Are Imports in Africa Responsive to Tariff Reductions?

In the 1980’s and 1990’s many African countries liberalised their trade policy, although since the mid 1990s there are countries that did not alter tariffs. This allows us to analyse the effects of trade liberalisation on the change in imports using Difference-in-Differences techniques that allow us to evaluate the impact on imports of trade liberalisation at the general and sector-specific level. During the period of study (1996-2004), Algeria (in 1997), Ethiopia (2001), Egypt (1998), Tanzania (2000) and Uganda (2000) all liberalised their tariffs. These countries act as a ‘treatment’ group. In comparison, Cameroon, Gabon and Madagascar all left their tariffs unchanged. These countries act as our ‘control’ group or counterfactual. We compare the effects on imports for liberalising countries relative to non-liberalising countries, controlling for the timing of liberalisation, trends in import capacity (country effects) and in sector imports across countries (product market effects). Overall, using three methods of measuring imports, there is little evidence that suggests imports increased for the treatment group countries relative to the control group countries. This is true at the general and sector-specific levels.Tariffs, Difference-in-Difference, liberalisation, Africa

Improved bounds on the set A(A+1)

For a subset A of a field F, write A(A + 1) for the set {a(b + 1):a,b\in A}. We establish new estimates on the size of A(A+1) in the case where F is either a finite field of prime order, or the real line. In the finite field case we show that A(A+1) is of cardinality at least C|A|^{57/56-o(1)} for some absolute constant C, so long as |A| < p^{1/2}. In the real case we show that the cardinality is at least C|A|^{24/19-o(1)}. These improve on the previously best-known exponents of 106/105-o(1) and 5/4 respectively

Prospects for the In Situ detection of Comet C/2019 Y4 ATLAS by Solar Orbiter

The European Space Agency's Solar Orbiter spacecraft will pass approximately downstream of the position of comet C/2019 Y4 (ATLAS) in late May and early June 2020. We predict that the spacecraft may encounter the comet's ion tail around 2020 May 31-June 1, and that the comet's dust tail may be crossed on 2020 June 6. We outline the solar wind features and dust grain collisions that the spacecraft's instruments may detect when crossing the comet's two tails. Solar Orbiter will also pass close to the orbital path of C/2020 F8 (SWAN) on 2020 May 22, but we believe that it is unlikely to detect any material associated with that comet.Comment: 3 pages, 1 figur

African Trade Policy in the 1990s: Political Economy or Technocratic Reforms?

The majority of African countries implemented import liberalisation in the 1990s. This paper explores factors that may explain the pattern of protection and of tariff reform. We consider political economy explanations, motivated specifically by the Grossman and Helpman (1994) model of protection in response to industry lobbies, and the possibility that reforms are technocratic. Using industry-level data for a sample of six African countries, we find limited evidence that political economy factors have influenced the pattern of tariffs or tariff reductions since the early 1990s. One result does appear frequently: relative sector size (measured by the number of employees or establishments) appears to be associated with the relative level of protection. We then explore various descriptive statistics for tariff changes in seven African countries. The analysis suggests that the pattern of tariff reductions was essentially technocratic in structure - across the board reduction in average tariffs and in the dispersion of rates, with larger proportional reductions for higher tariffs – consistent with policy reforms being guided by the World Bank. While political economy factors may have influenced the initial pattern of protection, the technocratic reforms since the early 1990s have diluted political economy influences on average and relative protection.Pattern of Protection, Tariff Reform, Political Economy, Africa

Evaluation

The importance of evaluation has grown in recent years so that this topic has become the focus of considerable policy and research interest (Oliver, 2000). As new learning technologies emerge there is a need to evaluate how these are used to support an increasingly diverse student population. All staff are now expected to carry out evaluations to account for resources or to justify strategic initiatives. Additionally, for individuals trying to instigate change, evaluation data can be important in providing relevant information to initiate, support and empower change by the “production of knowledge that makes a difference” (Patton, 1997)

