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This study aims to investigate whether changes in consumer interest rate, exchange rate and housing supply have permanent effects on housing inflation in Turkey.

For this purpose, data from 2010M01 to 2020M06 and changes in consumer interest rate, exchange rate, housing supply and housing inflation were used. Relationships between variables are analyzed first by the Granger causality tests and then the conditional frequency domain causality tests. The conditional frequency domain causality test specifically reveals the permanent causality between variables, whether there is a permanent effect.

According to the Granger causality test results, there are causality relationships from changes in the consumer interest rate and exchange rate to housing inflation. However, there is no causality relationship between housing supply and housing inflation. According to the conditional frequency domain causality test results, there is causality for the permanent and mid-term from changes in the consumer interest rate to housing inflation and causality for the mid-term and temporary from changes in the exchange rate to housing inflation. Additionally, it was found that there are causality relationships between changes in the consumer interest rate and changes in the exchange rate.

The first limit of the study is that only 2010M01-2020M06 months can be considered. Because the date that variables started common is 2010M01. Besides, there is a limit in the study in variables used. Many variables, both micro and macro, can be added to affect housing inflation.

Housing inflation is a remarkable issue in Turkey. There is an increase in the number of studies on the subject in recent years. For this reason, the study is trying to contribute by approaching the subject from a different angle. The most important contribution of the study is that it has not been investigated whether the determinants of housing inflation have permanent or temporary effects, which were not done in previous studies. In addition, the method used reveals how many months the effects of changes in exchange rates, consumer interest rates and housing supply on housing inflation last. Based on the findings obtained from the methods, important economic and political implications have been put forward in depth.

The purpose of this paper is to examine the price–volume relationship in the bitcoin market to validate near-stock properties of bitcoin.

Daily data of bitcoin returns, returns volatility and trading volume (TV) are utilized for the period August 17, 2010–April 16, 2017. Linear and non-linear causality tests are employed to examine price–volume relationship in the bitcoin market.

The linear causality analysis indicates that the bitcoin TV cannot be used to predict return; however, the reverse causality is significant. In contrast, the non-linear causality analysis shows that there are non-linear feedbacks between the bitcoin TV and returns. The bitcoin TV, which represents new information, leads to price changes, and large positive price changes lead to increased trading activity. Similarly, in recent periods (post-break period), the results of the non-linear causality test show a unidirectional causality from TV to the volatility of returns.

This study uses the average index value of major bitcoin exchanges. But further research on this relationship using data from different bitcoin exchanges may provide further insights into the price–volume relationship of bitcoin and its near-stock properties.

These findings from the non-linear causality analysis, therefore, suggest that investors cannot simply base their decisions on the linear dynamics of the bitcoin market. This is because new information in terms of the TV is neither linearly related to the price nor it is a one-to-one kind of relationship as most investors commonly understand it to be. Rather, investors’ decisions should be based on non-linear models, in general, and the best-fitting non-linear model, in particular.

The study examines bitcoin’s near-stock properties in a price–volume relationship framework with the help of both linear and non-linear causality tests, which to the best of the authors’ knowledge remains unexplored.

Purpose: Through globalization, financial markets have become more integrated and their tendency to act together has increased. The majority of the literature states that there is a cointegration between developed and emerging markets. How do positive or negative shocks in developed markets affect emerging markets? And how do positive or negative shocks in emerging markets affect developed markets? For this reason, the aim of the study is to investigate the asymmetric causality relationship between developed and emerging markets with Hatemi-J asymmetric causality test.

Design/methodology/approach: In this study, the Dow Jones Industrial Average (DJIA) index was used to represent developed markets and the Morgan Stanley Capital International (MSCI) Emerging Market Index was used to represent emerging markets. The asymmetric causality relationship between the DJIA Index and the MSCI Emerging Market Index was investigated using monthly data between January 2009 and April 2019. In the first step of the study, the Johansen Cointegration Test was used to determine whether there is a cointegration between the markets. In the next step, the Hatemi-J asymmetric causality test was applied to see the asymmetric causality relationship between the markets.

