Search results

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

With the rapid-growing house market in the past decade, the purpose of this paper is to study the important issue of house price information flows among 12 major cities in China, including Shanghai, Beijing, Xiamen, Shenzhen, Guangzhou, Hangzhou, Ningbo, Nanjing, Zhuhai, Fuzhou, Suzhou and Dongguan, during the period of June 2010 to May 2019.

The authors approach this issue in both time and frequency domains, latter of which is facilitated through wavelet analysis and by exploring both linear and nonlinear causality under the vector autoregressive framework.

The main findings are threefold. First, in the long run of the time domain and for timescales beyond 16 months of the frequency domain, house prices of all cities significantly affect each other. For timescales up to 16 months, linear causality is weaker and is most often identified for the scale of four to eight months. Second, while nonlinear causality is seldom determined in the time domain and is never found for timescales up to four months, it is identified for scales beyond four months and particularly for those beyond 32 months. Third, nonlinear causality found in the frequency domain is partly explained by the volatility spillover effect.

Results here should be of use to policymakers in certain policy analysis.

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.

This study is the first to investigate the causal relationship between Bitcoin and equity price returns by sectors. Previous studies have focused on aggregated indices such as S&P500, Nasdaq and Dow Jones, but this study uses mixed frequency and disaggregated data at the sectoral level. This allows the authors to examine the nature, direction and strength of causality between Bitcoin and equity prices in different sectors in more detail.

This paper utilizes an Unrestricted Asymmetric Mixed Data Sampling (U-AMIDAS) model to investigate the effect of high-frequency Bitcoin returns on a low-frequency series equity returns. This study also examines causality running from equity to Bitcoin returns by sector. The sample period covers United States (US) data from 3 Jan 2011 to 14 April 2023 across nine sectors: materials, energy, financial, industrial, technology, consumer staples, utilities, health and consumer discretionary.

The study found that there is no causality running from Bitcoin to equity returns in any sector except for the technology sector. In the tech sector, lagged Bitcoin returns Granger cause changes in future equity prices asymmetrically. This means that falling Bitcoin prices significantly influence the tech sector during market pullbacks, but the opposite cannot be said during market rallies. The findings are consistent with those of other studies that have established that during market pullbacks, individual asset prices have a tendency to decline together, whereas during market rallies, they have a tendency to rise independently. In contrast, this study finds evidence of causality running from all sectors of the equity market to Bitcoin.

The findings have significant implications for investors and fund managers, emphasizing the need to consider the asymmetric causality between Bitcoin and the tech sector. Investors should avoid excessive exposure to both Bitcoin and tech stocks in their portfolio, as this may lead to significant drawdowns during market corrections. Diversification across different asset classes and sectors may be a more prudent strategy to mitigate such risks.

The study's findings underscore the need for investors to pay close attention to the frequency and disaggregation of data by sector in order to fully understand the true extent of the relationship between Bitcoin and the equity market.

There is a growing trend among online merchants to conduct help-request marketing campaigns (HMCs), which refers to a kind of marketing campaign that leverages participants' help-request to encourage the subsequent engagement of participants' online friends. The paper aims to investigate how individuals respond to online HMCs in social networking groups (SNGs). Integrating the norm activation model and regulatory focus theory, this paper examines the mediation effects of the two facets of responsibility perception, i.e. perceived causality and perceived answerability.

A field experiment was conducted by organizing a real HMC on WeChat. To manipulate request individuation, experimental confederates were engaged to serve as requesters in the HMC. The actual responses provided by the recipients (subjects) were captured via the HMC pages. The multiple-group analysis was used for data analysis.

Empirical results reveal that request individuation strengthens the effect of relationship closeness on perceived causality but reverses the effect of relationship closeness on perceived answerability from being positive to negative. Except for the negligible impact of perceived answerability on inaction, both perceived causality and perceived answerability affect recipients' reactions to HMCs as expected.

First, social media platforms should promote other-oriented prosocial values when designing features or launching campaigns. Second, the designers of HMCs should introduce a “tagging” feature in HMCs and provide additional bonuses for requesters who perform tagging. Third, HMC requesters should prudently select tagging targets when making a request.

First, this paper contributes to the literature on social media engagement by identifying responsibility as an other-oriented motivation for individuals' social media engagement. Second, this paper also extends our understanding of responsibility by dividing it into perceived causality and answerability as well as measuring them with self-developed instruments. Third, this study contributes to the research on WOM by demonstrating that individuals' response behaviors toward help-requests embedded in HMCs can take the form of proactive helping, reactive helping or inaction.

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 aims to examine the interrelationship between financial stability and economic growth with a comprehensive analysis.

The panel Granger causality testing approach is carried out to the panels of the Fragile Five (F5) and the Group of Seven (G7) countries for the period 1998–2020. To capture the different aspects of financial stability the authors use eight different indicators.

