http://hdl.handle.net/2072/190 http://www.recercat.net/retrieve/3365 http://hdl.handle.net/2072/190 Search the Channel s http://www.recercat.net/simple-search http://hdl.handle.net/2072/9971 title: A Dynamic Analysis of Human Welfare in a Warming Planet authors: Llavador, Humberto; Roemer, John E.; Silvestre i Benach, Joaquim <br>abstract: Anthropogenic greenhouse gas (GHG) emissions have caused atmospheric concentrations with no precedents in the last half a million years, inducing serious uncertainties about future climates and their effects on human welfare. Recent climate science supports the view that the climate stabilization will require very low GHG emissions in the future. We ask: Is a path of low emissions compatible with sustainable levels of human welfare? With steady growth in human quality of life? Addressing these questions requires both defining welfare criteria and empirically estimating the possible paths of the economy. We specify and calibrate a dynamic model with four intertemporal links: education, physical capital, knowledge and the environment. In line with Nordhaus (2008a) and with the Stern Review (2007), we assume that GHG emissions allow increased production, while a higher stock of atmospheric carbon decreases production. Our index of human welfare, which we call quality of life (QuoL), emphasizes education, knowledge, and the environment, affected by greenhouse gas emissions, in addition to consumption and leisure. Thus, we avoid a Consumptionist Fallacy - that welfare depends only on commodity consumption and perhaps leisure. We reject discounted utilitarianism as a normative criterion, and consider two alternatives. The first is an intergenerational maximin criterion, which maximizes the quality of life of the first generation subject to maintaining at least that level for all successive generations. The second is human development optimization, that seeks the maximization of the QuoL of the first generation subject to achieving a given, constant rate of growth in all subsequent generations. Hence, our analysis focuses on a human notion of sustainability, as opposed to the conventional "green" sustainability, limited to keeping the quality of the environment constant. Because our dynamic optimization programs defy explicit analytical solutions, our approach has been computational. As a benchmark, we consider a simple model with physical and human capital, for which we prove a turnpike theorem. We then devise a computational algorithm inspired by the turnpike property to construct feasible, although not necessarily optimal, paths in the more complex and realistic model. Our analysis indicates that, with GHG emission paths entailing very low emissions in the future, positive rates of growth in QuoL are possible while the first generation experiences a QuoL higher than the historical reference level. We also observe a tradeoff between the quality of life of the first generation and the rate of growth in the quality of life. Yet Generation 1's sacrifice for the sake of a higher growth rate appears to be small. The paths that we compute involve investments in knowledge at noticeably higher levels than in the past. <br> http://hdl.handle.net/2072/9970 title: A New Method for Constructing Exact Tests without Making any Assumptions authors: Schlag, Karl H. <br>abstract: We present a new method for constructing exact distribution-free tests (and confidence intervals) for variables that can generate more than two possible outcomes. This method separates the search for an exact test from the goal to create a non- randomized test. Randomization is used to extend any exact test relating to means of variables with finitely many outcomes to variables with outcomes belonging to a given bounded set. Tests in terms of variance and covariance are reduced to tests relating to means. Randomness is then eliminated in a separate step. This method is used to create confidence intervals for the difference between two means (or variances) and tests of stochastic inequality and correlation. <br> http://hdl.handle.net/2072/9969 title: Emotion and reason in everyday risk perception authors: Hogarth, Robin M.; Portell Vidal, Mariona; Cuxart i Jardí, Anna; Kolev, Gueorgui I. <br>abstract: The importance of emotion in risk perception has been well documented in field and experimental studies. However, little is known about its role in everyday life. On thirty occasions over ten consecutive working days, ninety-four participants were prompted at random - via mobile telephones - to report on their emotions and to assess perceived risks. Subsequently, risks associated with six occasions were re-assessed. Emotion was found to explain significant variance in risk perception over and above "reason" (assessed severity and possibility of risks) and to contribute to the tendency to assess risk lower in retrospect than when experienced. Our investigation illuminates the pervasive role of emotion in everyday risk perception and the value and feasibility of collecting meaningful samples of naturally occurring behavior with simple technology. <br> http://hdl.handle.net/2072/9968 title: Measuring Subcompositional Incoherence authors: Greenacre, Michael J. <br>abstract: Subcompositional coherence is a fundamental property of Aitchison's approach to compositional data analysis, and is the principal justification for using ratios of components. We maintain, however, that lack of subcompositional coherence, that is incoherence, can be measured in an attempt to evaluate whether any given technique is close enough, for all practical purposes, to being subcompositionally coherent. This opens up the field to alternative methods, which might be better suited to cope with problems such as data zeros and outliers, while being only slightly incoherent. The measure that we propose is based on the distance measure between components. We show that the two-part subcompositions, which are the most sensitive to subcompositional incoherence, can be used to establish a distance matrix which can be directly compared with the pairwise distances in the full composition. The closeness of these two matrices can be quantified using a stress measure that is common in multidimensional scaling, providing a measure of subcompositional incoherence. Furthermore, we strongly advocate introducing weights into this measure, where rarer components are weighted proportionally less than more abundant components. The approach is illustrated using power-transformed correspondence analysis, which has already been shown to converge to logratio analysis as the power transform tends to zero. <br>