Search Results (18)

This study investigates the dynamic relationship between maritime trade and cultural convergence between China and Saudi Arabia, with a particular focus on the roles of creative goods and information and communication technology (ICT) exports as proxies for sociocultural integration. Utilizing quarterly data from 2012 to 2021, the analysis employs the Toda–Yamamoto Granger causality approach within a Vector Autoregression (VAR) framework. This methodology offers a robust means of testing causality without requiring data stationarity or cointegration, thereby reducing estimation bias and enhancing applicability to real-world economic data. The empirical model examines causal interactions among maritime trade, creative goods exports, ICT exports, and population, the latter serving as a control variable to account for demographic scale effects on trade dynamics. The results indicate statistically significant bidirectional causality between maritime trade and both creative goods and ICT exports, suggesting a reciprocal reinforcement between trade and cultural–technological exchange. In contrast, the relationship between maritime trade and population is found to be unidirectional. These findings underscore the strategic importance of cultural and technological flows in shaping maritime trade patterns. Furthermore, the study contextualizes its results within broader policy initiatives, notably China’s Belt and Road Initiative and Saudi Arabia’s Vision 2030, both of which aim to promote mutual economic diversification and regional integration. The study contributes to the literature on international trade and cultural economics by demonstrating how cultural convergence can serve as a catalyst for strengthening bilateral trade relations. Policy implications include the promotion of cultural and technological collaboration, investment in maritime infrastructure, and the incorporation of cultural dimensions into trade policy formulation. Full article

Energy efficiency potentially reduces global carbon emissions, whereas the need of emerging countries to maintain economic growth and development entails a sharp increase in energy consumption. However, to meet this, current energy systems need to be transformed. Several studies find different conclusions on the short-run and long-run relationship and the direction of causality, and none of the studies have considered energy efficiency in their model. This study investigates the direction of causality between energy efficiency, energy consumption, and economic growth in South Africa. To determine if a long-run relationship between the variables exists, the Johanson cointegration test is used, and the results indicate that there is a long-run relationship between economic growth, energy depletion, energy efficiency, non-renewable energy consumption, renewable energy consumption, and energy security, with trace statistics suggesting that the null hypothesis of no cointegration should be rejected at a 5% level of significance. The Toda and Yamamoto procedure of the Granger causality approach was then applied. This study finds a unidirectional causality between energy efficiency, non-renewable energy consumption, and economic growth and no causality between renewable energy consumption, energy depletion, energy security, and economic growth. The growth hypothesis is supported, while the neutrality hypothesis is only confirmed regarding renewable energy consumption and economic growth. The results further suggest that a unidirectional Granger causality exists between non-renewable consumption and energy efficiency, and economic growth in South Africa. In South Africa, energy efficiency is a significant tool to enhance sustainable growth and attain climate objectives. Also, energy efficiency helps to lower the costs of mitigating carbon emissions and further advance both social and economic development. Full article

This study analyzes Turkey’s development toward a green economy between 1990 and 2022 within the framework of certain green economic indicators. The data consist of secondary data from the official databases of the World Bank and the Turkish Statistical Institute (TURKSTAT). In the study, the total amount of carbon emissions was chosen as an indicator of green growth, while gross domestic product per capita (GDP) represents economic growth, domestic loans granted by banks to the private sector (as a percentage of GDP) and foreign direct investment represent financial development, and electricity generation represents pollution. To determine whether the variables are cointegrated and to determine the direction and strength of the relationship between the variables, the ARDL bounds test and the FMOLS and DOLS long-run estimators were used. Finally, Toda Yamamoto (TY)–Granger tests were performed to determine causality. The long-term relationship between the variables was confirmed by the results of the ARDL bounds test. The error correction coefficient (CointEq(−1)) was estimated to be statistically significant and negative (−0.757) when the short-term analysis was performed. This result shows that the short-term imbalances will be corrected in less than a year, and the system will approach the long-term equilibrium. In the long-term analysis of the model, all variables selected to explain the dependent variable were found to have a statistically significant impact on the dependent variable. The GDP per capita variable, the indicator of economic growth, has a negative effect on the dependent variable, while the other independent variables have a positive effect. The results of the causality analysis indicate that the dependent variable carbon emissions (CO₂) has a unidirectional causality relationship with domestic credit provided to the private sector by banks (DC), which represents financial development, and with total electricity production (EP), which serves as an indicator of pollutants. Full article

