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Using survey data from Shandong, Henan and Guizhou provinces of China, the purpose of this paper is to accurately measure the impact of rural residents’ financial education on financial literacy.

This paper chooses one province from the Eastern, Central and Western Regions of China, namely, Shandong, Henan and Guizhou, respectively, and 1,565 samples are obtained through a questionnaire survey. First, the paper constructs a financial literacy assessment framework and, then, scores the financial literacy of the respondents. Second, using ordinary least squares, feasible generalized least squares method and forward search method, the paper estimates the impact factors of financial literacy level. To avoid sample selection errors and endogeneity problems, the authors divide the respondents into treatment group (participated in financial education) and control group (non-participating in financial education) and, then, adopt propensity score matching (PSM) to analyze the impact of rural residents’ financial education on financial literacy.

The results show that education level and risk level have significant impact on rural residents’ participation in financial education, and some unobservable abilities and qualities also affect their participation. Therefore, the process of rural residents’ participation in financial education exists, which gives rise to self-selection and endogeneity problems; financial education is promoting rural residents’ financial literacy, but the effect of promotion becomes smaller after taking into account sample self-selection and endogenous problems. Rural residents of female, higher age, single, higher education level, higher parental education level, agricultural type, higher family annual per capita income and lower risk level show stronger effects on their financial literacy level, if they participate in financial education.

The survey sample was drawn from three provinces randomly but the site selection was not random. The implication is in rural China, financial education has positive effect on residents’ financial literacy level but considering the sample self- selection and endogenous nature, its impact becomes smaller.

The government should encourage rural residents to participate fully in financial education activities, especially those with a low educational level, low risk preference and mainly engaged in agricultural production.

The effect of financial education on financial literacy has not reached a consistent conclusion, and there is fewer quantitative discussion about this issue. The originality of this paper is based on the Organization for Economic Co-operation and Development evaluation index system; this paper constructs the evaluation index system of rural residents’ financial literacy in China and uses the PSM method to accurately measure the effect of financial education on financial literacy.

The ecosystem view is a fascinating perspective which provides management scholars with innovative conceptual tools to investigate the functioning of complex service systems. The purpose of this paper is to focus on the “mega” level of the education service ecosystem in an attempt to explain the relationships between education attainments and income disparities across Europe.

Data were collected from the European Union Statistics on Income and Living Conditions. Data trends over the time period (2007-2010) were investigated, involving 27 European countries. Unobserved time-invariant heterogeneity was controlled and dynamics over time were investigated. A random effects model was estimated for each country. The semi-log functional form is informed by Mincer’s (1974) human capital models.

Education levels were found to be a predictor of income inequality in all the countries included in this research, i.e. higher education level leads to higher income and vice versa. However, the effect of education attainments on individual earnings was irregular. Eastern European countries, inter alia, revealed a strong relationship between education attainments and individual earnings, whereas Scandinavian countries showed a weak link between education levels and income.

Education has the potential to affect income inequalities in Europe. Policy makers should develop tailored strategies to deal with the consequences of education levels on individual earnings. Both education services’ quality and the interaction between education and moderating socio-demographic variables may influence income inequality in European countries.

This is one of the first attempts to investigate the relationship between education and income inequalities drawing on the service ecosystem perspective. Further conceptual and practical developments are needed to better explain the effects of education attainments on income inequality.

The purpose of this paper is to provide a country‐level consideration of the relationship between entrepreneurship, immigration and education. In contrast to studies that report on immigration and entrepreneurship in a region or single country, the authors seek to determine whether levels of immigration, and the level of education obtained by the immigrants, are predictive of levels of entrepreneurship activity. A common set of variables and data from developed countries are used to test the hypothesized relationships.

Using data on 21 OECD countries and five measures of entrepreneurship from the Global Entrepreneurship Monitor project, the authors assess the significance of immigration and education level on entrepreneurial activity using regression analysis.

The stock of immigrants in a country was found to be predictive of the proportion of that country's population involved in starting and managing a new business (early stage entrepreneurship), as well as the growth expectations held by those early‐stage entrepreneurs. Also, levels of high growth and high growth expectation entrepreneurship were predicted by the proportion of more highly‐educated immigrants.

