Toda-Yamamoto Causality Research Articles

THE IMPACT OF EMPLOYMENT IN SELECTED SECTORS ON ECONOMIC ROWTH: THE CASE OF IRAQ

The aim of the research is to analyses the effect of employment on economic growth and to assess the impact of this effect on agriculture, industry and services. In line with the findings from the related literature, this study applied an ARDL bounds test and Toda Yamamoto causality analysis on the Iraqi case. The study found that, employment increases in agriculture, industry and services sectors have a positive impact on economic growth. Long-run coefficient results reveal that increases in employment in these sectors has a positive relationship with economic growth. In particular, increases in employment in the agricultural sector are found to significantly support economic growth. In accordance with the results of the Toda-Yamamoto causality analysis, there is a unidirectional causality relationship between economic growth and agriculture, industry and services sectors. This can be explained by the interaction of various sectors of the economy with each other and this interaction encourages economic growth. Although agriculture, industry and services sectors have different contributions to economic growth, each of them has a positive effect on growth.

Energy, Debt, and Growth: Time Series Evidence on Causality in OECD European Countries

In this paper, we explore the causal relationships between energy, debt, and growth for a selection of nine OECD European countries. This examination enables us to draw lessons and deduce implications regarding the interconnections between these variables, helping us determine whether they evolve independently, or are mutually related. To conduct this analysis, we utilize annual data and employ econometric techniques, including vector-autoregressive (VAR) models, as well as Granger and Toda-Yamamoto causality tests, applied to specific countries within the group. Our key findings provide significant insights, enabling us to categorize the countries by their levels of indebtedness and energy independence. The inclusion of energy supply results in a more coherent segmentation of countries, consistent with descriptions in the literature. This classification provides a clearer understanding of the economic and energy dynamics within these nations and helps inform policy decisions aimed at managing debt levels and enhancing energy security.

Effects of Social and Economic Development on CO2 Emissions in the Countries of the Visegrad Group

The aim of this study is to assess the impact of socio-economic development, consumption of renewable energy, educational spending, and foreign direct investment on carbon dioxide emissions in the Visegrad countries (Czech Republic, Hungary, Poland, and Slovakia) between 1991 and 2021. The study employed the Autoregressive-Distributed Lag Bound Testing model and Toda–Yamamoto causality tests to establish short- and long-term relationships for each of the dependent variables and countries, aiming to verify the hypotheses. For the Czech Republic and Slovakia, a bidirectional relationship was identified between carbon emissions and the Human Development Index (HDI). In Poland, bidirectional causality was indicated between renewable energy consumption and carbon dioxide emissions. Unidirectional causality was evident for the Czech Republic, Hungary, and Slovakia between the specified variables. Short-term findings indicate that an increase in renewable energy production may lead to higher carbon dioxide emissions in the Visegrad countries. In the long term, only Slovakia demonstrates a significant relationship between educational spending and reduced carbon emissions. Toda–Yamamoto tests reveal unidirectional causality between foreign direct investment and carbon dioxide emissions for the Czech Republic and Slovakia. Empirical findings suggest that policymakers should invest in socio-economic development and renewable energy to reduce CO2 emissions and achieve long-term sustainability in the Visegrad countries. Poland needs to shift its energy policy away from coal, and all countries should enhance education to effectively transmit environmental knowledge and values.

Assessing the impact of tourism on sustainable economic development in Indonesia: A comprehensive analysis using the Fourier bootstrap autoregressive distributed lag approach

This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

Is natural resource wealth a boon or a bane? The impact of oil rents and foreign direct investment on economic growth in Kazakhstan

The nexus between foreign direct investment, natural resource endowment, and their impact on sustained economic growth, is contentious. This study investigates the resource curse hypothesis and the effects of FDI on economic growth in Kazakhstan. The study covers the period from 1990 to 2022 and employs the Autoregressive Distributed Lag (ARDL) model and Toda-Yamamoto causality methods. The Bounds cointegration results reveal the existence of long-term equilibria between per capita GDP and the predictors. The findings reveal a significant impact of oil rents on economic growth, contradicting the resource curse hypothesis and suggesting a resource boon instead. In stark contrast, the impact of FDI on Kazakhstan’s economic growth is found to be insignificant, despite the presence of a causal nexus. Furthermore, economic freedom and export diversification have a positive significant impact on economic growth, while inflation exhibits a negative but significant impact. Although governance has a direct impact on GDP per capita, it is deemed insignificant, as the negative average governance index implies poor governance. Expectedly, the result establishes a causal effect between export diversification, economic freedom, governance, oil rents, and economic growth. This underscores the fundamental role played by the interplay of diversification, economic freedom, governance, and oil rents in fostering sustainable economic growth. In addition, economic freedom stimulates gross fixed capital formation, indicating that it enhances domestic investment. Notably, the findings refute the crowding-out effect of FDI on domestic investment in Kazakhstan. Consequently, to escape the resource curse and the Dutch disease syndrome, the study advocates for enhancing good governance capabilities in Kazakhstan. Thus, we recommend that good governance could reconcile the twin goals of economic diversification and deriving benefits from oil resources, ultimately transforming oil wealth into a boon in Kazakhstan.

