Panel Vector Autoregressive Model Research Articles

Evolution of innovation systems, economic growth, and sustainable competitiveness in Africa

This paper examines the systemic relationship between triple helix innovation systems and the gross domestic product per capita growth (GDPPC) in terms of sustainable competitiveness in Africa. To do this, the Generalized Moment Method on the panel vector autoregressive model is used to estimate helix models’ (triple helix, quadruple helix, quintuple helix, as well as the open quintuple helix, relative to external contributions) effects on GDPPC between 2007 and 2019 in 27 African countries, and causality tests completion as well. The results show 3 coevolution relationships resulting from the narrow innovation system, which is made up of the burden of government regulations, companies’ expenditures on research and development (R&D) as well as the quality of scientific research institutions. The system expansion (the broad innovation system) with the degree of consumer orientation and natural resource rents generate both 7 (respectively 3 and 4) coevolution relationships. Finally, the opening of the innovation system by considering the business impact of rules on foreign direct investment (BIFDI) alone, generates 5 coevolution relationships. So, in terms of overall sustainable competitiveness strategies in Africa, countries must focus on innovation system opening and natural resources exploitation to increase their GDPPC. Thus, this study fills the gap of a deficit in technological policy orientation on the relationships between innovation systems and sustainable competitiveness through economic growth in Africa.

Examining the causal relationship between bike-share and public transit in response to the COVID-19 pandemic

As urban transportation systems often face disruptive events, including natural and man-made disasters, the importance of resilience in the transportation sector has recently been on the rise. In particular, the worldwide spread of the COVID-19 pandemic resulted in a significant decrease in citizens’ public transit use to avoid unnecessary physical contact with others. Accordingly, bike-share has been highlighted as one of the sustainable modes that can replace public transit and, thus, improve the overall resilience of the urban transportation systems in response to COVID-19. This study aims to examine the changes in causal relationships between bike-share and public transit throughout the COVID-19 pandemic in Seoul, Korea. We analyzed bike-share and public transit ridership from Jan 2018 to Dec 2020. We developed a weekly panel vector autoregressive (PVAR) model to identify the bike-transit relationships before and after the pandemic. Our results showed that COVID-19 weakens the competitive relationships between bike-share and bus transit and modal integration between bike-share and subway transit. This study also found that bus and subway transit were more competitive with each other after the outbreak of COVID-19. The study’s findings suggest that bike-share can increase the overall resilience of the urban transportation system during the pandemic situation, particularly for those who rely on public transit for their mobility.

Environmental regulation, R&D investment, and green technology innovation in China: Based on the PVAR model.

The unreasonable economic development model of human beings has caused the environmental pollution problem to become increasingly serious. In order to achieve a positive relationship and interaction between environmental regulation, research and development (R&D) investment, and green technology innovation, and effectively solve the “strange circle” problem between high-quality economic development and environmental pollution in China and even the world, this paper takes the panel data of industrial enterprises above designated size in Chinese mainland 31 provinces from 2009 to 2019 as a research sample. The comprehensive index of R&D investment and green technology innovation was established by the entropy method, and the panel vector autoregressive (PVAR) model was constructed from the dynamic endogenous perspective, and the dynamic interaction and regional heterogeneity between environmental regulation, R&D investment, and green technology innovation were empirically analyzed by using impulse response function and variance decomposition. We obtain the following findings: (1) Environmental regulation has a two-way interaction relationship with R&D investment and green technology innovation, and R&D investment has a promotion effect on the “green degree” of technological innovation, but its role is still weak and has lagging characteristics. (2) There is significant regional heterogeneity in the dynamic responses of the eastern, central and western parts of China. (3) In the long run, environmental regulation has a “negative crowding out effect” on R&D investment in the central region, and the phenomenon of “central collapse” still exists but will gradually weaken. Environmental regulation has a “positive innovation compensation effect” on green technology innovation. Green technology innovation and R&D investment have an obvious “Pareto improvement” effect on environmental regulation, especially in the eastern region. The conclusions of this study help to clarify the dynamic interaction between environmental regulation, R&D investment, and green technology innovation, further improve environmental regulatory policies and green technology innovation R&D decision-making, and provide an effective way to achieve green and sustainable development in China and other parts of the world.

