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The network industries have been undergoing a process of reform, where liberalisation is one of the main features. This thesis studies the effect of liberalisation, with and without competition, on the incumbent's incentives to innovate. A model of incumbe ...
We prove that, in a heterogeneous economy with scale-invariant utilities, the yield of a long term bond is determined by the agent with maximal expected marginal utility. We also prove that the same result holds for the long term forward rates. Furthermore ...
The design and analysis of efficient approximation schemes are of fundamental importance in stochastic programming research. Bounding approximations are particularly popular for providing strict error bounds that can be made small by using partitioning tec ...
This thesis comprises three essays on the relationship between innovation and finance. Although previous research has acknowledged the multi-faceted nature of innovation, this thesis unpacks its constituent elements, compares alternative drivers of innovat ...
Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incur ...
This article presents a new approach for improving the power-delay performance of subthreshold source-couple logic (STSCL) circuits. Using a simple two-phase pipelining technique, it is possible to increase the activity rate of STSCL gates with negligible ...
This thesis describes the development of three conceptual models built to serve as decision support tools in liberalised electricity markets. The introduction of competition, higher uncertainty and decentralised planning requires new planning and analysis ...
Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incur ...
In this paper we present a novel approach for estimating feature-space maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maximizing the likelihood function by repeated line search in the direction of th ...
The lecture will consist in two parts. First, recent advances in discrete choice models will be presented and motivated. The estimation of these advanced models involves the maximization of a nonlinear, nonconcave loglikelihood function. The nonconcavity o ...
