Recession Phase Research Articles

Do External Impacts Cause Differences between Regional and National Business Cycles?: Focusing on the Dongnam Metropolitan Area

Purpose – This study analyzes large differences and similarities through comparison with national level business fluctuations, including differences between regions within the Dongnam metropolitan area, focusing on the impact of major domestic and international economic shocks. Design/Methodology/Approach – This study conducted econometric analysis using the Markov switching model with the monthly manufacturing production indexes of each region from 2000 to 2020 as data. Findings – The characteristics of Dongnam metropolitan area, distinguished from other regions nationwide, are as follows. First, the regions’s manufacturing focuses on the heavy chemical industry and did not shrink, even during the 7th cyclical recession caused by the global IT bubble bursting. Second, the manufacturing sector in the Dongnam metropolitan area continued a downward trend, even during the 11th cyclical expansion. However, economic impact was found to have varied in size by region. Our analysis results show that Busan was more affected by internal and external impacts than Ulsan and Gyeongnam, showing slower recovery. Ulsan was shown to have much higher manufacturing resilience than other regions, despite several internal and external economic impacts. Finally, Gyeongnam showed several recession phases in 2008 and after 2016, but the duration was found to have been much shorter than in Busan. Research Implications – The impact and characteristics of business cycles caused by external shocks were found to have varied by region. The results imply that regionally specialized industrial support measures are required together with economic stabilization policies at the national level. It was also found that separate measures at the regional level need to be implemented in connection with governmental support measures for regional manufacturing industries.

Role of Marketing Strategies to Generation Z in Emerging Markets

The aim of this research is to examine the marketing strategies to Generation Z, social media cognitive engagement, social media influencer, perceived corporate social responsibility and user-generated media communication and hedonic brand image as moderator on generation Gen Z purchase intention, and examining these effects in Covid’19 pandemic recession phase in Pakistan. Research was completed on Generation Z respondents, using an online survey questionnaire were evaluated using through factor analysis, model fit, SEM via Smart PLS 4. Empirical results via structural equation modeling demonstrate that the impact of the four constructs played a partially significant role on Gen Z purchase intention. Gen Z has strong bonding with social media engagement and aware of CSR activities of an organization and confirmed their behavior toward e-shopping. Brand equity and Citizen Behavior are could be examined as a dependent variable but we didn’t due to lack of literature. Social media cognitive engagement and perceived corporate social responsibility has strong relation with generation Z purchase intention which indicates generation Z is engage with social media and CSR activities. Online business operators and trend setter can identify and promote their business on social media sites. Through this study marketers and professionals can also formulate strategies to increase promote their business. The empirical results provide academic contributions to the current group of knowledge in the marketing to capture Gen Z. Using advanced quantitative data analysis will eventually enable future researchers to explain the contribution of the current study to understanding the importance of Generation Z psychology.

Сучасний стан світового фондового ринку та виклики його розвитку

The purpose of the article is to study the current state of the global stock market and potential challenges on the future path of its development. The study of the state of the world stock market, among other things, is carried out by analytical agencies that single out individual countries to analyze the state of their national stock markets: the USA, the Eurozone, the United Kingdom of Great Britain and Northern Ireland, Japan, China, Canada, and Australia. The largest in terms of proportion in the capitalization of the world market is the market of the group of North American countries (the USA and Canada), which occupies 83.13%. Currently, the global financial market is in a recession phase, which is characterized by high levels of inflation and certain specific features. Over the past decades, the global financial system has acquired additional trends that make their own adjustments to tendencies in the world stock market and create potential challenges to the development of the global securities market. Among the main challenges that affect the prospects of the global stock market, the following can be mentioned: 1) speculative challenge from the growth of the derivatives market; 2) potential challenge from the tendency of democratization of the global stock market. The democratization of the stock market is understood as an increase in the ability of individuals to gain access to capital markets, receive new information, access to investment platforms and investment products, that is, we are talking about the openness of the market and a decrease in its concentration; 3) challenges from the growth of cyber threats that can lead to manipulation of order management systems, which, in turn, leads to incorrect channels, fake orders or failure to submit along with damaging the trade surveillance systems, which will result in enabling the manipulative, illegal trade practices; 4) the negative consequence of standardization of capital raising through stock markets; 5) challenges within the post-COVID paradigm; 6) challenges from changes in the structure of investors; 7) challenges for the world stock market due to the full-scale invasion of Ukraine by the Russian Federation, which affected the energy and consumer sectors, as the commodity markets of oil, gas, agricultural products and fertilizers suffered, mainly having negative consequences for the markets of the continent of Eurasia and Africa. Thus, the global stock market is developing in a paradigm of uncertainty, geopolitical sharpness, significant rates of digitalization and the continuation of the boom in information technology, democratization and the post-pandemic period, which creates its own combination of challenges.

