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The purpose of this paper is twofold. First, the paper examines the risk transmission between crude oil and petroleum product prices of Japan’s oil futures market. Second, it compares the performance of two tests for Granger causality using realized variance (RV) and the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model.

The author measures the daily RV of crude oil, kerosene and gasoline futures listed on the Tokyo Commodity Exchange using high-frequency data, and he examines the Granger causality in variance between these variables using the vector autoregression model. Further, the author estimates the EGARCH model based on daily data and test for Granger causality in variance between commodity futures using Hong’s (2001) approach.

The results of the RV approach reveal that the hypothesis on the existence of a mutual volatility spillover between crude oil and petroleum product markets is accepted. However, the results of the conventional approach indicate that all the hypotheses on Granger causalities in variance are rejected. The methodology based on intraday high-frequency data exhibits higher power than the conventional approach based on daily data.

This is the first paper to investigate Japan’s oil market using RV. The authors conclude that the approach based on RV is universally adoptable when testing for Granger causality in variance.

To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

The purpose of this paper is to investigate both linear and/or nonlinear effects of inflation on income inequality and to test the Kuznets hypothesis using panel data of 24 developed countries (DCs) and 66 developing countries (LDCs) observed over the period of 1990–2014.

This paper explores the short- and long-run Granger causality relationship between inflation and income inequality using the Toda and Yamamoto (1995) procedure and a Vector Error Correction Model (VECM) approach. The existence of a nonlinear relationship between inflation and income inequality is confirmed implying as inflation rises income inequality decreases. Income inequality then reaches a minimum and then starts rising again. The findings of this paper show the existence of Kuznets “U-shaped” hypothesis between income inequality and real GDP per capita in DCs group, and the existence of Kuznets’ inverted “U-shaped” hypothesis for LDCs group.

The results indicate that there is no bi-directional Granger causality between inflation and income inequality in the short-run, but, there is bi-directional Granger causality in the long-run for both the DCs and LDCs group. The results help us to assess the effectiveness of monetary policy in reducing income inequality in both the DCs and LDCs group. As a policy implication, monetary policy is often aimed at controlling the annual rate of inflation in the long-run with a short-run focus on reducing output gaps and creating employment. However, managing inflation may have implications for income inequality.

This is original research paper which analyzes the “U-shaped” and inverted “U-shaped” paths of income inequality and real GDP per capita for large sample of two group countries including developed and developing countries, respectively. Also, this paper analyzes the nonlinear relationship between inflation and income inequality in two groups. Furthermore, this paper investigates the short- and long-run relationship between variables. The results are important for policy makers.

The purpose of this paper is to investigate the dynamic relationship among Gold, Crude oil, Indian Rupee-US Dollar and Stock market-Sensex (gold, oil, dollar and stock market (GODS)) in the pre-crisis, the crisis and the post-crisis periods in the Indian context.

The authors use Johansen’s cointegration technique, Vector Error Correction Model (VECM), Vector Auto Regression, VEC Granger Causality/Block Exogeneity Wald Test, and Granger Causality and Toda Yamamoto modified Granger causality to study long-run relationship and causality.

Johansen’s cointegration test results indicate that there is a long-run equilibrium relationship among the variables in the pre-crisis and the crisis periods but not in post-crisis period. VECM results report that none of four models of the variables show long-run causality in the pre-crisis period. During the crisis period, both crude oil and Sensex models show long-run causality. However, in some cases, results indicate short-run causality. The authors find one-way causality from USD and Sensex to crude oil, and from gold and Sensex to USD. Thus, the authors conclude that the relationship among GODS is dynamic across global financial crisis.

The research findings of this study are vital to the large group of stakeholders and participants of gold, crude oil, US dollar and stock market in emerging economies like India. The results are useful to importers, exporters, government, policy makers, corporate houses, retail investors, portfolio managers, commodity traders, treasury and fund managers, other commercial traders, etc.

This study is one of its kinds as it investigates the relationship among GODS in India in different sub-periods like before, during and after the global financial crisis of 2008. None of the studies compare phase-wise relationship among GODS in the Indian context. The study contributes to the economic theory and the body of knowledge. It highlights the need to revisit the economic theory to explain the interplay mechanism among GODS.

This paper seeks to study the impact of bio‐fuel policies on oil and food futures prices from December 6, 2004 to August 1, 2008.

The daily closing prices of brent crude oil, light sweet crude oil, corn, wheat, soybeans, and rough rice futures from December 6, 2004 to August 1, 2008 are used in this research. The vector error correction model is applied in order to study the impact of bio‐fuel policies on oil and agricultural futures prices.

Unit root and cointegration tests show that the brent crude oil, light sweet crude oil, wheat, corn, soybeans, and rough rice futures are stationary and have a long‐run equilibrium relationship. Granger causality tests of the four periods shows that the causality relationship between oil futures and food futures changes over time. The first period result shows many Granger causes on several variables at a 5 percent significance level. The second period has more Granger causes at the 5 percent significance level. However, the Granger causality relationships become fewer and fewer in the third and fourth period.

This is the first paper to study the impact of the four major bio‐fuel policies of Brazil, the European Union, and the USA.

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.

