Housing price variability: national and local impacts

This article examines the influence of national and local forces on housing prices in 20 local US real estate markets during the recent housing price run-up and decline. We use reduced-form panel data fixed-effects models with robust SEs to determine the impact of national and local effects on housing prices in 20 US cities across time. A national home price index and mortgage rate are used to measure national impacts on the local markets. A mix of socio-economic variables estimates local impacts. We find no results indicating that national trends lack relevance in local markets; however, we find wide support for the additional inclusion of local socio-economic factors in all markets. The findings are consistent with an environment in which national polices and trends influence all markets; however local policymakers and investors can continue to expect geographic differences in market outcomes.     

Real estate markets and the macroeconomy: A dynamic coherence framework

This paper analyzes the dynamic interactions between real estate markets, in the US and the UK and their macroeconomic environments. We apply a new approach based on a dynamic coherence function (DCF) to study these interactions bringing together different real estate markets (the securitized market, the commercial market and the residential market). The results suggest that there is a common trend that drives the different real estate markets in the UK and the US, particularly in the long run, since they have a similar shape of the DCF. We also find that, in the US, wealth and housing expenditure channels are very conductive during real estate crises. However, in the UK, only the wealth effect is significant as a transmission channel during real estate market downturns. In addition, real estate markets in the UK and the US react differently to institutional shocks. This brings some insights on the conduct of monetary policy in order to avoid disturbances in real estate markets.     

A national or local phenomenon? A comparison of the US and the Chinese housing markets

This article investigates the common movements of house prices across cities as well as the macroeconomic underpinnings of the comovements in the US and China. Our empirical results indicate more differences than similarities between the US and the Chinese housing markets. The results from a Bayesian dynamic latent factor model indicate that the fluctuations of house prices across cities in the US are more a national phenomenon, while the dynamics of house prices across cities in China are mainly driven by the city-specific component. We further use VAR models to compare the roles of the underlying determinants in these two housing markets. The results show that the roles of monetary policy shocks and aggregate fluctuations in driving the common movements of house prices across cities differ substantially between the US and China at both short and long horizons.     

Foreign News and Spillovers in Emerging European Stock Markets

We analyze foreign news and spillovers in the emerging EU stock markets (the Czech Republic, Hungary, and Poland). We employ high‐frequency five‐minute intraday data on stock market index returns and four classes of EU and US macroeconomic announcements during 2004–07. We account for the difference of each announcement from its market expectation and we jointly model the volatility of the returns accounting for intraday movements and day‐of‐the‐week effects. Our findings show that intraday interactions on the new EU markets are strongly determined by mature stock markets as well as the macroeconomic news originating thereby. We show that strong contemporaneous links across markets are present even after controlling for macroeconomic announcements. Finally, in terms of specific announcements, we are able to show the exact sources of macro news spillovers from the developed foreign markets to the three new EU markets under research.     

Financial cycles in asset markets and regions

This paper provides a comprehensive analysis of financial cycles in asset markets and regions. Using a large sample of 38 advanced and emerging economies to enable a comparative assessment, the analysis conforms with the prevailing literature pertaining to the characterization of financial cycles in advanced economies, but finds that equity market cycles in emerging market economies (EMEs) in Asia, Latin America, and Eastern Europe may be a more useful gauge of the financial cycle compared to cycles in credit and property markets. Similar to more advanced economies, it is found that financial and business cycles in emerging economies are synchronized, albeit partially and with some cross-country heterogeneity. This underscores the importance for policy makers to be vigilant of interlinkages between real and financial sectors, pointing toward a need for carefully designed macroprudential policies. Finally, it is found that financial cycles in emerging markets remain vulnerable to global risk aversion in financial markets and spillovers from the US, thereby reinforcing the importance of continuing to strengthen domestic macroeconomic fundamentals, and develop further local financial sectors through targeted structural reforms.     

