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Using a dynamic factor model that allows for changes in both the long- run growth rate of output and the volatility of business cycles, we document a significant decline in long-run output growth in the United States. Our evidence supports the view that this slowdown started prior to the Great...
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Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously...
Persistent link: https://www.econbiz.de/10012422115
Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously...
Persistent link: https://www.econbiz.de/10012259379
We show that the single-index dynamic factor model developed by Aruoba and Diebold (Am Econ Rev, 100:20-24, 2010) to construct an index of US business cycle conditions is also very useful for forecasting US GDP growth in real time. In addition, we adapt the model to include survey data and...
Persistent link: https://www.econbiz.de/10010936748
We propose a Markov-switching dynamic factor model to construct an index of global business cycle conditions, for performing short-term forecasts of quarterly world GDP growth in real time and computing real-time business cycle probabilities. To overcome the real-time forecasting challenges, the...
Persistent link: https://www.econbiz.de/10011212880
This paper proposes two refinements to the single-index dynamic factor model developed by Aruoba and Diebold (AD, 2010) to monitor US economic activity in real time. First, we adapt the model to include survey data and financial indicators. Second, we examine the predictive performance of the...
Persistent link: https://www.econbiz.de/10011132493
Learning with bounded memory in stochastic frameworks is incomplete in the sense that the learning dynamics cannot converge to an REE. The properties of the dunamics arising from such rules are studied for models with steady states. If in standard linear models the REE is in a certain sense...
Persistent link: https://www.econbiz.de/10005625278