On the asymmetries created by the Great Recession in the US real estate market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Achille Dargaud Fofack ◽  
Serge Djoudji Temkeng ◽  
Clement Oppong

PurposeThis paper aims at analyzing the asymmetries created by the Great Recession in the US real estate sector.Design/methodology/approachThis paper uses a Markov-switching dynamic regression model in which parameters change when the housing market moves from one regime to the other.FindingsThe results show that the effect of real estate loans, interest rate, quantitative easing and working age population are asymmetric across bull and bear regimes. It is also found that the estimated parameters are larger in bull regime than bear regime, indicating a tendency to create house price bubbles in bull market.Practical implicationsSince three of those asymmetric variables (real estate loans, interest rate and quantitative easing) are related to monetary policy, the Fed can mitigate their impact on an interest-sensitive sector such as housing by engaging in a countercyclical monetary policy.Originality/valueThe estimated intercept and the variance parameter both vary from one regime to the other, thus justifying the use of a regime-dependent model.

Subject Monetary policy moves. Significance The Bank of Mexico (Banxico) increased its target interest rate by 25 basis points, to 7.25%, on December 14, responding to a similar move by the US Federal Reserve (Fed) the previous day. The hike was the first to be taken under new Governor Alejandro Diaz de Leon and pushes the rate to its highest level since March 2009. Impacts Tighter monetary policy will weigh on growth in 2018 and may hit the PRI’s electoral prospects. More expensive credit will hit consumption moderately, as interest rates remain relatively low by historical standards. The possibility of wage increases edging up will feed inflationary expectations.


2018 ◽  
Vol 10 (2) ◽  
pp. 113-153 ◽  
Author(s):  
Matthew Rognlie ◽  
Andrei Shleifer ◽  
Alp Simsek

We present a model of investment hangover motivated by the Great Recession. Overbuilding of durable capital such as housing requires a reallocation of productive resources to other sectors, which is facilitated by a reduction in the interest rate. When monetary policy is constrained, overbuilding induces a demand-driven recession with limited reallocation and low output. Investment in other capital initially declines due to low demand, but it later booms and induces an asymmetric recovery in which the overbuilt sector is left behind. Welfare can be improved by ex post policies that stimulate investment (including in overbuilt capital) and ex ante policies that restrict investment. (JEL E22, E23, E32, E43, E52, R21, R31)


2020 ◽  
Vol 34 (1) ◽  
pp. 105-124
Author(s):  
Byron Marlowe ◽  
Tianshu Zheng ◽  
John Farrish ◽  
Jesus Bravo ◽  
Victor Pimentel

PurposeThe purpose of this study was to create a more balanced, comprehensive and valid illustration of the relationships between casino gaming volume and employment during economic downturns in urban and rural locations in nondestination gaming states.Design/methodology/approachThis study analyzes gaming volumes and employment prior, during and after the recession of 2007–2009, using a time series with intervention analysis on a monthly coin in, table drop and regression analysis on employment impacts of casinos.FindingsFindings indicate that while there was a slight drop in gaming revenue and employment figures during the economic downturn, nondestination gaming locations such as Indiana proved relatively resilient to an economic downturn.Originality/valueThe Great Recession had no significant impact on gaming volume because gamblers chose to spend their more limited entertainment dollars on less expensive gaming options; in other words, casinos closer to home requiring the expenditure of fewer dollars on travel and/or hotel rooms. The current pandemic and pressures of the macro-environment again threaten the US gaming and casino market with an economic downturn and the results of this study are as timely as ever for hospitality professionals and social scientists to understand the behavior of casinos in recessionary environments.


2018 ◽  
Vol 11 (2) ◽  
pp. 244-168 ◽  
Author(s):  
KimHiang Liow ◽  
Qing Ye

Purpose This paper aims to investigate volatility causality and return contagion on nine international securitized real estate markets by appealing to Markov-switching (MS) regime approach, from July 1992 to June 2014. Design/methodology/approach An MS causality interaction model (Psaradakis et al., 2005), an MS vector auto-regression mode (Krolzig, 1997) and a multivariate return contagion model (Dungey et al., 2005) were used to implement the empirical investigations. Findings There exist regime shifts in the volatility causality pattern, with the volatility causality effects more pronounced during high volatility periods. During high volatility period, real estate markets’ causality interactions and inter-linkages contribute to strong spillover effect that leads to extreme volatility. However, there is relatively limited return contagion evidence in the securitized real estate markets examined. As such, the US financial crisis might probably be due to cross-market interdependence rather than contagion. Research limitations/implications Because international investors incorporate into their portfolio allocation not only the long-run price relationship but also the short-run market volatility connectedness and return correlation structure, the results of this MS causality and contagion study have provided valuable information on the evaluation of regime-dependent securitized real estate market risk, as well as useful guidance on asset allocation and portfolio management decisions for institutional investors. Practical implications Financial crisis is one of the key determinants of cross-market volatility interactions. Portfolio managers should be alerted of the observation that the US and the other developed securitized real estate markets are increasingly sharing “common market cycles” in recent years, thereby diminishing the diversification benefits. For policymakers, this research indicates that the volatilities of the US securitized real estate market could be helpful to predict those of other developed markets. It is also important for them to pay attention to those potential risk factors behind the amplified causality, contagion and volatility spillover at times of crisis. Finally, a wider implication for policymakers is to manage the transmission channels through which global stock market return and volatility shocks can affect the local economies and domestic financial markets, including securitized real estate markets. Originality/value Real estate investments have emerged to show low correlation with stocks and bonds and contributed to portfolio optimization. With real estate that can serve as a type of consumption commodity and an investment tool, the risk-return profile of real estate is different from that of the underlying stock markets. Therefore, the performance and investment dynamics and real estate-stock link are not theoretically expected to be similar, that requires separate empirical investigations. This paper aims to stand out from the many papers on the same or similar topics in the application of the three MS methodologies to regime-dependent real estate market integration.


