Panel Vector Autoregressive Model Research Articles

Examination of carbon dioxide emissions and renewables in Southeast Asian countries based on a panel vector autoregressive model

Recently, the increasing energy consumption for economic growth has resulted in higher carbon dioxide (CO2) emissions. In this regard, the reduction of such emissions has become one of the main targets of economic planning for both developed and developing countries. Thus, this study determines whether economic growth and increased energy consumption can have a significant impact on CO2 emissions and whether this relationship is mutual, bidirectional, or unidirectional. For this purpose, we employ a panel autoregressive (VAR) model and focus on a group of developing countries in Southeast Asia in which their economic and population growth are expected to increase CO2 emissions in the future. Additionally, we examine their difficulties in meeting the CO2 emission targets and consider modern renewable energy sources (RES) in our quantitative research. Based on the results, there have been various rebound effects and rising expenses for modern RES in these countries, which have hampered their long-term goal of reducing CO2 emissions. The implication of the findings is that it is important to tailor subsidy schemes and energy policies to the specific needs of developing countries and their respective populations.

Dynamic effect of smartness on environmental sustainability: Based on PVAR model for 72 Chinese cities

With the continuous implementation of the smart city concept, smart cities have become an important tool for the country's new urbanization. Therefore, it is of great concern whether smart cities can help promote environmental sustainability. Most of the existing studies mainly discuss whether the proposed smart policies are effective for environmental sustainability, but the specific impact paths are not clear and long-term dynamic implications for policy have not yet been explored in depth
 This study takes 72 cities in China as an example, and divides the impact path of smart cities into four aspects: internet technology, science and technology innovation(STI), smart environment and smart people's livelihood. Environmental sustainability is measured by energy consumption and air pollution, and the cities are divided into characteristic cities according to resource endowment and economic development, and the dynamic impact on environmental sustainability is explored based on the Panel Vector Auto-Regression (PVAR) model. The results indicate that STI has a negative effect on air pollution in all cities in the early stage and a positive effect in the later stage, with the overall effect being more significant in developed cities. Internet development has an impact on air pollution control in developed cities, but the effect is positive in the early stage and negative in the later stage. STI and Internet technology have very significant results on energy consumption reduction. But for developed cities, the effect of STI on energy consumption is positive. This paper provides policy suggestions for the sustainable development of environment in cities with different characteristics in China from the perspective of smart city development.

Dynamics between electric vehicle uptake and green development: Understanding the role of local government competition

Electric vehicles (EVs) play a pivotal role in advancing transport electrification, a crucial step towards achieving a net-zero emission economy and facilitating decarbonization. This study presents groundbreaking evidence to systematically explore the impact of EV uptake on green development in China, using 35 national centre cities from 2010 to 2019. The empirical outcomes uncover that EV uptake contributes significantly to green development, irrespective of the procedures applied. Further analyses demonstrate that local governments' tax and revenue competition significantly inhibit green development, confirming the “race to bottom” effect. This competition, when coupled with increasing EV adoption, results in pronounced negative externalities for sustainable development mainly via the overcrowding effect. Reinforcing these findings, the panel vector autoregressive model provides further empirical validation. This study not only underscores the benefits of EVs but also highlights the nuanced challenges posed by local government dynamics in the quest for sustainability.

Empirical study on the impact of tax reduction on the development of Chinese green energy industry.

The implementation of tax reduction policies in China represents a significant and effective strategy. Accordingly, this strategy has been designed to facilitate the development of a green economy by establishing a market-oriented allocation system for environmental and resource elements, while simultaneously invigorating microeconomic entities. As the nation navigates towards the adoption of green, low-carbon production, and lifestyles, the role of clean and green energy emerges as a vital necessity. Therefore, to explain the impact of tax reduction policies on the green energy industry, this study collected and compiled financial indicator data from 100 listed companies in the green energy sector, utilizing the China Stock Market Accounting Research database (CSMAR) as a source for research samples. A Panel Vector Auto Regression (PVAR) model was employed to observe the effects of tax reduction policies on the energy industry, while the dosage effects Difference in Difference (DID) model was utilized to verify and supplement the findings. In summary, the findings of this study can be summarized as follows: firstly, tax reduction policies exert a positive impact on the green energy industry by effectively mitigating the financial cost burden on green energy enterprises, thereby reducing production expenses and amplifying their profitability. Secondly, such policies bolster the capital turnover rate of enterprises in the short term, thereby enabling augmented research and development investments, refining production efficiency, and enhancing competitiveness. Through rigorous analysis and demonstration, the research findings accentuate the stimulative and propulsive impacts of tax reduction policies on the flourishing development of the green energy industry. Furthermore, this study provides relevant fiscal and tax policy recommendations, thoughtfully derived from the research findings.

