1,720,999 research outputs found
Distinguishing between Endogenous and Exogenous Price Volatility in Food Security Assessment: An Empirical Nonlinear Dynamics Approach
We propose an empirical scheme—based on nonlinear dynamics—for diagnosing real-world market dynamics from observed price series data.
The scheme distinguishes between endogenous and exogenous volatility in observed price series, tests whether endogenous volatility is generated by low-dimensional deterministic market dynamics, simulates these dynamics with a phenomenological market model, and models extreme volatility probabilistically. These diagnostics allow policymakers to make an empirically-informed determination of whether laissez-faire or interventionist policies are most promising in reducing price volatility in particular cases. We apply the diagnostic scheme to provide compelling empirical evidence that observed volatility in organic apple, pear, orange, and lemon prices at the Milano (Italy) Ipercoop is due to endogenous market dynamics governed by low-dimensional nonlinear behavior. The implication for food policy is that this inherently unstable market cannot be relied upon to systematically stabilize observed price volatility from random exogenous shocks. There may be scope for public interventions targeted to increasing the flexibility of organic fruit producers in responding to changing market conditions
Reconstructing deterministic economic dynamics from volatile time series data
Economists conventionally attribute observed volatility in economic time series data to exogenous random shocks that agitate otherwise stable real-world markets; and consequently, model volatility with a variety of linear-stochastic and probabilistic methods. However, some economists have recognized another possible explanation for volatility: Markets may be intrinsically unstable, and we might be able to model attending volatility parsimoniously with low-dimensional, nonlinear, deterministic dynamic models without resorting to stochastic inputs. Whether observed volatility is generated by inherently stable or unstable markets has serious policy implications. Will laissez-faire policies suffice to dampen volatility because markets are self-correcting, or are interventionist policies required? This chapter introduces nonlinear time series analysis (NLTS)—a collection of methods developed in mathematical physics to diagnose the source of real-world volatility from observed time series data. Depending on data quality, economists can potentially use NLTS to reconstruct phase-space market dynamics and extract equations of motion from a single price series
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Judicial resolution of resource-use conflicts arising from sedimentation management in dam/reservoir projects A law and economics approach
The loss of the world’s reservoir capacity to sedimentation is catalyzing a paradigm shift toward managing dam/reservoir projects as renewable resources. This requires altering dam operations to stabilize storage capacity by releasing sediment downstream. Legal uncertainty regarding whether dam owners are liable for damages to surrounding property interests due to altered dam operations provides a significant disincentive for dam owners to engage in sustainable sedimentation management. We formulate an analytical framework that considers who courts should entitle, or give a right to prevail, to generate the greatest social-economic benefits from sedimentation management
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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