Triggered by the rising demand, a complex aircraft production network has been evolving during the past half century. In order to analysis the spatial-temporal evolution of this network, this paper establishes a novel and complex data by collecting 1774 major global aircraft manufacturers' production relationship from Jane's All the World' s Aircraft Development & Production (1965-2021), and visualizes the spatial temporal characteristics of the global aircraft production network by using Social Net Analysis method. The characteristics are summarized as follows: (1) the main aircraft firms from 48 counties form a complex production network centered on the United States, Europe and China; (2) The production network remains diffusion during 1965-2005, but it retracts after 2005, which documents evidences of de-globalization trend in the aircraft industry; (3)AVIC, Airbus, Boeing, Textron, Lockheed, Kawasaki, Mitsubishi, Sikorsky, Bell, and Embraer are all ranked high in the study period and play the role of leading firms in the production network and drive the cooperative connections of other companies.

The purpose of this paper is to examine and elucidate the effect of the announcement of winning a US federal contract by pharmaceutical companies, traded on the NASDAQ stock exchange on the share prices. The analysis is based on a sample of 327 event days from 12 pharmaceutical companies listed on the NASDAQ market for a given period (2010 – 2021). The sample is analysed by using the event study methodology and Capital Asset Pricing Model (CAPM) in order to examine the abnormal returns and cumulative abnormal returns during an event window of 10 days before the event and 10 days after the event. While prior researchers have identified significant positive abnormal returns following different types of contract announcements, this study aims to contribute to the existing literature by exploring the specific impact of the public contract in the pharmaceutical market on market shares. By investigating this unique aspect, the research fills a gap in previous studies and enhances our understanding of the relationship between public contract announcements and market performance. The data collection utilises secondary data from the official open data source of US federal spending information and daily stock prices. The collected data is analysed quantitatively using event study methodology, allowing for statistical examination of abnormal returns, such as ANOVA analysis, t-statistic, beta index, time series analysis and linear regression. The research findings indicate a significant impact of public contract-winning announcements on cumulative abnormal returns, suggesting a positive reaction from the market. However, average abnormal returns within the event window were positive but not statistically significant. These results imply that winning a government contract has a limited impact on the stock market. The implications of this research highlight the importance of public contract announcements in the pharmaceutical industry and their influence on share prices. The findings provide valuable insights for investors and stakeholders, aiding decision-making processes related to investment opportunities and market performance.

In the behavioral domain, this study discloses the pattern between microblogging-opinionated information and yields on the investment. This phenomenon is particularly related to the political instability in the Pakistan’s economy through the multivariate techniques. Pre-political crisis, the pessimistic sentiments were priced in yields on the investment. In environments of political instability, the intensity of decline in yields was more responsive against an incline in the negative opinions. Meanwhile, the intensity of increase in returns was less responsive against an incline in the positive opinions. The findings were further supported by the Bayesian approach. Before the political instability takes place in the Pakistan’s economy, the occurrence of yields was noted in response to the bearish market period. Post-political instability, there was a higher posterior probability for occurrence of returns against the bearish market period. Conversely, a higher posterior likelihood was noted for occurrence of investment’s yields in response to the bullish market period, but this relevance was not completely probable. From the impulse response analysis, the response of returns was reported against the standard deviation shocks in the microblogging sentiment indicators. The analysis may have potential implications in terms of disclosing the investors’ behavior from a political perspective.

Green-biased technological progress takes into account the influence of energy input and pollution emissions, which is of great significance to China's green development. This paper decomposes technological progress into two categories: green input-biased technological progress (IBTC) and green output-biased technological progress (OBTC), using the Slacks-based measure integrating (SBM) model. The factor bias in technological progress is determined based on data from 34 industries in China from 2000 to 2015. The results show that green-biased technological progress exists significantly in the industry, and most of it promotes the growth of green total factor productivity. IBTC first tends to consume energy to pursue capital between capital input and energy input, while it tends to save energy after the Eleventh Five-Year Plan. Between labor input and energy input, it is biased towards saving labor and consuming resources. OBTC is biased towards promoting industrial growth and curbing pollution emissions. Medium and light-polluting industries are biased toward promoting industrial growth and curbing pollution emissions, while heavy-polluting industries are biased towards emitting more pollution.

