Trade wars in the TRIPS Council: Intellectual property, technology transfer, and climate change

This Chapter considers the geopolitical conflicts in respect of intellectual property, trade, and climate change in the TRIPS Agreement 1994 under the World Trade Organization (WTO). In particular, it focuses upon debates in the TRIPS Council on the topic of patent law and clean energy in 2013 and 2014. The chapter highlights the development agenda of a number of developing countries who are keen for access to clean energy to combat climate change and global warming. It also considers the mixed contributions of members of the BRICS/ BASIC group – including Brazil, India, China, and South Africa. This chapter highlights the intellectual property maximalist position of a number of developed countries on intellectual property, climate change, and trade. Seeking to overcome this conflict and stalemate, this Chapter puts forward both procedural and substantial reform options in respect of intellectual property, trade, and climate change in the TRIPS Council and the WTO. It also flags that the TRIPS Agreement 1994 could well be displaced by the rise of mega-regional trade agreements – such as the Trans-Pacific Partnership (TPP), and the Trans-Atlantic Trade and Investment Partnership (TTIP).

A new constraint programming approach for optimising a coal rail system

Because of the bottlenecking operations in a complex coal rail system, millions of dollars are costed by mining companies. To handle this issue, this paper investigates a real-world coal rail system and aims to optimise the coal railing operations under constraints of limited resources (e.g., limited number of locomotives and wagons). In the literature, most studies considered the train scheduling problem on a single-track railway network to be strongly NP-hard and thus developed metaheuristics as the main solution methods. In this paper, a new mathematical programming model is formulated and coded by optimization programming language based on a constraint programming (CP) approach. A new depth-first-search technique is developed and embedded inside the CP model to obtain the optimised coal railing timetable efficiently. Computational experiments demonstrate that high-quality solutions are obtainable in industry-scale applications. To provide insightful decisions, sensitivity analysis is conducted in terms of different scenarios and specific criteria. Keywords Train scheduling · Rail transportation · Coal mining · Constraint programming

Exploring energy-performance trade-offs for heterogeneous interconnect clustered VLIW processors

Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving clock speed, reducing energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long global wires which leads to delay in execution and significantly high energy consumption.In this paper, we propose a new instruction scheduling algorithm that exploits scheduling slacks of instructions and communication slacks of data values together to achieve better energy-performance trade-offs for clustered architectures with heterogeneous interconnect. Our instruction scheduling algorithm achieves 35% and 40% reduction in communication energy, whereas the overall energy-delay product improves by 4.5% and 6.5% respectively for 2 cluster and 4 cluster machines with marginal increase (1.6% and 1.1%) in execution time. Our test bed uses the Trimaran compiler infrastructure.

Trade Liberalization, Heterogeneous Firms and Industrial Dynamics

This master thesis studies how trade liberalization affects the firm-level productivity and industrial evolution. To do so, I built a dynamic model that considers firm-level productivity as endogenous to investigate the influence of trade on firm’s productivity and the market structure. In the framework, heterogeneous firms in the same industry operate differently in equilibrium. Specifically, firms are ex ante identical but heterogeneity arises as an equilibrium outcome. Under the setting of monopolistic competition, this type of model yields an industry that is represented not by a steady-state outcome, but by an evolution that rely on the decisions made by individual firms. I prove that trade liberalization has a general positive impact on technological adoption rates and hence increases the firm-level productivity. Besides, this endogenous technology adoption model also captures the stylized facts: exporting firms are larger and more productive than their non-exporting counterparts in the same sector. I assume that the number of firms is endogenous, since, according to the empirical literature, the industrial evolution shows considerably different patterns across countries; some industries experience large scale of firms’ exit in the period of contracting market shares, while some industries display relative stable number of firms or gradually increase quantities. The special word “shakeout” is used to describe the dramatic decrease in the number of firms. In order to explain the causes of shakeout, I construct a model where forward-looking firms decide to enter and exit the market on the basis of their state of technology. In equilibrium, firms choose different dates to adopt innovation which generate a gradual diffusion process. It is exactly this gradual diffusion process that generates the rapid, large-scale exit phenomenon. Specifically, it demonstrates that there is a positive feedback between firm’s exit and adoption, the reduction in the number of firms increases the incentives for remaining firms to adopt innovation. Therefore, in the setting of complete information, this model not only generates a shakeout but also captures the stability of an industry. However, the solely national view of industrial evolution neglects the importance of international trade in determining the shape of market structure. In particular, I show that the higher trade barriers lead to more fragile markets, encouraging the over-entry in the initial stage of industry life cycle and raising the probability of a shakeout. Therefore, more liberalized trade generates more stable market structure from both national and international viewpoints. The main references are Ederington and McCalman(2008,2009).

