Forecasting aggregates using panels of nonlinear time series
2004-11-05
Research Paper
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Macroeconomic time series such as total unemployment or total industrial production concern data which are aggregated across regions, sectors, or age categories. In this paper we examine if forecasts for these aggregates can be improved by considering panel models for the disaggregate series. As many macroeconomic variables have nonlinear properties, we specifically focus on panels of nonlinear time series. We discuss the representation of such models, parameter estimation and a method to generate forecasts. We illustrate the usefulness of our approach for simulated data and for the US coincident index, making use of state-specific component series.
Keywords
Classifications using
Journal of Economic Literature (JEL) Classification System
- C51 : Model Construction and Estimation
- C53 : Forecasting and Other Model Applications
- C23 : Models with Panel Data
- E32 : Business Fluctuations; Cycles
Automatically Extracted Terms
- model
- state
- forecast
- growth
- series
- panel
- parameter
- panel star model
- growth rates
- forecasting
- indicator
- growth rate
- value
- index
- level
- cycle
- business
- state i
- nonlinear
- log yt
