924 research outputs found
Efficient Estimation of Linear Asset Pricing Models with Moving-Average Errors
This paper explores in depth the nature of the conditional moment restrictions implied by log-linear intertemporal capital asset pricing models (ICAPMs) and shows that the generalized instrumental variables (GMM) estimators of these models (as typically implemented in practice) are inefficient. The moment conditions in the presence of temporally aggregated consumption are derived for two log-linear ICAPMs. The first is a continuous time model in which agents maximize expected utility. In the context of this model, we show that there are important asymmetries between the implied moment conditions for infinitely and finitely-lived securities. The second model assumes that agents maximize non-expected utility, and leads to a very similar econometric relation for the return on the wealth portfolio. Then we describe the efficiency bound (greatest lower bound for the asymptotic variances) of the CNN estimators of the preference parameters in these models. In addition, we calculate the efficient CNN estimators that attain this bound. Finally, we assess the gains in precision from using this optimal CNN estimator relative to the commonly used inefficient CMN estimators.
Exploring the key components of a contemporary hospitality servicescape: Architecture, theology and community
This article aims to contribute to the theoretical understanding of the hospitality servicescape. Through this analysis this article makes recommendations to managers on how they can set about creating a genuine sense of welcome and hospitality in a contemporary setting. It uses a case study of Jabixhûs, a “prayer house” in the northern Dutch city of Leeuwarden to investigate how religious convictions can blend with architectural expertise and a lifetime love of hosting “the other” to create a hospitable space where people can share experiences. The location of Jabixhûs on the actual historical pilgrimage route to Santiago de Compostela and socially within the community in Leeuwarden provides a combination of influences on the religious hospitality experiences offered. As well as extensive observations, a phenomenological interview was conducted with its owners, designers and operators, supplemented by feedback posted on the accommodation’s Airbnb listing. The three theoretical servicescape-related themes identified are the provision of hospitality through architecture, theology and community. Management recommendations include the suggestion that the closer personal motivations and the hospitality offering are aligned, the easier it is to deliver ameaningful experience. A clear and authentic hospitality servicescape can help to ensure that this occurs.
Keywords: architecture, community, hospitableness, hospitality, religion, servicescape, theolog
A Time Series Analysis of Representative Agent Models of Consumption andLeisure Choice Under Uncertainty
This paper investigates empirically a model of aggregate consumption and leisure decisions in which goods and leisure provide services over time. The implied time non-separability of preferences introduces an endogenous source of dynamics which affects both the co-movements in aggregate compensation and hours worked and the cross-relations between prices and quantities. These cross-relations are examined empirically using post-war monthly U.S. data on quantities, real wages and the real return on the one-month Treasury bill. We find substantial evidence against the overidentifying restrictions. The test results suggest that the orthogonality conditions associated with the representative consumer's intratemporal Euler equation underlie the failure of the model. Additionally, the estimated values of key parameters differ significantly from the values assumed in several studies of real business models. Several possible reasons for these discrepancies are discussed.
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Analysis and clustering of residential customers energy behavioral demand using smart meter data
Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster.
In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability.
Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested
Quantum gravity, the cosmological constant, and parity transformation
One of the leading issues in quantum field theory and cosmology is the
mismatch between the observed and calculated values for the cosmological
constant in Einstein's field equations of up to 120 orders of magnitude. In
this paper, we discuss new methods to potentially bridge this chasm using the
generalized uncertainty principle (GUP). We find that if quantum gravity GUP
models are the solution to this puzzle, then it may require the gravitationally
modified position operator undergo a parity transformation at high energies.Comment: 10 pages, revtex-4, 0 figures, published in PL
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Comments on the cosmological constant in generalized uncertainty models
The existence of a small, non-zero cosmological constant is one of the major
puzzles in fundamental physics. Naively, quantum field theory arguments would
imply a cosmological constant which is up to 10 times larger than the
observed one. It is believed a comprehensive theory of quantum gravity would
resolve this enormous mismatch between theory and observation. In this work, we
study the ability of generalized uncertainty principle (GUP) models, which are
phenomenologically motivated models of quantum gravity, to address the
cosmological constant problem. In particular, we focus on how these GUP models
may change the phase space of QFT, and how this affects the momentum space
integration of the zero-point energies of normal modes of fields. We point out
several issues that make it unlikely that GUP models, in their current form,
would be able to adequately address the cosmological constant problem.Comment: 10 pages, revtex, no figures. Published in Frontiers in Astronomy and
Space Science. This article is part of the Research Topic "Generalized
Uncertainty Relations: Existing Paradigms and New Approaches" edited by Dr.
Matthew Lak
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