JOURNAL OF ECONOMIC STUDIES最新文献

Purpose

The objective of this study is to examine the various factors that exert an influence on the green economy. This study also investigates the impact of foreign direct investment (FDI) on the Malaysian economy, specifically focusing on its position as a mediator. This research also examines the correlation between FDI and its influence on the contemporary green economy.

Design/methodology/approach

The authors employed quantitative methodologies and a self-administered survey to evaluate data and derive a definitive conclusion. The result was constructed using SPSS and SEM-PLS as the analytical software.

Findings

The study reveals that technological advancement, investment country and government policy significantly and positively affect the green economy, catalyse SDG goals and restructure the economy in better shape.

Originality/value

The current empirical research bridges the research gap in the context of technology advancement in government policy from emerging economies by exploring important factors, proposing their impact on the performance of the green economy, and empirically testing those hypothesized relationships. This study deciphers that FDI influences the green economy, where the investment country plays a significant role. Also, for a graphical presentation of this abstract, see the online appendix.

Purpose

Our purpose is the examination of the effects of fiscal policy on private lending for the Eurozone countries. The emphasis is on the identification of the time path of government spending and bank lending.

Design/methodology/approach

Fiscal policy is a main factor of macroeconomic stability for the euro area economy. This paper, investigates the impact of government spending on bank lending. For this reason, we present a dynamic theoretical model with a perfectly competitive banking sector, estimated using panel cointegration for the Eurozone countries from 2000Q1 to 2022Q2.

Findings

Our findings highlight that, in the long run, consistent management of government spending can have a beneficial multiplicative impact on bank lending for housing and business reasons. This finding is stronger in magnitude for business versus housing lending. The high level of homogeneity of our results across Eurozone countries has positive implications for a common fiscal policy in the future. Finally, authorities should know that policy adjustments are quicker in housing lending when compared to business lending.

Originality/value

In this paper, we contribute to the existing literature, concentrating on the investigation of any existence of long-run and short-run relationships between government spending and bank lending. Additionally, our analysis allows one to investigate the contribution of each Eurozone member state in the short-run and long-run model’s dynamics, providing significant outcomes for the implementation of economic policy and the need for fiscal discipline in the Eurozone.

Purpose

This study investigates the correlation between economic development and scientific knowledge production indicators in the BRICS countries from 2000 to 2020, highlighting the importance of human resources, natural resources, and innovation. Addressing a gap in the existing literature, this study aims to contribute significantly to understanding this relationship.

Design/methodology/approach

Employing a descriptive statistical approach, this study utilizes GDP and per capita income as economic indicators and scientific data from WoS and SCOPUS databases, focusing on scientific document production and citations per document.

Findings

The analysis reveals a strong correlation between economic development and scientific performance within the BRICS nations during the specified period. It emphasizes the interdependence of economic progress and scientific prowess, underscoring that they cannot be considered independently.

Research limitations/implications

However, limitations exist, notably the reliance on specific databases that might not cover the entire scientific output and the inability to capture all factors influencing economic and scientific development.

Originality/value

Understanding this interdependence has crucial originality. Policymakers and stakeholders in BRICS countries can leverage these insights to prioritize investments in human capital development and scientific research. This approach can foster sustainable economic growth by reducing reliance on natural resources.

Purpose

This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

Design/methodology/approach

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

Findings

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

Originality/value

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

Purpose

The main aim of this study is to investigate the role of fathers and mothers in the intergenerational educational persistence for sons and daughters under two dimensions that characterize the clusters of countries: redistributive policy and governance.

Design/methodology/approach

Data from the Global Database of Intergenerational Mobility (GDIM), hierarchical cluster analysis on principal components and panel regression are used in this study to estimate intergenerational educational correlation and to investigate its determinants related to the parents’ and descendants’ education variables in 93 countries grouped in four clusters. The empirical analysis is differentiated by gender combinations of parents and descendants.

Findings

In the clusters of countries characterized by high inequalities and poor governance, our findings show that the role of the fathers is stronger than that of the mothers in educational transmission; fathers and mothers are more influential for the daughters rather than for the sons; parental educational privilege is the main driver of intergenerational educational persistence; there is an inverse U-curve in the association between educational inequality of the parents and educational correlation for the sons. Differently, in the countries characterized by high income, low redistributive conflict and better governance, the role of the mothers is stronger and education mobility for the daughters is higher than that for the sons.