MACRO-ECONOMETRIC ANALYSIS OF INWARD CAPITAL FLOWS: A CASE OF NIGERIA IN TIMES OF SECURITY CHALLENGES

This study used quarterly data for the period of 2014Q1–2021Q2 to investigate the macro-econometric implications of capital flows to Nigeria in the face of security challenges. The ARDL bounds test technique identified the long-run relationships between macroeconomic dynamics, insecurity, and total capital inflows to Nigeria, while the error correction mechanism (ECM) identified the short-run relationships. The Toda-Yamamoto test was used to determine whether the model variables were causally related or not. The findings pointed to a short-term negative relationship between insecurity, exchange rates, lending rates, and inflows of capital, while a positive relationship was found between industrial production capacity, the consumer price index, and the total inflows of capital to Nigeria, with insecurity, exchange rates, the consumer price index, and lending rates being the most significant variables. In the long run, insecurity, lending rate, and consumer price index had no significant impact on inward capital inflows, while exchange rate and industrial production capacity exerted significant impacts on capital inflows. The lending rate had a negative impact on overall inflows of capital, whereas the exchange rate, industrial production capacity, and consumer price index had positive impacts. The exchange rate and industrial production capacity were the most important variables that affected capital inflows. Based on the ECM, it was realized that aggregate inward capital flows were stabilized by a factor of roughly 47.2% per quarter in order to reach long-run equilibrium. The Toda-Yamamoto causality tests indicated that the interactions between macroeconomic variables and insecurity strongly influenced capital flows to Nigeria. The overall findings suggested that promoting macroeconomic stability and combating insecurity could improve the investment climate, encouraging foreign capital flows into Nigeria.

Exploring Saudi Arabia’s 2060 net zero-emission paths via fractional frequency Fourier procedures. The imperatives of resource efficiency, energy efficiency, and digitalization

ABSTRACT By applying the novel fractional frequency Fourier ARDL technique, we unraveled the intricacies underpinning resource efficiency, energy efficiency, digitalization, and environmental sustainability in Saudi Arabia. Compelled by the conflicting narratives of prior investigations and the need for updated insights, the analyzed time series spanning 1990–2022 periods divulged interesting insights amenable to policy optimization. First, the fractional frequency Fourier ADL cointegration procedure reveals a long-term association among all the enlisted series. Second, resource and energy efficiencies, as well as digitalization, improved environmental quality by limiting carbon intensities and ecological footprint with some heterogeneous attributes across the timeframes. Notably, while resource efficiency is more effective toward ecological footprint mitigations, energy efficiency proves more efficient for carbon intensity reductions. Lastly, the fractional frequency Fourier Toda-Yamamoto causality test affirms the predictive attributes of the enlisted series on environmental performance. Hence, these factors are critical to KSA’s environmental sustainability paths. Based on these empirical discoveries, policymakers in KSA must pay adequate attention to the efficient utilization of resources and energy to complement other steps toward realizing Saudi Arabia’s 2060 net zero-emission. Likewise, policymakers must ensure the efficient allocation of income to environmentally sensitive ventures to curtail its negative repercussions on the environment. Other relevant steps to curtail carbon intensities and ecological footprint for optimal environmental performance in KSA have been highlighted.

