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Introduction: Monetary policy resolutions issued by central banks play effective role in economy when accompanied with interest variable. In Keynesian approach to finance, interest is treated as the main determinant underlying financial policy resolutions. Thus interest is a pivotal factor in monetary transmission mechanism. Tight monetary policy practices, essentially decreasing money supply, eventually lead to a slump in investments, total demand and national income due to the increase in real interest rates.

Objective: The aim of this study is to determine what type of effects do monetary policy practitioner in Turkey have on macroeconomic variables via the interest channel of monetary transmission mechanism.

Methodology: Based on this objective, variables that could help in unveiling CBT overnight interest rates, direct fixed capital investment (GSSO), real gross domestic product (RGDP), industry production index (SUE) and domestic producer price index (YUFE) variables and that could explain monetary functions of transmission mechanism’s interest channel were selected. For the variables constituting the research topic, collected data belong the period of 2003Q1–2018Q3.

Findings: In the study relation between the variables has been analyzed under two parts via harnessing Toda–Yamamoto casualty test. In the first part, results of Toda–Yamamoto causality test from RGDP, GSSO and interest rate (FO) variables have been presented. The results manifest that interest channel directly affects direct fixed capital investment and RGDP. Interest channel was found to be effective on these variables of the analysis. In the second part, Toda–Yamamoto causality test was harnessed for SUE, YUFE and FO variables. Interest channel did not provide a result that affected YUFE and SUE.

The purpose of the paper is to investigate the causal relationships and speed of adjustment of stock prices to changes in macroeconomic information (MEI) in Ghana from 1996 to 2018 using monthly data. The paper seeks to conduct the investigation at individual MEI level rather than the composite MEI.

Quantitative approach was used in this paper. Monthly data span of 1996–2018 was used. The delay and half-life technique was used to determine the speed with which the information resulting from the changes in the macroeconomic are evident in the stock price. Thereafter, Toda–Yamamoto Granger no-causality approach was used to examine the causal relationship amongst variables.

The paper revealed that although the market adjustment to MEI has improved, the speed is till slow. The exchange rate exhibited the slowest speed in respect of the market reaction while the market reaction to money supply was the fastest. Toda–Yamamoto Granger no-causality estimation also revealed a bi-directional causality between MEI (gross domestic product, interest rate and money supply) and stock price and uni-directional relationship flowing from MEI (the exchange rate and foreign direct investment) to stock price. The paper also found no causality between inflation and stock price.

The findings although revealed improved level of market efficiency in comparison with the earlier data, the speed of adjustment is still undesirable. Rigorous approach should be adopted for the implementation of major reforms such as alternative market so as to increase the number of share listing and to increase the scope of investors' participation to enhancing trading volume and marketability and ultimately speed up information diffusion.

The practical implication of the low level of information processing rate of Ghana Stock Exchange (averagely more than a month) is that astute investors and market analysts could employ MEI to outperform the market prior to their infusion onto the stock market.

This study is one of the few studies in the Ghanaian literature that has extended the investigation of the speed of adjustment beyond composite or aggregate macroeconomic level estimation to estimation at individual variable level. This contribution is very relevant since each macroeconomic variable has unique characteristics and require specific policy framework, it is important to consider the speed of adjustment from the perspective of each of the individual variables.

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 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.

This study aims to answer the following questions which have not been investigated in the literature to the best knowledge: Is there any bubble in the German housing sector between 2005–2009 and 2012–2017? and Is there any linkage between economic policy uncertainty and the housing sector price index?

This study aims to shed some light on the German’s housing sector by investigating the housing sector bubble and the causal link between the housing sector index and economic policy uncertainty in Germany, using GSADF, Granger causality, Toda Yamamoto causality and wavelet coherence tests.

The findings reveal that there are some bubbles in the housing sector in Germany for the periods investigated, there is a positive correlation between economic policy uncertainty and housing sector price index at different frequencies and different periods and between 2008 and 2009 and between 2011 and 2013, economic policy uncertainty leads housing sector price index. The consistency of the findings from wavelet coherence is confirmed by the outcomes of Granger causality and Toda Yamamoto causality tests.

To the best knowledge, this is the first study that empirically investigates the relationship between the housing sector and EPU using a novel wavelet econometric method. In addition, this paper extends the research focused on the associations between the housing sector and EPU, by checking the bubbles in the market in different time horizons by using the longest available data span. Furthermore, the consistency of the findings from wavelet causality is confirmed by the outcomes of Granger causality and Toda Yamamoto causality tests. Finally, compared to the previous literature on the relationship between housing and EPU, the study uses a hedonic index for housing for the first time in the case of Germany.

This study aims to close a gap in the relevant literature by investigating the causal linkage between financial risk (FR) and economic risk (ER) in China for the period 1985Q1–2018Q4.

Based on the aim of the present study, Toda Yamamoto causality and wavelet coherence tests are used to capture the relationship between FR and ER in China.

The findings from wavelet coherence reveal that there is feedback causality between FR and ER in China at different frequencies and different periods between 1985 and 2018. The consistency of the findings from wavelet coherence is confirmed by the outcomes of Toda Yamamoto causality test.

Although this study provides strong and consistent empirical findings for China, further studies should consider advancing the argument by focusing on different emerging markets.

