Social Science Research Network

This study sought to investigate how key stakeholders in education, namely, parents, teachers, school, principals and Department of Education officers view the role of the South African Democratic Teachers Union in education to be. Generally Black teacher trade unions in South Africa has a very broad background, ranging from fiercely fighting the apartheid regime to defending labour rights of teachers. This role became important for SADTU because the laws that governed South Africa before 1994, suppressed Black people, had their educational and political rights violated, including their labour rights. Therefore, SADTU had a dual role to fulfil. The formation of SADTU led to a division within teacher unions that existed then, because of the divergent ideologies that SADTU and they held. Some of them believed in teacher professionalism, while others subscribed to better working conditions and teacher professional development. On the other hand, SADTU kept the militant approach and political affiliation. These two characteristics of SADTU are causing a great concern among stakeholders. This has led to SADTU, through media reports being blamed for the collapse of education especially in Black schools located in townships and rural areas. An interest to investigate this topic was triggered by the apparent gap that seems to exist between SADTU's official documents such as its constitution and Vision 2030. These documents which are seemingly founded on the country's constitution, paint the union in a good light, yet, in actuality, the state of education is collapsing in schools. As a teacher myself and a member of SADTU, I have observed unprofessional behaviour from some colleagues who are also SADTU-affiliates, and this has made me question the level of professionalism and the promotion of Culture of Learning and Teaching especially in our Black township schools. I have also seen how the principal seems to be having challenges, with most SADTU members especially the leaders. I have also observed the animosity that exist between some SGB members and union leaders in the school. Therefore, I sought to find out from the mentioned stakeholders what they viewed to be the role of SADTU based on their experiences. This study adopted a qualitative approach, and is located within the interpretivist paradigm. I adopted a multi-site case study research design. The study was conducted using individual face-to-face interviews, one group interview and document analysis. The findings suggest that SADTU is contributing to the collapse of education especially in township schools where there are high SADTU-affiliated teachers. This is caused by SADTU's militant approach, which involves violent protests and strikes, prolonged strikes, depriving learners from accessing education, unprofessional behaviour such as involvement in violent teacher strikes and prioritising union activities over teaching, which contributes to the death of the Culture of Learning and Teaching. The study recommends that SADTU begins to listen to the views and opinion of stakeholders, and to be consultative in approach, instead of being partisan and self-centred. Most importantly, it should invest in its members' professional development as it is happening in Europe. Lastly break away from the Tripartite Alliance, because SADTU seems to be distracted by politics from achieving the objective and visions set in its constitution and Vision 2030. vi

BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The papers are on subjects of topical interest and are technical in character. The views expressed in them are those of their authors and not necessarily the views of the BIS.

This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, we first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. We then construct tests that are in the spirit of and . In order to establish the asymptotic properties of our tests, we also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of . In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared.

In economics, common factors are often assumed to underlie the co-movements of a set of macroeconomic variables. For this reason, many authors have used estimated factors in the construction of prediction models. In this paper, we begin by surveying the extant literature on diffusion indexes. We then outline a number of approaches to the selection of factor proxies (observed variables that proxy unobserved estimated factors) using the statistics developed in Bai and Ng (2006a,b). Our approach to factor proxy selection is examined via a small Monte Carlo experiment, where evidence supporting our proposed methodology is presented, and via a large set of prediction experiments using the panel dataset of . One of our main empirical findings is that our "smoothed" approaches to factor proxy selection appear to yield predictions that are often superior not only to a benchmark factor model, but also to simple linear time series models which are generally difficult to beat in forecasting competitions. In some sense, by using our approach to predictive factor proxy selection, one is able to open up the "black box" often associated with factor analysis, and to identify actual variables that can serve as primitive building blocks for (prediction) models of a host of macroeconomic variables, and that can also serve are policy instruments, for example. Our findings suggest that important observable variables include: various S&P500 variables, including stock price indices and dividend series; a 1-year Treasury bond rate; various housing activity variables; industrial production; and exchange rates.

We review and construct consistent in-sample specification and out-of-sample model selection tests on conditional distributions and predictive densities associated with continuous multifactor (possibly with jumps) and (non)linear discrete models of the short term interest rate. The results of our empirical analysis are used to carry out a "horserace" comparing discrete and continuous models across multiple sample periods, forecast horizons, and evaluation intervals. Our evaluation involves comparing models during two distinct historical periods, as well as across our entire weekly sample of Eurodollar deposit rates from 1982-2008. Interestingly, when our entire sample of data is used to estimate competing models, the "best" performer in terms of distributional "fit" as well as predictive density accuracy, both in-sample and out-of-sample, is the three factor Chen (CHEN: 1996) model examined by Andersen, . Just as interestingly, a logistic type discrete smooth transition autoregression (STAR) model is preferred to the "best" continuous model (i.e. the one factor Cox, Ingersoll, and Ross (CIR: 1985) model) when comparing predictive accuracy for the "Stable 1990s" period that we examine. Moreover, an analogous result holds for the "Post 1990s" period that we examine, where the STAR model is preferred to a two factor stochastic mean model. Thus, when the STAR model is parameterized using only data corresponding to a particular sub-sample, it outperforms the "best" continuous alternative during that period. However, when models are estimated using the entire dataset, the continuous CHEN model is preferred, regardless of the variety of model specification (selection) test that is carried out. Given that it is very difficult to ascertain the particular future regime that will ensue when constructing ex ante predictions, thus, the CHEN model is our overall "winning" model, regardless of sample period.

Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a mapping between GL (CL) superiority and first (second) order stochastic dominance. This allows us to develop a forecast evaluation procedure based on an out-of-sample generalization of the tests introduced by Linton, . The asymptotic null distributions of our test statistics are nonstandard, and resampling procedures are used to obtain the critical values. Additionally, the tests are consistent and have nontrivial local power under a sequence of local alternatives. In addition to the stationary case, we outline theory extending our tests to the case of heterogeneity induced by distributional change over time. Monte Carlo simulations suggest that the tests perform reasonably well in finite samples; and an application to exchange rate data indicates that our tests can help identify superior forecasting models, regardless of loss function.

Diffusion index models have received considerable attention from both theoreticians and empirical econometricians in recent years. One reason for this is that datasets with many variables are increasingly becoming available and being utilized for economic modelling, and another is that common factors are often assumed to underlie the co-movements of a set of macroeconomic variables. In this paper we review some recent results in the study of diffusion index models, focusing primarily on advances due to [4, 5] and [1]. We discuss, for example, the construction of factors used in prediction models implemented using diffusion index methodology and approaches that are useful for assessing whether there are observable variables that adequately "proxy" for estimated factors.

We review and construct consistent in-sample specification and out-of-sample model selection tests on conditional distributions and predictive densities associated with continuous multifactor (possibly with jumps) and (non)linear discrete models of the short term interest rate. The results of our empirical analysis are used to carry out a "horserace" comparing discrete and continuous models across multiple sample periods, forecast horizons, and evaluation intervals. Our evaluation involves comparing models during two distinct historical periods, as well as across our entire weekly sample of Eurodollar deposit rates from 1982-2008. Interestingly, when our entire sample of data is used to estimate competing models, the "best" performer in terms of distributional "fit" as well as predictive density accuracy, both in-sample and out-of-sample, is the three factor Chen (CHEN: 1996) model examined by Andersen, . Just as interestingly, a logistic type discrete smooth transition autoregression (STAR) model is preferred to the "best" continuous model (i.e. the one factor Cox, Ingersoll, and Ross (CIR: 1985) model) when comparing predictive accuracy for the "Stable 1990s" period that we examine. Moreover, an analogous result holds for the "Post 1990s" period that we examine, where the STAR model is preferred to a two factor stochastic mean model. Thus, when the STAR model is parameterized using only data corresponding to a particular sub-sample, it outperforms the "best" continuous alternative during that period. However, when models are estimated using the entire dataset, the continuous CHEN model is preferred, regardless of the variety of model specification (selection) test that is carried out. Given that it is very difficult to ascertain the particular future regime that will ensue when constructing ex ante predictions, thus, the CHEN model is our overall "winning" model, regardless of sample period.

This paper makes two contributions. First, we outline a simple simulation based framework for constructing conditional distributions for multi-factor and multi-dimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be used, for example, to form predictive confidence intervals for time period t + τ , given information up to period t. Second, we use the simulation based approach to construct a test for the correct specification of a diffusion process. The suggested test is in the spirit of the conditional Kolmogorov test of Andrews (1997). However, in the present context the null conditional distribution is unknown and is replaced by its simulated counterpart. The limiting distribution of the test statistic is not nuisance parameter free. In light of this, asymptotically valid critical values are obtained via appropriate use of the block bootstrap. The suggested test has power against a larger class of alternatives than tests that are constructed using marginal distributions/densities, such as those in and Corradi and Swanson (2005a). The findings of a small Monte Carlo experiment underscore the good finite sample properties of the proposed test, and an empirical illustration underscores the ease with which the proposed simulation and testing methodology can be applied.

Litbanghan bukan sekadar pelengkap, tapi fondasi kesiapan TNI AD di era ancaman multidimensi.
Dari kolaborasi dengan BRIN hingga inovasi lokal anti-drone, inilah saatnya membangun ekosistem pertahanan yang tangguh dan mandiri, karena kesiapan tidak bisa ditunda.
The time to act was yesterday.

