The causality between house prices and stock prices: evidence from seven European countries

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manuchehr Irandoust
Keyword(s):  
Stock Prices ◽  
Stock Markets ◽  
Financial Stability ◽  
Structural Breaks ◽  
Causal Structure ◽  
Housing Prices ◽  
Control Variable ◽  
European Countries ◽  
Cross Sectional ◽  
Content Type

Purpose This paper aims to examine whether there exists a long-run causal relationship between the prices of households’ two major assets: stocks and houses over the period 1975Q1–2017Q1 for seven major European countries. Design/methodology/approach The paper uses the bootstrap panel Granger causality approach to determine the causal structure, focusing on cross-sectional dependence, slope heterogeneity and structural breaks. Findings The findings show that, in most cases, there is a unidirectional causality running from stock price to house price but the converse is not true. This confirms a strong wealth effect in housing markets. The findings are important for not only households but also policymakers concerned with financial stability and housing prices. Originality/value First, the methodology used here devotes full attention to dynamic co-movement between housing and stock markets. Second, this study uses a rather long quarterly data, which implies that the findings could be robust. Third, the study uses real personal disposable income as a control variable to remove the effects of economic growth. Fourth, most of the previous studies do not consider the presence of structural breaks and this makes the result of causality invalid and biased. Fifth, most of the previous studies on housing and stock markets concentrated on the US and non-European countries such as China, Korea and Singapore.

Stock prices' long memory in China and the United States

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhengxun Tan ◽  
Yao Fu ◽  
Hong Cheng ◽  
Juan Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Long Memory ◽  
Stock Markets ◽  
Information Disclosure ◽  
Structural Breaks ◽  
Efficient Market Hypothesis ◽  
The United States ◽  
Chinese Stock Market ◽  
Content Type

PurposeThis study aims to examine the long memory as well as the effect of structural breaks in the US and the Chinese stock markets. More importantly, it further explores possible causes of the differences in long memory between these two stock markets.Design/methodology/approachThe authors employ various methods to estimate the memory parameters, including the modified R/S, averaged periodogram, Lagrange multiplier, local Whittle and exact local Whittle estimations.FindingsChina's two stock markets exhibit long memory, whereas the two US markets do not. Furthermore, long memory is robust in Chinese markets even when we test break-adjusted data. The Chinese stock market does not meet the efficient market hypothesis (EMHs), including the efficiency of information disclosure, regulations and supervision, investors' behavior, and trading mechanisms. Therefore, its stock prices' sluggish response to information leads to momentum effects and long memory.Originality/valueThe authors elaborately illustrate how long memory develops by analyzing not only stock market indices but also typical individual stocks in both the emerging China and the developed US, which diversifies the EMH with wider international stylized facts and findings when compared with previous literature. A couple of tests conducted to analyze structural break effects and spurious long memory demonstrate the reliability of the results. The authors’ findings have significant implications for investors and policymakers worldwide.

House prices and unemployment: an empirical analysis of causality

2019 ◽  
Vol 12 (1) ◽  
pp. 148-164 ◽  
Author(s):  
Manuchehr Irandoust
Keyword(s):  
Granger Causality ◽  
Financial Stability ◽  
Structural Breaks ◽  
House Prices ◽  
House Price ◽  
Cross Sectional ◽  
Content Type ◽  
Unemployment Rates ◽  
Long Run ◽  
Panel Granger Causality

Purpose This paper aims to examine whether there exists a long-run causal relationship between house prices and unemployment rates for eight major European countries. Design/methodology/approach The bootstrap panel Granger causality approach that accounts for cross-sectional dependence, slope heterogeneity and structural breaks is used to detect the direction of causality. Findings The empirical findings for the overall panel support the presence of unidirectional causality running from house prices to unemployment. Practical implications The findings are not only important for households but also for policymakers concerned with economic and financial stability. Originality/value There are only a limited number of studies that have investigated the direct link between house prices and employment or unemployment. Given the increased importance of labor market variables, particularly the choice of the unemployment rate as a key indicator in designing forward guidance and the increased financial stability concerns regarding house price dynamics, it is important to better understand the causal linkages between house prices and unemployment rates. To the best of the author’s knowledge, this paper is the first to apply the bootstrap panel Granger causality approach to examine the relationship between house prices and unemployment rates.

