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The dynamic interrelationship between economic growth, the percentage of fossil fuels in the energy matrix, energy use, and CO2 emissions was examined. A panel vector autoregression (PVAR) was calculated for 75 countries and different income groups between 1974 and 2013. Our main results reveal that the shock reduces the percentage of fossil fuels in the energy matrix, in CO2 emissions per capita and in energy use per capita while not statistically affecting GDP per capita. In addition, the causality between economic growth and energy use is bidirectional in high-income and upper-middle-income countries. In contrast, energy causes economic growth in lower-middle-income and low-income countries. Finally, we found no evidence to support the Kuznets environmental curve (EKC).

Du, J.; Yan, B., and Su, X., 2025. Empirical analysis of financial agglomeration, industrial infrastructure, and economic growth of the marine industry: Using the PVAR model to analyze China's marine economy. Journal of Coastal Research, 41(1), 122–130. Charlotte (North Carolina), ISSN 0749-0208. To promote the high-quality development of China's marine economy, based on the panel data of 11 coastal provinces and cities from 2006 to 2016, the panel vector autoregression (PVAR) model was used to analyze the dynamic relationships among financial agglomeration, upgrades in marine industrial structure, and economic development. Based on the cointegration test, a long-term stable relationship was found between the three variables of financial agglomeration, marine industry structure upgrades, and the development of the marine economy, where financial agglomeration inhibits the growth of the marine economy, and a suitable interaction mechanism cannot be formed between the two, whereas upgrading of the marine industry structure is conducive to the development of the marine economy. In the short term, financial agglomeration can promote the upgrading of the marine industry structure, but the long-term effect is not ideal; in the long run, the development of the marine economy can encourage improvement in the level of financial agglomeration. In the short term, the development of the marine economy is mainly affected by itself and the upgraded marine industry structure, but in the long run, the inhibitory effect of financial agglomeration to the marine economy is greater.

How to improve the predictive accuracy of box office revenue with social media data is a big challenge and is particularly important for movie distributors and cinema operators. In this research, we find that microblogging UGC (MUGC) is a significant predictor of box office revenue and has stronger predictive power than UGC on Douban! Movies (DUGC) based on our examination of 60 movies released in China in 2012. To increase the attendance rate of movies, cinema operators can consider previous valence and volume of MUGC before scheduling the current film screenings because these messages can quickly predict the future box office revenue of a movie. Besides, we find that the volume of enterprise microblogs (i.e., MGC) can predict both box office revenue and MUGC, indicating that movie distributors should optimize their online media strategy by shifting more resources to utilizing enterprise microblogging. Although rebroadcasting volume from microblogging platforms does not predict box office revenue directly, it can indirectly predict it via MGC. Accordingly, compared with third-party platforms, rebroadcasting as one of the key distinct functions of microblogging platforms also shows its usefulness in box office revenue prediction. Overall, metrics from microblogging platforms are more effective in predicting box office revenue than those from third-party platforms. In this research, we build a prediction model of movie box office revenue by empirically exploring its intricate relationships with user-generated content (UGC) as well as marketer-generated content (MGC) on a microblogging platform and UGC on a third-party platform. Our analyses are based on a panel vector autoregression (PVAR) model that is calibrated with a combination of data from Weibo (microblogging platform) and Douban! Movies (third party). Our empirical results show that microblogging UGC (MUGC) is a significant predictor of box office revenue and has stronger predictive power than UGC on Douban! Movies (DUGC). In addition, we find that the volume of enterprise microblogs (i.e., MGC) predicts box office revenue directly and also indirectly via MUGC, and MUGC thus exerts a partial mediating effect on the predictive relationship between the volume of enterprise microblogs and box office revenue. Finally, a prediction model of box office revenue using lagged box office revenue, MGC, MUGC, and DUGC is proposed, and its forecasting accuracy is found to outperform that of existing models. Managerial implications on utilizing social media for enterprises are provided. The e-companion is available at https://doi.org/10.1287/isre.2018.0797 .

This paper investigates the presence of a causal relationship between energy poverty and income poverty in the EU Member States through a Panel Vector Autoregressive specification, and controlled with a set of explanatory variables collected from the Eurostat energy database and the OECD environment database for 2007–2018. Deepening the nexus between energy poverty and income poverty is a relevant issue for tailoring policies to tackle poverty and improve the well-being of citizens, supporting the policy makers in the allocation of planned funds provided by the Recovery plan, “Next Generation EU”. The results of the panel VAR model estimation and Dumitrescu and Hurlin test suggest that there will be no change in the long-run equilibrium when income poverty remains constant. Moreover, the reduction in energy poverty is expected to have a positive effect in terms of overall economic poverty reduction. Finally, there is evidence that substituting fossil fuels with renewables helps to reduce energy poverty and widespread poverty due to the leverage effect on economic development as well as to support the achievement of some of the 17 Sustainable Development Goals addressed by United Nations.