Introduction: Educational equity is a fundamental principle in any society. Investigating the academic performance of students based on gender helps assess if there are disparities in access to quality education, resources, or support systems. Accountancy is one of the most in-demand courses in the Philippines because of the employment opportunities and career progression in the field. The licensure examination for certified public accountants has long-been considered as one of the most difficult state board examination in the Philippine history. Studying the academic performance of accounting students by gender group in a developing country like the Philippines holds significant importance due to its potential to contribute to various aspects of education, society, and gender equality since prior research has tended to focus on developed nations like America and Europe. Purpose: The present article aims to present findings from relevant literature to enhance educational equity by investigating factors influencing academic performance which can help identify barriers that certain gender groups may face in pursuing accounting education. This knowledge can offer evidence-based policy recommendations to higher education institutions and regulatory bodies aimed at improving accounting teachinglearning, academic performance, production of licensed accountants, and overall improvement in the accountancy profession. Method: The review was conducted using PRISMA Statement (Preferred Reporting Items for Systematic reviews and Meta-Analyses) which allows for rigorous search for articles on gender disparities in classroom learning in accounting education. The resources include Google Scholar, Scopus and Web of Science journal databases. Several eligibility and exclusion criteria were determined including the time period from 2020 to 2024 to properly include recent studies and development; data should be from empirical study which means that article review, chapter in book, and conference proceeding are excluded. In addition, in order to avoid confusion in understanding, non-English publications are also excluded. Findings: This review finds that gender disparities in accounting education in the Philippines persist despite higher female enrollment rates, driven by intertwined socio-cultural, economic, and institutional factors. Cultural norms, economic constraints, and unequal access to mentorship and leadership roles contribute to differentiated educational experiences and career trajectories between men and women. Addressing these gaps requires coordinated action among policymakers, academic institutions, and professional bodies to promote gender-sensitive curricula, equitable resources, and inclusive networks. Such reforms align with Sustainable Development Goal 5 (Gender Equality) by eliminating systemic barriers and ensuring equal opportunities, thereby strengthening the diversity, competence, and resilience of the accounting profession. Recommendations: To address the persistent gender disparities in accounting education, it is recommended that gender equity principles be fully integrated into higher education policies, licensure requirements, and professional standards. Institutions and professional bodies should develop structured mentorship and leadership programs, particularly targeting underrepresented genders in senior accounting roles. Accounting curricula must be redesigned to incorporate gender-sensitive content, inclusive language, and equity-focused ethical training to normalize diversity in the profession. Equitable access to education should also be enhanced through expanded scholarships, financial subsidies for licensure review programs, and fee assistance for economically disadvantaged students. Moreover, national campaigns and institutional initiatives should actively challenge stereotypes and reshape cultural narratives that limit career opportunities for certain genders. Finally, continuous monitoring through gender audits and data-driven research should be institutionalized to track progress toward achieving SDG 5 and to inform evidence-based interventions.

Myanmar’s ongoing crisis pits the State Administrative Council (SAC), which seized power in 2021, against the National Unity Government (NUG) formed by ousted lawmakers. The SAC maintains military and institutional control but lacks de jure legitimacy, seeking to use the upcoming general election to secure recognition. The NUG maintains popular support yet remains fragmented and mostly in exile. ASEAN has shifted towards cautious engagement with both sides, while global powers remain split. The struggle’s outcome hinges on whether the NUG can transform sympathy into genuine de facto authority.

Centro Brasileiro de Análise e Planejamento (CEBRAP) α This empirical research was conducted by the Nucleus of Law and Democracy of CEBRAP, in partnership with DIREITOGV and in collaboration with the Latin American Institute of the Freie Universität Berlin. It is embedded in the larger context of a thematic project of FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) analyzing the relationship between social movements, law and the concept of autonomy. This research is partially funded by CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) coordinated by

The Carbon Border Adjustment Mechanism (CBAM) is tool designed to address the challenge of reducing greenhouse gas emissions while ensuring fair competition for industries within the EU. The paper analyses the CBAM' for regulating climate change and its broad ramifications. The CBAM is expected to limit greenhouse gases and contribute to global efforts to combat climate change. This article explores key features of the mechanism, looking at its guiding principles, expected advantages, and potential drawbacks. The analysis concludes that the European Union's Carbon Border Adjustment Mechanism (CBAM) exerts a negative impact on industries, highlighting the necessity of integrating the CBAM within the overarching framework of allowance allocation. Such integration would ensure the design of an allowance allocation system that preserves cost efficiency across sectors. Furthermore, the study suggests that a higher, more consistent carbon price in China could serve as an effective countermeasure to mitigate the adverse effects of the EU CBAM, thereby stabilizing the cost-effectiveness of various industries. Notably, the impact of the EU CBAM on industry cost efficiency would significantly diminish once the Chinese carbon price reaches 60 RMB per ton. Lastly, the research indicates that, beyond a certain export volume threshold to the EU, efforts to limit exports become increasingly ineffective in reducing the CBAM's

