This paper retains the distinction between the terms for two reasons. First the education and training series only goes back to the late 1980s, while the education series goes back much further, even with some breaks in the series the concept remains the same. Second the education and training series is more consistent over the period it is available for. The spending data are regularly revised. These revisions can change the total figure, or move items of expenditure from one sub-function to another. The detailed breakdown by sub-function is only revised back five years. This presents a problem with consistency when trying to compile long-term series based on sub-functions and the authors warn against simply splicing one set of data with another pre and post-revision. The education and training series in this paper is therefore consistent for its entire length, other than the break in 2011-12 detailed below. The education series is not and although revisions are generally quite small, readers should be careful when drawing conclusions from this data, especially those based on small differences.
The next table compares indicators of expenditure and expenditure growth for various time periods since 1987. As explained earlier, changes to the calculation of expenditure mean that the latter figures are based on both cash and resource accounting. The average percentages of GDP spent on education were lower in the first two periods than in any of the latter three. The average annual increase across the whole of the period 1997-98 to 2010-11 at 4.4% was well above the earlier two periods. It was also higher than the final period (covered by the 2007 spending review). The periods overlap and hence this illustrates the lower than average planned increases from 2007-08 onwards. Spending from 2010-11 fell in real terms from its high point
The chart shows that the largest annual increases occurred in the 2000s. The fastest rate of increase was in the 1950s and early 60s; spending doubled in real terms in the 11 years between 1952/53 and 1963/64. The real increase in the 11 years to 2009-10 was just over two-thirds. The next chart gives spending as a proportion of GDP. This produces a slightly more erratic trend, although again the main period of increase was in the two decades from the mid-1950s. The increases since the late 1990s were much smaller in comparison and did not take spending to a greater share of national income than the 1975-76 peak of 5.8%. The fall from this peak to 4.5% in 1979-80 was the fastest rate of change in the whole period
Note: Resource DEL excludes depreciation (and therefore does not include the estimated cost of student loans). ‘Science and research’ includes the activities of the seven research councils, research activities of the Higher Education Funding Council for England, the UK Space Agency and the UK Atomic Energy Authority. ‘Innovation, enterprise and business’ includes the Technology Strategy Board and BIS’s launch investments and financial guarantees. ‘Market frameworks’ includes the activities of the Insolvency Service, the Competition Commission, and the Advisory, Conciliation and Arbitration Service. ‘Higher education’ includes the teaching and learning grants of HEFCE and the student support system of grants (including the activities of the Student Loans Company). ‘Further education’ includes the Skills Funding Agency and the UK Commission for Employment and Skills. ‘Capability’ includes BIS administrative spending and some other areas of central spending. Figures are in 2013–14 prices, adjusted for inflation using the GDP deflator. Source: Department for Business, Innovation and Skills, 2013; HM Treasury, 2013c.
In this Briefing Note, we produce new estimates of the likely cuts to overall public spending on education in the UK up to 2014–15. We have also pieced together various published plans for grants and specific components of educationspending. This provides the most comprehensive analysis of the pattern of cuts across different areas of educationspending published to date. We also analyse which types of schools are likely to see the largest increases in funding and which are likely to see real-terms cuts. Throughout this Briefing Note, we focus on changes to the financial inputs into the education system rather than the outputs from it, such as young people’s exam results or earnings potential. We are concerned about the level of these inputs, of course, to the extent that they translate into the desired outputs. One would generally expect lower levels of financial inputs to make it tougher to deliver improvements in such outputs. Furthermore, even if there are offsetting improvements in the productivity of the inputs into education, such improvements could well have taken place in the absence of cuts to those financial inputs.
(Certificate, Diploma or Masters) in the subject (Davies and Parker 1994). Significantly, most of the major centres for the study of adult education were also themselves major providers of education for adults. At this stage, there was sometimes a fierce tension and even rivalry between those academics who worked professionally in the extra-mural programmes (organised through the Universities Council for Adult Education) and those who specialized academically in researching and teaching about adult learning (who met separately in the Standing Conference on University Teaching and Research in the Education of Adults) (Speightman 2004, 114). Most of these were long-established programmes, with a settled reputation, and they recruited small but significant numbers of students from overseas as well as in the UK. Moreover, until the late 1980s this was a difficult market for newcomers to enter. First, it was highly regulated by the Department of Education and Science and the local authorities, who funded most of the students. Second, the British Council’s ties to the established centres of excellence strongly influenced the choices of overseas students, particularly when they came to the UK as part of an aid programme.
