Macro Factors Research Articles

Magnetic Macro Drivers of Trade Openness: A Study of BRICS Economies

The major goal of this study endeavour is to thoroughly evaluate the impact of macro factors on trade openness (TOP). The study was conducted through the examination of numerous trade conceptions, with a specifically emphasis on examining these patterns within the economies of the BRICS nations (Russia, India, China and South Africa) from 1995 to 2020. Stepwise regression for selecting models, Pedroni, Johnson, Granger causality and advance panel regression are some of the techniques used including FMOLS, Panel OLS and FEM. The study’s outcomes reveal the presence of both long-term and short-term associations between TOP and (a) total investment, (b) human capital, (c) trade reserves, (d) trade balance and (e) exchange rate. The study authors found both one-way and two-way causal association between TOP and these five factors. Additionally, trade balance emerges as the most significant factor impacting TOP. Notably, the exchange rate does not exhibit significant economic importance. JEL Classification: F14, F15, F17

Migration, Urbanism and Health: Moving Toward Systems-Informed Policy and Practice

Migration and displacement are pivotal determinants of urban health, influencing both direct and indirect health outcomes. Migrants may face unique health risks, often exacerbated by economic, social, and environmental factors encountered during transit or upon resettlement. As migration patterns shift due to geopolitical, climatic, and economic pressures, they reshape the global and urban policy landscapes in unpredictable ways, presenting challenges that will continue to evolve in the coming decades. Current legal frameworks, in many cases, do not adequately account for migrant populations, hindering policy responses and complicating the protection of migrant health. Therefore, effective urban health interventions must be inclusive of migrant populations and expand beyond healthcare services. A systems-thinking approach that recognizes the broader determinants of health—including housing, employment, social services, and urban infrastructure—is essential to address the intersecting challenges migrants face. Despite these challenges, migration remains crucial to the functioning of urban environments. Migrant workers consistently contribute to the healthy operation of cities, underpinning key infrastructure and services. However, to optimize policy responses and improve urban health outcomes, more robust data and evidence on the health risks and outcomes of migrants, as well as the structural drivers of migration, are needed. Moreover, macro factors such as climate change, future pandemics, and geopolitical shifts are likely to influence both migration dynamics and migrant health. To anticipate and respond to these evolving challenges, a systems-informed and holistic vision of urban health is required—one that integrates migration into the broader urban policy and planning frameworks to foster healthier, more resilient cities.

A novel spatio-temporal prediction model of epidemic spread integrating cellular automata with agent-based modeling

Since 2019, major infectious disease outbreaks have placed tremendous pressure on global public health systems, triggering extensive research on the predictive modeling of infectious diseases. Cellular Automaton (CA) is primarily used in the spatial prediction of infectious diseases to establish a model to for simulating the interaction between different regions and the infection risk to simulate the transmission process of the disease and predict its development trend. However, CA models are governed by initial fixed rules and local interactions, and often fail to capture the complex dynamics of epidemic transmission, which are influenced by factors such as public behavior and government intervention. In view of these limitations, we propose a factorial simulation model for the spatial spread of epidemics, the CA-ABM, which divides agents into three categories–public, government, and hospital agents–to comprehensively express the macro factors that affect the development of epidemics. Agent-Based Modeling (ABM) influences the transition rules of the CA through agent choices, constraints and supporting behaviors. Focusing on the COVID-19 pandemic in mainland China from February 6 to March 20, 2020, we simulate its spread. The results showed an average improvement of 8.4 % in prediction accuracy, with few errors, RMSE under 200, and R2 values over 0.9 in most provinces, demonstrating strong macro-scale stability. This approach helps regions to understand influencing factors and enables targeted infection risk assessment and prevention. In addition, scenario analysis based on CA-ABM model changes epidemic decision-making from “prediction-response” to “scenario-response” and provides theoretical reference for future epidemic management.

Death from COVID-19 in contexts of social deprivation in Mexico.

