Dynamic spillovers between clean energy and non-ferrous metals markets in China: A network-based analysis during the COVID-19 pandemic

Due to the close production link between clean energy and non-ferrous metals, their price and market dynamics can easily affect one another through production costs. Furthermore, with the increased financialization of clean energy and non-ferrous metals markets, investment risk can easily spread between them. Therefore, this paper intends to explore the risk contagion between the two markets through the spillover index model and the minimum spanning tree (MST) method. Employing the data collected in China, this paper quantifies the magnitude of risk transfer by the volatility spillovers of eight clean energy stock markets as identified in The Energy Conservation and Environmental Protection Clean Industry Statistical Classification 2021 and the eight corresponding non-ferrous metals futures markets, while fully considering the heterogeneity between sub-markets. First, we find that risk is mainly transmitted from clean energy to non-ferrous metals. Second, this paper identifies not only the most influential market but also the shortest path of risk contagion based on the MST topology analysis. Last, the empirical results show that the COVID-19 has increased the scale of risk transmission between the two markets and their connectivity. During the COVID-19 period, the shortest path between the two markets shifted from "hydropower–gold” to "smart grid–zinc”, and the systematically influential markets correspondingly become smart grid and zinc. The results obtained in this paper might have practical implications for policymakers seeking to achieve effective risk management, which could also facilitate investors for diversification benefits. © 2023 Elsevier Ltd

Labour Market Dynamics and Worker Flows in India: Impact of Covid-19.

Tracking and analyzing the labour market dynamics at regular, frequent intervals is critical. However, this was not possible for India, a large emerging economy with a significant population undergoing demographic transition, due to a paucity of data. We use the new dataset Centre for Monitoring Indian Economy (CMIE)-Consumer Pyramids Household Survey (CPHS) and use a panel to create Labour Flow Charts and Transition Matrices for India from January 2019 to December 2021. To the best of our knowledge, this is the first time these were created for India. We then use that to look at the impact of Covid-19 on the Indian labour market. We not only look at transitions between employment, unemployment and out of labour force, but also across types of employment-full-time and part-time. The rich data also allows us to consider heterogeneity in the labour market and look at the differential impact of the pandemic across different education groups and gender. From the labour flow charts and transition probabilities, we find that while all groups have been impacted, the magnitude of the impact is different across groups. The recovery is also uneven, and the extent depends on education levels. Further, we do an event study analysis to examine the likelihood of getting a full-time job across different educational and gender groups. Men, on average, enjoy a higher likelihood of getting a full-time job than women. The likelihood coefficients also go up with increasing educational qualifications. Looking at skill heterogeneity, while the likelihood of getting a full-time job either goes down for most groups during the pandemic or the change is minuscule, strikingly it goes up for those with no education, for both men and women. The likelihood coefficients remain elevated for men even after the restrictions are removed, and that for women reverts to the level seen before the pandemic. Finally, this paper provides a way to continuously monitor the dynamics of the labour market as data is released in the regular intervals in the future, which would be of great value for researchers and policymakers alike.

Recurrence measures and transitions in stock market dynamics

The financial markets are understood as complex dynamical systems whose dynamics is analysed mostly using nonstationary and brief data sets from stock markets. For such data sets, the most reliable method of analysis is the one based on recurrence plots and recurrence networks, constructed from the data sets over the period of study. In this study, we do a comprehensive analysis of the complexity of the underlying dynamics of 26 markets around the globe using recurrence based measures. We also examine trends during the transitions as revealed from these measures by the sliding window analysis along the time series during the Global Financial Crisis (GFC) of 2008 and compare that with changes during the most recent pandemic related lock down. We show that the measures derived from recurrence patterns can be used to capture the nature of transitions in stock market dynamics. Thus, our study indicates that the transition in the dynamics prior to GFC is due to increasing stochasticity as seen from the recurrence measures. We also find that the markets have not stabilised after the 2020 pandemic and may possibly approach a crisis in recent future. Further the markets that go together during GFC are responding differently during the pandemic indicating that the underlying causes and mechanisms can be different. • Recurrence plots and networks from stock market data are used to study their dynamics. • Dynamics during Global Financial Crisis (GFC) and recent pandemic are studied. • Transitions in dynamics during GFC are found to be stochasticity driven. • Our study indicates that most of the markets have not stabilized after the pandemic. [ FROM AUTHOR]

An Analysis of the Housing Market Dynamics in the Italian Municipalities

The Covid-19 pandemic has caused numerous variations in the global economies with repercussions in all sectors. Once the emergency phase has finished, the entire worldwide population has changed its lifestyle and has had to adapt to live with the pandemic. In particular, the several modifications that have occurred in the job market and in schools and universities have determined a necessary reorganization of domestic spaces. The present study represents the first phase of a wider research aimed at verifying the transformation in the Italian residential market demand resulted by the Covid-19. The analysis carried out in this work has been performed at the municipal level, by considering the data published by the National Institute of Statistics collected for the 15th General Census of the population and housing in 2011. The dataset collected has been processed through an advanced econometric technique in order to identify the functional relationships between the residential average unit market value and the main architectural, socio-demographic and territorial factors. Further developments of this research will concern the application of the same methodological approach proposed to data detected by the National Institute of Statistics for the 16th Census scheduled for 2021. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Survey data on growth companies' and control group's perceptions on innovative behavior.

