Quantifying the Energy & carbon emissions implications of a 10% electric vehicles target

EU Directive 2009/28/EC on Renewable Energy requires each Member State to ensure 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020 (10% RES-T target). In addition to the anticipated growth in biofuels, this target is expected to be met by the increased electrification of transport coupled with a growing contribution from renewable energy to electricity generation. Energy use in transport accounted for nearly half of Ireland’s total final energy demand and about a third of energy-related carbon dioxide emissions in 2007. Energy use in transport has grown by 6.3% per annum on average in the period 1990 – 2007. This high share and fast growth relative to other countries highlights the challenges Ireland faces in meeting ambitious renewable energy targets. The Irish Government has set a specific target for Electric Vehicles (EV) as part of its strategy to deliver the 10% RES-T target. By 2020, 10% of all vehicles in its transport fleet are to be powered by electricity. This paper quantifies the impacts on energy and carbon dioxide emissions of this 10% EV target by 2020. In order to do this an ‘EV Car Stock’ model was developed to analyse the historical and future make-up of the passenger car portion of the fleet to 2025. Three scenarios for possible take-up in EVs were examined and the associated energy and emissions impacts are quantified. These impacts are then compared to Ireland’s 10% RES-T target and greenhouse gas (GHG) emissions reduction targets for 2020. Two key findings of the study are that the 10% EV target contributes 1.7% to the 10% RES-T target by 2020 and 1.4% to the 20% reduction in Non-ETS emissions by 2020 relative to 2005.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Stock-recruitment relations controlled by feeding interactions alone

Stock-recruitment (S-R) relationships are the centrepiece of fisheries management aimed at achieving maximum sustainable yield (MSY). Here we consider the possibility that the density dependence evident in S-R relations is controlled by feeding interactions alone. We simulate a food-web model with dynamic representations of intra- and interspecific size structure and a linear relation between food intake and hatchling production of adults. Population sizes of individual stocks are modified by imposing additional mortality. The predominant functional forms and the steepness of resulting S-R relationships agree well with observations. We conclude that recruitment is plausibly regulated by feeding interactions alone.

Avoiding Negligence and Profusion: The failure of the Joint-Stock form in the Anglo-Indian Tea Trade, 1840-1870

In the 19th century, firms operating in the Anglo-Indian tea trade were organised using a variety ownership forms including the partnership, joint-stock and a combination of the two known as the Managing agency. Faced with both an increasing need for fixed capital and high agency costs caused by the distance between owners and managers, the firms adapted and increasingly adopted the hybrid managing agency model to overcome these problems. Using new data from Calcutta and Bengal Commercial Registers and detailed case studies of the Assam Company and Gillanders, Arbuthnot and Co, this paper demonstrates that British entrepreneurs did not see the choice of ownership as a dichotomy or firm boundaries as fixed, but instead innovatively drew on the strengths of different forms of ownership to compete and grow successfully.

Identifying the relative importance of stock characteristics

There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.

The Adaptiveness in Stock Markets: Testing the Stylized Facts in the DAX 30

By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.