Findings: There is a weak correlation between developed and emerging markets. This result is important for international investors who want to diversify their portfolios. As a result of the Johansen Cointegration Test, it was found that there is a long-term relationship between the MSCI Emerging Market Index and the DJIA Index. Therefore, investors who make long-term investment plans should not forget that these markets act together and take into account the causal relationship between them. According to the asymmetric causality test results, a unidirectional causality relationship from the MSCI Emerging Market Index to the DJIA Index was determined. This causality shows that negative shocks in the MSCI Emerging Market Index have positive effects on the DJIA Index.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the asymmetrical relationship between developed and emerging markets. This study is also useful in predicting the short- and long-term relationship between markets. In addition, this study helps investors, portfolio managers, company managers, policymakers, etc., to understand the integration of financial markets.

This study investigates if the causal relationships between the exchange rates and selected inbound markets’ tourism demand are temporary or permanent, and compares market reactions in Türkiye.

Tourism demand is examined with a regional approach, focusing on the geographical markets, namely Europe, Commonwealth of Independent States (CIS) members and Asian countries, as the top inbound tourism markets, in addition to the total number of inbound tourists to Türkiye. Granger, frequency-domain causality, asymmetric Toda–Yamamoto, and asymmetric frequency-domain causality tests were employed to investigate and compare markets on exchange rate–tourism demand relationship for 2008M01-2020M02.

The results indicate that exchange rates affect European tourism demand both in the short and long run. The meaning of this Frequency Domain Causality (FDC) analysis finding shows that the exchange rate has both permanent and temporary effects on European tourists. The relationships are statistically insignificant for CIS members and Asian countries. The exchange rates also permanently affect total inbound tourism demand, but the independent variable has no short-run (temporary) effects on total demand. Asymmetric causality tests confirmed a permanent causality relationship from the positive and negative components of exchange rates to the positive and negative components of European and total tourism demand.

The Granger causality test provides information on the presence of a causal relation, while the FDC test, an extended version of Granger causality, enlightens the short- (temporary) and long-run (permanent) relationships and allows for analyzing the duration of the impact. In addition, asymmetric causality relationships are also investigated in the study. Besides, this study is the first in the literature to examine the relationship between tourism demand and the exchange rate regionally (continentally) for Türkiye.

The direction of the causality relationship between Foreign Direct Investment (FDI) and economic growth is a highly controversial issue in the literature. There are two basic approaches advocating different causal directions between FDI and growth, which are called hypotheses of FDI-led Growth and Growth-led FDI. The aim of this study is to analyze the causality relationship between FDI and economic growth in RCEP countries and thus make a new contribution to the discussions in the relevant literature. In addition, the results of the study are expected to provide important implications for the policies to be designed for economic growth based on FDI flows to RCEP countries. Thus, by examining the direction of causality between FDI and economic growth in RCEP countries, we aim to provide a new contribution to related literature and make some implications for the policy design process of economic growth in the RCEP area.

We empirically examined the direction of a causal link between FDI and economic growth in the context of Regional Comprehensive Economic Partnership (RPEC) countries in order to test the hypothesis of FDI-led growth and Growth-led FDI. Accordingly, as our main variables of interest, we incorporated the inward foreign direct investment stock to gross domestic product ratio (FDI) and gross domestic product per capita (GDP). Hatemi-J (2012) asymmetric causality test has been employed in the investigation of the direction of causality between FDI and GDP over the period of 1980–2020. Thus, unlike most of the studies investigating the direction of causality between FDI and growth using the linear causality analysis method, our study performed a nonlinear causality analysis.