Poverty is one of the macro factors that has been little studied in terms of its effect on death from COVID-19 since most studies have focused only on investigating whether the pandemic increased poverty or not. With that on mind, the present study aims to analyze how the social deprivations that comprise the measurement of municipal poverty in interaction with health comorbidities and sociodemographic characteristics, increased the probability of death from COVID-19. The study is cross-sectional and covers daily reports on the conditions of COVID-19 in the Mexican population for almost 2 years. Using data from the National Epidemiological Surveillance System and the National Council for Evaluation of the Social Development Policy (N = 5,387,981), we employ a Generalized Linear Mixed Model (GLMM), specifically a binomial generalized linear mixed model. The findings indicate that, besides comorbidities, sociodemographic traits, and clinical aspects, living in a municipality where one or more of the social deprivations exist increases the probability of death. Specifically, in those municipalities where there is deprivation in education, social security, and food, as well as deprivation due to access to health services and deprivation in household services, the probability of death was greater. Living in a municipality with one or more of the social deprivations that compose poverty generated a greater probability of death. Each one of them or together, shows that poverty is a substantial factor for a pandemic like COVID-19 to worsen contagion and death, becoming a circle from which it is difficult to escape.

The Impact of the Last Two Presidential Periods on the Performance of the Indonesia Stock Exchanges: An Approach of Arbitrage Pricing Theory

This study aims to examine the influence of economic and non-economic macro factors on the performance of the Indonesia Stock Exchange (IDX) and the differences in their effects on the last two presidential terms using the Arbitrage Pricing Theory (APT) approach. The macro factors studied are an aggregate of 41 indicators of stock market index returns, benchmark interest rates, exchange rates, economic stability indicators, commodity prices, and corruption perception index (CPI). For the process of aggregation and identification of macro factors, this study uses Principal Component Analysis (PCA). The population studied were publicly listed companies on the IDX since October 2004 (299 companies) with a sample size of 157 companies. The observation period is 205 months: 120 months of the presidency of Susilo Bambang Yudhoyono (SBY) and 85 months of the presidency of Joko Widodo (JKW). The research design used the explanatory study method. The research model was analyzed using panel data regression. The results identified seven macro factor aggregates from 41 indicators studied: global index, macro economy, world oil prices, China index, Arabia index, inflation, and competitive resources. There was a simultaneous effect of macro factors on stock performance during the presidency of SBY and JKW. Partially, stock returns during the SBY era were positively influenced by the global index, world oil prices, the China index, the Arabian index, and inflation and negatively influenced by the macroeconomy. Meanwhile, during the JKW period, returns were positively influenced by the global, China, and Arabia indexes and inflation.

Typology and Development of Value Chains in Science, Technology and Innovation Organizations: Efficiency of Operating Model

The structure and activities of science, technology and innovation organizations should be reviewed in planning for change in accordance with (a) a framework operating model, (b) principles of organizational structures and (c) value chains in order to identify (1) areas of inefficiency, (2) the existence and maturity of chain links as well as (3) gaps with best practice. The operating model of organizations, whose support, development and effectiveness are influenced by legislation, budget and external factors, includes many components, from management policy to culture. Changes in organizational charts together with renaming of departments sometimes look like promising reforms. However, in any case, values brought by organizations should be put on the agenda. Social effect of science, technology and innovation as a contribution to public good or a measure of the social good extend to groups in society or to the whole of society both directly and indirectly, for example, through other values and social mechanisms of influence. In this article, the following typology of values is used in the context of the innovation ecosystem and discussions on public good: internal, economic, social and humanitarian ones. The last three values are often generalized by the term “impact”. Internal values of science and technology express the essence of development that knowledge is built on knowledge, and thereby increase the level and readiness of organizations. We consider links in the value proposition chains produced by these organizations, from planning to legal support management. Current national macro factors that influence them are formulated. The contemporary generation of the innovation ecosystem in the Republic of Kazakhstan is characterized by a lack of a group of elements that determine national internal and external goals, ways to achieve them, as well as monitoring the results of activities and impact. This article aims to formulate and study the linking of management at the level of the principles of the organizational structure and the framework operating model to the values at the level of the introduced typology, which are created in a certain way by science, technology and innovation organizations. In terms of research and practical significance, this allows for a detailed review, identification of areas of inefficiency and gaps with best practice. And then, by formulating and implementing initiatives, this allows to increase their capabilities and effectiveness taking into account the ambiguity and delayed nature of results of scientific, technological and innovative activities, as well as specific external national and international factors that influence organizations. Comparing value chain links to the typology of values, we have identified a specific distribution of their influence of on the types of these values. In terms of academic and theoretical significance, this study also attempts to reveal contradictions between resulting and procedural values in science, technology and innovation organizations by examining the development of value chains and the context of public good.