This study employs empirical analysis using an econometric model that examines the interdependence among environmental degradation, exports, and economic development with energy use. It also provides an environmental Kuznets curve (EKC) for selected South Asian economies utilizing time-series data. The findings reveal a long-term, stable equilibrium link between energy demand and pollution. There exists a positive relationship between structural factors and pollution. Moreover, this study constructs a model of exports and pollution from an interdependent perspective. The three perspectives are tested: the scale and structure of energy consumption considering the twin constraints of export-trade and pollution, and the scale of pollution in export-trade constraint. These results show that the increase in energy use leads to higher CO2 emissions amidst export volume. However, in the presence of income, the scale of effect lowers a little. The analysis also supports the presence of Kuznets curve for south-Asian economies. The results imply substantial scope for development in the energy use and pollution structure within South Asia's current export trade process. This development can be attained by regulating energy use and enhancing system efficacy without necessitating changes to the scale effect or structural effect.

The digital transformation provides an opportunity for the development of a green and low-carbon economy. This study used panel data collected from 30 Chinese provinces between 2011 and 2018, and assessed the impact of digitization (Dig) on environmental efficiency (EE). Quantile regression is employed to scrutinize the evolution of the marginal effect. From the perspectives of population and institutional factors, this study empirically investigates nonlinear relationships and potential mechanisms using Hansen threshold and mediation models. The findings reveal several key insights. Overall, levels of digitization and environmental efficiency (EE) are increasing with regional dispersion expansion, indicating a “polarization” characteristic. The impact of digitization on EE exhibits noticeable stage and regional heterogeneity. Analysis of population factors reveals that population structure, population size, and human capital trigger a sharp “marginal increase” of positive effects with single thresholds of 0.8155, 7.2284, and 11.0497, respectively. Analysis of institutional factors highlights the significance of fiscal policy quality (tax proportion), education expenditure, and tax system structure as important intermediaries. Finally, this paper presents corresponding policy implications.

Human factor inputs are key to promoting agricultural modernisation. Traditional economic theory suggests that improving human capital is the key to boosting agricultural productivity, but can this conclusion hold in China's dualistic economic structure? We use Chinese provincial panel data from 2000-2017 to examine the impact of rural human capital inputs on agricultural total factor productivity. We find that, on the whole, rural human capital inputs have a negative effect on agricultural total factor productivity, and that there is a "rural human capital trap". Mechanism analysis reveals that rural human capital inputs, on the one hand, cause labour loss and reduce the quality of agricultural workers, while on the other hand, they may promote the application of mechanization, which has both positive and negative effects on agricultural total factor productivity. Heterogeneity analysis finds that this negative effect is more pronounced in the central region of China because of the serious loss of rural labour. This study provides new policy insights for further improving the structure of rural education inputs and promoting human capital accumulation in agriculture.

The digital transformation of manufacturing industry can promote the development of green transformation and promote the differentiation of workers’ skill structure; On the other hand, it will also hinder the green development due to the huge energy consumption generated by the application of digital technology and facilities. In addition, the green transformation of manufacturing industry will also have differentiated impacts on the employment of labour with different skills due to the innovation of green technology. The existing research has not discussed too much about the interaction among the digital transformation and green transformation in manufacturing industry and labour structure. So, this paper uses the PVAR model to examine the dynamic relationship between digital and green transformation within the industrial sector from the perspective of labour structure, specifically analyzing the impact difference across regions. The results suggest that there is a reciprocal connection between the digitization of manufacturing sector and the labour structure, particularly in the eastern region of China, but the overall interaction between the two remains weak. The interactive between the green transformation of manufacturing industry and the labour structure in the central and western areas has been delayed over periods 1-6. Digital and green manufacturing transformation reinforce each other in central and western regions. However, the digital revolution in the manufacturing industry is hindered by the green transformation in eastern region.

Economic globalization has intensified economic volatility around the world, and the importance of economic resilience has become increasingly prominent in the face of rising uncertainty due to frequent domestic and foreign shocks. Based on provincial panel data in China from 2008-2019, a comprehensive indicator system is constructed to measure regional economic resilience (RER), and the impact of financial driver (FD) on RER is explored from staged, pathway and non-linear perspectives. The main findings are as follows. (1) Both national and regional levels of FD and RER show an upward trend, and the impact of FD on RER has an “inverted-U” shape: as the capacity of FD increases, its impact on regional economic resilience shifts from promoting to inhibiting. The RER has significant spatial agglomeration characteristic. (2) Interestingly, staged analysis shows FD can significantly promote RER only when it is in the “recovery stage”. (3) The pathway analysis of its effect on regional economic resilience shows the following characteristics: financial scale > financial efficiency > financial deepening. (4) From different regions, there are significant differences in the effect of FD on the promotion of regional economic resilience: central region > western region > eastern region. Finally, the corresponding suggestions were provided.

