A dynamic social relations model for clustered longitudinal dyadic data with continuous or ordinal responses.

Social relations models allow the identification of cluster, actor, partner, and relationship effects when analysing clustered dyadic data on interactions between individuals or other units of analysis. We propose an extension of this model which handles longitudinal data and incorporates dynamic structure, where the response may be continuous, binary, or ordinal. This allows the disentangling of the relationship effects from temporal fluctuation and measurement error and the investigation of whether individuals respond to their partner's behaviour at the previous observation. We motivate and illustrate the model with an application to Canadian data on pairs of individuals within families observed working together on a conflict discussion task.

Causal relationship between household consumption transition and CO2 emission in China: a dynamic panel model.

The mitigation of carbon dioxide (CO2) generated from household consumption, accounting for 52% of China's total greenhouse gas emissions, plays a pivotal role in China's pursuit of reaching a carbon peak by 2030. The study used three waves of nationally representative longitudinal data, energy statistics data, and input-output table to estimate household CO2 emissions (HCEs) in China at the micro-scale. The dynamic relationship between household consumption pattern transition and HCEs per capita was explored by applying maximum likelihood and structural equation modeling (ML-SEM) with panel data. The results indicate that per capita HCE level in a given year appears to be positively associated with HCE level for the same household in the previous year. A U-shaped relationship between consumption pattern transition and HCEs per capita was confirmed, as well as the reinforcement effect of income on the impacts of consumption pattern transition. The increase in consumption propensity, household income, share of wage-income, household asset values, and house space results in higher HCEs per capita. The family size and dependency ratio have a negative relationship with HCEs, whereas households that are female-oriented and more Internet-dependent tend to produce more CO2. Exploring the consumption transition of households is crucial for reducing CO2 emissions at the household level in China.

Exploring the effect of city size on carbon emissions: Evidence from 259 prefecture-level cities in China.

As a gathering place for human production activities, cities are the main places where energy consumption and carbon dioxide emissions occur. How to accurately measure city size and test the impact mechanism of city size on carbon emissions of different city levels is still controversial. This study uses the global nighttime light data to identify urban bright areas and built-up areas, and accordingly constructs the city size index of 259 prefecture level cities in China from 2003 to 2019. It avoids the problem of only considering the single index of population size or space size, and makes the measurement of city size more reasonable. We use a dynamic panel model to study the impact of city size on urban carbon emissions per capita, and discuss the heterogeneity of various cities under different population levels and economic development levels. The empirical results indicate that in the scale of cities in China showed a fluctuating growth trend in recent years. The city size index of most cities is clustered at medium and high values. The city size index of cities with different economic development levels and different population-scale levels shows obvious gradient differences but maintains an upward trend. The expansion of supercities (with a population of more than 5 million) introduces a drastic increase in carbon emissions. The carbon emissions growth caused by the expansion of cities that are classified as third tier and below is the smallest, while that caused by the expansion of cities that are classified as first-tier is the largest. The findings suggest differentiated emissions reduction suggestions for cities with different sizes.

The Reciprocal Relationship of Self-Rated Health and Instrumental Help From Adult Children: Evidence From Germany.

OBJECTIVES: Receiving support from adult children may promote or be harmful for older adults' health. Poor health, however, often precedes the need for intergenerational support. To date, few studies have addressed the relationship between instrumental help (i.e., help with household chores) and older adults' self-rated health (SRH) simultaneously, thereby accounting for potential reverse causality. Moreover, little research has accounted for omitted variable bias. METHODS: Dynamic panel models with fixed effects provide an opportunity to address these methodological issues. Drawing on four waves of the German Ageing Survey, which provide a sample of 3,914 parents aged 40-95 years, I investigate the bidirectional linkages between instrumental help from adult children and SRH. RESULTS: Results suggest that prior receipt of instrumental help is not a significant predictor of future reported SRH. Similarly, previous SRH does not significantly predict the likelihood of receiving instrumental help at follow-up. Instead, earlier values of SRH and instrumental help are most important for predicting future SRH and instrumental help. DISCUSSION: The results shed new light on the interplay between SRH and instrumental help from adult children. The study suggests that older adults' health and support in later life are not interdependent. I discuss these findings in relation to future policies for healthy aging to focus on interventions that facilitate optimal health in the earlier stages of the life course and for adult children to provide continued support to their parents.

The Impact of Financial Development on Renewable Energy Consumption: A Multidimensional Analysis Based on Global Panel Data.

