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Recent empirical work has considered the prediction of inflation by combining the information in a large number of time … the forecasts over a large number of different models, each of which is a linear regression model that relates inflation … pseudo out-of-sample prediction of US inflation, and find that it gives more accurate forecasts than simple equal weighted …
Persistent link: https://www.econbiz.de/10014075008
In this paper we consider the value of Google Trends search data for nowcasting (and forecasting) GDP growth for a developed (U.S.) and emerging-market economy (Brazil). Our focus is on the marginal contribution of "Big Data" in the form of Google Trends data over and above that of traditional...
Persistent link: https://www.econbiz.de/10013222547
applied to quarterly and monthly US inflation in an empirical study. We find that the persistence of quarterly inflation has … and density forecasts for monthly US inflation …
Persistent link: https://www.econbiz.de/10012924242
applied to quarterly and monthly US inflation in an empirical study. We find that the persistence of quarterly inflation has … and density forecasts for monthly US inflation. …
Persistent link: https://www.econbiz.de/10011809984
estimates for inflation forecasting both in the short term (one-quarter and one-year ahead) and the medium term (two-year and … measure appears superior to all others in all respects. - Output gap ; real-time data ; euro area ; inflation forecasts ; real …
Persistent link: https://www.econbiz.de/10003971060
We provide a new way to filter US inflation into trend and cycle components, based on extracting long-run forecasts …, then estimating parameters, and then extracting the stochastic trend in inflation. The trend-cycle model with unobserved … components is consistent with numerous studies of US inflation history and is of interest partly because the trend may be viewed …
Persistent link: https://www.econbiz.de/10009788463
Persistent link: https://www.econbiz.de/10003729279
The difficulty in modelling inflation and the significance in discovering the underlying data generating process of … inflation is expressed in an ample literature regarding inflation forecasting. In this paper we evaluate nonlinear machine … learning and econometric methodologies in forecasting the U.S. inflation based on autoregressive and structural models of the …
Persistent link: https://www.econbiz.de/10012953784
year ahead inflation. In addition, it turns out that the performance of MDS model forecasting is competitive in comparison … with other models found to be useful in the inflation forecasting literature. …
Persistent link: https://www.econbiz.de/10011720713
variables such as inflation or employment. A key aspect of this challenge is evaluating the incoming flow of information …
Persistent link: https://www.econbiz.de/10012967136