In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To investigate the forecasting performance of the models, two naive benchmark models (one is a variant of a random walk and the other is an autoregressive model) are first built based on...

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

In general, central banks are concerned with keeping the inflation rate stable while also sustaining output close to an efficient level. Under "inflation targeting", forecasts of the evolution of the general price level are an essential input for policy decisions and these are usually released...

In this paper, we analyse nominal exchange rate and price dynamics after risk shocks with short-term interest rates constrained by the zero lower bound (ZLB). We show with a stylized theoretical model that temporary risk shocks may lead to permanent shifts of the exchange rate and the price...

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

This paper studies the role of the real money gap - the deviation of real money balance from its long-run equilibrium level - for predicting inflation in India. Using quarterly data on manufacturing inflation from 1982 to 2007, we find that the real money gap is a significant predictor of...

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment...

Assessing macroeconomic demand conditions is critical for monetary policy to gaugeimminent inflationary pressures. Generally, measures of output gap, calculated byapplying statistical filters on GDP data, are used for this purpose. GDP data, however,are released only at quarterly frequency with...

Forecasting inflation is an important and challenging task. In this paper we assume that the core inflation components evolve as a multivariate local level process. This model, which is theoretically attractive for modelling inflation dynamics, has been used only to a limited extent to date...

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...