Individual Decision-Making and Inflation Persistence

The traditional task of a central bank is to preserve price stability and, in doing so, not to impair the real economy more than necessary. To meet this challenge, it is of great relevance whether inflation is only driven by inflation expectations and the current output gap or whether it is, in addition, influenced by past inflation. In the former case, as described by the New Keynesian Phillips curve, the central bank can immediately and simultaneously achieve price stability and equilibrium output, the so-called ‘divine coincidence’ (Blanchard and Galí 2007). In the latter case, the achievement of price stability is costly in terms of output and will be pursued over several periods. Similarly, it is important to distinguish this latter case, which describes ‘intrinsic’ inflation persistence, from that of ‘extrinsic’ inflation persistence, where the sluggishness of inflation is not a ‘structural’ feature of the economy but merely ‘inherited’ from the sluggishness of the other driving forces, inflation expectations and output. ‘Extrinsic’ inflation persistence is usually considered to be the less challenging case, as policy-makers are supposed to fight against the persistence in the driving forces, especially to reduce the stickiness of inflation expectations by a credible monetary policy, in order to reestablish the ‘divine coincidence’. The scope of this dissertation is to contribute to the vast literature and ongoing discussion on inflation persistence: Chapter 1 describes the policy consequences of inflation persistence and summarizes the empirical and theoretical literature. Chapter 2 compares two models of staggered price setting, one with a fixed two-period duration and the other with a stochastic duration of prices. I show that in an economy with a timeless optimizing central bank the model with the two-period alternating price-setting (for most parameter values) leads to more persistent inflation than the model with stochastic price duration. This result amends earlier work by Kiley (2002) who found that the model with stochastic price duration generates more persistent inflation in response to an exogenous monetary shock. Chapter 3 extends the two-period alternating price-setting model to the case of 3- and 4-period price durations. This results in a more complex Phillips curve with a negative impact of past inflation on current inflation. As simulations show, this multi-period Phillips curve generates a too low degree of autocorrelation and too early turnings points of inflation and is outperformed by a simple Hybrid Phillips curve. Chapter 4 starts from the critique of Driscoll and Holden (2003) on the relative real-wage model of Fuhrer and Moore (1995). While taking the critique seriously that Fuhrer and Moore’s model will collapse to a much simpler one without intrinsic inflation persistence if one takes their arguments literally, I extend the model by a term for inequality aversion. This model extension is not only in line with experimental evidence but results in a Hybrid Phillips curve with inflation persistence that is observably equivalent to that presented by Fuhrer and Moore (1995). In chapter 5, I present a model that especially allows to study the relationship between fairness attitudes and time preference (impatience). In the model, two individuals take decisions in two subsequent periods. In period 1, both individuals are endowed with resources and are able to donate a share of their resources to the other individual. In period 2, the two individuals might join in a common production after having bargained on the split of its output. The size of the production output depends on the relative share of resources at the end of period 1 as the human capital of the individuals, which is built by means of their resources, cannot fully be substituted one against each other. Therefore, it might be rational for a well-endowed individual in period 1 to act in a seemingly ‘fair’ manner and to donate own resources to its poorer counterpart. This decision also depends on the individuals’ impatience which is induced by the small but positive probability that production is not possible in period 2. As a general result, the individuals in the model economy are more likely to behave in a ‘fair’ manner, i.e., to donate resources to the other individual, the lower their own impatience and the higher the productivity of the other individual. As the (seemingly) ‘fair’ behavior is modelled as an endogenous outcome and as it is related to the aspect of time preference, the presented framework might help to further integrate behavioral economics and macroeconomics.

The Wrong Kind of Lean: Over-Commitment and Under-Represented Skills on Technology Teams

This paper reports on results from five companies in the aerospace and automotive industries to show that over-commitment of technical professionals and under-representation of key skills on technology development and transition teams seriously impairs team performance. The research finds that 40 percent of the projects studied were inadequately staffed, resulting in weaker team communications and alignment. Most importantly, the weak staffing on these teams is found to be associated with a doubling of project failure rate to reach full production. Those weakly staffed teams that did successfully insert technology into production systems were also much more likely than other teams to have development delays and late engineering changes. The conclusion suggests that the expense of project failure, delay and late engineering changes in these companies must greatly out-weigh the savings gained from reduced staffing costs, and that this problem is likely going to be found in other technology-intensive firms intent on seeing project budgets as a cost to be minimized rather than an investment to be maximized.

