Boom-bust Episodes Research Articles

House Price Dynamics, Optimal LTV Limits and the Liquidity Trap

Abstract This paper studies the optimal design of a macro-prudential instrument, a loan-to-value (LTV) limit, and its implications for monetary policy in a model with nominal rigidities and financial frictions. The analysis accounts for both an effective lower bound on the nominal interest rate and an upper bound on the ability of LTV limits to stimulate credit demand. The welfare-based loss function features a role for macro-prudential policy to enhance risk-sharing. Optimal LTV limits are strongly countercyclical. In a house price boom-bust episode, the active use of LTV limits alleviates debt-deleveraging dynamics and prevents the economy from falling into a liquidity trap.

House Price Dynamics, Optimal Ltv Limits and the Liquidity Trap

The inception of macro-prudential policy frameworks in the wake of the global financial crisis raises questions about the effects of the newly available policy tools and their interaction with the existing ones. We study the optimal setting of a loan-to-value (LTV) limit, and its implications for optimal monetary policy, in a model with nominal rigidities and financial frictions. The welfare-based loss function implies a role for macro-prudential policy to enhance risk-sharing. Following a house price boom-bust episode, macro-prudential policy alleviates debt-deleveraging dynamics and prevents the economy from falling into a liquidity trap. In this scenario, optimal policy always entails countercyclical LTV limits, while the response of the nominal interest rate depends on the nature of the underlying shock driving house prices.

News and noise bubbles in the housing market

Employing a non-standard VAR technique, I decompose house price movements into news and noise shocks and I analyze their macroeconomic effects in the US between 1963 and 2016. News shocks are identified as disturbances that induce a lagged permanent effect on rents, the key fundamental in the housing market, while noise shocks are assumed to move house prices without affecting rents. News shocks are the main driver of the US housing market in the long-run. However, noise shocks explain a large share of house prices volatility and they have a non-negligible effect on residential investment and GDP over short and medium horizons. Noise shocks contributed to all housing cycles since the '60s, including the boom-bust episode of 2001-2009.

Boom–bust economics and vegetation dynamics in a desert city: How strong is the link?

AbstractIn cities, human activities such as supplemental watering and plantings of ornamental species are thought to decouple vegetation diversity from biophysical processes. Consequently, socioeconomics may arguably be one of the most important factors influencing the pattern and dynamics of vegetation in urban ecosystems. Socioeconomic disturbances, like The Great Recession of 2007 to post‐2010, disrupt normal social and economic activity causing changes to the ecology of cities that have yet to be examined. Using the rapidly growing metropolitan area of Phoenix, Arizona, USA, as a case study, we explored the dynamics of residential vegetation diversity from before to after The Great Recession. Our findings linked changing plant community composition and increasing richness with socioeconomics of the housing boom, (from 2000 to 2006) followed by the Great Recession (from 2007 to post‐2010). Specifically, we found that the housing market boom–bust episode acted as a socioeconomic driver of overall plant community composition. However, plant species with annual reproduction strategies were instead linked to the previous winter's precipitation and did not respond to socioeconomic disturbance, a behavior expected in native desert plant communities, but not from constructed and managed urban plant communities. This study demonstrates how disturbances to socioeconomic components of ecosystems can result in changes to plant community diversity and dynamics; though, biophysical drivers remain important to short‐lived annual species regardless. Undertakings that aim to maintain or increase urban biodiversity for ecosystem services and human well‐being need to systematically approach the effects of socioeconomic fluctuations on urban flora. Cross‐site comparisons will be key to developing a broader understanding of these coupled dynamics across older and newer, mesic and arid, and growing and shrinking cities.

How Strong is the Case for Dollarization in Central America? An Empirical Analysis of Business Cycles, Credit Market Imperfections and the Exchange Rate

In this paper, we contrast two different views in the debate on official dollarization. The Mundell (1961) framework of optimal currency areas and a model on boom-bust cycles, by Schneider and Tornell (2004), who take account of credit market imperfections prevalent in middle income countries. We highlight that the role of the exchange rate is strikingly different in the two models. While in the Mundell framework the exchange rate is expected to smooth the business cycle, the other model predicts that the exchange rate plays an amplifying role. We empirically evaluate both models for eight highly dollarized Central American economies, and find that the main benefit of official dollarization derives from avoiding a mismatch between foreign currency liabilities and domestic revenues, as well as the boom-bust episodes that are likely to follow from it. Using a new method of Cubadda (1999, 2007), we furthermore test for cyclical comovement and reject the hypothesis that the countries form an optimal currency area with the United States according to the Mundell definition.