Esta investigación aborda la identificación y el diagnóstico general de los materiales y/o colecciones patrimoniales bibliográficas y documentales (no archivísticas) bajo la custodia de instituciones, organizaciones o particulares, con asiento en las cabeceras de los municipios que conforman la subregión del Oriente antioqueño (Colombia). Se reconocieron acciones de organización,

There is an ongoing debate about the role of income diversification in enhancing bank stability within the financial services industry in Europe. Some advocate for diversification, while others argue that its importance should not be overstated. Some financial institutions are encouraged to focus on their traditional investments instead of income diversification, while others suggest that income diversification can stabilize or destabilize, depending on the regulatory environment. These conflicting results indicate a lack of clear evidence regarding the effectiveness of income diversification. Therefore, this paper aims to study the impact of income diversification on bank stability and enhance the predictive performance of bank stability by analyzing the period from 2000 to 2021 using a sample from 26 European countries, based on aggregate bank data. It employs a hybrid method that combines econometric techniques, specifically the generalized method of moments and a fixed-effects model, with machine-learning algorithms such as Random Forest and Support Vector Machine. These methods are applied to enhance the reliability and predictive power of the analysis by addressing the problem of endogeneity (via generalized method of moments) and capturing non-linearities, interactions, and high-dimensional patterns (via machine learning). The econometric findings reveal that income diversification can reduce non-performing loans, improve bank solvency, and enhance the Z-score, indicating the significant role of income diversification in improving bank stability. Conversely, the results also show that the machine-learning algorithms used play a crucial role in enhancing the predictive performance of bank stability.

A baixa qualidade do sistema educacional brasileiro é um dos obstáculos ao crescimento de sua economia. Uma das maneiras para se reverter tal situação é a melhoria na qualidade de ensino, a qual depende, devido à restrição orçamentária do governo, da correta identificação das prioridades no que se refere à aplicação dos recursos entre os diferentes níveis de ensino. Sendo assim, esse estudo tem o intuito de analisar qual o nível de ensino mais importante na geração de renda e crescimento econômico no Paraná utilizando os micro-dados da PNAD de 2005 e o método de HECKMAN (1979). Para tanto, foram identificados os retornos em escolaridade de acordo com cada nível escolar. A conclusão é de que o ensino superior é o que apresenta maior retorno. No entanto, isso não significa que os outros níveis de ensino não sejam de crucial importância na decisão da alocação dos gastos destinados à educação. Palavras-chave: Retorno dos diferentes níveis de escolaridade; Método de HECKMAN, Investimentos no sistema educacional.

There is a dissonance between the legal framework, international conventions and the practices of political and economic groups that endorse the abuse of nature, devastating huge areas through logging, mining, industrial chemical production and industrial agriculture, notorious culprits of the severe environmental problems that plague the world. Current policies cannot keep pace with the environmental degradation we face today. Challenges are conceptual, more civic and political than technical: institutional capacity, judicial neutrality, informational transparency, social spaces for civic engagement are the main factors to deal with the dynamics that sustain lock-ins and barriers to change.

This research delves into a comprehensive examination of the application and convergence analysis of a newly developed block method for simulating epidemic models. The focal point of this study revolves around the derivation and implementation of a novel scheme, crafted through the utilization of power series polynomials, ensuring the fulfilment of essential properties. The formulation of the new scheme was rooted in the power series polynomial, a mathematical construct known for its versatility and precision. The rigorous validation process confirmed that the derived scheme satisfied the requisite properties, thereby establishing its theoretical soundness. The crux of the investigation lies in the practical application of this innovative scheme to simulate an epidemic model. Through meticulous simulations, the results yielded compelling evidence of the new method's superiority over existing approaches considered in this research. The comparative analysis demonstrated a notable enhancement in both accuracy and convergence speed, highlighting the efficacy of the newly proposed scheme in capturing and predicting the dynamics of epidemics. The observed advantages of the new scheme are particularly noteworthy, showcasing its potential to revolutionize the field of epidemiological modelling. By outperforming established methods, the new approach not only contributes to the theoretical underpinnings of epidemic modelling but also holds significant promise for practical applications, such as forecasting disease spread and optimizing intervention strategies.