Empirical Studies on the Dynamic Relationship between Port Logistics and Marine Economic Development in Fujian Province

The marine economy in coastal areas has a great role in promoting social development, and efficient port logistics serves the high-quality development of the marine economy. There is a dynamic relationship of dependence, restriction, and mutual promotion between port logistics and marine economy, which has regional differences. Based on panel vector autoregressive model (PVAR model), the relevant panel data of Fujian Province from 2000 to 2020 were analyzed by using the Granger causality test, impulse response, and variance decomposition methods. The interactive relationship between port logistics and marine economic development was discussed, and development suggestions were put forward. The results show that the development level of port logistics in Fujian Province is low, the logistics supply cannot meet the needs of marine economy, the effect of port logistics is not significant, and the support ability for the development of marine economy is insufficient. On the contrary, the development of marine economy promotes the development of port logistics industry and the economic growth of logistics related industries, and the strong market demand promotes the further improvement of logistics supply capacity. On the whole, the two-way feedback effect between the indicators of logistics industry and the development of marine economy is weak. In the future, it is necessary to further increase the layout of port logistics network system, strengthen the support ability of port logistics to the development of marine economy, and promote the scale and quality of port logistics by relying on marine economy.

IMPLEMENTASI MODEL PANEL VAR PADA HUBUNGAN INFLASI DAN PERTUMBUHAN JUMLAH UANG BEREDAR

This study aims to determine the causality relationship between the growth of the money supply (JUB) and inflation. The data used is panel data from 6 ASEAN countries in the 2009-2020 period. The analysis used is the Panel Vector Auto Regression (PVAR) model. The results showed a two-way causality relationship between the inflation rate and the growth of the money supply. The increase in inflation will reduce the growth of the money supply. Conversely an increase in the money supply will increase inflation. The government should keep these two macro variables balanced through existing fiscal and monetary instruments, for example with interest rate policy and price control, especially related to the price of staples and fuel

Renewable Energy (Solar and Wind) Generation and its Effect on some Variables for Selected EU Countries with Panel VAR Model

Keeping the world livable, the policy makers are giving their extended focus on green energy. They are trying to move on hand-on-hand with rising green energy and lessening carbon dioxide (CO2) emission steading the economic activities specially for the open and developing countries. This can be helpful to provide a more lucrative economic environment to meet the extended demand of the society. The paper highlights to find out whether the economic growth, renewable energy consumption, fossil fuel-based energy generation and CO2 emission are significantly impactful on renewable energy generation or not? Is there any mutual, bi-directorial, unidirectional relationship with each other? For this, the Vector Autoregression (VAR) model is run. The paper focuses on six EU countries who are practicing auction scheme for deploying robust green energy (especially solar and wind) by reducing dependency on fossil fuel and expanding their economy with less CO2 emission. The result of the analysis shows that a positive influence of each concern variable on renewable energy (RE) generation and auction scheme might have a significant impact if robustness of the generation occurs.

Study on the coupling and coordination degree between urban tourism development and habitat environment in the Yangtze River Delta in China.

By constructing the two evaluation systems of urban tourism development (TD) and habitat environment (HE), the dynamic response relationship between the two systems in the Yangtze River Delta urban agglomeration from 2001 to 2020 is explored by using panel vector autoregression (PVAR) model and coupled coordination degree model. The study unearthed four intriguing findings: (1) the level of TD in the study area has been continuously rising from 2001 to 2020, with an initial slow growth rate and then fast. The level of HE is increasing steadily at an average annual rate of 7.05%. There exists a reciprocal response relationship between the two systems, with a strong shock effect in the short term and a synergistic evolution in the long term. (2) The coupling degree between the urban TD and HE has an increasing trend, and the coupling coordination degree of the two systems has an average annual rate of 4.165%, implying the interaction and promotion effect between the two systems is improving. (3) Most of the cities in the Yangtze River Delta gradually realize the evolution from dysfunctional type to coordinated type, but the overall coordination intensity is low. (4) The barrier degrees of TD system indicators show a small annual increasing trend, while the barrier degrees of HE system indicators show a substantial and continuous decreasing trend. In terms of the barrier degree factors, some important factors that restrict the coupled and coordinated development of the two systems are also reported. This research can provide a useful reference for the synergistic improvement of urban tourism economy and habitat environment.