International Portfolio Investments and The Informational Value of Trade

A large volume of literature suggests that information asymmetry resulting from the spatial separation between investors and investments have a significant impact on the composition of investors’ domestic and international portfolios. I show that institutional factors affecting trading in tangible goods help explain a substantial portion of investors’ spatial bias. More importantly, I demonstrate that an information flow medium with breadth and richness directly linked to the bilateral commitment of resources between countries, that I measure by their trading intensity in tangible goods, is consistent with the prevailing country allocation in investors’ international portfolios.

The Relay Selection and Transmission Trade-off in Cooperative Communication Systems

A common and practical paradigm in cooperative communication systems is the use of a dynamically selected `best' relay to decode and forward information from a source to a destination. Such systems use two phases - a relay selection phase, in which the system uses transmission time and energy to select the best relay, and a data transmission phase, in which it uses the spatial diversity benefits of selection to transmit data. In this paper, we derive closed-form expressions for the overall throughput and energy consumption, and study the time and energy trade-off between the selection and data transmission phases. To this end, we analyze a baseline non-adaptive system and several adaptive systems that adapt the selection phase, relay transmission power, or transmission time. Our results show that while selection yields significant benefits, the selection phase's time and energy overhead can be significant. In fact, at the optimal point, the selection can be far from perfect, and depends on the number of relays and the mode of adaptation. The results also provide guidelines about the optimal system operating point for different modes of adaptation. The analysis also sheds new insights on the fast splitting-based algorithm considered in this paper for relay selection.

A modell of socially optimal hydro reservoir usage - yelding socially optimal outcomes in nordic electricity markets

An extensive electricity transmission network facilitates electricity trading between Finland, Sweden, Norway and Denmark. Currently most of the area's power generation is traded at NordPool, where the trading volumes have steadily increased since the early 1990's, when the exchange was founded. The Nordic electricity is expected to follow the current trend and further integrate with the other European electricity markets. Hydro power is the source for roughly a half of the supply in the Nordic electricity market and most of the hydro is generated in Norway. The dominating role of hydro power distinguishes the Nordic electricity market from most of the other market places. Production of hydro power varies mainly due to hydro reservoirs and demand for electricity. Hydro reservoirs are affected by water inflows that differ each year. The hydro reservoirs explain remarkably the behaviour of the Nordic electricity markets. Therefore among others, Kauppi and Liski (2008) have developed a model that analyzes the behaviour of the markets using hydro reservoirs as explanatory factors. Their model includes, for example, welfare loss due to socially suboptimal hydro reservoir usage, socially optimal electricity price, hydro reservoir storage and thermal reservoir storage; that are referred as outcomes. However, the model does not explain the real market condition but rather an ideal situation. In the model the market is controlled by one agent, i.e. one agent controls all the power generation reserves; it is referred to as a socially optimal strategy. Article by Kauppi and Liski (2008) includes an assumption where an individual agent has a certain fraction of market power, e.g. 20 % or 30 %. In order to maintain the focus of this thesis, this part of their paper is omitted. The goal of this thesis is two-fold. Firstly we expand the results from the socially optimal strategy for years 2006-08, as the earlier study finishes in 2005. The second objective is to improve on the methods from the previous study. This thesis results several outcomes (SPOT-price and welfare loss, etc.) due to socially optimal actions. Welfare loss is interesting as it describes the inefficiency of the market. SPOT-price is an important output for the market participants as it often has an effect on end users' electricity bills. Another function is to modify and try to improve the model by means of using more accurate input data, e.g. by considering pollution trade rights effect on input data. After modifications to the model, new welfare losses are calculated and compared with the same results before the modifications. The hydro reservoir has the higher explanatory significance in the model followed by thermal power. In Nordic markets, thermal power reserves are mostly nuclear power and other thermal sources (coal, natural gas, oil, peat). It can be argued that hydro and thermal reservoirs determine electricity supply. Roughly speaking, the model takes into account electricity demand and supply, and several parameters related to them (water inflow, oil price, etc.), yielding finally the socially optimal outcomes. The author of this thesis is not aware of any similar model being tested before. There have been some other studies that are close to the Kauppi and Liski (2008) model, but those have a somewhat different focus. For example, a specific feature in the model is the focus on long-run capacity usage that differs from the previous studies on short-run market power. The closest study to the model is from California's wholesale electricity markets that, however, uses different methodology. Work is constructed as follows.