The availability of agricultural land is central to stimulating reserves in sustainable food and crop production amidst accelerating economic sustainability and growth. Therefore, this article aims to investigate the influence of agricultural land (AGL) on food production (FP) and crop production (CP) with the linkage of environmental sustainability (ES) as a moderator from 1990 to 2021 for the economy of China with the autoregressive distributed lag (ARDL) bounds testing estimation model. Our findings showed that the ARDL model estimates the long-term and short-term joint matching relationships between agricultural land and the independent variables in the model, which is a statistically significant outcome. Therefore, in the long term, the food and crop production adjustment for speed to steadiness was huge as it was projected at 1.337%, 53.6%, 133.5%, and 37.4%, respectively, in all the models, which shows that the adjustment for speed of models is a good post-shock association process. We found evidence for a significant and positive relationship between agricultural land and food and crop production in ordinary least square (OLS) estimation, which also ensured the outcomes of the primary model. Furthermore, Toda–Yamamoto Granger causality test estimation found reverse causality between food production (FP) and crop production (CP) and showed evidence of the conservation hypothesis. We found bidirectional causality between food production and agricultural land and between crop production and agricultural land, which shows evidence of the feedback hypothesis. Additionally, the empirical findings of a robustness check with fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) techniques showed consistency with the investigations of ARDL estimation in the long run, ensuring the validity and strength of the primary outcomes. Overall, the present paper brings fresh knowledge about agricultural land use, and food and crop production to promote environmental sustainability. Full article

This study examines the relationship between carbon dioxide (CO₂) emissions and gross domestic product (GDP) in the tourism industry, using annual time series data from 1955 to 2019 for Greece and 1930 to 2019 for Italy. The Autoregressive Distributed Lags (ARDL) model was used to determine the threshold point at which the tourism-induced Environmental Kuznets Curve (EKC) emerges in each stage of tourism, as indicated by the Tourism Area Life Cycle (TALC) model. The existence and direction of causality between CO₂ emissions, GDP, and tourist arrivals was determined using the Toda–Yamamoto Granger causality test. The analysis emphasizes the complex relationship between economic growth, environmental degradation, and the tourism industry. The EKC hypothesis is supported by empirical findings that show a strong long-term cointegration between tourist arrivals, GDP, and CO₂ emissions. This suggests that, while tourism growth initially contributes to environmental degradation, it also fosters conditions for sustainable development as economies progress, providing critical insights for policy-makers seeking to promote environmentally sustainable tourism. Full article

This study examines the combined and individual effects of gross domestic product (GDP), microfinance loan disbursement, per capita power consumption, and total energy consumption on poverty rate in Bangladesh by using annual time series data over the period of 1995–2022. This study determines the direction of causality by applying the Toda–Yamamoto (T–Y) procedure of the Granger causality test in the vector auto regression (VAR) model given the presence of a mixed order of integration of I(1) and I(2). The results of the stationary tests show that all variables except poverty rate are stationary at the I(1) order of integration, according to both the augmented Dicky–Fuller (ADF) and Phillips–Perron (PP) methods, while the poverty rate shows stationarity at the I(2) order in both methods. The T–Y empirical test result shows that the four independent variables combined affect the poverty rate significantly. Power consumption affects both GDP and microfinance and they have bi-directional causality relationship with each other. Our study shows that GDP and total energy consumption individually contribute to poverty reduction. Based on the findings, it is imperative that national policy makers place a greater emphasis on increased domestic production and the proper utilization of power and energy to reduce poverty rates. Policy implications may include strategies to promote sustainable energy development, improve energy efficiency, and provide equitable access to energy services. Full article

In South Africa, the agricultural sector is a crucial pillar of the economy, with the livestock and grain industries playing significant roles in ensuring food security, fostering economic growth, and providing employment opportunities, particularly in rural areas. This research addresses the relatively unexplored relationship between the livestock and grain industries in South Africa. This study employs a comprehensive approach using a VAR/VECM framework alongside VECM Granger causality tests, Toda Yamamoto causality tests, impulse response functions, and variance decomposition analysis. The main findings of this study demonstrate a long-run relationship among the study variables, with consistently low error correction terms indicating slow short-term adjustments. Significant long-run relationships were observed between grain feed prices and livestock prices, where yellow maize and soybean prices affect live weaner prices, while beef carcass prices influence yellow maize prices. Overall, the results highlight the pivotal role that yellow maize plays as a link between the South African livestock and grain markets. The study concluded that policy formulation for the South African agricultural sector must consider the interconnected nature of the grain and livestock markets to achieve sustainable and effective outcomes. Full article

