inflation has always been an economic problem and different solutions have been proposed to control it. although it is said that “higher output lowers inflation rate” but it is true when other factors are constant. this study searches the answer to the following question: “what is the effect of inflation rate and output in a case that inflation rate and output growth has a volatility trend?” to...

In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final...

Absfrucf -A universal nearly efficient estimator is proposed for the first order autoregressive (AR) model where the probability distribution of the driving noise is unknown. The proposed estimator has an intuitively appealing relation to universal data compression and to universal tests for randomness. Index Terms -asymptotically efficient estimation, universal estimation, Cramer-Rao bound, Fi...

We prove the large deviation principle for the posterior distributions on the (unknown) parameter of a multivariate autoregressive process with i.i.d. Normal innovations. As a particular case, we recover a previous result for univariate first-order autoregressive processes. We also show that the rate function can be expressed in terms of the divergence between two spectral densities.