The effects of privatization and consolidation on bank productivity: comparative evidence from Italy and Germany

The Italian and German banking systems shared similar characteristics early in the 1990s but have evolved in different directions since then: Italy privatized its publicly-owned banks while Germany has maintained a large share of state-owned savings banks. Contemporaneously, banks in both markets engaged heavily in mergers and acquisitions. We analyze how these activities have affected banksÂ’ productivity in the period 1994-2004, differentiating between technical change, efficiency change and scale economies. We find that privatized banks experienced a significant increase in productivity, especially if they subsequently merged with other banks. German banks were still able to increase their productivity through consolidation.banking market integration, deregulation, total factor productivity, Italy, Germany

The effects of privatization and consolidation on bank productivity: comparative evidence from Italy and Germany

The Italian and German banking systems shared similar characteristics early in the 1990s but have evolved in different directions since then: Italy privatized its publicly-owned banks while Germany has maintained a large share of state-owned savings banks. Contemporaneously, banks in both markets engaged heavily in mergers and acquisitions. We analyze how these activities have affected banks' productivity in the period 1994-2004, differentiating between technical change, efficiency change and scale economies. We find that privatized banks experienced a significant increase in productivity, especially if they subsequently merged with other banks. German banks were still able to increase their productivity through consolidation. --Banking market integration,deregulation,total factor productivity,Italy,Germany

Lessons learned from the financial crisis for financial stability and banking supervision

The financial crisis that began in 2007 has revealed a need for a new supervisory and regulatory approach aimed at strengthening the system and containing the risk of future financial and economic disruptions. Three ingredients are needed to ensure financial stability: robust analysis, better regulation, and international cooperation. First, financial stability analysis must be improved to take full account of the different sources of systemic risk. Data coverage of the balance sheets of both non-bank financial institutions and the non-financial sectors should be increased. Moreover, to address the problems raised by the interconnections among financial institutions more granular and timely information on their exposures is needed. There must be further integration of macro- and micro-information and an upgrading of financial stability models. The second ingredient is the design of robust regulatory measures. Under the auspices of the G20 and the Financial Stability Board, the Basel Committee on Banking Supervision recently put forward substantial proposals on capital and liquidity. They will result in more robust capital base, lower leverage, less cyclical capital rules and better control of liquidity risk. Finally, the third ingredient is strong international cooperation. Ensuring more effective exchanges of information among supervisors in different jurisdictions and successful common actions is key in preserving financial integration, while avoiding negative cross-border spill-overs. Better resolution regimes are part of the efforts to ensure that the crisis of one institution does not impair the ability of the financial markets to provide essential services to the economy.financial crisis, international cooperation, macroprudential analysis, procyclicality, prudential regulation, stress tests

FUS mutant human motoneurons display altered transcriptome and microRNA pathways with implications for ALS pathogenesis

The FUS gene has been linked to amyotrophic lateral sclerosis (ALS). FUS is a ubiquitous RNA-binding protein, and the mechanisms leading to selective motoneuron loss downstream of ALS-linked mutations are largely unknown. We report the transcriptome analysis of human purified motoneurons, obtained from FUS wild-type or mutant isogenic induced pluripotent stem cells (iPSCs). Gene ontology analysis of differentially expressed genes identified significant enrichment of pathways previously associated to sporadic ALS and other neurological diseases. Several microRNAs (miRNAs) were also deregulated in FUS mutant motoneurons, including miR-375, involved in motoneuron survival. We report that relevant targets of miR-375, including the neural RNA-binding protein ELAVL4 and apoptotic factors, are aberrantly increased in FUS mutant motoneurons. Characterization of transcriptome changes in the cell type primarily affected by the disease contributes to the definition of the pathogenic mechanisms of FUS-linked ALS

Effect of electric field polarization and temperature on the effective permittivity and conductivity of porous anodic aluminium oxide membranes

Porous insulators offer new opportunities for the controlled guest–host synthesis of nanowires for future integrated circuits characterized by low propagation delay, crosstalk and power consumption. We propose a method to estimate the effect of the electric field polarization and temperature on the electrical properties of different types of synthesized porous anodic aluminium oxide membranes. It results that the effective permittivity along the pore axis is generally 20% higher than the one in the orthogonal direction. The type of solution and the voltage level applied during anodization are the main parameters affecting the AAO templates characteristics, i.e. their porosity and chemical content. The values of permittivity of the final material, are typically in the range 2.6–3.2 for large pore diameter membranes including phosphorus element and having a low water content, and in the range 3.5–4 for the ones with smaller pores, and showing sulphur element incorporation. Moreover, the dc conductivity of the different membranes appears to be correlated to the pore density

Reconstructions of Ir (110) and (100): an ab initio study

Prediction criteria for surface reconstructions are discussed, with reference to ab initio calculations of the (110)-$1\times 2$ missing-row and (100)-$5\times 1$ quasi-hexagonal reconstructions of Ir and Rh.Comment: 3 pages RevTeX two-column, to appear in Surface Scienc

Performance prediction of the coherent radar detector on measured UAVs data

This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. A first-order statistical analysis of the measured RCSs is firstly reported prior to assessing the radar detection performance on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets

Radar detection performance prediction using measured UAVs RCS data

This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. The experimental setup and the data pre-processing, which include coherent background subtraction and range gating procedures, are illustrated in detail. Furthermore, a thorough description of the calibration process, which is based on the substitution method, is discussed. Then, a first-order statistical analysis of the measured RCSs is provided by means of the Cramér-von Mises (CVM) distance and the Kolmogorov-Smirnov (KS) test. Finally, radar detection performance is assessed on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets

Radar detection performance via frequency agility using measured UAVs RCS data

This paper addresses radar detection performance prediction (via measured data) for drone targets using a frequency agility-based incoherent (square-law) detector. To this end, a preliminary statistical analysis of the integrated Radar Cross Section (RCS) resulting from frequency agile pulses is carried out for drones of different sizes and characteristics, using data acquired in a semi-controlled environment for distinct frequencies, angles, and polarizations. The analysis involves fitting the integrated RCS measurements with commonly used one-parametric and two-parametric probability distributions and leverages the Cramér-von Mises distance and the Kolmogorov Smirnov test. Results show that the Gamma distribution appears to accurately model the resulting fluctuations. Hence, the impact of integration and frequency agility on the RCS fluctuation dispersion is studied. Finally, detection performance of the incoherent square-law detector is assessed for different target and radar parameters, using both measured and simulated data drawn from a Gamma distribution whose parameters follow the preliminary RCS statistical analysis. The results highlight a good agreement between simulated and measurement-based curves