Using the survey data of U.S. professional forecasters, this paper assesses how their inattentiveness evolve over time and its implications for fluctuations in dispersion among their forecasts. To do so, I employ a time-varying structural VAR consisting of dispersion among forecasters and...

In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is...

Strong consistency of least squares estimators of the slope parameter in simple linear regression models is established for predetermined stochastic regressors. The main result covers a class of models which falls outside the applicability of what is presently available in the literature. An...

This study investigates the utility of business uncertainty indicators as predictive tools for forecasting economic activity in the context of Russia. In an era characterized by global economic volatility and geopolitical shifts, understanding the dynamics of economic uncertainty and its impact...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

This paper evaluates whether the primary and secondary dissemination of earnings forecast revisions by security analysts is reflected in security prices. Security prices were used to determine the profitability (before the cost of search) of trading strategies based on the nonpublic knowledge of...

This paper provides an adaptive model depicting the interaction between the disclosure of interim earnings and the accuracy of earnings forecasts that are made public by security analysts. Our results indicate that accuracy of annual earnings forecasts is highly correlated with the announcement...

Via the use of rolling regression technique and a specific procedure for analyzing strong structural breaks in a univariate time series model, we forecast the rate of future inflation in Finland for the time period of unregulated financial markets since the beginning of 1987. We are able to...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

By using the Economic Sentiment Indicator and Autoregressive Markov Switching models, this paper provides an effective tool to identify and characterize expectations of business cycle phases for Germany, Spain, the Euro Area, and the European Union. This information is useful for policy makers...