Expected risk and excess returns predictability in emerging bond markets

This study examines the predictability of expected excess returns from eight emerging bond markets within an international asset pricing framework. Two sets of instruments are used, which include both world and local factors, to forecast emerging bond returns. Besides investigating the influence of the macroeconomic factors in specific countries on bond returns in those countries, this study also divides local factors into macroeconomic and financial factors. Unlike previous studies, we apply macroeconomic instruments that contain more information on excess returns as a proxy for local risk factors via principal component analysis methodology. The information variable approach enables the prediction of excess bond returns based on world and local factors and facilitating understanding of the degree of integration between emerging bond markets and developed bond markets. The results indicate that the bond market in emerging world is partially integrated to that in the developed world and the predictability of local factors that include both financial and macroeconomic information variables can forecast around 25–66% of the returns of emerging bonds. Incorporating the macroeconomic variables increases the explanatory power of the model. Both world and country-specific local instruments can forecast excess bond returns, but local instruments appear to be better predictors of such returns, particularly the local credit spread to US. Additionally, this study finds that investor risk aversion is significant among most of sample countries.     

Which News Moves the Euro Area Bond Market?

Abstract. This paper explores a long dataset (1999–2005) of intraday prices on German long-term bond futures and examines market responses to major macroeconomic announcements and ECB monetary policy releases. German bond markets tend to react more strongly to the surprise component in US macro releases compared with aggregated and national euro area and UK releases, and the strength of those reactions to US releases has increased over the period considered. We also document that the numbers of German unemployed workers consistently have been known to investors before official releases.     

House price dynamics,conditional higher-order moments,and density forecasts

Most studies on housing price dynamics are only concerned with the conditional mean and variance, but overlook other higher-order conditional moments and the structural change characteristics inherent in housing prices. In order to take into account these two important issues, this study utilizes the generalized Markov switching GARCH model to explore house price dynamics and conditional distribution for US market over 1975Q1–2007Q4. The housing return follows two distinct dynamics: the bust regime and the boom regime. The volatility pattern is different in the bust and boom regimes. In addition, the conditional densities derived by the regime-switching model change dramatically over time and are significantly different from normal distribution. More importantly, the regime-switching model can detect in advance a weak US housing market such as the one that occurred in the middle of 2007. The in-sample fitting ability of regime-switching model, which incorporates higher-order moments, has significant improvements compared to the single-regime AR and AR-GARCH models. For the out-of-sample Value-at-Risk forecasting performance, the ability of regime-switching AR-GARCH model to forecast one-step-ahead density is better compared to the single-regime AR-GARCH model.     

The impact of foreign macroeconomic news on financial markets in the Czech Republic, Hungary, and Poland

In this paper, we investigate the effects of euro area and US macroeconomic news on financial markets in the Czech Republic, Hungary, and Poland (CEEC-3) from 1999 to 2006. Using a GARCH model, we examine the impact of news on daily returns of 3-month interest rates, stock market indices, exchange rates versus the euro, and the US dollar. First, both US and European macroeconomic news has a significant impact on CEEC-3 financial markets. Second, the process of European integration is accompanied by an increasing importance of euro area news relative to US news. Third, there are country-specific differences: for example, the Czech stock market is relatively more affected by foreign news since the Copenhagen Summit in December 2002. In general, our results support the hypothesis of a deepening euro area influence on the CEEC-3 over time and a corresponding reduction in the relative importance of US shocks.     

Housing and credit market shocks: Exploring the role of rule-based Basel III counter-cyclical capital requirements

This paper examines the extent to which the Basel III bank capital regulation attenuates fluctuations in housing and credit markets and fosters financial and macroeconomic stability. We use a positive housing demand shock to mimic a housing market boom and a negative financial shock for credit squeeze and economic meltdown. The results show that the rule-based Basel III counter-cyclical capital requirement effectively attenuates fluctuations in housing and credit markets and prevents bubbles. In the case of a negative financial shock, it significantly reduces the magnitude of economic meltdown. Our analysis of the transition from Basel II to Basel III suggests that it is the counter-cyclical capital buffer that effectively mitigates the pro-cyclicality of its predecessor, while the impact of the conservative buffer is marginal. In contrast to the credit-to-GDP ratio, the optimal policy analysis suggests that the regulatory authority should adjust the capital requirement to changes in credit and output when implementing the counter-cyclical buffer. Future research could extend the study by comparing the effectiveness of the rule-based Basel III with other macroprudential tools in achieving financial and macroeconomic stability.     

