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This study aims to investigate Granger-causal relations between the Ringgit-USD exchange rate and selected domestic and international economic variables after the flotation of the Ringgit beginning with 25 July 2005.

The study uses lag-augmented vector autoregression (LA-VAR) developed by Toda and Yamamoto (1995) to test for Granger-causality. To visualize short-run dynamics in the Malaysian Ringgit (RM)-USD exchange rate to shocks in predictor variables, generalized impulse-response functions (Pesaran and Shin, 1998) are derived from the estimated LA-VAR models.

Results based on LA-VAR generalized impulse responses and data measured in daily frequency indicate strong Granger-causal relationships with the Dow Jones Industrial Average and oil prices. Evidence is also indicative for a causal relationship with the Shanghai Composite Index. Positive shocks in these three variables lead an appreciation of the Ringgit.

These results provide insights for policymakers in East Asia in their attempt to manage the floating of their currency.

The paper adds to existing empirical literature in three ways. First, it investigates the RM-USD exchange rate after its managed flotation beginning with 25 July 2005. Second, the study provides results for exchange rates measured in two frequencies, namely, daily and monthly. Third, the empirical LA-VAR model applied includes variables capturing economic and financial conditions in China. Prior literature puts a focus on macroeconomic conditions in the USA. Yet, since 2009, China has been the largest trading partner of Malaysia.

The purpose of this paper is to develop a new framework to test the hypothesis that portfolio model predicts a negative correlation between stock prices and exchange rates in a trivariate transmission channel for foreign portfolio equity investment.

This paper utilizes panel data for eight economies to extend the Dumitrescu and Hurlin (2012) Granger non-causality test of heterogeneous panels to a trivariate model by integrating the Toda and Yamamoto (1995) approach to Granger causality.

The evidence suggests that stock prices Granger-cause exchange rates and portfolio equity flows Granger-cause exchange rates. However, the overall panel evidence casts doubt on the explicit trivariate model of portfolio balance model. The study shows that Indonesia may be the only case where stock prices affect exchange rates through portfolio equity flows.

The proposed test does not account for potential asymmetries or structural shifts associated with the crisis period. To isolate the impact of the Asian Financial crisis, this paper rather splits the sample period into two sub-periods: pre- and post-crises. The sample period and countries are also limited due to the use of the balance of payment statistics.

The study casts doubt on the maintained hypothesis of a trivariate transmission channel, as posited by the portfolio model. Policy makers of an economy may integrate capital market and fiscal policies in order to maintain stable exchange rate.

This paper integrates a portfolio equity inflow variable into a single framework with stock price and exchange rate variables. It extends the Dumitrescu and Hurlin’s (2012) bivariate stationary Granger non-causality test in heterogeneous panels to a trivariate setting in the framework of Toda and Yamamoto (1995).

The aim of the study is to evaluate role of trade war between the United States and China on oil price. For this purpose, global oil price and US trade balance with China are selected as variables. In addition to this issue, monthly data of these variables for the periods between 1990 and 2019 are taken into consideration. In the evaluation process, both Engle–Granger cointegration and Toda–Yamamoto causality analysis are considered. The results of Engle–Granger cointegration analysis indicates that there is a ­relationship between trade war and oil prices. Nevertheless, according to the results of Toda–Yamamoto causality analysis, it is identified that trade war does not cause oil prices. While looking at these results, it is determined that trade war between the United States and China has an influence on the oil price changes. However, it is also understood that it is not the main factor of this volatility. Thus, it is recommended that in order to identify the main indicator of the oil price volatility, some different factors should also be taken into consideration.

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.

This paper attempts to discover whether or not social networks work in the same way in different sectors of the labour market in the same society, using data from the 2008 Asian Social Survey. Labour markets in some societies are segmented; there are two segments in the labour market, namely, the core sector and the peripheral sector. The practices of each sector differs from the others. Some sectors employ CME labour markets, while others favour LME labour markets (Kanbayashi and Takenoshita, 2014). In other words, we can find both CME and LME labour market in one society.

Since Granovetter’s (1973) pioneer study, scholars are interested in investigating in what way social network influence our job searching outcomes. However, these researchers have not yet yielded consistent results. Scholars argue that the institutional context of labour market can shape the network impacts on our job search outcome (Chen, 2014; Chua, 2011).

Surprisingly, this paper finds that there is no room for the use of personal contact in the public sector in both China and Japan. But, mean status is positively related to annual income in the private companies sector in both Japan and China. The significant influences of mean status in the private sectors in both China and Japan reflect the reinforcing of existing social inequality structure. This is because as the status of contact can facilitate respondents' job attainment process, those who are already in higher social status are more likely than those who are in the bottom of the social strata, to get a better job with the help from their network members.