Social implications

The authors’ results remark on the importance of social welfare policies aimed to expand a meritocratic public education system including schooling transfers for lower social class students and narrowing the gender gap in educational mobility between daughters and sons. Social welfare policies should also be oriented to spread high quality child care systems that help to foster greater women equality in the labor market, because the strength of educational persistence depends on the position of the mother in the economic hierarchy.

Originality/value

The distinctiveness of the paper can be found in the fact that this study investigates the parental role differentiating by gender and coupling hierarchical cluster analysis on principal components with panel regression models. This allows us to have a sample of 93 countries aggregated in four groups defined in two dimensions: redistributive policy and governance. Amongst the determinants of educational transmission, we consider not only education’s years of the parents but also other determinants, such as educational inequality and privilege of the parents. We also identify the effects of investment in human capital and educational inequalities for the descendants on education mobility.

Purpose

The purpose of this study is to investigate whether and how inter-firm cooperation and firm age moderate the relationship between family ownership and productivity.

Design/methodology/approach

We first estimate the total factor productivity (TFP) of a large sample of Italian firms observed over the period 2010–2018 and then apply a Poisson random effects model.

Findings

TFP is, on average, higher for non-family firms (non-FFs) than for FF. Furthermore, inter-organizational cooperation and firm age mitigate the negative effect of family ownership. In detail, it is found that belonging to a network acts as a moderator in different ways according to firm age. Indeed, young FFs underperform non-FF peers, although the TFP gap decreases with age. In contrast, the benefits of a formal network are high for older FFs, suggesting that an age-related learning process is at work.

Practical implications

The study provides evidence that FFs can outperform non-FFs when they move away from Socio-Emotional Wealth-centered reference points and exploit knowledge flows arising from high levels of social capital. In the case of mature FFs, networking is a driver of TFP, allowing them to acquire external resources. Since FFs often do not have sufficient in-house knowledge and resources, they must be aware of the value of business cooperation. While preserving the familiar identity of small companies, networks grant FFs the competitive and scale advantages of being large.

Originality/value

Despite the wide but ambiguous body of research on the performance gap between FFs and non-FFs, little is known about the role of FFs’ heterogeneity. This study has proven successful in detecting age as a factor in heterogeneity, specifically to explain the network effect on the link between ownership and TFP. Based on a representative sample, the study provides a solid framework for FFs, policymakers and academic research on family-owned companies.

Purpose

Previous literature has investigated the connection amongst remittances, political stability and unemployment in remittance-receiving economies separately. Besides, they did not cover the Middle East and North African (MENA) region.

Design/methodology/approach

To this end, this research uses the pooled mean group (PMG) method.

Findings

The findings suggest that the influence of remittances on lowering unemployment accelerates in recipient economies with high levels of political stability.

Practical implications

Policymakers in MENA countries should vigorously pursue political stability, which plays a crucial role in boosting the influence of inward remittances on unemployment alleviation. This is accomplished by establishing solid institutions that contribute to ensuring fair politics, increasing citizens' trust in the government, enhancing the rule of law and protecting investors and prioritizing policies and programs that promote political stability.

Originality/value

This paper, therefore, aspires to empirically examine the impacts of inward remittances on unemployment via the moderating role of political stability in thirteen MENA-receiving countries from 1996 to 2020.

Purpose

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

Design/methodology/approach

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

Findings

We show that our extended model yields a Pareto efficient outcome.

Practical implications

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Social implications

Long-term modelling and sustainability can be modelled in our setting.

Originality/value

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

Purpose

The COVID-19 pandemic has induced tourism destinations to reconsider organisational aspects related to health safety measures, as perceptions of health safety may have become particularly important for tourists. Using data from summer 2020, the period immediately after the outbreak of the pandemic, we investigate the factors that affected tourist perceptions of health safety.

Design/methodology/approach

Data come from a survey of tourist-card holders in Trentino, an Italian mountain destination. Through regressions, we assess the conditional correlation between health safety measure evaluations following a holiday and a set of covariates related to the features of the tourist area and the tourists themselves, as well as COVID-19 incidence in their province of residence in the months before the holiday.

Findings

Tourist-related features seem not to impact on perceived health safety, whereas some destination- and accommodation-related elements do. In particular, the number of tourist beds affects it negatively, and staying at a hotel does it in a positive way. COVID-19 incidence in one’s home province does not affect perceptions of health safety measures, which suggests a possible sample selection effect and/or the need for more fine-grained data.

Originality/value

This paper is one of the few on the immediate effects of the COVID-19 pandemic using data from a large sample of actual tourists. Our findings point out the importance of the intrinsic features of some places and accommodation in influencing perceptions of safety. We discuss implications for scholars and destination managers.