The Asymmetric Wealth Effect in the US Housing and Stock Markets: Evidence from the Threshold Cointegration Model

Tsai, I‐Chun; Lee, Cheng-Feng; Chiang, Ming-Chu

doi:10.1007/s11146-011-9304-5

Cited by 77 publications

(77 citation statements)

References 29 publications

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“…Similar as above, this provides evidence for asymmetric responses to news. This is in line with previous research showing asymmetrical responses to shocks on the housing and stock markets (Copper et al 2000;McDonald et al 2000;Tsai et al 2012;Hoesli and Reka 2013). However, we find that market participants are not always responding negatively to tighter regulation news.…”

Section: Aifmdsupporting

confidence: 93%

Is Financial Regulation Good or Bad for Real Estate Companies? – An Event Study

Hoesli

Milcheva

Moss

2017

J Real Estate Finan Econ

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This study investigates how three regulatory reforms undertaken in the aftermath of the global financial crisis have affected returns of real estate companies. The three reforms are aimed at regulating different segments of the market -Basel III targets banks, and could restrict the availability of bank debt to the sector; the Alternative Investment Fund Management Directive (AIFMD) targets funds, which could increase compliance costs and reduce the potential investor pool; the European Market Infrastructure Regulation (EMIR) is aimed at derivative trading and could impact the cost of debt capital. We employ an event study methodology using daily stock returns of real estate companies and identify the regulatory events through news published in major international financial newspapers and news agencies. Our results show different responses across the three regulations. For Basel III we find support for the regulatory burden hypothesis of the bank lending channel for small real estate firms and firms with low debt-to-equity ratios as they cannot diversify their funding sources.The direct regulatory effect as tested using AIFMD announcements supports the profitbased reaction hypothesis for large firms. We also show that the news have asymmetric effects with tighter regulation news more frequently leading to significant responses in average abnormal returns (AARs) than loosening regulation news.

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Section: Aifmdsupporting

confidence: 93%

Is Financial Regulation Good or Bad for Real Estate Companies? – An Event Study

Hoesli

Milcheva

Moss

2017

J Real Estate Finan Econ

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“…First, researchers employ linear and non-linear cointegration techniques, such as Johansen, fractional, and threshold cointegration tests, to determine whether the two markets integrate with or segment from each other (Ambrose et al, 1992;Wilson and Okunev, 1999;Liow, 2006;Lin and Fuerst, 2012;Liow and Yang, 2005;Tsai et al, 2012). Policymakers (and practitioners) will respond differently, depending on whether these markets as integrated or segmented.…”

mentioning

confidence: 99%

The co-movement and causality between the U.S. housing and stock markets in the time and frequency domains

Chang

Miller

et al. 2015

International Review of Economics & Finance

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This study applies wavelet analysis to examine the relationship between the U.S. housing and stock markets over the period 1890-2012. Wavelet analysis allows the simultaneous examination of co-movement and causality between the two markets in both the time and frequency domains. Our findings provide robust evidence that co-movement and causality vary across frequencies and evolve over time. Examining market co-movement in the time domain, the two markets exhibit positive co-movement over recent decades, except for 1998-2002 when a high negative co-movement emerged. In the frequency domain, the two markets correlate with each other mainly at low frequencies (longer term), except in the second half of the 1900s as well as in 1998-2002, when the two markets correlate at high frequencies (shorter term). In addition, we find that the causal effects between the markets in the frequency domain occur generally at low frequencies (longer term). In the time-domain, the time-varying nature of long-run causalities implies structural changes in the two markets. These findings provide a more complete picture of the relationship between the U.S. real estate and stock markets over time and frequency, offering important implications for policymakers (and practitioners).

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“…As mentioned above, many previous empirical studies have analyzed the relation between the real estate and stock markets (e.g., Gyourko and Keim (1992) ;Ibbotson and Siegel (1984); Ibrahim (2010); Kapapoulos and Siokis (2005); Lin and Fuerst (2014); Liow (2006); Liow (2012); Liow and Yang (2005); Louis and Sun (2013); Okunev and Wilson (1997) ;Okunev, Wilson, and Zurbruegg (2000); Quan and Titman (1999); Su (2011);and Tsai, Lee, and Chiang (2012)). To the best of our knowledge, no studies have analyzed the causality-in-variance between the real estate and stock markets.…”

Section: Introductionmentioning

confidence: 99%

“…In this research, almost all studies have focused on the cointegration relation between the two markets. In recent years, not only a linear cointegration method but also a nonlinear cointegration method has been undertaken (e.g., Liow and Yang (2005) ;Okunev, Wilson, and Zurbruegg (2000); Su (2011);and Tsai, Lee, and Chiang (2012)). Using data from four major Asian countries (Japan, Hong Kong, Singapore, and Malaysia), Liow and Yang (2005) analyzed the relation between the securitized real estate and stock markets.…”

Section: Introductionmentioning

confidence: 99%

“…Unidirectional causality from the stock market to the real estate market was observed in Belgium and Italy, and feedback effects were discovered in France, Spain, and Switzerland. Tsai, Lee, and Chiang (2012) used nonlinear models to analyze the long-term relation between the US housing and stock markets. Empirical results demonstrated that the wealth effect between the stock and housing markets is more significant when the stock price outperforms the housing price by an estimated threshold level.…”

Section: Introductionmentioning

confidence: 99%

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