Анализ рынка искусственного интеллекта Российской Федерации

Artificial intelligence (AI) technologies are used in various fields of activity. Not only commercial organizations, but also the state are actively investing in the development of artificial intelligence. This is due to the fact that the use of AI tools and methods allows the development of many areas of activity, expanding their potential. Artificial intelligence has significant potential in the social and scientific spheres, in education, healthcare, industry and other areas. This necessitates the search for the most significant factors affecting the growth rate of artificial intelligence both within individual organizations and within the country as a whole. The purpose of the work is to conduct a scientific analysis of the artificial intelligence market of the Russian Federation, to identify factors affecting this market, as well as the main trends in its development. In the process of scientific research, the method of system analysis was used, as well as correlation-regression data analysis. The article examines the dynamics of the artificial intelligence market of the Russian Federation. The factors that had the strongest impact on this market were identified. The geography of companies operating in this field is investigated. The analysis of the dependence of the volume of the artificial intelligence market on various factors was carried out. Conclusions are made on the dynamics and development prospects of the studied market. The scientific novelty lies in the identified relationship between the volume of the artificial intelligence market and such factors as the total volume of transactions and the number of transactions in the AI venture market, the volume of government funding and government procurement in the field of artificial intelligence. The practical significance lies in the fact that the results obtained can be used to increase the effectiveness of stimulating the growth and development of the AI market in the Russian Federation. This becomes relevant due to the fact that in the short term, it is most likely that the growth rate of the AI market will slow down both in Russia and in the world, due to the negative impact of a complex of factors on the market. Such factors are, for example, the global shortage of semiconductors, the supply chain crisis, as well as the entry of the economies of many countries into a recession phase.

Global Seasonal-Scale Meteorological Droughts. Part I: Detection, Metrics, and Inland/Coastal Types

Knowledge of spatiotemporal characteristics and process evolutions is the fundamental basis of understanding drought mechanisms, especially from a global perspective. For a comprehensive investigation, we implemented event detection, type grouping, and spatiotemporal metrics from 3-dimensional (3D, longitude–latitude–time) perspectives. The major procedures and achievements were as follows. First, we identified global-scale seasonal-scale meteorological drought events following the recently proposed 3D DBSCAN (Density-Based Spatial Clustering of Applications with Noise)-based workflow of event detection. The 3D DBSCAN clustering algorithm can directly obtain arbitrarily shaped point collections over a given 3D space, as drought events can spread over space and evolve over time. Subsequently, these detected drought events are further grouped into inland and coastal types, as the observations revealed that some droughts over coastal regions originate from, extend to, or are accompanied by long-term precipitation deficits over adjacent oceans. Third, typical spatiotemporal characteristics (e.g., lifetime, genesis locations, migration/local developments, and process evolutions) were investigated with coastal/inland-type differences considered. The drought ratios originating from continents in all coastal-type droughts were ~50% over Africa, Asia, and South America, indicating the nonnegligible extension from continents to oceans. Additionally, process evolution-based analysis revealed intensity variations in intensification or recession phases, and coastal types overall displayed larger intensity variations than inland types. Moreover, ~92% of inland types and ~70% of coastal types can be treated as having symmetric development. Notably, the grouping type and spatiotemporal metrics herein can provide adequate preliminary knowledge for global-scale drought mechanism exploration.