The limited usefulness of macroeconomic Bayesian VARs when estimating the probability of a US recession

The Bayesian VAR model provides a convenient tool for generating predictive densities and making probability statements regarding the future development of economic variables. This paper investigates the usefulness of standard macroeconomic Bayesian VAR models to estimate the probability of a US recession. Defining a recession as two quarters in a row of negative GDP growth, the probability is estimated for two quarters of the most recent US recession, namely 2008Q3–2008Q4. In contrast to judgemental probabilities from this point in time, it is found that the BVAR assigns a very low probability to such an event. This is true also when survey data, which generally are considered as good leading indicators, are included in the models. We conclude that while Bayesian VAR models are good forecasting tools in many cases, the results in this paper raise question marks regarding their usefulness for predicting recessions.     

Speculative bubbles or market fundamentals? An investigation of US regional housing markets

This paper investigates the existence of speculative bubbles in the US national and 21 regional housing markets over three decades (1978–2015). A new method for real-time monitoring exuberance in housing markets is proposed. By taking changes in the macroeconomic conditions (such as interest rate, per-capita income, employment, and population growth) into consideration, the new method provides better control for housing market fundamentals and thereby it is expected to significantly reduce the chance of false positive identification. Compared with the method of Phillips et al. (2015a, 2015b), the new approach finds a dramatic reduction in the number of speculative housing markets and shorter bubble episodes in the US. It locates only one bubble episode in the early-to-mid 2000s over the whole sample period in the national housing market. At the regional level, it identifies two periods of speculation: late 1980s and early-to-mid 2000s. The early-to-mid 2000s bubble episode lasts longer and involves 16 metropolitan statistical areas.     

The impact of housing market disturbances on the US financial system: a pre-crisis analysis

A common critique of the Federal Reserve over the past crisis is that it should have better anticipated the impact of the run-up in home mortgage debt and the subsequent housing market crash on the financial system. As a result, the Federal Reserve should have moved much more quickly to shore up financial markets. Our article tests the hypothesis that the impact of the housing market crash on the financial system could have been anticipated. Using a VAR model along with impulse response functions and variance decompositions, we examine the link between housing market mortgage debt shocks and the financial intermediaries’ credit market behaviour. We find important connections between key macroeconomic variables and the credit behaviour of these financial institutions. However, using the pre-crisis data, we find that housing market debt shocks fail to have an impact on the credit markets accessed by these firms. These results support the notion that the impact of this crisis on the financial system could not have been anticipated given the information available at the time.     

Global capital markets,housing prices,and partisan fiscal policies

In recent years, global imbalances have channeled the excess savings of surplus countries toward the real estate markets of deficit countries. By consequence, the deficit countries that attracted lots of foreign capital experienced large run‐ups in house prices, whereas most surplus countries that exported capital exhibited flat or slow house price growth. We first use new house price data and a novel instrumental variable design to show the causal relationship between housing prices and capital inflows, particularly through debt bonanzas. We then argue that international capital flows affect the fiscal policy preferences of both voters and political parties by way of their impact on housing prices. Where capital inflows are large and housing prices are rising, we expect voters to respond by demanding both lower taxes and less publicly‐provided social insurance because rising house prices allow homeowners to self‐insure against income loss. In contrast, declining house prices produce greater demands for social insurance, particularly among those most exposed to housing market risk. We present evidence from two cross‐national surveys that supports these claims, as well as a “before and after” analysis of the housing crash in Eastern Europe. We also show that the connection between house prices and social policy also manifests itself in government spending outcomes, mediated by partisan control.     

A New Approach to Predicting Recessions

This paper presents a new approach to recession prediction. The methodology relies on the shape of the yield curve alone and does not incorporate macroeconomic information or other explanatory variables. This makes the modelling framework less data intensive and more intuitive than other models that have the same goal. The workhorses of the approach are (i) data transformation of observed yields with the purpose of normalizing the yield spread, and (ii) a three-state regime-switching version of the Nelson–Siegel parametric model of the yield curves' shape and location. In an out-of-sample exercise the model predicts all US NBER recessions from 1973 to 2004 at least eight months in advance of their occurrences.     