Examining learning in relation to the contexts of use of ICT

Although ICT resources are commonly expected to produce uniform benefits, they are necessarily employed within pre-existing contexts of educational and social activity, and the outcome in terms of both pattern of use and learning depends on how they fit in with these. As a result, the same technology or software may have unexpectedly diverse effects, according to specific setting. If the object is to exercise control over outcome, then the conditions of use need to be planned for within the design and implementation of the technology. In order to do this, it is crucial that research gathers data on how outcomes are affected by the interplay between technology and context. This raises questions about the methods that would be appropriate for the conduct and dissemination of such research. These points are discussed in relation to three studies, one each at primary, secondary and university levels of education

The role of protostellar heating in star formation

Previous studies have shown that thermal feedback from protostars plays a key role in the process of low-mass star formation. In this thesis, we explore the effects of protostellar heating on the formation of stellar clusters. We describe new methods for modelling protostellar accretion luminosities and protostellar evolution in calculations of star formation. We then present results of a series of numerical simulations of stellar cluster formation which include these effects, and examine their impact. We begin by investigating the dependence of stellar properties on the initial density of molecular clouds. We find that the dependence of the median stellar mass on the initial density of the cloud is weaker than the dependence of the thermal Jeans mass when radiative effects are included. We suggest that including protostellar accretion luminosities and protostellar evolution may weaken this dependence further, and may account for the observed invariance of the median stellar mass in Galactic star-forming regions. Next, we investigate the effects of including accretion feedback from sink particles on the formation of small stellar groups. We find that including accretion feedback in calculations suppresses fragmentation even further than calculations that only include radiative transfer within the gas. Including feedback also produces a higher median stellar mass, which is insensitive to the sink particle accretion radius used. Finally, we compare calculations of small stellar clusters which model the evolution of protostars using a live stellar model with those which use a fixed stellar structure. We find that the dynamics of the clusters are primarily determined by the accretion luminosities of protostars, but that the relative effects of protostellar evolution depend on the accretion rate and advection of energy into the protostar. We also demonstrate how such calculations may be used to study the properties of young stellar populations

A study of how English teachers use digital tools to teach English in Norwegian lower secondary schools

This study aims to investigate teachers´ use of digital tools in lower secondary Norwegian EFL classrooms. To shed light on this topic, this study will investigate what digital tools Norwegian teachers use. Moreover, it will investigate why and how the teachers use them. In addition, the study seeks out to establish how frequent teachers use digital tools. To say something about teachers´ use of digital tools, it is best for teachers to answer for themselves. Therefore, a mixed methods approach was used through using a questionnaire and online interviews. The questionnaire consists of 183 EFL teachers from Norwegian lower secondary schools, whereas the online interview consists of 9 interviewees. The result from the questionnaire suggests that teachers face a several challenges using digital tools in the classroom. The biggest challenge is reported to be distracted students. The data indicate that the biggest benefit with digital tools is the great amount of resources available. Further, the data indicates that teachers rely on digital tools to obtain authentic material for their teaching practice. Among the tools being used, the participants mention E-books or digital texts to be the most used digital tool in their EFL teaching practice. However, the data shows there is a great variety in digital competence amongst the participants. Whereas some of the participants has additional education on the use of digital tools. Most of the participants reported to not have any additional education. This could suggest there is a great variety in formal education, and more specifically, a variety within digital competence amongst the participants in this study. Furthermore, the respondents believe students read more English on screen compared to printed text in general. However, studies show that reading on screen is less comprehensible and therefore not as effective as reading on printed material (Sparks, 2021). However, the research indicates that e-books, digital texts, and multimodal texts are widely used and might enhance reading comprehension as they are more interactive than printed texts (Fenner & Skulstad, 2020). Most (51%) participants reported using digital tools between 1-3 times per day, whereas 20% reported using digital tools more than 6 times per day. This indicates that the participants vary their use based on their own interest and digital competence. However, 1% of the participants state that they never use digital tools and only rely on the textbook