Examining the Relationship between Tourism and Gender Equality: Evidence from Asia

This study analyzes the relationship between tourism and gender equality using panel vector autoregression and vector error correction models estimated by the generalized method of moment. This methodology is based on panel data from 36 Asian countries between 2006 and 2019. The other three variables including the economy, employment, and education are also analyzed. The results show that there is a long-run equilibrium relationship between tourism and gender equality. In the short run, tourism is not the Granger cause for gender equality; however, tourism significantly contributes to gender equality in all regions in the long run. Furthermore, a heterogeneous causality between tourism and gender equality is found across the regions. Tourism’s positive effect on gender equality does not depend entirely on economic empowerment. All the economy, education and employment mostly contribute to realizing gender equality, but this contribution is not decisive. The findings and policy implications are finally discussed.

Coupling Coordination and Interactive Response Analysis of Ecological Environment and Urban Resilience in the Yangtze River Economic Belt.

There is a complex dynamic coupling interaction process between the ecological environment and urban resilience. It is important to clarify the coordination relationship and interactive response mechanism between them for sustainable development construction of the Yangtze River Economic Belt. The coupling coordination degree model and the panel vector autoregressive model (PVAR) were adopted to quantitatively examine the dynamic coordination and interactive response of the ecological environment and urban resilience in the Yangtze River Economic Belt from 2000 to 2019. Our study’s results are the following: (1) The ecological environment index and urban resilience index have a generally positive trend of fluctuation and increase during the study period but show significant regional differentiation. (2) The coupling coordination degree of ecological environment and urban resilience in the Yangtze River Economic Belt increased steadily, forming a spatial distribution pattern of “strong in the east and weak in the west”, with cities in the region mainly at the basic coordination level and generally lagging behind in development. (3) Both the ecological environment and urban resilience systems in the Yangtze River Economic Belt have significant self-reinforcing mechanisms, but the reinforcing effect is gradually decreasing, and the two positively promote each other, with urban resilience showing a more obvious promoting effect on the ecological environment.

On New Two-Step GMM Estimation of the Panel Vector Autoregressive Models with Missing observations

Few estimation methods were discussed to handle the missing data problem in the panel data models. However, in the panel vector autoregressive (PVAR) model, there is no estimator to handle this problem. The traditional treatment in the case of incomplete data is to use the generalized method of moment (GMM) estimation based on only available data without imputation of the missing data. Therefore, this paper introduces a new GMM estimation for the PVAR model in case of incomplete data based on the mean imputation. Moreover, we make a Monte Carlo simulation study to study the efficiency of the proposed estimator. We compare between two GMM estimators based on the mean squared error (MSE) and relative bias (RB) criteria. The first is the GMM estimation based on the list-wise (LW) and the second is the GMM estimation using the mean imputation (MI) at multi-missing levels. The results showed that the MI estimator provides more efficiency than the LW estimator.

Spatio-temporal impulse effect of foreign direct investment on intra- and inter-regional carbon emissions

The introduction of foreign capital has promoted China's economy but causing environmental pollution problems. A novel PVAR model integrating spatio-temporal analysis impulse could eliminate the endogenous problem and reveal the evolution of FDI shocks on carbon emissions. Traditional models often ignore endogeneity problems, which leads to insignificant results. The existing research has mostly focused on the impact of foreign direct investment (FDI) on CO2 emissions at intra-region level. This study filled the research gaps by studying the spillover effect of FDI on carbon emissions at inter-regional level. The study aims to characterise the impact of FDI on carbon emissions at intra- and inter-regional levels where the endogenous problem is eliminated. Based on the panel data of the 229 cities in China from 2003 to 2015, this paper establishes a novel panel vector autoregression (PVAR) model which integrated the spatio-temporal impulse analysis to reveal the evolution of FDI shocks on intra- and inter-regional carbon emissions. The results corroborate that the evolution of FDI shocks increased intra-regional carbon emissions as shown by the inverted U-curve; while the evolution of FDI shocks decreased inter-regional carbon emissions as shown by the U-curve. Interaction mechanism between FDI and China's low-carbon economy should be strengthened.

