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The purpose of this study is to examine the linkages between Australian house prices and stock prices under the Toda and Yamamoto test framework. Specifically, it investigated whether there is a capital switching effect between house prices and stock prices.

This study examined the linkages between house prices and stock prices under the Toda and Yamamoto test framework. To accommodate the impact of the global financial crisis (GFC), a sub-period analysis was undertaken. To assess the impact of investor structure, the tests were also performed for small cap stocks and large cap stocks individually.

The empirical results reveal a negative lead–lag relationship between house prices and stock prices in Australia, suggesting the existence of capital switching activities between housing and stocks. The impact of the GFC on the lead–lag relationship between house prices and stock prices is also documented. Before the crisis, a causality transmission was running from house prices to stock prices, whilst stock prices appeared to lead house prices after the crisis. The capital switching activities between housing and stocks are more evident for small cap stocks.

This study is the first to examine the linkages between house prices and stock prices under the Toda and Yamamoto test framework. This is the first study to explore the impacts of the GFC on the lead–lag relationship between the two asset prices under the capital switching framework. This study is also the first to provide empirical evidence regarding the existence of capital switching activities between housing and stocks. In addition, the impact of investor structure on the interrelationship between the two asset prices is examined for the first time under the capital switching framework.

This study aims to determine whether there is an effect of internal and public debt on income inequality in Kenya for the period 1970–2018.

The relationship is examined by using the Autoregressive Distributed Lag (ARDL) model by Pesaran et al. (2001) and Toda Yamamoto causality by Toda and Yamamoto (1995).

Our findings suggest that both internal and public debt harm inequality in Kenya in the long term. Furthermore, a one-way causality from internal debt to income inequality is also obtained while no causality relationship is found to exist between public debt and income inequality. Based on these findings, the study recommends that to reduce income inequality levels in Kenya, other methods of financing other than debt financing should be preferred because debt financing is not pro-poor.

This study is unique based on the fact that no previous paper has analysed the debt and inequality relationship in Kenya. To the best of our knowledge, this will be the first study to analyse the applicability of redistribution effect of debt in Kenya. The study is also different in that it provides separate analysis for public debt and internal debt on their effects on income inequality.

This study aims to establish the relationship between house acquisitions by foreigners (HAF) and house price index (HPI) in Turkey.

Due to the nature of this study, the data spans from January 2020 to March 2022. The house price index and the number of foreign house acquisitions across three provinces: Ankara, Izmir and Bursa, and national-level data were obtained from the TurkStat database. Consumer price index (CPI) and Turkish interest rates are control variables. In addition, monthly Turkish interest rates and CPI were obtained from the investing.com and TurkStat database, respectively. Furthermore, this study used autoregressive-distributed lag and Toda Yamamoto Granger causality models to avoid analysis bias. HPI and HAF are the variables used to accomplish the objectives of this study.

This study established a short-run equilibrium between foreign house acquisitions at the provincial and national levels. The short-run deviations were adjusted faster, ranging from 57.53% to 89.24% for some provinces, while Izmir is struggling to adjust at 6.48%. Both unidirectional and bidirectional Granger causality evidence suggests that the Turkish house price index increases at the national and provincial levels. This finding suggests the need for continuous policy intervention in the Turkish housing market because house prices play a pivotal role in Turkish economic development and daily lives.

This study’s scope and single-country study are its limitations. However, those limitations make the findings appropriate for the country of the study rather than generalising the results.

The study provides empirical evidence that foreign housing acquisition contributes negatively to housing affordability in Turkey and calls for authority intervention. This is because housing is considered shelter, a fundamental need to which citizens are expected to be entitled. Most citizens are low- and medium-income earners who may be unable to afford a house out of their income if it becomes costly. Once the expenditure to secure housing exceeds 30% of their income, it is considered unaffordable.

To the authors' best knowledge, this is the first empirical study that established the influence of foreign house acquisitions on Turkish house price increases and adversely reduced house affordability by Turkish citizens. The study is the first on foreign Turkish housing acquisition that used both theory of ownership and justice motivation theory to explain HAF.

The purpose of this paper is two folds: first, to analyze the long-run relationship between terrorism and key macroeconomic indicators (GDP growth, GDP per capita, inflation and unemployment) and second, to determine the direction of causality between these variables in Pakistan.