This study provides national‐level comparative evidence linking entrepreneurial activity to immigration and to the level of education obtained by those immigrants, thereby adding to our understanding of immigration, education and entrepreneurship. The results have implications for the immigration policies of countries seeking to add to their economic base by encouraging entrepreneurship and job creation.

Identifies an error in the measurement of private rates of return to aggregate levels of education. When education is viewed as a continuous variable, the estimated rate of return is to an incremental year of schooling. However, rates of return are often estimated for aggregate levels of education such as the secondary and university levels. When an aggregate level has sub‐levels, such as bachelors′ and masters′ for the university level, the conventional procedure underestimates the rate of return to the aggregate level due to the dominance of up‐front costs in the discounting procedure used to compute rates of return.

There is plenty of individual-level evidence, based on the estimation of Mincerian equations, showing that better-educated individuals earn more. This is usually interpreted as a proof that education raises labour productivity. Some macroeconomists, analysing cross-country time series, also support the idea that the continuous expansion of education has contributed positively to growth. Surprisingly, most economists with an interest in human capital have neglected the level of the firm to study the education-productivity-wage nexus. And the few published works considering firm-level evidence are lacking a proper strategy to cope with the endogeneity problem inherent to the estimation production and wage functions. The purpose of this paper is to aim at providing estimates of the causal effect of education on productivity and wage labour costs.

This paper taps into a rich, firm-level, Belgian panel database that contains information on productivity, labour cost and the workforce’s educational attainment to deliver estimates of the causal effect of education on productivity and wage/labour costs. Therefore, it exclusively resorts to within firm changes to deal with time-invariant heterogeneity bias. What is more, it addresses the risk of simultaneity bias (endogeneity of firms’ education-mix choices in the short run) using the structural approach suggested by Ackerberg et al. (2006), alongside more traditional system-GMM methods (Blundell and Bond, 1998) where lagged values of labour inputs are used as instruments.

Results suggest that human capital, in particular larger shares of university-educated workers inside firms, translate into significantly higher firm-level labour productivity, and that labour costs are relatively well aligned on education-driven labour productivity differences. In other words, the authors find evidence that the Mincerian relationship between education and individual wages is driven by a strong positive link between education and firm-level productivity.

Surprisingly, most economists with an interest in human capital have neglected the level of the firm to study the education-productivity-pay nexus. Other characteristics of the workforce, like gender or age have been much more investigated at the level of the firm by industrial or labour economists (Hellerstein et al., 1999; Aubert and Crépon, 2003; Hellerstein and Neumark, 2007; Vandenberghe, 2011a, b, 2012; Rigo et al., 2012; Dostie, 2011; van Ours and Stoeldraijer, 2011). At present, the small literature based on firm-level evidence provides some suggestive evidence of the link between education, productivity and pay at the level of firms. Examples are Hægeland and Klette (1999); Haltiwanger et al. (1999). Other notable papers examining a similar question are Galindo-Rueda and Haskel (2005), Prskawetz et al. (2007) and Turcotte and Whewell Rennison (2004). But, despite offering plausible and intuitive results, many of the above studies essentially rely on cross-sectional evidence and most of them do not tackle the two crucial aspects of the endogeneity problem affecting the estimation of production and wage functions (Griliches and Mairesse, 1995): first, heterogeneity bias (unobserved time-invariant determinants of firms’ productivity that may be correlated to the workforce structure) and second, simultaneity bias (endogeneity in input choice, in the short-run, that includes the workforce mix of the firm). While the authors know that labour productivity is highly heterogeneous across firms (Syverson, 2011), only Haltiwanger et al. (1999) control for firm level-unobservables using firm-fixed effects. The problem of simultaneity has also generally been overlooked. Certain short-term productivity shocks affecting the choice of labour inputs, can be anticipated by the firms and influence their employment decision and thus the workforce mix. Yet these shocks and the resulting decisions by firms’ manager are unobservable by the econometrician. Hægeland and Klette (1999) try to solve this problem by proxying productivity shocks with intermediate goods, but their methodology inspired by Levinsohn and Petrin (2003) suffers from serious identification issues due to collinearity between labour and intermediate goods (Ackerberg et al., 2006).

