Combining the universe of transactions from the England and Wales Land Registry with online listings from WhenFresh/Zoopla, I identify a BTL purchase as a transaction where a rental listing on the same property appears on the web in the six subsequent months. The micro data reproduce the increase in BTL transactions over 2009–14 and show that BTL investors are more likely to invest in regions with large rental markets. I find that, on average, BTL investors pay 0.9%–1.1% less than other buyers for equivalent properties. Discounts are larger (around 2%) in regions with less liquid housing markets. Results are robust to including detailed geographical fixed effect and advertised sale prices in the regressions. I also show that properties purchased by investors spend on average five days less on the market.

I analyze a real estate agency's proprietary dataset containing tens of thousands of housing sale and rental transactions in Central London during the 2006–2012 period. I isolate 1,922 properties that were both sold and rented out within six months and measure their rent‐price ratios. I find that rent‐price ratios are lower for bigger and more central units. These stylized facts are consistent with the user cost formula and reflect differences in maintenance costs, vacancy rates, growth expectations and risk premia.

Most housing transactions in London involve trading long leases of varying lengths. We exploit this feature to estimate the time value of housing --- the relationship between the value of a property and the length of time it will be owned for --- over the range 1-99 years. To do so, we compile a unique historical dataset from 1987 to 1992 to abstract from current institutional features of the UK system, for instance rights to extend leases that could confound our results. By applying hedonic techniques to these data we provide new evidence on how the market values leasehold properties. We find that the time value of housing over the range 1-99 is similar to an exponential shape, a finding that suggests sophisticated pricing behaviour in the London residential market. Digging deeper, however, we show that leasehold prices depart from this predictable pattern in a way that is consistent with a declining discount rate schedule

We study the link between homeownership, mortgage debt, and entrepreneurship using a model of occupational choice and housing tenure where homeowners commit to mortgage payments. Our model predicts that, as long as mortgage rates exceed the rate of interest on liquid wealth: (i) mortgage debt, by amplifying risk aversion, diminishes the likelihood that homeowners start a business; and (ii) the negative relation between mortgage debt and entrepreneurship is more pronounced when income volatility is higher. Our model further predicts that the relation between housing wealth and entrepreneurship is ambiguously signed because of competing portfolio and hedging considerations. Exploiting the longitudinal dimension of the British Household Panel Survey to control for unobservables, we test and confirm these predictions. A one standard deviation increase in leverage makes a homeowner 10-12 percent less likely to become an entrepreneur.

This paper analyzes the duration of house price upturns and downturns in the last 40 years for 19 OECD countries. I provide two sets of results, one pertaining to the average length and the other to the length distribution. On average, upturns are longer than downturns, but the difference disappears once the last house price boom is excluded. In terms of length distribution, upturns (but not downturns) are more likely to end as their duration increases. This duration dependence is consistent with a boom-bust view of house price dynamics, where booms represent departures from fundamentals that are increasingly difficult to sustain.

In this paper I study unit-level data on house prices and rents in Central London. I document the existence of systematic differences in price-rent ratios across property types within the same urban area: bigger properties and properties located in more expensive neighborhoods have higher price-rent ratios. My analysis is based on a unique new dataset: the records of a major Central London real estate agency. The dataset contains information on achieved prices and rents for tens of thousands of properties, as well as detailed descriptions of property characteristics. The period of analysis, 2005 to 2011, covers the last part of the housing boom, the bust of 2008, and the subsequent recovery. In terms of empirical methodology, I use hedonic regressions to estimate average prices and rents within cells of observationally equivalent properties. Since hedonic regressions cannot control for unobserved characteristics, I also run a restricted analysis with properties that are both sold and rented out within 6 months: in this way I am able to measure price-rent ratios directly. In the last part of the paper I discuss potential explanations for the differences in price-rent ratios. One possibility is that gross price-rent ratio disparities hide differences in maintenance costs or vacancy rates. Another possibility, related to the dividend pricing model, is that properties with higher price-rent ratios feature higher expected rent growth or lower risk premia. Contrary to this second view, I find that within Central London the rent growth rates of more expensive properties are not different from those of cheaper properties, but their volatility is significantly higher. This is consistent with a hedging model where higher rent volatility in some housing submarkets pushes people to buy in order to lock in future rents. In order to verify the above mechanisms, I use price and rent indexes derived from the hedonic regressions to estimate the growth and aggregate volatility of prices and rents for different property categories. Using data at the individual property level, I also measure idiosyncratic volatilities by restricting attention to properties that were sold or rented at least twice during the sample period. Since the expectations of agents might differ from the actual historical performance of house prices and rents, I complement my analysis with an expectation survey carried out through the mailing list of the real estate agency that provided the property data.

We study the link between homeownership and entrepreneurship by exploiting the longitudinal dimension of the British Household Panel Survey (BHPS) and constructing a detailed monthly-spell dataset that tracks individuals‟ job history and tenure choice, coupled with other time-varying characteristics. Our fixed-effects estimates show that purchasing a house reduces the likelihood of starting a business by 20-25%. This result is driven by homeowners with mortgages and persists for several years after entering homeownership. The negative link can be rationalized by portfolio considerations: leveraged housing investments crowd out entrepreneurial investments. Alternative explanations based on credit constraints find little support in our data.