This paper assesses the nowcasting performance of confidence in a one-equation model based on the Purchasing Managers Index (PMI). We look at the interactions between the PMI and confidence and the reasons why confidence affects real GDP growth besides the PMI. Moreover, we explain why our model...

This paper presents evidence that the economic stall speed concept has some empirical content, and can be moderately useful in forecasting recessions. Specifically, output tends to transition to a slow-growth phase at the end of expansions before falling into a recession, and the paper designs...

In this paper, we construct the country-specific chronologies of the house price bubbles for 12 OECD countries over the period 1969:Q1 - 2010:Q2. These chronologies are obtained using a combination of a fundamental and a filter approaches. The resulting speculative bubble chronology is the one...

We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the...

We construct a framework for measuring economic activity in real time (e.g., minute-by-minute), using a variety of stock and flow data observed at mixed frequencies. Specifically, we propose a dynamic factor model that permits exact filtering, and we explore the efficacy of our methods both in a...

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a...

This paper considers a sticky price model with a cash-in-advance constraint where agents forecast inflation rates with the help of econometric models. Agents use least squares learning to estimate two competing models of which one is consistent with rational expectations once learning is...

The question of what is the economic environment that is most likely to anticipate a recession is still open, as the literature has emphasized either the importance of deteriorating financial conditions and that of worsening macroeconomic indicators. Using a probit forecasting model, we show...

In this paper we apply economic narratives to inflation forecasting using a large news corpus and machine learning algorithms. We measure economic narratives quantitatively from the full text content of over 880,000 Wall Street Journal articles and represent them as interpretable news topics....

This paper develops a simulation-based solution method to solve large state space macrofinance models using machine learning. We use a neural network (NN) to approximate the expectations in the optimality conditions in the spirit of the stochastic parameterized expectations algorithm (PEA)....