An acute contradiction such as seen in the frame of everyday life is found within the reams of text available which informs education policy at the direction of the New Labour government whose policy has uncritically embraced EU encumbrances, and aggressively recommends a particular set of practices and duties for workers‘ lifelong survival in the increasingly unstable world of work. Perhaps the current rhetoric of employability reflects the state‘s fear of mass resistance such as was seen in the 1980s in response to Margaret Thatcher‘s almost complete destruction of manufacturing. Typically, management attempts to organise production in specific ways that they think will minimise the chance for resistance. New Labour‘s employability campaign, in its rational and seemingly logical promotion of education and learning as intimately linked with work, and with the resultant blurring of productive with political man, is a case of colonisation of the everyday of people who continue the struggle for survival in the neoliberal capitalist world. The implication is that those individuals who are fortunate enough to find employment in a rapidly flexibilising job market would then be held directly responsible for not only their own employability project, coupled with the drive toward ‗lifelong learning‘, but also will be responsible for the prosperity of their nation on the globally competitive stage.
How has the incidence of public educationspending changed over time? Has targeting improved over the years? Here we consider the change in the benefit incidence of public educationspending by comparing the results to Demery et al. (1995). These studies are actually comparable because the databases are similar. The study of Demery at al. (1995) is based on the GLSS 2 (1989) and 3 (1992) while the present study is based on GLSS 5 (2005/06), all of which are nationally representative household surveys conducted by the Ghana Statistical Service (GSS). For the sake of this comparison, we group pre-school and primary into primary education; JHS, SHS, and TVET are grouped into secondary, while universities, polytechnics, and teacher education are grouped into post-secondary. After basic school (JHS), children can either enroll in SHS or TVET. However, SHS is required for tertiary (university and polytechnic) and teacher training. For 2005, the benefit to secondary is a weighted average of JHS and SHS (including TVET). Table 5 reports the changes in distribution of education benefits between 1989 and 2005. The poorest quintile remains the smallest beneficiary of total education benefits, showing a declining share of total benefits between 1989 and 2005. For instance, the share of total benefits accruing to the poorest quintile has declined by 2.3 percentage points; falling from 17.1 percent in 1989 to 14.8 percent in 2005. It declined by 0.7 percentage point between 1989 and 1992, and further by 2.6 percentage points between 1992 and 2005. The bottom two quintiles accounted for an accumulated share of 32.3 percent of total benefits in 2005 compared with their cumulative income share of about 16 percent. The richest quintile however, appropriated 26.3 percent of total education benefits in 2005, gaining by 5.5 percentage points between 1992 and 2005 and 2.6 percentage points over the period 1989-2005 (Table 5). The bottom two quintiles witnessed a decrease in primary education benefits over the period 1992 and 2005, with benefits decreasing by 3.4 and 1.4 percent respectively over this period.
The impact of tuition fees on participation in higher education in the UK assessed by the Institute for Fiscal Studies as part of the Higher Education Fees and Funding Review (Dearden, Fitzsimons and Wyness (2010)). Using cross sectional information from the Labour Force Surveys between 1992 and 2008, the authors assess the impact of various HE student reforms that took place over the last 16 years including the introduction of upfront fees in 1998/99; deferred fees and loans in 2006/07; the reduction and abolition of student grants in 1999 and the re-introduction of student grants in 2004 (and extension in 2006). The authors found that an increase in tuition fees by £1,000 per annum – holding all other factors constant – would be expected to lead to a 4.4 percentage point decline in participation. The authors also find that a £1,000 per annum increase in grants increases participation by 2.1 percentage points, while a £1,000 per annum increase in loans appears to be worth more in terms of participation than an equivalent increase in grants (3.2 percentage points). The authors state that the “results indicate that a £1,000 increase in loans or grants is not sufficient to counteract the impact of a £1,000 increase in fees – the coefficient on fees being significantly higher than both loans and grants’. All results were statistically significant. Thus, increasing fees without increasing loans by the same value (or more) will result in a negative impact on participation. The authors also
Supporters of globalization argue that economic growth can change families’ incentives to spend on education (Shultz 2006:7), they argue for trade liberalization, capital flows, and openness as a means to attain gender equality (Seguino 2007:1). Trade liberalization and globalization increase trade opportunities and output (Arora2012:148), which increases job opportunities. Likewise, opening new industries and new markets to accommodate products through globalization drives wages and improved working conditions. Families, they posit, will invest more in women’s human capital if they anticipate job opportunities for their daughters. However, institutional, economic, and social factors may counteract this mechanism in terms of closing the gender gap. Research shows globalization has a limited impact on women's participation in the workplace, especially in rural areas (Arora 2012:148-150). Women tend to continue to work in the informal sector, which is characterized by low barriers to entry and does not require education. Increased incentives to educate women are minimal when globalization does not offer women opportunities outside of low wage sectors such as the garment industry, which do not pay educated women higher than uneducated women (UNCTAD 2008:11-13). Moreover, research shows that trade reduces gender equality measured by the female participation in the labor force decreases (Seguino 2007:1). In many developing countries, an increase in exports of raw materials resulting from trade liberalization has coincided with a decline of women’s health and education, as the job opportunities it provides are low-skilled (Potrafke and Ursprung 2011:2; Shultz 2006:7). To summarize, it is difficult to predict the impact of globalization on gender equality in education.