Green innovation, driven by China's new development concept, plays a crucial role in high-quality economic development. In line with the green development trend, businesses increasingly prioritize whether their corporate environmental responsibilities (CER) can effectively enhance corporate green innovation (CGI) levels. This paper examines the influence and mechanism of CER on CGI using a dynamic perspective, drawing from 1,640 manually-collected panel data of Shanghai and Shenzhen A-share listed companies between 2010 and 2017. The primary findings indicate that the impact of CER on CGI possesses phase-specific characteristics and a dual effect of "crowding in" and "crowding out." The current phase of CER negatively affects green innovation, while the lag phase has a positive effect. CER's impact on various CGI types is heterogeneous: specifically, it follows an "inverted-N" trajectory (inhibition-promotion-inhibition) for "strategic green innovation" and has a promotional effect on "substantive green innovation," which is stronger and has a longer time lag. The mechanism analysis reveals that financing constraints play a critical mediating role. A heterogeneity analysis based on multiple dimensions (ownership, industry, and location) suggests that CER has a more significant driving force for CGI among state-owned firms, high-polluting industries, and enterprises in inland areas. Finally, the paper presents corresponding suggestions for government and corporate entities.

The expansion of urban infrastructure is an important indicator of agglomeration and a major factor in the deterioration of the urban environment. The investment in urban infrastructure is accompanied by the sealing of ground. The implementation of effective policies to reduce the practice of sealing ground is impeded by the existence of conflicting interests and fiscal disincentives. A significant challenge is the dearth of policy-relevant information. Conventional analysis considers urban outcome indicators in proportion to population and neglects non-linear distribution patterns, thus obscuring global regularities that contain important information. The study contributes to a more comprehensive understanding of urban imperviousness through the lens of urban scaling. The present study employs Germany as a case study to examine the extent to which the parameters of the scaling function differ between two types of cities. District Affiliated Cities (DACs) and Administrative City Districts (ACDs), which are afforded greater fiscal autonomy. The analysis indicates that the amount of sealed land exhibited a notable increase between 2006 and 2018 in the ACDs. Calibration of the scaling functions for cities with the actual coefficient of the DAC control estimate and a global orientation exponent (5/6) resulted in a 16% reduction of sealed ground. In conclusion, urban scaling laws offer a valuable tool for analyzing the complex dynamics of urban imperviousness and its control costs, thereby contributing to the formulation of more effective urban policies and planning.

In light of the events of 2020 and 2022, this study aims to examine the co-movements between the capital markets of the Netherlands (AEX), France (CAC 40), Germany (DAX 30), the United Kingdom (FTSE 100), Italy (FTSE MIB), Spain (IBEX 35), Russia (IMOEX), and spot prices of crude oil (WTI), silver (XAG), gold (XAU), and platinum (XPT) from January 1, 2018 to December 31, 2022. The purpose of this analysis is to answer the following research question: (i) Did the events of 2020 and 2022 increase the shocks between stock markets and WTI, XAG, XAU, and XPT prices? The findings indicate that time series do not follow a normal distribution and are stationary. In response to the question of investigation, we found that during the Tranquil period, it was possible to verify the existence of 28 causal relationships (out of 110 possibilities). During the stress period, there was a very significant increase in the number of causal relationships between the market pairs under analysis (62 causal relationships out of 110 possibilities), including a relative increase in the influence of commodities on capital markets and capital markets on commodities. These findings show that during the events of 2020 and 2022, capital markets and commodities significantly accentuated their co-movements among themselves, indicating that alternative markets such as WTI, XAG, XAU, and XPT do not provide safe-haven properties. These results have implications for portfolio diversification during times of global economic uncertainty.