This study determined the gender variability on land rights, land tenure and method of land acquisition among farmers in Dadin kowa Irrigation Scheme Gombe and Borno States, Nigeria. The study adopted a multi-stage sampling technique; 2 LGAs, 6 villages and 300 farmers were systematically selected in stages. Households specific information was collected using structured questionnaires. A combination of analytical tools employed in the analyses includes descriptive statistics (means, frequencies and percentages), and inferential statistics (t/z tests). The results showed that 29.0% of the respondents were aged 31-40 years; while those within the ages of 20-30, 41-50, 51-60 and above 60 years age brackets constituted 17.0%, 16.3%, 16.0% and 19.3% respectively. Similarly, the sex segregation shows that majority of the respondents (95.3%) were male while 4.7% of the respondents were of the female category. Similarly, 24.7% of the respondents had household size of 7 -10 persons while 21.0% and 20.0% had a household size of 3 -6 and 11 -14 persons respectively. Also, 61.3% of the respondents belong to one form of cooperative body or the other. The results indicated that, the land rights include the rights to sell, rent, graze, bequeath, and use as religious center. The land tenure systems include family inheritance (92.3%), individual ownership by purchase (79%), renting (78%); while individual ownership through gift, leasing, and government allocation were ranked 4 th ,5 th and 6 th respectively. Also, land acquisition by inheritance was most common among males than females (69.3% and 27.7 % respectively) and the chi-square value indicated significant variability at 1% probability level. Similarly, land acquisition through buying, renting and through government allocation was more common among the male users (59.5, 58.8, and 22.3%) correspondingly. Results also indicated an average farm size of 0.9 ha and 0.3ha for male and female farmers respectively, and a significant difference with T-value of -4.231, significant at 1% probability. The study concluded that the most common land ownership structure among both females and males is inheritance. Land holding in number of plots and farm size are higher among males than females in the study area . Recommendations include the need for gender mainstreaming in transforming the irrigation systems, enlightenment of land users to embrace membership of farmers associations and more women friendly agro practices should be the focus of extension services.

Extending research on organizational learning to multi-product environments is of particular importance given that the vast majority of products are manufactured in such environments. We investigate learning in a multi-product facility drawing on exceptionally rich data for a manufacturing firm that is a leading producer of high technology components. Weekly data for 10 years from the firm's production and human resource tracking systems are augmented by surveys of managers and engineers and by extensive first-hand observation. We find that productivity improves when multiple generations of the firm's primary product family are produced concurrently, reflecting the firm's ability to augment and transfer knowledge from older to newer product generations. No significant transfer of knowledge is evident between the primary product family and other products. Productivity is, however, decreased when the production facility is faced with extensive within-product buyer-specific customizations.We develop the implications of these findings for theory and practice.

Extending research on organizational learning to multi-product environments is of particular importance given that the vast majority of products are manufactured in such environments. We investigate learning in a multi-product facility drawing on exceptionally rich data for a manufacturing firm that is a leading producer of high technology components. Weekly data for 10 years from the firm's production and human resource tracking systems are augmented by surveys of managers and engineers and by extensive first-hand observation. We find that productivity improves when multiple generations of the firm's primary product family are produced concurrently, reflecting the firm's ability to augment and transfer knowledge from older to newer product generations. No significant transfer of knowledge is evident between the primary product family and other products. Productivity is, however, decreased when the production facility is faced with extensive within-product buyer-specific customizations.We develop the implications of these findings for theory and practice.

This study employs a cross sectional design with stratified random sampling method to examine the effect of Amanah Ikhtiar Malaysia's (AIM) microcredit program on hardcore poor households' microenterprise assets in Peninsular Malaysia. So far no known study has been conducted to measure the effect of AIMs microcredit programs on microenterprise assets owned by hardcore poor households. It is evident that AIM's microcredit program increased microenterprise assets owned by hardcore poor households who received credit from AIM. This program should, therefore, focus on providing adequate training, flexible and diversified loan programs, and increasing outreach. The policy may also be reviewed and re-organized to reduce the dropout rate.

In this paper we propose a framework in order to analyze the dynamical process of decision and opinion formation of two economic homogeneous and boundedly rational agents that interact and learn from each other over time. The decisional process described in our model is an adaptive adjustment mechanism in which two agents take into account the difference between their own opinion and the opinion of the other agent. The smaller that difference, the larger the weight given to the comparison of the opinions. We also assume that if the distance between the two opinions is larger than a given threshold, then there is no interaction and the agents do not change their opinion anymore. Introducing an auxiliary variable describing the distance between the opinions, we obtain a one-dimensional map for which we investigate, mainly via analytical tools, the stability of the steady states, their bifurcations, as well as the existence of chaotic dynamics and multistability phenomena, i.e., the presence of coexisting attractors.

Starting from a Muthian cobweb model, we extend the profit-based evolutionary setting in Hommes and Wagener (2010) populated by pessimistic, optimistic and unbiased fundamentalists, by assuming that agents face heterogeneous information costs, inversely proportional to the entity of their bias. Hommes and Wagener (2010) proved that, when the unique steady state of their model is globally eductively stable in the sense of , the equilibrium under evolutionary learning may be just locally, but not globally, stable, due to the presence of a period-two cycle. Thanks to the introduction of information costs, we find that the equilibrium, when globally eductively stable, may be not even locally stable under evolutionary learning. More precisely, we analyze our setting by measuring the influence of agents' heterogeneity through the parameter describing the degree of optimism and pessimism. According to the considered parameter configuration, the unique steady state, which coincides with the fundamental, may be (locally or globally) stable for every value of the bias, like in Hommes and Wagener (2010), or it may be stable

In this paper we show how a rich variety of dynamical behaviors can emerge in the standard Keynesian income-expenditure model when a nonlinearity is introduced, both in the cases with and without endogenous government spending. A specific sigmoidal functional form is used for the adjustment mechanism of income with respect to the excess demand, in order to bound the income variation. With the aid of analytical and numerical tools, we investigate the stability conditions, bifurcations, as well as periodic and chaotic dynamics. Globally, we study multistability phenomena, i.e., the coexistence of different kinds of attractors.

