House Price Cycles Research Articles

A continuous spatio-temporal model for house prices in the USA

We revisit the studies on the evolution of house prices in the USA using a spatio-temporal model estimated using a Bayesian method. This method introduces a new specification of an error correction model with random effects measured continuously in space. This model allows observing the deviations from the co-integration relationship in each analyzed location and a clearer interpretation of the house price dynamics between 1975 and 2011 for 381 metropolitan areas in the USA. The results indicate the presence of a housing price cycle, consistent with the patterns observed in the analyzed period.

Macroprudential Policy in an Agent-Based Model of the UK Housing Market

This paper develops an agent-based model of the UK housing market to study the impact of macroprudential policies on key housing market indicators. This approach enables us to tackle the heterogeneity in this market by modelling the individual behaviour and interactions of first-time buyers, home owners, buy-to-let investors, and renters from the bottom up, and observe the resulting aggregate dynamics in the property and credit markets. The model is calibrated using a large selection of micro-data, mostly from household surveys and housing market data sources. We perform a series of comparative statics exercises to investigate the impact of the size of the rental/buy-to-let sector and different types of buy-to-let investors on housing booms and busts. The results suggest that an increase in the size of the buy-to-let sector may amplify house price cycles and increase house price volatility.Furthermore, in order to illustrate the effects of macroprudential policies on several housing market indicators, we implement a loan-to-income portfolio limit. We find that this policy attenuates the house price cycle.

House price cycles in Australia’s four largest capital cities

The aims of this paper are twofold. First, we propose a threshold cube equation, augmented with the optimal number of autoregressive terms, to model the likely future path of house prices in Australia’s four major capital cities. The proposed framework can be adopted to simulate house prices in other cities experiencing similar price cycles (spirals) such as London and Vancouver. Second, using a proprietary dataset not publicly available (1995m12–2015m10), we use the proposed model to simulate house prices in Brisbane, Melbourne, Perth and Sydney, which have been on a steep upward trajectory since 2013. To check the sensitivity and robustness of our results, we evaluate the model in terms of the out-of-sample accuracy for two separate 12-month periods. We find that the forecasting performance of the model appears to be reasonable. Then we use the model to provide the ex ante future path of house prices during the next twelve months (2015m11–2016m10). Although we do not seek to forecast all see-saw changes in property prices, based on the historical length of boom and bust cycles in the past, some interesting overall price paths are detected. It is observed that during the next year house prices in all capital cities will start plateauing with some likely moderate falls. This downward price adjustment is particularly more noticeable in Perth.

Long-Term Natural Cycle Momentum and Housing Price Changes in Israel, 1995–2013

Measures of price momentum, typically a moving average of previous price changes, are known to improve the predictive power of empirical price models. We introduce polynomially-smoothed price-trend derivatives as a refined momentum measure and apply them to a database of 216 consecutive months of Israeli housing prices. Over the entire housing price cycle and for phases characterized by prices that increase or decrease at an accelerating or decelerating rate, our models perform better than models with only economic fundamentals or those that add a moving average of past prices. We also show that some predictor variables that are significant over the entire housing cycle are not key predictors in all four phases; moreover, momentum is a key explanatory variable in some but not all phases of the housing price cycle.

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.

Dynamic asymmetries in house price cycles: A generalized smooth transition model

In this paper we propose a novel nonlinear model to capture asymmetries in real estate cycles. The approach involves a particular parametrization of the transition function used in the transition equation of a smooth transition autoregressive model which improves the fit in the non-central probability region. The dynamic symmetry in house price cycles is strongly rejected for the housing markets taken into consideration. Further, our results show that the proposed model performs well in a out of sample forecasting exercise.

China's housing bubble burst?

AbstractIn this paper, we developed the recursive unit root tests to identify the beginning and end of potential speculative bubbles in the Chinese housing price cycles during 2006–2013 for the 70 major cities of China. The method is best suited for a practical implementation with a time series and delivers a consistent date‐stamping strategy for the origination and termination of multiple bubbles. Simulations demonstrate that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. Overall, the results indicate that the speculative housing price bubbles in China are not bursting, and they indicate that the stationarity of the housing price level varies across the different city sizes. Between the cities, approximately one‐fourth of the bubbles have burst up to December 2013, while the first‐tier city bubble may not burst due to the urbanization process.