Empirical results reveal that the causal relationship between FDI and national income in RPEC countries is non-linear or asymmetric . The results of the symmetric causality test for both from FDI to national income and from national income to FDI are statistically insignificant for all countries. Therefore, this finding obtained from the study provided an important guide to the econometric methods to be used in other studies to be conducted in the same region in the future. Concerning the asymmetric causality relationship from FDI to growth, positive FDI shocks are an important cause of national income in most RCEP countries. However, the effect of negative FDI shocks on national income is quite weak compared to positive shocks. Regarding the asymmetric causality relationship from growth to FDI, positive national income shocks do not create a significant causal relationship with FDI. Similarly, the effects of negative national income shocks on FDI are statistically insignificant. Overall, asymmetric causality test results reveal that positive FDI shocks have an important causal impact on economic growth in most RCEP countries. Thus, the results of econometric analysis mostly support the argument that the FDI-led growth hypothesis rather than the Growth-led FDI hypothesis in RCEP countries. Accordingly, policy-makers in most of the RCEP countries should continue to provide more incentives and facilities to multinational companies in order to ensure constant economic growth.

Our study brings a significant difference in the econometric method used compared to most of the other studies in the literature. Existing empirical studies on the direction of causality between FDI and growth mostly use standard Granger-linear causality-type tests to detect the direction of causality among FDI and growth. Unlike most of the studies in the literature, our study adopted a different methodological approach, namely the Hatemi J test to detect the non-linear causality between FDI and economic growth in RCEP countries. Therefore, this paper made a new methodological contribution significantly to the literature focusing on the causal relationship between FDI and economic growth by using a non-linear causality method rather than a linear causality one.

The purpose of this paper is to study the market efficiency, unbiasedness and the direction of causality among four agricultural commodity futures contracts for a forecasting horizon of 28 days, 56 days and 84 days which are traded at National Commodity and Derivatives Exchange Ltd.

To analyse the efficiency of futures market in Indian scenario, we focus on maize, chickpea, soybean and wheat which are among the most important agricultural commodities traded in India. In the first step, Augmented Dickey-Fuller test and nonparametric Phillips-Perron approaches have been used to examine the stationarity of all futures and spot price series. After testing the presence of cointegration in futures and spot series using Johansen’s Cointegration approach, the joint restrictions of β ₀=0, β ₁=1 and β ₁=1 on the cointegrating vectors were imposed to test whether the futures price is an unbiased predictor of spot at contract maturity. In the next step, linear Toda and Yamamoto (1995) and the nonparametric Diks and Panchenko (2006) causality tests were applied to examine the direction of causality. Finally, nonlinear test were applied on the vector error correction model (VECM) residuals to investigate whether any remaining causality is strictly nonlinear in nature.

The results of cointegration tests between futures and spot prices of the selected agricultural commodities indicated a long term relationship do exist in three out of four futures contracts. However, the Wald tests results on the cointegrating vectors indicate markets as inefficient and biased. Further, analysis of short-term relationship using alternate tests of causality do not give consistent results for same commodity series indicating that results may vary due to alternate measures and specifications. Finally, if we consider the results of Diks-Panchenko test on the filtered VECM-residuals, results provide evidence that if cointegration is taken into account; neither spot nor future leads or lags the other consistently.

The results are based on the sample of four agricultural futures commodity contracts. The study can be extended to a larger sample of contracts and relative efficiency of each contract can be explored.

There are very few studies that have explored the efficiency, unbiasedness and direction of causality using both linear and nonlinear techniques for Indian agriculture commodity futures market for different forecasting horizons.

This study aims to reveal new information about the relationship between energy consumption and economic growth for the time-varying causality.

Economic growth and renewable and nonrenewable energy consumption data of the G7 countries (Canada, France, Germany, Italy, Japan, the UK and the USA) for the 1980–2016 period were used in the study. The nonasymmetric causality test developed by Hacker and Hatemi-J (2006) and both traditional and time-varying forms of the asymmetric causality test by Hatemi-J (2012) were used as the study method.

While the study favors feedback hypothesis for renewable energy consumption in the nonasymmetric causality tests in the UK economy, it favors the same hypothesis for nonrenewable energy consumption in the US economy. However, according to the results reported by Hatemi-J (2012), the feedback hypothesis, which is supported for the UK, is supported only in positive shocks, yet not for each period of analysis. Similarly, feedback hypothesis, which is supported in the USA, is supported only in the negative shocks, yet not for each period of analysis.

