Long-run Inflation-Unemployment Dynamics: The Spanish Phillips Curve and Economic Policy

This paper takes a new look at the long-run dynamics of inflation and unemployment in response to permanent changes in the growth rate of the money supply. We examine the Phillips curve from the perspective of what we call "frictional growth", i.e. the interaction between money growth and nominal frictions. After presenting theoretical models of this phenomenon, we construct an empirical model of the Spanish economy and, in this context, we evaluate the long-run inflation-unemployment trade for Spain and examine how recent policy changes have afected it.

Dance movement patterns recognition

"Es tracta d'un projecte dividit en dues parts independents però complementàries, realitzades per autors diferents. Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia"

Discriminating groups: a comprehensive overview

Discriminating groups were introduced by G.Baumslag, A.Myasnikov and V.Remeslennikov as an outgrowth of their theory of algebraic geometry over groups. However they have taken on a life of their own and have been an object of a considerable amount of study. In this paper we survey the large array results concerning the class of discriminating groups that have been developed over the past decade.

The Macroeconomics of the labor market: three fundamental views

We distinguish and assess three fundamental views of the labor market regarding the movements in unempoyment: (i) the frictionless equilibrium view; (ii) the chain reaction theory, or prolonged adjustment view; and (iii) the hysteresis view. While the frictionless view implies a clear compartmentalization between the short- and long-run, the hysteresis view implies that all the short-run fluctuations automatically turn into long-run changes in the unemployment rate. We assert the problems faced by these conceptions in explaining the diversity of labor market experiences across the OECD labor markets. We argue that the prolonged adjustment view can overcome these problems since it implies that the short, medium, and long runs are interrelated, merging with one another along an intertemporal continuum.

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.

SNM Guide

This is a guide that explains how to use software that implements the simulated nonparametric moments (SNM) estimator proposed by Creel and Kristensen (2009). The guide shows how results of that paper may easily be replicated, and explains how to install and use the software for estimation of simulable econometric models.

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.

Comparació de les dues traduccions al català de This Side of Paradise

En aquest treball es fa una anàlisi de This Side of Paradise, de Scott Fitzgerald, enfocada a avaluar les traduccions catalanes. A continuació, es comparen les dues traduccions existents: una de Francesc Parcerisas (Aquest costat del paradís, 1984) i l’altra de Josep Maria Fulquet (En aquest costat del paradís, 2003).

Free Flows, Limited Diversification: Explaining the Fall and Rise of Stock Market Correlations, 1890-2001

Using a new dataset on capital account openness, we investigate why equity return correlations changed over the last century. Based on a new, long-run dataset on capital account regulations in a group of 16 countries over the period 1890-2001, we show that correlations increase as financial markets are liberalized. These findings are robust to controlling for both the Forbes-Rigobon bias and global averages in equity return correlations. We test the robustness of our conclusions, and show that greater synchronization of fundamentals is not the main cause of increasing correlations. These results imply that the home bias puzzle may be smaller than traditionally claimed.

A century of global equity market correlations

In this paper, we use a unique long-run dataset of regulatory constraints on capital account openness to explain stock market correlations. Since stock returns themselves are highly volatile, any examination of what drives correlations needs to focus on long runs of data. This is particularly true since some of the short-term changes in co-movements appear to reverse themselves (Delroy Hunter 2005). We argue that changes in the co-movement of indices have not been random. Rather, they are mainly driven by greater freedom to move funds from one country to another. In related work, Geert Bekaert and Campbell Harvey (2000) show that equity correlations increase after liberalization of capital markets, using a number of case studies from emerging countries. We examine this pattern systematically for the last century, and find it to be most pronounced in the recent past. We compare the importance of capital account openness with one main alternative explanation, the growing synchronization of economic fundamentals. We conclude that greater openness has been the single most important cause of growing correlations during the last quarter of a century, though increasingly correlated economic fundamentals also matter. In the conclusion, we offer some thoughts on why the effects of greater openness appear to be so much stronger today than they were during the last era of globalization before 1914.

Power supply noise and logic error probability

Voltage fluctuations caused by parasitic impedances in the power supply rails of modern ICs are a major concern in nowadays ICs. The voltage fluctuations are spread out to the diverse nodes of the internal sections causing two effects: a degradation of performances mainly impacting gate delays anda noisy contamination of the quiescent levels of the logic that drives the node. Both effects are presented together, in thispaper, showing than both are a cause of errors in modern and future digital circuits. The paper groups both error mechanismsand shows how the global error rate is related with the voltage deviation and the period of the clock of the digital system.

Voltage fluctuations in IC power supply distribution

The supply voltage decrease and powerconsumption increase of modern ICs made the requirements for low voltage fluctuation caused by packaging and on-chip parasitic impedances more difficult to achieve. Most of the research works on the area assume that all the nodes of the chip are fed at thesame voltage, in such a way that the main cause of disturbance or fluctuation is the parasitic impedance of packaging. In the paper an approach to analyze the effect of high and fast current demands on the on-chip power supply network. First an approach to model the entire network by considering a homogeneous conductive foil is presented. The modification of the timing parameters of flipflops caused by spatial voltage drops through the IC surface are also investigated.

Sustained CTL activation by murine pulmonary epithelial cells promotes the development of COPD-like disease

Chronic obstructive pulmonary disease (COPD) is a lethal progressive lung disease culminating in permanent airway obstruction and alveolar enlargement. Previous studies suggest CTL involvement in COPD progression; however, their precise role remains unknown. Here, we investigated whether the CTL activation receptor NK cell group 2D (NKG2D) contributes to the development of COPD. Using primary murine lung epithelium isolated from mice chronically exposed to cigarette smoke and cultured epithelial cells exposed to cigarette smoke extract in vitro, we demonstrated induced expression of the NKG2D ligand retinoic acid early tran - script 1 (RAET1)as well as NKG2D-mediated cytotoxicity. Furthermore, a genetic model of inducible RAET1 expression on mouse pulmonary epithelial cells yielded a severe emphysematous phenotype characterized by epithelial apoptosis and increased CTL activation, which was reversed by blocking NKG2D activation. We also assessed whether NKG2D ligand expression corresponded with pulmonary disease in human patients by staining airway and peripheral lung tissues from never smokers, smokers with normal lung function, and current and former smokers with COPD. NKG2D ligand expression was independent of NKG2D receptor expression in COPD patients, demonstrating that ligand expression is the limiting factor in CTL activation. These results demonstrate that aberrant, persistent NKG2D ligand expression in the pulmonary epithelium contributes to the development of COPD pathologies.

Climate change impacts on lakes: an integrated ecological perspective based on a multi-faceted approach, with special focus on shallow lakes

Freshwater ecosystems and their biodiversity are presently seriously threatened by global development and population growth, leading to increases in nutrient inputs and intensification of eutrophication-induced problems in receiving fresh waters, particularly in lakes. Climate change constitutes another threat exacerbating the symptoms of eutrophication and species migration and loss. Unequivocal evidence of climate change impacts is still highly fragmented despite the intensive research, in part due to the variety and uncertainty of climate models and underlying emission scenarios but also due to the different approaches applied to study its effects. We first describe the strengths and weaknesses of the multi-faceted approaches that are presently available for elucidating the effects of climate change in lakes, including space-for-time substitution, time series, experiments, palaeoecology and modelling. Reviewing combined results from studies based on the various approaches, we describe the likely effects of climate changes on biological communities, trophic dynamics and the ecological state of lakes. We further discuss potential mitigation and adaptation measures to counteract the effects of climate change on lakes and, finally, we highlight some of the future challenges that we face to improve our capacity for successful prediction.