Abstract splines in Krein spaces

"Vegeu el resum a l'inici del document del fitxer adjunt."

Implementación de movimientos suaves en robots industriales mediante splines cúbicos: aplicación a un laboratorio remoto de robótica

La solución a los problemas de disponibilidad horaria para la realización de sesiones prácticas por parte de los estudiantes se encuentra en los laboratorios remotos, que permiten a estos interactuar con los elementos instalados en los laboratorios sin necesidad de estar presentes físicamente. Este proyecto pretende crear un laboratorio remoto para la asignatura “Robótica y Automatización Industrial” impartida en la ETSE, UAB, en el cual los estudiantes puedan ejecutar trayectorias de tipo spline cúbico en un brazo robot y observar a través de vídeo en tiempo real los movimientos del robot desde cualquier lugar con conexión a Internet.

Book vs. Fair Value Accounting in Banking, and Intertemporal Smoothing

The aim of this paper is to examine the pros and cons of book and fair value accounting from the perspective of the theory of banking. We consider the implications of the two accounting methods in an overlapping generations environment. As observed by Allen and Gale(1997), in an overlapping generation model, banks have a role as intergenerational connectors as they allow for intertemporal smoothing. Our main result is that when dividends depend on profits, book value ex ante dominates fair value, as it provides better intertemporal smoothing. This is in contrast with the standard view that states that, fair value yields a better allocation as it reflects the real opportunity cost of assets. Banking regulation play an important role by providing the right incentives for banks to smooth intertemporal consumption whereas market discipline improves intratemporal efficiency.

A generalization of histogram type estimators

We introduce simple nonparametric density estimators that generalize theclassical histogram and frequency polygon. The new estimators are expressed as linear combination of density functions that are piecewisepolynomials, where the coefficients are optimally chosen in order to minimize the integrated square error of the estimator. We establish the asymptotic behaviour of the proposed estimators, and study theirperformance in a simulation study.

Book vs. fair value accounting in banking and intertemporal smoothing

The aim of this paper is to examine the pros and cons of book and fair value accounting from the perspective of the theory of banking. We consider the implications of the two accounting methods in an overlapping generations environment. As observed by Allen and Gale(1997), in an overlapping generation model, banks have a role as intergenerational connectors as they allow for intertemporal smoothing. Our main result is that when dividends depend on profits, book value ex ante dominates fair value, as it provides better intertemporal smoothing. This is in contrast with the standard view that states that, fair value yields a better allocation as it reflects the real opportunity cost of assets. Banking regulation play an important role by providing the right incentives for banks to smooth intertemporal consumption whereas market discipline improves intratemporal efficiency.

Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal

This comment corrects the errors in the estimation process that appear in Martins (2001). The first error is in the parametric probit estimation, as the previously presented results do not maximize the log-likelihood function. In the global maximum more variables become significant. As for the semiparametric estimation method, the kernel function used in Martins (2001) can take on both positive and negative values, which implies that the participation probability estimates may be outside the interval [0,1]. We have solved the problem by applying local smoothing in the kernel estimation, as suggested by Klein and Spady (1993).

Estimation of dynamic latent variable models using simulated nonparametric moments

Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.

The Monetary policy rules in Europe: heterogeneity and common patters

The objective of this study is the empirical identification of the monetary policy rules pursued in individual countries of EU before and after the launch of European Monetary Union. In particular, we have employed an estimation of the augmented version of the Taylor rule (TR) for 25 countries of the EU in two periods (1992-1998, 1999-2006). While uniequational estimation methods have been used to identify the policy rules of individual central banks, for the rule of the European Central Bank has been employed a dynamic panel setting. We have found that most central banks really followed some interest rate rule but its form was usually different from the original TR (proposing that domestic interest rate responds only to domestic inflation rate and output gap). Crucial features of policy rules in many countries have been the presence of interest rate smoothing as well as response to foreign interest rate. Any response to domestic macroeconomic variables have been missing in the rules of countries with inflexible exchange rate regimes and the rules consisted in mimicking of the foreign interest rates. While we have found response to long-term interest rates and exchange rate in rules of some countries, the importance of monetary growth and asset prices has been generally negligible. The Taylor principle (the response of interest rates to domestic inflation rate must be more than unity as a necessary condition for achieving the price stability) has been confirmed only in large economies and economies troubled with unsustainable inflation rates. Finally, the deviation of the actual interest rate from the rule-implied target rate can be interpreted as policy shocks (these deviation often coincided with actual turbulent periods).

