Towards a General Large Sample Theory for Regularized Estimators

We present a general framework for studying regularized estimators; such estimators are pervasive in estimation problems wherein "plug-in" type estimators are either ill-defined or ill-behaved. Within this framework, we derive, under primitive conditions, consistency and a generalization of the asymptotic linearity property. We also provide data-driven methods for choosing tuning parameters that, under some conditions, achieve the aforementioned properties. We illustrate the scope of our approach by presenting a wide range of applications

Progressive and merging-proof taxation

We investigate the implications and logical relations between progressivity (a principle of distributive justice) and merging-proofness (a strategic principle) in taxation. By means of two characterization results, we show that these two principles are intimately related, despite their different nature. In particular, we show that, in the presence of continuity and consistency (a widely accepted framework for taxation) progressivity implies merging-proofness and that the converse implication holds if we add an additional strategic principle extending the scope of merging-proofness to a multilateral setting. By considering operators on the space of taxation rules, we also show that progressivity is slightly more robust than merging-proofness.taxation, progressivity, merging-proofness, consistency, operators

The Aesthetics of Theory Selection and the Logics of Art

Philosophers of science discuss whether theory selection depends on aesthetic judgments or criteria, and whether these putatively aesthetic features are genuinely extra-epistemic. As examples, judgments involving criteria such as simplicity and symmetry are often cited. However, other theory selection criteria, such as fecundity, coherence, internal consistency, and fertility, more closely match those criteria used in art contexts and by scholars working in aesthetics. Paying closer attention to the way these criteria are used in art contexts allows us to understand some evaluative and developmental practices in scientific theory selection as genuinely aesthetic, enlarging the scope of the goals of science

Information encountering re-encountered: A conceptual re-examination of serendipity in the context of information acquisition

Purpose In order to understand the totality, diversity and richness of human information behavior, increasing research attention has been paid to examining serendipity in the context of information acquisition. However, several issues have arisen as this research subfield has tried to find its feet; we have used different, inconsistent terminology to define this phenomenon (e.g. information encountering, accidental information discovery, incidental information acquisition), the scope of the phenomenon has not been clearly defined and its nature was not fully understood or fleshed-out. Design/methodology/approach In this paper, information encountering (IE) was proposed as the preferred term for serendipity in the context of information acquisition. Findings A reconceptualized definition and scope of IE was presented, a temporal model of IE and a refined model of IE that integrates the IE process with contextual factors and extends previous models of IE to include additional information acquisition activities pre- and postencounter. Originality/value By providing a more precise definition, clearer scope and richer theoretical description of the nature of IE, there was hope to make the phenomenon of serendipity in the context of information acquisition more accessible, encouraging future research consistency and thereby promoting deeper, more unified theoretical development

Clockwork SUSY: Supersymmetric Ward and Slavnov-Taylor Identities At Work in Green's Functions and Scattering Amplitudes

We study the cancellations among Feynman diagrams that implement the Ward and Slavnov-Taylor identities corresponding to the conserved supersymmetry current in supersymmetric quantum field theories. In particular, we show that the Faddeev-Popov ghosts of gauge- and supersymmetries never decouple from the physical fields, even for abelian gauge groups. The supersymmetric Slavnov-Taylor identities provide efficient consistency checks for automatized calculations and can verify the supersymmetry of Feynman rules and the numerical stability of phenomenological predictions simultaneously.Comment: 12 pages, feynmp.sty. References added, minor typos corrected and clarified the scope of the paper in the introduction, published versio

Superparamagnetic relaxation in Cu_{x}Fe_{3-x}O_{4} (x=0.5 and x=1) nanoparticles

The scope of this article is to report very detailed results of the measurements of magnetic relaxation phenomena in the new Cu$_{0.5}$Fe$_{2.5}$O$_{4}$ nanoparticles and known CuFe$_{2}$O$_{4}$ nanoparticles. The size of synthesized particles is (6.5$\pm$1.5)nm. Both samples show the superparamagnetic behaviour, with the well-defined phenomena of blocking of magnetic moment. This includes the splitting of zero-field-cooled and field-cooled magnetic moment curves, dynamical hysteresis, slow quasi-logarithmic relaxation of magnetic moment below blocking temperature. The scaling of the magnetic moment relaxation data at different temperatures confirms the applicability of the simple thermal relaxation model. The two copper-ferrites with similar structures show significantly different magnetic anisotropy density and other magnetic properties. Investigated systems exhibit the consistency of all obtained results.Comment: 18 pages, 8 figure

Learning as a rational foundation for macroeconomics and finance

Expectations play a central role in modern macroeconomics. The econometric learning approach, in line with the cognitive consistency principle, models agents as forming expectations by estimating and updating subjective forecasting models in real time. This approach provides a stability test for RE equilibria and a selection criterion in models with multiple equilibria. Further features of learning – such as discounting of older data, use of misspecified models or heterogeneous choice by agents between competing models – generate novel learning dynamics. Empirical applications are reviewed and the roles of the planning horizon and structural knowledge are discussed. We develop several applications of learning with relevance to macroeconomic policy: the scope of Ricardian equivalence, appropriate specification of interest-rate rules, implementation of price-level targeting to achieve learning stability of the optimal RE equilibrium and whether, under learning, price-level targeting can rule out the deflation trap at the zero lower bound.cognitive consistency; E-stability; least-squares; persistent learning dynamics; business cycles; monetary policy; asset prices

Cluster science from ROSAT to eROSITA

Galaxy clusters are one of the important cosmological probes to test the consistency of the observable structure and evolution of our Universe with the predictions of specific cosmological models. We use results from our analysis of the X-ray flux-limited REFLEX cluster sample from the ROSAT All-Sky Survey to illustrate the constraints on cosmological parameters that can be achieved with this approach. The upcoming eROSITA project of the Spektrum-Roentgen-Gamma mission will increase these capabilities by two orders of magnitude and importantly also increase the redshift range of such studies. We use the projected instrument performance to make predictions on the scope of the eROSITA survey and the potential of its exploitation.Comment: 5 pages, 8 figures, accepted for publication in Astronomische Nachrichten; the proceedings of the XMM-Newton Science Workshop: "Galaxy Clusters as Giant Cosmic Laboratories" at ESAC, Madrid, Spain, 21-23 May 201