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1 – 10 of 29Mohd Nadeem Bhat and Mohd Hammad Naeem
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
The distinguishing feature of the study is that SDGs classified by the FAO from a global investment perspective have not been studied so far.
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Nguyen Minh Ha and Bui Hoang Ngoc
The study aims to discover the spatial relationship between financial development, energy consumption and economic growth in 11 ASIA countries, using panel data from 1980 to 2016.
Abstract
Purpose
The study aims to discover the spatial relationship between financial development, energy consumption and economic growth in 11 ASIA countries, using panel data from 1980 to 2016.
Design/methodology/approach
The study applies three popular spatial models, namely, (1) spatial error model (SEM), (2) spatial autoregressive model (SAR) and (3) spatial Durbin model (SDM), to explore the direct and spillover effect of financial development and energy consumption on economic growth. Furthermore, a novel test proposed by Juodis et al. (2020) is employed to check the Granger non-causality between each pair of variables.
Findings
The empirical outcomes found direct and spillover effects of financial development and energy consumption on economic growth in 11 ASIA countries. Accordingly, an expansion of the financial development in country i is beneficial for the growth of the host country and neighboring countries, and vice versa. However, an increase in energy consumption in country i leads to a decrease in the economic growth of neighboring countries. The test of Granger non-causality indicated a bidirectional causality between financial development and economic growth, and unidirectional causality running from economic growth to energy consumption.
Research limitations/implications
Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.
Practical implications
Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.
Originality/value
Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.
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Anam Ul Haq Ganie, Arif Mohd Khah and Masroor Ahmad
The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).
Abstract
Purpose
The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).
Design/methodology/approach
This study employs econometric techniques, including Westerlund cointegration tests, cross-sectional augmented distributive lag model (CS-ARDL) and Dumitrescu and Hurlin (DH) causality tests to investigate the relationship between renewable and non-renewable energy consumption, agriculture, economic growth, financial development and carbon emissions in SAE from 1990 to 2019.
Findings
The CS-ARDL test outcome supports the presence of the agriculture-induced EKC hypothesis in SAE. Additionally, through the application of the DH causality test, the study confirms a unidirectional causality running from renewable energy consumption (REC), fossil fuel consumption (FFC), economic growth (GDP) and squared economic growth (GDP2) to carbon dioxide (CO2) emissions.
Research limitations/implications
This study proposes that future research should extend comparisons to worldwide intergovernmental bodies, use advanced econometric methodologies for accurate estimates, and investigate incorporating the service or primary sector into the EKC. Such multidimensional studies can inform various methods for mitigating global climate change and ensuring ecological sustainability.
Originality/value
Environmental degradation has been extensively studied in different regions and countries, but SAE face significant constraints in addressing this issue, and comprehensive studies in this area are scarce. This research is pioneering as it is the first study to investigate the applicability of the agriculture-induced EKC in the South Asian region. By filling this gap in the current literature, the study provides valuable insights into major SAE and their environmental challenges.
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Jihane Benkhaira and Hafid El Hassani
The present article aims to estimate an autoregressive vector model covering the period of 1990–2021 to analyze the effect of public spending and monetary supply increases in…
Abstract
Purpose
The present article aims to estimate an autoregressive vector model covering the period of 1990–2021 to analyze the effect of public spending and monetary supply increases in economic activity in Morocco.
Design/methodology/approach
A literature review on the policy of recovery with fiscal and monetary tools and its theoretical foundations was established. Then, an empirical study on the Moroccan context was executed to study the effectiveness of these instruments in Morocco from 1990 to 2021, using autoregressive vector modeling.
Findings
The results present a state of a positive relationship and statistical significance of public spending, money supply and economic growth. The impulse response function analysis and the forecast error variance decomposition showed that public spending does not have a large impact on gross domestic product, while the money supply has a real power to stimulate the growth of economic activity in Morocco.
Originality/value
This study aims to demonstrate the positive effect of the coordination of public spending and monetary supply increases on gross domestic product in Morocco. Additionally, the analysis using vector autoregressive modeling, impulse response functions, variance decomposition techniques and causality tests, provides crucial insights to guide researchers, practitioners and policymakers in developing more effective and resilient economic strategies. The findings from this study not only illuminate immediate recovery strategies but also contribute to strengthening the resilience of economies against potential future shocks.
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Xingrui Zhang, Eunhwa Yang and Yunpeng Wang
Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive…
Abstract
Purpose
Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive studies on PRRESCON forecasting. This study aims to address the gap in knowledge by conducting a comprehensive exploration of indicators for PRRESCON using time series methods.
Design/methodology/approach
Granger causality test trials were conducted between PRRESCON and all of its potential indicators before the vector autoregression model was implemented. Extensive effort was exerted toward model interpretation in the form of impulse–response functions.
Findings
Impulse–response functions indicated that the escalation of labor supply, material/construction costs and issued building permits at any given time consistently had a positive impact on PRRESCON 10–11 months later, with a 95% confidence interval. Conversely, the unemployment rate and housing value escalations at any given time were found to have a negative impact on PRRESCON 10–11 months later in more than 95% of the instances. Furthermore, material/construction cost escalations at any given time were shown to have a negative impact on PRRESCON 7 months later in more than 95% of the instances.
