The Contribution of Growth and Interest Rate Differentials to the Persistence of Real Exchange Rates.

This paper employs a new methodology for measuring the contribution of growth and interest rate differentials to the half-life of deviations from Purchasing Power Parity (PPP). Our method is based on directly comparing the impulse response function of a VAR model, where the real exchange rate is Granger caused by these variables with the impulse response function of a univatiate ARMA model for the real exchange rate. We show that the impulse response function of the VAR model is not, in general, the same with the impulse response function obtained from the equivalent ARMA representation, if the real exchange rate is Granger caused by other variables in the system. The difference between the two functions captures the effects of the Granger-causing variables on the half-life of deviations from PPP. Our empirical results for a set of four currencies suggest that real and nominal long term interest rate differentials and real GDP growth differentials account for 22% to 50% of the half-life of deviations from PPP.real exchange rate; persistence measures; VAR; impulse response function; PPP

Nonparametric estimation of mark's distribution of an exponential Shot-noise process

In this paper, we consider a nonlinear inverse problem occurring in nuclear science. Gamma rays randomly hit a semiconductor detector which produces an impulse response of electric current. Because the sampling period of the measured current is larger than the mean inter arrival time of photons, the impulse responses associated to different gamma rays can overlap: this phenomenon is known as pileup. In this work, it is assumed that the impulse response is an exponentially decaying function. We propose a novel method to infer the distribution of gamma photon energies from the indirect measurements obtained from the detector. This technique is based on a formula linking the characteristic function of the photon density to a function involving the characteristic function and its derivative of the observations. We establish that our estimator converges to the mark density in uniform norm at a logarithmic rate. A limited Monte-Carlo experiment is provided to support our findings.Comment: Electronic Journal of Statistics, Institute of Mathematical Statistics and Bernoulli Society, 201

Impulse/response functions of individual components of flow-injection manifolds

The dispersion behaviour of the various individual parts making up a flow-injection manifold is often difficult to establish because it is virtually impossible to obtainthe required very small injection and detection volumes. It is shown that it is possible, under suitable experimental conditions, to find the impulse/response functionof each component by means of a deconvolution process of the response functions have been established, the response function of any arrangement can be predicted by convoluting the impulse/response functions of all the individuaol parts involved. Convolution and deconvolution were done in the Fourier domain, by using a fast FT algorithm

Impulse-response functions of several detectors used in flow-injection analysis

A procedure for the determination of the impulse-response function of a detector is given. Its application to photometers, ion-sensitive field effect transistors, a potentiometric detector at constant current and a voltammetric detector shows that the impulse-response function can be used to obtain specific information about the performance of the detector in the manifold. This function clearly shows the contribution of the detector to the peak broadening and how the detector generates the final signal from the presented concentration profile. From this information one could derive improvements to the detector, such as changing the construction of the detector cell, minimizing the influence of other parts of the manifold or adapting the attached electronics

On the construction of a digital transfer function from its real part on unit circle

It is shown in this correspondence that the system function H(z) of a linear time invariant (LTI) causal digital filter with real impulse response coefficients can be obtained from the real part of its frequency response HR(ejω) given in the form of a rational trigonomentric function, using algebraic methods rather than complex contour integration techniques

Real-Time Nearfield Acoustic Holography: Implementation of the Direct and Inverse Impulse Responses in the Time-Wavenumber Domain

The aim of the study is to demonstrate that some methods are more relevant for implementing the Real-Time Nearfield Acoustic Holography than others. First by focusing on the forward propagation problem, different approaches are compared to build the impulse response to be used. One of them in particular is computed by an inverse Fourier transform applied to the theoretical transfer function for propagation in the frequency-wavenumber domain. Others are obtained by directly sampling an analytical impulse response in the time-wavenumber domain or by additional low-pass filtering. To estimate the performance of each impulse response, a simulation test involving several monopoles excited by non stationary signals is presented and some features are proposed to assess the accuracy of the temporal signals resulting from reconstruction processing on a forward plane. Then several inverse impulse responses used to solve the inverse problem, which consists in back propagating the acoustic signals acquired by the microphone array, are built directly from a transfer function or by using Wiener inverse filtering from the direct impulse responses obtained for the direct problem. Another simulation test is performed to compare the signals reconstructed on the source plane. The same indicators as for the propagation study are used to highlight the differences between the methods tested for solving the Holography inverse problem.Comment: 15 th International Congress on Sound and Vibration, Daejeon : Cor\'ee, R\'epublique de (2008

The Contribution of Growth and Interest Rate Differentials to the Persistence of Real Exchange Rates

This paper employs a new methodology for measuring the contribution of growth and interest rate differentials to the half-life of deviations from Purchasing Power Parity (PPP). Our method is based on directly comparing the impulse response function of a VAR model, where the real exchange rate is Granger caused by these variables with the impulse response function of a univatiate ARMA model for the real exchange rate. We show that the impulse response function of the VAR model is not, in general, the same with the impulse response function obtained from the equivalent ARMA representation, if the real exchange rate is Granger caused by other variables in the system. The difference between the two functions captures the effects of the Granger-causing variables on the half-life of deviations from PPP. Our empirical results for a set of four currencies suggest that real and nominal long term interest rate differentials and real GDP growth differentials account for 22% to 50% of the half-life of deviations from PPP.real exchange rate; persistence measures; VAR; impulse response function; PPP.

Solving DSGE Models with a Nonlinear Moving Average

We introduce a nonlinear infinite moving average as an alternative to the standard state-space policy function for solving nonlinear DSGE models. Perturbation of the nonlinear moving average policy function provides a direct mapping from a history of innovations to endogenous variables, decomposes the contributions from individual orders of uncertainty and nonlinearity, and enables familiar impulse response analysis in nonlinear settings. When the linear approximation is saddle stable and free of unit roots, higher order terms are likewise saddle stable and first order corrections for uncertainty are zero. We derive the third order approximation explicitly and examine the accuracy of the method using Euler equation tests.Perturbation, nonlinear impulse response, DSGE, solution methods

Modeling spin transport with current-sensing spin detectors

By incorporating the proper boundary conditions, we analytically derive the impulse response (or "Green's function") of a current-sensing spin detector. We also compare this result to a Monte-Carlo simulation (which automatically takes the proper boundary condition into account) and an empirical spin transit time distribution obtained from experimental spin precession measurements. In the strong drift-dominated transport regime, this spin current impulse response can be approximated by multiplying the spin density impulse response by the average drift velocity. However, in weak drift fields, large modeling errors up to a factor of 3 in most-probable spin transit time can be incurred unless the full spin current Green's function is used