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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).

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 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 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.

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.

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 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.