We document five novel empirical findings on the well-known potential ordering drawback associated with the time-varying parameter vector autoregression with stochastic volatility developed by Cogley and Sargent (2005) and Primiceri (2005), CSP-SV. First, the ordering does not affect point...

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of the mean equation follows a threshold distribution...

Contemporaneous inference from economic data releases for policy and business decisions has become increasingly relevant in the high pace of the information age. The released data are typically filtered to eliminate seasonal patterns to reveal underlying trends and cycles. The nature of economic...

The purpose of this paper is to investigate the asymptotic null distribution of stationarity and nonstationarity tests when the distribution of the error term belongs to the normal domain of attraction of a stable law in any finite sample but the error term is an i.i.d. process with finite...

Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning...

This paper applies the Bayesian method to estimate a Dynamic Stochastic General Equilibrium (DSGE) model using quarterly data for the UK over the period from 1971:Q1 through 2009:Q2. The contribution of the paper is two-fold. First, we estimate a model characterised by nominal and real...

This study was carried out to estimate underlying inflation in Nigeria using Unobserved Component (UC) model. Also, different channels were used to identify the source of inflation persistence and volatility. This was estimated using Bayesian analysis in order to examine the role of priors in...

Strategies for constructing a Markov decision chain approximating a continuous-time finite-horizon optimal control problem are investigated. Some simple, analytically soluble, examples are treated and low computational complexity is reported. Extensions to the method and implementation are...

We compare Bayesian and sample theory model specification criteria. For the Bayesian criteria we use the deviance information criterion and the cumulative density of the mean squared errors of forecast. For the sample theory criterion we use the conditional Kolmogorov test. We use Markov chain...

We study measures of foreign exchange rate volatility based on high-frequency (5-minute) $/DM exchange rate returns using recent nonparametric statistical techniques to compute realized return volatility and its separate continuous sample path and jump components, and measures based on prices of...