We propose a discrete-time exchange economy evolutionary model, in which two groups of agents are possibly characterized by heterogeneous preference structures. With respect to the classical Walrasian framework, in our setting the definition of equilibrium, in addition to utility functions and endowments, depends also on population shares, which affect the market clearing conditions. We prove that, despite such difference with the standard framework, for every economy and for each population shares there exists at least one equilibrium and we show that, for all population shares, generically in the set of the economies, equilibria are finite and regular. We then introduce the dynamic law governing the evolution of the population shares, and we investigate the existence and the stability of the resulting stationary equilibria. More precisely, we assume that the reproduction level of a group is related to its attractiveness degree, which depends on the social visibility level, determined by the consumption choices of the agents in that group. The attractiveness of a group is described via a generic bell-shaped map, increasing for low visibility levels, but decreasing when the visibility of the group exceeds a given threshold value, due to a congestion effect. Thanks to the combined action of the price mechanism and of the share updating rule, the model may reproduce the recurrent dynamic behavior typical of the fashion cycle, presenting booms and busts in the agents' consumption choices, and in the groups' attractiveness and population shares. We illustrate the emergence of fashion cycle dynamics in the case of Stone-Geary utility functions, which generalize the Cobb-Douglas utility functions, and for different formulations of the attractiveness maps, already considered in the literature.

In the present note we prove the first fundamental theorem of welfare economics, according to which all equilibrium allocations are Pareto optimal, for the standard pure exchange model with shares. In this context the social interaction among agents enters the definition of equilibrium only through the market clearing conditions, but it does not affect the agents' maximization problem. We show that the first fundamental theorem of welfare holds true also when introducing stationary equilibria in relation to a share updating mechanism.

The proposed real economy model grounds on a nonlinear multiplieraccelerator setup • The interplay between monetary and fiscal policy rules is investigated • The monetary policy is able to lead the economy toward the targeted level of output • Policies can be the source of endogenous fluctuations resembling business cycle • The interplay between policies is responsible for the occurrence of multistability

Starting from a Muthian cobweb model, we extend the profit-based evolutionary setting in Hommes and Wagener (2010) populated by pessimistic, optimistic and unbiased fundamentalists, by assuming that agents face heterogeneous information costs, inversely proportional to the entity of their bias. Hommes and Wagener (2010) proved that, when the unique steady state of their model is globally eductively stable in the sense of , the equilibrium under evolutionary learning may be just locally, but not globally, stable, due to the presence of a period-two cycle. Thanks to the introduction of information costs, we find that the equilibrium, when globally eductively stable, may be not even locally stable under evolutionary learning. More precisely, we analyze our setting by measuring the influence of agents' heterogeneity through the parameter describing the degree of optimism and pessimism. According to the considered parameter configuration, the unique steady state, which coincides with the fundamental, may be (locally or globally) stable for every value of the bias, like in Hommes and Wagener (2010), or it may be stable

We develop a macroeconomic behavioral model in order to analyze the interactions between real and financial markets. The real subsystem is represented by a simple Keynesian income-expenditure model, while the financial subsystem is represented by an equilibrium stock market with heterogeneous speculators, i.e., chartists and fundamentalists. The interactions between the two markets are modeled in the following way: the aggregate demand depends, among other variables, also on the stock market price, while the fundamental value used by speculators in their decisional process depends on real economic conditions. In our model we introduce a parameter that represents the degree of interaction. With the aid of analytical and numerical tools we show that an increasing degree of interaction between markets tends to locally stabilize the system. This stabilization occurs via a sequence of period-halving bifurcations. Globally, we find that the stabilization process implies multistability, i.e., the coexistence of different kinds of attractors.

Horrific images of war generate pressure on belligerent parties to avoid or reduce civilian casualties. The demands from this pressure often exceed the standard of care which belligerent parties apply to uphold their obligations under international humanitarian law (IHL). By tracing the role that wartime images have played in shaping the public discourse of IHL implementation, this article examines the dynamics through which these images might skew the standard of care applicable to targeting operations under IHL. It does so by dissecting the pitfalls of wartime imagery with reference to: (a) command intent; (b) factual knowledge; and (c) adversarial manipulation. Having identified these pitfalls, the article then discusses how imagery-driven legal assessment could shift the standard of care that military decision-makers are reasonably expected to take when applying the principle of distinction, proportionality, and the duty to exercise feasible precautions during targeting operations. This article concludes that differentiated standards of care only serve the interests of a belligerent that shows little respect for IHL and therefore, in the long run, undermines the normative foundation upon which this body of law has been built to safeguard humanity in warfighting.