The co-movement and causality between housing and stock markets in the time and frequency domains considering inflation

2018 ◽  
Vol 8 (1) ◽  
pp. 92-108 ◽  
Author(s):  
Jiaojiao Fan ◽  
Xin Li ◽  
Qinghua Shi ◽  
Chi-Wei Su
Keyword(s):  
Wavelet Analysis ◽  
Frequency Domain ◽  
Causal Relationship ◽  
Time Domain ◽  
Stock Prices ◽  
Stock Markets ◽  
Housing Prices ◽  
Price Effect ◽  
Content Type ◽  
Positive Effect

Purpose The purpose of this paper is to examine the causal relationship between Chinese housing and stock markets. The authors discuss the three transmission mechanisms between the two markets: wealth effect, modern portfolio theory and credit-price effect. Moreover, the authors focus on the effects of inflation on the relationship between the two markets. Design/methodology/approach This paper uses wavelet analysis to test the housing and stock markets relationship both in the frequency domain and time domain. Findings The empirical results indicate that housing prices have a positive effect on stock prices, and these have the same effect on housing prices. Moreover, this positive effect means that stock prices have a wealth effect on housing prices and these have a credit-price effect on stock prices. Research limitations/implications These results provide information to financial institutions and individual investors in China to assist them in constructing investment portfolios within these two asset markets. Originality/value The authors first use wavelet analysis to analyze Chinese housing and stock markets and to provide information both on the frequency domain and time domain. Moreover, the authors take the inflation factor as a control variable in the causal relationship between the housing and stock markets.

Determinants of housing demand in the Erzurum province, Turkey

2014 ◽  
Vol 7 (4) ◽  
pp. 586-602 ◽  
Author(s):  
Erkan Oktay ◽  
Abdulkerim Karaaslan ◽  
Ömer Alkan ◽  
Ali Kemal Çelik
Keyword(s):  
Housing Prices ◽  
Binary Logistic Regression ◽  
Housing Demand ◽  
Outcome Variable ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Content Type ◽  
Comprehensive Survey ◽  
Income Expectations

Purpose – The main aim of this study is to determine the factors that influence the housing demand of households in Erzurum, northeastern Turkey. Housing demand is generally affected by several factors including housing prices, individuals’ income, expectations and choices and so on, as a means of its demographic and socio-psychological contexts. Design/methodology/approach – A questionnaire-based cross-sectional survey was carried out, in which the outcome variable had binary responses such as whether to invest in housing or not. A binary logistic regression analysis was performed to estimate the underlying data. Findings – The questionnaire was conducted in 2,927 households living in Erzurum city center, and 47 per cent of the respondents claimed that they would consider investing in housing in the future. The estimation results reveal that demographic or socio-economic factors that may possibly influence housing demand of the respondents are as follows: household head’s and spouse’s occupation, monthly income, the number of individuals in the family and car ownership. Originality/value – This paper involves the most comprehensive survey addressing the housing demand in the East Anatolian Region, Turkey. Additionally, this paper aims to contribute to the existing housing literature through establishing the statistical analysis of housing demand in an unstudied territory of the world.

scholarly journals Integrated management systems diffusion models in South European countries