Uncertainties of Temporary Protection: Forcibly Displaced People From Ukraine and Bosnia and Herzegovina

ABSTRACTThe experiences of displaced persons, currently particularly from Ukraine, are reflected in the concept of temporary protection as an immediate response to mass displacement. This article proposes a consideration of temporary protection from the perspective of ‘openness’, ‘in‐betweenness’ and the various forms of insecurities in people's lives in new societies and on their journeys. Refugees are connected in multi‐layered networks along their routes; forced migration goes in all directions; therefore, fluidity, situational dependency and macro factors determine its dynamics. The empirical data on Ukrainian refugees in Slovenia and the consideration of the situation of Bosnian refugees in the period of the Yugoslav wars show a complex interplay of structural and individual factors that determine the position of temporarily protected persons in larger transnational networks. The article also reflects on the relational question of international protection from the perspective of ‘deservedness’ and hierarchies among different migrant groups.

The impact of factors on environmental pollution in asean countries: The role of institutional quality

The impact of institutional quality on environmental pollution in ASEAN countries is analyzed in this study. The researcher collected 250 observations from the World Bank dataset using data from 1996 to 2020. The author applied principal component analysis (PCA) and autoregressive distributed lag (ARDL) techniques to estimate panel data. The evidence of this study suggests that institutional quality has a negative impact on environmental pollution in the short run and a positive impact in the long run. Other macro factors, such as economic growth, trade openness, financial development, FDI, and energy consumption, have varying degrees of impact on environmental pollution. To the best of the authors' knowledge, there is currently no research examining the impact of institutional quality on environmental pollution in ASEAN countries, with the institutional quality variable created from six indicators based on the WGI database by using the PCA technique.

Agency Penalties From Taking Parental Leave for Women in Men-Dominated Occupations: Archival and Experimental Evidence.

Organizations have started more progressively using and offering family benefits including parental leaves to address the issues of balancing work and family life. Although such leaves are fundamental for supporting, attracting, and retaining women, we examine whether such leaves may also inadvertently affect women's careers in occupations that overly value masculine traits, unless managed carefully. Drawing on the literature on gender stereotypes (micro factors) and occupation gender type (macro factors), we argue that longer (vs. shorter) parental leaves negatively affect women's work outcomes (i.e., annual income, salary recommendation, hireability, and leadership effectiveness) in men-dominated but not in women-dominated occupations because it lowers perceptions of women's agency. We find support for our hypotheses across three studies in the Australian context with an archival data set and two experiments. Our work shows that men-dominated organizational structures reinforce traditional gender stereotypes, whereas such reinforcement does not happen in women-dominated organizational structures. Our research equips leaders and organizations with insights into the unintended negative consequences of parental leave for women. This understanding serves as a crucial first step in developing strategies and programs to mitigate these effects, thereby supporting women in men-dominated occupations and fostering more inclusive and healthy workplaces.