Green technological innovation is one of the endogenous drivers of green economic growth, and digitalization can promote green economic development in the form of industrial empowerment. The interactive relationship and the degree of influence between digitalization, technological innovation, and green economic development is thus an urgent issue to be addressed. Based on the panel data of 30 Chinese provinces from 2011 to 2019, we measured digitalization, technological innovation, and green economic development for the first time using the entropy method and included them in the same analytical framework by constructing a PVAR model to empirically test their interrelationship and degree of influence. Our findings suggest that: (1) There is an inertial development and self-reinforcing mechanism among the three variables. (2) The impact of digitalization on green economic development has a positive promotion effect, while the impact of technological innovation on green economic development is not significant. (3) The impact of green economic development on technological innovation has a positive promotion effect in the short term, but this effect gradually declines and tends to zero in the long term. Finally, based on the findings, several practical suggestions are made.

Our research critically investigates the impact of social media astroturfing on movie sales, the circumstances under which it appears to have an effect, and the negative implications associated with this practice. Leveraging a distinct dataset from the Chinese movie industry, we utilized panel vector autoregression to dissect the dynamics between social media astroturfing, box office revenues, and the performance of media across digital and traditional platforms. We further applied a dynamic matching approach to address the identification issue. Our findings suggest that while social media astroturfing might temporarily boost box office revenues, its effectiveness is limited to the short term, and it harbors negative consequences for consumers. By systematically examining the effects of social media astroturfing, our study enriches both academic literature and practical understanding, cautioning against the reliance on such deceptive marketing tactics.

The aim of this paper is to investigate the nexus between natural resources, gross capital formation, globalization, and economic growth in the developing countries from European, Asian, African, and American continents. It adopted the panel vector autoregression (PVAR) approach to test this relationship for the period from 1980 to 2018. Results suggest that natural resources and globalization have a positive impact on economic growth in European, Asian, and American countries, while capital formation negatively affects growth. In African countries, the effect of globalization and gross capital formation is positive, but natural resources have a negative impact on GDP. Evidence from all continents illustrate that there is bidirectional causality between globalization and economic growth. Also, there is bidirectional causality detected between capital formation and growth in Europe and Asia and between natural resources and growth in Asia and America, while there is unidirectional causality from GDP to natural resources in Europe, from capital formation to GDP in Africa and America, from GDP to natural resources in Europe, and from natural resources to GDP in America. Based on these results, it can be said that new growth models can no longer be independent of natural resource rents and globalization.

South Asia faces the dual challenge of sustaining rapid economic growth while managing severe ecological pressures. This study explores the relationship between Ecological Footprint (EF), Financial Development (FD), Economic Growth (GDP), Foreign Direct Investment (FDI), and Political Stability (PS) in SAARC countries from 2000 to 2020. Using a Panel Vector Autoregression (PVAR) combined with a Vector Error Correction Model (VECM), the analysis captures both short-run dynamics and long-run equilibrium relationships, addressing endogeneity among variables. Results reveal that EF negatively correlates with FD, GDP, and FDI, while showing a positive association with PS. Cointegration tests using dynamic and fully modified ordinary least squares confirm long-term relationships between the variables. Impulse response functions illustrate how shocks to one variable affect others over time, highlighting complex interactions. Granger causality tests suggest limited short-term causal links, reflecting the multifaceted nature of these relationships. This research is particularly relevant as SAARC countries face the dual challenge of sustaining rapid economic growth while mitigating ecological pressures. The study advances the literature by explicitly integrating political stability into the environmental–economic nexus, a factor often overlooked in earlier regional analyses. By providing empirical evidence on the joint role of economic, financial, and political drivers of ecological sustainability, the paper contributes both to academic debate and to the design of more balanced policy frameworks for sustainable development in South Asia.

One of the key indicators of a population’s well-being and the economic development of a country is represented by health, the main proxy for which is life expectancy at birth. Some factors, such as industrialization and modernization, have allowed this to improve considerably. On the other hand, along with high global population growth, the factor which may jeopardize human health the most is environmental degradation, which can be tackled through the transition to renewable energy. The main purpose of our study is to investigate the relationship between renewable energy consumption, social factors, and health, using a Panel Vector Auto Regression (PVAR) technique. We explore the link between some proxy variables for renewable energy consumption, government policy, general public awareness, the market, lobbying activity, the energy dependence on third countries, and health, spanning the period from 1990 to 2015, for a cluster of 12 European countries characterized by common features. Specifically, our analysis shows the importance of having a stringent policy for the development of renewable energy consumption and its influence over other social factors, rather than the existence of causal relationships between health and renewable energy consumption for the analyzed countries. This kind of analysis has a great potential for policy-makers. Further, a deeper understanding of these relationships can create a more effective decision-making process.