The combined effect of regulators’ and retailers’ actions to stimulate consumer participation in retail energy markets

Active consumer participation in retail markets is crucial for an affordable and sustainable energy transition. While energy regulators encourage active consumer participation through policies which decrease consumers’ switching costs, energy retailers seek to advance customer retention to boost profits. This study investigates how these seemingly opposing goals influence consumer participation in energy retail markets. Using data on the Dutch energy markets, we combine micro-economic and marketing insights through a retailer-aggregated panel vector auto-regression (VAR) model and a market-level VAR to analyse the dynamic interactions. The results indicate that the regulator affects consumer participation both directly and indirectly through energy retailers’ actions. We conclude that energy retailers’ acquisition and retention actions do not counteract the regulator’s efforts to increase active consumer participation. While retention actions lead to decreased switching behaviour, they concurrently decrease perceived switch costs while increasing search behaviour and the consideration to switch. Therefore, retention actions may still improve consumer welfare. Our research reveals mediating relations that require comprehensive examination of the overall impacts of regulatory policies and energy retailer’s actions.

Dynamic relationship between marine fisheries economic development, environmental protection and fisheries technological Progress—A case of coastal provinces in China

With the deepening of economic globalization and regional economic integration, as well as the emergence of “black swan” events such as the novel coronavirus epidemic and the Russia-Ukraine conflict, marine fisheries is increasingly linked to national strategic interests and economic lifeblood. Under the new situation, it is necessary to explore the synergistic evolution of marine fisheries economic development, environmental protection and fisheries technological progress, so as to help the sustainable and healthy development of marine fisheries. Based on the panel data of 11 coastal provinces and cities in China, from 2006 to 2020, this study constructs an integrated framework of a marine fisheries economy–environment–technology system and utilizes methods such as entropy method, Tapio decoupling index, coupling coordination degree model, and panel vector autoregressive model to analyze its comprehensive development, collaborative evolution, and dynamic correlation mechanism. Results show the following: (1) The comprehensive development index of the fisheries economy and technology subsystems was generally on the rise, but that of the marine environment subsystem was on the decline and fluctuating. (2) The development of the marine fisheries economy–technology subsystem was relatively coordinated, but the decoupling of marine environment from fisheries economy and technology was relatively obvious. The three marine fisheries subsystems reached reluctant coordination, but most of the regions shifted from being driven by economy–environment coupling to leading by economy–technology coupling, which indicates that the deteriorating marine environment hindered the marine fisheries system from achieving high-level coordinated symbiosis. (3) The three marine fisheries subsystems possessed self-reinforcing mechanisms, but the positive effect was relatively limited in long-term development. Moreover, the marine fisheries environment subsystem has yet to achieve sustainable and benign interaction with the economy and technology subsystems. Therefore, it is urgent to take quality and efficiency improvement as the core, facilitating the leap of marine fisheries economy, adopt green environmental protection as the key, consolidating the bearing foundation of marine environment, and employ scientific innovation as the sail, effectively playing the leading role of fisheries technology.

Online reviews, customer Q&As, and product sales: A PVAR approach.

Online reviews and customer Q&As have emerged as two vital forms of electronic word-of-mouth (eWOM) that significantly influence consumer decisions in e-commerce. Yet, a comprehensive understanding of the individual and combined roles of these eWOM types in shaping market dynamics remains elusive. This study addresses this research gap by tracking and analyzing three months of eWOM and sales data for 120 laptops on Amazon, comprising 7,205 online reviews, 6,365 customer Q&A questions, and 7,419 answers. Leveraging the Panel Vector Autoregression (PVAR) model and STATA16.0 software, we unravel the intricate dynamics between online reviews, customer Q&As, and laptop sales. The empirical results reveal distinctive influence mechanisms of online reviews and customer Q&As on product sales, with review volume and answer valence positively affecting sales. Importantly, answer volume was found to stimulate online reviews and enhance their valence. Our study elucidates the interplay among online reviews, customer Q&As, and product sales, underscoring the need for future research on multi-type eWOM. Further, the insights gleaned offer valuable guidance for online platforms and retailers to strategize their eWOM management.

