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The literature on economic forecasting has made great strides in the past ten to fifteen years. For example, new real-time databases have led to the development of new tools that can account for revisions to past data; dynamic stochastic general equilibrium models are increasingly being used to forecast; and diffusion indexes allow forecasters to incorporate the information in hundreds of series when producing forecasts. However, from a practical perspective, such innovations have not trickled-down into the toolboxes of most professional economists. When confronted with a practical forecasting problem, many of these tend to rely on simple approaches that they know and understand, such as vector autoregressions (VARs). Many existing forecasting texts are typically either beyond the scope of practitioners who simply wish to learn some of the latest tools or issues or are written at too introductory a level. In light of the above, this textbook aims to bridge the gap between the specialized forecasting literature and the ultimate producers of forecasts.
List of contents
Part One: Background Material 1. Introduction 2. Data 3. Topics in Econometrics Part Two: Forecasting Econometrics 4. Forecast Evaluation 5. Time Series Methods 6. Leading Indicators 7. Error-Correction Models 8. Dynamic Stochastic General Equilibrium (DSGE) Models 9. Nonlinear Methods 10. Forecast Combination 11. Forecast Horizons Part Three: Special Topics 12. Density Forecasting 13. Nowcasting 14. Forecasts of Binary Variables
About the author
Greg Tkacz is Assistant Chief of the Canadian Economic Analysis Department at the Bank of Canada. He teaches in the economics department at the University of Ottawa and has also held positions at McGill and Carleton Universities.