The relationship between terrorism and various macroeconomic indicators is analyzed by applying Johansen cointegration analysis. Furthermore, the causality between terrorism and macroeconomic indicators is tested by applying Toda Yamamoto Granger causality test.

The results show that there exists a long-run relationship between terrorism and key macroeconomic indicators. Furthermore, the results suggest that there exists a bi-directional causality between terrorism and inflation. The causality between GDP per capita, unemployment, GDP growth and terrorism is unidirectional.

There is a lack of research work conducted to analyze the long-run relationship and direction of causation between terrorism and various macroeconomic indicators specifically for Pakistan. The current paper fills the gap in the literature by using sophisticated econometric techniques and recent data set to provide the evidence of the relationship between terrorism and various macroeconomic indicators.

The purpose of this paper is to examine the causal relationship between economic development and financial sector development for 28 countries at different stages of their development. The authors specifically focus on the nature of causality during economic boom and tranquil cycles.

The study uses quarterly time series panels of 17 developed and 11 emerging countries, during 1993Q1-2014Q4 with each having three sub-panels – full sample, a period of the economic uptrend (UP), and period of the economic downtrend. The authors use a univariate analysis for initial screening followed by panel unit root test, panel co-integration and causality test proposed by Toda–Yamamoto to examine the causal relationship.

The principal results suggest that for developed economies, there is a causal flow from financial sector to real sector in line with the “supply-leading” hypothesis, whereas for emerging economies, it is from real sector to financial sector, in line with the “demand-following” hypothesis. This overall relationship is strong for both emerging and developed economies during economic boom or UP cycles, but becomes weak during economic downturns or tranquil periods.

This study is different from previous studies on this issue and contributes to the existing literature in a number of ways. First, the focus of this paper revolves around identification of differential patterns in causal flows between real and financial sectors for different economies, across different economic cycles. Second, to present a robust representation of financial sector, the authors consider both banking sector and stock market parameters as the proxy for financial sector development. Third, the authors address the “stock-flow problem” in the measurement of financial variables a typical criticism of some of the previous studies. Finally, the authors use a rich sample size comprising of about 2,500 quarterly observations for each variable, with about 1,500 observations from developed and 1,000 from emerging economies.

Real estate and stocks are two major asset types in an investor’s portfolio. Therefore, this paper aims to investigate the relationship between these two markets to provide a valuable insight into the process of portfolio optimization and security selection.

This study examines the long-run relationship between residential real estate prices and stock market index in the case of Germany for the period of 2005-2017 by applying time series econometrics techniques. To this aim, this study uses Hedonic House Price Index as a proxy for real estate prices and DAX30 as a proxy for stock prices. Moreover, three additional variables, namely, consumer confidence, credit availability and supply of mortgage loans, are incorporated as control variables to assess the robustness of the results.

Obtained empirical results indicate a long-run relationship between stock prices and real estate prices which suggests that in long-run, there is no diversification benefit from allocating stock and real estate assets in a portfolio. This finding is especially important for long-term investors such as pension funds.

To the authors’ best knowledge, this is the first study that empirically investigates the relationship between the real estate market and stock prices using the Hedonic Price Index for the case of Germany.

The purpose of this study is to investigate the synergy between sectoral output, energy use and CO₂ emission with other factors for a panel of South Asian economies including Afghanistan, Bangladesh, Bhutan, India, Pakistan, Maldives, Nepal and Sri Lanka.

The analysis is done using annual panel data from 1980–2019 using dynamic ordinary least squares (DOLS), fully modified OLS (FMOLS) and Toda-Yamamoto techniques.

Empirical findings reveal the existence of a statistically significant long-run cointegrating relationship between energy use, sectoral output such as agricultural, industry and service gross domestic product (GDP), globalization, urbanization and CO₂ emission. DOLS and FMOLS result posits that in the case of the South Asian region agriculture GDP does not contribute to increasing CO₂ emission while service and industrial GDP is responsible for increasing CO₂ emission along with urban population, energy use and to some extent globalization. More remarkably, the contribution of the service GDP is greater than the other two sectoral outputs in increasing CO₂ emission with a feedback hypothesis.

As CO₂ emission is a global phenomenon with a cross-boundary effect, these empirical findings might contribute to formulating implementable energy and environmental policies to sustain growth, as well as to protect the environment in the regional context.

