The Impact of State Taxes on Self-Insurance

This paper assesses whether insurers' state taxes reduce purchases of property-casualty coverage. Tests are conducted using state aggregates of insurer-level data from publicly-available, annual accounting reports for 1993, 1994, and 1995. A positive relation between self-insurance and state taxes is detected, consistent with consumers opting to self-insure rather than bear the incidence of higher insurer taxes. The primary empirical estimates imply that a 1 percent increase in the state premium tax rate reduces non-automobile insured losses by 0.18 percent to 0.28 percent. These elasticities suggest that for the mean state, a standard deviation increase in the state tax rate (0.5 percent) would lower insured losses by approximately $140 million or 7.5 percent of current coverage. As expected, tax effects vary with the elasticity of demand. When demand is largely inelastic, e.g., automobile liability coverage, taxes do not affect self-insurance.

Inverse Statistics in the Foreign Exchange Market

We investigate intra-day foreign exchange (FX) time series using the inverse statistic analysis developed in [1,2]. Specifically, we study the time-averaged distributions of waiting times needed to obtain a certain increase (decrease) $\rho$ in the price of an investment. The analysis is performed for the Deutsch mark (DM) against the $US for the full year of 1998, but similar results are obtained for the Japanese Yen against the$US. With high statistical significance, the presence of "resonance peaks" in the waiting time distributions is established. Such peaks are a consequence of the trading habits of the markets participants as they are not present in the corresponding tick (business) waiting time distributions. Furthermore, a new {\em stylized fact}, is observed for the waiting time distribution in the form of a power law Pdf. This result is achieved by rescaling of the physical waiting time by the corresponding tick time thereby partially removing scale dependent features of the market activity.Comment: 8 pages. Accepted Physica

Stochastic collective dynamics of charged--particle beams in the stability regime

We introduce a description of the collective transverse dynamics of charged (proton) beams in the stability regime by suitable classical stochastic fluctuations. In this scheme, the collective beam dynamics is described by time--reversal invariant diffusion processes deduced by stochastic variational principles (Nelson processes). By general arguments, we show that the diffusion coefficient, expressed in units of length, is given by $\lambda_c\sqrt{N}$, where $N$ is the number of particles in the beam and $\lambda_c$ the Compton wavelength of a single constituent. This diffusion coefficient represents an effective unit of beam emittance. The hydrodynamic equations of the stochastic dynamics can be easily recast in the form of a Schr\"odinger equation, with the unit of emittance replacing the Planck action constant. This fact provides a natural connection to the so--called ``quantum--like approaches'' to beam dynamics. The transition probabilities associated to Nelson processes can be exploited to model evolutions suitable to control the transverse beam dynamics. In particular we show how to control, in the quadrupole approximation to the beam--field interaction, both the focusing and the transverse oscillations of the beam, either together or independently.Comment: 15 pages, 9 figure

Statistical Dynamics of Religions and Adherents

Religiosity is one of the most important sociological aspects of populations. All religions may evolve in their beliefs and adapt to the society developments. A religion is a social variable, like a language or wealth, to be studied like any other organizational parameter. Several questions can be raised, as considered in this study: e.g. (i) from a ``macroscopic'' point of view : How many religions exist at a given time? (ii) from a ``microscopic'' view point: How many adherents belong to one religion? Does the number of adherents increase or not, and how? No need to say that if quantitative answers and mathematical laws are found, agent based models can be imagined to describe such non-equilibrium processes. It is found that empirical laws can be deduced and related to preferential attachment processes, like on evolving network; we propose two different algorithmic models reproducing as well the data. Moreover, a population growth-death equation is shown to be a plausible modeling of evolution dynamics in a continuous time framework. Differences with language dynamic competition is emphasized.Comment: submitted to EP