International Real Estate Review

Since the recent turmoil in UK housing, there has been controversy over whether house prices in the past decade have entered a bubble. While there are numerous techniques employed to investigate the presence of bubbles, testing the significance of breaks in the dynamics of prices has been utilized in other research to detect such bubbles. This is important in itself, as changing parameters in housing time series models make forecasting and portfolio management more difficult. We examine thirteen regions of the UK as well as the national home prices. The results indicate that while there were some breaks over the 2000s, more regions (and the UK as a whole) experienced breaks over the late 1980s and early 1990s. These results indicate that while there have been large price swings over the past decade, the late 1980s/early 1990s, which followed sharp changes in housing, monetary and fiscal policies, appear to be the larger boom-bust episode.

GROWTH OPPORTUNITIES, STRATEGIC SAVINGS, AND THE DOT-COM BOOM AND BUST

Data from the dot-com boom-bust episode suggest that growth opportunities played an important role in explaining firms' financing strategy during this understudied episode. The low leverage of this sector was mainly driven by high growth firms which increased their leverage following the crash despite suffering a much larger fall in their market value. We present a parsimonious dynamic firm financing model where growth opportunities alone can generate the heterogeneous patterns in the financing and performance between high and low growth information technology firms prior to and following the market crash. The calibrated model also sheds light on the role played by monetary policy during that episode. (JEL G32, E22, E5)

Imperfect Information, Lending Standards and Capital Requirements

We propose a quantitative model of lending standards with two reasons for inefficient credit: lenders' moral hazard from deposit insurance or government guarantees, and imperfect information about the persistence of asset price growth, which generates incorrect but rational beliefs in the lenders. We calibrate the model to match recent credit boom-bust episodes. Then we study which patterns of real estate price growth and banks' beliefs could serve as early warning indicators of a crisis. Finally, we propose a Value-at-Risk (VaR) rule to implement the capital requirements. The VaR framework ensures that the probability of banks not having enough equity to cover their losses is maintained at a certain level. Capital requirements should be state-contingent and lean against lenders' beliefs by tightening after periods of asset price growth. However, the relationship between asset price growth and financial risk is not monotone and this should be integrated in the setting of the capital requirements and early warning indicators.

Monitoring Housing Markets for Episodes of Exuberance: An Application of the Phillips Et Al. (2012, 2013) GSADF Test on the Dallas Fed International House Price Database

The detection of explosive behavior in house prices and the implementation of early warning diagnosis tests are of great importance for policy-making. This paper applies the GSADF test developed by Phillips et al. (2012) and Phillips et al. (2013), a novel procedure for testing, detection and date-stamping of explosive behavior, to the data from the Dallas Fed International House Price Database documented in Mack and Martinez-Garcia (2011). We discuss the use of the GSADF test to monitor international housing markets. We assess the international boom and bust cycle experienced during the past 15 years through this lens — with special attention to the United States, the United Kingdom, and Spain. Our empirical results suggest that these three countries experienced a period of exuberance in housing prices during the late 90s and the first half of the 2000s that cannot be attributed solely to the behavior of fundamentals. Looking at all 22 countries covered in the International House Price Database, we detect a pattern of synchronized explosive behavior during the last international house boom-bust episode not seen before.

Identifying Speculative Bubbles: A Two-Pillar Surveillance Framework

In the aftermath of the global financial crisis, the issue of how best to identify speculative asset bubbles (in real-time) remains in flux. This owes to the difficulty of disentangling irrational investor exuberance from the rational response to lower risk based on price behavior alone. In response, I introduce a two-pillar (price and quantity) approach for financial market surveillance. The intuition is straightforward: while asset pricing models comprise a valuable component of the surveillance toolkit, risk taking behavior, and financial vulnerabilities more generally, can also be reflected in subtler, non-price terms. The framework appears to capture stylized facts of asset booms and busts—some of the largest in history have been associated with below average risk premia (captured by the ‘pricing pillar’) and unusually elevated patterns of issuance, trading volumes, fund flows, and survey-based return projections (reflected in the ‘quantities pillar’). Based on a comparison to past boom-bust episodes, the approach is signaling mounting vulnerabilities in risky U.S. credit markets. Policy makers and regulators should be attune to any further deterioration in issuance quality, and where possible, take steps to ensure the post-crisis financial infrastructure is braced to accommodate a re-pricing in credit risk.