The paper investigates two issues regarding household expenditure on primary education of own children using the Second Malawi Integrated Household Survey (IHS2) data. Firstly, we look at factors which in‡uence a household’s decision to spend or not (the participation decision), and by how much (the expenditure decision). This is done for urban and rural households. We …nd that there are di¤erences in the factors which in‡uence both decision levels for the two groups of households. Secondly, to get a deeper understanding of these rural-urban spend- ing di¤erences, the study develops the Blinder-Oaxaca decomposition technique for the independent Double Hurdle model. The proposed decomposition is done at the aggregate and disaggregated levels. The aggregated decomposition allows us to isolate the expenditure di¤erences into a part attributable to di¤erences in characteristics and a part which is due to di¤erences in coe¢cients. The detailed (disaggregated) decomposition enables us to pinpoint the major factors behind the spending gap. At the aggregate decomposition level, our results show that at least 66% of the expenditure di¤erential is explained by di¤erences in characteristics between rural and urban households, implying that an equalization of household characteristics would lead to about 66% of the spending gap disappearing. At the disaggregated decomposition level, the rural-urban di¤erence in household income is found to be the largest contributor to the spending gap, followed by quality of access of primary schools. Besides, rural-urban di¤erences in mothers education and employment are found to contribute more to the spending di¤erential relative to the same for fathers.
Census Bureau. Costs (C) are the sum of expenditures on teacher salaries, transportation, and supplies. Average teacher salary serves as our input price (W). We include student enrollment (N) and the square of enrollment to effectively model the U-shaped average cost curve. Both the dropout rate and placement test scores in each district measure student achievement (A). We use ACT (American College Test) scores from the previous year to measure student performance. This test score variable is the average score on the three sections of the ACT test - English, comprehension, and mathematics. Both measures of student achievement are simultaneously determined with expenditure decisions. Student characteristics and family background are measured by the percent of students below the poverty level, the percent of students receiving free lunches, and the percent of adults in the district’s county that have a college education.
Globally, gender inequality in education is considered one of the main problems facing developing countries. Accordingly, within the context of the Sustainable Development Goals (SDGs), the gender equality in education is considered one of the most challenging goals for most developing Countries (united nation). There is no doubt on the importance of educating women. Educated women are more aware of their rights, can change the culture of the community against discrimination, and have more opportunities in the political field and in decision-making that affect their society. Educated mothers are more likely to bring up their children in better way, such as to supporting equality between sons and daughters in health care, food, and learning opportunities. The qualitative improvement and decrease in number of children due to low fertility rate among educated women contribute in building human capital that leads to poverty reduction and economic growth (Qaisrani & Ahmed 2014:6). Despite the expected role of the economic growth in bridging the gender gap in education, large number of researchers highlights several factors that must complement economic growth in narrowing down the gender gap in education. Proponents of either ICT or public expenditure on education, argue that economic growth is achieved by facilitating and spreading access and widening infrastructures of ICT and increasing and spreading schools can ease access and improve the quality of education which all have statistically significant impact on gender gap in education. Supporters of globalization claim that economic growth needs to be complemented by openness, liberalization of trade, and international financial flows to increase the possibility of overcoming gender inequality in education. On the other hand, there are some doubts about the expected favorable effect on the gender gap. The economic growth will not achieve the aim of gender equality in education if there is a lack of adopting a redistributive social spending policy (Bourguignon, et al. 2008) or if the country is at the early stages of economic growth (Dollar & Gatti 1999:13). Globalization may put downward pressures on public spending, which negatively impact female education (Seguino 2007:1). ICT is still considered a luxury good for the majority of people in developing countries because of poor and costly infrastructure, illiteracy and other social obstacles (Gurumurthy 2004:23).
