David Hendry’s automated econometric methodology

This paper focuses on the econometric methodology developed by Professor David Hendry, Hendry’s Methodology (HM), with his associates over more than 50 years. It discusses the statistical foundations of the methodology and formulates a framework that structures the content of HM into four main planks, incorporating 11 basic methodology features which are then explained in detail. They include: the Local Data Generation Process (LDGP); the General Unrestricted Model (GUM); the reduction process from the GUM to a final congruent model; the question of having more variables than observations; the problem of the contamination of the data by outliers, location shifts, truncated trends, changes in estimated parameters and possible changes with specific shape; and the statistical problems in selecting economic variables. A selection of the many applications of HM is discussed in this paper. This methodology has been incorporated into Climate Econometrics and the paper illustrates the connection between problems in Climate Science and Economics. Moreover, a big component of HM is forecasting and the pivotal findings incorporated into robustifying forecasting methods developed by Hendry and associates are outlined and discussed in this paper.