- Consulting Editors
- Vars, Cointegration, and Common Cycle Restrictions
- Dynamic Factor Models
- Forecasting With Nonlinear Time Series Models
- Forecasting With DSGE Models
- Forecasting Economic Time Series Using Unobserved Components Time Series Models
- Improving the Role of Judgment in Economic Forecasting
- Forecasting with Mixed-Frequency Data
- Forecasting with Real-Time Data Vintages
- Forecasting from misspecified Models in the Presence of Unanticipated Location Shifts
- Forecasting Breaks and Forecasting During Breaks
- Forecast Combinations
- Multiple Forecast Model Evaluation
- Testing for Unconditional Predictive Ability
- Testing Conditional Predictive Ability
- Interpreting and Combining Heterogeneous Survey Forecasts
- Analyzing Three-Dimensional Panel Data of Forecasts
- Forecasting Financial Time Series
- Forecasting Volatility Using High-Frequency Data
- Economic Value of Weather and Climate Forecasts
- Long-Horizon Growth Forecasting and Demography
- Forecasting the Energy Markets
- Models for Health Care
- Election Forecasting
- Marketing and Sales
Abstract and Keywords
This article focuses on the forecasting of national GDP measures at long horizons, and argues that demography should be taken into account. It is organized as follows. Section 2 provides a brief discussion of some crucial theoretical issues for forecasting growth. Section 3 discusses the connection between demography and economic growth. Section 4 discusses alternative approaches and methods to make use of demographic–economic connections and the scope for combination forecasts in order to allow for long-run features. Section 5 summarizes the discussion.
Thomas Lindh is a professor in labour economics at Linnaeus University, Vaxjo, Sweden, but is also affiliated with the Institute for Futures Studies in Stockholm. His research has been focused on issues of economic growth and demographic structure, including the use of demographic variables for forecasting.
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