The findings reveal some important implications: the relationship between financial stability and economic growth is sensitive to the financial stability indicators for both the F5 and G7 countries. The stability indicators related to the credit market contain much more causality relationship with economic growth than the indicators related to the stock market. Z-score and provisions to nonperforming loans (NPLs) are among the two variables with the highest causality relationship with economic growth. The least number of causality link is found for the Regulatory Capital Ratio and Stock Price Volatility in F5 countries and Credit Ratio, NPLs and Stock Price Volatility in G7 countries. Economic growth affects financial stability through credit market stability indicators and mostly for the F5 countries. No causal relationship is found for any of the financial stability indicators of Canada, the UK and the USA from economic growth to financial stability.

Since the linkages between financial stability and economic growth may vary due to country/group specific differences, apart from the previous studies, the authors select two different groups of countries in terms of financial stability and economic size.

The purpose of this paper is to investigate the impact of changes in credit stock on real and financial indicators in Turkey with a focus on conditional and time-varying dynamics.

In addition to lag-augmented vector autoregression (LA-VAR) based time-varying Granger causality tests, threshold models and a research setting that identifies high/low states of credit growth based on 24-month moving averages are used to explore regime-dependent behavior. For investigating the asymmetric dynamics, the authors use a methodology that identifies good/bad news in credit growth based on 24-month moving averages and standard deviations.

Results strongly suggest that the impact of changes in credit stock induces conditional responses. Moreover, we find evidence for asymmetric responses. In the case of Turkey, efforts to spur growth through credit produce a strong negative byproduct, a depreciation in the exchange rate. The authors also find that changes in credit stock have become more relevant for uncertainties in inflation and exchange rate expectations, particularly in the era after mid-2018 in which credit growth volatility has increased noticeably.

This study provides a comprehensive analysis of time-varying and conditional responses to a change in credit stock in a major emerging economy. Using a moving threshold based only on the available information in the analysis of state-dependency represents a new approach.

Accelerating the green economy’s transition is a practical means of lowering emissions and conserving energy, and its effects on the greenhouse effect merit careful consideration. Growing environmental deterioration has compelled decision-makers to prioritize sustainability alongside economic growth. Policymakers and the business community are interested in green investment (GRE), but its effects on social and environmental sustainability are still unknown. Based on this, this study aims at looking into the time-frequency interplay between GRE and carbon dioxide emissions and assessing the impacts of economic growth, financial globalization and fossil fuel energy (FUE) usage on this nexus in Vietnam across different time and frequency domains.

The authors employ continuous wavelets, cross wavelet transforms, wavelet coherence, Rua’s wavelet correlation and wavelet-based Granger causality tests to capture how the domestic variance and covariance of two-time series co-vary as well as the co-movement interdependence between two variables in the time-frequency domain.

The results shed new light on the fact that GRE will increase the levels of environmental quality in Vietnam in the short and medium run and there is a bidirectional causality between the two indicators across different time and frequencies. In addition, when the authors observe the effect of economic growth, financial globalization and fossil fuel energy consumption on this interplay, the findings suggest that, in different time and frequencies, any joined positive change in these indicators will move the CO₂ emissions-GRE nexus.

Policymakers and governments can greatly benefit from this topic by utilizing the function of economic institutions in capital control of GRE and CO₂ emissions and modifying the impact of GRE on the greenhouse effect by accelerating the green growth of economic industries.

The current work contributes to the current literature on GRE and CO₂ emissions in several dimensions: (1) considering the sustainable development in Vietnam, by employing a new single-country dataset of GRE index, this paper aims to contribute to the growing body of research on the factors that influence CO₂ emissions, as well as to provide a detailed explanation for the relationship between GRE and CO₂ emissions; (2) localized oscillatory components in the time-domain region have been used to evaluate the interplay between GRE and CO₂ emission in the frequency domain, overcoming the limitations of the fundamental time-series analysis; (3) the mediation role of economic growth, financial globalization and FUE in affecting the GRE-CO₂ relationship is empirically explored in the study.

The study aims to find the synchronization between foreign agriculture investment (FAI) and Sustainable Development Goals (SDGs) related to agriculture as classified by the Food and Agriculture Organization (FAO). The study tries to find such an association in India over 2 decades from 2001.

The Toda-Yamamoto Granger using the M-Wald test for the non-causality procedure is applied to find the synchronization. Stationarity is tested using the Augmented Dickey-Fuller, Phillips-Perron and Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The Johanson methodology with MacKinnon-Haug-Michelis P-value is employed for the Cointegration test.

The empirical results indicate that the FAI Granger cause SDG2 “Zero hunger” and “Overall sustainability”, but SDG13 “Climate Change”, SDG6 “Clean water and sanitation”, SDG12 “Responsible production and consumption” and SDG15 “Life on Land” granger cause global investments. Notwithstanding, SDG5 “Gender equality” and SDG14 “Life below water” found no-way causality with FAI.

Host governments should prioritize sector-level sustainable development, notably agricultural SDGs, to attract global investments. Foreign agriculture investment is influenced differently by various SDGs; thus, policymakers should concentrate on specific agricultural SDGs to enhance the flow of capital into the agriculture sector. Global investors should take sustainability into account while framing foreign investment plans, and the supra-national organization may consider global agricultural investments while addressing the problems related to global food security.

The distinguishing feature of the study is that SDGs classified by the FAO from a global investment perspective have not been studied so far.