This paper investigates sensitivity of U.S. natural gas price to crude oil price changes, using time-varying coefficient models. Identification of the range of variation of the sensitivity of natural gas price to oil price change allows more accurate assessment of upper and minimum risk levels...

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

The transition process of the Romanian economy motivated the design of a model that provides for a parsimonious representation of the structure of the economy, exploits the increased availability of data for the system of national accounts, and recognizes time-variant parameters that can result...

The study aims to calculate Egypt’s real effective exchange rate at both the bilateral and multilateral levels, estimates the effect of real cross-rate movements on trade in goods and services and on foreign direct investment, and determines the fundamental equilibrium exchange rate for...

We propose a theoretical approach to bandwidth choice for continuous-time Markov processes. We do so in the context of stationary and nonstationary processes of the recurrent kind. The procedure consists of two steps. In the first step, by invoking local Gaussianity, we suggest an automated...

The study develops a parsimonious representation of the macro economy of Bangladesh. It aims to serve a dual purpose. First, it provides a framework for making rational and consistent predictions about Bangladesh's overall economic activity, the standard components of the balance of payments,...

Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e.g. contrarian or cyclical), provide greater robustness to jumps and outliers, and guarantee the positivity of volatility. The latter is not guaranteed in ordinary ARCH models, in particular when...

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag (ADL) model is chosen. The results show that a...

The paper compares one-period ahead forecasting performance of linear vector-autoregressive (VAR) models and single-equation Markov-switching (MS) models for two cases: when leading information is available and when it is not. The results show that single-equation MS models tend to perform...

I present evidence that higher frequency measures of inflation expectations outperform lower frequency measures of inflation expectations in tests of accuracy, predictive power, and rationality. For decades, the academic literature has focused on three survey measures of expected inflation: the...