Effects of FDI on the Growth of Agricultural Sector in Côte d'Ivoire: An Empirical Analysis Based on Toda-Yamamoto Causality Tests and ARDL Cointegration

This paper analyses the contribution of Foreign Direct Investment (FDI) to agricultural growth in Côte d'Ivoire over the period 1980-2021. The data come from World Development Indicators WDI (World Bank). The Toda-Yamamoto causality test and the ARDL cointegration approach are used. The results of the Toda-Yamamoto test show no causal link between FDI and agricultural growth, while those of the ARDL approach indicate that FDI has a negative impact on agricultural growth. There are several reasons for these results: insufficient resources allocated to the agricultural sector and the predominance of FDI in other sectors of activity in Côte d'Ivoire. Our results also show the role that the State must play in building infrastructure and increasing foreign trade.

The Relationship Between Sectoral Employment and Real Sector Economic Confidence: Fourier Causation Analysis

Purpose –In order to ensure economic growth in the short term and economic development in the long term, it is important to evaluate the events occurring in the political and economic order correctly and to meet the expectations. This study was created to evaluate the effectiveness of economic confidence on the relevant sectors on a sectoral basisDesign/Methodology/Approach –In this study, the relationship between the real sector economic confidence index and employment rates in industry, construction and services sectors will be analyzed. Turkey is selected as the sample and the data range subject to the analysis is determined as 2009:01-2023:08. In the study, the Fourier analysis method, which is among the new generation analysis methods, was applied, and Fractional Frequency Fourier Augmented Dickey Fuller Unit Root Test and Fourier Toda-Yamamoto Causality Test were applied.Findings –As a result of the application, a one-way causality relationship from the real sector economic confidence index to building and industry sector employment was determined. A recommendation should be made regarding the necessity of making political arrangements that will maintain the stability level of employment in the relevant sector.Discussion –In line with the data obtained in this study, the fact that real economic confidence has an effect on employment in the construction and industrial sectors, in addition to the fact that sectoral employment has no effect on the real economic confidence index, can be linked to the fact that sectoral leaders pursue a policy of contraction or expansion within the framework of expectations

The Relationship between Agricultural Production, Agricultural Exports and Economic Growth in Türkiye: Cointegration and Causality Analysis

This study aimed to assess the influence of agricultural production and agricultural product exports on economic growth within the Turkish economy. To achieve this, annual data spanning from 1980 to 2022 were utilized to construct a model, employing the ARDL Bounds Test to discern the long-term cointegration relationship among variables and the Fourier Toda-Yamamoto Causality Test to determine causality relationships. The empirical findings from the ARDL Bounds Test indicate that increases in both agricultural production and agricultural product exports positively impact economic growth. Moreover, results from the Fourier Toda-Yamamoto Causality Test unveil a two-way causal relationship between agricultural production and GDP, while a one-way causality relationship is observed between agricultural product exports and GDP. Despite the declining share of the agricultural sector in GDP over the years in Turkey, these findings underscore the enduring importance of agriculture in driving economic growth and creating value. As potential solutions to Turkey's balance of payments challenges, strategies such as boosting domestic demand, expanding the domestic market, and augmenting agricultural sector contributions to foreign exchange earnings through agricultural export subsidies are proposed. Furthermore, efforts to mitigate income disparities between the agricultural sector and other sectors could foster socio-economic development in rural areas, thus promoting a more equitable distribution of national income across society.

Powering Growth: The Dynamic Impact of Renewable Energy on GDP in ASEAN-5

This study investigates the dynamic relationships between renewable energy consumption, labor force, gross fixed capital (GFC), and GDP across ASEAN-5 nations from 1984 to 2020. Utilizing data from the World Development Indicators (WDI), the Energy Information Agency (EIA), and national labor statistics, we employ unit root tests, ARDL bound testing for cointegration, and Toda-Yamamoto causality procedures. Our findings indicate significant long-term cointegration between the studied variables in Indonesia and the Philippines, suggesting persistent economic relationships, while results for Malaysia show no cointegration and remain inconclusive for Thailand. The economic analysis reveals that GFC robustly drives GDP growth across these countries, whereas the impacts from labor force and renewable energy consumption are more variable. Causality tests further demonstrate that renewable energy consumption significantly fosters GDP growth in Indonesia, Malaysia, and Singapore, aligning with the growth hypothesis. Conversely, findings for the Philippines and Thailand support the neutrality hypothesis, indicating no direct causal impacts. These insights underline the crucial role of tailored renewable energy strategies to enhance economic growth and sustainability in ASEAN-5, providing valuable policy implications for regional energy governance.