2018 ◽  
Vol 35 (10) ◽  
pp. 2289-2303 ◽  
Author(s):  
Mónica Cabecinhas ◽  
Pedro Domingues ◽  
Paulo Sampaio ◽  
Merce Bernardo ◽  
Fiorenzo Franceschini ◽  
...  
Keyword(s):  
Integrated Management ◽  
Early Years ◽  
Iso 14001 ◽  
European Countries ◽  
Saturation Level ◽  
Management Systems ◽  
The South ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to dissect the diffusion of the number of organizations that implemented multiple management systems (MSs), considering the International Organization for Standardization (ISO) 9001, ISO 14001 and OHSAS 18001 standards (quality, environment and safety) in the South European countries: Italy, Portugal and Spain. In addition, based on the data collected, forecasting models were developed to assess at which extent the multiple certifications are expected to occur in each studied country. Design/methodology/approach Data concerning the evolution of the amount of multiple MSs in Italy, Portugal and Spain were collected for the period between 1999 and 2015. The behavior of the evolution of the number of MSs over the years was studied adopting both the Gompertz and the Logistic models. The results obtained with these two models were compared and analyzed to provide a forecast for the next years. Findings The diffusion throughout the years of the number of MSs presents an S-shaped behavior. The evolution of the amount of MSs in countries with a lower saturation level are properly fitted by the Gompertz model whereas the Logistic model fits more accurately when considering countries with a larger saturation level. Research limitations/implications The data related to the early years are not available in some of the countries. To overcome this shortcoming missing data were extrapolated from the data set provided by the annual ISO survey. Additionally, the integration level attained by each company was not assessed and, on this regard and in the scope of this paper, an integrated management system is understood as implemented when organizations have multiple MSs implemented. Practical implications The results provide a cross-sectional portrayal of the diffusion of MSs certifications in the South European countries and enable a forecast for the trend in the next years. Originality/value This study aims for the first time, to the best of the authors’ knowledge, to analyze the diffusion of multiple MSs throughout the years.

Spatial analysis of Twitter sentiment and district-level housing prices

2019 ◽  
Vol 12 (2) ◽  
pp. 173-189
Author(s):  
Christopher Hannum ◽  
Kerem Yavuz Arslanli ◽  
Ali Furkan Kalay
Keyword(s):  
News Media ◽  
Housing Prices ◽  
District Level ◽  
Future Research ◽  
Scoring Method ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
Property Prices ◽  
Price Appreciation

Purpose Studies have shown a correlation and predictive impact of sentiment on asset prices, including Twitter sentiment on markets and individual stocks. This paper aims to determine whether there exists such a correlation between Twitter sentiment and property prices. Design/methodology/approach The authors construct district-level sentiment indices for every district of Istanbul using a dictionary-based polarity scoring method applied to a data set of 1.7 million original tweets that mention one or more of those districts. The authors apply a spatial lag model to estimate the relationship between Twitter sentiment regarding a district and housing prices or housing price appreciation in that district. Findings The findings indicate a significant but negative correlation between Twitter sentiment and property prices and price appreciation. However, the percentage of check-in tweets is found to be positively correlated with prices and price appreciation. Research limitations/implications The analysis is cross-sectional, and therefore, unable to answer the question of whether Twitter can Granger-cause changes in housing markets. Future research should focus on creation of a property-focused lexicon and panel analysis over a longer time horizon. Practical implications The findings suggest a role for Twitter-derived sentiment in predictive models for local variation in property prices as it can be observed in real time. Originality/value This is the first study to analyze the link between sentiment measures derived from Twitter, rather than surveys or news media, on property prices.

US tax reform advantages the Republicans, for now

2017 ◽  
Keyword(s):  
Stock Prices ◽  
Republican Party ◽  
Financial Stability ◽  
Budget Deficit ◽  
Tax Reform ◽  
The United States ◽  
Content Type ◽  
Oil Drilling ◽  
The Us ◽  
Tax Returns

Significance The sweeping tax reform is US President Donald Trump’s first major legislative victory. Although the bill met strong opposition, and criticism from many leading economists, Trump secured support from his fellow Republican party legislators in Congress. The bill, the first major federal tax reform since 1986, passed on a partisan vote with no Democratic legislators’ support. Impacts Stock prices will rise on the tax legislation’s passage; overseas money could flow back into the United States. The new legislation accomplishes for many Trump’s goal of simplifying the annual tax returns filing process. The tax reform will increase the US budget deficit and the national debt, damaging financial stability over the medium to longer term. If the Democrats win the House or Senate in 2018, they will likely try pushing back on the tax reform. The tax reform will allow new oil drilling in Alaska and undermines parts of the ‘Obamacare’ health scheme.

scholarly journals Do the electricity price shocks influence the Sectoral Production and KSE100 Index in Pakistan? An ARDL structural breaks approach