Supply network position, digital transformation and innovation performance: Evidence from listed Chinese manufacturing firms.

This study provides evidence for the supply network position influencing innovation performance and the moderating effect of digital transformation. Supply chain relationships have been evaluated in earlier research to demonstrate how concentrations of customers and suppliers may either favorably or adversely impact innovation. These metrics, however, only take into account how closely a firm is connected to its direct customers or suppliers. This study integrates the top five suppliers and customers of Chinese listed manufacturing firms and considers the relationship embeddedness of each firm's direct customers and suppliers, as well as the structure embeddedness among the customers' customers, customers' suppliers, suppliers' customers, and suppliers' suppliers to reveal the true impact of supply chain relationships on innovation performance. The top five suppliers and consumers of each firm are chosen to build a supply network for each year using panel data of listed Chinese manufacturing firms from 2013 to 2020. Social network analysis is used to determine network centrality and structural holes. The results show that in the supply network, network centrality and structural holes are significantly negatively correlated with innovation performance, especially in small and medium-sized firms, non-state-owned firms, and firms in recession phase. According to the moderating effect model, digital transformation is an efficient way to reduce the negative effect of supply network position on innovation performance. The research results will further improve the supply network cooperation mechanism, which is of great significance for improving supply chain resilience and firms' innovation.

Paradigm Shift in Indian Banking System-Banking 5.0

The global economy is going through the phase of recession and the pandemic after effects are open to all. They have their unprecedented effects on all organizations, banking sector is not isolated. In view of all the vital developments and crisis, it’s essential to innovate strategies in banking sector. Finance being the lifeline for any economy and economic activities, how far the finance is managed and controlled. This article is a highlight of this issue. Banks and financial institutions need to offer customer products and services relevantly and promptly. There is need for new vision of banking .promoting fin techs and digital economy is the emerging area to be focused on. In view of digital transformation, such changes are termed as Banking 5.0. In this article, author focuses on economics of banking 5.0. AI can revolutionize banking by increasing productivity and customer value.

Implementing turnaround strategies as an entrepreneurial process

Recovery strategy belongs to the group of rescue/reversing business strategies and is used mainly by companies facing financial or other problems which they are trying to overcome. Moreover, this strategy is alternatively used by companies wishing to prevent future problems. The overall objective of the recovery strategy is to return of this sluggish situation in terms of acceptable levels of profitability. The implementation of turnaround strategy achieved through the implementation of proper planning and specific procedures (processes) like: Change management, divestitures of specific assets (divestment), cost reduction (cost reduction—operating and others), and strategic acquisitions. This strategy is so drastic, that in many senses it is like creating a new company, so it has many similarities to an entrepreneurial process. Obviously, there is a previous experience by managers, but when implementing this radical strategy, they must think in developing something new. The main objective of this paper is to explain how to implement a successful turnaround strategy during a recession phase of the economy. To analyze the turnover strategy, we developed a survey to 152 trading and industrial Greek companies that represent more than 3% of the Greek GDP. The study examines the role of successful turnaround based to whom formulated the strategic plan of the company, investigating the knowledge of the Greek managers on the tactics implemented during a turnaround plan. The paper offers information for management practitioners to understand how to implement a turnaround strategy in a turbulent economic environment, and which tactics apply.