The Coupling Coordination and Interaction Mechanism of Land Ecological Security and High-Quality Economic Development in the Beijing–Tianjin–Hebei Region

Land ecological security (LES) and high-quality economic development (HED) are mutually influential. China has three world-class urban agglomerations; the Beijing–Tianjin–Hebei (BTH) region is one of them. It is an important platform for participating in international competition and cooperation. To promote regional sustainable development, it is critical to study the coupling coordination and interaction mechanism of LES–HED subsystems over time and space in the BTH region. This study involved the construction of an aggregated index system to obtain a comprehensive understanding of the subsystems, and then investigated the coupling coordination degree (CCD) of the LES–HED subsystems from 2007 to 2018 using a CCD model. Additionally, a panel vector autoregressive (PVAR) model was applied to analyze the interactive mechanism of the LES–HED subsystems. Finally, a model of the degree of relative development was used to classify the types of regional development. The results showed that the CCD of the LES–HED subsystems in the BTH region had significant spatial and temporal differences. The spatial distribution could be characterized as low in the central area and high in the peripheral area, and the evolutionary law of CCD in the system was from lower to higher levels over time. In addition, improvements in LES promoted HED, but the impact of HED on LES was limited. The development patterns within the cities of the study area included three development types, including an slightly lagging type of LES, a slightly lagging type of HED, and a significantly lagging type of HED. Given the spatial variability of the coupled and coordinated development of LES–HED subsystems, it is necessary to implement different development strategies. This study can inform decisions promoting the coordinated development of LES–HED subsystems for sustainable regional development.

Green finance, economic growth, and carbon emissions: a PVAR analysis.

The study examines the relationship between green finance development, carbon emission intensity, and economic development in China's 30 provinces. The entropy approach is used to calculate the green finance development index, and a panel vector autoregressive model is established using this index along with economic development and carbon emission intensity. The study finds that green finance can promote economic growth and help achieve emission reduction objectives, while increasing carbon emissions can also promote economic growth. The study also highlights regional differences, with the economic growth of the eastern and central regions negatively correlated with carbon emissions after surpassing the inflection point of the environmental Kuznets curve. Additionally, the study suggests that there is still room for growth in green finance in the western region. The findings have important policy implications for China in developing targeted development strategies.

The tapestry of green economics: mapping the nexus of CO2 emissions, economic growth, and renewable energy

ABSTRACT This study examines the relationships between CO2 emissions, GDP, renewable energy consumption, and trade openness across 37 OECD countries from 1995–2020. Using a Panel Vector Autoregressive (PVAR) model and Granger Causality tests, the research probes the causality among these factors. Key findings show a notable causality from GDP, renewable energy, and trade openness to CO2 emissions. Specifically, lags in renewable energy consumption and trade openness significantly decrease CO2 emissions. Surprisingly, GDP's influence on CO2 emissions is found to be negligible, challenging the typical belief linking economic growth to environmental degradation. These insights hold great value for policymakers in environmental governance and climate finance. The data underscores the importance of promoting renewable energy and trade openness for effective CO2 reduction. The study advocates a sustainable environmental governance model, emphasizing strong legal structures and clarity in execution. Since GDP doesn't significantly impact CO2 emissions, there's potential to pivot towards sustainable economic growth models. The research offers a foundational empirical groundwork, suggesting that expanding future studies to include diverse variables might yield a more comprehensive understanding of the relationships in question.

Dynamics of Macroeconomy, Medicaid, and State Fiscal Conditions: A Role of Medicaid Expansion.

One of the main concerns of state governments about Medicaid expansion is the potential increase in state fiscal burden following the rise in enrollments. In previous literature, limited attention has been paid to the effect of macroeconomic changes, which are closely linked to Medicaid enrollments, in understanding the impact of Medicaid expansion on a state. To narrow the gap, this study establishes a synthetic model to represent the transmission channel from an unemployment shock to the Medicaid program and state expenditures. The panel vector autoregression (VAR) model is adopted for the empirical analysis using annual data from 2010 to 2019 for 50 US states and D.C. The unit root and Granger causality tests are conducted to check the model's appropriateness. The estimated results are analyzed by using impulse response functions. A sudden increase in the unemployment rate will raise the number of Medicaid enrollees and the state Medicaid expenditure, but the impact on the overall state budget is not clear. States that adopt Medicaid expansion will encounter surges in enrollment and increasing Medicaid expenditure during the economic recession, while the non-expansion states will only have moderate enrollment increases. However, an increased budgetary burden per new enrollees will not be significant at its level. Medicaid expansion will allow more people to benefit from the public health insurance program during an economic recession while the impact on states' fiscal burden will be moderate.

