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...

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...

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...

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...

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...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...

This paper proposes a methodology to nowcast and forecast inflation using data with sampling frequency higher than monthly. The nowcasting literature has been focused on GDP, typically using monthly indicators in order to produce an accurate estimate for the current and next quarter. This paper...

This paper studies professional forecasts on a micro level using three alternative data sets. The analysis is mainly based on the ECB Survey of Professional Forecasts for the euro area, but for comparison, Consensus Economics survey and the Survey of Professional Forecasts for the US are also...

This paper studies uncertainty using the ECB Survey of Professional Forecasters' data. We consider both inflation and real GDP growth forecasts at the micro level and explore forecast uncertainty using two alternative measures, i.e. conventional standard deviation of individual point forecasts...