The Phenomenon of MSMEs Performance in Magelang City During the Pandemic COVID-19

Micro, Small, and Medium Enterprises (MSMEs) have a fundamental role in the regional economy as well as the national economy. This study aims to provide empirical evidence regarding the performance variability of MSMEs during the COVID-19 pandemic. The research population is all MSMEs in Magelang City. The research sample was 7,924 MSMEs obtained through purposive sampling. This study uses descriptive statistical analysis. The results and discussion show that the City of Magelang, from an economic perspective, has a fairly stable economic condition from 2015 to 2019. However, the COVID-19 pandemic in 2020 put the economy of Magelang City in a recession phase. Nevertheless, the competitiveness of Magelang City in 2020 has increased compared to 2019. The analysis of the variability of the performance of MSMEs shows that the South Magelang District has the lowest turnover of MSMEs. Central Magelang Subdistrict has the highest MSME turnover value. South Magelang Subdistrict has the highest average turnover of MSME compared to the average turnover of MSME in North Magelang and Central Magelang Districts.

Evolution and Controlling Factors of the Reef and Carbonate Platform in Wan’an Basin, South China Sea

In this study, high-resolution seismic profiles and well data provided a good opportunity for better understanding the reefs and carbonate platforms in the Wan’an Basin, southwest of the South China Sea, and also provided valuable information for the oil–gas exploration in the reef reservoirs. Four evolutional phases, including the initial phase, the prosperous phase, the recession phase and the submerged phase, of the reefs and carbonate platforms are proposed according to our data. In the Early Miocene, a few small, isolated carbonate platforms initiated in the center of the basin. In the Middle Miocene, they flourished and mainly formed around the Northern Uplift and Central Uplift, with two belts of carbonate platforms in the western area and eastern area that were mainly platform-edge reefs, massive reefs and a few point reefs. In the Late Miocene, the carbonate platforms began to retreat towards the high topographic position because of the rising of sea level. Meanwhile, the numbers and styles of reefs increased to include platform-edge reefs, massive reefs, atoll reefs and point reefs. Since the Pliocene, most of the carbonate platforms have been covered by detrital materials from terrestrial sources. Crustal tectonic activity provides favorable topography for reef growth and the distribution of platforms, and eustasy controlled the vertical growth and lateral migration of reefs. Since the Late Miocene, the rapidly crustal tectonic subsidence and the rising of relative sea level may lead to the drowning of the carbonate platform.

Multiscale tip asymptotics for a deflating hydraulic fracture with leak-off

This paper deals with the construction of the tip asymptotes for a hydraulic fracture deflating in a permeable elastic medium. Specifically, the paper describes the changing nature of the asymptotic fields during the arrest and recession phases following propagation of the fracture after fluid injection has ended. It shows that as the fracture deflates in the arrest phase, the region of dominance of the linear elastic fracture mechanics tip asymptote $w\sim x^{1/2}$ of the fracture aperture $w$ with distance $x$ from the front shrinks to the benefit of an intermediate asymptote $w\sim x^{3/4}$ . Hence only the velocity-independent $3/4$ asymptote is left at the arrest–recession transition. Furthermore, with increasing receding velocity of the front, a linear asymptote $w\sim x$ develops progressively at the fracture tip, with $w\sim x^{3/4}$ again becoming an intermediate asymptote. These universal multiscale asymptotes for the arrest and recession phases are key to determining, in combination with a computational algorithm that can simulate the evolution of a finite fracture, the decaying stress intensity factor during arrest, the time at which the fracture transitions from arrest to recession, and the negative front velocity during recession.