This research delves into the effects of carbon dioxide emissions and energy consumption on economic growth in Korea from 1980 to 2022, employing a sophisticated nonlinear autoregressive distributed lag model. The study unveils pivotal findings, most notably the positive association between carbon dioxide emissions and economic growth, suggesting that periods of economic expansion in Korea have been accompanied by surges in emissions. Furthermore, the investigation highlights a significant, albeit asymmetrical, positive impact of primary energy consumption on economic growth, illuminating the critical role of energy in the nation’s economic trajectory. The analysis also identifies essential economic determinants—namely, the labor force, gross fixed capital formation, and net inflows of foreign direct investment—underscoring their pivotal contributions to economic proliferation. The reliability of these insights is corroborated through advanced econometric techniques, including fully modified ordinary least squares and dynamic ordinary least squares methods. A noteworthy discovery emerges from the Toda–Yamamoto causality test, revealing bidirectional Granger causality between carbon dioxide emissions and economic growth, as well as between energy consumption and economic growth. Moreover, it uncovers a unidirectional causality flowing from labor, capital formation, and foreign direct investment towards economic growth. These findings elucidate the complex interplay between environmental and economic elements, highlighting the critical need for sustainable energy policies and proactive environmental stewardship in Korea. By advocating for a synthesis of economic advancement and environmental sustainability, this study presents indispensable insights for policymakers. It calls for a judicious approach to balancing Korea’s economic ambitions with its ecological responsibilities, thereby charting a sustainable path forward for the nation. Through its comprehensive analysis, this research contributes valuable perspectives to the discourse on economic development and environmental sustainability, offering guidance for Korea’s strategic planning and policy formulation. Full article

This study examines the dynamic relationship between the business cycle and the construction sector activity in 27 EU countries, focusing on Poland. Using the cross-correlation function (CCF) and a set of economic- and construction-related variables, including GDP growth, construction production, building permits, and construction operating time by backlog, quarterly data from 2000Q1 to 2023Q2 (94 quarters in total) are analyzed. Beyond the CCF analysis, causality is also examined using Toda–Yamamoto tests to explore the nuanced temporal relationships between GDP growth and construction activity proxies. The research uncovers synchronized positive lag max results for construction production, suggesting a harmonized response to broader economic changes, especially within 9 to 11 quarters. In contrast, building permits and construction time by backlog show divergent positive lag max values, suggesting the need for tailored, localized strategies. Negative lag max values emphasize the anticipatory role of the construction sector as an early indicator of economic change. Overcoming methodological challenges, this study provides insights critical for policymakers and researchers, promoting a nuanced understanding of economic synchrony and guiding informed strategies for sustainable development. Future recommendations include refining localized strategies based on lag patterns for optimal economic management. Full article

While construction costs and housing prices are implicitly examined in the construction economics literature, dedicated studies on their theoretical underpinning are rare. In this study, we investigated the application of different pricing theories in Auckland by testing the relationship between house prices and construction costs in Auckland from 1995 to 2021. The results contrast the tendering pricing theory, which posits that construction prices are optimal mark-ups unaffected by market demand, with the full-cost pricing theory, which acknowledges the market-dependent nature of pricing. By using the Toda-Yamamoto’s granger-causality test and Pesaran’s Autoregressive Distributive Lag (ARDL) bound tests, we analysed the relationship between the house price index (HPI) and construction cost index (CCI). The result suggests a significant relationship between housing prices and construction costs in both the short and long term, supporting the predominance of the full-cost pricing theory in Auckland’s housing market. The finding highlights the potential need for property industry participants to evaluate the market structure of the construction industry, fostering a more competitive environment and paving the way for more effective supply-related housing policies. Full article

This paper investigates the relationship between geothermal energy consumption, economic growth, and foreign direct investments in countries where geothermal energy production is possible. Panel Fourier Granger causality and panel Fourier Toda–Yamamoto causality tests (2020–2021) were applied, which can take into account smooth transitional structural breaks with trigonometric functions using quarterly data for the period 2016 Q1–2020 Q3. Data were obtained from the International Energy Agency (IEA), Federal Reserve Economic Data (FRED), and the OECD official website. According to the results obtained based on panels, there is one-way causality from economic growth to geothermal energy and one-way causality from geothermal energy consumption to foreign direct investments. The results obtained based on individual countries indicate that one-way causality from foreign direct investment to geothermal energy consumption was found for Mexico and Portugal, and one-way causality from geothermal energy consumption to economic growth was found for Italy and Mexico. On the other hand, causality from economic growth to geothermal energy consumption was observed for Germany, Japan, and USA. No significant results were found for Turkey and New Zealand, and it is understood that the macroeconomic structures of these countries are not affected by geothermal energy. The difference in the results reveals that the application recommendations on this subject should also be different. Full article