Identifying Speculative Bubbles: A Two-Pillar Surveillance Framework

In the aftermath of the global financial crisis, the issue of how best to identify speculative asset bubbles (in real-time) remains in flux. This owes to the difficulty of disentangling irrational investor exuberance from the rational response to lower risk based on price behavior alone. In response, I introduce a two-pillar (price and quantity) approach for financial market surveillance. The intuition is straightforward: while asset pricing models comprise a valuable component of the surveillance toolkit, risk taking behavior, and financial vulnerabilities more generally, can also be reflected in subtler, non-price terms. The framework appears to capture stylized facts of asset booms and busts—some of the largest in history have been associated with below average risk premia (captured by the ‘pricing pillar’) and unusually elevated patterns of issuance, trading volumes, fund flows, and survey-based return projections (reflected in the ‘quantities pillar’). Based on a comparison to past boom-bust episodes, the approach is signaling mounting vulnerabilities in risky U.S. credit markets. Policy makers and regulators should be attune to any further deterioration in issuance quality, and where possible, take steps to ensure the post-crisis financial infrastructure is braced to accommodate a re-pricing in credit risk.

Toxic Asset Bubble and Global Imbalances

We analyze the relationships between bubbles, capital flows, and economic activities in a rational bubble model with two open economies. An asymmetry in frictions in the credit markets causes capital to flow upstream from the South to the North. Capital inflows to the North in turn facilitate the emergence of bubbles that further exacerbate global imbalances. The collapse of these bubbles, however, precipitates a readjustment in capital flows, debt deleveraging, and sharp contractions in economic activities. The model can simultaneously explain several stylized features of recent boom-bust episodes.

How to deal with real estate booms: Lessons from country experiences

The financial crisis showed, once again, that neglecting real estate booms can have disastrous consequences. In this paper, we spell out the circumstances under which a more active policy agenda on this front would be justified. Then, we offer insights on the pros and cons as well as implementation challenges of various policy tools that can be used to contain the damage to the financial system and the economy from real estate boom–bust episodes. These insights derive from econometric analysis, when possible, and case studies of country experiences. Broadly, booms financed through credit and involving leverage are more likely to warrant a policy response. In that context, macroprudential measures can be targeted more precisely to specific sources of risk, but they may prove ineffective because of circumvention. In that case, monetary policy may have to be used to lean against the wind.

A Robust Model of Bubbles With Multidimensional Uncertainty

Boom-bust episodes in asset markets have often been interpreted by observers as speculative frenzies where asymmetrically informed investors buy overvalued assets hoping to sell to a greater fool before the crash. While intuitively appealing, this notion of speculative bubbles has been difficult to reconcile with standard economic theory. Existing models of speculation have been criticized on the basis that they assume irrationality, that prices are somewhat unresponsiveness to sales, or that they depend on fragile, knife-edge restrictions. To address these issues, I construct a rational version of Abreu and Brunnermeier (2003), where agents invest growing endowments into an asset, fueling appreciation and eventual overvaluation. Riding bubbles is optimal as long as the price grows quickly and there is a probability of exiting before the crash. This probability increases with the amount of noise in the economy, as random price flucutations make it difficult for agents to infer sales from the price.