In this paper, we examined the impact of financial development on renewable energy consumption from a global perspective based on a dynamic panel model and panel data of 103 economies. We conducted the research from the different levels of financial development using an index system including nine variables, and also explored national heterogeneity by dividing samples into developed economies and developing economies. The empirical results indicated that the financial development had a positive impact on renewable energy consumption from the macro perspective, and this effect was mainly driven by the development of a financial institution (mainly including bank). Further analysis on the depth, access, and efficiency of a financial institution and financial market (mainly including stock market and bond market) revealed that all three aspects of a financial institution had a positive influence on renewable energy consumption, while this effect only existed in the aspect of efficiency for a financial market. The investigation of national heterogeneity showed that the financial development performed well in promoting renewable energy consumption in developed economies, while this positive effect only existed for financial institutions in developing economies. We suggest to policymakers to attach importance to the positive effect of financial development when formulating renewable-energy-related policies, and provide a system guarantee for renewable energy enterprises concerning financial sectors in developing economies.

China's industrial green development and its influencing factors under the background of carbon neutrality.

To measure and analyze the evolution characteristics and influencing factors of China's industrial green development level is of great significance in achieving carbon neutrality goal. Based on the panel data from 2000 to 2018 of 30 provinces in China, this research uses the super slack-based measuring model and the Malmquist-Luenberger index to calculates China's industrial green total factor productivity and to describe its evolution characteristics using the kernel density function and moreover uses the Spatial Durbin model and the partial differential method to explores its main influencing factors. This study finds that China's overall industrial green development level is not high but shows an upward trend year by year; carbon emissions, fiscal decentralization, and urbanization are not conducive to improving the national industrial green development level, whereas economic development, foreign direct investment, industrial structure, and technological progress are positive contributors. At the same time, the level of economic development and technological progress have significant direct and spatial spillover effect. Our findings also provide some policy implications for improving China's industrial green development.

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China.

Although the digital economy has become a new driving force for development worldwide, it is still unclear how digital economy development affects green total factor energy efficiency (GTFEE). Using panel data from 281 prefecture-level cities in China from 2003 to 2018, this study empirically analyzes the effect of digital economy development on GTFEE by adopting a dynamic panel model, a mediation effect model, a dynamic threshold panel model, and a spatial Durbin model. The empirical results show that digital economy development has a significantly negative direct effect on GTFEE. The digital economy can impact GTFEE by the mechanisms of electrification, hollowing out of industrial scale, and hollowing out of industrial efficiency. Neither innovation nor environmental regulations significantly change this negative impact. The dynamic threshold panel model shows a nonlinear relationship between digital economy development and GTFEE, which indicates that the effect of digital economy development on GTFEE significantly inverts from negative to positive as the digital economy develops. In addition, GTFEE has a significantly positive spatial correlation, and the digital economy has a positive spatial spillover effect on GTFEE.

Have public environmental appeals inspired green total factor productivity? empirical evidence from Baidu Environmental Search Index.

Literatures focus on whether formal environmental regulatory policies can effectively stimulate green total factor productivity (GTFP), but generally ignore the role of informal institutions such as public environmental appeals. This paper uses inter-provincial panel data and Non-Radial Slacks-Based Measure (SBM) model to measure GTFP. With the Baidu Environmental Search Index presenting the public environmental appeals, the dynamic panel System Generalized Method of Moments (SYS-GMM) and Differenced Generalized Method of Moments (DIFF-GMM) methods are used to explore the effect, transmission mechanism and conditions of the public's environmental demands on green total factor productivity. The study concludes that public environmental appeals are beneficial to improve GTFP, and this result still holds after endogenous and robustness tests. The mechanism results show that the green technology innovation effect is an important mechanism for public environmental appeals to improve GTFP. In addition, public environmental appeals of different pollutants and different locations have heterogeneous effects on GTFP. In addition, the public wealth level, human capital level, and government institutional environment play an important role in the impact of public environmental appeals on GTFP.

The Dynamic Relationship Between Social Capital and Suicide Rates.

Background: Suicide is an important public health concern worldwide. Among various factors, social capital has been suggested to be an effective factor to prevent and reduce suicide. Aims: The purpose of this study was to investigate the association between social capital and suicide rates in Seoul, South Korea, using panel data from 2005 to 2018 at the administrative-district level. Methods: Data for the current study were obtained from Seoul Statistics. The within estimator and the system generalized methods of moments estimator were used. Results: The results showed that there was an inverse association between community facility and suicide rates. This result remained the same even after considering the dynamic relationship between social capital and suicide rates (B = -0.57, 95% CI: -1.10, -0.04) while adjusting for dynamic panel bias. A 10% increase in community facility per 1,000 population was associated with 5.2% reduction in age-standardized suicide rates per 100,000 population. Limitations: In this study, only a structural dimension of social capital was utilized due to the lack of available data. Conclusion: The results indicate that facilitating opportunities for social interactions and community lives has a potential to prevent and reduce suicide.

