Financial Integration, Trade Openness and International Transmission

[cat] Com afecten l’obertura comercial i financera a la volatilitat macroeconòmica? La literatura existent, tant empírica com teòrica, no ha assolit encara un consens. Aquest article usa un model microfonamentat de dos països simètrics amb entrada endògena d’empreses per estudiar-ho. L’anàlisis es du a terme per tres règims econòmics diferents amb diferents nivells d’integració internacional: una economia tancada, una autarquia financera i una integració plena. Es consideren diversos nivells d’obertura comercial, en forma de biaix domèstic de la demanda i l’economia pot patir pertorbacions en la productivitat del treball i en innovació. El model conclou que la incertesa macroeconòmica, representada principalment per la volatilitat del consum, la producció i la relació real d’intercanvi internacional, depèn del grau d’obertura i del tipus de pertorbació.

GDP and life expectancy in Italy and Spain over the long-run (1861-2008): insights from a timeseries approach

The article presents and discusses long-run series of per capita GDP and life expectancy for Italy and Spain (1861-2008). After refining the available estimates in order to make them comparable and with the avail of the most up-to-date researches, the main changes in the international economy and in technological and sociobiological regimes are used as analytical frameworks to re-assess the performances of the two countries; then structural breaks are searched for and Granger causality between the two variables is investigated. The long-run convergence notwithstanding, significant cyclical differences between the two countries can be detected: Spain began to modernize later in GDP, with higher volatility in life expectancy until recent decades; by contrast, Italy showed a more stable pattern of life expectancy, following early breaks in per capita GDP, but also a negative GDP break in the last decades. Our series confirm that, whereas at the early stages of development differences in GDP tend to mirror those in life expectancy, this is no longer true at later stages of development, when, if any, there seems to be a negative correlation between GDP and life expectancy: this finding is in line with the thesis of a non-monotonic relation between life expectancy and GDP and is supported by tests of Granger causality.

Uncertainty, electoral incentives and political myopia

We study the determinants of political myopia in a rational model of electoral accountability where the key elements are informational frictions and uncertainty. We build aframework where political ability is ex-ante unknown and policy choices are not perfectlyobservable. On the one hand, elections improve accountability and allow to keep well-performing incumbents. On the other, politicians invest too little in costly policies withfuture returns in an attempt to signal high ability and increase their reelection probability.Contrary to the conventional wisdom, uncertainty reduces political myopia and may, undersome conditions, increase social welfare. We use the model to study how political rewardscan be set so as to maximise social welfare and the desirability of imposing a one-term limitto governments. The predictions of our theory are consistent with a number of stylised factsand with a new empirical observation documented in this paper: aggregate uncertainty, measured by economic volatility, is associated to better fiscal discipline in a panel of 20 OECDcountries.

Man-bites-dog business cycles

The newsworthiness of an event is partly determined by how unusual it isand this paper investigates the business cycle implications of this fact. In particular, weanalyze the consequences of information structures in which some types of signals are morelikely to be observed after unusual events. Such signals may increase both uncertainty anddisagreement among agents and when embedded in a simple business cycle model, can helpus understand why we observe (i) occasional large changes in macro economic aggregatevariables without a correspondingly large change in underlying fundamentals (ii) persistentperiods of high macroeconomic volatility and (iii) a positive correlation between absolutechanges in macro variables and the cross-sectional dispersion of expectations as measuredby survey data. These results are consequences of optimal updating by agents when theavailability of some signals is positively correlated with tail-events. The model is estimatedby likelihood based methods using individual survey responses and a quarterly time seriesof total factor productivity along with standard aggregate time series. The estimated modelsuggests that there have been episodes in recent US history when the impact on outputof innovations to productivity of a given magnitude was more than eight times as largecompared to other times.

Anàlisi del risc del preu dels índex IBEX-35 i DAX-30

En aquest treball es porta a terme l’anàlisi del comportament dels índexs IBEX-35 i DAX-30 en el període comprès entre els anys 2008 – 2012. L’objectiu del treball és analitzar com han evolucionat determinades mesures del risc, com són, la Volatilitat, el VaR i el CVaR en els dos índexs. Aquest anàlisi té la finalitat d’aconseguir evidències del diferent comportament d’aquests índexs en el període analitzat, i així veure el diferent impacte que ha tingut la crisis econòmica actual en l’economia espanyola i alemanya.

First-passage and escape problems in the Feller process

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

Firms, destinations, and aggregate fluctuations

This paper uses a database covering the universe of French firms for the period 1990-2007 to provide a forensic account of the role of individual firms in generating aggregatefluctuations. We set up a simple multi-sector model of heterogeneous firms selling tomultiple markets to motivate a theoretically-founded decomposition of firms' annualsales growth rate into different components. We find that the firm-specific componentcontributes substantially to aggregate sales volatility, mattering about as much as thecomponents capturing shocks that are common across firms within a sector or country.We then decompose the firm-specific component to provide evidence on two mechanismsthat generate aggregate fluctuations from microeconomic shocks highlighted in the recentliterature: (i) when the firm size distribution is fat-tailed, idiosyncratic shocks tolarge firms directly contribute to aggregate fluctuations; and (ii) aggregate fluctuationscan arise from idiosyncratic shocks due to input-output linkages across the economy.Firm linkages are approximately three times as important as the direct effect of firmshocks in driving aggregate fluctuations.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

First-passage and escape problems in the Feller process

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.