Markov processes and generalized Schroedinger equations

Starting from the forward and backward infinitesimal generators of bilateral, time-homogeneous Markov processes, the self-adjoint Hamiltonians of the generalized Schroedinger equations are first introduced by means of suitable Doob transformations. Then, by broadening with the aid of the Dirichlet forms the results of the Nelson stochastic mechanics, we prove that it is possible to associate bilateral, and time-homogeneous Markov processes to the wave functions stationary solutions of our generalized Schroedinger equations. Particular attention is then paid to the special case of the Levy-Schroedinger equations and to their associated Levy-type Markov processes, and to a few examples of Cauchy background noise

The digitalization of supply chain: A review

The emergence of new digital technologies as part of Industry 4.0 has enabled the supply chain to be managed more efficiently. We talk about digitalization of the supply chain and this trend refers to the evolution towards a smarter model that involves digital technologies such as Blockchain, IoT, Machine Learning, etc. These technologies actually increase and enhance the ability to optimize planning, sourcing and procurement strategies. Since this topic is of relevant interest for the scientific community, this paper aims to investigate the main discussion themes related to supply chain digitalization using a keyword-based organizing framework to identify, classify and investigate relevant intellectual contributions in this field. Results showed which are the main issues regarding supply chain digitalization as well as promising future research avenues

On the Effect of Channel Knowledge in Underwater Acoustic Communications: Estimation, Prediction and Protocol

Underwater acoustic communications are limited by the following channel impairments: time variability, narrow bandwidth, multipath, frequency selective fading and the Doppler effect. Orthogonal Frequency Division Modulation (OFDM) is recognized as an effective solution to such impairments, especially when optimally designed according to the propagation conditions. On the other hand, OFDM implementation requires accurate channel knowledge atboth transmitter and receiver sides. Long propagation delay may lead to outdated channel information. In this work, we present an adaptive OFDM scheme where channel state information is predicted through a Kalman-like filter so as to optimize communication parameters, including the cyclic prefix length. This mechanism aims to mitigate the variability of channel delay spread. This is cast in a protocol where channel estimation/prediction are jointly considered, so as to allow efficiency. The performance obtained through extensive simulations using real channels and interference show the effectiveness of the proposed scheme, both in terms of rate and reliability, at the expense of an increasing complexity. However, this solution is significantly preferable to the conventional mechanism, where channel estimation is performed only at the receiver, with channel coefficients sent back to the transmit node by means of frequent overhead signaling

Blind fractionally spaced channel equalization for shallow water PPM digital communications links

Underwater acoustic digital communications suffer from inter-symbol interference deriving from signal distortions caused by the channel propagation. Facing such kind of impairment becomes particularly challenging when dealing with shallow water scenarios characterized by short channel coherence time and large delay spread caused by time-varying multipath effects. Channel equalization operated on the received signal represents a crucial issue in order to mitigate the effect of inter-symbol interference and improve the link reliability. In this direction, this contribution presents a preliminary performance analysis of acoustic digital links adopting pulse position modulation in severe multipath scenarios. First, we show how the spectral redundancy offered by pulse position modulated signals can be fruitfully exploited when using fractional sampling at the receiver side, which is an interesting approach rarely addressed by the current literature. In this context, a novel blind equalization scheme is devised. Specifically, the equalizer is blindly designed according to a suitably modified Bussgang scheme in which the zero-memory nonlinearity is replaced by a M-memory nonlinearity, M being the pulse position modulation order. Numerical results not only confirm the feasibility of the technique described here, but also assess the quality of its performance. An extension to a very interesting complex case is also provided

Lexical evolution rates by automated stability measure

Phylogenetic trees can be reconstructed from the matrix which contains the distances between all pairs of languages in a family. Recently, we proposed a new method which uses normalized Levenshtein distances among words with same meaning and averages on all the items of a given list. Decisions about the number of items in the input lists for language comparison have been debated since the beginning of glottochronology. The point is that words associated to some of the meanings have a rapid lexical evolution. Therefore, a large vocabulary comparison is only apparently more accurate then a smaller one since many of the words do not carry any useful information. In principle, one should find the optimal length of the input lists studying the stability of the different items. In this paper we tackle the problem with an automated methodology only based on our normalized Levenshtein distance. With this approach, the program of an automated reconstruction of languages relationships is completed