Does federal flood hazard mitigation assistance affect community rating system participation?

With the inexorable march of climate change, increased flooding is inevitable. Understanding the feedback between federal flood mitigation policies and the ways in which local governments build flood resilience is a significant gap in the literature. In particular, the effect that federal flood mitigation grants have on the intensity of local flood mitigation is nonexistent. This work measures flood risk mitigation by using the level of participation in FEMA's Community Rating System (CRS). Communities that participate in the CRS and undertake mitigation are awarded points; more points imply a higher level of participation. Since its inception in 1990, CRS communities have received considerably more federal pre-disaster flood mitigation grants compared to non-CRS communities. This study assesses the effect of federal pre-disaster flood mitigation grants on the level of participation in the CRS program. We use data on Hazard Mitigation Assistance programs and CRS participation data between 2010 and 2015. We link these data to flood risk and socioeconomic information. Our results indicate (i) federal pre-disaster flood mitigation grants do not appear to significantly influence the level of CRS participation, (ii) the effect of flood risk and socioeconomic factors on the level of CRS participation are mixed, and (iii) the current level of CRS participation is influenced by the previous level of CRS participation, which is not tied to federal pre-disaster flood mitigation grant. These findings add to the growing discussions on the drivers and barriers of local flood risk mitigation.

Forecasting consumption expenditure using a dynamic panel model with cross-sectional dependence: the case of Japan.

In this study, we predict the future trends of consumption expenditure in disaggregated age groups in both the within-sample and out-of-sample periods. In addition, we incorporate the estimation of a dynamic panel model with cross-sectional dependence into our forecasting methodology. As a whole, our dynamic panel model generates accurate forecasts for within sample. In particular, the accuracy is better in the 40-49 age group, while it is the most inaccurate for the over-70 age group. The out-of-sample period forecast results show that the dynamic panel model generates more accurate than the AR model in almost all age groups. Further, the impact of the COVID-19 shock in 2020 will be retained in many age groups for some time, leading to a decline in consumption. However, after a while, this impact will gradually disappear, and consumption will increase for most age groups. On the other hand, the out-of-sample period forecast results show that the older age group drags out the COVID-19 shock longer than the younger age group and will take longer to recover its consumption levels. In addition, aging of the heads of Japanese households will make it difficult for these households to maintain their current consumption levels unless some measures are taken to deal with the older age group.

Cost of high leverage in socially responsible firms in a linear dynamic panel model. Evidence from product market interactions.

Corporate Social responsibility is the major challenge for senior management of firms and they devoted the significant resources for CSR initiatives. Despite of significant comprehension of CSR, an ongoing debate is still under consideration about its economic repercussions in terms of "do well by doing good". Corporations are facing huge leverage cost with bad customer reputation in the product market. This study attempt to examine this phenomenon as the cost of high leverage in socially responsible firms and the product market interactions of those firms. The data is collected from 2009-2020 in linear dynamic setting for product market interaction, and two step system GMM estimation technique is applied for endogeneity concerns. The study identified that socially responsible firms are experiencing better growth in their sales in product market that maximize the financial benefits. However, the high leverage cost worsen their performance in product market because leverage is associated with some losses in market share due to unfavorable actions of competitors and customers. Socially responsible firms experience the low cost of high leverage which helps the firms to increase the performance in product market. Moreover, the corporate governance effectively devises the strategies to diminish the high leverage cost in the way towards better product market interactions. The results are conclusive across the financial crisis, firm's classifications and different channels of firms. The study enables the holistic and broader understanding of CSR in the reduction of high leverage cost with an intention to increase the firm's sustainability in product market. The study contributes with a view to ascertain the cost of high leverage in socially responsible firms for product market interactions of Pakistani firms in a linear dynamic panel.

The impacts of the 1997 Asian financial crisis and the 2008 global financial crisis on renewable energy consumption and carbon dioxide emissions for developed and developing countries.