Electrical Design: A Problem for Artificial Intelligence Research

This report outlines the problem of intelligent failure recovery in a problem-solver for electrical design. We want our problem solver to learn as much as it can from its mistakes. Thus we cast the engineering design process on terms of Problem Solving by Debugging Almost-Right Plans, a paradigm for automatic problem solving based on the belief that creation and removal of "bugs" is an unavoidable part of the process of solving a complex problem. The process of localization and removal of bugs called for by the PSBDARP theory requires an approach to engineering analysis in which every result has a justification which describes the exact set of assumptions it depends upon. We have developed a program based on Analysis by Propagation of Constraints which can explain the basis of its deductions. In addition to being useful to a PSBDARP designer, these justifications are used in Dependency-Directed Backtracking to limit the combinatorial search in the analysis routines. Although the research we will describe is explicitly about electrical circuits, we believe that similar principles and methods are employed by other kinds of engineers, including computer programmers.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Central notations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform. In this way very elaborated aspects of mathematical statistics can be understood easily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating, combination of likelihood and robust M-estimation functions are simple additions/ perturbations in A2(Pprior). Weighting observations corresponds to a weighted addition of the corresponding evidence. Likelihood based statistics for general exponential families turns out to have a particularly easy interpretation in terms of A2(P). Regular exponential families form finite dimensional linear subspaces of A2(P) and they correspond to finite dimensional subspaces formed by their posterior in the dual information space A2(Pprior). The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P. The discussion of A2(P) valued random variables, such as estimation functions or likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

Analyzing shapes as compositions of distances

We propose to analyze shapes as “compositions” of distances in Aitchison geometry as an alternate and complementary tool to classical shape analysis, especially when size is non-informative. Shapes are typically described by the location of user-chosen landmarks. However the shape – considered as invariant under scaling, translation, mirroring and rotation – does not uniquely define the location of landmarks. A simple approach is to use distances of landmarks instead of the locations of landmarks them self. Distances are positive numbers defined up to joint scaling, a mathematical structure quite similar to compositions. The shape fixes only ratios of distances. Perturbations correspond to relative changes of the size of subshapes and of aspect ratios. The power transform increases the expression of the shape by increasing distance ratios. In analogy to the subcompositional consistency, results should not depend too much on the choice of distances, because different subsets of the pairwise distances of landmarks uniquely define the shape. Various compositional analysis tools can be applied to sets of distances directly or after minor modifications concerning the singularity of the covariance matrix and yield results with direct interpretations in terms of shape changes. The remaining problem is that not all sets of distances correspond to a valid shape. Nevertheless interpolated or predicted shapes can be backtransformated by multidimensional scaling (when all pairwise distances are used) or free geodetic adjustment (when sufficiently many distances are used)

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data. It contains four classes corresponding to the four different types of compositional and positive geometry (including the Aitchison geometry). It provides means for computation, plotting and high-level multivariate statistical analysis in all four geometries. These geometries are treated in an fully analogous way, based on the principle of working in coordinates, and the object-oriented programming paradigm of R. In this way, called functions automatically select the most appropriate type of analysis as a function of the geometry. The graphical capabilities include ternary diagrams and tetrahedrons, various compositional plots (boxplots, barplots, piecharts) and extensive graphical tools for principal components. Afterwards, ortion and proportion lines, straight lines and ellipses in all geometries can be added to plots. The package is accompanied by a hands-on-introduction, documentation for every function, demos of the graphical capabilities and plenty of usage examples. It allows direct and parallel computation in all four vector spaces and provides the beginner with a copy-and-paste style of data analysis, while letting advanced users keep the functionality and customizability they demand of R, as well as all necessary tools to add own analysis routines. A complete example is included in the appendix

