The impacts of carbon emissions on global manufacturing value chain relocation: Theoretical and empirical development of a meso-level model

As a stark contrast to the diminishing media profile of the UN climate change talks, the global manufacturers appear to have become more carbon aware than ever before. Carbon audits have been carried out within many corporations to assess the carbon intensity of production processes. This is partly to address cost issues of the present (i.e. the recent rise in fossil fuel prices) and of the future (e.g. new carbon related taxes and trade tariffs). Moreover, the adoption of low carbon, clean manufacturing processes has become an increasingly prominent part of branding for many products, which could affect market share and business performance in ways that go beyond questions of cost competitiveness. How will this carbon awareness affect the configuration of the value chains of global manufacturing? Will the individual manufacturers’ decisions lead to an effective reduction of total carbon emissions at the global value chain scale? Our paper aims to answer these questions through developing a theoretical model and testing it empirically through case studies of global value chains. The model accounts explicitly costs of energy, carbon, other intermediate inputs and primary inputs in the production and transport of each component, product assembly and delivery to the market. Much work has been done on the value chain location problem – e.g. on the production unbundling among different countries from a macro-economic perspective, or on operations management at the microscopic or individual manufacturer level. It is only until recently that the economic and technology aspects have been combined in the study of global value chains (for example in the paper by Baldwin and Venables in last year’s ERSA Congress). The appropriate spatial scale for our research questions would appear to be at a meso-level: i.e. the model goes beyond the micro-level operational analysis of a single plant to cover the entire value chain for a given product, but does not cover the full interactions at the macro level. This perspective is relatively rare in the literature and provides a tool that connects the micro level and macro level perspectives.

Representation Theorems for Quadratic F{\cal F}-Consistent Nonlinear Expectations

In this paper we extend the notion of ``filtration-consistent nonlinear expectation" (or "${\cal F}$-consistent nonlinear expectation") to the case when it is allowed to be dominated by a $g$-expectation that may have a quadratic growth. We show that for such a nonlinear expectation many fundamental properties of a martingale can still make sense, including the Doob-Meyer type decomposition theorem and the optional sampling theorem. More importantly, we show that any quadratic ${\cal F}$-consistent nonlinear expectation with a certain domination property must be a quadratic $g$-expectation. The main contribution of this paper is the finding of the domination condition to replace the one used in all the previous works, which is no longer valid in the quadratic case. We also show that the representation generator must be deterministic, continuous, and actually must be of the simple form

Impacts of road pricing upon travel demand in an integral city region: A case study of London and its surrounding regions

This paper aims to study ways in which the impacts of road pricing upon travel demand can be examined in the wider city region, with a view to inform the design and possible future adaptations of road charges. Its theoretical framework incorporates the medium to long term impact of transport costs (including road charging) upon business location and commuting patterns. A case study is carried out on London and its surrounding regions, through a review of existing evidence and a set of simulation tests using a land use/transport model that has been calibrated to represent realistic travel demand elasticities. The new feature of these simulation tests is that they account for business productivity effects as well as land use/transport interaction. A generic, city-region wide marginal social cost pricing scheme is estimated together with different land use development scenarios to identify directions and range of the effects. The model results show that the social marginal cost based road pricing scheme can have significant long term impacts upon travel demand if they trigger land use changes, which could either enhance or negate the initial travel time savings and reliability benefits. Note: an extended abstract has been previously submitted via email to convenor

Upper bounds on the Natarajan dimensions of some function classes

The Natarajan dimension is a fundamental tool for characterizing multi-class PAC learnability, generalizing the Vapnik-Chervonenkis (VC) dimension from binary to multi-class classification problems. This work establishes upper bounds on Natarajan dimensions for certain function classes, including (i) multi-class decision tree and random forests, and (ii) multi-class neural networks with binary, linear and ReLU activations. These results may be relevant for describing the performance of certain multi-class learning algorithms.Comment: To appear at IEEE ISIT 202