This paper examines whether the 1997 Asian financial crisis affected the renewable energy/carbon dioxide (CO2) emissions relationship differently when compared to the 2008 global financial crises. Using the Dynamic Panel Data Model, we examine separately the impact of the 1997 crisis and the 2008 crises on the stated relationship for annual data between the 1987-2018 period for a group of high, upper-middle, and lower middle-income countries. Our findings suggest that the results were crisis and country specific. For the overall sample, the relationship between the two variables was positive (and significant post-1997 and pre-2008 crises) but negative post-2008 crisis. In contrast, the positive relationship remained unchanged for the lower middle-income subsample through the two crises. We also find evidence that the 1997 Asian crisis altered the relationship differently than the 2008 financial crisis especially for the upper and middle-income groups. Clearly, reduction of CO2 emissions may not be guaranteed even if host countries adopt renewable energy sources since country income levels and the nature of the crisis may matter. Future research may consider how the degree of pollution controls and differential costs of renewable energy adoption in countries may alter this relationship.

Temporal Relationship Between Change in Subjective Distress and PTSD Symptom Decrease During Prolonged Exposure Therapy for Posttraumatic Stress Disorder.

There is growing evidence that change in distress is an indicator of change during Prolonged Exposure (PE) for posttraumatic stress disorder (PTSD). However, temporal sequencing studies investigating whether change in distress precedes PTSD symptom decline are lacking. These studies are essential since the timeline between indicators of change and treatment outcome is a key assumption for mediation. The aim of the present study was to assess the temporal relationship between within- and between-session change in subjective distress and PTSD symptom decrease. We analyzed session data from 86 patients with PTSD. Data were analyzed using dynamic panel models. We distinguished temporal effects (within-persons) from averaged effects (between-persons). Results regarding the temporal effect showed that within-session change in subjective distress preceded PTSD symptom improvement while the reversed effect was absent. Averaged within-session change in subjective distress was also related to PTSD symptom improvement. Results regarding the temporal effect of between-session change in subjective distress showed that it did not precede PTSD symptom improvement. Averaged between-session change in subjective distress was related to PTSD symptom improvement. This study provides evidence for within- but not between-session change in subjective distress as indicator of change during PE. We also found that the way of modeling potential indicators of change affects results and implications. We recommend future studies to analyze mediators during treatment using temporal rather than averaged effects.

The positive role of trade openness in industrial green total factor productivity-provincial evidence from China.

The sustainable development of the economy is a key issue of global concern. Green total factor productivity (GTFP) combining economic growth with resources and the environment can evaluate the quality of economic development comprehensively and accurately. In this paper, super slack-based measure (Super-SBM) model and Malmquist-Luenberger (ML) index were used to calculate GTFP. The trend of industrial GTFP in China's 30 provinces from 2006-2015 was analyzed. Furtherly, a dynamic panel model was used to discuss the impact of trade openness on GTFP. The results showed that (1) the growth rate of GTFP rose from 2007 to 2011 and declined significantly from 2011 to 2015, and GTFP only achieved positive growth in 2011; (2) the growth rate of GTFP in the eastern region was higher than that in the central and western regions; (3) the trend of technical progress change (MLTECH) index was highly consistent with that of ML index. That was, technical progress played a major role in the variation of GTFP; (4) trade openness could significantly improve China's GTFP. Every 1% increase in trade openness could increase GTFP by 0.097% on average. It is advisable to implement differentiated economic development and environmental policies in different regions. Meanwhile, relevant measures can be taken to promote import and export trade, such as encouraging companies to increase investment in green technology research and development, optimizing the trade environment.

Mediating role of depressive symptoms linking insecure attachment and disordered eating in adolescents: A multiwave longitudinal study.

Research has supported a link between insecure attachment and disordered eating in adolescents; however, how this influence is exerted remains unclear. This study explored whether depressive symptoms constitute a pathway through which insecure attachment to parents predicts subsequent development of disordered eating in the transition from childhood to adolescence. The study also examines whether there are differential effects regarding the attachment figure, child's gender, or reciprocity between variables. A community-based sample of Spanish youth (n = 904; 49.4% girls) was followed biennially from age 10 to 16 years. Attachment, depressive symptoms, and disordered eating were measured using the Inventory of Parental and Peer Attachment, Children's Depression Inventory, and Children's Eating Attitudes Test, respectively. Prospective data were analyzed using a dynamic panel model, which accounts for unmeasured time-invariant factors. Whereas insecure attachment to the father did not predict later depression or disordered eating, higher insecure attachment to the mother at ages 10 and 12 years predicted more disordered eating at ages 14 and 16 years via increased depressive symptoms at ages 12 and 14 years. No child's gender-specific or reverse mediational effects were found. This study suggests that an increase in depressive symptoms might be one mechanism by which insecure attachment exerts its influence on the development of eating disorders symptomatology in adolescence. Intervention efforts aimed at strengthening particularly the mother-child attachment relationship may reduce the vulnerability to develop depressive symptoms and disordered eating.

