Add to ORKGMany contemporaneously aggregated variables have stochastic aggregation weights. We compare different forecasts for such variables including univariate forecasts of the aggregate, a multivariate forecast of the aggregate that uses information from the disaggregate components, a forecast which aggregates a multivariate forecast of the disaggregate components and the aggregation weights, and a forecast which aggregates univariate forecasts for individual disaggregate components and the aggregation weights. In empirical illustrations based on aggregate GDP and money growth rates, we find forecast efficiency gains from using the information in the stochastic aggregation weights. A Monte Carlo study confirms that using the Information on stochas...
The aggregation of the variables that compose an indicator, as GDP, which should beforecasted, is no...
When forecasting aggregated time series, several options are available. For example, the multivariat...
Temporal aggregation (TA) refers to transforming a time series from higher to lower frequencies (e.g...
Many contemporaneously aggregated variables have stochastic aggregation weights. We compare differen...
We explore whether forecasting an aggregate variable using information on its disaggregate component...
Despite the fact that many aggregates are nonlinear functions and the aggregation weights of many ma...
To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts o...
We extend the “bottom up” approach for forecasting economic aggregates with disaggregates to probabi...
We propose a methodology for producing forecast densities for economic aggregates based on disaggreg...
Aggregated times series variables can be forecasted in different ways. For example, they may be fore...
This paper compares the performance of “aggregate” and “disaggregate” predictors in forecasting cont...
European Monetary Union (EMU) member countries' forecasts are often combined to obtain the forecasts...
The aggregation of the variables that compose an indicator, as GDP, which should be forecasted, is n...
When forecasting aggregated time series, several options are available. For example, the multivariat...
This paper focuses on providing consistent forecasts for an aggregate economic indicator, such as a...
The aggregation of the variables that compose an indicator, as GDP, which should beforecasted, is no...
When forecasting aggregated time series, several options are available. For example, the multivariat...
Temporal aggregation (TA) refers to transforming a time series from higher to lower frequencies (e.g...
Many contemporaneously aggregated variables have stochastic aggregation weights. We compare differen...
We explore whether forecasting an aggregate variable using information on its disaggregate component...
Despite the fact that many aggregates are nonlinear functions and the aggregation weights of many ma...
To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts o...
We extend the “bottom up” approach for forecasting economic aggregates with disaggregates to probabi...
We propose a methodology for producing forecast densities for economic aggregates based on disaggreg...
Aggregated times series variables can be forecasted in different ways. For example, they may be fore...
This paper compares the performance of “aggregate” and “disaggregate” predictors in forecasting cont...
European Monetary Union (EMU) member countries' forecasts are often combined to obtain the forecasts...
The aggregation of the variables that compose an indicator, as GDP, which should be forecasted, is n...
When forecasting aggregated time series, several options are available. For example, the multivariat...
This paper focuses on providing consistent forecasts for an aggregate economic indicator, such as a...
The aggregation of the variables that compose an indicator, as GDP, which should beforecasted, is no...
When forecasting aggregated time series, several options are available. For example, the multivariat...
Temporal aggregation (TA) refers to transforming a time series from higher to lower frequencies (e.g...