The current paper evaluates the role of disintegrated trade, financial development, and renewable energy on consumption-based carbon emissions (CCO₂) in MINT nations between 1990Q1 and 2019Q4. This paper utilizes the novel Bootstrap Fourier Granger causality in quantiles (BFGC-Q) to evaluate this connection. This approach produces tail-causal and asymmetric causal connections between the indicators within the Fourier approximation, contrary to the Toda–Yamamoto causality and other conventional Granger tests. The outcomes uncover a unidirectional causality from economic growth and renewable energy to CCO₂ emissions in each MINT nation. Moreover, unidirectional causality emerged from financial development to CCO₂ for Indonesia, Nigeria, and Turkey. Moreover, exports have predictive power over CCO₂ in Indonesia, Turkey, and Mexico, while imports only have predictive power over CCO₂ emissions in Turkey. Lastly, financial development causes CCO₂ in Indonesia, Nigeria, and Mexico. In summary, green energy and exports are essential factors that decrease CCO₂ emissions and therefore decrease ecological deterioration in Mexico, Indonesia, and Turkey. On the flip side, imports only trigger CCO₂ emissions in Turkey and Mexico. Lastly, the financial development effect on CCO₂ emissions is positive in Mexico, Indonesia, and Nigeria, while an insignificant impact is found in Turkey. Based on these findings, policy ramifications are initiated. Full article

This study examines the direction of causality between Gross Domestic Product, foreign aid, foreign direct investment, and gross capital formation in Indonesia from 1970 to 2019, using the augmented Toda–Yamamoto approach with the Granger causality test. Furthermore, this study achieved the unit root test for both variables using the ADF test, which confirmed that the variables studied were cointegrated and had a prolonged equilibrium relationship with GDP, ODA, FDI, and GCA. The Toda–Yamamoto causality test was used to investigate the direction of causality between variables. The results showed a positive one-way causality between ODA and GDP as well as between FDI and GDP. ODA has promoted the expansion of economic and development activities, thereby leading to GDP in Indonesia. However, despite having a long-run relationship, the study failed to prove a causal relationship between ODA and GCA in Indonesia. Therefore, there is a need for more optimal foreign aid management to attract foreign direct investment. Full article

Rapid urbanization, coupled with income growth, will inevitably cause the residential energy consumption in the North Africa region to continue to increase, with adverse effects on the climate, human health, and the economy. In these regards, this paper explores the relationship between residential carbon dioxide emissions (RCO₂), urbanization, economic growth, and residential energy use in four North African countries (Morocco, Tunisia, Algeria, and Egypt) over the period 1990–2016. To do this, we used the bounds cointegration and the Toda–Yamamoto Granger causality test. The existence of cointegration relationships was confirmed for the four countries. In the long run, the environment Kuznets curve relationship between increased income per capita and RCO₂ emissions was verified for only Morocco and Tunisia. The causality analysis also reveals a combination of neutral, unidirectional, and bidirectional relationships for all countries. The RCO₂ emissions have not proved to be a limiting factor in any country’s economic growth. The findings of this study certainly contribute to advancing the existing literature by emphasizing the income–pollution nexus in African countries. Policy makers and government regulators should implement the necessary policies that accelerate the development of renewable technologies to drive sustainable cooling and heating as well as water management. Full article

This research is the earliest attempt to understand the impact of inflation and the interest rate on output growth in the context of Pakistan using the wavelet transformation approach. For this study, we used monthly data on inflation, the interest rate, and industrial production from January 1991 to May 2020. The COVID-19 pandemic has affected economies around the world, especially in view of the measures taken by governmental authorities regarding enforced lockdowns and social distancing. Traditional studies empirically explored the relationship between these important macroeconomic variables only for the short run and long run. Firstly, we employed the autoregressive distributed lag (ARDL) cointegration test and two causality tests (Granger causality and Toda–Yamamoto) to check the cointegration properties and causal relationship among these variables, respectively. After confirming the long-run causality from the ARDL bound test, we decomposed the time series of growth, inflation, and the interest rate into different time scales using wavelet analysis which allows us to study the relationship among variables for the very short run, medium run, long run, and very long run. The continuous wavelet transform (CWT), the cross-wavelet transform (XWT), cross-wavelet coherence (WTC), and multi-scale Granger causality tests were used to investigate the co-movement and nature of the causality between inflation and growth and the interest rate and growth. The results of the wavelet and multi-scale Granger causality tests show that the causal relationship between these variables is not the same across all time horizons; rather, it is unidirectional in the short-run and medium-run but bi-directional in the long-run. Therefore, this study suggests that the central bank should try to maintain inflation and the interest rate at a low level in the short run and medium run instead of putting too much pressure on these variables in the long-run. Full article