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

How does monetary policy change? evidence on inflation targeting countries

We examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom) applying moment- based estimator at time-varying parameter model with endogenous regressors. Using this novel flexible framework, our main findings are threefold. First, monetary policy rules change gradually pointing to the importance of applying time-varying estimation framework. Second, the interest rate smoothing parameter is much lower that what previous time-invariant estimates of policy rules typically report. External factors matter for all countries, albeit the importance of exchange rate diminishes after the adoption of inflation targeting. Third, the response of interest rates on inflation is particularly strong during the periods, when central bankers want to break the record of high inflation such as in the U.K. or in Australia at the beginning of 1980s. Contrary to common wisdom, the response becomes less aggressive after the adoption of inflation targeting suggesting the positive effect of this regime on anchoring inflation expectations. This result is supported by our finding that inflation persistence as well as policy neutral rate typically decreased after the adoption of inflation targeting.

Nonparametric estimation of Value-at-Risk

A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation. We derive optimal bandwidth selection methods that have a direct expression for the smoothing parameter. The bandwidth can accommodate to the given quantile level. The procedure is useful for large data sets and improves quantile estimation compared to other methods in heavy tailed distributions. Implementation is straightforward and R programs are available.

Clustering compositional data trajectories

Our essay aims at studying suitable statistical methods for the clustering ofcompositional data in situations where observations are constituted by trajectories ofcompositional data, that is, by sequences of composition measurements along a domain.Observed trajectories are known as “functional data” and several methods have beenproposed for their analysis.In particular, methods for clustering functional data, known as Functional ClusterAnalysis (FCA), have been applied by practitioners and scientists in many fields. To ourknowledge, FCA techniques have not been extended to cope with the problem ofclustering compositional data trajectories. In order to extend FCA techniques to theanalysis of compositional data, FCA clustering techniques have to be adapted by using asuitable compositional algebra.The present work centres on the following question: given a sample of compositionaldata trajectories, how can we formulate a segmentation procedure giving homogeneousclasses? To address this problem we follow the steps described below.First of all we adapt the well-known spline smoothing techniques in order to cope withthe smoothing of compositional data trajectories. In fact, an observed curve can bethought of as the sum of a smooth part plus some noise due to measurement errors.Spline smoothing techniques are used to isolate the smooth part of the trajectory:clustering algorithms are then applied to these smooth curves.The second step consists in building suitable metrics for measuring the dissimilaritybetween trajectories: we propose a metric that accounts for difference in both shape andlevel, and a metric accounting for differences in shape only.A simulation study is performed in order to evaluate the proposed methodologies, usingboth hierarchical and partitional clustering algorithm. The quality of the obtained resultsis assessed by means of several indices

From severance pay to self-insurance: Effects of severance payments savings accounts in Colombia

In 1990 Colombia replaced its traditional system of severance paymentswith a new system of severance payments savings accounts (SPSAs). Althoughseverance payments often are justified on the grounds that they provideinsurance against earnings loss, they also increase costs for employersand distort employment decisions. The impact of severance payments dependslargely on how much of the costs to employers can be shifted to workers.The theoretical analysis in this paper shows that, in contrast to atraditional system of severance payments, the system of SPSAs facilitatesthe shifting of severance payments costs to workers in the form of lowerwages. Empirical results using the Colombian National Household Surveysindicate that the introduction of SPSAs shifted around 80% of the totalseverance payments contributions to wages and had a positive effect onweekly hours. Results using the 1997 Colombian Living Standards MeasurementSurvey suggest that, although SPSAs in part replaced employer insurancewith self-insurance, SPSAs continue to play a consumption smoothing rolefor the non-employed.

Debt and deficit fluctuations and the structure of bond markets

This paper tests for the market environment within which US fiscal policyoperates, that is we test for the incompleteness of the US government bondmarket. We document the stochastic properties of US debt and deficits andthen consider the ability of competing optimal tax models to account forthis behaviour. We show that when a government pursues an optimal taxpolicy and issues a full set of contingent claims, the value of debthas the same or less persistence than other variables in the economyand declines in response to higher deficit shocks. By contrast, ifgovernments only issue one-period risk free bonds (incomplete markets),debt shows more persistence than other variables and it increases inresponse to expenditure shocks. Maintaining the hypothesis of Ramseybehavior, US data conflicts.

Variable Kernel estimates: On the impossibility of tuning the parameters

For the standard kernel density estimate, it is known that one can tune the bandwidth such that the expected L1 error is within a constant factor of the optimal L1 error (obtained when one is allowed to choose the bandwidth with knowledge of the density). In this paper, we pose the same problem for variable bandwidth kernel estimates where the bandwidths are allowed to depend upon the location. We show in particular that for positive kernels on the real line, for any data-based bandwidth, there exists a densityfor which the ratio of expected L1 error over optimal L1 error tends to infinity. Thus, the problem of tuning the variable bandwidth in an optimal manner is ``too hard''. Moreover, from the class of counterexamples exhibited in the paper, it appears thatplacing conditions on the densities (monotonicity, convexity, smoothness) does not help.