The study contributes to the literature by providing an empirical investigation of South Asia incorporating the contribution of sectoral output to understand the potential contribution of each sector on energy and emission. This is the first study on the South Asian context from the perspective of sectoral output, energy and emission.

This study aims to test the Malthusian and Kremer theories by exploring the relationship between population and economic growth in a low middle-income economy of India.

The autoregressive distributed lag approach is employed based on the nature of time-series data to achieve the study objectives. In this study, regressand is economic growth measured by real GDP, and the regressors are population growth rate, investment, life expectancy and inflation rate from 1980 to 2018.

Empirical results confirm the applicability of Kremer’s theory. In this theory, population growth has a significant and positive impact on economic growth in the short and long run. Moreover, investment and life expectancy variables have a positive and significant impact on economic growth, whereas inflation rate has a negative association with economic growth. Empirical results support the population-growth-driven economic growth hypothesis, which indicates that population growth stimulates economic growth and development.

Empirical findings in this study provide guides for management authorities in formulating the right and relatable policies on population growth whilst promoting economic growth and social welfare.

Achieving a desirable level of economic growth is the prime objective of every country. The role of the population in the process of economic growth and development cannot be overlooked. Malthus' and Kremer's views are opposite. Extant literature exhibits that scant research has been carried out on this significant topic in developing countries. Therefore, empirically investigating the effect of population on the growth performance of India as a developing country is necessary and will significantly contribute to the literature.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2019-0496

The purpose of this paper is to analyze cointegration and causality relationships between spot and futures markets in Turkish foreign‐exchange markets.

The research employs Bounds cointegration test and Toda‐Yamamoto causality test to detect a possible risk transmission between spot and futures markets. Time series of Turkish spot and futures foreign‐exchange markets from January 2, 2006 to March 25, 2008 on a daily basis are used for empirical analysis.

The empirical tests suggest that there is unidirectional causality running from future exchange‐rate market to spot market implying that foreign‐exchange markets have informational efficiency in Turkey.

The paper has originality in both employing Bounds test and Toda‐Yamamoto test to examine the relationship between spots and derivative markets, and in being one of the first empirical papers examining Turkish futures markets. In addition, the paper presents a guide on how Bounds and Toda‐Yamamoto tests can be applied to detect interactions among markets without data stationarity.

The purpose of this study is to investigate the dynamic relationship that exists between energy consumption, environmental pollution and per capita economic growth in Tanzania. The energy consumption is represented by electricity usage in kilowatt hours (kWh) per capita, while environmental pollution is represented by carbon emission per metric tons and economic growth by gross domestic product (GDP) per capita.

This investigation is made based on the Environmental Kuznets Curve using time series annual data from 1975 to 2013 by applying the more robust causality technique of Toda and Yamamoto non-Causality test (1995), Impulse response and Variance Decomposition, Augumented and Dickey–Fueller test and Philips and Perron Test of unit root tests.

Economic growth rate (LGDP) and energy consumption per capita (LENGY), both being unidirectional, cause environmental pollution through carbon emission (LCO₂) in Tanzania. Interestingly, after using impulse response, a significant and positive economic growth (GDP per capita) was found due to shocks from electricity per capita (energy consumption) and carbon emission (LCO₂) with time. The Variance Decomposition suggested that the percentage of the variations due to shocks or innovations of economic growth (LGDP) and energy consumption (LENGY) to carbon emission is very high and significant, accounting to 46 and 41 per cent, respectively, in 10 years to come.

The study recommends that, in the future, the relationship be examined using super-exogeneity causality tests that takes into consideration the changes in policy or regime in contrast to Toda and Yamamoto. Furthermore, the addition of other variables such as fixed capital formation and labor force, which were not considered in this study, may result in strong correlation.

The results imply that the government of Tanzania can adopt environment conservation and energy saving policies without affecting its economic growth. As a matter of fact, to put a stop to persistent environmental pollution in Tanzania, the energy saving policy should be put in place rather quickly. It is imperative that the government implements policies and strategies that ensure continuous economic growth without forsaking the environment.

Despite the increase in carbon emissions, energy consumption and economic growth in Tanzania since 2000, to date, no previous work has been done to investigate their multivariate relationship. This is the first study that uses the Toda and Yamamoto non-Causality test, Impulse Response and Variance Decomposition Analysis to investigate a trivariate relationship of the variables mentioned above.