Mortgage Defaults

A model of mortgage defaults is built into the standard incomplete markets model. Households face income and house-price shocks and purchase houses using long-term mortgages. Interest rates on mortgages are determined in equilibrium according to the risk of default. The model accounts for the observed patterns of housing consumption, mortgage borrowing, and defaults. Default-prevention policies are evaluated. The mortgage default rate, housing demand, households’ ability to self-insure, and welfare are hump-shaped in the degree of recourse (the level of defaulters’ wealth that can be garnished). Two forces affect default. More recourse implies that the punishment for default is harsher; this reduces the default rate. But more recourse also decreases the interest rates offered; this increases borrowing and the default rate. Introducing loan-to-value (LTV) limits for new mortgages contains borrowing, lowering the default rate with negligible negative effects on housing demand. The combination of recourse mortgages and LTV limits reduces the default rate while boosting housing demand. The behavior of economies with alternative prudential regulations is evaluated during a boom-bust episode in aggregate house prices. In the economy with both recourse mortgages and LTV limits, the mortgage default rate is less sensitive to fluctuations in aggregate house prices.

Financial Factors in the Boom-Bust Episode in Finland in the Late 1980s and Early 1990s

This paper proposes a framework for studying the boom and bust in Finland in the late 1980s and early 1990s. We develop a small open economy DSGE model with balance sheet-constrained firms a la BGG and calibrate it to the Finnish economy. We use the model to simulate three events that are claimed to have played a key role in the Finnish boom-bust episode and compare the model outcome with actual Finnish data. Firstly, we assess in our DSGE framework the role of financial market deregulation in the 1980s in the boom that preceded the crises. Secondly, we use our model to evaluate the negative impact of the collapse of Soviet-Finnish trade at the beginning of 1991. Thirdly, we investigate the effect of the collapse of the fixed exchange rate regime in September 1992. We conclude that financial frictions combined with the shocks that hit the Finnish economy are able to produce a boom and a severe depression similar to the one observed in Finland in the late 1980s and early 1990s. A key finding is the crucial role played by the financial accelerator mechanism in the ability of the model to mimic the response of the Finnish economy to the shocks it encountered. A key contribution is the incorporating unconventional shocks into the model: domestic financial market shocks to capture the deregulation of the financial market; a capital obsolescence shock to model the sudden redundancy of Soviet-oriented manufacturing; and a shock from the international financial market, a country borrowing premium shock, to capture the collapse of the fixed exchange rate regime.

Housing Cycle and Interet Rate

The most recent boom-bust episode in the housing market and its unprecedented negative repercussions on the overall economy led to a debate on its possible causes. The common assumption underlying the debate is that interest rates were the main driver of the bubble in house prices. However the empirical literature provides merely inconclusive evidence on the dominant role of interest rates in house price dynamism. Based on a comprehensive review of the existing literature combined with the author's own reasoning and observation, a hypothesis is elicited that not only interest rates but also expectation play major roles in rendering house prices more volatile than otherwise. To check for the validity of it, a different regression strategy from common empirical models is adopted employing the volatile components of house prices as a dependent variable instead of house prices themselves. The empirical results using the U.S. data are consistent with the hypothesis confirming the primacy of interest rates in generating house price fluctuations and the importance of expectation channel transmitting the effects of interest rates.

Understanding Booms and Busts in Housing Markets

Some booms in housing prices are followed by busts. Others are not. It is generally difficult to find observable fundamentals that are useful for predicting whether a boom will turn into a bust or not. We develop a model consistent with these observations. Agents have heterogeneous expectations about long-run fundamentals but change their views because of “social dynamics.” Agents with tighter priors are more likely to convert others to their beliefs. Boom-bust episodes typically occur when skeptical agents happen to be correct. The booms that are not followed by busts typically occur when optimistic agents happen to be correct.

Capital Flows to EU New Member States: Does Sector Destination Matter?

The recent boom-bust episode in Emerging Europe was largely the product of surges and sudden stops in capital inflows. This paper empirically argues that the sectors into which capital flows determines their impact on GDP growth. Applying data from EU New Member States, it is found that capital flows into real estate have a greater impact on swings in GDP than other sectors, irrespective of a country's exchange rate or fiscal policy. Consequently, as new waves of capital inflows spread to emerging markets, policies may usefully focus on supporting capital inflows towards economic sectors that minimize large swings in GDP.

How to Deal with Real Estate Booms: Lessons From Country Experiences

The financial crisis showed, once again, that neglecting real estate booms can have disastrous consequences. In this paper, we spell out the circumstances under which a more active policy agenda on this front would be justified. Then, we offer tentative insights on the pros and cons as well as implementation challenges of various policy tools that can be used to contain the damage to the financial system and the economy from real estate boom-bust episodes.