Author(s):  
Francesco Papadia ◽  
Tuomas Vӓlimӓki

The central banking model prevailing before the Great Recession suffered six hits during the crisis. First, new financial stability responsibilities created dilemmas in the use of the interest rate. Second, quantitative easing blurred the borders between monetary and fiscal policy. Third, the action to support banks and, in the euro-area, peripheral sovereigns created moral hazard. Fourth, the ECB had to take on itself the task of preserving the euro. Fifth, the ECB had to participate in the so-called troika. Sixth, both the Fed and the ECB had to adopt a more global perspective. This chapter concludes that these hits have not basically jeopardized the pre-crisis central bank model. Still, four of the six hits to the pre-crisis central bank model identified above have a good probability of requiring changes in the pre-crisis model, thus some incremental adaptations to that model are proposed.


2015 ◽  
Vol 7 (1) ◽  
pp. 68-88 ◽  
Author(s):  
Robert A. Eisenbeis ◽  
Richard J. Herring

Purpose – The purpose of this paper is to examine the events leading up to the Great Recession, the US Federal Reserve’s response to what it perceived to be a short-term liquidity problem, and the programs it put in place to address liquidity needs from 2007 through the third quarter of 2008. Design/methodology/approach – These programs were designed to channel liquidity to some of the largest institutions, most of which were primary dealers. We describe these programs, examine available evidence regarding their effectiveness and detail which institutions received the largest amounts under each program. Findings – We argue that increasing financial fragility and potential insolvencies in several major institutions were evident prior to the crisis. While it is inherently difficult to disentangle issues of illiquidity from issues of insolvency, failure to recognize and address those insolvency problems delayed necessary adjustments, undermined confidence in the financial system and may have exacerbated the crisis. Research limitations/implications – Disentangling issues of illiquidity from issues of insolvency is inherently difficult and so it is not possible to specify a definitive counterfactual scenario. Nonetheless, failure to recognize and address the insolvency problems in several major institutions until more than a year after the crisis had begun delayed the necessary adjustment and undermined confidence in the financial system. Originality/value – This paper is among the first to analyze data showing the amounts of lending and the distribution of these loans across institutions under the Fed’s special liquidity facilities during the first 18 months of the financial crisis.


2014 ◽  
Vol 716-717 ◽  
pp. 474-478
Author(s):  
Yi Yang ◽  
Shan Li

Based on the housing holding cost model, this paper obtains the causes of real estate price expectations, and analyzes the four factors which affects real estate price expectations from the theory: the supply side, demand side, the local government and some main monetary policy variables. Combined with the actual situation in Chinese real estate market this paper puts forward the corresponding hypothesis. The empirical results show that the main source of housing prices driving force is the demand side, while the impact of local government on prices is not obvious; the effect of supply side and monetary policy on house prices is relatively small. The nominal interest rate has no significant effect on prices, and the real interest rate has more obvious effect. Based on the empirical conclusions, this paper puts forward the corresponding policy suggestion of houses prices expectation management.


2017 ◽  
Vol 35 (3) ◽  
pp. 321-340 ◽  
Author(s):  
Steven Laposa ◽  
Andrew Mueller

Purpose The purpose of this paper is twofold: the authors initially survey a sample of literature published after the Great Recession that address macroeconomic and commercial real estate forecasting methods related to the Great Recession and compare significant lessons learned, or lack thereof. The authors then seek to identify new models to improve the predictability of commercial real estate early warning signals regarding cyclical turning points which result in negative appreciation rates. Design/methodology/approach The authors develop a probit model to estimate quarterly probabilities of negative office appreciation returns using an alternative methodology to Tsolaco et al. (2014). The authors’ alternative method incorporates generally publicly available macroeconomic and real estate variables such as gross domestic product, office-related employment sectors, cap rate spreads, and commercial mortgage flow of funds into a probit model in order to estimate the probability of future quarterly negative office appreciation rates. Findings The authors’ models demonstrate the predictive power of macroeconomic variables typically associated with office demand. The probit model specification shows probabilities of negative office appreciations rates greater than 50 percent either as the quarterly office returns become negative, or in some cases several quarters before office returns become negative, for both the Great Recession and the recession occurring in the early 1990s. The models fail to show probabilities greater than 50 percent of negative office returns until after they occur for the recession in 2001. While this indicates need for further improvement in early warning models, the models do predict the more severe periods of negative office returns in advance, indicating the findings useful to real estate investors to monitor the changes in economic and real estate data identified as statistically significant in the results. Practical implications The Great Recession is a unique laboratory of significant contractions, recessions, and recoveries that challenge pre-recessionary real estate cycle models. The models provide guidance on which historical economic indicators are important to track, and gives a framework with which to calculate the probability that office prices are likely to decline. Because the models use macroeconomic indicators that are publicly available from at least one quarter in the past, the models or variations of them may provide real estate professionals with some indication of an impending decrease in office prices, even if that indication comes only one quarter in advance. Armed with this information, property owners, investors, and brokers can make more informed decisions on whether to buy or sell, and how sensitive their real estate transactions may be to timing. Originality/value The authors introduce several new models that examine the ability of historical macroeconomic indicators to provide early warning signals and identify turning points in real estate valuations, specifically negative office appreciation rates caused by the Great Recession. Using data from at least one quarter in the past, all the data in the models are publicly available (excluding National Council of Real Estate Investment Fiduciaries data) at the observed return quarter being predicted, which gives practitioners rational insights that can provide at least one source of guidance about the likelihood of an impending decrease in office prices.


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