André K. Anundsen

Econometric Regime Shifts and the US Subprime Bubble

Using aggregate quarterly data for the period 1975q1–2010q4, I find that the US housing market changed from a stable regime with prices determined by fundamentals, to a highly unstable regime at the beginning of the previous decade. My results indicate that these imbalances could have been detected with the aid of real time econometric modeling and that they were caused by the sharp rise in subprime lending in the early to mid 2000s. These results are based on the detection of huge parameter non-constancies and a loss of equilibrium correction in two theory derived cointegrating relationships shown to be very stable for earlier periods. Controlling for the increased subprime exposure during this period, enables me to reestablish the pre-break relationships also for the full sample. This suggests that the US housing bubble was caused by the increased borrowing to a more risky segment of the market, which may have allowed for a latent frenzy behavior that previously was constrained by the lack of financing. With reference to Stiglitz’s general conception of a bubble, I use the econometric results to construct two bubble indicators, which clearly demonstrate the transition to an unstable regime. Such indicators can be part of an early warning system and are shown to Granger cause a set of coincident indicators and financial (in)stability measures.

Supply Restrictions, Subprime Lending and Regional US House Prices

With regard to the recent US house price cycle, we analyze how the interaction between housing supply restrictions, mortgage credit constraints and a price-to-price feedback loop affects house price volatility. Considering 247 Metropolitan Statistical Areas, we estimate a simultaneous boom-bust system for house prices, housing supply and subprime lending. The model accounts for regional differences in supply elasticities that are determined by local variations in topographical and regulatory supply restrictions. Our results suggest that tighter supply restrictions lead to both a larger house price boom and bust, and that this is due to supply restricted areas being significantly more exposed to a financial accelerator effect and a price-to-price expectation mechanism. We further find that the presence of endogenous price acceleration mechanisms contribute to dilute the positive relationship between the total quantity response and the supply elasticity during a housing boom.

Strategic sequencing behavior among owner-occupiers: The role played by sell-first movers in a housing recovery

Purpose – This article aims to study the dual search problem using data on the Norwegian housing market during the financial crisis of 2008 and begin the detailed mapping of the elements in the transmission mechanism from policy to the housing market. Moving owner occupiers face a simultaneous dual search and matching problem, as they must locate both a buyer and a seller with whom to transact. Individual agents solve this optimization under uncertainty by planning to make their bids for a new house partially conditional upon the sale of the old house. Design/methodology/approach – Norway may function as a window into a policy quasi-laboratory since the housing market was turned around in December 2008 in the midst of a worldwide financial crisis and after a year and a half of price decreases. The article proposes that one key dimension in the recovery was the reduced frequency of households with conditional demand involving sell-first strategies and acquires data to shed light on this proposition. Findin...

TESTING FOR MICRO-EFFICIENCY IN THE HOUSING MARKET: TESTING FOR MICRO-EFFICIENCY IN THE HOUSING MARKET

While aggregate house price indices display time persistence, less is known about micro persistence. This article proposes that absence of micro persistence implies that an excessively high or low sell price in one transaction is not repeated in the next transaction. We exploit a unique Norwegian data set of publically registered housing transactions between 2002 and 2014 and follow housing units over time to see if excessive prices persist or revert. In a regression with time and unit-fixed effects of sell-price-to-predicted-price ratios on previous sell-price-to-predicted-price ratios, we reject persistence and find substantial reversion. We also test for possible arbitrage opportunities in the form of excess returns. Once we control for price increases that are due to home improvements, we document that there is little scope for profitable arbitrage in excess of the market return. The overall impression is that the Norwegian housing market is relatively micro efficient.

Residential investment and recession predictability

We assess the importance of residential investment in predicting economic recessions for an unbalanced panel of 12 OECD countries over the period 1960Q1–2014Q4. Our approach is to estimate various probit models with different leading indicators and evaluate their relative prediction accuracy using the receiver operating characteristic curve. We document that residential investment contains information useful in predicting recessions both in-sample and out-of-sample. This result is robust to adding typical leading indicators, such as the term spread, stock prices, consumer confidence surveys and oil prices. It is shown that residential investment is particularly useful in predicting recessions for countries with high home-ownership rates. Finally, in a separate exercise for the US economy, we show that the predictive ability of residential investment is robust to employing real-time data.

Did US Consumers 'Save for a Rainy Day' Before the Great Recession?

The ‘saving for a rainy day’ hypothesis implies that households’ saving decisions reflect that they can (rationally) predict future income declines. The empirical relevance of this hypothesis plays a key role in discussions of fiscal policy multipliers and it holds under the null that the permanent income hypothesis is true. We find mixed support for this hypothesis using time series data for the 100 largest US Metropolitan Statistical Areas, as well as aggregate macro time series, for the period 1980q1-2011q4. That is, income is more often found to predict consumption and saving than the converse. Our modus operandi is to investigate the ‘saving for a rainy day’ hypothesis by testing (weak) exogeneity of income and consumption and by exploring the direction of Granger causality between the two series. We also give evidence that house price changes played a role in the US income and consumption dynamics, before, during and after the Great Recession.