Evaluation of the Policy Effect of China's Environmental Interview System for Effective Air Quality Governance.

The Ministry of Ecology and Environment of the People's Republic of China formally proposed an environmental interview system in May 2014, which applies pressure on local governments to fulfill their responsibility toward environmental protection by conducting face-to-face public interviews with their officials. In this paper, 48 cities that were publicly interviewed from 2014-2020 were considered the experimental group and 48 cities surrounding them were the control group. First, the dynamic panel model is applied to initially determine the effect of the policy. Then, a regression discontinuity method (Sharp RD) is used to analyze the short-term and long-term effects and compare the reasons for the differences observed among the estimates of various types of samples. Finally, a series of robustness tests were also conducted. The results show that the environmental interview system can improve air quality. However, because an emergency short-term local governance system exists at present, the governance effect is not long-term and, therefore, not sustainable. Therefore, it suggests that the government should continue to improve the environmental interview system, establish an optimal environmental protection incentive mechanism, and encourage local governments to implement environmental protection policies effectively in the long term. The results of the research are of great significance to the environmental impact assessment system of the world, especially in countries with similar economic systems, which are facing a trade-off between economic growth and environmental sustainability.

Government corruption, market segmentation and renewable energy technology innovation: Evidence from China.

Due to global warming and increasingly severe resource and environmental constraints, the role of renewable energy in reducing pollutant emissions and mitigating environmental degradation has gradually attracted the attention of all countries. This study examines the relationship between government corruption, market segmentation, and renewable energy technology innovation. The regression results show that government corruption can increase the degree of market segmentation, and both government corruption and market segmentation can significantly reduce regional renewable energy technology innovation. Further analysis shows that the improvement in market segmentation can lead to a negative moderating effect of corruption on renewable energy technology innovation. In addition, corruption and market segmentation have complementary effects on the impact of renewable energy technology innovation. The improvement of corruption level can increase the negative influences of market segmentation on renewable energy technology innovation. Similarly, the higher degree of market segmentation can increase the restraining effect of corruption on renewable energy technology innovation. Therefore, this study provides a valuable reference for all countries to accelerate the construction of regional market integration, break through interprovincial barriers, and improve renewable energy technology innovation.

Impacts of Industrial Restructuring and Technological Progress on PM2.5 Pollution: Evidence from Prefecture-Level Cities in China.

PM2.5 pollution has produced adverse effects all over the world, especially in fast-developing China. PM2.5 pollution in China is widespread and serious, which has aroused widespread concern of the government, the public and scholars. This paper evaluates the evolution trend and spatial pattern of PM2.5 pollution in China based on the data of 281 prefecture-level cities in China from 2007 to 2017, and reveals the pollution situation of PM2.5 and its relationship with industrial restructuring and technological progress by using spatial dynamic panel model. The results show that China's PM2.5 pollution has significant path dependence and spatial correlation, and the industrial restructuring and technological progress have significant positive effects on alleviating PM2.5 pollution. As a decomposition item of technological progress, technical change effectively alleviates PM2.5 pollution. Another important discovery is that the interaction between industrial restructuring and technological progress will aggravate PM2.5 pollution. Finally, in order to effectively improve China's air quality, while advocating the Chinese government to pursue high-quality development, this paper puts forward a regional joint prevention mechanism.

Can Industrial Collaborative Agglomeration Reduce Haze Pollution? City-Level Empirical Evidence from China.

We analyze the mechanism for industrial co-agglomeration in Chinese 283 cities to affect haze pollution from 2003 to 2016 and examine the possible mediating effects of urbanization and energy structure between haze pollution and industrial co-agglomeration, finally obtaining the following results. First, industrial co-agglomeration and haze pollution across China, including central and eastern regions keep a typical inverted U-shaped curve relationship. That is, industrial co-agglomeration first promotes haze pollution and then restrains it. However, the impact of industrial co-agglomeration on haze pollution in western China is still on the left side of the inverted U-shaped curve, reflecting a promotion effect. Second, industrial co-agglomeration has a significant spatial spillover effect on haze pollution. Additionally, industrial co-agglomeration can promote haze pollution in local regions but inhibit it in surrounding regions in both the short and long run. In contrast, when the industrial co-agglomeration index exceeds the inflection point (3.6531), it benefits the reduction of haze pollution in local regions, while not being conducive to it in the neighboring regions. Third, industrial co-agglomeration can affect haze pollution through urbanization and energy structure, that is, urbanization and energy structure play an intermediary role between them.