The Relationship between Renewable Energy Consumption and Economic Growth: Insights from Iceland and Azerbaijan

Iceland leads globally in per capita green energy production, while oil-dependent Azerbaijan endeavors to transition its energy policy towards sustainable alternatives. Investigating the impacts of renewable energy consumption on the economy represents a significant contemporary scientific inquiry. The objective of this research is to empirically examine the causal relationship between GDP per capita, a key metric of economic growth, and renewable energy consumption, a fundamental aspect of the green economy. In this research, the Toda-Yamamoto causality test framework of the vector autoregressive (VAR) model was utilized to examine the causal relationship between the variables. The outcomes of this investigation reveal a significant causality between renewable energy consumption and economic growth in Iceland and Azerbaijan.

The role of environmental innovation on ecological footprint in nations with high technology exports concentrations in international trade

This study focuses on four major high-technology exporting countries––the USA, Germany, France, and China––to explore the long and short-run associations among ecological footprint, environmental technology patents, high-technology exports, and economic growth. The sample covering 1988–2019 is subject to a set of structural breaks, including 2009 Global Recession in addition to uncertainty in the order of integration captured by unit root tests, which provide basis for novel Fourier ARDL and Fourier Toda-Yamamoto causality methods. The Fourier ARDL findings reveal the importance of environmental technology innovations in dampening the level of ecological footprints and promoting a more sustainable environment in the USA, Germany, and France, whereas more high-technology exports in international trade worsen the ecological footprints in these countries in addition to the negative effects of economic growth in all countries including China. In contrast, high-technology exports appear to mitigate ecological footprint in China, however, eco-friendly technologies fail to reduce ecological footprints as in other analysed nations. The causality tests indicate bidirectional and unidirectional causal relationships among variables with the exception of China where the neutrality hypothesis holds between economic growth and ecological patents and also high-technology exports and ecological patents. These findings provide important insights in achieving sustainable development.

The impact of renewable energy, eco-innovation, and GDP growth on CO2 emissions: Pathways to the UK's net zero target

In May 2019, the Climate Change Committee (CCC) recommended that the UK adopt a net-zero target, aiming to reduce its greenhouse gas emissions (GHG) by 100% from the 1990s baseline by 2050. The government accepted the recommendation, and the UK became the first major economy to establish a net-zero emissions law. To progress towards its climate objectives, the government took several initiatives, such as increasing its reliance on renewable energy sources and investing in climate mitigation technologies, which are commonly referred to as process eco-innovation. This study examines the impact of eco-innovation, process eco-innovation, renewable energy consumption, and economic growth on CO2 emissions in the UK using data from 1988 to 2020. We used the ARDL bound test with an error correction model (ECM) to examine the long-run and short-run cointegration between the variables of concern. We found that eco-innovation, process eco-innovation, and renewable energy consumption have significant roles in mitigating CO2 emissions, while economic growth contributes to environmental degradation in the UK. We also found that the effect of eco-innovation on CO2 emissions abatement is stronger than that of process eco-innovation in the short and long-run. Our robustness tests have confirmed the accuracy of those findings. In addition, the results from the Toda-Yamamoto causality revealed a one-way causality from process eco-innovation to CO2, renewable energy to CO2, and eco-innovation to CO2 emissions. Further, a bidirectional causality was found between GDP and CO2 emissions. The evidence presented in this paper provides great insight for shaping the energy policy in the UK and for establishing the climate budget in line with the country's net-zero target.

Impacts of economic development, globalization, and gross capital formation on natural resources rents: Evidence from India

Natural resources are a country's wealth, and resources economics and policy literature has extensively researched how to utilize this richness as a determinant of the country's growth. However, the primary challenges reside in establishing economic development as a driver for natural resource rents. Given this context, this study explores the association between economic development, globalization, gross capital formation, and natural resources rents in India. For the empirical research, the study employed Dynamic Auto-Regressive Distributive Lag (DARDL) simulation and Kernel-based Regularized Least Squares (KRLS) approaches on yearly data from 1990 to 2020. The present research used a unit root test to ascertain the stationary state across all variables, establishing their long-term cointegration connection. Results suggest that capital formation and economic development positively impact rents derived from natural resources in India, while globalization negatively affects natural resources rents. Unidirectional causation of economic development, globalization, and gross capital creation to natural resources rents has been established in this study using the Toda-Yamamoto causality model. Our findings have important policy implications and support the idea that sustainable economic growth models inherently rely on factors like the efficient utilization of natural resources and globalization.