The sooner, the better? Interactions of stakeholders in online food delivery service platforms

PurposeThis research aims to explore the interactions of stakeholders in online food delivery (OFD) platforms, including restaurants, the delivery system and the platform, and the effect on total sales. In order to comprehensively analyze the service of stakeholders, the authors adopted the time duration which provides a unified metric for assessing service performance.Design/methodology/approachThe authors used panel vector autoregressive (PVAR) model analysis to verify the interactions among restaurants, the delivery system, and the platform itself, and to assess their effects on the sales. Data were collected from one of the biggest OFD service platforms in China – Eleme.com.FindingsFirst, the findings confirmed that the service performance of restaurants, the delivery system and the platform itself influence one another. There is a bidirectional causality between food preparation time (FPT) and actual delivery time (ACDT), as well as between FPT and advance arrival time (ADAT), ACDT and ADAT. Second, the service performance of restaurants, the delivery system, and the platform itself all positively affect sales, thus demonstrating unidirectional causality.Originality/valueThe current research is a pioneering empirical study, as it confirms the dynamic interactions between participants in OFD platforms and the dynamic influence of their respective service performances on sales. The findings of this research have a number of implications for the management and operation of online food ordering and delivery platforms.

Do remittances matter for health outcomes in developing countries? Fresh evidence from a panel vector autoregressive (PVAR) model

PurposeThis study aims to contribute to the growing literature on the effects of remittances and the determinants of health outcomes by analysing for the first time the effect of remittances on health outcomes in developing countries using a panel vector autoregression (PVAR) model.Design/methodology/approachThis study uses panel data from 107 developing countries over the period from 1990 to 2018 to examine the effect of remittances on health outcome in developing countries.FindingsThe main findings from study is that remittances improve health outcomes in developing countries. Another finding of this study is that income, trade, foreign direct investment and financial devlopment improve health outcome.Originality/valueThe contribution of this study is fourfold. Firstly, it adopts the PVAR methodology in a Generalized Method of Moments framework proposed by Abrigo and Love (2016). Secondly, it analyses the implications of remittances on health outcomes by relying on two comprehensive measures of health outcomes commonly used in the literature which are life expectancy at birth and the rate of under-five mortality rates. Thirdly, we identify governance and maternal education as the channels through which remittances improve health outcomes in developing countries. Finally, the current paper covers an extensive time span (29 years) and focuses on a large sample (107 countries).

The dynamic relationships among growth in the logistics industry, energy consumption, and carbon emission: recent evidence from China

In the post-pandemic era, there is a need to achieve the dynamic and coordinated development of growth in the logistics industry, energy consumption, and carbon dioxide (CO2) emissions in China’s four major economic regions to ensure the high-quality development of green logistics in China. Using the data indicators of growth in the logistics industry, energy consumption, CO2 emissions, and fixed asset investment in 30 Chinese provinces from 2004 to 2018, a panel vector autoregressive model was established for the four major economic development regions of central, east, west, and northeast China. The model coefficients were estimated using the systematic generalized matrix estimation method (System-GMM), which was evaluated by a Granger causality test. The model coefficients were estimated using the System-GMM method, and the dynamic relationships between growth in the logistics industry, energy consumption, and CO2 emissions was obtained through a Granger causality test, impulse response analysis, and variance decomposition. The results showed that the growth of the logistics industry in the four major economic regions had a positive impact on energy consumption and CO2 emissions, with the degree of contribution being smaller in the east and central regions, and larger in the west and northeast regions. Fixed asset investment had a negative impact on energy consumption and CO2 emissions, with the degree of contribution being largest in the northeast, larger in the east than in the central region, and smallest in the west. Finally, according to the conclusion and analysis of the results, from the aspects of government guidance and policy support, low-carbon logistics technology innovation, and infrastructure investment, we propose the need to pay attention to the role of government guidance, accelerate the pace of energy adjustments using the structure of the logistics industry, and increase the investment in renewable energy infrastructure, while focusing on strengthening the cooperation between regions and exploring new models of low-carbon logistics development between regions. This will ensure that the country achieves its goal of reaching peak carbon by 2030 and carbon neutrality by 2060.