Gold has been traditionally well recognized as a safe heaven for financial markets. Lately, Bitcoin has been gradually considered as a popular alternative. Since the outbreak of COVID-19 in early 2020, it has become even more necessary and critical to examine the diversification capability of them to hedge financial risks associated with an unexpected crisis comparable to the pandemic. This paper hence employs the wavelet analysis, complemented by the multivariate DCC-GARCH approach, to measure the coherence of the gold and Bitcoin prices with six representative stock market indices, three for developed economies and three for emerging economies, all of which are heavily affected by the pandemic. To have a more balanced and comprehensive analysis, two-year data are used, spanning from 12th April 2019 to 15th April 2021, which covers approximately one year before and one year after the announcement of the COVID-19 pandemic. The results suggest that the returns of both gold and Bitcoin are generally not strongly correlated with the market returns of all six indices, particularly for short-term investment horizons. That is, investors in all six indices can benefit through gold, as well as Bitcoin, in terms of hedging. Meanwhile, compared with Bitcoin, gold shows to be less correlated with the indices, particularly for long-term investment horizons. The findings hence suggest that gold and Bitcoin offer diversification benefits to investors in the market indices during a crisis such as the COVID-19 pandemic, especially for short-term investment horizons. The study also reminds policymakers thinking beyond the pandemic about the future of the earth, including air pollution and health, for sustainable development of the whole world.

This study investigates the impact of inventor CEOs on firm performance using a manually collected database of firms' inventors. Our findings reveal that, on average, firms with inventor CEOs experience a one- and two-percentage-point increase in ROA and ROE, respectively, compared to firms with noninventor CEOs. To address potential endogeneity issues, we employ turnover analysis, an instrumental variable approach, and propensity score matching. The estimation results suggest that inventor CEOs significantly enhance firm performance by fostering innovation and total factor productivity. This research contributes novel evidence on the relationship between inventor CEOs and firm performance.

By introducing time to build, which creates a time-lag between government investment and the accumulation of productive capital, into an analysis of fiscal stimulus to the economy with financial frictions, we find that the effectiveness of fiscal policy is dampened. While the weakening effects of time to build become significantly weaker alongside with a higher fraction of government bonds allocated to leverage-constrained banks, which can be explained by a high correlation between time to build and financial frictions in both worsening balance sheet conditions of banks. Furthermore, the stimulus effects of public investment become stronger associated with shorter time-to-build period.

The vigorous development of the digital economy has brought new opportunities and challenges to the construction of local fiscal revenue efficiency. Based on the panel data from 2011 to 2020, this paper uses the fixed effect model, instrumental variable method and other empirical studies to investigate the impact of the development of the digital economy on the efficiency of local fiscal revenue. The research results show that the development of the digital economy has directly improved the efficiency of local fiscal revenue, and the regression results of instrumental variables are still significant. The mechanism analysis shows that the development of digital economy mainly promotes local fiscal revenue such as efficiency improvement by cultivating tax sources.

This paper empirically investigates the relation between firm performance in corporate social responsibility (CSR) and the need and likelihood of external financing to test the predictions of agency and stakeholder theories. Empirical results from Logit, Linear Probability Model, OLS and Firm fixed effects regressions indicate that CSR is negatively related to the likelihood and level of external financing. Further analysis indicates that CSR has a negative and significant effect on both net equity issued (NEI) and net debt issued (NDI), the two components of external financing. Overall, the empirical results support the predictions of agency theory.

The relation between fund flows and returns in the Australian ETF industry is assessed in this study. Daily data from 43 equity ETFs over the period 2019-2023 are used. The main research objective is to accentuate whether past returns can predict future fund flows and in what way and vice versa. According to the results of the applied regression analysis, past flows and past returns can predict to some extent concurrent flows. This is also the case about concurrent returns. However, in both cases, the results are not unanimous and depend on the specification of the applied regression model.

This paper investigates the impacts of COVID-19 on women’s employment and gender disparity with a longitudinal dataset spanning the pandemic. We exploit the regional intensities of social vulnerability and temporal variation to implement the difference-in-differences (DID) estimation. The results indicate that the pandemic and its associated lockdowns generate a significant and negative impact on women’s employment but not on men’s employment. Moreover, a counterfactual analysis using pre-pandemic data further supports the causal nature of the documented relationships. The evidence suggests that economic downturns caused by public health emergencies, unlike previous economic recessions, have a greater impact on women, and differentiated policies should be designed.

This study analyses the effects of piped water on household food consumption per capita by adopting inverse-probability-weighted regression adjustment and endogenous treatment effects approaches with data from the Cambodia Socio-Economic Survey carried out in 2013 and 2017. A complementary analysis of the effects on primary household income per working-age member is also conducted to give insights into the potential consequences. The study also conducts a robustness check by estimating the fixed effects of piped water utilising village panel data. The results suggest that households using piped water are likely to enjoy higher food consumption per capita, with a complementary finding demonstrating that the use of piped water is likely to increase household income per working-age member.