Results are crucial for policy decision-making and can be used by researchers and macro-economic policymakers to take an action, if necessary, by implementing more appropriate or alternative economic and financial decisions.

To the best of the author’s knowledge, this relationship in China has not been comprehensively explored by using newly developed econometrics techniques. Therefore, this study is likely to open a debate about the literature as the study concludes with a discussion on short- and long-run implications for policymakers in China.

The current wave of decreasing electricity supply to meet the immediate demand of the populace is influencing not only economic growth but also the industrial productivity of the ECOWAS sub-region. In this context, this paper investigates the long-run and causal relationships between electricity consumption and industrial output in selected ECOWAS countries over the period 1971–2017.

The Autoregressive Distributed Lag (ARDL) bound testing approach is employed to determine the existence of relationships among the variables. The causal nexus between electricity consumption and industrial output is examined using both the Toda-Yamamoto causality test and the bootstrap-corrected causality technique.

The long run results indicated that increasing electricity supply enhances industrial output only in Benin, Cote d'Ivoire, Gambia, Guinea, Liberia, Nigeria, Senegal, and Sierra Leone. Furthermore, the causality test results confirmed the presence of all four hypotheses in this study, but the two causality tests agree, particularly in the evidence of growth and neutrality hypotheses. In the cases of Benin, Burkina Faso, Gambia, Ghana, Nigeria, and Sierra Leone, a unilateral causality running from electricity consumption to industrial output is found. However, no evidence of causality between electricity consumption and industrial production has been confirmed in Cote d'Ivoire, Guinea Bissau, Liberia and Niger.

The relevant energy stakeholders in the subregion need to reprioritize their policy framework to focus more on the electricity sector of their economies since electricity consumption is identified as an important driver of industrial growth in the West African countries.

This is the first study to provide a comparative and country-specific investigation of the nexus between electricity consumption and industrial output in Africa, particularly in the West African region.

The study aims to examine the appropriateness of the coefficient of elasticity of trading (CET) as a measure of liquidity using Nigerian stock market data. Given that liquidity is multidimensional, the CET is complemented with the popular measure of liquidity, turnover ratio to explore the causal relationship among the CET, turnover ratio and market return to determine their relevance in security valuation. In other words, an attempt is made to examine if either of these two measures of liquidity is a relevant factor in explaining stock market return.

The Toda-Yamamoto version of Granger causality test is applied to two sets of data on the Nigerian Stock Exchange (NSE). The available monthly time series data are from 2008 to 2019 while the annual data are from 1986 to 2018. The Toda-Yamamoto test is preferred because it is more robust to integration and cointegration of the variables.

The results of the Toda-Yamamoto version of the Granger causality test on monthly data reveal no causal relationship between CET and market return, turnover and market return and CET with turnover and market return. These results are consistent with those for several frontier countries reported by Rubio et al. (2005), Hartian and Sitorus (2015), Batten and Vo (2019) and Sterenczak et al. (2020). The results support the conclusion that the Nigerian economy is not fully integrated with the global economy. Market inefficiency due to order imbalances given the nature of the trading system can also explain the reported results. However, the results from annual data do not tally with the monthly results. There is causality running from CET to market return. There is also causality running from turnover to market return. Therefore, both CET and turnover are statistically significant causal predictors of market return. The results from annual data are consistent with those reported by Marozva (2019).

The key limitation is availability of high-frequency transaction-level data to researchers to consider many measures of liquidity that have been employed in developed countries. The research implication is that more researchers will be encouraged to conduct more studies on liquidity and how the study results can drive policy recommendations. The standard asymptotic distribution of underlying the Toda-Yamamoto approach has been found to lead to overrejection.

This study is the first to apply Toda-Yamamoto model on data from Nigeria to investigate the causal relationship between stock market return and liquidity proxied by the CET given the nature of the automated trading system (ATS) in use. The CET is also complemented with the turnover ratio to explore the multidimensional nature of liquidity and its causal relationship with market return. The study is also interpreted as a determination of the integration of Nigeria's economy with the global economy with its implication on investment diversification.

This paper empirically examines the impact of financial development on domestic investment in India for the period 1989–2017.

This study employs the autoregressive distributed lag (ARDL) bounds testing approach to co-integration to test the long-run relationship between financial development and domestic investment. To test the direction of causality, Toda–Yamamoto causality test and vector error correction model (VECM) Granger causality/Block Exogeneity Wald test have been employed. Investment has been measured by Gross Capital Formation. To capture various aspects of financial development in India, eight alternative indicators (both bank based and market based) have been used. With the help selected indicators, a composite index (FINDEX) of financial development has been constructed using principal component analysis (PCA).

The estimated result finds evidence in favour of positive, short-run and long-run impact of financial development on investment in the Indian economy. Both bank-based and market-based indicators are found to significantly affect the level of investment. The significant effect of efficiency-based financial development indicators (both bank based and market based) upon domestic investment implies that there is a need to implement policies that ensure the efficiency of financial intermediation.

To the best of authors' knowledge, not much research has been done to explore the relationship between financial development and domestic investment, especially in the case of Indian economy. This study also tries to find the impact of bank-based and market-based financial development indicators upon domestic investment to explore banks vs market issue.

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.