The data set contains data collected using a paper format and an online survey. The data includes a sample of 120 Finnish companies. The survey, structured into six sections focuses on the firms' growth outlooks and the underlying management practices and principles. The data reports the perceptions of top managers on growth, innovativeness, and the ability for renewal. The majority of the data comprises Likert scale questions on respondents' agreement or disagreement on innovation behaviors. This is complemented with micro-level data based indicator if a company is a growth company, the companies' growth expectations as percentage, and if COVID-19 has had business impacts. The data description is associated with a codebook and survey form. The data can be used to better understand growth and non-growth companies behaviours and outcomes. The associated material offers an opportunity to replicate the study in different regions.

Pre-Engineered Standardized Turbomachinery Solutions: A Strategic Approach to Lean Project Management

Effective project management plays a crucial role to the success of organizations via resilient execution of activities, in terms of performance and efficiency. Due to the recent market dynamics and its associated uncertainties, affecting several segments in the oil and gas (O&G) industry, utilization of innovative contracting schemes such as Front End Engineering Design (FEED) competition, and value engineered products are becoming of great importance to achieve the project's goals optimally. This paper discusses the competitiveness and strategic benefits of employing the vendor's pre-engineered and standardized turbomachinery equipment/solutions, to meet the required functionality while maintaining the highest levels of quality and safety. Several project management concepts and tools were employed, such as SWOT analysis, to discuss the benefits of supplying vendor's pre-engineered high value and long-lead turbomachinery equipment within projects, as a cost-effective solution, in place of customized products. A Requirements-to-Implementation Mapping (RIM) exercise was also carried out to benchmark the pre-engineered solutions with the industry practices while considering the packaging requirements from well-known international and national oil companies. This paper also presents success stories of implementing pre-engineered solutions that strongly contributed in improving the management of projects from engineering to operational phase. This study works in line with the recent O&G operators' initiatives in promoting agile approach to mitigate the forces that are impacting the industry and in turn the economy, such as COVID-19 pandemic. The study analysis, employing semi-quantitative approach, revealed that the pre-engineered solution brings to customers an improved value proposition in terms of cost, delivery, quality, safety, and aftermarket support, which contributes greatly in minimizing gold plating to achieve leaner projects. Standardized equipment is also found to be effective in minimizing the risks associated with changes and therefore improving the control on project constraints as well as simplifying the purchasing management of strategic equipment. In this respect, the use of standardization and pre-engineered activities could lead to a reduction of lead time up to 30%. The reliability of the standardized equipment will also be increased due to the proven frozen designs which have been repeatedly manufactured, tested, and supplied and therefore ensures successful and seamless project close-out. The proposed approach of mixing pre-engineered commodities to customized and configurable features based on site conditions provides the proper flexibility required by O&G industry while, simultaneously, maximizing the benefits of standardization. The strategic benefits of pre-engineered turbomachinery packages in the context of project management and supply chain process is not well recognized. This study explains these benefits to increase the customer's confidence level in utilizing this approach and benefit from its values, especially during the changing dynamics of the O&G industry. © Copyright 2021, Society of Petroleum Engineers

Scientific collaboration networks and firm innovation: the contingent impact of a dynamic environment

PurposeThe environment in high-tech industries is highly dynamic, and after COVID-19, it has become even more unpredictable. Hence, it has become critical for firms to develop strategies to cope with a highly dynamic environment. This paper aims to analyze how the impact of the scientific collaboration networks with URIs (universities and research institutes) on firm innovation performance is contingent on technological and market dynamics.Design/methodology/approachUsing a sample of 174 Chinese firms in the new-energy vehicle industry during 2004–2015, the authors applied a random-effects negative binomial modeling approach to model these relationships.FindingsA broad and strong scientific collaboration network promotes firm innovation network effects are contingent on technological and market dynamics. While technological dynamics strengthen the effect market dynamics weaken it due to the different purposes of collaboration for firms and URIs.Practical implicationsFirms should adjust the structure of scientific collaboration networks with URIs when facing different environments. The government should encourage firms to jointly research with diverse URIs and play an active role in stabilizing market environments.Originality/valueThis study contributes to the academic debate on university-industry scientific collaborations. Applying the temporary competitive advantage (TCA) framework, we provide nuances to the literature that studies the factors that condition the effects of networks. This study also adds to the research on firm scientific collaboration networks by measuring networks based on the coauthorship between firms and URIs.

The Importance of the Part-Time and Participation Margins for Real Wage Adjustment

We introduce a decomposition of the growth in real median usual weekly earnings of full-time wage and salary earners into parts due to earnings increases of those who remain employed, the intensive margin, and due to changes in those who are employed, the extensive margin. The intensive margin is procyclical and dominates during expansions. The extensive margin is countercyclical and important during downturns, especially during the Great and COVID Recessions. The extensive margin is mainly driven by entries from and exits to part-time employment and nonparticipation, not unemployment.