The purpose of this study is to analyze the setting of the education right for child labour in working relationships. The method used in this study is empirical normative. The results showed that the regulation of the fulfillment of the education right for child labour in the working relationship have not been maximal, because there is still a legal void in the Employment Law and the absence of synchronization of Law No. 20 of 2003 on the National Education System, Government Regulation No. 48/2008 on Education Funding. The implementation of the 20% education budget has not been achieved so that uneven education is enjoyed. Therefore, a revision of the rules on the fulfillment of educational rights for child labour in an integrated and harmonious working relationship is required.

This study finds out relationship of charismatic leadership with Organizational citizenship behavior, work engagement and job responsibilities. The study also aims to find out relationship of charismatic leadership with OCB and Job responsibilities via mediating role of work engagement. The survey was carried with quantitative in nature and questionnaire was used as tool for data collection from employees of banking sector. The sampling technique was cluster sampling and sample size was 107 respondents. Results showed that there are positive relations between charismatic leadership and OCB, also positive relation between charismatic leadership and work engagement. Charismatic leadership and OCB have positive relationship via mediating role of work engagement. Charismatic leadership have relationship with job responsibilities, but in charismatic leadership and job responsibilities work engagement not work as mediator.

In a knowledge economy, people are facing increased competition hence developing more greed due to lack of love and kindness. Most of the organization now set their spiritual standards to ensure more love and kindness towards one's role and colleagues. Organizations and people should ensure workplace spirituality. This study is conducted to explore and determine the relationship between workplace spirituality, job satisfaction, organizational commitment and job involvement. Our target population was employees (lecturer level) of public sector Universities of Punjab. A sample of 150 employees was selected by systematic sampling in which 101 were responded at rate of 67 %. A research questionnaire was developed for data collection and data analysis was based on descriptive and inferential statistics. As from previous studies and on basis of our hypothesis testing and data collection, it can be concluded that there is a significant relationship between workplace spirituality, job s...

Purpose: Aim of this paper is to explore the role of leadership styles (transformational and transactional leadership) on knowledge management practices of small and medium enterprise in Pakistan.   Design/Methodology/Approach– Data was collected via structured questionnaire. Total 400 questionnaires were distributed randomly among employees of SME sector in Pakistan. Regression analysis was used to test the hypothesis. Findings– Findings supported that transformational and transactional leadership styles have significant effect on knowledge management practices (socialization, externalization, combination and internalization) of small and medium enterprise in Pakistan.   Practical Implications– This study provide insight about the knowledge management that which leadership style is preferable in order to enhance the knowledge management practices of organization. Originality/Value– There are few studies which clarify a link between leadership and knowledge management in context of ...

Th e Relationship between Pre-trade Transparency, Order 1mbalance and lnvestors ' Behavioral Biases transparency, order imbalance and investors ' behavioral biases. The impact of increasing pre-甘ade 仕ansparency on the varied order behavior is determined for three different types of investors: indívídual ínvestors, domestíc and foreígn ínstitutíonal ínvestors. The empírical results show that the intraday pattem of order imbalance for individual investors exhibits an inverse U-pattem, while that for institutional investors displays a quasi W -pattem and the several peak poínts of the W-p甜em move forward in a more 仕ansparent market. Additionally, the measure of herding for individual investors increases as market transparency increases and the current order imbalance of individual investors is significant1y negatívely affected by the previous order imbalance of foreígn ínstitutional investors. As foreign traders produce a larger order ímbalance, índividual ínvestors begín to pay attention. Foreign traders also seem to be more vigorous and confident in a more transparent market. However, they also 甘Y to conceal their real motive by using order splitting s仕ategies to avoid information leaks fast according to the in仕aday pa位em of order imbalance and 仕ading activity.

In this paper we estimate the probability of informed trading (P i ) in an order-driven stock market as well as perform a comprehensive analysis on the interrelations among probability of informed trading and three common performance indicators, i.e., liquidity, volatility and efficiency. We find that uninformed traders exhibit price chasing behavior even over very short time interval and that volatility in stock price attracts uninformed traders. Using 3SLS which takes into consideration the endogeneity of the probability of informed trading and the liquidity, volatility and efficiency measures, our empirical results provide new evidence on market microstructure literature. We find that P i and the volatility and liquidity of stocks are simultaneously determined. Higher P i leads to lower liquidity and higher volatility, and vice versa. Firms with larger size, higher ownership concentration and lower turnover have higher probability of informed trading.

