State-guided entrepreneurship: A case study

The premise that active engagement by the state in business is crucial for small, developing economies for global competitiveness is based on the assumption that the state has the wherewithal to support such competitiveness. This paper advocates the view that governments of developing economies should be involved in business. While this view goes against the trend of popular and current thinking of the free market economy and a non-interventionist government, it needs to be recognized that such ideals are beyond many struggling, developing economies whose space in the global economy is heavily constricted by the presence of the developed economies. Using Singapore, more specifically, its government-owned company Temasek Holdings, as a case study, this paper argues that the concept of state-guided entrepreneurship has beenapplied successfully based on the hypothesis offered in this paper

Contours and conflicts in tax design: principles and international practice

Tax design is said to be based on certain principles comprising efficiency of resource allocation despite taxation’s distortionary effects, maintenance or encouragement of equity among taxpayers, and assisting in macro-economic stabilisation. Other safeguards are a tax system’s revenue productivity, clarity of taxation law, ease of tax compliance, and facilitation of tax administration. Common experience reveals, however, that no tax structure complies with these criteria all at once, for the principles tend to conflict with one another. The term reform is variously used by authors and across tax professions — economists, legal experts, accountants, administrators — their emphasis varying significantly. Bridging these gaps remains a crucial challenge. Empirical evidence also suggests that when a new administration takes over, it puts its own stamp on tax policy, egged on by lobbyists who were adversely affected in earlier change cycles. And, with the internationalisation of taxation, a country’s tax structure gets affected by developments in political or trading blocs. With this background, this paper points towards vacillations and drifts in the way tax changes occur. Consumption taxes (VAT/GST), production taxes such as excises, environment taxes, and user charges, as well as direct taxes including income and wealth taxes, and their component taxes on dividends, capital gains, cash-flow, presumptive bases, minimum tax payments, and emerging factors in international taxation, are taken up. In conclusion, the effects of taxes go beyond narrow economic aspects. Legal, accountancy or administrative aspects carry important implications. The glass wall between tax economics and tax law or accountancy, and between tax economics and tax administration, if removed, would generate an awareness with beneficial crossover effects. Then tax reform can be discussed on the same plane and be implemented with comparable understandings

Scalable Asymptotically-Optimal Multi-Robot Motion Planning

Finding asymptotically-optimal paths in multi-robot motion planning problems could be achieved, in principle, using sampling-based planners in the composite configuration space of all of the robots in the space. The dimensionality of this space increases with the number of robots, rendering this approach impractical. This work focuses on a scalable sampling-based planner for coupled multi-robot problems that provides asymptotic optimality. It extends the dRRT approach, which proposed building roadmaps for each robot and searching an implicit roadmap in the composite configuration space. This work presents a new method, dRRT* , and develops theory for scalable convergence to optimal paths in multi-robot problems. Simulated experiments indicate dRRT* converges to high-quality paths while scaling to higher numbers of robots where the naive approach fails. Furthermore, dRRT* is applicable to high-dimensional problems, such as planning for robot manipulatorsComment: 8 pages, 12 figures, submitted to the first International Symposium on Multi-Robot and Multi-Agent Systems (MRS