Control of false information in social networks: A short review of communication mechanisms and management strategies

In the digital era, social networks serve as critical platforms for information dissemination but are also plagued by the spread of false information, which can undermine public trust and incite societal discord. This study examines the dynamics of false information dissemination on social networks, including its types, influential factors, and detection and management strategies. We explore various forms of false informationsuch as impersonation, misleading content, and AI-generated forgeriesand analyze the role of user interactions, network topology, and macro factors in the spread of misinformation. Detection methods are reviewed, highlighting advancements in technologies like deep learning, and management strategies are proposed, including user behavior regulation and dissemination path control. Challenges related to legal, ethical, and privacy issues are discussed, alongside the complexities of user behavior and future research directions. The findings underscore the need for comprehensive, adaptive approaches to safeguard the integrity of online information ecosystems.

A Financial Analysis and Valuation of Occidental Petroleum Corporation

Oil has always been an important political and strategic resource in a country. In recent times, the significant changes in the international situation and the mergers and acquisitions of American oil giants have intensified the changes in the oil industry, directly leading to fluctuations in American oil stock prices. Therefore, this article collects financial data from Occidental Petroleum Corporation in recent years and conducts comparative analysis to explore the development prospects of Occidental Petroleum Corporation and some changes in the petroleum industry. Research has found that Occidental Petroleum Corporation has good development prospects based on its own oil production capacity and environmentally friendly technology development, and its stock price may experience a significant increase. In addition, various macro factors such as the Russia Ukraine war and changes in the international situation may lead to a shock to the US oil industry and make a decrease in overall profits for it.

Competition policy and enterprise competitiveness: Catalyst or barrier?

As a seminal institutional innovation within the framework of Chinese-style modern competition theory, the question of whether the Fair Competition Review System (FCRS) can harness policy dividends and bolster enterprise competitiveness stands as a pivotal concern for accelerating the emergence of new productive forces and fostering a harmonious integration of an "effective government + efficient market." Leveraging data from China's listed manufacturing enterprises spanning the period from 2010 to 2020, this paper undertakes an empirical examination of the impact of competition policy frameworks on the competitiveness of manufacturing enterprises. The FCRS is treated as a quasi-natural experiment, and a difference-in-differences (DID) methodology is employed for analysis.The findings of this paper are as follows: (1) The implementation of the FCRS has been found to effectively augment the competitiveness of manufacturing enterprises by approximately 1.97 %, and this fundamental conclusion retains its validity after a battery of robustness tests; (2) The FCRS primarily influences enterprise competitiveness by lowering financing costs, enhancing technological innovation, and mitigating over-investment; (3) Heterogeneity analysis reveals that non-high-tech enterprises and those with lower financing constraints can attain more pronounced effects in promoting enterprise competitiveness through competition policies. Additionally, enterprise size and operational risks also exert an influence on the efficacy of competition policies in enhancing competitiveness; (4) Expanded analysis indicates that competition policies optimize the capital structure of enterprises through "debt reduction" and "capacity enhancement," thereby exploring the viability of analyzing the macro factors that impact enterprise "deleveraging" from the lens of competition policies. The research conclusions presented in this paper carry substantial guiding significance for the government in clarifying the preeminent role of market allocation of resources, promoting the establishment of a unified national market, and orchestrating a coherent fair competition system.

Unravelling The Nexus: Social Environment and Peer Influence in Drug Abuse in Lawas, Sarawak

The rising issue of drug abuse in Sarawak, demands urgent attention as the problem shows no signs of abating. The primary goal of this research is to investigate the most influential factor that contributes to the rise in drug abuse in Lawas and how it affects the selected individual social awareness. By delving into this dynamic, the study aims to enhance the comprehension of the issue and, consequently, develop more effective strategies to mitigate its consequences. The research employed qualitative methodology, with in-depth interviews as the primary data collection method. Six participants participated in the in-depth interviews and each referred to using pseudonyms. Participants 1 and 2 are presently enrolled in rehabilitation programs facilitated by the National Anti-Drug Agency (NADA/AADK) division in Limbang. Participants 3, 4, and 5 were selected from the families, relatives, and friends of former addicts. Participant 6 plays a pivotal role as an officer responsible for drug enforcement in Lawas. The study employed social learning theory to gain a comprehensive perspective on the subject matter. The data analysis revealed that the social environment functions as the macro factor, while susceptibility to peer influence serves as the micro factor in drug abuse cases in Lawas and there is a relationship between the factor and the selected individual social awareness. The findings from this research hold immense relevance for a wide spectrum of stakeholders, with a particular emphasis on community and societal development, in addressing the multifaceted challenges posed by drug abuse issues in Lawas, Sarawak.