Dynamic effects of financial development on economic activity

ABSTRACT In this article, we provide evidence of the dynamic effects of financial development on a group of key macroeconomic variables, namely, output, consumption, investment, inflation, money, the interest rate and the exchange rate. As the measure of financial development we use a new broad measure of financial development instead of the narrow measures usually employed in the related literature. Another novelty is that we estimate the dynamic effects of financial development on economic activity in the context of a panel vector autoregressive model, comprising 36 countries observed in the period 1983–2019. Our results suggest that financial development has a positive impact on output, investment, and consumption. The results reported in this article also support the proposition that the benefits from financial development are larger in economies where the financial system is market-based. These results survive a battery of robustness checks.

The State-Level Nonlinear Effects of Government Spending Shocks in the US: The Role of Partisan Conflict

Utilising a nonlinear (regime-switching) mixed-frequency panel vector autoregression model, we study the effects of government spending shocks in the United States (US) over the business cycle, while considering the role of partisan conflict. In particular, we investigate whether partisan conflict is relevant to the differences in fiscal spending multipliers in expansionary and recessionary business cycle phases upon the impact of annual government spending shocks, using quarterly state-level data covering 1950:Q1 to 2016:Q4. We find new evidence that fiscal multipliers can vary with economic and political conditions. The cumulated effects of government spending shocks are strong and persistent in recessions when the level of partisan conflict is low.

Dynamic Relationship between Agricultural Technology Progress, Agricultural Insurance and Farmers’ Income

The implementation of the agricultural insurance policy and advancement of agricultural technology has great significance for the development of the agricultural economy of China, and it is an important source of national stability and modernization and development of the agriculture sector. Agricultural insurance policy uses the expansion of agricultural technology progress in the process of evaluation, investigation and claims settlement, and so on. Agricultural technology progress is effective in the reduction of some agricultural risks, it also affects farmers’ agricultural insurance behaviors, and optimizes the operating environment of agricultural insurance. The objective of this research is to explore the relationship between agricultural technology progress, agricultural insurance and farmers’ income. It also explains the mutual/cooperative relationship between agricultural technology progress and agricultural insurance. It provides the theoretical basis and data support to verify the promotion effect of agricultural insurance and agricultural technology progress on farmers’ income. This gives the improvement path for alleviating the spatial imbalance of China’s agricultural development. Keeping in view the aforementioned background and this research explores the effects of agricultural technological progress and agricultural insurance on the farmers’ income level. The panel data used for this research were from 2004 to 2019 and were grouped into two parts: high-density agricultural insurance areas and low-density agricultural insurance areas. The relationship between agricultural technology progress, agricultural insurance and farmers’ income was estimated using the Panel Vector Autoregressive (PVAR) model. The results revealed that: (i) both agricultural technology progress and agricultural insurance have a positive effect on the farmers’ income level, but this effect varies across regions; (ii) impact of the agricultural insurance on farmers’ income is greater than the impact of agricultural technology progress on farmers’ income; and (iii) the role of agricultural insurance in promoting agricultural technology progress exists only in areas with high-density agricultural insurance. Therefore, when formulating policies, the policymakers should consider regional differences and characteristics, and adopt development models keeping in view regional variations in adaptability with different agricultural insurance densities, Moreover, they should improve agricultural security policies, optimize agricultural capital allocation, promote the transformation of the agricultural economy from extensional growth to connotative growth, and further improve the agricultural productive income of rural residents.

Economic Growth and Environmental Quality: Analysis of Government Expenditure and the Causal Effect.