Originality/value
Current forecasting literature on construction spending focuses exclusively on the parameter’s relationship with gross domestic product and the architectural billing index. This study reveals many additional indicators, many of which are directly related to the implementation of housing development projects. The paper is also the first in the body of forecasting literature, to the best of the authors’ knowledge, to conduct impulse–response analysis on residential construction spending.
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Aarzoo Sharma, Aviral Kumar Tiwari, Emmanuel Joel Aikins Abakah and Freeman Brobbey Owusu
This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be…
Abstract
Purpose
This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis.
Design/methodology/approach
The authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot.
Findings
From the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets.
Practical implications
The quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions.
Social implications
The outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds.
Originality/value
This paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.
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Gildas Dohba Dinga, Dobdinga Cletus Fonchamnyo, Nkoa Bruno Emmanuel Ongo and Festus Victor Bekun
The study examined the impact of financial development, foreign direct investment, market size and trade openness on domestic investment for 119 countries divided into four panels…
Abstract
Purpose
The study examined the impact of financial development, foreign direct investment, market size and trade openness on domestic investment for 119 countries divided into four panels that are low-income countries (LIC), lower middle-income countries (LMIC), upper middle-income countries (UMIC) and high-income countries (HIC) between 1995 and 2019.
Design/methodology/approach
The present study bases its empirical procedure on the bases of the data mix. To this end, based on the presence of cross-sectional dependence, covariate-augmented Dickey–Fuller unit root and Westerlund cointegration second-generation tests were employed to validate the stationarity and cointegration of the variables, respectively. The novel Dynamic Common Correlation Effects estimator was employed to estimate the heterogeneous parameters while the Dumitrescu and Hurlin test was used to test for causality direction of the highlighted variables.
Findings
The empirical results show that market size and trade openness had a positive and statistically significant effect on domestic investment for all the income groups. Results also show that financial development had a positive and statically significant effect on domestic investment only for LMIC and HIC economies, while a positive and statistically insignificant effect was obtained for LIC, UMIC and the global panel. The causality results revealed a bidirectional relationship between domestic investment and the exogenous variables – financial development, foreign direct investment, market size and trade openness.
Research limitations/implications
It is therefore, recommended that LIC and LMIC need to consider harmonising the financial system to lower credit limitations and adopt business-friendly policies. HIC and UMIC should seek more outward FDI policies and harmonise their trade policy, to reap more benefits from FDI and international trade.
Originality/value
On novelty, previous studies have been criticised for the effect on technical innovation of bank financing and institutional quality. This research tackles the deficiency using systematic institutional quality indicators and by taking other variables into account.
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Anushka Verma, Arun Kumar Giri and Byomakesh Debata
The main purpose of this paper is to analyze the role of information and communication technology (ICT) diffusion in women empowerment and in fostering the process of achieving…
Abstract
Purpose
The main purpose of this paper is to analyze the role of information and communication technology (ICT) diffusion in women empowerment and in fostering the process of achieving the Sustainable Development Goals (SDGs) in South Asian Association for Regional Cooperation (SAARC) countries using panel data from 2005 to 2020.
Design/methodology/approach
An ICT diffusion index was constructed using principal component analysis (PCA). Further, the study uses econometric techniques robust to cross-sectional dependence (CSD) which include Pesaran's CSD tests, second-generation unit root test, Pedroni, Kao, Westerlund cointegration test, FMOLS, DCCE, Driscoll–Kraay (DK) regression, and D&H causality tests.
Findings
ICT diffusion and economic growth have a significant and favorable impact on women's empowerment. However, fertility rates and trade openness harm women's empowerment. In addition, the causality test results depict a bidirectional causal relationship between ICT and women empowerment and between growth and women empowerment. In addition, unidirectional causality is detected between education and women's empowerment. Overall, the findings indicate that expanding ICT and bridging the digital divide, particularly among women, can be effective in achieving empowerment-related SDGs.
Originality/value
To date, there are hardly any studies in SAARC context that empirically evaluate the link between ICT, women empowerment, and the issue of sustainability in a unified framework. Therefore, this study is unique in terms of conceptualization and methodological robustness in this context. The study will benefit policymakers and regulatory bodies to formulate appropriate policies to empower women and thereby attain the SDGs by 2030.
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Everton Anger Cavalheiro, Kelmara Mendes Vieira and Pascal Silas Thue
This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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In this study, the author intend to investigate the impacts of renewable energy use and environmental taxation on sustainable development measured by the adjusted net savings…
Abstract
Purpose
In this study, the author intend to investigate the impacts of renewable energy use and environmental taxation on sustainable development measured by the adjusted net savings (ANS).
Design/methodology/approach
This study employs the quantile regression (QR) for a set of 24 Organization for Cooperation and Economic Development (OECD) countries over the period 1994–2018.
Findings
The main empirical findings of estimates show that access to renewable energy and environmental taxation generate positive and significant effects in increasing the ANS for most quantiles. Hence, they are practical tools for achieving sustainable development goals (SDGs).
Practical implications
This study has important implications for governments and policymakers of the OECD countries. Therefore, governments can use subsidies and incentives to promote the adoption of renewable energy sources, energy-efficient technologies and sustainable practices. Similarly, by imposing taxes on pollution and resource use, governments can encourage the adoption of cleaner technologies and practices toward more sustainable behavior.
Originality/value
This paper is based on a novel measure of sustainable development (ANS) and a novel econometric method (QR).
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