Spatiotemporal Heterogeneity Analysis of Provincial Road Traffic Accidents and Its Influencing Factors in China

To objectively evaluate the road traffic safety levels across different provinces in China, this study investigated the spatiotemporal heterogeneity characteristics of macro factors influencing road traffic accidents. Panel data from 31 provinces in China from 2009 to 2021 were collected, and after data preprocessing, traffic accident data were selected as the dependent variables. Population size, economic level, motorization level, highway mileage, unemployment rate, and passenger volume were selected as explanatory variables. Based on the spatiotemporal non-stationarity testing of traffic accident data, three models, namely, ordinary least squares (OLS), geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR), were constructed for empirical research. The results showed that the spatiotemporal heterogeneity characterizing the macro factors of traffic accidents could not be ignored. In terms of impact effects, highway mileage, population size, motorization level and passenger volume had positive promoting effects on road traffic accidents, while economic level and unemployment rate mainly exhibited negative inhibitory effects. In terms of impact magnitude, highway mileage had the greatest impact on traffic accidents, followed by population size, motorization level, and passenger volume. Comparatively, the impact magnitude of economic level and unemployment rate was relatively small. The conclusions were aimed at contributing to the objective evaluation of road traffic safety levels in different provinces and providing a basis for the formulation of reasonable macro traffic safety planning and management decisions. The findings offer valuable insights that can be used to optimize regional traffic safety policies and strategies, thereby enhancing road safety.

Reimagining entrepreneurship by utilizing venture dynamics in sharing economy: Evaluating the symbiosis of macro and micro factors for sustainable capital flows in developing markets

AbstractVenture capital (VC) plays a vital role in fostering revolution and entrepreneurship in emerging economies. However, attracting VC investments remains a significant challenge for startups in these markets. This study investigates the macro and micro factors influencing VC attraction in the Bangladeshi startup ecosystem, employing a mixed‐methods approach. A systematic literature review was performed to recognize the key factors influencing VC attraction in emerging markets. Qualitative interviews with 20 stakeholders, including startup founders, investors, and policymakers, were undertaken to gain insights into the challenges and opportunities for VC attraction in Bangladesh. Quantitative analysis of secondary data on VC investments and startup characteristics was executed to examine the associations connecting the identified factors and VC investment amount. The findings reveal that government policies, human capital availability, and informal institutions are critical macro factors influencing VC attraction, while founder and team characteristics, business model and scalability, and traction and validation are key micro factors. The study contributes to the literature on VC in developing economies by providing a comprehensive examination of the interplay of institutional, human capital, cultural, and startup‐specific factors shaping VC investment decisions. The findings have important implications for policymakers, investors, and entrepreneurs seeking to foster a more vibrant and sustainable startup ecosystem in Bangladesh and beyond. The research underlines the need for a holistic approach to addressing the challenges and leveraging the opportunities for VC attraction in emerging markets.

Infrastructure Investment and Finance in the Global South: Private Participation and Its Determinants

While the public sector is traditionally the sole provider for much of infrastructure, the pendulum is shifting in light of the enormous investment gap. Across the Global South, public utilities and planning agencies are engaging with the private sector to help bridge the gap. What are the key patterns of private participation in infrastructure (PPI) across countries in the Global South? What macro factors underscore such private participation? These research questions motivate this paper, focusing on five infrastructure sectors across the Global South and its regions. Following a historical synthesis of the changing balance of public and private provision, the paper outlines recent patterns of PPI. Drawing from a World Bank database, a regression analysis includes key macro-level predictors for private sector financing, for both the number of projects and stock of investment. Key results point to the importance of market size and in turn the potential for risk diversification, as well as a set of governance factors underlining investor confidence and stable environment.

