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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.

This paper examines the causal relationship between stock market performance and foreign exchange market in Egypt over the period 2009–2016. The study period is divided into two sub-periods: pre- and post-January 25th Egyptian revolution (ER). The reason is to examine how this revolution affects the causal relationship between the two markets' performance.

In this study, the daily basis data are used to enable good and effective observation changes in the foreign exchange rate and stock market performance over time. Stock market indexes and stock market capitalization are used as proxies for stock market performance. Further, the Egyptian pound to US$ exchange rate is used as a measure for foreign exchange market performance. The study analysis is done in stages. The first is to check the variables' stationarity for the pre- and post-revaluation. The second is to examine the cointegration among the variables. The third is to run vector autoregression (VAR) estimates, after which VAR Granger causality tests are employed.

The results show that the data are not stationary at their levels but stationary in their first difference level while there is no cointegration in the long-run among the variables in both sub-periods. Further, findings indicate that, in the pre-January 25th revolution period, there is a significant causal relationship between the foreign exchange market and stock market indexes and a significant causal relationship between market capitalization (CAP) and exchange rate at the 1% level. However, in the post-January 25th revolution period, the study does not find a significant causal relationship between foreign exchange market and stock market indexes and capitalization.

As this study focuses on the causal relationship between foreign exchange and stock markets before and after the 25th January Revolution, other macroeconomic variables such as consumer price index, interest rate and GDP were excluded for the comparison purposes with other studies. Further research is suggested to include them in the analysis to find out its effect on the performance of stock market and foreign exchange market.

The existence of long-run bidirectional causality means that portfolio managers and hedgers may have improved their understanding regarding the dynamic relationship between foreign exchange market and stock market performance as this may help them to plan and implement suitable hedging strategies to guard against currency risk in future crises or events. Investors, fund and portfolio managers and policymakers should give much attention to these event-specific interactions when they make capital budgeting decisions and implement regulation policies. Furthermore, our results may allow portfolio managers, investors and policymakers to assess the importance of informational efficiency for both markets.

This paper is an original contribution to the literature that concerns the causal relationship between stock market and foreign exchange market in the period of political instability and social unrest such as the January 25th Revolution in one of the emerging markets, namely Egypt.

The purpose of the paper is to examine empirically Granger causality relationships between corporate social performance (CSP) and corporate financial performance (CFP) in four different industries.

The paper uses the Granger causality test to analyse the causality relationships between CSP and CFP in clothing, energy, food and forest industries in the USA. The panel data used combined CSP and CFP measures over the years 1991-2009. CSP strengths and concerns are handled as distinct constructs.

There is some evidence of bidirectional causality between CSP and CFP in the clothing, energy and forest industries; but in the food industry, CSP appears not to Granger-cause CFP. The results encourage accounting for the industry in empirical analyses, as well as the use of more than one measure for CFP in the analyses.

The direction of causality between CSP and CFP has been specifically addressed in only a few studies. Because the causality relationship may, in addition, be concealed when multi-industry data are used, this paper contributes to the literature by examining the Granger causality between CSP and CFP in four different industry contexts using two different measures of CFP.

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.

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

This study investigates the dynamic causality linkages between fiscal deficits and selected macroeconomic indicators in a panel of five East African Community countries.

The research design is based on panel cointegration tests, panel cross-section dependence tests, panel error correction-based Granger causality tests and panel impulse response functions.

Results show that there is long-run feedback causality among fiscal deficits and each of the variables include gross domestic product (GDP) growth, current account balance, interest rates, inflation, grants and debt service. Short-run Granger causality dynamics indicate that there is feedback causality between fiscal deficits and GDP growth; no causality between fiscal deficits and inflation; no causality between fiscal deficits and current account; no causality between fiscal deficits and interest rates; feedback causality between fiscal deficits and grants; and no causality between fiscal deficits and debt service. Impulse response functions show positive and significant impacts of current account balance, inflation and grants; negative and significant impacts of real GDP growth and lending rates; and insignificant effects of debt service.

While the study examines the dynamic causality between fiscal deficits and selected macroeconomic indicators in the East African Community, the analysis excludes South Sudan due to significant data limitations.

In light of the East African Community's aspirations to achieve convergence on key macroeconomic targets, including the fiscal deficit, this research provides novel insights on fiscal policy determinants and causality dynamics.

The dynamic relationships between fiscal policy and macroeconomic variables may have social implications for welfare, equitable growth and distribution of resources.

With a focus on the East African Community, this paper contributes to the literature on the macroeconomic determinants of fiscal deficits in regional economic communities.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

Since the famous tapering talk of Bernanke, US Dollar (USD) made a significant appreciation on emerging market local currencies. When the stock indices are adjusted to USD, a negative relationship is usually the case. USD index is a natural candidate for measurement of these effects. It is seen that some emerging stock indices exhibit negative causality with USD index in Granger sense. Moreover, the authors take into account rolling correlations of USD index and the relevant stock indices and examine them on the investment horizon beginning from tapering talk. The authors deduce that Granger causality test and correlation results are coherent with each other which sheds light to the famous discussion whether causality implies correlation or vice versa.

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.

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.