Fiscal foresight, forecast revisions and the effects of government spending in the open economy

This paper investigates the effects of government spending on the real exchange rate and the trade balance in the US using a new VAR identification procedure based on spending forecast revisions. I find that the real exchange rate appreciates and the trade balance deteriorates after a government spending shock, although the effects are quantitatively small. The findings broadly match the theoretical predictions of the standard Mundell-Fleming model and differ substantially from those existing in literature. Differences are attributable to the fact that, because of fiscal foresight, the government spending is non-fundamental for the variables typically used in open economy VARs. Here, on the contrary, the estimated shock is fundamental.

Out-of-sample forecast tests robust to the choice of window size

This paper proposes new methodologies for evaluating out-of-sample forecastingperformance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide rangeof window sizes. We show that the tests proposed in the literature may lack the powerto detect predictive ability and might be subject to data snooping across differentwindow sizes if used repeatedly. An empirical application shows the usefulness of themethodologies for evaluating exchange rate models' forecasting ability.

Preface: Forecast and projection in climate scenario of Mediterranean intense events: uncertainties and propagation on environment (the MEDUP project)

The Mediterranean basin is a particularly vulnerable region to climate change, partly due to its quite unique character that results both from physiographic conditions and societal development. The region features indeed a near-closed sea surrounded by very urbanised littorals and mountains from which numerous rivers originate. This results in a lot of interactions and feedbacks between oceanic-atmospheric-hydrological processes that play a predominant role on climate and extreme events that frequently cause heavy dam- ages and human losses in the Mediterranean ...

Combine to compete: improving fiscal forecast accuracy over time

Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.

Combine to compete: improving fiscal forecast accuracy over time

Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.

Knowledge, networks of cities and growth in regional urban systems

The objective of this paper is to measure the impact of different kinds of knowledge and external economies on urban growth in an intraregional context. The main hypothesis is that knowledge leads to growth, and that this knowledge is related to the existence of agglomeration and network externalities in cities. We develop a three-tage methodology: first, we measure the amount and growth of knowledge in cities using the OCDE (2003) classification and employment data; second, we identify the spatial structure of the area of analysis (networks of cities); third, we combine the Glaeser - Henderson - De Lucio models with spatial econometric specifications in order to contrast the existence of spatially static (agglomeration) and spatially dynamic (network) external economies in an urban growth model. Results suggest that higher growth rates are associated to higher levels of technology and knowledge. The growth of the different kinds of knowledge is related to local and spatial factors (agglomeration and network externalities) and each knowledge intensity shows a particular response to these factors. These results have implications for policy design, since we can forecast and intervene on local knowledge development paths.

Estudi de l'evolució del sòl urbà a la Vall d'Àneu

Aquest treball té com a principal objectiu analitzar l’evolució del sòl urbà als pobles de la Vall d’Àneu, dins l’àmbit del Parc Natural de l’Alt Pirineu. La Vall d’Àneu, situada en el Pirineu axial català, està formda pels municipis de l’Alt Àneu, Espot, Esterri d’Àneu i La Guingueta d’Àneu, i amb un total de 24 poblacions, totes elles per sota la cota de 1500 m. A mitjans del segle passat, el conjunt de pobles de la Vall mostraven una homogeneïtat envers la seva grandaria i distribució, on l’alçada no era un factor determinant. En les darreres dècades, la Vall d’Àneu ha experimentat un creixement demogràfic i econòmic, basat en el sector serveis (estacions d’esquí, turisme rural, esports d’aventura, etc.). Aquest gir econòmic ha desencadenat un creixmenet de les poblacions, accentuat en els últims anys. Aquest no ha estat homogeni, sinó que s’ha focalitzat en determinades zones segons el període. Així, en els darrers anys, aquest creixement s’ha centrat en els pobles propers a les pistes d’esquí i segons les previsions del PTPAPiA per l’any 2026, la tendència seguirà sent la mateixa.

Stock market volatility and learning

Introducing bounded rationality in a standard consumption-based asset pricing model with time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though our learning scheme introduces just one free parameter and we only consider learning schemes that imply small deviations from full rationality. The findings are robust to the learning rule used and other model features. What is key is that agents forecast future stock prices using past information on prices.

Leading indicator properties of US high-yield credit spreads

In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding real-time and revised data on employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that, especially for employment, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor. Moreover, forecasts based on real-time data are generally comparable to forecasts based on revised data. JEL Classification: C22; C53; E32 Keywords: Credit spreads; Principal components; Forecasting; Real-time data.