Overlooked carbon sinks in the house building industry and the influential factors

The study aims to establish a carbon sink measurement model for the house building industry and analyze the time-varying characteristics of influential factors. China's house building industry exhibited an increasing trend in carbon sink, from 0.336 billion tons in 2000 to 234.1 million tons in 2020. This study defines the carbon sink coefficient of the house building industry to understand its carbon sink capacity. From 2000 to 2020, the average carbon dioxide absorption per square meter of floor space annually, throughout its life cycle, is 2.09 kg. Factors influencing the carbon sink were analyzed using Logarithmic Mean Divisia Index (LMDI) model. The most influential factor was resource consumption intensity, followed by value dependence level and output scale effect. Employing Time-Varying Parameter Vector Autoregression (TVP-VAR), this study examines the impact of macro factors on carbon sinks at various lead times and specific points. Resource consumption intensity exhibits significant time-varying effects. Value dependence level negatively influences, primarily in the medium and long terms, while the output scale effect consistently shows a positive influence, mainly in the long term. Scenario forecasting suggests that by 2035, under low-carbon transition scenarios, carbon sinks could increase by 8.28% and 17.26% compared to baseline and high-carbon crude scenarios, respectively. To foster this growth, prolonging the service life of houses, enhancing construction site management and waste treatment, and employing higher value-added production factors are recommended.

Factors about the Corporate Bond Return

Recently, there are more and more literatures on the return factors of corporate bonds. We would like to provide a review of the latest factors affecting corporate bond returns. First, we summarized the classic models for studying corporate bond returns, such as CAPM Model, Merton Model and Fama-French Model. In this paper, the factors that affect the return of corporate bonds can be classified into micro and macro factors, and we collate the literature we have collected from these two perspectives.

Marriage and Divorce: A Qualitative Study from the Perspective of Iranian Academic Experts, Counselors, and Clients

ABSTRACT Over the recent few years, divorce rates have increased steadily, and marriage rates have decreased in Iran, which highlights the necessity to study. Obviously, the unidimensional study is insufficient due to the complex nature of the issue. Therefore, the qualitative study was conducted through the grounded theory approach and a purposeful and theoretical sampling method and data collection through triangulation, including semi-structured interviews with academic experts, counselors, and young adult clients. The data were analyzed in a cyclical process using open, axial, and selective coding. Macro factors are not only known as the causes of marriage reduction and divorce increase; they also play a role as a double pressure of marital conflicts and some micro factors such as addiction and violence. Accordingly, in addition to considering the micro and macro factors, necessary to pay attention to their impacts and influence on each other systemically.

Controlling the money supply from macroeconomics perspective: Saving interest and exchange rate

<p>The M2 money supply over the last five years has tended to increase by 10-12%, which is allegedly due to macro factors, namely, low savings interest and increasing exchange rate requirements, causing rising inflation rates. This research aims to determine the influence of savings interest and the exchange rate on the money supply in Indonesia for the 2004-2023 period. The analysis technique used in this research is linear regression with annual time series data of 20 observation units. This simultaneous model has never been studied by previous researchers. The results of this research analysis provide information that every change in savings interest negatively affects the M2 Money supply by 78.60% and a significant, positive effect between the Exchange Rate and Money in circulation by 78.40%. Meanwhile, simultaneous changes in savings interest and exchange rates have a significant effect on changes in money supply in Indonesia and the influence is substantial at 91.20%. Therefore, the conclusion of this research is, that partially and simultaneously the proposed model exhibits a significant influence between savings interest and the exchange rate on the amount of money circulating in Indonesia. Therefore, it is crucial to pay attention to the current macroeconomic conditions concerning these two factors, especially the stability of the exchange rate, to ensure that it does not increase the money supply and inflation which may reduce people’s purchasing power in Indonesia.</p>