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basic functionality has seen some conceptual improvement, containing now some facilities to work with and represent ilr bases built from balances, and an elaborated subsys- tem for dealing with several kinds of irregular data: (rounded or structural) zeroes, incomplete observations and outliers. The general approach to these irregularities is based on subcompositions: for an irregular datum, one can distinguish a “regular” sub- composition (where all parts are actually observed and the datum behaves typically) and a “problematic” subcomposition (with those unobserved, zero or rounded parts, or else where the datum shows an erratic or atypical behaviour). Systematic classification schemes are proposed for both outliers and missing values (including zeros) focusing on the nature of irregularities in the datum subcomposition(s). To compute statistics with values missing at random and structural zeros, a projection approach is implemented: a given datum contributes to the estimation of the desired parameters only on the subcompositon where it was observed. For data sets with values below the detection limit, two different approaches are provided: the well-known imputation technique, and also the projection approach. To compute statistics in the presence of outliers, robust statistics are adapted to the characteristics of compositional data, based on the minimum covariance determinant approach. The outlier classification is based on four different models of outlier occur- rence and Monte-Carlo-based tests for their characterization. Furthermore the package provides special plots helping to understand the nature of outliers in the dataset. Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator, robustness, rounded zeros

Mixing compositions and other scales

Theory of compositional data analysis is often focused on the composition only. However in practical applications we often treat a composition together with covariables with some other scale. This contribution systematically gathers and develop statistical tools for this situation. For instance, for the graphical display of the dependence of a composition with a categorical variable, a colored set of ternary diagrams might be a good idea for a first look at the data, but it will fast hide important aspects if the composition has many parts, or it takes extreme values. On the other hand colored scatterplots of ilr components could not be very instructive for the analyst, if the conventional, black-box ilr is used. Thinking on terms of the Euclidean structure of the simplex, we suggest to set up appropriate projections, which on one side show the compositional geometry and on the other side are still comprehensible by a non-expert analyst, readable for all locations and scales of the data. This is e.g. done by defining special balance displays with carefully- selected axes. Following this idea, we need to systematically ask how to display, explore, describe, and test the relation to complementary or explanatory data of categorical, real, ratio or again compositional scales. This contribution shows that it is sufficient to use some basic concepts and very few advanced tools from multivariate statistics (principal covariances, multivariate linear models, trellis or parallel plots, etc.) to build appropriate procedures for all these combinations of scales. This has some fundamental implications in their software implementation, and how might they be taught to analysts not already experts in multivariate analysis

Statistical treatment of grain-size curves and empirical distributions: densities as compositions?

The preceding two editions of CoDaWork included talks on the possible consideration of densities as infinite compositions: Egozcue and D´ıaz-Barrero (2003) extended the Euclidean structure of the simplex to a Hilbert space structure of the set of densities within a bounded interval, and van den Boogaart (2005) generalized this to the set of densities bounded by an arbitrary reference density. From the many variations of the Hilbert structures available, we work with three cases. For bounded variables, a basis derived from Legendre polynomials is used. For variables with a lower bound, we standardize them with respect to an exponential distribution and express their densities as coordinates in a basis derived from Laguerre polynomials. Finally, for unbounded variables, a normal distribution is used as reference, and coordinates are obtained with respect to a Hermite-polynomials-based basis. To get the coordinates, several approaches can be considered. A numerical accuracy problem occurs if one estimates the coordinates directly by using discretized scalar products. Thus we propose to use a weighted linear regression approach, where all k- order polynomials are used as predictand variables and weights are proportional to the reference density. Finally, for the case of 2-order Hermite polinomials (normal reference) and 1-order Laguerre polinomials (exponential), one can also derive the coordinates from their relationships to the classical mean and variance. Apart of these theoretical issues, this contribution focuses on the application of this theory to two main problems in sedimentary geology: the comparison of several grain size distributions, and the comparison among different rocks of the empirical distribution of a property measured on a batch of individual grains from the same rock or sediment, like their composition

Análisis de los programas de la agencia española de cooperación internacional para el desarrollo dirigidos a las mujeres en la lucha contra el vih/sida en mozambique (2005-2010)