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.

The Dynamic Relationship Between Housing Prices and the Macroeconomy: Evidence from OECD Countries

This paper studies the dynamic relationship among house prices, income and interest rates in 15 OECD countries. We find that any disequilibrium in the long-run cointegrating relationship among these variables is corrected by the subsequent movement in house prices in most of these countries. This error-correction property of house prices implies that most of the variations in house prices are transitory, as compared to the movements in income and interest rates that are permanent, suggesting that the short-run movements in house prices are independent of the movements in income and interest rates. The results suggest that only the permanent movement in house prices, income and interest rates are associated with each other. We also find that the correlation in house price cycles across different OECD countries has changed over time with the highest correlation during the boom period of 1998–2005.

International Co-movement of Housing Price Cycles in East Asia and Greater China

This paper examines the characteristics of housing price cycles in East Asia and Greater China for the period from 2001:Q1 to 2010:Q1. We find that housing price cycles in East Asia (China, Hong Kong, Japan, Korea, Singapore, and Taiwan) are accounted for mainly by region-specific and country-specific factors. East Asia's regional housing price cycles co-move strongly with the world housing price cycle in the long run, but relatively weak co-movement is found in the short run. Housing cycles in Greater China (China, Hong Kong, and Taiwan) and Singapore co-move with Northeast Asia's regional housing price cycle in the long run, but this tendency fails to show up in the short run. Both domestic monetary and business-cycle effects are important in accounting for housing price cycles in China, Hong Kong, Japan, and Taiwan, while credit supply is crucial for Korea. Fiscal policy does not play a significant role. We find empirical evidence of a China effect in housing price cycles in Hong Kong, Taiwan, and Singapore.

Comments by Bhanupong Nidhiprabha, on International Co-movement of Housing Price Cycles in East Asia and Greater China

Bhanupong Nidhiprabha: The authors have extended the understanding of housing price cycles in East Asia by introducing two measures of dynamic co-movement based on dynamic correlation (cohesion) and time-varying dynamic conditional correlation. The problem with correlation analysis is that correlation does not necessarily imply causation. Even when the Granger causality test is used (Table 13), it does not mean causality in the usual cause–effect reasoning, because Granger causality is based on prediction criterion. There may be other factors that influence housing prices to move in tandem in East Asia, such as expectations, uncertainties, panic, or animal spirits. These factors are difficult to measure but it is not impossible to find some proxies for such expectations.The authors need to provide a convincing explanation of the co-movement of international housing prices rather than interpreting the statistical result from ten marching tables on variance decomposition in various countries. In addition, readers should be guided by the authors on how the booms started and peaked before their bust. Detailed explanations are required for different strength of the driving forces. For example, the authors should provide reasons why Germany, Taiwan, and Hong Kong have the lowest world factor determining housing price growth (Table 1). What are those country factors? Are they different from one country to another? The authors are quite right in pointing out in the last paragraph of the paper that demographic structure, supply side regulations, and socioeconomic determinants play a crucial role in determining housing prices. According to Table 13, housing prices in Taiwan is Granger-caused by China, Hong Kong, and Singapore. Therefore the China Effect is strong in “Greater China.” There is also a question on the definition of Greater China. I am wondering if the rent and housing prices are determined by the number of Chinese expatriates who work in Taiwan. A discussion of the demand and supply side constraints can make a coherent explanation supporting the Granger causality test.It is obvious from Figure 1 that the housing price cycles in Hong Kong and Singapore are synchronized and the movements reflect the world business cycle. The trade openness variable in tables showing variance decomposition actually reflect exposure to shocks transmitted from the rest of the world rather than indicating trade integration. It is well known that monetary policy, rather than fiscal policy has a direct impact on the housing sector through credit availability and cost of borrowing for long-term loans. As such, it is difficult to completely separate the monetary policy factor (broad money supply) and credit supply factors. Deposits and credits are simply on different sides of bank balance sheets. The paper provides and interesting statistical finding, but it would be more readable if the authors support the finding with more convincing arguments.