Measurement of returns to vocational education has always remained a matter of controversy (Psacharopoulos, 1994; Bennell and Segerstrom, 1998; Ziderman, 1997). Based upon the return evidence many World Bank projects were scrapped (Middleton and Ziderman, 1997, Bennell and Segerstrom, 1998). However, there is again a growing interest for Vocational Education in different countries as well as in international body like UNESCO (Debroy, 2009; King, 2009; McGrath, 2012). Unfortunately there is little justification for this growth from the returns to Vocational Education literature. India is one among the countries where fervent around vocational education and training (henceforth VET) is quite discernible at present. The paper aims to discuss these issues.

Standard Minerian, extended Mincerian and Heckman two-stage methods are used to measure returns to VET vis-à-vis returns to general education in Indian context while taking care of selection bias problem. It is measured at different levels of education since the characteristics of VET changes significantly at different levels of education. This work also considers different classifications of VET (Formal, Hereditary, On the Job). National Sample Survey (NSS) data which recently has included data on VET is used for this measurement.

It shows that the returns to formal VET and On the Job training (OJT) are quite high in the primary level. There is a gradual decline in these returns when compared with general education at higher levels, namely, secondary and tertiary level. At tertiary level effect of formal VET or OJT on income becomes almost insignificant. On the other hand, hereditary training and other category of VET have significantly negative impact and insignificant impact on income, respectively.

This work suggests that the investment in VET in present context is justified however there is a requirement to focus on specific area within the VET for this investment. Investment in higher level of formal VET as well as in the OJT set up can provide better return to the individuals. However, NSS data does not provide income data for the self-employed persons. Hence, self-employed category remains outside the purview of this study.

In general, formal VET and OJT are profitable for individual in wage employment. However, this profitability declines when the effect of the training is measured at a higher level of general education. Formal vocational training/OJT for the primary and secondary school dropouts are clearly profitable. However, OTJ seems to be providing a return similar to what is provided by formal training. A poor performance of formal VET indicates an institutional gap and reflects present cry from industry for “quality” manpower.

To author’s knowledge there is no study on return evidence from various types of VET in Indian context. This study is a deviance from the existing literature on VET in following ways. First, this study suggests that investment in VET can be profitable. Second, many earlier works missed out to consider different types of VET and compare them with general education at different levels. Putting all types of VET into one basket and then analyzing returns has the risk to misleading the policies. Different VETs have completely different dynamics and hence it is required to treat them separately.

This account aims to introduce contrasting perspectives on teaching and learning methods, and to detail the growth of new forms and vocabularies of access to learning. As we move towards the new millennium, the development of national, yet diversified, credit frameworks and systems will provide an essential underpinning for the organisational culture that will be needed to sustain the wellbeing and growth of the educational system. These new systems are already being incorporated into the practice of ‘virtual’ education. Lifelong learning has widespread support across the social and political spectrum and its importance can hardly be over‐stated as we seek to maintain competitiveness in a changing world. Increasing knowledge and understanding to serve both the needs of the economy and of individuals to play a major role in democratic life has become an agenda of necessity as well as desire. An open society requires open systems of knowledge. A prognosis for the future is submitted where the significance of part‐time modular and open flexible learning is evaluated in terms of a curriculum rooted in useful knowledge and competences, acquired at different sites of learning, including the workplace. It is argued that modular structures, using the potential offered by credit accumulation and transfer to different institutions with different missions, can transcend and transform the learning opportunities for students in a mass system of higher education which is rapidly becoming part of a global market economy and society. Continuous lifelong learning involving its key features of open access, recognition of learning wherever it takes place and the growth of new learning networks and partnerships, is at the conceptual heart of the development of the virtual university.

This systematic literature review aims to identify the pattern of data mining (DM) research by looking at the levels and aspects of education.

This paper reviews 113 conference and research papers from well-known publishers of educational data mining (EDM) and learning analytics-related research using a recognized literature review in computer science by Carrera-Rivera et al. (2022a). Two major stages, planning and conducting the review, were used. The databases of Elsevier, Springer, IEEE, SAI, Hindawi, MDPI, Wiley, Emerald and Sage were searched to retrieve EDM papers from the period 2017 to 2023. The papers retrieved were then filtered based on the application of DM to the three educational levels – basic, pre-tertiary and tertiary education.