The above findings show us that social network can exert various impacts on people's job searching process even in the same society. This is because it is possible that the labour market are segmented. These segments have very different practices. This difference attributes to the inconsistent findings of network effects on occupational attainment process. Therefore, it is essential to locate which labour market respondents are in, and the features of this labour market. This can help us know more about the use and effectiveness of network in different types of labour markets.

This paper examines the causal relationship between foreign direct investment (FDI) and economic growth in Turkey using annual data for the period 1968‐2002, by means of cointegration, error‐correction models (ECM) and the augmented vector autoregressive (VAR) methodology developed by Toda and Yamamoto (1995). Johansen (1992) cointegration test results indicate that these two variables are cointegrated. The empirical results from Granger causality tests based on error‐correction models and the augmented level VAR suggest that there is a strong evidence of bi‐directional Granger causality between FDI and economic growth, corroborating the feedback hypothesis for Turkey over the sample period.

The crude oil market plays a key role in addressing the issue of energy economics. This paper aims to detect the causality relationship between the crude oil market and economy based on the financial system.

This paper used the static and dynamic Hatemi-J Bootstrap Toda–Yamamoto and Diebold–Yilmaz connectedness index. The Hatemi-J Bootstrap Toda-Yamamoto approach allows researchers to use nonstationary data and that method is robust to nonnormal distribution and heteroscedasticity. The Diebold–Yilmaz connectedness index model provides researchers to detect the power of connectedness besides linkage direction. The analyzed period is the span from January 3, 2005 to October 3, 2022.

The results show bidirectional causality in the full sample but unidirectional causality before and after the 2008 financial crisis. During the 2008 financial crisis period and the COVID-19 period, there was a bidirectional and unidirectional causality, respectively. The connectedness approach indicates that the crude oil market affects financial stress through investors’ risk preferences.

The Diebold–Yilmaz spillover index model is based on vector autoregression methods with a stationarity precondition. However, some of the five dimensions that constitute the financial stress index (FSI) are nonstationary in level. Therefore, the authors takes the first difference of the nonstationary data.

The linkage between the crude oil market and the FSI provides useful information for investors and policymakers. For instance, this paper indicates that an investor wanted to forecast future value of the crude oil (financial stress) should consider the current and past values of financial stress (crude oil). Moreover, policymaker should consider the crude oil market (FSI) to make a policy proposal for financial system (crude oil market).

Recently, indicators of economic activity levels (economic policy uncertainty, implied volatility index) have begun to be considered to analyze the relationship between energy and the economy but very little is known in the literature about the leading and lagging roles of data in subsample periods and the linkage channel. The other originality of this research is using the new econometric approaches.

The purpose of this study is to empirically examine the extent to which volatility associated with corporate performance could be attributed to specific adverse macroeconomic conditions in a bivariate causality analysis.

The study uses the Toda–Yamamoto Wald test approach to Granger causality analysis in verifying significant causal interactions if any, between corporate performance volatility and seven macroeconomic conditions or variables.

This study finds that economic policy uncertainty and macroeconomic uncertainty tend to have bidirectional causal interaction with corporate performance volatility. In addition, estimated results further suggest significant unidirectional causal interaction between corporate performance volatility and inflation expectations, exchange rate volatility, inflation and inflation uncertainty, with direction of causality running from the macroeconomic variables toward corporate performance volatility. This study, however, found no significant causal interaction between corporate performance volatility and recessionary probability or likelihood of recession.

This study’s conclusions could have significant and critical policy implications for key corporate policymakers responsible for corporate performance strategy. Various causal interactions identified could inform policy framework and, subsequently, strategies geared toward minimizing volatility associated with performance during episodes of any of the various macroeconomic conditions examined in this study.

The uniqueness of this study stems from its focus on corporate performance volatility instead of corporate performance and potential causal interactions it might have with key adverse macroeconomic conditions, some of which have not been examined in previous studies according to reviewed literature.

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 investigates the causal relationship between financial innovation (FI) as proxied by the bank credits to private sector, as percentage of GDP and economic growth in case of Azerbaijan using annual data covering the period from 1992 to 2018. For this purpose, the Toda–Yamamoto causality test with the framework of vector autoregressive (VAR) model is utilized to test causal relationship between the variables. The estimation results reveal that there is bidirectional causal relationship between FI and economic growth. The findings of the study suggest the researchers and policy makers to understand the role of FI in economic growth for macroeconomic stability and sustainable development purposes in Azerbaijan and other developing oil-rich countries.