Summary of the General Discussion on “International Co-movement of Housing Price Cycles in East Asia and Greater China”

Summary of the General Discussion on “International Co-movement of Housing Price Cycles in East Asia and Greater China”

Comments by Anwar Nasution, on International Co-movement of Housing Price Cycles in East Asia and Greater China

Anwar Nasution: This paper analyzes the characteristics of international housing cycle co-movement of six East Asian countries for the period from 2001:Q1 to 2010:Q1. The six countries are China, Hong Kong, Japan, Korea, Singapore, and Taiwan. This paper is rich in econometric techniques, but does not provide a sensible explanation on what causes the cycles in each country or how the problems are linked and transmitted to other countries. The housing sector and real estate sector in general belong to the non-traded sector of the economy. The non-traded goods and services are only consumed where they are being produced and, because of this, they are neither exported nor imported.The demand for housing is affected by demographic and economic factors. In countries such as the United States, the demographic factors—the increasing demand or shortage for housing—is, among others, determined by the number of immigrants and the baby boom generation. In contract, China's one-child policy implemented in 1979 reduced the demand for housing. Originally, the main purpose of the policy was to curb the surging population to avoid potential food shortage. As in other Asian countries, a Chinese parent prefers boys over girls, who could presumably work harder on farms, earn more money, and carry the family name. Experts estimate that by 2020 there will be 30 million more Chinese men of marrying age than women. To meet the supply of brides, China now imports women from Indochina and other Asian countries (Nikkei Asian Review, 11–17 May 2015). Except from a small number of inter-marriages and flows of skilled technicians and managers, there is no large migration from one country to the others between East and South East Asia. Increasing openness of the economies in this region to international trade does not necessarily mean openness to international migration.In general, the paper discusses economic factors, such as fiscal and monetary policies, that affect both the supply and demand for housing. The 2008–09 global financial crisis suppressed external demand for export-oriented China and other Asian countries. To avoid recession, all of these countries stimulated their economies through the expansion of fiscal and monetary policies. The policy expansion was partly done through the shadow banking system, which is popular mainly in China. Most of the shadow banks in China are owned by local governments and are not regulated or supervised by the central bank. The central and local governments released undeveloped state land for the construction of new housing projects. The stimulus was not only in the form of easy credit with lower interest rates but also in homebuyer tax credits to motivate households to become homeowners. Some have more than one house to be used as investment.The paper failed to discuss the issue of how the housing sector in one country in East or Southeast Asia is transmitted to other countries in the same region. The lesson we learned from the U.S. housing crisis in 2007–08 was that it was transmitted all over the world through mortgage-backed securities. These derivatives were then sold all over the world mainly to mortgage brokers and investment bankers in Canada, the EU, and the UK. There are no such securities in relatively underdeveloped financial markets in Asia.

Business and Real Estate Price Cycles Across the U.S.: Evidence from a Vector Markov-Switching Regression Exercise

In this study, we examine whether house price cycles led or lagged business cycles in the state-level U.S. data from 1979 to 2012. We use a vector Markov-switching model to test for various lead/lag scenarios across the U.S. For the majority of the U.S. states as well as the aggregate U.S., we could not reject the hypothesis that between 1979 and 2012 house prices did not lead the economy. We find that between 2002 and 2011, house prices led the economy in 22 states and nationally. The states where prior to the 2007 recession house prices grew faster than six times the state's population growth rate were almost guaranteed to suffer the economic consequences of the pre-2007 house price decline.