Modeling of Brazilian Wind Power Generation Capacity: A Multivariate Analysis with Neural Networks

Over the last twenty years, Brazil has experienced significant changes in its electric energy matrix, notably with the expansion of wind and solar energy sources. In the early 2000s, hydroelectric plants with a capacity of 70 gigawatts (GW) were responsible for generating 90% of the country's electricity, while solar and wind sources contributed merely 1%. Today, the scenario has evolved, with wind and solar energy comprising approximately 25% of the national generation, indicating a departure from the previous hydro-dominated matrix. This research aims to apply specific types of neural networks to multivariate data to forecast Brazil's wind power generation capacity, providing insight into the potential for future energy strategies. This research contributes as a as a decision support tool contemplating relevant information for analysts, researchers, and participants in the renewable energy market. The monetary volume destined to import key components of the wind, considering specific time lags, was utilized to forecast the Installed capacity of the wind farms in Brazil. The Toda-Yamamoto Causality Tests revealed unidirectional Granger causality in the sense of the Import variable for the Brazilian Installed Capacity variable for wind energy production. Another result obtained was the finding that the variable that matters most in the multivariate configuration of the Neural Network is the variation in Installed Capacity in megawatts, followed by the import volume of wind energy components, which exhibited critical lags at 3 and 6 months.

The Impact of Nuclear Energy Consumption, Green Technological Innovation, and Trade Openness on the Sustainable Environment in the USA

Nuclear energy, renewable energy, and alternative energy sources are all crucial for sustainable green energy. However, the existing literature often needs to pay more attention to the role of nuclear energy in achieving sustainable development goals. This study analyzes the impact of green technological innovation, nuclear energy consumption, and trade openness on environmental quality in the US. The authors used the ARDL bounds to identify cointegration relationships, which is appropriate for this study’s dataset as it works well with smaller samples. They also used the Toda–Yamamoto causality test to examine causal links. The ARDL cointegration results indicate a significant long-term relationship between CO2 emissions, green technological innovation, nuclear energy consumption, and trade openness. Green technological innovation has a negative impact on CO2 emissions. Higher nuclear energy consumption is associated with lower CO2 emissions, while greater trade openness is associated with higher CO2 emissions, although these effects are less certain. The results suggest promoting green technological innovation and nuclear energy can be effective strategies for reducing CO2 emissions, while the impact of trade openness requires careful consideration due to its potential to increase emissions.

The Impact of Climate Change on Life Expectancy in the UK: Empirical Evidence from Fourier Bootstrap ARDL Procedure

This study aims to determine the impact of surface temperature change, considered a proxy for climate change in the United Kingdom, on life expectancy using annual data from 1990–2021. Government expenditure is used as a control variable. The Fourier function-based bootstrap autoregressive distributed lag model is utilized to examine the cointegration among variables. The analysis outcomes reveal a long-term relationship between life expectancy, surface temperature change, and government expenditure. Furthermore, the findings reveal that surface temperature change significantly reduces life expectancy in the long run, while there is no significant relationship between the two variables in the short term. The Toda-Yamamoto causality analysis results show a unidirectional causality relationship between surface temperature change and life expectancy. Additionally, a significant bidirectional causality relationship is found between life expectancy and government expenditure.

Why Did House Prices Go Up During COVID-19 Pandemic? Policy-Driven or Market-Driven?

During the spread of the COVID-19 virus, governments in many countries took temporary measures to mitigate and/or remove the cost of its negative effects on both society and the economy. In Türkiye, as in many countries, the deposit banks cut mortgage interest rates. Thus, Türkiye has experienced large increases in house prices, as have many countries. Türkiye has also become the country with the highest average annual rate of house price increase among the Organisation for Economic Co-operation and Development (OECD) countries during the pandemic period. However, despite an increase in the number of studies on house prices or mortgage loans during the pandemic period, there is a research gap in terms of a comparison of the relationship between house prices and mortgage loans in the pre-pandemic and the pandemic periods compared with that on other assets or in other sectors,. This study aims to rectify this gap. To achieve this, both the Fourier Granger and the Fourier Toda-Yamamoto causality tests are used. The results indicate that there are differences in both periods of time with respect to the relationship between mortgage loans and house prices in Türkiye, and that there is a causal relationship between both factors in the prepandemic period, but not during the pandemic period.

The Causal Relationship Among Barley Production and Some Variables in Libya Using The Toda-Yamamoto Causality Test

The Causal Relationship Among Barley Production and Some Variables in Libya Using The Toda-Yamamoto Causality Test