This paper aims to focus on the contribution of segregated renewable energy (RE) sources such as solar, wind, bagasse, biomass, small hydropower (SHP) and waste to heat in driving sustainable industrial production in India.

This study uses non-linear modelling techniques such as quantile regression and the non-linear Granger causality test to explore the interplay between segregated RE generation and industrial production in India.

The study findings support the role of segregated RE sources generation, especially SHP and bagasse, on industrial production in India. This paper finds unidirectional non-linear Granger causality running from segregated RE sources to industrial production. Bidirectional non-linear Granger causality has been established from biomass, waste-heat to index of industrial production and vice versa, supporting an asymmetric feedback hypothesis.

The study findings will aid the energy policymaker in framing policies for RE sources, especially bagasse-based and SHP generation for the sustainable industrial growth of India.

To the best of the authors’ knowledge, this is one of the first studies to explore the role of segregated RE sources generation to drive sustainable industrial growth in India using non-linear techniques.

Asymmetric information impedes the efficiency of financial intermediation by widening the gap between lending and deposit rates. The cost of information gathering is high and often translates into high borrowing costs. Consequently, high borrowing costs may make it hard for borrowers to repay loans and increase the volume of non-performing loans – a recipe for financial instability. This study first compares the application of the simple GARCH (1,1) and BGARCH (1,1,1) models in the estimation of macroeconomic volatility and finds that the latter is more suitable for this purpose. Moreover, the choice of BGARCH (1,1,1) over the simple GARCH (1,1) implies different outcomes for Granger causality tests. This finding implies that the BGARCH (1,1,1) model minimises loss of important information when estimating macroeconomic volatility in developing countries. Second, the study uses bootstrap panel Granger causality to test the hypothesis that there is a causal relationship between financial instability and the financial intermediation spread in Southern African Customs Union (SACU). The findings support this hypothesis and underscore the importance of implementing sound macroeconomic policies for high and stable growth as well as effective monetary policy to attain and maintain low and stable prices in order to narrow the financial intermediation spread in SACU. The paper aims to discuss these issues.

This study uses bootstrap panel Granger causality to test the hypothesis that there is a causal relationship between financial instability and the financial intermediation spread in SACU.

The findings support this hypothesis and underscore the importance of implementing sound macroeconomic policies for high and stable growth as well as effective monetary policy to attain and maintain low and stable prices in order to narrow the financial intermediation spread in SACU.

Application of panel bootstrap Granger causality test to test for a casual relationship between financial intermediation spread and financial stability in the context of SACU.

The purpose of this paper is to explore the dynamic influence of WTI crude oil returns on the stock returns of China’s traditional energy sectors, including oil and gas exploitation, coal mining and processing, petroleum processing and coking, electricity, heat production and supply and mining services.

Hong’s information spill-over test and the DP Granger causality test are applied to investigate the relationship between the two markets. Moreover, a rolling window is introduced into the above two tests to capture time-varying characteristics of the influence of WTI crude oil returns.

The empirical results indicate that, first, there exists significant bidirectional linear causality between WTI crude oil returns and China’s traditional energy sectoral stock returns, but the nonlinear causality appears weaker. Second, the influence of WTI crude oil returns on traditional energy sectoral stock returns has time-varying characteristics and industry heterogeneity both in the linear and nonlinear cases. Finally, the decline of WTI crude oil prices may strengthen its linear influence on the stock returns of traditional energy sectors, while the excessive rise of market values in traditional energy sectors may weaken the linear and nonlinear influence of WTI on them.

The general nexus between international crude oil market and China’s traditional energy stock market is explored both in the linear and nonlinear perspectives. In particular, the dynamic linear and nonlinear influence of WTI crude oil returns on China’s traditional energy sectoral stock returns and its industry heterogeneity are analysed in detail.

The purpose of this study is to examine whether there is a unidirectional or a bidirectional relationship between women and the environment, and to further study the effect of women on environmental quality.

To achieve this purpose, a Granger causality test and a random effects panel data model are used to study women–environment relationship in developing countries. Error correction model (ECM) is the chosen estimation technique. A Granger causality test is used because of its frequent use in examining the existence of a unidirectional or a bidirectional relationship between two or more variables. A random effects panel data model is used as it has proven to be more efficient than the fixed-effects panel data model.

Women Granger-cause environmental quality while the opposite is not true in developing countries in the long run. This indicates the existence of a unidirectional relationship between women and the environment when the long-run relationship is considered. However, when considering the long- and short-run relationship together, the results indicate the presence of a bidirectional relationship. The empirical results of the random effects panel data model through ECM estimation indicate the positive effect of women on improving environmental quality as illustrated by the coefficient of the current change of women. This shows that women are concerned about environmental degradation. In addition, the empirical results highlight the persistence of CO₂ emissions. Results also confirm that foreign direct investment inflows lead to further environmental degradation. However, education and trade openness coefficients are found insignificant at the current period.

The research results have great implications on women empowerment, the reduction of gender bias and the increase in government expenditure on women’s education and health because of women’s positive effect in improving environmental quality.

To the best of the author’s knowledge, this is the first paper that examines the two-way relationship between women and the environment and, hence, it fills the gap present in the literature.