Countercyclical capital regime revisited: Tests of robustness

Financial entities have been subject to risk-based capital requirements for many years. The experiences of the recent financial crisis led to heightened criticism that these rules are pro-cyclical, meaning they require insufficient capital during economic booms and excessive capital during busts. In response, recent revisions to such rules have included a countercyclical capital buffer, but it is problematic because implementation is discretionary with respect to both timing and amount on the part of regulators. An alternative rules-based countercyclical capital proposal put forth by Smith and Weiher (April, 2012. Countercyclical capital regime: a proposed design and empirical evaluation. Federal housing finance agency, working paper no. 12-2) that embodies a dynamically adjusting stress test for mortgage assets was intentionally structured to address these concerns.This paper tests the robustness of key elements of the Smith and Weiher (SW) countercyclical capital regime. Specifically, we examine each of the key design elements of the stress test, including construction of the trend line, the trough, and the time-path. We also expand on the empirical results presented by SW by showing how the resulting capital requirements might vary when their countercyclical stress test is applied using several different credit models.These tests of robustness support the conclusion that the SW countercyclical capital regime should produce capital requirements sufficient to ensure an entity would remain solvent during severe house price cycles. This conclusion is strongly supported by a test of concept of the countercyclical framework using Fannie Mae's historical book of business. If the countercyclical capital requirement had been in place during the run-up to the recent house price bubble, Fannie Mae would have been sufficiently capitalized to withstand losses it sustained in the subsequent housing crisis. This result is particularly noteworthy given that key components of the SW stress test were designed based upon pre-2002 data.

Global Liquidity, House Prices, and the Macroeconomy: Evidence from Advanced and Emerging Economies

In this paper, we first compare house price cycles in advanced and emerging economies using a new quarterly house price data set covering the period 1990–2012. We find that house prices in emerging economies grow faster, are more volatile, less persistent, and less synchronized across countries than in advanced economies (AEs). We also find that they correlate with capital flows more closely than in AEs. We then condition the analysis on an exogenous change to a particular component of capital flows: global liquidity, broadly understood as a proxy for the international supply of credit. We identify this shock by aggregating bank‐to‐bank cross‐border credit and by using the external instrumental variable approach introduced by Stock and Watson (2012) and Mertens and Ravn (2013). We find that in emerging markets (EMs) a global liquidity shock has a much stronger impact on house prices and consumption than in AEs. We finally show that holding house prices constant in response to this shock tends to dampen its effects on consumption in both AEs and EMs, but possibly through different channels: in AEs by boosting the value of housing collateral and hence supporting domestic borrowing; in EMs, by appreciating the exchange rate and hence supporting the international borrowing capacity of the economy.

Global Liquidity, House Prices and the Macroeconomy: Evidence from Advanced and Emerging Economies

In this paper we first compare house price cycles in advanced and emerging economies using anew quarterly house price data set covering the period 1990-2012. We find that house prices in emerging economies grow faster, are more volatile, less persistent and less synchronized across countries than in advanced economies. We also find that they correlate with capital flows more closely than in advanced economies. We then condition the analysis on an exogenous change to a particular component of capital flows. We find that a global liquidity shock, identified by aggregating bank-to-bank cross border flows and by using the external instrumental variable approach of Stock and Watson (2012) and Mertens and Ravn (2013), has a much stronger impact on house prices and consumption in emerging markets than in advanced economies. In our empirical model, holding house prices or the exchange rate constant in response to this shock tends to dampen its effects on consumption in emerging economies.

Dynamic Asymmetries in House Price Cycles: A Generalized Smooth Transition Model

This paper investigates dynamic asymmetries in house price cycles. We introduce an ad-hoc nonlinear model to capture real estate cycles. The suggested model involves a particular parametrization of the transition function used in the transition equation of a smooth transition autoregressive model which improves the fit in the non-central probability region. The dynamic symmetry in house price cycles is strongly rejected for the housing markets taken into consideration. Further, our results show that the proposed model performs well in a out of sample forecasting exercise.

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 ac-celeration mechanisms contribute to dilute the positive relationship between the total quantity response and the supply elasticity during a housing boom.

Recognizing the Bias: Financial Cycles and Fiscal Policy

This paper argues that asset price cycles have significant effects on fiscal outcomes. In particular, there is evidence of debt bias—the tendency of debt to increase over the cycle— that is significantly larger for house price cycles than stand-alone business cycles. Automatic stabilizers and discretionary fiscal policy generally respond to output fluctuations, whereas revenue increases due to house price booms are largely treated as permanent. Thus, neglecting the direct and indirect impact of asset prices on fiscal accounts encourages procyclical fiscal policies.