2021 ◽  
Vol 5 (1) ◽  
pp. 17-46
Author(s):  
Abbas Khan ◽  
Muhammad Yar Khan ◽  
Abdul Qayyum Khan
Keyword(s):  
Stock Prices ◽  
Structural Breaks ◽  
Price Change ◽  
Equity Market ◽  
Electricity Price ◽  
Price Shocks ◽  
Cross Sectional ◽  
Industrial Sectors ◽  
Bound Test

This research investigates the long-term cointegration of electricity price with sectoral production and equity market in Pakistan. Fourteen major industrial sectors and the KSE100 index is taken into consideration to determine the relationship. Literature in this regard is available but this research is distinct from previous literature for it tests the sectoral production and equity market relationship with electricity price change in Pakistan. Monthly data from 1st Jan 2011 till 31st Dec 2019 is taken for fourteen sectors from the sources of Quantum Index Pakistan Bureau of Statistics (PBS) and for KSE100 index from (www.investing.com). An Auto Regressive Distributed Lag (ARDL) model and bound test for multiple structural breaks has been applied. It is found that almost the production of all industrial sectors and KSE100 index stock prices are adversely affected by the electricity price shocks both in long-term and short-term. The study suggests that management should implement a moderate monitory policy that is neither more expansionary nor contractionary. The government should provide incentives to those who successfully control energy wastage. A mixed kind of energy policy is recommended with higher weightage to the development of renewable energies to reduce foreign exchange outflow with imported furnace oil. This study is limited to the sectoral production and equity market of Pakistan. A cross-sectional research is encouraged to compare the connection between major energy costs and macroeconomic variables in different countries.

Determinants of telecommunication stock prices

2015 ◽  
Vol 42 (4) ◽  
pp. 534-548 ◽  
Author(s):  
Andros Gregoriou ◽  
Jerome Healy ◽  
Jairaj Gupta
Keyword(s):  
Developing Countries ◽  
Stock Prices ◽  
Capital Expenditure ◽  
Explanatory Power ◽  
Price Volatility ◽  
Mobile Internet ◽  
Cross Sectional ◽  
Content Type ◽  
The World ◽  
Significant Factors

Purpose – The purpose of this paper is to analyze the determinants affecting the stock prices of telecommunications firms in both developed and developing countries around the world. Design/methodology/approach – The empirical analysis is performed using panel data from 160 countries and 45 companies, covering the time period from 2000 to 2011. To identify the significant factors, company level firm-specific financial and non-financial factors have been analyzed that are expected to bear significant impact on price volatility of telecommunications stock. Findings – The test results reveal that capital expenditure and book value are the most significant factors. Dividends and debt levels only affect prices significantly in specification tests with either time-series or cross-sectional effects, whereas firms’ earnings and numbers of mobile internet subscribers do not contribute to the explanatory power of telecommunication stock price variability. Practical implications – The study sheds light to the potential investors in evaluating the risk associated with investment in stocks of telecommunications firms and take informed investment decisions. Originality/value – This is the first study that presents a comprehensive analysis of determinants affecting the stock prices of telecommunications firms in both developed and developing countries around the world.

The stock market’s reaction to accounting information: the cases of Chile and Peru

2016 ◽  
Vol 6 (3) ◽  
pp. 254-268 ◽  
Author(s):  
Mauricio Melgarejo ◽  
Eduardo Montiel ◽  
Luis Sanz
Keyword(s):  
Latin American ◽  
Stock Prices ◽  
Stock Markets ◽  
Stock Price ◽  
Small Firms ◽  
Accounting Information ◽  
Abnormal Returns ◽  
Earnings Announcement ◽  
Content Type ◽  
The Impact

Purpose – The purpose of this paper is to analyze the stock price and volume reactions around firms’ earnings announcement dates in two Latin American stock markets: Chile and Peru. Design/methodology/approach – This study uses multivariate regression analysis to determine the impact of accounting information on stock prices and volume traded around the firms’ earnings announcement dates. Findings – The authors find that quarterly earnings surprises explain stock abnormal returns and abnormal trading volumes around the earnings announcement dates in the Santiago (Chile) and Lima (Peru) stock exchanges. The authors also find that these two effects are driven by small firms. Originality/value – This is one of the first articles to study the price and volume reactions to accounting information in Latin American stock markets.

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