Alper Ozun, Hasan Murat Ertugrul and Yener Coskun
The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and…
Abstract
Purpose
The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies.
Design/methodology/approach
The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method.
Findings
The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach.
Research limitations/implications
One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets.
Practical implications
The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City.
Social implications
The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice.
Originality/value
The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.
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Mohit Kumar and P. Krishna Prasanna
While the existing literature lacks a holistic approach to determining credit spreads and is limited to mostly developed countries, this study investigates credit spread…
Abstract
Purpose
While the existing literature lacks a holistic approach to determining credit spreads and is limited to mostly developed countries, this study investigates credit spread determinants and their cross-country connectedness in the context of four emerging economies in Asia by incorporating bonds, market risk, macroeconomic and global factors.
Design/methodology/approach
This study utilizes principal component analysis for dimensionality reduction and variable representation. Furthermore, we employ the dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity model to capture the cross-country credit spread connectedness between the variables.
Findings
The findings indicate that market volatilities are the most significant drivers of credit spreads, while global factors play a moderating role. Furthermore, the results provide compelling evidence of cross-country credit spread connectedness, with China as the primary transmitter and Malaysia as the primary receiver among the selected emerging economies.
Originality/value
This study addresses the limitations of previous research by extending the analysis beyond the commonly studied developed economies and focusing on emerging economies in Asia. It also employs a comprehensive approach to determine credit spread and explores cross-country credit spread connectedness in developing economies, thereby shedding light on financial risks and vulnerabilities within interconnected global financial systems.
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Matt Larriva and Peter Linneman
Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and…
Abstract
Purpose
Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and multifamily sectors.
Design/methodology/approach
The authors specify a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.
Findings
Using a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.
Practical implications
This has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.
Originality/value
This study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).
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Marcelo Rabelo Henrique, Sandro Braz Silva and Antonio Saporito
The article consists of analyzing the behavior of the determinants of the capital structure of Chilean companies between 2007 and 2016. The objective of this study was achieved…
Abstract
Purpose
The article consists of analyzing the behavior of the determinants of the capital structure of Chilean companies between 2007 and 2016. The objective of this study was achieved through a typology of research based on bibliographic, documentary, exploratory and explanatory, considering annual financial reports from Economática in the chosen period.
Design/methodology/approach
As this is a research study with a quantitative approach, the statistical tools used were descriptive analysis, Pearson correlation, variance inflation factor (VIF) and panel regression.
Findings
The results show that Chilean companies (240) have higher and costly long-term debt. These companies have high averages in current liquidity, return to shareholders, growth in sales and assets and market-to-book (MTB). Long-term debt was highlighted with an explanatory power of 85%. Current liquidity was highlighted as being significant in most of the indebtedness proposed in the survey, failing to register brands like this in expensive short-term and long-term indebtedness. It is noticed that flip flops companies are more prone to the pecking order theory (POT). The gap occupied by this study is linked to research involving South American countries, especially the Chilean market, and the determinants of the capital structure.
Originality/value
As future research, it is suggested to include other types of variables related to indebtedness and the same action for its determinants, in addition to the speed technique of adjusting corporate debts.