En este estudio de caso pretende dar respuesta a que factores vitalizan la cooperación Española en Mozambique a través del análisis de programas como el VITA, dirigidos específicamente al desarrollo y mejoramiento de la salud en el continente Africano. Este estudio de caso se centra en el investigación de los discursos de desarrollo que se fundamentan en las políticas internacionales de cooperación , basadas en la existencia de una enfermedad como el VIH que ha puesto en manifiesto la interacción entre la esfera biológica y social , social e individual entre el fenómeno existencial y cultural, lo que fundamenta su importancia y estudio. Se ha escogido esta herramienta de investigación social, en este estudio de caso, para abordar la forma en que funciona y opera la AECID en Mozambique a través de los programas con enfoque de género encaminados al problema del VIH. Se pretende dar a conocer el desarrollo en materia de la cooperación internacional de una organización tan importante como la AECID, cuyos proyectos gozan de una gran credibilidad en cuanto a la ejecución de sus acciones y que en general dichos proyectos se adecuan a las necesidades de la población, a los objetivos de desarrollo nacionales y a las prioridades de la cooperación española.

Guía para el diagnóstico, atención integral y seguimiento de asma en niños y niñas

El Ministerio de la Protección Social encargó a la Asociación Colombiana de Neumología Pediátrica el desarrollo de una Guía Clínica sobre asma en pediatría. La Guía establece recomendaciones basadas en la mejor evidencia clínica disponible y en la racionalización del gasto. El grupo desarrollador de la guía (GDG) fue conformado por un grupo multidisciplinario que asegura que todas las áreas del conocimiento pertinentes de la enfermedad estén representadas y que toda la evidencia científica sea evaluada de forma crítica. Se aplicó la matriz de decisión: adaptación o desarrollo de novo de GPC, se eligió adaptar una o más GPC. Con base en lo anterior y con la aplicación de la matriz de decisión – adaptación o desarrollo de novo de guías de práctica clínica se decidió adaptar para Colombia las guías de atención integral de la BTS y el NAEPP, tomando como prioritaria para la adaptación la guía de atención integral de la BTS; en el área de terapia respiratoria e inhaloterapia, las preguntas se respondieron de novo por no encontrar la mejor información y aplicabilidad para nuestro medio. El GDG realizó una alianza estratégica con el Instituto de Efectividad Clínica Sanitaria (IECS) de la ciudad de Buenos Aires, este es un grupo de expertos en evaluaciones económicas de medicamentos y tecnologías sanitarias quien participó en el proceso de la elaboración de las evaluaciones económicas contenidas en la Guía y en la definición del alcance de dichas evaluaciones.

Analisis de la politica exterior china para Africa Subsahariana en materia politica y energetica. Una aproximacion a la relacion sino sudanesa. Periodo 1996 - 2005

Este trabajo explica las razones por las cuales China se estrecha sus vinculos con Afirca. El tema principal es el inicio de la relacion sino-sudanesa y la evolucion de esta hasta el fin de la guerra civil en Sudan.

Convergencia de vías de señalización en un modelo de apoptosis

La sepsis es un evento inflamatorio generalizado del organismo inducido por un daño causado generalmente por un agente infeccioso. El patógeno más frecuentemente asociado con esta entidad es el Staphylococcus aureus, responsable de la inducción de apoptosis en células endoteliales debida a la producción de ceramida. Se ha descrito el efecto protector de la proteína C activada (PCA) en sepsis y su relación con la disminución de la apoptosis de las células endoteliales. En este trabajo se analizó la activación de las quinasas AKT, ASK1, SAPK/JNK y p38 en un modelo de apoptosis endotelial usando las técnicas de Western Blotting y ELISA. Las células endoteliales (EA.hy926), se trataron con C2-ceramida (130μM) en presencia de inhibidores químicos de cada una de estas quinasas y PCA. La supervivencia de las células en presencia de inhibidores químicos y PCA fue evaluada por medio de ensayos de activación de las caspasas 3, 7 y 9, que verificaban la muerte celular por apoptosis. Los resultados evidencian que la ceramida reduce la activación de AKT y aumenta la activación de las quinasas ASK, SAPK/JNK y p38, en tanto que PCA ejerce el efecto contrario. Adicionalmente se encontró que la tiorredoxina incrementa la activación/fosforilación de AKT, mientras que la quinasa p38 induce la defosforilación de AKT.