This paper reviews the analysis of the threshold autoregressive, smooth threshold autoregressive, and Markov switching autoregressive models from the Bayesian perspective. For each model we start by describing a baseline model and discussing possible extensions and applications. Then we review the choice of prior, inference, tests against the linear hypothesis, and conclude with models selectio...

Multiresolution wavelet analysis is a natural way to decompose economic time series into components of various frequencies: long-run trend, business-cycle component, and high frequency noise. This paper illustrates the method on real GNP and inflation. The business-cycle component of the wavelet-filtered series closely resembles the series filtered by the approximate bandpass filter (Baxter and...

This paper assesses whether the UK public finances were sustainable for the period 1919 to 2001 using a nonlinear representation of the debt to GDP ratio and thus provides a more robust test of debt sustainability. Empirical evidence supports debt sustainability. Moreover, the ESTAR representation is evidence that sustainability is the result of active debt management rather than tax-smoothing....

Monthly seasonally unadjusted data can exhibit roots with possibly fractional orders of integration, corresponding to the monthly but also to the quarterly and to the long-run or trending components of the series. In this paper we use a procedure which is suitable to test simultaneously for the order of integration of each of these components and apply it to several US monetary aggregates. JEL ...

this paper aims to investigate the role of each aggregate spending component in the monetary policy transmission in indonesia. it assesses the relative strength of the role of each spending component in the monetary policy transmission. in so doing, this study employs the contribution analysis, which is calculated based on the cumulative impulse response of each component of gdp to a monetary p...

A panel of ex-ante forecasts of a single time series is modeled as a dynamic factor model, where the conditional expectation is the single unobserved factor. When applied to out-of-sample forecasting, this leads to combination forecasts that are based on methods other than OLS. These methods perform well in a Monte Carlo experiment. These methods are evaluated empirically in a panel of simulate...

Abstract The aim of the paper is to compare forecasting performance a class statedependent autoregressive (SDAR) models for univariate time series with two alternative families nonlinear models, such as SETAR and GARCH models. study conducted on US GDP growth rate using quarterly data. Two methods forecast comparison are employed. first method consists in evaluation average by measures root mea...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions ability to flexibly whole distribution inflation. In order make our approach accessible and relevant forecasting, we derive an efficient Gibbs sampler by transforming stat...

abstract comparison of food prices in different periods, indicates fluctuations and continually upward trend. any change in agricultural sector variables, as main food supplier, will affect food price. productivity shocks and production gap are examples of such variables. in this paper ,hodrick prescott and kalman filters are used as generators of productivity shocks and production gap series. ...

This paper provides a comprehensive analysis of the interest rate pass-through euro area monetary policy to retail rates outside area, contributing literature on consequences unofficial financial euroisation and transmission channels spillovers. The results suggest that in long run, more than one third all euroised countries central, eastern south-eastern Europe (CESEE) are linked shadow rate. ...