Comparing the conditions for small business and entrepreneurship in Sweden and Australia: Lessons for the European Charter for Small Enterprises

A growing body of literature is concerned with explaining cross-national performance of small business and entrepreneurs in advanced economies. This literature has considered a range of policy and institutional variables which create an environment supportive of small firms and entrepreneurial activities including macroeconomic variables such as taxation, labour market regulation, social security and income policy; regulatory factors such as establishment legislation, bankruptcy policy, administrative burdens, compliance costs, deregulation and competition policy; and cultural factors such as social and cultural norms that support entrepreneurship. However, this literature has not always distinguished between the policy environment of small firms operating in different industry sectors. The purpose of this paper is to examine the institutional and policy environment of small firms in knowledge intensive sectors. The characteristics of the business environment of particular relevance to knowledge intensive firms are somewhat different from the conditions for entrepreneurship and small business success more generally. This paper compares the science, technology and industry infrastructure of Australia, Denmark, Sweden with other OECD countries. The purpose of the paper is to identify cross-national differences in the business environment of small knowledge intensive firms. The paper seeks to explore whether particular institutional environments appear to be more supportive of small firms in knowledge intensive sectors.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

It's all very well, in theory: Theoretical perspectives and their applications in contemporary pedagogical research

Current debates about educational theory are concerned with the relationship between knowledge and power and thereby issues such as who possesses a truth and how have they arrived at it, what questions are important to ask, and how should they best be answered. As such, these debates revolve around questions of preferred, appropriate, and useful theoretical perspectives. This paper overviews the key theoretical perspectives that are currently used in physical education pedagogy research and considers how these inform the questions we ask and shapes the conduct of research. It also addresses what is contested with respect to these perspectives. The paper concludes with some cautions about allegiances to and use of theories in line with concerns for the applicability of educational research to pressing social issues.

Protein crystallography and examples of its applications in medicinal chemistry

The field of protein crystallography inspires and enthrals, whether it be for the beauty and symmetry of a perfectly formed protein crystal, the unlocked secrets of a novel protein fold, or the precise atomic-level detail yielded from a protein-ligand complex. Since 1958, when the first protein structure was solved, there have been tremendous advances in all aspects of protein crystallography, from protein preparation and crystallisation through to diffraction data measurement and structure refinement. These advances have significantly reduced the time required to solve protein crystal structures, while at the same time substantially improving the quality and resolution of the resulting structures. Moreover, the technological developments have induced researchers to tackle ever more complex systems, including ribosomes and intact membrane-bound proteins, with a reasonable expectation of success. In this review, the steps involved in determining a protein crystal structure are described and the impact of recent methodological advances identified. Protein crystal structures have proved to be extraordinarily useful in medicinal chemistry research, particularly with respect to inhibitor design. The precise interaction between a drug and its receptor can be visualised at the molecular level using protein crystal structures, and this information then used to improve the complementarity and thus increase the potency and selectivity of an inhibitor. The use of protein crystal structures in receptor-based drug design is highlighted by (i) HIV protease, (ii) influenza virus neuraminidase and (iii) prostaglandin H-2-synthetase. These represent, respectively, examples of protein crystal structures that (i) influenced the design of drugs currently approved for use in the treatment of HIV infection, (ii) led to the design of compounds currently in clinical trials for the treatment of influenza infection and (iii) could enable the design of highly specific non-steroidal anti-inflammatory drugs that lack the common side-effects of this drug class.

Family size, economics and child gender preference: A case study in the Nyeri district of Kenya

Kenyan women have more children, especially in rural areas, than in most developing nations. This is widely believed to be an impediment to Kenya’s economic development. Thus, factors influencing family size in the Kenyan context are important for its future. A brief review of economic theories of fertility leads to the conclusion that both economics and social/cultural factors must be considered simultaneously when examining factors that determine the number of children in a family. The need to do this is borne out in Kenya’s situation by utilising responses from a random sample of rural households in the Nyeri district of Kenya. Economic and social/cultural factors intertwine to influence family sizes in this district. After providing a summary of the main statistical results from the survey, we use multiple regression analysis to explore the influences of a woman’s age, level of education, whether she has outside employment, whether the family keeps livestock, whether she expresses a preference for more boys than girls, whether the family uses only family labour (including child labour) and the size of the farm, which is used as a proxy for family income. It was found that preference for male children has an important positive influence on family size in this district. Women were found to have greater preference for male children than their male counterparts possibly because of their fear of being disinherited if they do not produce an heir for their husbands. Preference for sons was also found in allocation of human capital resources at the household level in that the female respondents were found to have lower levels of education than their male counterparts. Various long-term policies are outlined that may help to reduce the number of offspring of women in Kenya.