This text provides up-to-date coverage of both new developments and well-established fields in the sphere of economic forecasting. The articles aim to provide accounts of the key concepts, subject matter, and techniques in a number of diverse but related areas. It covers the ways in which the availability of ever more plentiful data and computational power have been used in forecasting, either in terms of the frequency of observations, the number of variables, or the use of multiple data vintages. Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained; the volume provides explanations and critiques of these developments. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models, as well as models for handling data observed at mixed frequencies, high-frequency data, multiple data vintages, and methods for forecasting when there are structural breaks, and how breaks might be forecast. Also covered are areas that are less commonly associated with economic forecasting, such as climate change, health economics, long-horizon growth forecasting, and political elections. Econometric forecasting has important contributions to make in these areas, as well as their developments informing the mainstream. In the early twenty-first century, climate change and the forecasting of health expenditures and population are topics of pressing importance.
Keywords: economic forecasting, frequency of observations, number of variables, multiple data vintages, statistical theory, economic theory, factor models, DSGE models, restricted vector autoregressions, non-linear models