EDM is concentrated on higher education. Basic education is not given the needed attention in EDM. This does not enhance inclusivity and equity. Learner performance is given much attention. Resource availability and teaching and learning are not given the needed attention.

This review is limited to only EDM. Literature from the year 2017 to 2023 is covered. Other aspects of DM and other relevant literature published in EDM outside the research period are not considered.

As the current trend of EDM shows an increase in zeal, future research in EDM should concentrate on the lower levels of education to identify the challenges of basic education which serves as the core of education. This will enable addressing the challenges of education at an early stage and facilitate getting a quality education at all levels of education. Appropriate EDM techniques for mining the data at this level should be the focus of the research. Specifically, techniques that can cater for the variation in learner abilities and the appropriate identification of learner needs should be considered.

Content sequencing is necessary in facilitating an easy understanding of concepts. Curriculum design from basic to higher education dwells much on this. Identifying the challenge of learning at the early stages will facilitate efficient learning. At the basic level of learning, data on learning should be collected by educational institutions just as it is done at the tertiary level. This will enable EDM to accurately identify the challenges and appropriate solutions to educational problems. Resource availability is a catalyst for effective teaching and learning. The attributes of a learner will enable knowing the true nature of the learner to determine the prospects of the learner.

This research has not been published in any journal. The information presented is the original knowledge of the authors. However, a pre-print of the work is in Research Square.

The COVID-19 crisis caused a high level of job insecurity, layoff and low employment opportunities. It generated a worldwide shock, which might have a long-lasting effect on individuals' careers. Changes might occur in terms of individuals’ career choices, objectives, perception of career success and preferences in terms of industries and work arrangements. This study aims to examine crisis-induced career shock among the workforce, which might be translated into changes or doubts related to career choices, objectives and perception of career success, and to analyze individuals' preferences in terms of industries and work arrangements. It focuses mainly on investigating variations among the workforce, based on gender, education level and ethnic origin. These variations are also examined regarding job insecurity, layoff and perceived employability.

Frequency counts, percentages, mean ranking, independent t-test and analysis of variance (ANOVA) were used for a sample of 317 workers in the United Arab Emirates (UAE). Three research questions were developed and examined, which are: (1) is there a variation in the workforce, based on gender, education level and ethnic origin concerning crisis-induced career shock (specifically changes related to career choices, objectives and career success? (2) Is there a variation among the workforce related to career preference per industry and work arrangement? If yes, is there a difference in the workforce-based gender, education level and ethnic origin? And (3) is there a variation in the workforce, based on gender, education level and ethnic origin concerning job insecurity, layoff and perceived employability?

The findings revealed that career shock was significantly higher among pre-university respondents (specifically, doubts about career choices and perceived career success). As for career preferences per industry, e-business, media and marketing had significant values for all respondents, with e-business as the top-rated choice except for Emiratis who rated it as their third choice. Education was the choice of both men and women. The choices related to other industries (e.g. Healthcare, information, communication technology, etc.) and work arrangements (telework) varied significantly based on gender, education and ethnic origin. Men seem to worry more than women about losing their job as well as Emiratis compared to expatriates, and university-level respondents compared to pre-university.

This study contributes to highlighting variations related to career shock and career preferences per industry among the workforce based on gender, education level and ethnic origin. This can help organizations in these industries to have a portrait of the situation in the employment market to be able to develop relevant interventions. This research provides insights for managers and HRM practitioners.

This study contributes to expanding research on career and career shocks in a context of a crisis. It responded to authors who called for more research about career shocks, as well as their implication for specific target groups, by examining variations based on gender, education level and ethnic origin.

Library assistants were originally considered to be professional librarians in the making, and were trained accordingly. With the expansion of libraries and librarianship, Britain's “apprenticeship” system of qualification gave way to formal library school education, and a new category of “non‐professional staff” was created, of people who were unwilling or unable to proceed to graduate‐level qualification. The development of non‐professional certificates of competence in the UK is described against parallel developments in the US, Canada and Australia; the COMLA training modules are also examined. The theoretical and practical issues surrounding training are discussed, training schemes and qualifications in the four countries analysed, and the relative merits of in‐house training and external certificate programmes argued.