The Dynamic Relation between the Oil Price Volatility, Stock Market, Exchange and Interest Rate in GCC Countries: Panel Vector Autoregressive (PVAR) Model

The Dynamic Relation between the Oil Price Volatility, Stock Market, Exchange and Interest Rate in GCC Countries: Panel Vector Autoregressive (PVAR) Model

Recognizing the nexus between grid infrastructure, renewable energy, net interregional transmission and carbon emissions: Evidence from China

AbstractOver the past few decades, China has undergone an unprecedented structural transformation, stupendously transforming its energy and environmental systems and decarbonizing pathways. Nevertheless, around the share of clean and renewable energy generation with the goal of low‐carbon, it is still ambiguous how the dynamic relationship between the upgrading of grid infrastructure, interregional power trading and the investment and economic foundation that support their collaborative promotion forms. Thus, under the framework of panel vector autoregressive models, we study the bridge that links the key dominant factors in the pattern of electricity supply and demand such as grid infrastructure, power generation share of clean and renewable energy, net power input and carbon emissions. The results show that the governance framework dominated by power grid infrastructure upgrading, interregional power input dependence and carbon constraint mechanism to promote clean‐oriented energy mix is still flawed. In addition to improve the utilization rate of power grid infrastructure, relevant policy makers should devote more efforts to software conditions including interregional and interprovincial power trading and grid‐connecting mechanisms of clean and renewable energy.

Tourism Demand in the Face of Geopolitical Risk: Insights From a Cross-Country Analysis

This paper develops a novel Bayesian heterogeneous panel vector autoregressive model (B-HP-VAR) that quantifies the impact of geopolitical risk shocks on the tourism industry of 14 emerging market and developing economies (EMDE). We find that increasing geopolitical tensions have a persistent negative effect on tourism demand in most of these countries, as shown by our impulse response estimates. Furthermore, evidence from forecast error variance decomposition reveals that geopolitical risk shocks in many EMDE economies constitute the main driver of tourism demand. Analysis from historical decompositions demonstrates that geopolitical tensions have been particularly influential in driving tourism demand in Ukraine, Russia, Turkey, China, Indonesia, Thailand, Colombia, and Mexico. Our main findings are robust to several perturbations to the benchmark specification. Our results have several important implications for policymakers in their efforts to strengthen the ability of the tourism industry to absorb shocks from geopolitical tensions.

On public policies in the energy transition: Evidence on the role of socio-technical regimes for renewable technologies

Our purpose is to contribute to the debate on the energy transition by investigating the role of social, technical, political, and cultural aspects in stimulating the export of renewable technologies (RTs). The literature draws attention to the need to complement public policies with a supportive socio-technical regime, even if evidence is scarce. We maintain that countries' capability in environment-related technologies, public concern and awareness of climate change, and understanding of its damaging effects are relevant drivers, alongside renewable energy policies. Moreover, we expect that such socio-technical drivers, if operating together, amplify the stimulus of policies. We test these arguments through a panel vector autoregressive (PVAR) model in first differences in the EU over the period 1996–2020. Due to heterogeneity across countries, we test the determinants on high-performing countries. Results confirm the role of public awareness and show that the export of RTs is also stimulated by increases in the share of environment-related technologies and understanding of climate change. Countries' capability in green technologies is also supported by increases in public awareness and understanding of the climate issue.

Dynamic and Static Effects of Digital Services Trading on Economic Growth of World Regions

The study examines the effect of digital services trading on the economic growth of panel data from five (5) world regions, namely, Africa, Asia, Latin America, Europe, and the Organization for Economic Cooperation and Development (OECD) between 2005 and 2021. The study employs quantitative experimental methods of Panel vector autoregression (PVAR) models as dynamic estimators and the Fixed Effects (FE) models as static estimators. The PVAR model analyses indicate that the digital services trade has a significant positive long-run effect on Gross Domestic Product (GDP) growth in all five regions. For every 1% increase in digital services trade, GDP in the OECD region increases by 6.75%, followed by Europe at 3.19%, 2.11% in Latin America, 1.02% in Asia, and is lowest in the African region panel at 0.82%. The static FE analyses also shows similar results. These findings confirm the hypothesis that deep internet/digital penetration positively impacts the efficiency of digital services trade. The study, therefore, recommends that policymakers from developing world regions should increase investments in digital deepening infrastructure which should include among others, promoting, policy and regulatory measures that augment digital infrastructure installations in rural places, developing the digital skills to mitigate digital illiteracy, and promoting the adoption of cutting-edge digital technologies.