We examine the precautionary savings explanation and the mispricing explanation of the positive association between cash holdings and average future stock return. (1) As predicted by the optimal corporate cash holdings policy in precautionary savings models, high cash holders have higher systematic default risk than low cash holders. (2) Inconsistent with the asset pricing implication of precautionary savings models, adjusting for default risk and other macroeconomic risks do not explain the positive association and the main culprit is the empirically negative default risk premium. (3) Cash holdings is negatively correlated with a relatively (over)valuation index and, as predicted by the mispricing explanation, the positive association disappears when limits to arbitrage are low, reappears when limits to arbitrage get more severe and is strongest when limits to arbitrage are high. (4) Consistent with the mispricing explanation, the positive association is strongest when high cash ho...

This study aims at explaining the deviation between the budget balance ratio forecasts and the outcomes in the Portuguese official forecasts and in the European Commission (EC) vintage forecasts. Therefore, we used data from the EC for the period 1969-2011 and also the Portuguese official forecasts for 1977-2011. We explain the deviation of the budget balanceto-GDP through econometric estimations and present statistical decomposition about budget balance, revenue and spending-to-GDP deviations. The statistical significance of real GDP and inflation deviations reveals the effect of automatic stabilizers and the imperfect tax indexation system. The European panel reveals statistical significance (no significance) of investment (unemployment) deviations in the budget-to-GDP ratio. Countries with better fiscal rules seem to present favourable deviations (in the absence of fixed effects). In Portugal, there is evidence of unfavourable errors about the budget balance in nominal currency in most years, which has been offset (totally or partially) by a favourable nominal GDP effect deviation.

The pervasive use of mobile applications and social networks has intensified privacy concerns due to the widespread collection, processing, and sharing of personal data. To address these challenges, we introduce SafeMountain, a novel AI-driven framework designed to systematically quantify, evaluate, and visualize privacy risks in mobile apps and social platforms, ensuring strict compliance with international regulations, particularly the General Data Protection Regulation (GDPR). SafeMountain combines static and dynamic code analyses to scrutinize real-world data handling practices and detect potential privacy breaches. It also employs advanced Natural Language Processing (NLP) techniques for automated interpretation and evaluation of privacy policies and Terms of Service. By mapping textual policy disclosures to actual app permissions and behaviors, it identifies discrepancies and highlights potential non-compliance and data misuse. The framework introduces an objective risk scoring mechanism aligned with international standards and regulatory requirements, offering a structured methodology to classify and visualize privacy risks. This risk assessment spans multiple dimensions (predictability, manageability, and disassociability) leveraging privacy engineering principles and regulatory risk factors, and uses an intuitive traffic-light system (Green, Yellow, Red) to enhance transparency and user comprehension. SafeMountain addresses major research gaps, notably the absence of standardized privacy risk scoring and comprehensive visualization tools. By delivering actionable insights into permission consistency, policy transparency, compliance gaps, and data leakage vulnerabilities, it empowers users, developers, and organizations to manage privacy risks proactively. Ultimately, SafeMountain fosters trust through more transparent and accountable data privacy practices across digital ecosystems.

For many fluidized bed applications, the particle movement inside the reactor is accompanied by reactions at the particle scale. The current study presents for the first time in literature a multi-scale modelling approach coupling a one-dimensional volumetric particle model with the dense discrete phase model (DDPM) of ANSYS Fluent via user defined functions. To validate the developed modelling approach, the current study uses experimental data of pressure drop, temperature and gas composition obtained with a lab-scale bubbling fluidized bed biomass gasifier. Therefore, a particle model developed previously for pyrolysis was modified implementing a heat transfer model valid for fluidized bed conditions as well as kinetics for char gasification taken from literature. The kinetic theory of granular flow is used to describe particle-particle interactions allowing for feasible calculation times at the reactor level whereas an optimized solver is employed to guarantee a fast solution at the particle level. A newly developed initialization routine uses an initial bed of reacting particles at different states of conversion calculated previously with a standalone version of the particle model. This allows to start the simulation at conditions very close to stable operation of the reactor. A coupled multi-scale simulation of over 30 s of process time employing 300.000 inert bed parcels and about 25.000 reacting fuel parcels showed good agreement with experimental data at a feasible calculation time. Furthermore, the developed approach allows for an in-depth analysis of the processes inside the reactor allowing to track individual reacting particles while resolving gradients inside the particle.

gmu.edu. This report contains results from a nationally representative survey of American adults conducted in April and May 2012. The survey examined public beliefs about federal agencies that are engaged in climate change research, and assessed which agencies the public looks to for answers to their questions on the issue. Furthermore, participants visited NASA's climate change website: climate.nasa.gov. See the methods section for a complete description of the study design. Selected key findings .

economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.