Traffic forecasts under uncertainty and capacity constraints

Traffic forecasts provide essential input for the appraisal of transport investment projects. However, according to recent empirical evidence, long-term predictions are subject to high levels of uncertainty. This paper quantifies uncertainty in traffic forecasts for the tolled motorway network in Spain. Uncertainty is quantified in the form of a confidence interval for the traffic forecast that includes both model uncertainty and input uncertainty. We apply a stochastic simulation process based on bootstrapping techniques. Furthermore, the paper proposes a new methodology to account for capacity constraints in long-term traffic forecasts. Specifically, we suggest a dynamic model in which the speed of adjustment is related to the ratio between the actual traffic flow and the maximum capacity of the motorway. This methodology is applied to a specific public policy that consists of suppressing the toll on a certain motorway section before the concession expires.

Anàlisi de la modelització hidrològica com a eina per la predicció d'inundacions i la gestió del territori

Les inundacions són actualment les catàstrofes naturals més recurrents i les que generen un major nombre de danys i víctimes arreu del món. L'ocupació de les zones inundables a les lleres del riu és la causa principal d’aquests desastres naturals. En aquest article es descriu la realització de models hidrològics com a mecanisme per la predicció d’inundacions i la gestió del territori. S’han estudiat les conques de la Riera de Santa Coloma (Catalunya) i del riu San Francisco (Guatemala) mitjançant els programes HEC-HMS i HEC-RAS, dels quals s’avalua la seva capacitat com eina per a la gestió del territori. S’ha analitzat l’efecte de la urbanització en el risc d’inundació en el cas de la Riera de Santa Coloma en base a la previsió del Plà d’Ordenament Urbanístic Municipal. S’han determinat les zones inundables resultants de episodis de precipitació extrems al Riu San Francisco per als episodis de les tempestes Stan(2005) i Agatha(2010).

Diseño e implementación de un capturador de paquetes de red

En l'actualitat les xarxes de comunicacions són bàsicament digitals; el camí que s'ha avançat en els darrers quaranta anys ha estat molt llarg, amb un desenvolupament tan ràpid que ha fet que qualsevol previsió quedés molt endarrerida abans d'hora (o que de vegades se sobreestimés aquest desenvolupament, com va passar amb el

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult toachieve because the relative values of the forecast components often fail to behave ina way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It hasbeen shown that cause-specic mortality forecasts are pessimistic when compared withall-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approachof using log mortality rates and forecasts the density of deaths in the life table. Sincethese values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbingstate), they are intrinsically relative rather than absolute values across decrements aswell as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison(1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that theunit sum constraint is honoured. The structure of the best-known, single-decrementmortality-rate forecasting model, devised by Lee and Carter (1992), is expressed incompositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortalityby cause of death for Japan

Shocking policy coefficients

This paper proposes an empirical framework to study the effects of a policy regime change defined as an unpredictable and permanent change in the policy parameters. In particular I show how to make conditional forecast and perform impulse response functions and counterfactual analysis. As an application, the effects of changes in fiscal policy rules in the US are investigated. I find that discretionary fiscal policy has become more countercyclical over the last decades. In absence of such a change, surplus would have been higher, debt lower and output gap more volatile but only until mid 80s. An increase in the degree of counter-cyclicality of fiscal policy has a positive effect on output gap in periods where the level of debt-to-GDP ratio is low and a zero or negative effect when the ratio is high. This explains why a more countercylical stance of the systematic fiscal policy taking place in 2008:II is predicted to be rather ineffective for recovering from the crisis.

Modification of the Perrine-Baum diagram to improve the calculation of high voltage electric lines

Through the history of Electrical Engineering education, vectorial and phasorial diagrams have been used as a fundamental learning tool. At present, computational power has replaced them by long data lists, the result of solving equation systems by means of numerical methods. In this sense, diagrams have been shifted to an academic background and although theoretically explained, they are not used in a practical way within specific examples. This fact may be against the understanding of the complex behavior of the electrical power systems by students. This article proposes a modification of the classical Perrine-Baum diagram construction to allowing both a more practical representation and a better understanding of the behavior of a high-voltage electric line under different levels of load. This modification allows, at the same time, the forecast of the obsolescence of this behavior and line’s loading capacity. Complementary, we evaluate the impact of this tool in the learning process showing comparative undergraduate results during three academic years