Participants had experience of ESD at different levels of education. Individuals suggested that they could assess what was likely to work in practice; that they could relate the proposed indicator to other initiatives such as healthy schools; that they had experience of developing their own indicators; that they could draw on developments in the regions and nations of the UK; that they had specialist expertise developed in such settings as the Higher Education
Scottish schools are expected to follow national guidelines, devised in a largely consensual process by working groups of teachers, ad visers, researc hers, adm inistrators and in- spectors. The guidelines are not prescriptive but they do establish benchmarks for attainment at different stages and set paramete rs for programmes of study. The National Guidelines for Curriculum and Assessment 5-14 resemble the National Curriculum in England and Wales in some respects. Pupils are as sessed at P rimary 4 an d Primary 7 in core curricular areas such as Language (including Gaelic) and Maths. Curriculum advice is offered in these core areas and also in broad areas such as Environmental Studies, Expressive Arts and Religious and Moral Education. The 5-14 curriculum embraces the first two years of secondary school while the third and fou rth years follow syllabus and assessment gu idelines set out in the Standard Grade Develop ment Prog ramme. P upils sit Standard Grade Examinations in chosen subjects, including Gaelic, towards the end of Fou rth Year. T hese exa minati ons are ad- ministered by the Sco ttish Qualifica tions Authority (SQA) which also has responsibility for Higher and Advanced Higher examinations which are normally sat in Fifth and Sixth year respectively. A major overhaul of Post-16 syllabus and assessment has recently been undertaken under the banne r of the High er Still Deve lopment P rogramm e. support structures At national leve l, Learnin g and Teaching Scotland, an
institutions with certainty about the future levels of funding. The cap on the number of students entering higher education was abolished in 2015–16, which is expected to lead to a 20% increase in the number of students entering higher education each year (Hillman, 2014). This is not likely to have a significant impact on the level of higher education funding per student as the vast majority of university income is fee income, which is already determined on a per-student basis. The challenge instead comes from the risk to the public finances. An increase in the number of students taking up tuition fee loans increases the government’s exposure to non-repayment. This might be particularly severe if the additional students have lower expected future earnings, and so repay less of their student loans, than the average graduate so far.
As much as it might be the product of institutional differences, the com- parative lack of responsiveness in UK health care expenditures might also be derivative of the way in which health care policies have been differently defined by UK and US policy-makers. A considerable body of literature suggests that problem definition can have a significant impact on policy- making (Cobb and Elder 1972; Rochefort and Cobb 1994). Scholars in this tradition argue that the ‘social construction’ of issues can affect policy via any of a variety of ways (Spector and Kitsuse 1977; Seidman and Rappaport 1986). Participants involved in policy-making can be affected by the redefinition of an issue (Baumgartner and Jones 1993); the active manipulation of images of conditions by competing political actors can affect how (and if) problems are dealt with by policy-makers (Stone, Deborah A. (1989) ‘Causal Stories and the Formation of Policy Agendas’. Political Science Quarterly 104 (2): 281:300); finally, and most pertinent to the current line of inquiry, the way in which a problem is defined by policy-makers is intimately linked to the means by which they deal with that problem.
In addition to the macro-economic risks, public service managers have various issues to consider when deciding where to make spending cuts locally. For example if an organisation decides to stop providing some discretionary services that may have a knock-on impact on statutory provision, which would raise questions about their legality. Cuts in some preventative areas (such as services for children or young people, or some types of adult social care) may mean that other departments or agencies are faced with additional demands and effectively result in cost-shunting. In many areas it will be dificult to get local politicians to agree to cut services, but in the end some compromise will need to be reached. Cuts to budgets such as corporate training or ‘back ofice’ areas are likely to store up problems for the future, as organisations could face a shortage of people with the right skills and experience to take them forward. Any redundancies need to be taken in the context of a robust workforce strategy. Some cuts will have a direct impact on the local economy, particularly in areas that are relatively more dependent upon public expenditure, such as Scotland, Northern Ireland, Northern England and the West Midlands.
The efficacy of public spending is considered a major issue for policymakers. Related to the formation of human capital, it is important to examine how public spending on education influences educational outcomes. Although public spending would be expected to increase the supply of education, it is not clear if this spending really improves economic efficiency through human capital formation. With respect to this issue, a number of case studies have suggested that the performance of public school students is worse than that of private school students (e.g., Bedi and Garg, 2000; Lassibille and Tan, 2003). The association between public educationspending and educational outcomes is ambiguous, possibly due to the lack of incentives for both teachers and students (Hanushek, 2003). Supporting empirical study results, theoretical studies suggest that public spending on education increases enrollment but decreases incentives for student achievement (Blankenau and Camera, 2009). When educational outcomes are considered, quantity as well as quality are considered important.