Women’s Employment and Digital Technology: A Regional Analysis in India

The article explores women’s employment and the future of work due to the changing nature of jobs as a result of the onslaught of new technologies. Adoption of new digital technologies, industry 4.0 technologies and the increasing influence of platform or gig economy has had intense effects on the ‘future of work’, causing dramatic changes. Further, COVID-19 has severely impacted the economy, especially women, reflected in the consistent fall in female labour force participation across states. The unemployment rate (UR) is significantly higher among urban women. A large proportion of woman workers are vulnerable from automation because of their low-skill and the unskilled and routine nature of their work. The risk of automation is much higher in the case of women working in manufacturing and modern services. Women in India are engaged largely in traditional jobs with low level of education and skill, and having limited or negligible social security, particularly in the unorganised sector. The article is based on the secondary data provided by the National Sample Survey Organisation (NSSO) and uses the International Labour Organization (ILO) skill framework. The analysis clearly shows that skill sets among women is abysmally low. Noticeably, enhancing skill development as per the emerging market demand, including digital literacy, will go a long way to expand job opportunities for women. © 2021 Institute for Human Development.

Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19.

This paper uses new and recently introduced methodologies to study the similarity in the dynamics and behaviours of cryptocurrencies and equities surrounding the COVID-19 pandemic. We study two collections; 45 cryptocurrencies and 72 equities, both independently and in conjunction. First, we examine the evolution of cryptocurrency and equity market dynamics, with a particular focus on their change during the COVID-19 pandemic. We demonstrate markedly more similar dynamics during times of crisis. Next, we apply recently introduced methods to contrast trajectories, erratic behaviours, and extreme values among the two multivariate time series. Finally, we introduce a new framework for determining the persistence of market anomalies over time. Surprisingly, we find that although cryptocurrencies exhibit stronger collective dynamics and correlation in all market conditions, equities behave more similarly in their trajectories and extremes, and show greater persistence in anomalies over time.

Association between COVID-19 cases and international equity indices.

This paper analyzes the impact of COVID-19 on the populations and equity markets of 92 countries. We compare country-by-country equity market dynamics to cumulative COVID-19 case and death counts and new case trajectories. First, we examine the multivariate time series of cumulative cases and deaths, particularly regarding their changing structure over time. We reveal similarities between the case and death time series, and key dates that the structure of the time series changed. Next, we classify new case time series, demonstrate five characteristic classes of trajectories, and quantify discrepancy between them with respect to the behavior of waves of the disease. Finally, we show there is no relationship between countries' equity market performance and their success in managing COVID-19. Each country's equity index has been unresponsive to the domestic or global state of the pandemic. Instead, these indices have been highly uniform, with most movement in March.

The distributional impact of recessions: The global financial crisis and the COVID-19 pandemic recession.

Using U.S. Current Population Survey data, this paper compares the distributional impacts of the COVID-19 Pandemic Crisis and those of Global Financial Crisis in terms of (i) worker characteristics, (ii) job characteristics-"social" (where individuals interact to consume goods), "teleworkable" (where individuals have the option of working at home), and "essential" jobs (which were not subject to government mandated shutdowns during the recent recession), and (iii) wage distributions. We find that young and less educated workers have always been affected more in recessions, while women and Hispanics were more severely affected during the Pandemic Recession. Surprisingly, teleworkable, social and essential jobs have been historically less cyclical. This historical acyclicality of teleworkable occupations is attributable to its higher share of skilled workers. Unlike during the Global Financial Crisis, however, employment in social industries fell more whereas employment in teleworkable and essential jobs fell less during the Pandemic Crisis. During both recessions, workers at low-income earnings have suffered more than top-income earners, suggesting a significant distributional impact of the two recessions. Lastly, a large share of unemployed persons was on temporary layoff during the COVID-19 recession, unlike the Global Financial Crisis.

The recovery of global stock markets indices after impacts due to pandemics.

The COVID-19 brings back the debate about the impact of disease outbreaks in economies and financial markets. The error correction terms (ECT) and cointegration processing tools have been applied in studies for identifying possible transmission mechanisms between distinct time series. This paper adopts the vector error correction model (VECM) to investigate the dynamic coupling between the pandemics (e.g., the COVID-19, EBOLA, MERS and SARS) and the evolution of key stocks exchange indices (e.g., Dow-Jones, S&P 500, EuroStoxx, DAX, CAC, Nikkei, HSI, Kospi, S&P ASX, Nifty and Ibov). The results show that the shocks caused by the diseases significantly affected the markets. Nonetheless, except for the COVID-19, the stock exchange indices reveal a sustained and fast recovering when an identical length time window of 79 days is analyzed. In addition, our findings contribute to point a higher volatility for all financial indices during the COVID-19, a strong impact over the Ibov-Brazil and its poor recover when compared to the other indices.