A VAR Model for the Analysis of the Effects of Monetary Policy in the Euro Area

This paper, by the estimation of a structural VAR model on aggregate data from 1980 to 2002, examines the macroeconomic effects of an unexpected change in monetary policy on the euro area. The results are in line with the economic theory and they are close to the one estimated by other authors. These results, considering the formation of the European Monetary Union, give rise to some doubts and require some considerations. Thus, this paper discusses the limits of both the econometric technique used, and the data compilation methodology usually applied in these works.

Monetary Policy, the Housing Market, and the 2008 Recession: A Structural Factor Analysis

DThis paper estimates a Structural Dynamic Factor Model on a panel of 102 US quarterly series. We model economic comovements by means of 5 underlying structural shocks (oil price, productivity, aggregate demand, monetary policy, and housing demand). The results of the benchmark model (impulse responses and variance decompositions) are in line with those predicted by economic theory and usually estimated by the empirical literature. We show that while over the whole sample the contribution of the housing demand shock is negligible, after the early eighties' liberalizations in housing finance, the housing demand shock has become a substantial source of business cycle fluctuations. The model is then used to analyze the causes of the 2008 recession: results indicate that we cannot exclude that monetary policy played a non negligible role in leading the way for the downturn in residential investment and the ensuing recession.\\ JEL Classification: C32, E32, E52, R2Structural Factor Model, Business Cycle, Monetary Policy, Housing.Structural Factor Model, Business Cycle, Monetary Policy, Housing

Security of Supply for Natural Gas Markets. What is it and What is it not?

The issue of security of gas supplies is frequently discussed on the basis of intuitive and non-systematic arguments. Greater import dependence is normally equated with greater insecurity, and strategic stocks are the risk management tool most commonly considered. This paper strives to offer a systematic framework of analysis and shows that import dependence does not necessarily entail greater insecurity – actually, the opposite may well be the case. It also discusses several alternatives to strategic stocks for risk management, which are more interesting and promising.Natural gas market, Security of supply

Oil spill detection using optical sensors: a multi-temporal approach

Oil pollution is one of the most destructive consequences due to human activities in the marine environment. Oil wastes come from many sources and take decades to be disposed of. Satellite based remote sensing systems can be implemented into a surveillance and monitoring network. In this study, a multi-temporal approach to the oil spill detection problem is investigated. Change Detection (CD) analysis was applied to MODIS/Terra and Aqua and OLI/Landsat 8 images of several reported oil spill events, characterized by different geographic location, sea conditions, source and extension of the spill. Toward the development of an automatic detection algorithm, a Change Vector Analysis (CVA) technique was implemented to carry out the comparison between the current image of the area of interest and a dataset of reference image, statistically analyzed to reduce the sea spectral variability between different dates. The proposed approach highlights the optical sensors’ capabilities in detecting oil spills at sea. The effectiveness of different sensors’ resolution towards the detection of spills of different size, and the relevance of the sensors’ revisiting time to track and monitor the evolution of the event is also investigated

Sensitivity of Dar Es Salaam coastal aquifer to climate change with regard to seawater intrusion and groundwater availability

This paper presents the initial results of three years of investigation activities, carried on in the Dar es Salaam coastal plain (Tanzania) by the Adapting to Climate Change in Coastal Dar es Salaam (ACC-DAR) project, a cofounded research project, granted by the European Union, led by the Sapienza, University of Rome, in cooperation with Ardhi University of Dar es Salaam. The ACC-DAR project activities will enhance the capacities of Dar’s municipalities by increasing their understanding of adaptation practices, and by developing methodologies for integrating adaptation activities into strategies and plans for Urban Development and Environment Management (UDEM) in unplanned and unserviced coastal settlements. In order to provide a series of enhanced methodologies for improving municipal activities related to climate change (CC) issues in the water management sector, the specific environmental phenomenon of seawater intrusion was investigated. This phenomenon is already contributing, and will increasingly contribute as CC progresses, to the degradation of those natural resources on which a large part of Dar es Salaam’s peri-urban livelihoods depends. The target of this study was to investigate groundwater availability changes in Dar es Salaam’s coastal aquifer as a consequence of seawater intrusion and urbanization processes in the framework of CC effects, with the aim to set up an integrated approach to evaluate CC effects on groundwater resources in coastal plains affected by seawater intrusion, and to better manage these important natural resources. As such, geological and hydrogeological characterization of the area is part of the study, as lithological properties of outcropping geological formations and their main hydrogeological settings, as well as chemical groundwater characterization also depend on them, but they were not the target of the study

A multi-temporal phenology based classification approach for Crop Monitoring in Kenya

The SBAM (Satellite Based Agricultural Monitoring) project, funded by the Italian Space Agency aims at: developing a validated satellite imagery based method for estimating and updating the agricultural areas in the region of Central-Africa; implementing an automated process chain capable of providing periodical agricultural land cover maps of the area of interest and, possibly, an estimate of the crop yield. The project aims at filling the gap existing in the availability of high spatial resolution maps of the agricultural areas of Kenya. A high spatial resolution land cover map of Central-Eastern Africa including Kenya was compiled in the year 2000 in the framework of the Africover project using Landsat images acquired, mostly, in 1995. We investigated the use of phenological information in supporting the use of remotely sensed images for crop classification and monitoring based on Landsat 8 and, in the near future, Sentinel 2 imagery. Phenological information on crop condition was collected using time series of NDVI (Normalized Difference Vegetation Index) based on Landsat 8 images. Kenyan countryside is mainly characterized by a high number of fragmented small and medium size farmlands that dramatically increase the difficulty in classification; 30 m spatial resolution images are not enough for a proper classification of such areas. So, a pan-sharpening FIHS (Fast Intensity Hue Saturation) technique was implemented to increase image resolution from 30 m to 15 m. Ground test sites were selected, searching for agricultural vegetated areas from which phenological information was extracted. Therefore, the classification of agricultural areas is based on crop phenology, vegetation index behaviour retrieved from a time series of satellite images and on AEZ (Agro Ecological Zones) information made available by FAO (FAO, 1996) for the area of interest. This paper presents the results of the proposed classification procedure in comparison with land cover maps produced in the past years by other projects. The results refer to the Nakuru County and they were validated using field campaigns data. It showed a satisfactory overall accuracy of 92.66 % which is a significant improvement with respect to previous land cover maps

Auditioning for empathy:dance, acting, and psychology students

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Measuring Euro Area Monetary Policy Transmission in a Structural Dynamic Factor Model

We study the effects of euro area common monetary policy by means of a structural dynamic factor model estimated on a large panel of euro area quarterly series. While we estimate a flat response of prices to a monetary policy shock, which we explain as aggregation of heterogeneous country-specific responses, we find no relevant asymmetries between countries in terms of output reaction. However, for both Spain and Italy, we find asymmetries in consumption, investment and unemployment. The introduction of the single currency in 1999 has helped reducing asymmetries in price responses but not in consumption and investment.