Global imbalances and asymmetric returns to US foreign assets: fitting the missing pieces of the US balance of payments puzzle

The issue of whether the US earns a persistently higher return on its foreign direct investment (relative to returns to foreign-owned direct investment in the US) has received considerable attention but little closure in the ‘global imbalances’ debate. Measuring the rate of returns to US direct investment abroad and foreign direct investment in the US we find higher returns to US foreign direct investment relative to its foreign counterparts in the US. Given the evidence indicating higher returns to US direct investment overseas, we link the irresolution in the contemporary literature regarding the existence of these returns to the unsettled debate over the origin of global imbalances. Reviewing the macro-financial literature on global imbalances, we find a failure to acknowledge that the US current account deficit is, in part, the outcome of transnational production networks in a global economy under-pinned by dollar hegemony. Given the growth in US multinational supply chains, we argue that the US trade deficit is consistent with asymmetric returns to US direct investment and that the sustainability of these return differentials rests on the stability of the status quo.     

Forecasting the US real house price index: Structural and non-structural models with and without fundamentals

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its downturn in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data sets — extracting common factors (principle components) in factor-augmented vector autoregressive or Bayesian factor-augmented vector autoregressive models as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive model. We compare the out-of-sample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). In addition, when we use simple average forecast combinations, the combination forecast using the 10 best atheoretical models produces the minimum RMSEs compared to each of the individual models, followed closely by the combination forecast using the 10 atheoretical models and the DSGE model. Finally, we use each model to forecast the downturn point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a downturn with any accuracy, suggesting that forward-looking microfounded dynamic stochastic general equilibrium models of the housing market may prove crucial in forecasting turning points.     

Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets

This study investigates the dynamic conditional correlations (DCCs) between eight emerging East Asian stock markets and the US stock market and analyses the dynamic equicorrelation among these nine stock markets. We find a significant increase in the conditional correlations and equicorrelation in the first phase of the global financial crisis. We refer to this finding as contagion from the US stock market to the emerging East Asian markets. We also find an additional significant process of increasing correlations and equicorrelation (herding) in the second phase of the global financial crisis. Further, we employ two new models, namely DCCX-MGARCH (a DCC Multivariate GARCH model with exogenous variables) and DECOX-MGARCH (a dynamic equicorrelation multivariate GARCH model with exogenous variables), to identify the channels of contagion. We find that an increase in the VIX Index increases the conditional correlations and equicorrelation, while increases in TED spreads decrease the conditional correlations of six emerging East Asian countries with the USA. We compare the accuracy of the conditional correlation estimates of the DCC and DCCX models (or DECO and DECOX models) by constructing a loss function. We find that the DCCX (DECOX) model provides more accurate conditional correlation estimates than the DCC (DECO) model by extracting additional information from exogenous variables.     

The static and dynamic connectedness of environmental,social, and governance investments: International evidence

We investigate the connectedness of the most significant global equity indices that comprise companies with the highest environmental, social, and governance (ESG) performance. Motivated by the rapid growth of socially responsible investing during the last two decades, we examine whether these investments are prone to similar exogenous economic and financial shocks as their conventional counterparts. Employing a variety of influential macroeconomic and financial variables over the period 10/1/2007–4/15/2020, we document statistically significant and consistent transmissions between the employed equity indices throughout the sample period. In particular, the connectedness exhibits dynamic patterns during three periods: the European sovereign debt crisis, the systemic Greek problems, and the outbreak of the coronavirus pandemic. We also find that developed equity markets are the shock transmitters to Asian and other emerging markets. Our results highlight the risk of contagion and the diminishing portfolio diversification benefits of these equity indices during turbulent periods.     

Speculative trading in Chinese housing market: a panel regression method

ABSTRACT

The major Chinese cities experienced dramatic increases in their house prices in the recent years. This paper derives the fundamental value of the housing markets based on the personal disposable income of individual cities. By controlling macroeconomic variables and government intervention, we detect speculative trading based on fundamental value and historical price movements. Fundamentalists expect house prices to converge to the fundamental values while chartists hold a momentum trading expectation. Further differentiating the cities into tier-1 and non-tier-1, the non-tier-1 cities are found to be subject to a risk of plummeting arising from the interaction terms between the fundamentalists and chartists.