Environmental expenditures (EX) are made by the government and industries which are either long-term or short-term investments. The principal target of EX is to eliminate environmental hazards, promote sustainable natural resources, and improve environmental quality (EQ). Thus, this study looks at the impact of economic growth (EG), and government finance expenditure (GEX) on EQ in Northern Africa and Southern Africa (NASA) republics from 2000–2016. The panel quantile regression (PQR) and panel vector autoregressive (PVAR) model in a generalized method of moment framework (GMM) were employed as a framework. The PQR results show that; (i) In Northern republics, GEX had a significant positive effect on EQ at 25%, 50%, and 75% quantiles levels. (ii) In the Southern republics, GEX had a significant negative impact on EQ at 25%. Moreover, the PVAR through the GMM established that EG and GEX are significantly positive while the parameter for CO2 is insignificant and negative in the North. However, in the South, GEX and CO2 were statistically significant, while EG positively impacts EQ. Lastly, the granger causality report in North indicates uni-directional causation running from LNGEX → LNGDPpc, LNCO2 → LNGDPpc, LNFF → LNGEX, and LNFDI → LNGEX. Similarly, there is uni-directional causation in South republics from LNGEX → LNGDPpc, LNCO2 → LNGEX, and LNFDI → LNGEX.

Transmission Machine of International Financial Crisis Based on VAR Model

The financial crisis has always been accompanied by human economic activities, and its outbreak has a serious impact on people's normal life, and it has no warning, which is a problem of great concern to all countries in the current economic development. Based on the monthly data of long-term bond yields of eight countries (six European countries, the United States and Japan) from December 2009 to February 2012, through correlation test and Granger causality analysis, the results show that there is no Granger causality between the bond yields of various countries and the bond yields of Greece before the European debt crisis, but Granger causality exists between the bond yields of Germany, France and Italy and Greece after the crisis. Finally, it puts forward the process of China's complete opening of capital account and the problems that should be paid attention to after that. The latest development direction of vector autoregressive model is the identification of exogenous policy shocks and the estimation of panel vector autoregressive model. This paper studies and analyzes the transmission mechanism of international financial crisis. Vector autoregressive model is used to describe the transmission mechanism of international financial crisis. The enhancement of the ability to resist the contagion of financial crisis is an important factor to promote the sound development of China's economy. Starting with the related concepts of the transmission mechanism of international financial crisis, this paper probes into the specific transmission modes of international financial crisis and the suppression measures of the transmission mechanism of international financial crisis.

A dynamic view of environmental regulation influence mechanism on manufacturing agglomeration-a case study of the Yangtze River Delta city cluster.

Rapid development and agglomeration of manufacturing industries in China inevitably lead to serious environmental pollution problems. The government restrains development of manufacturing industries through environmental regulation policies, but this may affect manufacturing industries agglomeration. Therefore, studying the impact of environmental regulation (ER) on manufacturing agglomeration (MA) is a critical prerequisite for the sustainability of China's manufacturing industry. Based on the panel data of 41 cities in Yangtze River Delta (YRD) region of China from 2003 to 2017, this paper explores the threshold effect of ER on MA using a panel threshold model and analyzes the heterogeneity impact of ER on MA in different regions and analyzes the dynamic mechanism and contribution of each influencing factor on MA using a panel vector autoregressive model. The results show that (1) there is a double threshold effect of ER on MA, showing an inverted "U"-shaped effect of rising and then falling; there are threshold effects of ER on MA based on foreign direct investment (FDI) and economic development level (EDL). The effect of ER on MA has the threshold effect under different FDI and EDL level, in which the effect based on FDI shows an inverted "U" shape relationship of rising and then falling; the effect based on EDL shows a growing trend. (2) There are 29 cities in YRD region in the "weak regulation" or "strong regulation" stage, both of which are not conducive to MA. (3) ER has a facilitating effect on MA, but with the extension of forecast period, this facilitating effect turns into an inhibiting effect. MA is mainly influenced by itself and transportation conditions (TC). Our study can provide some insights for improving the ecological environment and promoting the development of manufacturing clusters in YRD region.