Groundwater metabolome responds to recharge in fractured sedimentary strata

Understanding the sources, structure and fate of dissolved organic matter (DOM) in groundwater is paramount for the protection and sustainable use of this vital resource. On its passage through the Critical Zone, DOM is subject to biogeochemical conversions. Therefore, it carries valuable cross-habitat information for monitoring and predicting the stability of groundwater ecosystem services and assessing these ecosystems’ response to fluctuations caused by external impacts such as climatic extremes. Challenges arise from insufficient knowledge on groundwater metabolite composition and dynamics due to a lack of consistent analytical approaches for long-term monitoring. Our study establishes groundwater metabolomics to decipher the complex biogeochemical transport and conversion of DOM. We explore fractured sedimentary bedrock along a hillslope recharge area by a 5-year untargeted metabolomics monitoring of oxic perched and anoxic phreatic groundwater. A summer with extremely high temperatures and low precipitation was included in the monitoring. Water was accessed by a monitoring well-transect and regularly collected for liquid chromatography-mass spectrometry (LC-MS) investigation. Dimension reduction of the resulting complex data set by principal component analysis revealed that metabolome dissimilarities between distant wells coincide with transient cross-stratal flow indicated by groundwater levels. Time series of the groundwater metabolome data provides detailed insights into subsurface responses to recharge dynamics. We demonstrate that dissimilarity variability between groundwater bodies with contrasting aquifer properties coincides with recharge dynamics. This includes groundwater high- and lowstands as well as recharge and recession phases. Our monitoring approach allows to survey groundwater ecosystems even under extreme conditions. Notably, the metabolome was highly variable lacking seasonal patterns and did not segregate by geographical location of sampling wells, thus ruling out vegetation or (agricultural) land use as a primary driving factor. Patterns that emerge from metabolomics monitoring give insight into subsurface ecosystem functioning and water quality evolution, essential for sustainable groundwater use and climate change-adapted management.

The arrest and recession dynamics of a deflating hydraulic fracture in a permeable elastic medium in a state of plane strain

We investigate the deflation dynamics of a fluid-driven fracture in a permeable elastic medium in a state of plane strain after fluid injection has ceased. Depending on the leak-off characteristics of the porous medium and the volume of injected fluid retained in the fracture at the time of shut-in, the fracture may start to recede almost immediately or continue to propagate till it arrests when the stress intensity factor drops below the fracture toughness. While occupying the arrest footprint, the fracture continues to deflate while the stress intensity factor decreases due to fluid loss to the porous medium. When the stress intensity factor drops to zero, the fracture starts the process of recession, which continues until it finally collapses. To establish a rigorous numerical scheme to explore the deflation dynamics of plane strain hydraulic fractures, we use recently established vertex and multiscale tip asymptotes for arrested and receding hydraulic fractures (Peirce and Detournay, 2022), including the r-vertex linear tip aperture asymptote wˆ∼xˆ for a receding hydraulic fracture and the stationary g-vertex asymptote wˆ∼xˆ3/4. Numerical experiments demonstrate that the multiscale asymptotes are required in order to achieve solutions that remain smooth through the arrest–recession transition point. In contrast, numerical solutions, obtained by only using vertex solutions to model the arrest and recession, exhibit jump discontinuities through this transition point. However, once the transients from these jump discontinuities have decayed the numerical schemes that use vertex and multiscale asymptotes yield almost identical solutions. A scaling analysis shows the existence of asymptotic power law behaviour for various quantities, such as the arrest time, in terms of two new dimensionless parameters. Finally, numerical solutions explore the dependence on the two dimensionless parameters of the arrest time, the duration of the arrest period, and the duration of the recession phase and confirm their asymptotic power law behaviours.

Dynamics of traumatism, mortality and lethality in damage by sharp objects in Leningrad – St. Petersburg in 1978–2020

Purpose of the study. Тo analyze the dynamics of traumatism, mortality and lethality from injuries with sharp objects in Leningrad — St. Petersburg, taking into account economic processes, regulation of the alcoholic beverages market and the capabilities of the ambulance service.Materials and methods. The work is based on archival material of the St. Petersburg State Budgetary Healthcare Institution “Bureau of Forensic Medicine” for 1978–2020.Results and discussion. For 43 years in the evolution of traumatism, mortality and lethality from injuries from sharp objects, periods have been traced: pre-crisis (1978–1990), crisis with phases of rise (1991–1993), turning-point (1994) and recession (1995–2004), exit from the crisis or the beginning of stabilization (2005–2011), post-crisis stabilization (2012–2020). The dynamics of statisti cal indicators was influenced by the anti-alcohol campaign (1985), the destabilization of the alcohol market and the elimination of the state monopoly on alcohol (1990–1992), the restoration of state regulation of the turnover of alcoholic products (1993), and the restriction of alcohol consumption (since 1995), financial and economic crises (1991, 1998, 2008–2009), improvement of the emergency medical service (2004, 2013).Conclusions. Economic crises were accompanied by negative dynamics of traumatism. The destabilization of the alcoholic beverages market was accompanied by an increase in traumatism and mortality. The well-organized work of the ambulance service ensures an acceptable level of lethality and mortality.

Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?

This study investigates the connection/disconnection between the stock market and macroeconomic fundamentals in the United States from January 1960 to December 2021. Using a recent time-varying Granger causality framework, tests revealed asymmetric bidirectionnal causality. The lead-lag relationships between stock prices and key macroeconomic indicators are more prevalent during recession phases. However, the significance and intensity of the causal relationships during the Covid crisis varied greatly; which could indicate a possible disconnection.

The arrest and recession dynamics of a deflating radial hydraulic fracture in a permeable elastic medium

In this paper we describe the post injection deflation dynamics of a radially symmetric hydraulic fracture in a permeable elastic medium. Depending on the parameters of the problem, the fracture may arrest almost immediately after injection has ceased, or continue to propagate despite the fluid loss to the porous medium. After arrest the fracture continues to deflate while the stress intensity factor decreases to zero, after which it recedes until the fracture finally collapses. In order to establish rigorous numerical solutions to explore this deflation dynamics, we make use of recent research (Peirce and Detournay, 2021) that derived vertex asymptotes for the arrest and recession phases of the deflation process as well as multiscale asymptotic solutions that connect these vertex asymptotes: during arrest, through the arrest–recession transition, and during recession. If only vertex asymptotes are used to capture the arrest and recession, the solution exhibits jump discontinuities through this arrest–recession transition point. We describe how the multiscale asymptotes can be used to obtain a smooth solution valid through the arrest–recession transition. Significantly, after the arrest–recession transition, the jump-induced transients decay and the solutions using vertex asymptotes converge to those that use multiscale asymptotes. Thus unless it is important to obtain a smooth solution through the arrest–recession transition, a practical, and more efficient, approach would be to use an algorithm based solely on vertex asymptotes. We also provide numerical confirmation of the emergence, beyond the arrest–recession transition time, of the dominant balance used in the asymptotic analysis to establish the linear recession asymptote wˆ∼rˆ. We present a novel scaling analysis to establish the characteristic power laws for the arrest time, arrest radius, arrest aperture, and the deflation time, in terms of two new dimensionless parameters, which make it possible to unify the power laws between the zero and finite toughness cases. These power laws show close agreement with those obtained by regression of the numerical results over a range of the dimensionless parameters. Numerical solutions are provided to illustrate the solution landscape in parameter space and the effect that each of the dimensionless parameters has on: the duration of the period of propagation after injection has ceased, the duration of the arrest period, and the time from the initiation of recession to collapse.

The Effect of Corporate Social Responsibility Performance on Financial Distress over the Life Cycle Using the Directional Distance Function

Rising inflation in recent years has caused financial distress and many problems for companies. Most of these problems are affected by life cycle stages. One way out of these problems is to increase corporate social responsibility (CSR) performance. Therefore, our aim in this study is to investigate the effect of CSR performance on financial distress over the life cycle of the company for a period of 10 years. Data collection was done through the website of the Tehran Stock Exchange and related software for a sample of 112 companies during the period 2009 to 2019. The mathematical method (directional distance function) is used to evaluate the CSR performance, and the models of Berger et al., Almida, Campello, and Altman are used to measure financial distress. The research hypotheses are tested using panel data and fixed effects by multivariate regression statistical method. The results show that CSR performance alone does not affect financial distress. The combination of CSR and life cycle in the growth and maturity phases has a significant and negative effect on financial distress. The CSR performance and life cycle together reduce financial distress. The combination of CSR performance and life cycle in the recession phase has a positive and significant effect on financial distress and in the fall phase, does not affect it. Given that companies compete more in the phase of growth and maturity than other phases of the life cycle, they also pay more attention to CSR. Therefore, according to these results, it can be concluded that the life cycle of the company and the CSR performance together, reduce financial distress.