This study examined that the asymmetric causality relationship between variables can be analyzed in time-varying form. Therefore, whether positive and negative shocks in renewable and nonrenewable energy consumption always provide useful information in estimations about economic growth is analyzed.

The purpose of this study is to examine whether there is a causal relationship between mortgage credit and house prices in Turkey.

Granger causality test, Toda–Yamamoto causality test, Fourier Granger causality test and Fourier Toda–Yamamoto causality tests are applied.

The findings show that there is a strong one-way causality between mortgage credit and house prices and that the developments in credit markets are more decisive in the relationship between mortgage credit and house prices than the developments in the housing markets.

Considering a causal relationship between mortgage credit and house prices may contribute to more efficient use of the tools of both macroeconomic and microeconomic policies for the mortgage credit and housing markets in Turkey. Furthermore, by understanding the importance of the direction of causality between both dynamics, it may be possible to prevent and/or mitigate the negative effects of large house price movements on both Turkish housing and mortgage markets as well as on Turkish economy.

To the best of the authors’ knowledge, the contribution of this study is to examine for the first time whether the causal relationship between mortgage credit and house prices in Turkey is mutual as well as to apply four different causality tests and to compare their results for the first time.

The purpose of this paper is to examine the causal relationship between inward foreign direct investment (FDI) and economic growth in Southern African Development Community (SADC) countries over the period 1980-2012. It also investigates whether the causal relationship between FDI inflows and economic growth is dependent on the level of income.

In order to assess whether the causal relationship between FDI inflows and economic growth is dependent on the level of income, the study divided the SADC countries into two groups, namely, the middle-income countries and the low-income countries. The study used the recent panel-data analysis methods to examine this linkage. The Granger causality test for the middle-income countries was conducted within a vector-error correction mechanism framework; while that of the low-income countries was conducted within a vector autoregressions framework.

The results for the middle-income countries’ panel show that there is a uni-directional causal flow from GDP to FDI, and not vice versa. However, for the low-income countries’ panel, there was no evidence of causality in either direction. The study concludes that the FDI-led growth hypothesis does not apply to SADC countries.

Methodology applied in this study is a bivariate framework which is likely to suffer from the omission of variable bias (Odhiambo, 2008, 2011). Second, the Granger causality analysis employed in this only investigates the direction of causality and whether each variable can be used to explain another, but does not directly test for the mechanisms through which FDI leads to economic growth and economic growth leads to FDI.

Future studies may include a third variable such as domestic savings, exports, or financial development in a trivariate or multivariate panel causality model. A more complete analysis which seeks to explain the channels through which FDI impacts growth is suggested for future studies. Lastly, sector level analysis will help policy makers draft effective industrial policies, which can guide allocation of incentives.

The results of this study support the Growth-led FDI hypothesis, but not the FDI-led growth hypothesis. In other words, it is economic growth that drives FDI inflows into the SADC region and into Southern Africa, and not vice versa. This implies that the recent high economic growth rates that have been recorded in some of the SADC countries, especially the middle-income countries, have led to a massive inflow of FDI into this region.

At the regional level, SADC as a regional bloc has been actively pursuing policies and strategies aimed at attracting FDI into the region. Despite the important role of FDI in economic development, and the increase in FDI inflows into SADC countries in particular, there is a significant dearth of literature on the causal relationship between FDI and economic growth. The study used the recent panel-data analysis methods to examine the causal relationship between FDI and economic growth in SADC countries.

In financial analysis, forecasting often involves regressing one time series variable on another. However, to ensure that the models are correctly specified, one needs to first test for stationarity, co‐integration and causality. In testing for causality, the variables should be stationary. If non‐stationary, one can estimate the model in difference form, unless the variables are co‐integrated. This article determines whether cash flow and earnings variables are stationary, and which variable causes the other, using econometric analysis. In most cases, cash flow variables are found to cause earnings variables. This is so when the models are estimated in levels. However, when estimated in first differences, the causal relationship tends to be reversed such that earnings cause cash flows. Further study is recommended, whereby panel data could be used to improve the power of the tests.