We evaluate various economic models ’ relative performance in forecasting future US output growth and inflation on a monthly basis. Our approach takes into account the possibility that the models ’ relative performance can be varying over time. We show that the models’ relative performance has, in fact, changed dramatically over time, both for revised and real-time data, and investigate possible factors that might explain such changes. In addition, this paper establishes two empirical stylized facts. Namely, most predictors for output growth lost their predictive ability in the mid-1970s, and became essentially useless in the last two decades. When forecasting inflation, instead, fewer predictors are significant, and their predictive abilit...
Forecasting has become one of the widely discussed aspects of business cycle theory and policy. It i...
Abstract: We compare the medium-term GDP growth forecasts generated by experts to those generated b...
We examine how the accuracy of real-time forecasts from models that include autoregressive terms can...
High forecasting power is essential for understanding scientific relationships. In economics, foreca...
A theoretical model for growth or inflation should be able to reproduce the empirical features of th...
Have macroeconomic forecasts grown more or less accurate over time? This paper assembles, examines, ...
In this paper, we evaluate the relative merits of three alternative approaches to extracting informa...
We investigate how the forecasting performance of the Federal Reserve Greenbooks has changed relativ...
Forecasts are presented for the 12-month ahead US rate of inflation measured by the chain weighted p...
ABSTRACT Dynamic stochastic general equilibrium (DSGE) models are a prominent tool for forecasting a...
These lecture notes codify extensive recent research on economic forecasting. When a forecast-ing mo...
This paper considers the forecast performance of the Federal Reserve staff, five atheo-retical reduc...
This paper revisits inflation forecasting using reduced form Phillips curve forecasts, i.e., inflati...
We assess the forecasting performance of the nowcasting model developed at the New York FED. We show...
A theoretical model for growth or inflation should be able to reproduce the empirical features of th...
Forecasting has become one of the widely discussed aspects of business cycle theory and policy. It i...
Abstract: We compare the medium-term GDP growth forecasts generated by experts to those generated b...
We examine how the accuracy of real-time forecasts from models that include autoregressive terms can...
High forecasting power is essential for understanding scientific relationships. In economics, foreca...
A theoretical model for growth or inflation should be able to reproduce the empirical features of th...
Have macroeconomic forecasts grown more or less accurate over time? This paper assembles, examines, ...
In this paper, we evaluate the relative merits of three alternative approaches to extracting informa...
We investigate how the forecasting performance of the Federal Reserve Greenbooks has changed relativ...
Forecasts are presented for the 12-month ahead US rate of inflation measured by the chain weighted p...
ABSTRACT Dynamic stochastic general equilibrium (DSGE) models are a prominent tool for forecasting a...
These lecture notes codify extensive recent research on economic forecasting. When a forecast-ing mo...
This paper considers the forecast performance of the Federal Reserve staff, five atheo-retical reduc...
This paper revisits inflation forecasting using reduced form Phillips curve forecasts, i.e., inflati...
We assess the forecasting performance of the nowcasting model developed at the New York FED. We show...
A theoretical model for growth or inflation should be able to reproduce the empirical features of th...
Forecasting has become one of the widely discussed aspects of business cycle theory and policy. It i...
Abstract: We compare the medium-term GDP growth forecasts generated by experts to those generated b...
We examine how the accuracy of real-time forecasts from models that include autoregressive terms can...