Release and Demand of Public Health Information in Social Media During the Outbreak of COVID-19 in China.

Information release is a key to the macro-economy during the outbreak of the Coronavirus Diosease-2019 (COVID-19). To explore the relationship between information supply by the government and public information demand in the pandemic, this study collected over 4,000 posts published on the most popular social media platform, i.e., WeChat. Many approaches, such as text mining, are employed to explore the information at different stages during the pandemic. According to the results, the government attached great importance to the information related to the pandemic. The main topics of information released by the government included the latest situation of the pandemic, announcements by the State Council, and prevention policies for COVID-19. Information mismatch between the public and Chinese governments contributed to the economic depression caused by the pandemic. Specifically, the topics of “the latest situation” and “popular scientific knowledge regarding the pandemic” have gained the most attention of the public. The information demand of the public has changed from the pandemic itself to the recovery of social life and industrial activities after the authority announced the control of the pandemic. However, during the recession phase, the information demand has shifted to asymptomatic infections and global pandemic trends. By contrast, some of the main topics provided by the government, such as “How beautiful you are,” were excessive because the public demand is insufficient. Therefore, severe mismatches existed between information release of the government and public information demand during the pandemic, which impeded the recovery of the economy. The results in this study provide strategical suggestions of information release and opinion guidance for the authorities.

Understanding the impacts induced by cut-off thresholds and likelihood measures on confidence interval when applying GLUE approach

Generalized likelihood uncertainty estimate (GLUE) approach is affected heavily by the choice of cut-off threshold (Tr) and likelihood measure. This work presents a research on investigating potential mechanisms behind the impacts of Tr and likelihood measure on 95% confidence interval estimated by GLUE (95 CI). Several typical likelihood measures are classified into five groups according to error models. Theoretical analysis reveals strict mathematical relationships between likelihood measures based on a same error model. Besides, a multiple attribute decision making (MADM) framework is proposed to assess overall quality of various geometrical features for 95 CI by integrating a range of interval indicators into a comprehensive score. Case studies indicate that (1) As Tr increases, 95 CI widens in low-level flow section, moves upward in recession phase of medium-level flow section and narrows in high-level flow section. The variations of interval indicators with Tr can be attributed to trade-off mechanism amongst the variations of geometrical features caused by widening, moving and narrowing trends of 95 CIs. (2) Much higher similarity in interval indicators and 95 CIs occurs for likelihood measures of a same group than those of different groups. (3) Formula of likelihood measure controls individuality of 95 CIs, error model of likelihood measure controls commonality of 95 CIs, and Tr acts as a regulator between individuality and commonality. (4) 95 CI shows similar responses to the choice of Tr and likelihood measure regardless of time span and climate variability. To summarize, this work offers further understanding and guidance in chose of Tr and likelihood measure for GLUE applications.

Spatial dependence in regional business cycles: evidence from Mexican states

This study investigates how regional business cycles are spatially dependent in Mexico by developing a Markov switching model with a spatial autoregressive process. The Markov switching model with two regimes distinguishes business cycles between expansion and recession phases (i.e., high- and low-growth rate regimes). The objective of this study is twofold. First, this study aims to identify which states transitioned from expansion to recession during the Great Recession in 2008–2009. Second, it numerically examines the extent to which states that experienced this transition caused a deterioration in neighboring states’ economies. Employing Bayesian inference for the Markov switching model with quarterly data of state economic activity during the period 2003:Q1–2015:Q4, this study finds that Mexican states with higher manufacturing sector shares tended to be in recession during the Great Recession. Although some states experienced economic downturns in this period, they were not in a recessionary regime. This study also finds that business cycles across states were spatially dependent during the Great Recession. The numerical simulations of spatial spillover effects suggest that states that regime-switched from expansion to recession during the Great Recession caused a reduction in the quarterly growth rate of their neighboring economies by an average of 0.39 percentage points.