Economic uncertainty and population health: insights from emerging markets and developing countries

This study employs a Bayesian panel vector autoregressive model to examine the impact of economic uncertainty on public health, using an annual, country-level panel dataset of 103 emerging markets and developing countries spanning the years 1995 through 2019. The results from the full sample suggest that the immediate effects of heightened economic uncertainty on health are marginal, yet it may engender prolonged life expectancy and lowered mortality rates. The analysis unveils considerable heterogeneities among various country classifications. The health-enhancing effects of economic uncertainty are predominantly discernible in emerging markets, low-income and upper-middle-income countries. Additionally, a diminution in suicide rates, attributed to escalated economic uncertainty, is uniquely detected in upper-middle-income countries. Furthermore, economic growth and healthcare expenditure emerge as paramount determinants in bolstering overall population health, particularly in lower-middle-income countries. The detrimental effect of environmental pollution on health is more pronounced in emerging markets and middle-income nations. Excluding high-income countries, it is essential to emphasize the beneficial health outcomes resulting from financial development and globalization, as well as the deleterious effects of environmental pollution. Lastly, several policy implications aligned with the findings are outlined, providing a roadmap for decision-makers in these diverse economies to promote better health outcomes.

A PVAR dynamic correlation appraisal of China’s carbon emissions in conjunction with economic growth and clean energy use

This study aims to explore the dynamic relationship among economic growth, clean energy, and carbon dioxide (CO2) emissions in China. The indicators of economic growth, clean energy, CO2 emissions, fixed assets investment, and research and development intensity of 30 provinces and municipalities for the period of 2005–2019 in China have been investigated by Panel Vector Autoregression model (PVAR). To further explore regional differences, three types of regions were classified by K-means cluster analysis. The results show that clean energy has a positive impact on economic growth in China; Clean energy reduces CO2 emissions in Region II while others do not; Both fixed assets investment and research and development promote clean energy development; The dynamic relationship between the 5 indicators varies across regions. Various regions in China should combine their development characteristics and location advantages, increase capital investment and research and development input in clean energy, strengthen environmental regulations, and improve the energy consumption structure.

Impact of energy and industrial structure on environmental quality and urbanization: evidence from a panel of BRICS countries.

Global sustainable development demands boosting renewable energy and optimizing industrial structures. This study employs a panel vector autoregressive (PVAR) model to examine the dynamic relationship between energy structure, industrial structure, environmental quality, and urbanization in the BRICS countries from 1990 to 2021. Energy structure, industrial structure, environmental quality, and urbanization cointegrate empirically. Energy mix optimization and industrial structure upgrades can improve environmental quality. Energy enhancements also supported urbanization. Accelerating industrial change could adversely impact urbanization. The impulse response results demonstrate that expanding renewable energy and tertiary industries such as financial and service boost environmental quality and urbanization. The variance decomposition investigation reveals significant "path dependence" in reducing carbon emissions and increasing urbanization. Finally, based on the findings, policy insights for enhancing environmental quality and fostering urbanization are laid out and disputed, with long-term implications for environmental managers and urban planners.

The contribution and influence of total external debt, FDI, and HCI on economic growth in Indonesia, Thailand, Vietnam, and Philippines

The goal of this research is to ascertain how much foreign debt, foreign investment, and HCI have contributed to the growth of the economies of the four ASEAN nations. This research uses the Panel Vector AutoRegression Model (PVAR). The PVAR method is a method used to analyze the relationship between several variables that change over time. This method combines two approaches, namely Vector Autoregression (VAR) and panel data. The type of data used in this research is secondary data, an annual time series with a time range from 2000 to 2020 for all cross-section variables taken from four countries in ASEAN, namely Indonesia, Thailand, Vietnam and the Philippines. The World Bank provided the data for this study. The variables examined in this study are GDP, total foreign debt, foreign debt, FDI, and HCI which are represented by education and health variables. From this study, we find that the relationship between variables varies, such as gross domestic product which has a significant negative relationship with FDI but has a significant positive relationship with debt service. In addition, there is a significant and negative relationship between GDP and total foreign debt, GDP is also negatively and significantly related to education and health variables, which means that GDP is also negatively and significantly related to HCI. It can be concluded that in the four countries we studied, an increase in debt service will increase people's consumption capacity which will lead to an increase in economic growth, but in this study total foreign debt and debt service have a negative relationship with gross domestic product. This research shows that foreign direct investment (FDI) has a significant positive relationship with the gross domestic product (GDP) of ASEAN member countries, especially Indonesia, Thailand, Vietnam and the Philippines. Therefore, it is recommended that the governments of ASEAN member countries jointly determine foreign investment policies and manage their foreign debt to increase economic growth in the Southeast Asia region. In addition, it is recommended that the governments of ASEAN member countries pay more attention to their fiscal policies, because increasing debt service costs can reduce economic growth. This can be seen when there is a surge in foreign debt which is disproportionate to the ability to pay ASEAN member countries.